id float64 706 1.8k | title stringlengths 1 343 | abstract stringlengths 6 6.09k | categories stringlengths 5 125 | processed_abstract stringlengths 2 5.96k | tokenized_abstract stringlengths 8 8.74k | centroid stringlengths 2.1k 2.17k |
|---|---|---|---|---|---|---|
1,802.0366 | Tuning emission energy and fine structure splitting in quantum dots
emitting in the telecom O-band | We report on optical investigations of MOVPE-grown InGaAs/GaAs quantum dots
emitting at the telecom O-band that were integrated onto uniaxial piezoelectric
actuators. This promising technique, which does not degrade the optical quality
or performances of the quantum emitters, enables us to tune the quantum dot
emission wavelengths and their fine-structure splitting. By spectrally
analyzing the emitted light with respect to its polarization, we are able to
demonstrate the cancelation of the fine structure splitting within the
experimental resolution limit. This work represents an important step towards
the high-yield generation of entangled photon pairs at telecommunication
wavelength, together with the capability to precisely tune the emission to
target wavelengths.
| cond-mat.mes-hall quant-ph | we report on optical investigations of movpegrown ingaasgaas quantum dots emitting at the telecom oband that were integrated onto uniaxial piezoelectric actuators this promising technique which does not degrade the optical quality or performances of the quantum emitters enables us to tune the quantum dot emission wavelengths and their finestructure splitting by spectrally analyzing the emitted light with respect to its polarization we are able to demonstrate the cancelation of the fine structure splitting within the experimental resolution limit this work represents an important step towards the highyield generation of entangled photon pairs at telecommunication wavelength together with the capability to precisely tune the emission to target wavelengths | [['we', 'report', 'on', 'optical', 'investigations', 'of', 'movpegrown', 'ingaasgaas', 'quantum', 'dots', 'emitting', 'at', 'the', 'telecom', 'oband', 'that', 'were', 'integrated', 'onto', 'uniaxial', 'piezoelectric', 'actuators', 'this', 'promising', 'technique', 'which', 'does', 'not', 'degrade', 'the', 'optical', 'quality', 'or', 'performances', 'of', 'the', 'quantum', 'emitters', 'enables', 'us', 'to', 'tune', 'the', 'quantum', 'dot', 'emission', 'wavelengths', 'and', 'their', 'finestructure', 'splitting', 'by', 'spectrally', 'analyzing', 'the', 'emitted', 'light', 'with', 'respect', 'to', 'its', 'polarization', 'we', 'are', 'able', 'to', 'demonstrate', 'the', 'cancelation', 'of', 'the', 'fine', 'structure', 'splitting', 'within', 'the', 'experimental', 'resolution', 'limit', 'this', 'work', 'represents', 'an', 'important', 'step', 'towards', 'the', 'highyield', 'generation', 'of', 'entangled', 'photon', 'pairs', 'at', 'telecommunication', 'wavelength', 'together', 'with', 'the', 'capability', 'to', 'precisely', 'tune', 'the', 'emission', 'to', 'target', 'wavelengths']] | [-0.09349018940266883, 0.14866902879953373, -0.034226319578554584, -0.02683445050736898, -0.053313538675831856, -0.17719447979633915, 0.04685770768767971, 0.530958881131678, -0.2430242136703961, -0.3003089576246974, 0.014292785584508815, -0.29709379692675075, -0.020149862537352004, 0.2292920194335595, -0.001154174407453534, 0.07879184194237743, 0.04012637986109601, -0.09071721595703303, 0.010067753204379543, -0.15788777780536317, 0.26535205434241865, 0.12366914657645241, 0.3474300079870203, 0.07726908449048751, 0.10604035957916597, 0.008972779373316286, 0.023435204907833972, -0.06908937075793325, -0.09065163748973391, 0.18053311365469557, 0.26727893675250985, 0.0046737622165025396, 0.22016551614321211, -0.386596182726811, -0.17287176820475644, 0.05850435421741176, 0.1535633386234605, 0.13097077630629989, -0.025991277977014744, -0.2981157821959981, 0.05238117611853876, -0.07737436653854692, -0.1445278294501983, -0.02844545555901583, -0.04663191212637124, -0.003915617843027984, -0.21689666030660845, -0.021558428718490858, -0.005289012089667615, -0.0034293292229559936, 0.0037612445537157564, -0.02951811662674925, -0.02223547696022787, 0.14214084345507913, -0.046892243250334094, 0.00636919949826062, 0.20658973846791276, -0.10027298194826276, -0.1458862058679077, 0.38157497581407845, -0.07955747906327526, -0.08467504094903157, 0.15443847081667492, -0.18415794368924696, -0.08532398490226506, 0.17923040869080017, 0.15600275087701243, 0.10593626330493489, -0.10183030885489762, 0.01284435105011755, 0.06549459778938756, 0.2503163440666536, 0.10325270417477135, 0.19154355959166017, 0.26589061001263486, 0.14553986093743104, 0.02711386123463233, 0.1739831098886294, -0.15790822008998942, -0.05218085369626147, -0.25496369551553905, -0.16812042385409368, -0.18342211538932296, 0.13467575496763848, -0.04989659326207045, -0.12974820102382206, 0.422147058072352, 0.1681695789203187, 0.1597068788936344, 0.0005256095215695623, 0.3369006300083945, 0.10015518487230918, 0.11896449668881283, -0.007769295712932944, 0.3455648756821022, 0.14439855193475556, 0.1193614300867003, -0.2906873616951335, 0.006302390974363156, -0.04975309697301867] |
1,802.03661 | Irrationality of motivic zeta functions | Let $K_0(\mathrm{Var}_{\mathbb{Q}})[1/\mathbb{L}]$ denote the Grothendieck
ring of $\mathbb{Q}$-varieties with the Lefschetz class inverted. We show that
there exists a K3 surface X over $\mathbb{Q}$ such that the motivic zeta
function $\zeta_X(t) := \sum_n [\mathrm{Sym}^n X]t^n$ regarded as an element in
$K_0(\mathrm{Var}_{\mathbb{Q}})[1/\mathbb{L}][[t]]$ is not a rational function
in $t$, thus disproving a conjecture of Denef and Loeser.
| math.AG | let k_0mathrmvar_mathbbq1mathbbl denote the grothendieck ring of mathbbqvarieties with the lefschetz class inverted we show that there exists a k3 surface x over mathbbq such that the motivic zeta function zeta_xt sum_n mathrmsymn xtn regarded as an element in k_0mathrmvar_mathbbq1mathbblt is not a rational function in t thus disproving a conjecture of denef and loeser | [['let', 'k_0mathrmvar_mathbbq1mathbbl', 'denote', 'the', 'grothendieck', 'ring', 'of', 'mathbbqvarieties', 'with', 'the', 'lefschetz', 'class', 'inverted', 'we', 'show', 'that', 'there', 'exists', 'a', 'k3', 'surface', 'x', 'over', 'mathbbq', 'such', 'that', 'the', 'motivic', 'zeta', 'function', 'zeta_xt', 'sum_n', 'mathrmsymn', 'xtn', 'regarded', 'as', 'an', 'element', 'in', 'k_0mathrmvar_mathbbq1mathbblt', 'is', 'not', 'a', 'rational', 'function', 'in', 't', 'thus', 'disproving', 'a', 'conjecture', 'of', 'denef', 'and', 'loeser']] | [-0.26355560090392827, 0.053270819199096875, -0.1600216108188033, 0.05123090399662033, -0.0399057480879128, -0.1885576666984707, 0.0068562901765108104, 0.2980721397674643, -0.3681969937682152, -0.16071920638903975, 0.0024462235160171986, -0.22729098047595472, -0.15351987548172474, 0.24638501739129423, -0.16270970570854842, -0.049454382229596375, -0.04953167341649532, 0.06705806827638298, -0.0836880019120872, -0.30899774614721537, 0.3501071678334847, -0.08128505643457175, 0.1407959647476673, 0.13057285659015178, 0.11152152724564075, 0.028299768893048166, 0.0768093726132065, -0.03841190246865153, -0.14175065408606316, 0.03978105952963233, 0.35746574484743177, 0.08927686210721732, 0.26230334816500545, -0.3361577270179987, -0.1608993148850277, 0.2697126227989793, 0.1798518936848268, -0.1374108382128179, -0.025332817733287813, -0.2042206910531968, 0.16813355403020977, -0.1906179568124935, -0.18981386631727218, -0.0708391303755343, 0.12936813935637473, 0.051462621875107285, -0.2966153988707811, -0.03388824630528688, 0.06963433131575585, 0.1590564381889999, -0.042343346839770674, -0.1444218350946903, -0.1022899780422449, 0.018738947650417684, 0.012454887353815138, 0.17388356355018914, 0.030792793510481715, -0.09025861471891403, -0.11252411156892776, 0.33038474086672065, -0.1341018568724394, -0.17964338146150113, 0.025255416743457316, -0.1969529197178781, -0.15008860329166054, 0.1272739641740918, -0.04374200329184532, 0.23763812925666572, 0.09211056953296065, 0.25043613782036117, -0.22300428555347027, 0.13500219826120882, 0.14002248199656606, -0.05310464611276984, 0.18738125463947652, 0.04790164299309254, 0.06153868011257146, 0.10542825274867937, 0.014286877484992147, 0.03376775135751814, -0.36965935587883, -0.24986579868476838, -0.18042500005103648, 0.26559994156035827, -0.09286163569398923, -0.2528469605091959, 0.355983160994947, 0.036004872103221716, 0.1859533017873764, 0.17820852095261216, 0.16885364367393776, 0.07656144674634562, 0.06628837187541649, 0.03626414825208485, 0.035209568440914156, 0.20905348266474902, -0.042785061311442406, -0.12010297691915184, 0.02088109001982957, 0.26030487891286613] |
1,802.03662 | Sparse Random Matrices have Simple Spectrum | Let $M_n$ be a class of symmetric sparse random matrices, with independent
entries $M_{ij} = \delta_{ij} \xi_{ij}$ for $i \leq j$. $\delta_{ij}$ are
i.i.d. Bernoulli random variables taking the value $1$ with probability $p \geq
n^{-1+\delta}$ for any constant $\delta > 0$ and $\xi_{ij}$ are i.i.d.
centered, subgaussian random variables. We show that with high probability this
class of random matrices has simple spectrum (i.e. the eigenvalues appear with
multiplicity one). We can slightly modify our proof to show that the adjacency
matrix of a sparse Erd\H{o}s-R\'enyi graph has simple spectrum for
$n^{-1+\delta } \leq p \leq 1- n^{-1+\delta}$. These results are optimal in the
exponent. The result for graphs has connections to the notorious graph
isomorphism problem.
| math.PR math.CO | let m_n be a class of symmetric sparse random matrices with independent entries m_ij delta_ij xi_ij for i leq j delta_ij are iid bernoulli random variables taking the value 1 with probability p geq n1delta for any constant delta 0 and xi_ij are iid centered subgaussian random variables we show that with high probability this class of random matrices has simple spectrum ie the eigenvalues appear with multiplicity one we can slightly modify our proof to show that the adjacency matrix of a sparse erdhosrenyi graph has simple spectrum for n1delta leq p leq 1 n1delta these results are optimal in the exponent the result for graphs has connections to the notorious graph isomorphism problem | [['let', 'm_n', 'be', 'a', 'class', 'of', 'symmetric', 'sparse', 'random', 'matrices', 'with', 'independent', 'entries', 'm_ij', 'delta_ij', 'xi_ij', 'for', 'i', 'leq', 'j', 'delta_ij', 'are', 'iid', 'bernoulli', 'random', 'variables', 'taking', 'the', 'value', '1', 'with', 'probability', 'p', 'geq', 'n1delta', 'for', 'any', 'constant', 'delta', '0', 'and', 'xi_ij', 'are', 'iid', 'centered', 'subgaussian', 'random', 'variables', 'we', 'show', 'that', 'with', 'high', 'probability', 'this', 'class', 'of', 'random', 'matrices', 'has', 'simple', 'spectrum', 'ie', 'the', 'eigenvalues', 'appear', 'with', 'multiplicity', 'one', 'we', 'can', 'slightly', 'modify', 'our', 'proof', 'to', 'show', 'that', 'the', 'adjacency', 'matrix', 'of', 'a', 'sparse', 'erdhosrenyi', 'graph', 'has', 'simple', 'spectrum', 'for', 'n1delta', 'leq', 'p', 'leq', '1', 'n1delta', 'these', 'results', 'are', 'optimal', 'in', 'the', 'exponent', 'the', 'result', 'for', 'graphs', 'has', 'connections', 'to', 'the', 'notorious', 'graph', 'isomorphism', 'problem']] | [-0.14802579443861286, 0.20385798448696732, -0.012923719223750674, -0.008113169618477316, -0.054224945777399544, -0.2459034572476926, 0.03570042711318187, 0.40451484257760256, -0.28903705169973165, -0.23304027444480555, 0.0883017598843688, -0.3358352007749288, -0.12547688460098985, 0.08926710161258992, -0.08751755023030969, 0.04563875581421282, 0.05044438461975559, 0.10351002566192462, -0.05174837455396419, -0.26666391177113047, 0.2951436208561063, -0.05701356225687525, 0.15441393519108912, -0.03455572715845293, 0.059546755450656234, 0.05569376450679872, 0.010292757144602744, -0.017424253465445794, -0.14781703731391843, 0.033183671842815114, 0.2622695038783485, 0.12895553016714983, 0.2759111591371829, -0.30097914047377267, -0.14767143416177966, 0.27872328643241656, 0.15027652459381066, -0.009059455116157947, 0.0001143994781634082, -0.2561346065172035, 0.2177128270065979, -0.12171285708343772, -0.12519828010623787, -0.01994642061991212, 0.09297725804474043, 0.05771814915958954, -0.4360799763878079, 0.08006766965288831, 0.11835275937843581, 0.006298084921486999, 0.055860688691229926, -0.3141541761832069, 0.049341716651764254, 0.08224613132846097, -0.007781112671870253, 0.03627624543302733, 0.04469513728323838, -0.030537441994427986, -0.11029950492893872, 0.3065871472753908, -0.028873909912679508, -0.2130761699832004, 0.05551895222262196, -0.20868875659678293, -0.22362475945897725, 0.11485356004584743, 0.13015355228081993, 0.11026765075714692, -0.05413351974490544, 0.1986179470524961, -0.1282696329219186, 0.1441768660766842, 0.07437756957648241, -0.0031800299558950506, 0.07744521880775447, 0.03680676902522859, 0.11089894464644401, 0.08840931849250488, -0.029156512933094864, -0.0340420495354287, -0.28926531813390877, -0.08447674772013788, -0.3081641879621083, 0.17233677425462265, -0.2834065617870732, -0.15592105757931005, 0.34649787558161693, 0.08558793482168213, 0.24069981021077735, 0.2047990533725723, 0.15588332072062336, 0.13972974816924366, -0.04667137693816229, 0.1582418321267418, 0.059363271522781126, 0.23021448060222294, 0.042310219112297764, -0.08083911366841716, 0.07495228569985003, 0.10768249856874995] |
1,802.03663 | On the microscopic bidomain problem with FitzHugh-Nagumo ionic transport | The microscopic bidomain problem with FitzHhugh-Nagumo ionic transport is
studied in the $L_p\!-\!L_q$-framework. Reformulating the problem as a
semilinear evolution equation on the interface, local well-posedness is proved
in strong as well as in weak settings. We obtain solvability for initial data
in the critical spaces of the problem. For dimension $d\leq 3$, by means of
energy estimates and a recent result of Serrin type, global existence is shown.
Finally, stability of spatially constant equilibria is investigated, to the
result that the stability properties of such equilibria parallel those of the
classical FitzHugh-Nagumo system in ODE's. These properties of the bidomain
equations are obtained combining recent results on Dirichlet-to-Neumann
operators, on critical spaces for parabolic evolution equations, and
qualitative theory of evolution equations.
| math.AP | the microscopic bidomain problem with fitzhhughnagumo ionic transport is studied in the l_pl_qframework reformulating the problem as a semilinear evolution equation on the interface local wellposedness is proved in strong as well as in weak settings we obtain solvability for initial data in the critical spaces of the problem for dimension dleq 3 by means of energy estimates and a recent result of serrin type global existence is shown finally stability of spatially constant equilibria is investigated to the result that the stability properties of such equilibria parallel those of the classical fitzhughnagumo system in odes these properties of the bidomain equations are obtained combining recent results on dirichlettoneumann operators on critical spaces for parabolic evolution equations and qualitative theory of evolution equations | [['the', 'microscopic', 'bidomain', 'problem', 'with', 'fitzhhughnagumo', 'ionic', 'transport', 'is', 'studied', 'in', 'the', 'l_pl_qframework', 'reformulating', 'the', 'problem', 'as', 'a', 'semilinear', 'evolution', 'equation', 'on', 'the', 'interface', 'local', 'wellposedness', 'is', 'proved', 'in', 'strong', 'as', 'well', 'as', 'in', 'weak', 'settings', 'we', 'obtain', 'solvability', 'for', 'initial', 'data', 'in', 'the', 'critical', 'spaces', 'of', 'the', 'problem', 'for', 'dimension', 'dleq', '3', 'by', 'means', 'of', 'energy', 'estimates', 'and', 'a', 'recent', 'result', 'of', 'serrin', 'type', 'global', 'existence', 'is', 'shown', 'finally', 'stability', 'of', 'spatially', 'constant', 'equilibria', 'is', 'investigated', 'to', 'the', 'result', 'that', 'the', 'stability', 'properties', 'of', 'such', 'equilibria', 'parallel', 'those', 'of', 'the', 'classical', 'fitzhughnagumo', 'system', 'in', 'odes', 'these', 'properties', 'of', 'the', 'bidomain', 'equations', 'are', 'obtained', 'combining', 'recent', 'results', 'on', 'dirichlettoneumann', 'operators', 'on', 'critical', 'spaces', 'for', 'parabolic', 'evolution', 'equations', 'and', 'qualitative', 'theory', 'of', 'evolution', 'equations']] | [-0.15695330342263453, 0.03811764237586378, -0.043800465554799425, 0.07533719162033363, -0.034053808191698814, -0.09576426367929652, -0.040524294485399605, 0.2757789641310853, -0.314938541147704, -0.27179867572589844, 0.15768550992904862, -0.2801796035794926, -0.15194258777316938, 0.20454826977965998, -0.03429870606661767, 0.12863736900246955, 0.05991997649077295, 0.004619080240430295, -0.0780354719974624, -0.2468787998149618, 0.3956807458057445, -0.018065522463361093, 0.25084743314722846, 0.04442910606056944, 0.09885376016898004, -0.0009735750134510935, 0.014188904626956902, 0.056835426348607894, -0.19099927415393247, 0.07805881812333414, 0.24131539305441144, 0.06535049653150264, 0.2776757834771694, -0.42817059470232854, -0.2680762721887551, 0.05603495668158058, 0.12941760283102058, 0.11376712870714832, -0.05132823550692675, -0.29728505041542624, 0.08636932263982074, -0.07600448447980049, -0.21704945791404973, -0.07009525579392664, 0.02933665771376003, 0.10478692579521867, -0.29046615627247935, 0.1485417025925761, 0.07810123361096802, 0.07648006282854548, -0.2085128376829969, -0.07891973677718596, -0.04647800452383774, 0.0889166338313448, 0.03306800405848925, -0.026804969422827084, 0.05066756886037544, -0.14650695470800576, -0.114428307487791, 0.3537521239154595, -0.08735556830507742, -0.25690345955850974, 0.18839423306871297, -0.10957689886173803, -0.12158171873354962, 0.0712414829460673, 0.13832340060256051, 0.16300446298435206, -0.1456932242621075, 0.1390480583693355, -0.07086282972754403, 0.12844330424920095, 0.054533340467894376, 0.023206651306995923, 0.08084000449258187, 0.18869461062987727, 0.12941103891954442, 0.11846745994196019, 0.03824677543227815, -0.1495722871117894, -0.30241288127731686, -0.1215802128080371, -0.13664460005161683, 0.10011355548881548, -0.11204211622325526, -0.1728945283961486, 0.35639125808750177, 0.10862878857186249, 0.14938965330885584, 0.047457308650848046, 0.2246428464408502, 0.16059534603148728, -0.04192950172457567, 0.059952703965317905, 0.262601869927396, 0.20216539133655692, 0.1747532763098913, -0.2347648882514928, 0.06607151627425135, 0.19286492506180666] |
1,802.03664 | The role of breccia lenses in regolith generation from the formation of
small, simple craters: Application to the Apollo 15 landing site | Impact cratering is likely a primary agent of regolith generation on airless
bodies. Regolith production via impact cratering has long been a key topic of
study since the Apollo era. The evolution of regolith due to impact cratering,
however, is not well understood. A better formulation is needed to help
quantify the formation mechanism and timescale of regolith evolution. Here, we
propose an analytically derived stochastic model that describes the evolution
of regolith generated by small, simple craters. We account for ejecta
blanketing as well as regolith infilling of the transient crater cavity. Our
results show that the regolith infilling plays a key role in producing
regolith. Our model demonstrates that, because of the stochastic nature of
impact cratering, the regolith thickness varies laterally, which is consistent
with earlier work. We apply this analytical model to the regolith evolution at
the Apollo 15 site. The regolith thickness is computed considering the observed
crater size-frequency distribution of small, simple lunar craters (< 381 m in
radius for ejecta blanketing and < 100 m in radius for the regolith infilling).
Allowing for some amount of regolith coming from the outside of the area, our
result is consistent with an empirical result from the Apollo 15 seismic
experiment. Finally, we find that the timescale of regolith growth is longer
than that of crater equilibrium, implying that even if crater equilibrium is
observed on a cratered surface, it is likely the regolith thickness is still
evolving due to additional impact craters.
| astro-ph.EP | impact cratering is likely a primary agent of regolith generation on airless bodies regolith production via impact cratering has long been a key topic of study since the apollo era the evolution of regolith due to impact cratering however is not well understood a better formulation is needed to help quantify the formation mechanism and timescale of regolith evolution here we propose an analytically derived stochastic model that describes the evolution of regolith generated by small simple craters we account for ejecta blanketing as well as regolith infilling of the transient crater cavity our results show that the regolith infilling plays a key role in producing regolith our model demonstrates that because of the stochastic nature of impact cratering the regolith thickness varies laterally which is consistent with earlier work we apply this analytical model to the regolith evolution at the apollo 15 site the regolith thickness is computed considering the observed crater sizefrequency distribution of small simple lunar craters 381 m in radius for ejecta blanketing and 100 m in radius for the regolith infilling allowing for some amount of regolith coming from the outside of the area our result is consistent with an empirical result from the apollo 15 seismic experiment finally we find that the timescale of regolith growth is longer than that of crater equilibrium implying that even if crater equilibrium is observed on a cratered surface it is likely the regolith thickness is still evolving due to additional impact craters | [['impact', 'cratering', 'is', 'likely', 'a', 'primary', 'agent', 'of', 'regolith', 'generation', 'on', 'airless', 'bodies', 'regolith', 'production', 'via', 'impact', 'cratering', 'has', 'long', 'been', 'a', 'key', 'topic', 'of', 'study', 'since', 'the', 'apollo', 'era', 'the', 'evolution', 'of', 'regolith', 'due', 'to', 'impact', 'cratering', 'however', 'is', 'not', 'well', 'understood', 'a', 'better', 'formulation', 'is', 'needed', 'to', 'help', 'quantify', 'the', 'formation', 'mechanism', 'and', 'timescale', 'of', 'regolith', 'evolution', 'here', 'we', 'propose', 'an', 'analytically', 'derived', 'stochastic', 'model', 'that', 'describes', 'the', 'evolution', 'of', 'regolith', 'generated', 'by', 'small', 'simple', 'craters', 'we', 'account', 'for', 'ejecta', 'blanketing', 'as', 'well', 'as', 'regolith', 'infilling', 'of', 'the', 'transient', 'crater', 'cavity', 'our', 'results', 'show', 'that', 'the', 'regolith', 'infilling', 'plays', 'a', 'key', 'role', 'in', 'producing', 'regolith', 'our', 'model', 'demonstrates', 'that', 'because', 'of', 'the', 'stochastic', 'nature', 'of', 'impact', 'cratering', 'the', 'regolith', 'thickness', 'varies', 'laterally', 'which', 'is', 'consistent', 'with', 'earlier', 'work', 'we', 'apply', 'this', 'analytical', 'model', 'to', 'the', 'regolith', 'evolution', 'at', 'the', 'apollo', '15', 'site', 'the', 'regolith', 'thickness', 'is', 'computed', 'considering', 'the', 'observed', 'crater', 'sizefrequency', 'distribution', 'of', 'small', 'simple', 'lunar', 'craters', '381', 'm', 'in', 'radius', 'for', 'ejecta', 'blanketing', 'and', '100', 'm', 'in', 'radius', 'for', 'the', 'regolith', 'infilling', 'allowing', 'for', 'some', 'amount', 'of', 'regolith', 'coming', 'from', 'the', 'outside', 'of', 'the', 'area', 'our', 'result', 'is', 'consistent', 'with', 'an', 'empirical', 'result', 'from', 'the', 'apollo', '15', 'seismic', 'experiment', 'finally', 'we', 'find', 'that', 'the', 'timescale', 'of', 'regolith', 'growth', 'is', 'longer', 'than', 'that', 'of', 'crater', 'equilibrium', 'implying', 'that', 'even', 'if', 'crater', 'equilibrium', 'is', 'observed', 'on', 'a', 'cratered', 'surface', 'it', 'is', 'likely', 'the', 'regolith', 'thickness', 'is', 'still', 'evolving', 'due', 'to', 'additional', 'impact', 'craters']] | [-0.03422838983848235, 0.20997914693102107, -0.13878282487240373, 0.08119662639599445, -0.07809465309909108, -0.023157228179732148, 0.020337533785923557, 0.3366045085960353, -0.24610356479997234, -0.35684040396246225, 0.08670485689143213, -0.24876674318410533, -0.1593702795630207, 0.22139261561916304, -0.12921764670339014, -0.00044920589508754867, 0.13357266364714168, -0.0642182043677538, 0.041838898905552924, -0.23835430209078276, 0.276986896706631, 0.1483430706116618, 0.1844038763387623, 0.12950712269010517, 0.09147755401399063, -0.07287542225759742, -0.019763227874099523, -0.010891851018734125, -0.2059359632631436, 0.0839931542559869, 0.14345857519466354, 0.08076964725968333, 0.24675670922068613, -0.4566814196961267, -0.2624261345571781, 0.06040375198959848, 0.10286526942307282, 0.04809556806184428, -0.06193768864744628, -0.22064153371112688, 0.05959612899935063, -0.22005244920229805, -0.18910989548288742, 0.05975975884238676, 0.10250564603211017, 0.0013077010574028352, -0.23813394183371386, 0.07985353568160185, 0.0869861451842423, 0.09514110390267962, -0.13996266963777645, -0.13057046542799441, -0.08465300981164435, 0.10870155304746361, 0.10577205265686569, -0.00950687685791327, 0.24307210335807342, -0.05505990947748782, 0.02605340415801929, 0.41805172014449327, -0.065148005216936, -0.07092102545560623, 0.21009494205461626, -0.21626623956182478, -0.04844303859245716, 0.18763623175838468, 0.19510705175011286, 0.07947164119354316, -0.13803768524263357, 0.012046775339903044, -0.06709384106916888, 0.21455139102846651, 0.07386631591967782, 0.006063882269117297, 0.2875187689096344, 0.2670627718221168, 0.04712172266361969, 0.08850982064590314, -0.18261635175963142, -0.05934335651940533, -0.24056288338437373, -0.12107644401566715, -0.1979156005405346, 0.07962828493987124, -0.107786512634199, -0.1682656477853461, 0.3201298733850067, 0.14958591650107078, 0.1703166756931008, 0.04278105106252265, 0.2785938035316613, 0.0010476447456535332, 0.0823235488534734, 0.07980188328240599, 0.293943571393991, 0.08693079092748919, 0.10351195209564604, -0.22163264507579863, 0.24387619375080175, 0.04532290023409438] |
1,802.03665 | On quantum compatibility of counterterm deformations and duality
symmetries in ${\cal N}\geq 5$ supergravities | In ${\cal N}=5, 6, 8$ supergravities there are hidden symmetries of equations
of motion, described by duality groups $SU(1,5), \, SO^*(12), \, E_{7(7)}$
respectively. UV divergences and known candidate counterterms violate the
deformed duality symmetry current conservation. Extra higher derivative terms
in the action are required to restore duality. We study the effect of a
two-vector part of the counterterm for ${\cal N}\geq 5$ supergravities using
the universality of the symplectic structure of extended supergravities. We
construct a compact form of a deformed action with infinite number of higher
derivative terms and restored duality symmetry with deformation parameter
$\lambda$. We find, in $\lambda^2$ approximation, that the $SU({\cal N})$
symmetry of the deformed theory is restored on shell.
| hep-th | in cal n5 6 8 supergravities there are hidden symmetries of equations of motion described by duality groups su15 so12 e_77 respectively uv divergences and known candidate counterterms violate the deformed duality symmetry current conservation extra higher derivative terms in the action are required to restore duality we study the effect of a twovector part of the counterterm for cal ngeq 5 supergravities using the universality of the symplectic structure of extended supergravities we construct a compact form of a deformed action with infinite number of higher derivative terms and restored duality symmetry with deformation parameter lambda we find in lambda2 approximation that the sucal n symmetry of the deformed theory is restored on shell | [['in', 'cal', 'n5', '6', '8', 'supergravities', 'there', 'are', 'hidden', 'symmetries', 'of', 'equations', 'of', 'motion', 'described', 'by', 'duality', 'groups', 'su15', 'so12', 'e_77', 'respectively', 'uv', 'divergences', 'and', 'known', 'candidate', 'counterterms', 'violate', 'the', 'deformed', 'duality', 'symmetry', 'current', 'conservation', 'extra', 'higher', 'derivative', 'terms', 'in', 'the', 'action', 'are', 'required', 'to', 'restore', 'duality', 'we', 'study', 'the', 'effect', 'of', 'a', 'twovector', 'part', 'of', 'the', 'counterterm', 'for', 'cal', 'ngeq', '5', 'supergravities', 'using', 'the', 'universality', 'of', 'the', 'symplectic', 'structure', 'of', 'extended', 'supergravities', 'we', 'construct', 'a', 'compact', 'form', 'of', 'a', 'deformed', 'action', 'with', 'infinite', 'number', 'of', 'higher', 'derivative', 'terms', 'and', 'restored', 'duality', 'symmetry', 'with', 'deformation', 'parameter', 'lambda', 'we', 'find', 'in', 'lambda2', 'approximation', 'that', 'the', 'sucal', 'n', 'symmetry', 'of', 'the', 'deformed', 'theory', 'is', 'restored', 'on', 'shell']] | [-0.1798587534372417, 0.16898672691987535, -0.034343074801941646, 0.10446742418520316, -0.09627937141544464, -0.15358900036581122, -0.02511634910785544, 0.3196941489157708, -0.18156172866165116, -0.3035977721773905, 0.08874242236478287, -0.2831792089957417, -0.14977227451010167, 0.011011161294095871, -0.07258324383088109, 0.0014782793352200666, -0.06518041211989169, 0.06507187104261104, -0.1708526207387382, -0.24523901883635277, 0.3027764271511778, -0.029273614502846868, 0.25058716591937763, 0.009094226000454734, 0.1133741079380311, -0.015989516857652028, 0.01973830026231314, -0.009989756049196186, -0.09307268896711257, 0.12538456658704059, 0.20868006828363592, 0.05301780392428076, 0.0973465759082485, -0.43902789587318375, -0.18155961287649056, 0.08891893382972564, 0.1648614865302909, 0.07471632502213317, -0.016815000949958504, -0.2879769294359313, 0.07197931185037944, -0.2133465461073476, -0.25016153600524393, -0.1118456180505618, 0.03813949745279132, -0.12030292114675895, -0.25670054363211403, 0.11410158529485527, 0.057649011960612576, 0.0804575656197573, -0.06715306584578286, -0.056297112512606474, -0.11269140825198408, 0.03003717383794617, 0.09472983031893116, 0.037024984195452644, 0.0904213891909948, -0.16823526156102225, -0.11134710485573139, 0.3797601383963698, -0.04442961793354602, -0.24249644188635183, 0.08767266804352403, -0.16796654284310839, -0.21124536248348785, 0.12662310233316562, 0.062139189536601566, 0.17169786096354456, -0.0756759620276729, 0.23017014060563892, -0.020272331607421826, 0.11663020211026857, 0.13167120161744064, 0.0563290984034865, 0.1443816884420812, 0.07821337420599568, 0.05027929021110922, 0.14850492848965682, 0.014345116988886474, -0.09720353516668342, -0.47371930151916386, -0.10932266271342278, -0.10934612878778002, 0.11569790467017396, -0.15761996767245715, -0.09981868029041052, 0.32221985718423274, 0.06024708999974424, 0.14645450544061564, 0.07429184195618227, 0.14280031476447588, 0.1338445014757382, 0.160980557369297, 0.04498466900386439, 0.23862736486715444, 0.18687070111474513, -0.014029993802276357, -0.264974750035132, -0.15596542739832217, 0.20418502479432182] |
1,802.03666 | Bound electron nonlinearity beyond the ionization threshold | Although high field laser-induced ionization is a fundamental process
underlying many applications, there have been no absolute measurements of the
nonlinear polarizability of atoms and molecules in the presence of ionization.
Such information is crucial, for example, for understanding the propagation of
high intensity ultrashort pulses in matter. Here, we present absolute space-
and time-resolved measurements of the ultrafast laser-driven nonlinear
polarizability in argon, krypton, xenon, nitrogen, and oxygen up to an
ionization fraction of a few percent. These measurements enable determination
of the non-perturbative bound electron nonlinearity well beyond the ionization
threshold, where it is found to be approximately linear in intensity.
| physics.optics | although high field laserinduced ionization is a fundamental process underlying many applications there have been no absolute measurements of the nonlinear polarizability of atoms and molecules in the presence of ionization such information is crucial for example for understanding the propagation of high intensity ultrashort pulses in matter here we present absolute space and timeresolved measurements of the ultrafast laserdriven nonlinear polarizability in argon krypton xenon nitrogen and oxygen up to an ionization fraction of a few percent these measurements enable determination of the nonperturbative bound electron nonlinearity well beyond the ionization threshold where it is found to be approximately linear in intensity | [['although', 'high', 'field', 'laserinduced', 'ionization', 'is', 'a', 'fundamental', 'process', 'underlying', 'many', 'applications', 'there', 'have', 'been', 'no', 'absolute', 'measurements', 'of', 'the', 'nonlinear', 'polarizability', 'of', 'atoms', 'and', 'molecules', 'in', 'the', 'presence', 'of', 'ionization', 'such', 'information', 'is', 'crucial', 'for', 'example', 'for', 'understanding', 'the', 'propagation', 'of', 'high', 'intensity', 'ultrashort', 'pulses', 'in', 'matter', 'here', 'we', 'present', 'absolute', 'space', 'and', 'timeresolved', 'measurements', 'of', 'the', 'ultrafast', 'laserdriven', 'nonlinear', 'polarizability', 'in', 'argon', 'krypton', 'xenon', 'nitrogen', 'and', 'oxygen', 'up', 'to', 'an', 'ionization', 'fraction', 'of', 'a', 'few', 'percent', 'these', 'measurements', 'enable', 'determination', 'of', 'the', 'nonperturbative', 'bound', 'electron', 'nonlinearity', 'well', 'beyond', 'the', 'ionization', 'threshold', 'where', 'it', 'is', 'found', 'to', 'be', 'approximately', 'linear', 'in', 'intensity']] | [-0.04345687265220794, 0.18538226122706247, -0.01978766601713537, 0.030045586208182356, 0.03181555670532353, -0.10731360193305803, 0.037452076767453726, 0.44176852381200465, -0.23894051147751438, -0.35056065239952605, 0.02036208619625823, -0.3096143506621056, -0.052374886493515044, 0.21586397030725352, 0.042020491663438894, 0.07859669453961757, 0.0030135729313981764, -0.016172998015163014, -0.0400057169563562, -0.18860892325784395, 0.21938223014721303, 0.09557444155888713, 0.22407626243561363, 0.14707323156966312, 0.12418188796677057, -0.018141972139541024, -0.00442332105295172, -0.05097377240161628, -0.11175422269615878, 0.08522184958084694, 0.2871189591592377, 0.0400424755689263, 0.2645085781758416, -0.4507866677764839, -0.23538145369135785, 0.08755122951584533, 0.14332115312911642, 0.16222992049331225, -0.12597602129308055, -0.23019261907297864, -0.03249067490359823, -0.12068019816380682, -0.14167574393897525, -0.08522530305154115, 0.0466100351525543, 0.06703069770383169, -0.26836433378782903, 0.08269848563319561, 0.017749175073316737, 0.07645338403910977, -0.07201698879729414, -0.07688485371690353, 0.016998633880222453, 0.05041924873095693, -0.005737255827819893, 0.03415293823724197, 0.23237838582542625, -0.1685045592315061, -0.05415979238425933, 0.4071707736194423, -0.12543282515676782, -0.08559807446938984, 0.16210719231443788, -0.24207941280509507, -0.10780974666280582, 0.2464225118057531, 0.16348852089931737, 0.13248988271699946, -0.12407587494393721, 0.029048295061497326, -0.012029146169791522, 0.2361716914885831, 0.11796684311793267, 0.11735678585223601, 0.19105889900469952, 0.2100169367622584, 0.05970732206919511, 0.03613935378312305, -0.1396754491640237, -0.018415564436067657, -0.2774248105898789, -0.1762621788815505, -0.1385301565344545, 0.08116172179376291, -0.05197402420275714, -0.14567142677690056, 0.36990133161629435, 0.1309347066268759, 0.13376337402834765, -0.11889817610889383, 0.33119468022029375, 0.15306595089456554, 0.007366516069029864, -0.01597113202515881, 0.3244911229590551, 0.21437436344047772, 0.06283324631270093, -0.27189735579530444, 0.10195172987697483, -0.025548471953918777] |
1,802.03667 | An Investigation of the Monitoring Activity in Self Adaptive Systems | Runtime monitoring is essential for the violation detection during the
underlying software system execution. In this paper, an investigation of the
monitoring activity of MAPE-K control loop is performed which aims at
exploring:(1) the architecture of the monitoring activity in terms of the
involved components and control and data flow between them; (2) the standard
interface of the monitoring component with other MAPE-K components; (3) the
adaptive monitoring and its importance to the monitoring overhead issue; and
(4) the monitoring mode and its relevance to some specific situations and
systems. This paper also presented a Java framework for the monitoring process
for self adaptive systems.
| cs.SE | runtime monitoring is essential for the violation detection during the underlying software system execution in this paper an investigation of the monitoring activity of mapek control loop is performed which aims at exploring1 the architecture of the monitoring activity in terms of the involved components and control and data flow between them 2 the standard interface of the monitoring component with other mapek components 3 the adaptive monitoring and its importance to the monitoring overhead issue and 4 the monitoring mode and its relevance to some specific situations and systems this paper also presented a java framework for the monitoring process for self adaptive systems | [['runtime', 'monitoring', 'is', 'essential', 'for', 'the', 'violation', 'detection', 'during', 'the', 'underlying', 'software', 'system', 'execution', 'in', 'this', 'paper', 'an', 'investigation', 'of', 'the', 'monitoring', 'activity', 'of', 'mapek', 'control', 'loop', 'is', 'performed', 'which', 'aims', 'at', 'exploring1', 'the', 'architecture', 'of', 'the', 'monitoring', 'activity', 'in', 'terms', 'of', 'the', 'involved', 'components', 'and', 'control', 'and', 'data', 'flow', 'between', 'them', '2', 'the', 'standard', 'interface', 'of', 'the', 'monitoring', 'component', 'with', 'other', 'mapek', 'components', '3', 'the', 'adaptive', 'monitoring', 'and', 'its', 'importance', 'to', 'the', 'monitoring', 'overhead', 'issue', 'and', '4', 'the', 'monitoring', 'mode', 'and', 'its', 'relevance', 'to', 'some', 'specific', 'situations', 'and', 'systems', 'this', 'paper', 'also', 'presented', 'a', 'java', 'framework', 'for', 'the', 'monitoring', 'process', 'for', 'self', 'adaptive', 'systems']] | [-0.16860401927708432, 0.0346420373838415, -0.054040593726453014, -0.00900369811550333, -0.034547186707361385, -0.1469393456936814, 0.062293298670108646, 0.3674779069036819, -0.26428654867385587, -0.3395387139887764, 0.21720133901600583, -0.2395300797965879, -0.12747959826643077, 0.2068919686784144, -0.061653088191703245, 0.08190151028079876, 0.07322052203548643, 0.005199232230482336, -0.0042376386392369075, -0.18981691673308468, 0.28502245666235326, 0.10671598407833909, 0.285091085631463, 0.05794253891620498, 0.09133201196024086, 0.05840789272602146, -0.08265795557347771, -0.034563291110456563, -0.027317204342510264, 0.1486522216929678, 0.28951078228419647, 0.18227431250180906, 0.2876924134235686, -0.39465958041210586, -0.20780578171588088, 0.08375195054283652, 0.11871996606574751, 0.012168820476150498, -0.03963996197294014, -0.26300225037042624, 0.0625880211770821, -0.19125959699830183, -0.14869348967644888, -0.05207016090683352, 0.04848026498411155, -0.020484750374005392, -0.2593888691089188, 0.015202035077191586, 0.05925319017282723, 0.14155408702432537, -0.08496527687664358, -0.02070630880301066, -0.0008908324346591074, 0.2088438729988411, 0.033636518910498125, 0.019357034247010373, 0.18033825838490605, -0.14760604003318945, -0.12364863734155034, 0.3516415152161454, -0.004189730297254685, -0.13896756608468983, 0.2443840273011189, -0.06791478049014515, -0.19000204239721194, 0.09051651960740295, 0.2281271125942182, 0.1073427211600714, -0.21539458877836856, 0.016029813469056256, 0.0912558257740994, 0.19639500091971757, -0.039293398906011134, 0.03252392606988836, 0.16575642007116514, 0.23310209645961338, 0.05630671765189058, 0.13087374409000263, -0.1130930248610429, -0.06324629856345172, -0.3159585690770585, -0.18199900595936924, -0.09115732066829178, -0.0543245565025315, -0.07191946714710166, -0.10183791798324539, 0.450048741293498, 0.16085692742951954, 0.11541175552478168, 0.028078457552160565, 0.364607446316558, 0.07842658868601295, 0.07653285198746464, 0.08976499885410213, 0.21573937452950093, 0.05511734331957996, 0.18241333597912812, -0.29057046583889484, 0.10708642973510835, -0.002383767224203509] |
1,802.03668 | A 100 au-Wide Bipolar Rotating Shell Emanating From The HH
212Protostellar Disk: A Disk Wind? | HH 212 is a Class 0 protostellar system found to host a "hamburger"-shaped
dusty disk with a rotating disk atmosphere and a collimated SiO jet at a
distance of ~ 400 pc. Recently, a compact rotating outflow has been detected in
SO and SO2 toward the center along the jet axis at ~ 52 au (0.13") resolution.
Here we resolve the compact outflow into a small-scale wide-opening rotating
outflow shell and a collimated jet, with the observations in the same S-bearing
molecules at ~ 16 au (0.04") resolution. The collimated jet is aligned with the
SiO jet, tracing the shock interactions in the jet. The wide-opening outflow
shell is seen extending out from the inner disk around the SiO jet and has a
width of ~ 100 au. It is not only expanding away from the center, but also
rotating around the jet axis. The specific angular momentum of the outflow
shell is ~ 40 au km/s. Simple modeling of the observed kinematics suggests that
the rotating outflow shell can trace either a disk wind or disk material pushed
away by an unseen wind from the inner disk or protostar. We also resolve the
disk atmosphere in the same S-bearing molecules, confirming the Keplerian
rotation there.
| astro-ph.GA | hh 212 is a class 0 protostellar system found to host a hamburgershaped dusty disk with a rotating disk atmosphere and a collimated sio jet at a distance of 400 pc recently a compact rotating outflow has been detected in so and so2 toward the center along the jet axis at 52 au 013 resolution here we resolve the compact outflow into a smallscale wideopening rotating outflow shell and a collimated jet with the observations in the same sbearing molecules at 16 au 004 resolution the collimated jet is aligned with the sio jet tracing the shock interactions in the jet the wideopening outflow shell is seen extending out from the inner disk around the sio jet and has a width of 100 au it is not only expanding away from the center but also rotating around the jet axis the specific angular momentum of the outflow shell is 40 au kms simple modeling of the observed kinematics suggests that the rotating outflow shell can trace either a disk wind or disk material pushed away by an unseen wind from the inner disk or protostar we also resolve the disk atmosphere in the same sbearing molecules confirming the keplerian rotation there | [['hh', '212', 'is', 'a', 'class', '0', 'protostellar', 'system', 'found', 'to', 'host', 'a', 'hamburgershaped', 'dusty', 'disk', 'with', 'a', 'rotating', 'disk', 'atmosphere', 'and', 'a', 'collimated', 'sio', 'jet', 'at', 'a', 'distance', 'of', '400', 'pc', 'recently', 'a', 'compact', 'rotating', 'outflow', 'has', 'been', 'detected', 'in', 'so', 'and', 'so2', 'toward', 'the', 'center', 'along', 'the', 'jet', 'axis', 'at', '52', 'au', '013', 'resolution', 'here', 'we', 'resolve', 'the', 'compact', 'outflow', 'into', 'a', 'smallscale', 'wideopening', 'rotating', 'outflow', 'shell', 'and', 'a', 'collimated', 'jet', 'with', 'the', 'observations', 'in', 'the', 'same', 'sbearing', 'molecules', 'at', '16', 'au', '004', 'resolution', 'the', 'collimated', 'jet', 'is', 'aligned', 'with', 'the', 'sio', 'jet', 'tracing', 'the', 'shock', 'interactions', 'in', 'the', 'jet', 'the', 'wideopening', 'outflow', 'shell', 'is', 'seen', 'extending', 'out', 'from', 'the', 'inner', 'disk', 'around', 'the', 'sio', 'jet', 'and', 'has', 'a', 'width', 'of', '100', 'au', 'it', 'is', 'not', 'only', 'expanding', 'away', 'from', 'the', 'center', 'but', 'also', 'rotating', 'around', 'the', 'jet', 'axis', 'the', 'specific', 'angular', 'momentum', 'of', 'the', 'outflow', 'shell', 'is', '40', 'au', 'kms', 'simple', 'modeling', 'of', 'the', 'observed', 'kinematics', 'suggests', 'that', 'the', 'rotating', 'outflow', 'shell', 'can', 'trace', 'either', 'a', 'disk', 'wind', 'or', 'disk', 'material', 'pushed', 'away', 'by', 'an', 'unseen', 'wind', 'from', 'the', 'inner', 'disk', 'or', 'protostar', 'we', 'also', 'resolve', 'the', 'disk', 'atmosphere', 'in', 'the', 'same', 'sbearing', 'molecules', 'confirming', 'the', 'keplerian', 'rotation', 'there']] | [-0.09548049674277305, 0.08524419082537472, -0.03562906754361836, 0.03801687377382218, -0.11399368288004724, -0.09655593993404037, -0.03245153162739615, 0.4757351444024055, -0.22553595201768542, -0.28287189733700374, 0.06680995393984612, -0.24033980085039558, 0.10583256956755151, 0.13801059189810885, 0.016894121466677136, -0.03796633710477742, 0.07957283352543391, -0.10130696040253845, -0.08009786269886984, -0.07065395457178947, 0.28907266038178064, 0.11838452256544127, 0.05247253767128997, 0.02207260530434977, 0.10119071323540414, -0.19323688904541678, 0.011453826698608956, -0.03500066856061345, -0.12974927876630726, 0.05153238605615215, 0.1554357798391286, 0.06637828624158616, 0.20290783317342623, -0.370254685451272, -0.2144420597683731, -0.06996281846514463, 0.23232798516490863, 0.036266943337688276, -0.027134644071483492, -0.26457518339157104, 0.07447434125458868, -0.24271441081455394, -0.24276367875872484, 0.12547768572280507, 0.08291881865085061, -0.02896121229781811, -0.20708112213158267, 0.10560781426874884, 0.09504840924260925, 0.1154707682009703, -0.0756613437552005, -0.08461248381376099, -0.14210875841339504, 0.009821609501258948, 0.08843580875383569, 0.19322603894165943, 0.3093909794135733, -0.09933758422556282, -0.022839223762130857, 0.415603719318091, -0.06868335453038155, -0.08277743842582501, 0.25696057924972987, -0.30150861330984846, -0.13731129863415265, 0.2860488735245939, 0.12677651316096047, 0.14569969864942095, -0.07499960254280091, -0.03392459558373993, -0.11237675298598424, 0.20547685805541366, 0.11837358337210778, -0.004382778387702075, 0.3922451405382868, 0.08782456247877349, 0.019449556686577215, 0.14901321000577095, -0.28898705575448363, -0.07126405081521739, -0.23669864531416465, -0.13057264927728332, -0.12467147582743447, 0.10211941706769884, -0.12862662048471757, -0.06968508173333103, 0.29774246561753365, 0.023500518682276695, 0.24812992239157802, -0.04029487932288547, 0.31318290706095375, 0.007294934305515307, 0.11850259463483495, 0.26994005090033457, 0.34633068972503517, 0.19361212173249776, 0.1665020737477314, -0.22901893496184392, 0.0743430196145429, -0.02571976767732433] |
1,802.03669 | The Power Allocation Game on A Network: A Paradox | The well-known Braess paradox in congestion games states that adding an
additional road to a transportation network may increase the total travel time,
and consequently decrease the overall efficiency. Motivated by this, this paper
presents a paradox in a similar spirit emerging from another distributed
resource allocation game on networks, namely the power allocation game between
countries developed in \cite{allocation}. The paradox is that by having
additional friends may actually decrease a country's total welfare in
equilibrium. Conditions for this paradox to occur as well as some price of
anarchy results are also derived.
| cs.GT cs.SI | the wellknown braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time and consequently decrease the overall efficiency motivated by this this paper presents a paradox in a similar spirit emerging from another distributed resource allocation game on networks namely the power allocation game between countries developed in citeallocation the paradox is that by having additional friends may actually decrease a countrys total welfare in equilibrium conditions for this paradox to occur as well as some price of anarchy results are also derived | [['the', 'wellknown', 'braess', 'paradox', 'in', 'congestion', 'games', 'states', 'that', 'adding', 'an', 'additional', 'road', 'to', 'a', 'transportation', 'network', 'may', 'increase', 'the', 'total', 'travel', 'time', 'and', 'consequently', 'decrease', 'the', 'overall', 'efficiency', 'motivated', 'by', 'this', 'this', 'paper', 'presents', 'a', 'paradox', 'in', 'a', 'similar', 'spirit', 'emerging', 'from', 'another', 'distributed', 'resource', 'allocation', 'game', 'on', 'networks', 'namely', 'the', 'power', 'allocation', 'game', 'between', 'countries', 'developed', 'in', 'citeallocation', 'the', 'paradox', 'is', 'that', 'by', 'having', 'additional', 'friends', 'may', 'actually', 'decrease', 'a', 'countrys', 'total', 'welfare', 'in', 'equilibrium', 'conditions', 'for', 'this', 'paradox', 'to', 'occur', 'as', 'well', 'as', 'some', 'price', 'of', 'anarchy', 'results', 'are', 'also', 'derived']] | [-0.13565062683947543, 0.08028726772286934, -0.0889346609783775, 0.12350275078937015, -0.0691407550735637, -0.1682015440050275, 0.16336279181253283, 0.34953830319833246, -0.2824203827358941, -0.37037670939288875, 0.09261186283448354, -0.2940524387559754, -0.18339299501236925, 0.10767564692712844, -0.22337370262818135, -0.0014409958731700131, 0.07499031298744314, 0.024781612005639584, 0.05691562199895765, -0.2576435260335974, 0.30426287614527414, 0.12647911007615162, 0.31046090252509223, 0.11013599208734454, 0.05655334482048118, -0.02627783245407045, 0.014048830893366261, 0.07776858413745551, -0.097999162829086, 0.11338497028733167, 0.2984587155639174, 0.19249965118224474, 0.38111478189363124, -0.4190508525947386, -0.2525012951834682, 0.13571790899050998, 0.12947481591749857, 0.06844231495237414, -0.03913646269876985, -0.24248779319385264, 0.014082309993063199, -0.24260964469260912, -0.11696425314616174, 0.017745427039273558, 0.01484396103571387, 0.02065858742757205, -0.24887321090840914, 0.08216223016627718, 0.024480299160944574, 0.0433095638677998, -0.052126085024049626, -0.11296260343032315, -0.02842330745609596, 0.14741392922092308, 0.07685300151252762, -0.02455816874181495, 0.10432437217814174, -0.13799978516490616, -0.22127625144066962, 0.3766629612073302, -0.03078089550414935, -0.1566332041699578, 0.13163631447798949, -0.05016036872613303, -0.13187974124175914, 0.06667336723222299, 0.16970995491608343, 0.05377872717229927, -0.1487614207286784, -0.0496983662194404, -0.13079802628527296, 0.1557569641897336, 0.13950085658282835, 0.06123837409541011, 0.15369170416701347, 0.16834666560146402, 0.19905149373424022, 0.15349651907540937, 0.007953212054030217, -0.205166153282799, -0.2477201806874252, -0.13209285064441886, -0.16414439020321725, 0.08662827166312552, -0.08710234499263374, -0.08459994708376124, 0.345637939949619, 0.12066943620757616, 0.12834686174136686, 0.09131577619886462, 0.2978178125191876, 0.11335750213487351, 0.038139078776015245, 0.13267123116120855, 0.19696012429275025, 0.02144189507383457, 0.22917384377735212, -0.2222718958448163, 0.13639723626956185, 0.001614640843360982] |
1,802.0367 | Non-Axisymmetric Line Driven Disc Winds II - Full Velocity Gradient | We study non-axisymetric features of 3D line driven winds in the Sobolev
approximation, where the optical depth is calculated using the full velocity
gradient. We find that non-axisymmetric density features, so called clumps,
form primarily at the base of the wind on super-Sobolev length scales. The
density of clumps differs by a factor of $\sim 3$ from the azimuthal average,
the magnitude of their velocity dispersion is comparable to the flow velocity
and they produce $\sim 20\%$ variations in the column density. Clumps may be
observable because differences in density produce enhancements in emission and
absorption profiles or through their velocity dispersion which enhances line
broadening.
| astro-ph.HE | we study nonaxisymetric features of 3d line driven winds in the sobolev approximation where the optical depth is calculated using the full velocity gradient we find that nonaxisymmetric density features so called clumps form primarily at the base of the wind on supersobolev length scales the density of clumps differs by a factor of sim 3 from the azimuthal average the magnitude of their velocity dispersion is comparable to the flow velocity and they produce sim 20 variations in the column density clumps may be observable because differences in density produce enhancements in emission and absorption profiles or through their velocity dispersion which enhances line broadening | [['we', 'study', 'nonaxisymetric', 'features', 'of', '3d', 'line', 'driven', 'winds', 'in', 'the', 'sobolev', 'approximation', 'where', 'the', 'optical', 'depth', 'is', 'calculated', 'using', 'the', 'full', 'velocity', 'gradient', 'we', 'find', 'that', 'nonaxisymmetric', 'density', 'features', 'so', 'called', 'clumps', 'form', 'primarily', 'at', 'the', 'base', 'of', 'the', 'wind', 'on', 'supersobolev', 'length', 'scales', 'the', 'density', 'of', 'clumps', 'differs', 'by', 'a', 'factor', 'of', 'sim', '3', 'from', 'the', 'azimuthal', 'average', 'the', 'magnitude', 'of', 'their', 'velocity', 'dispersion', 'is', 'comparable', 'to', 'the', 'flow', 'velocity', 'and', 'they', 'produce', 'sim', '20', 'variations', 'in', 'the', 'column', 'density', 'clumps', 'may', 'be', 'observable', 'because', 'differences', 'in', 'density', 'produce', 'enhancements', 'in', 'emission', 'and', 'absorption', 'profiles', 'or', 'through', 'their', 'velocity', 'dispersion', 'which', 'enhances', 'line', 'broadening']] | [-0.1101931678937175, 0.15107582821152532, -0.06873616471644849, 0.05619577915058471, -0.03893191013664294, -0.01203035718600194, -0.02789907446500505, 0.4246091117652563, -0.2554167092491228, -0.31204146103790176, 0.03131042363104196, -0.294330170019888, -0.037434702347337194, 0.16135869581529944, 0.035297834524849, -0.021635313755653512, 0.012458020295106018, -0.03160742940963246, -0.09286596810236986, -0.15908904157829687, 0.32029927387618673, 0.0637226612430263, 0.24671075558468986, 0.04134410560184803, 0.06360895982204685, -0.1167104557568494, -0.0576909058010922, 0.06872726259350131, -0.1378119391137471, 0.09578998506521412, 0.1726535426994535, 0.0668638129808152, 0.22714956363107866, -0.40260111511899876, -0.2534065671587506, 0.04113803327065678, 0.21414139363556528, 0.07111347975688449, -0.006346660031480356, -0.26064634703708667, 0.0527063865133991, -0.14936849707849503, -0.16945827959212834, 0.018166243557621222, 0.06851675029611215, 0.09361610119902672, -0.24185485382062885, 0.17889481116659367, -0.006004900840567783, 0.09636807884089649, -0.06446093895311396, -0.09283000727793059, -0.09843458664657262, 0.03646659703540186, 0.036212314990384936, 0.05039243098536435, 0.23442913862751225, -0.18878780899999234, 0.02270921066183991, 0.4129077394564564, -0.13745807530806184, -0.1087288165715738, 0.15387863381273256, -0.20303561859047756, -0.08009947669387867, 0.22904672951867375, 0.19883510639752225, 0.08224748263063912, -0.030909339252572793, -0.020027083292146787, -0.02279920846922323, 0.23507344572303387, 0.09461485977786091, 0.04974547431069928, 0.25154577008484363, 0.05281184045956112, 0.05437254657646498, 0.06360036061624459, -0.23255707005871676, -0.05771930570839546, -0.24332182320694512, -0.11240058928692284, -0.13275057969328302, 0.033706189782466166, -0.12681190448319496, -0.14062804984748184, 0.3605918611037151, 0.15849860638151697, 0.2677616312419279, 0.045705109079090804, 0.32670021332943666, 0.1834642599345758, 0.1299230705615348, 0.18055816255330753, 0.28293871142579097, 0.15363566364193013, 0.08852319843852176, -0.25098667309570233, 0.10054674325063108, 0.024090578772442174] |
1,802.03671 | Faster Distributed Shortest Path Approximations via Shortcuts | A long series of recent results and breakthroughs have led to faster and
better distributed approximation algorithms for single source shortest paths
(SSSP) and related problems in the CONGEST model. The runtime of all these
algorithms, however, is $\tilde{\Omega}(\sqrt{n})$, regardless of the network
topology, even on nice networks with a (poly)logarithmic network diameter $D$.
While this is known to be necessary for some pathological networks, most
topologies of interest are arguably not of this type.
We give the first distributed approximation algorithms for shortest paths
problems that adjust to the topology they are run on, thus achieving
significantly faster running times on many topologies of interest. The running
time of our algorithms depends on and is close to $Q$, where $Q$ is the quality
of the best shortcut that exists for the given topology. While $Q =
\tilde{\Theta}(\sqrt{n} + D)$ for pathological worst-case topologies, many
topologies of interest have $Q = \tilde{\Theta}(D)$, which results in near
instance optimal running times for our algorithm, given the trivial $\Omega(D)$
lower bound.
The problems we consider are as follows: (1) an approximate shortest path
tree and SSSP distances, (2) a polylogarithmic size distance label for every
node such that from the labels of any two nodes alone one can determine their
distance (approximately), and (3) an (approximately) optimal flow for the
transshipment problem.
Our algorithms have a tunable tradeoff between running time and approximation
ratio. Our fastest algorithms have an arbitrarily good polynomial approximation
guarantee and an essentially optimal $\tilde{O}(Q)$ running time. On the other
end of the spectrum, we achieve polylogarithmic approximations in $\tilde{O}(Q
\cdot n^{\epsilon})$ rounds for any $\epsilon > 0$.
| cs.DS cs.DC | a long series of recent results and breakthroughs have led to faster and better distributed approximation algorithms for single source shortest paths sssp and related problems in the congest model the runtime of all these algorithms however is tildeomegasqrtn regardless of the network topology even on nice networks with a polylogarithmic network diameter d while this is known to be necessary for some pathological networks most topologies of interest are arguably not of this type we give the first distributed approximation algorithms for shortest paths problems that adjust to the topology they are run on thus achieving significantly faster running times on many topologies of interest the running time of our algorithms depends on and is close to q where q is the quality of the best shortcut that exists for the given topology while q tildethetasqrtn d for pathological worstcase topologies many topologies of interest have q tildethetad which results in near instance optimal running times for our algorithm given the trivial omegad lower bound the problems we consider are as follows 1 an approximate shortest path tree and sssp distances 2 a polylogarithmic size distance label for every node such that from the labels of any two nodes alone one can determine their distance approximately and 3 an approximately optimal flow for the transshipment problem our algorithms have a tunable tradeoff between running time and approximation ratio our fastest algorithms have an arbitrarily good polynomial approximation guarantee and an essentially optimal tildeoq running time on the other end of the spectrum we achieve polylogarithmic approximations in tildeoq cdot nepsilon rounds for any epsilon 0 | [['a', 'long', 'series', 'of', 'recent', 'results', 'and', 'breakthroughs', 'have', 'led', 'to', 'faster', 'and', 'better', 'distributed', 'approximation', 'algorithms', 'for', 'single', 'source', 'shortest', 'paths', 'sssp', 'and', 'related', 'problems', 'in', 'the', 'congest', 'model', 'the', 'runtime', 'of', 'all', 'these', 'algorithms', 'however', 'is', 'tildeomegasqrtn', 'regardless', 'of', 'the', 'network', 'topology', 'even', 'on', 'nice', 'networks', 'with', 'a', 'polylogarithmic', 'network', 'diameter', 'd', 'while', 'this', 'is', 'known', 'to', 'be', 'necessary', 'for', 'some', 'pathological', 'networks', 'most', 'topologies', 'of', 'interest', 'are', 'arguably', 'not', 'of', 'this', 'type', 'we', 'give', 'the', 'first', 'distributed', 'approximation', 'algorithms', 'for', 'shortest', 'paths', 'problems', 'that', 'adjust', 'to', 'the', 'topology', 'they', 'are', 'run', 'on', 'thus', 'achieving', 'significantly', 'faster', 'running', 'times', 'on', 'many', 'topologies', 'of', 'interest', 'the', 'running', 'time', 'of', 'our', 'algorithms', 'depends', 'on', 'and', 'is', 'close', 'to', 'q', 'where', 'q', 'is', 'the', 'quality', 'of', 'the', 'best', 'shortcut', 'that', 'exists', 'for', 'the', 'given', 'topology', 'while', 'q', 'tildethetasqrtn', 'd', 'for', 'pathological', 'worstcase', 'topologies', 'many', 'topologies', 'of', 'interest', 'have', 'q', 'tildethetad', 'which', 'results', 'in', 'near', 'instance', 'optimal', 'running', 'times', 'for', 'our', 'algorithm', 'given', 'the', 'trivial', 'omegad', 'lower', 'bound', 'the', 'problems', 'we', 'consider', 'are', 'as', 'follows', '1', 'an', 'approximate', 'shortest', 'path', 'tree', 'and', 'sssp', 'distances', '2', 'a', 'polylogarithmic', 'size', 'distance', 'label', 'for', 'every', 'node', 'such', 'that', 'from', 'the', 'labels', 'of', 'any', 'two', 'nodes', 'alone', 'one', 'can', 'determine', 'their', 'distance', 'approximately', 'and', '3', 'an', 'approximately', 'optimal', 'flow', 'for', 'the', 'transshipment', 'problem', 'our', 'algorithms', 'have', 'a', 'tunable', 'tradeoff', 'between', 'running', 'time', 'and', 'approximation', 'ratio', 'our', 'fastest', 'algorithms', 'have', 'an', 'arbitrarily', 'good', 'polynomial', 'approximation', 'guarantee', 'and', 'an', 'essentially', 'optimal', 'tildeoq', 'running', 'time', 'on', 'the', 'other', 'end', 'of', 'the', 'spectrum', 'we', 'achieve', 'polylogarithmic', 'approximations', 'in', 'tildeoq', 'cdot', 'nepsilon', 'rounds', 'for', 'any', 'epsilon', '0']] | [-0.16085033857608003, 0.0675854542031052, -0.04074469030951593, 0.05343820124124478, -0.047198329793693, -0.19002629568651602, 0.08865792345620352, 0.4203638329308749, -0.27599618823166594, -0.3403408733734811, 0.0999841224176441, -0.25172624943296323, -0.13309051899926405, 0.231794991395029, -0.05916262086248025, 0.09916173161260657, 0.090970327256127, 0.08265713065952955, -0.04197712515316153, -0.3186600334444809, 0.2329159502875429, 0.034828813778441894, 0.23375679801143848, 0.0475396366292848, 0.077088352178574, -0.01500570605342549, 0.022772369500844537, 0.011362504903466119, -0.1313895160248386, 0.09316751036922245, 0.25458281786984877, 0.16854865326432816, 0.2831621575541086, -0.42065579197849784, -0.16503443606436863, 0.1609538218168942, 0.17098495319924767, 0.08340952670628368, 0.021425167368211477, -0.2064557782730208, 0.13766894224028992, -0.09111528410027406, -0.06294108118805256, -0.03214131465036521, 0.07158068704379886, 0.019273733827192514, -0.29263004421755784, -0.006473778751891234, 0.058673379017870536, -0.027810541365805574, -0.014732458526906009, -0.15489967355235504, 0.07370806081015122, 0.17460686866611866, 0.024047771320030262, 0.09883975540199263, 0.06056844289352614, -0.12876025985788284, -0.19034695101923135, 0.36501815577990204, -0.02332342269975593, -0.17693511622306313, 0.16792144024427696, -0.07079449592923087, -0.1469349240133461, 0.13775456096169614, 0.19262478971843228, 0.15924271518017516, -0.07831396232270582, 0.12022159875728218, -0.04795288399371811, 0.17218524085697737, 0.09967573350578716, 0.052231525908447374, 0.07861860666128903, 0.16501566779732477, 0.17455733262893067, 0.08285792322963044, -0.021244737657385493, -0.09735822656453931, -0.2626832058979021, -0.10875194617693167, -0.2181522226095653, 0.019343547922341744, -0.21225593694062556, -0.17046688001659546, 0.38430491571063213, 0.13486791542950777, 0.23217842250552467, 0.15466403332671697, 0.29918319188516956, 0.08261804787057873, 0.045939122825974295, 0.21501777482266846, 0.20928658347764095, 0.0553736095608853, 0.057671403816012316, -0.18650740346988173, 0.1358970815104259, 0.07216832300155873] |
1,802.03672 | On the Scalar-Vector-Tensor Gravity: Black Hole, Thermodynamics and
Geometrothermodynamics | Recently, a new class of modified gravity theories formulated via an
additional scalar and vector field on top of the standard tensor field has been
proposed. The direct implications of these theories are expected to be relevant
for cosmology and astrophysics. In the present work, we revisit the modified
framework of the scalar-vector-tensor theories of gravity. Surprisingly, we
discover novel metric function for the black hole solutions. We also
investigate the semi-classical thermodynamics of the black holes and study the
thermodynamic properties of the obtained solutions. Moreover, we quantify the
entropy and the temperature of the new black hole and also calculate the heat
capacity. Finally, we also apply the formalism of the geometrothermodynamics to
examine thermodynamic properties of the new black hole. This formalism yields
results consistent with those obtained from the usual thermodynamic
implementation.
| gr-qc hep-ph hep-th | recently a new class of modified gravity theories formulated via an additional scalar and vector field on top of the standard tensor field has been proposed the direct implications of these theories are expected to be relevant for cosmology and astrophysics in the present work we revisit the modified framework of the scalarvectortensor theories of gravity surprisingly we discover novel metric function for the black hole solutions we also investigate the semiclassical thermodynamics of the black holes and study the thermodynamic properties of the obtained solutions moreover we quantify the entropy and the temperature of the new black hole and also calculate the heat capacity finally we also apply the formalism of the geometrothermodynamics to examine thermodynamic properties of the new black hole this formalism yields results consistent with those obtained from the usual thermodynamic implementation | [['recently', 'a', 'new', 'class', 'of', 'modified', 'gravity', 'theories', 'formulated', 'via', 'an', 'additional', 'scalar', 'and', 'vector', 'field', 'on', 'top', 'of', 'the', 'standard', 'tensor', 'field', 'has', 'been', 'proposed', 'the', 'direct', 'implications', 'of', 'these', 'theories', 'are', 'expected', 'to', 'be', 'relevant', 'for', 'cosmology', 'and', 'astrophysics', 'in', 'the', 'present', 'work', 'we', 'revisit', 'the', 'modified', 'framework', 'of', 'the', 'scalarvectortensor', 'theories', 'of', 'gravity', 'surprisingly', 'we', 'discover', 'novel', 'metric', 'function', 'for', 'the', 'black', 'hole', 'solutions', 'we', 'also', 'investigate', 'the', 'semiclassical', 'thermodynamics', 'of', 'the', 'black', 'holes', 'and', 'study', 'the', 'thermodynamic', 'properties', 'of', 'the', 'obtained', 'solutions', 'moreover', 'we', 'quantify', 'the', 'entropy', 'and', 'the', 'temperature', 'of', 'the', 'new', 'black', 'hole', 'and', 'also', 'calculate', 'the', 'heat', 'capacity', 'finally', 'we', 'also', 'apply', 'the', 'formalism', 'of', 'the', 'geometrothermodynamics', 'to', 'examine', 'thermodynamic', 'properties', 'of', 'the', 'new', 'black', 'hole', 'this', 'formalism', 'yields', 'results', 'consistent', 'with', 'those', 'obtained', 'from', 'the', 'usual', 'thermodynamic', 'implementation']] | [-0.09744264311431085, 0.06569977848448616, -0.09544080704697133, 0.12677254849233363, -0.07219597343903254, -0.10968097227776204, 0.025667303753674358, 0.27032654583180216, -0.2145833740291624, -0.2818338526036207, 0.0691389487037668, -0.28025261550347375, -0.15878642136265306, 0.20570618378491523, -0.036362905317218974, 0.07098372846923988, -0.01925439585465938, 0.06543647366411545, -0.1326411657192854, -0.21774686436744078, 0.3886866589241168, 0.1035507084657986, 0.26180252121241, 0.06427408641149454, 0.0843018518815584, -0.013417311528053902, -0.017400473808212316, 0.10077340765993166, -0.23468863385256983, 0.11643007595215321, 0.15131695380242652, 0.15023951142553843, 0.19172621047233834, -0.42537365662043586, -0.2688687846187831, 0.05502409068867564, 0.08572955355938415, 0.16642381257877467, -0.09971236611240517, -0.2669093367123209, 0.07789992148001842, -0.2293708624338786, -0.14613699852762854, -0.12355357719420948, -0.020644784273292104, -0.024619997254750857, -0.1938425043652601, 0.09669072496955564, 0.03408647966845071, -0.05062160805648412, -0.13233022361665087, -0.09548303904525443, -0.008860480500837131, 0.09538865085992523, 0.11120811432106968, 0.0006007032532258617, 0.1269957922743154, -0.13348444807856782, -0.13571805231057463, 0.36130100844756646, -0.10712173312212518, -0.1774302762316759, 0.18225368063362754, -0.1791812484152615, -0.16210250884486252, 0.019637021164218074, 0.16325485096860895, 0.21870171932352925, -0.1978040130719926, 0.15270248389766922, -0.010551015302018426, 0.12284931810641223, 0.040722417977282446, 0.07854511589753468, 0.3084993878215113, 0.11267224161693935, -0.019741339903489193, 0.2054986506298198, -0.06341205657672082, -0.13257205842049136, -0.3271538728971363, -0.21198347995622874, -0.13200785725048797, 0.057311977780259704, -0.14688297561962613, -0.1638738201410674, 0.3752871888470562, 0.18465852208079442, 0.14315369431492667, 0.054856224738828396, 0.22914120524249965, 0.14061016509966814, 0.033160160425776505, 0.06786804450059529, 0.34140301493051295, 0.17631159169661045, 0.12704496834810605, -0.2551846997281673, -0.056695124648018354, 0.1110757516717593] |
1,802.03673 | Two-dimensional Iron Monocarbide with Planar Hypercoordinate Iron and
Carbon | We report on the theoretical discovery of Iron monocarbide binary sheets
stabilized at two-dimensional confined space, which we call tetragonal-FeC
(t-FeC) and orthorhombic-FeC (o-FeC), respectively. From the energy viewpoint,
the proposed t-FeC is the global minimum configuration in the 2D space, and
each carbon atom is four-coordinated with ambient four Iron atoms. Strikingly,
the o-FeC monolayer is an orthorhombic phase with planar pentacoordinate carbon
moiety and planar seven-coordinate Fe moiety. To our knowledge, this monolayer
is the first example of a simultaneously pentacoordinate carbon and planar
seven-coordinate Fe-containing material. State-of-the-art theoretical
calculations confirm that all these monolayers have significantly dynamic,
mechanical, and thermal stabilities. Among these two monolayers, t-FeC
monolayer shows a higher theoretical capacity (395 mAh g-1 ), and can stably
adsorb Li up to t-FeCLi3 . Low migration energy barrier is predicted as small
as 0.26 eV for Li, which result in the fast diffusion of Li atom on this
monolayer. Moreover, electron-phonon calculations coupled with
Bardeen-Cooper-Schrieffer arguments suggest t-FeC can be potential
two-dimensional superconductors with 6.77 K superconducting transition
temperature.
| cond-mat.mtrl-sci | we report on the theoretical discovery of iron monocarbide binary sheets stabilized at twodimensional confined space which we call tetragonalfec tfec and orthorhombicfec ofec respectively from the energy viewpoint the proposed tfec is the global minimum configuration in the 2d space and each carbon atom is fourcoordinated with ambient four iron atoms strikingly the ofec monolayer is an orthorhombic phase with planar pentacoordinate carbon moiety and planar sevencoordinate fe moiety to our knowledge this monolayer is the first example of a simultaneously pentacoordinate carbon and planar sevencoordinate fecontaining material stateoftheart theoretical calculations confirm that all these monolayers have significantly dynamic mechanical and thermal stabilities among these two monolayers tfec monolayer shows a higher theoretical capacity 395 mah g1 and can stably adsorb li up to tfecli3 low migration energy barrier is predicted as small as 026 ev for li which result in the fast diffusion of li atom on this monolayer moreover electronphonon calculations coupled with bardeencooperschrieffer arguments suggest tfec can be potential twodimensional superconductors with 677 k superconducting transition temperature | [['we', 'report', 'on', 'the', 'theoretical', 'discovery', 'of', 'iron', 'monocarbide', 'binary', 'sheets', 'stabilized', 'at', 'twodimensional', 'confined', 'space', 'which', 'we', 'call', 'tetragonalfec', 'tfec', 'and', 'orthorhombicfec', 'ofec', 'respectively', 'from', 'the', 'energy', 'viewpoint', 'the', 'proposed', 'tfec', 'is', 'the', 'global', 'minimum', 'configuration', 'in', 'the', '2d', 'space', 'and', 'each', 'carbon', 'atom', 'is', 'fourcoordinated', 'with', 'ambient', 'four', 'iron', 'atoms', 'strikingly', 'the', 'ofec', 'monolayer', 'is', 'an', 'orthorhombic', 'phase', 'with', 'planar', 'pentacoordinate', 'carbon', 'moiety', 'and', 'planar', 'sevencoordinate', 'fe', 'moiety', 'to', 'our', 'knowledge', 'this', 'monolayer', 'is', 'the', 'first', 'example', 'of', 'a', 'simultaneously', 'pentacoordinate', 'carbon', 'and', 'planar', 'sevencoordinate', 'fecontaining', 'material', 'stateoftheart', 'theoretical', 'calculations', 'confirm', 'that', 'all', 'these', 'monolayers', 'have', 'significantly', 'dynamic', 'mechanical', 'and', 'thermal', 'stabilities', 'among', 'these', 'two', 'monolayers', 'tfec', 'monolayer', 'shows', 'a', 'higher', 'theoretical', 'capacity', '395', 'mah', 'g1', 'and', 'can', 'stably', 'adsorb', 'li', 'up', 'to', 'tfecli3', 'low', 'migration', 'energy', 'barrier', 'is', 'predicted', 'as', 'small', 'as', '026', 'ev', 'for', 'li', 'which', 'result', 'in', 'the', 'fast', 'diffusion', 'of', 'li', 'atom', 'on', 'this', 'monolayer', 'moreover', 'electronphonon', 'calculations', 'coupled', 'with', 'bardeencooperschrieffer', 'arguments', 'suggest', 'tfec', 'can', 'be', 'potential', 'twodimensional', 'superconductors', 'with', '677', 'k', 'superconducting', 'transition', 'temperature']] | [-0.10606915159555881, 0.1819558216654587, 0.02283697015380267, -0.044050510987922877, 0.00593523018102607, -0.1727957735185205, 0.11610954364917894, 0.4315677262157179, -0.22730616985397958, -0.3159764825788714, -0.018319285343117688, -0.3245122974842602, -0.12450193529746131, 0.14202800269892313, 0.013124450020237554, 0.0016518570786423009, 0.026142474172798837, -0.05044362272326806, -0.08487357166364373, -0.23336741140022618, 0.2352330856971003, 0.04163664544665729, 0.30692190091524807, 0.10477165913394426, 0.010007040480062112, -0.06485660891625264, 0.13025199225091416, 0.02710727191499799, -0.19643791871578672, 0.10531713522288093, 0.24371205801896242, -0.0747267986584154, 0.17638999285604456, -0.44027455255204107, -0.2264141962044259, 0.007224848003687789, 0.1273977669456291, 0.14627665357508043, -0.08365857610276536, -0.23425189437278146, 0.07568613273020752, -0.14056153375343045, -0.09813530310722333, -0.062182159484103786, -0.008509199612235986, 0.01949692463143642, -0.2143043163030044, 0.07987095576404414, 0.04341632069626487, 0.051078391481123676, -0.1301451154202888, -0.17406198653965171, -0.133232837084461, 0.012909776046698601, -0.006088858211278534, 0.049695502136550516, 0.17918620124945175, -0.03525442949580086, -0.08023478380572166, 0.4113332690347148, -0.09005674521109054, -0.06368018864937451, 0.21285706075914898, -0.14863827640931151, -0.09624054901567954, 0.19505929368221264, 0.08347052344994516, 0.11295186455783822, -0.13085095283014248, 0.05455342559552439, -0.048995732256032015, 0.1779864219151819, 0.06996833279682613, 0.02819449874508825, 0.23887851667989576, 0.21868660187302447, 0.028558734769684187, 0.09585228160686027, -0.12459516435064757, -0.039167361467012336, -0.1706259206215047, -0.21937028074460624, -0.18400646948258492, 0.0657787163198133, -0.11429729939800665, -0.17470238589166853, 0.3382311397295746, 0.08609521434416775, 0.17143274342745357, -0.031738600481058594, 0.23894455967332173, 0.07756023736155783, 0.04711224703314882, 0.04675635608399044, 0.2810941581825454, 0.16634409103588843, 0.08625881229845449, -0.2462999428078671, 0.05043570392747751, 0.04990302089902555] |
1,802.03674 | Compressive Spectrum Sensing for Cognitive Radio Networks | A cognitive radio system has the ability to observe and learn from the
environment, adapt to the environmental conditions, and use the radio spectrum
more efficiently. It allows secondary users (SUs) to use the primary users
(PUs) channels when they are not being utilized. Cognitive radio involves three
main processes: spectrum sensing, deciding, and acting. In the spectrum sensing
process, the channel occupancy is measured with spectrum sensing techniques in
order to detect unused channels. In the deciding process, sensing results are
analyzed and decisions are made based on these results. In the acting process,
actions are made by adjusting the transmission parameters to enhance the
cognitive radio performance.
One of the main challenges of cognitive radio is the wideband spectrum
sensing. Existing spectrum sensing techniques are based on a set of
observations sampled by an ADC at the Nyquist rate. However, those techniques
can sense only one channel at a time because of the hardware limitations on the
sampling rate. In addition, in order to sense a wideband spectrum, the wideband
is divided into narrow bands or multiple frequency bands. SUs have to sense
each band using multiple RF frontends simultaneously, which can result in a
very high processing time, hardware cost, and computational complexity. In
order to overcome this problem, the signal sampling should be as fast as
possible even with high dimensional signals. Compressive sensing has been
proposed as a low-cost solution to reduce the processing time and accelerate
the scanning process. It allows reducing the number of samples required for
high dimensional signal acquisition while keeping the essential information.
| cs.IT math.IT | a cognitive radio system has the ability to observe and learn from the environment adapt to the environmental conditions and use the radio spectrum more efficiently it allows secondary users sus to use the primary users pus channels when they are not being utilized cognitive radio involves three main processes spectrum sensing deciding and acting in the spectrum sensing process the channel occupancy is measured with spectrum sensing techniques in order to detect unused channels in the deciding process sensing results are analyzed and decisions are made based on these results in the acting process actions are made by adjusting the transmission parameters to enhance the cognitive radio performance one of the main challenges of cognitive radio is the wideband spectrum sensing existing spectrum sensing techniques are based on a set of observations sampled by an adc at the nyquist rate however those techniques can sense only one channel at a time because of the hardware limitations on the sampling rate in addition in order to sense a wideband spectrum the wideband is divided into narrow bands or multiple frequency bands sus have to sense each band using multiple rf frontends simultaneously which can result in a very high processing time hardware cost and computational complexity in order to overcome this problem the signal sampling should be as fast as possible even with high dimensional signals compressive sensing has been proposed as a lowcost solution to reduce the processing time and accelerate the scanning process it allows reducing the number of samples required for high dimensional signal acquisition while keeping the essential information | [['a', 'cognitive', 'radio', 'system', 'has', 'the', 'ability', 'to', 'observe', 'and', 'learn', 'from', 'the', 'environment', 'adapt', 'to', 'the', 'environmental', 'conditions', 'and', 'use', 'the', 'radio', 'spectrum', 'more', 'efficiently', 'it', 'allows', 'secondary', 'users', 'sus', 'to', 'use', 'the', 'primary', 'users', 'pus', 'channels', 'when', 'they', 'are', 'not', 'being', 'utilized', 'cognitive', 'radio', 'involves', 'three', 'main', 'processes', 'spectrum', 'sensing', 'deciding', 'and', 'acting', 'in', 'the', 'spectrum', 'sensing', 'process', 'the', 'channel', 'occupancy', 'is', 'measured', 'with', 'spectrum', 'sensing', 'techniques', 'in', 'order', 'to', 'detect', 'unused', 'channels', 'in', 'the', 'deciding', 'process', 'sensing', 'results', 'are', 'analyzed', 'and', 'decisions', 'are', 'made', 'based', 'on', 'these', 'results', 'in', 'the', 'acting', 'process', 'actions', 'are', 'made', 'by', 'adjusting', 'the', 'transmission', 'parameters', 'to', 'enhance', 'the', 'cognitive', 'radio', 'performance', 'one', 'of', 'the', 'main', 'challenges', 'of', 'cognitive', 'radio', 'is', 'the', 'wideband', 'spectrum', 'sensing', 'existing', 'spectrum', 'sensing', 'techniques', 'are', 'based', 'on', 'a', 'set', 'of', 'observations', 'sampled', 'by', 'an', 'adc', 'at', 'the', 'nyquist', 'rate', 'however', 'those', 'techniques', 'can', 'sense', 'only', 'one', 'channel', 'at', 'a', 'time', 'because', 'of', 'the', 'hardware', 'limitations', 'on', 'the', 'sampling', 'rate', 'in', 'addition', 'in', 'order', 'to', 'sense', 'a', 'wideband', 'spectrum', 'the', 'wideband', 'is', 'divided', 'into', 'narrow', 'bands', 'or', 'multiple', 'frequency', 'bands', 'sus', 'have', 'to', 'sense', 'each', 'band', 'using', 'multiple', 'rf', 'frontends', 'simultaneously', 'which', 'can', 'result', 'in', 'a', 'very', 'high', 'processing', 'time', 'hardware', 'cost', 'and', 'computational', 'complexity', 'in', 'order', 'to', 'overcome', 'this', 'problem', 'the', 'signal', 'sampling', 'should', 'be', 'as', 'fast', 'as', 'possible', 'even', 'with', 'high', 'dimensional', 'signals', 'compressive', 'sensing', 'has', 'been', 'proposed', 'as', 'a', 'lowcost', 'solution', 'to', 'reduce', 'the', 'processing', 'time', 'and', 'accelerate', 'the', 'scanning', 'process', 'it', 'allows', 'reducing', 'the', 'number', 'of', 'samples', 'required', 'for', 'high', 'dimensional', 'signal', 'acquisition', 'while', 'keeping', 'the', 'essential', 'information']] | [-0.13112959560033857, 0.09555387249737207, -0.03625107342518951, 0.015639749017129997, -0.09849526058128209, -0.18668175849199523, 0.07194097834185983, 0.4395857829451844, -0.2972810637460802, -0.31878268607173244, 0.14355150853441284, -0.24207377882274628, -0.13659760880482316, 0.19308633088247545, -0.11039372490534821, 0.06926653646959607, 0.05567221774475316, 0.033780631183437694, -0.006997878389687989, -0.21082013234064095, 0.25092447106682203, 0.15053698536320217, 0.3387036728690389, -0.007313889233544185, 0.0640902199920536, 0.01985056751882197, -0.044975466100444145, -0.06506516205628506, -0.03247560235360078, 0.1006279232528436, 0.3422308586805195, 0.1705401919105899, 0.28797671084819865, -0.44022252256610206, -0.2614211137322426, 0.1036355224882426, 0.16659541246870765, 0.05211238709000424, -0.03686504628397073, -0.2712324034819245, 0.12104602214905076, -0.159262218719752, -0.04046233559820532, -0.02846710902139431, -0.06624226105140926, 0.007417131598884799, -0.29472931088284793, 0.00790672539113649, -0.0029860592886323937, -0.0024704081643755218, -0.07549540357205649, -0.08009777052156244, 0.038006764397285384, 0.2137978034234073, 0.03261152868638941, -0.02277827745581492, 0.15786833666838676, -0.10315203877434571, -0.12003113451624509, 0.3881551142739479, -0.011742056315116755, -0.1774187368825928, 0.23556538610037472, -0.1420266674977582, -0.12874263175143488, 0.18503672127326873, 0.2007290968665244, 0.0494546682410962, -0.17029709406552293, 0.06378333875599597, 0.07164311837121674, 0.20470381375382735, 0.07617528931531672, 0.11327116557719193, 0.17651682869113358, 0.15981302376678957, 0.11162944076168475, 0.10364242221986585, -0.13598464270469382, -0.007237729358180522, -0.1762038192173073, -0.10863369839715668, -0.23294460484510138, 0.004702634970489766, -0.044625135565007516, -0.08243560307631986, 0.39651522614564677, 0.1455903006660019, 0.16723369886193906, 0.06390608794599446, 0.40623630367984337, 0.13839126340235972, 0.09429328692120857, 0.08371564862938038, 0.19394593686529368, 0.11524917113244137, 0.1457964518284974, -0.19282580598721372, 0.05241030411167998, -0.029653759492639126] |
1,802.03675 | Understanding Convolutional Networks with APPLE : Automatic Patch
Pattern Labeling for Explanation | With the success of deep learning, recent efforts have been focused on
analyzing how learned networks make their classifications. We are interested in
analyzing the network output based on the network structure and information
flow through the network layers. We contribute an algorithm for 1) analyzing a
deep network to find neurons that are 'important' in terms of the network
classification outcome, and 2)automatically labeling the patches of the input
image that activate these important neurons. We propose several measures of
importance for neurons and demonstrate that our technique can be used to gain
insight into, and explain how a network decomposes an image to make its final
classification.
| cs.LG cs.CY stat.ML | with the success of deep learning recent efforts have been focused on analyzing how learned networks make their classifications we are interested in analyzing the network output based on the network structure and information flow through the network layers we contribute an algorithm for 1 analyzing a deep network to find neurons that are important in terms of the network classification outcome and 2automatically labeling the patches of the input image that activate these important neurons we propose several measures of importance for neurons and demonstrate that our technique can be used to gain insight into and explain how a network decomposes an image to make its final classification | [['with', 'the', 'success', 'of', 'deep', 'learning', 'recent', 'efforts', 'have', 'been', 'focused', 'on', 'analyzing', 'how', 'learned', 'networks', 'make', 'their', 'classifications', 'we', 'are', 'interested', 'in', 'analyzing', 'the', 'network', 'output', 'based', 'on', 'the', 'network', 'structure', 'and', 'information', 'flow', 'through', 'the', 'network', 'layers', 'we', 'contribute', 'an', 'algorithm', 'for', '1', 'analyzing', 'a', 'deep', 'network', 'to', 'find', 'neurons', 'that', 'are', 'important', 'in', 'terms', 'of', 'the', 'network', 'classification', 'outcome', 'and', '2automatically', 'labeling', 'the', 'patches', 'of', 'the', 'input', 'image', 'that', 'activate', 'these', 'important', 'neurons', 'we', 'propose', 'several', 'measures', 'of', 'importance', 'for', 'neurons', 'and', 'demonstrate', 'that', 'our', 'technique', 'can', 'be', 'used', 'to', 'gain', 'insight', 'into', 'and', 'explain', 'how', 'a', 'network', 'decomposes', 'an', 'image', 'to', 'make', 'its', 'final', 'classification']] | [-0.04694851745282196, -0.004933685061890476, -0.07981977678180018, 0.06613749617719333, -0.06427216452235977, -0.13172271931802648, 0.028987628808762465, 0.4801247849439581, -0.2683383388168834, -0.3050295593286002, 0.09039565649409606, -0.2546784561817293, -0.2725431809408797, 0.1788641997155975, -0.09781343829645603, 0.054243702156344185, 0.12615023498181943, 0.0656568338982416, 0.000782274958004968, -0.29597626762093837, 0.34914561333479704, 0.04252559389364992, 0.32687188289343827, 0.03492864056628336, 0.12906771722784335, -0.024305396079499688, -0.06513622499726436, -0.0008272856055689907, -0.07325662799168506, 0.21749612923573564, 0.29038547800802106, 0.21811951618076786, 0.3313054778134554, -0.5025961728835547, -0.26142155153987306, 0.10863389752167105, 0.16959986125153523, 0.11324704501829627, -0.01198838414253529, -0.31149280389029255, 0.10686490356521164, -0.1357712272071728, 0.030388244574337645, -0.17773447828194885, -0.021247089780108246, 0.02155409360097514, -0.2543436664192187, -0.012224289881824344, 0.08146230801422563, 0.02585459211022007, -0.0348516741079813, -0.10940263338421506, -0.026208204124554026, 0.25367631861957274, 0.01988204094339852, 0.04991812264887375, 0.15395243996668054, -0.21406521663690606, -0.12619050057535922, 0.30862726977405447, -0.023159723778479493, -0.18486533786118445, 0.17460731008409144, -0.042691874363097466, -0.1543087251311927, 0.09091503892300858, 0.28242770375476944, 0.06582481200220408, -0.15455585269578645, -0.042045276170096325, -0.04189468024264055, 0.18224265801728945, 0.012385333319091134, 0.03681331736044268, 0.20465781182671586, 0.27927111116824327, 0.02599432925193536, 0.15918810595650468, -0.13190725869342848, -0.03095232412818371, -0.19874270969173974, -0.11625056881112633, -0.17223982175777633, 0.002028646240769713, -0.09089054483262805, -0.09822189147342686, 0.46481829131436014, 0.19882278260343741, 0.27714379061513617, 0.07625644147844503, 0.28850584569024956, 0.0489731470168206, 0.10629087972187402, 0.08253650588449091, 0.23080381777792894, 0.09861828610128551, 0.10524818687958436, -0.16653814394440916, 0.11236315349190219, 0.04433035014059256] |
1,802.03676 | Differentiable Dynamic Programming for Structured Prediction and
Attention | Dynamic programming (DP) solves a variety of structured combinatorial
problems by iteratively breaking them down into smaller subproblems. In spite
of their versatility, DP algorithms are usually non-differentiable, which
hampers their use as a layer in neural networks trained by backpropagation. To
address this issue, we propose to smooth the max operator in the dynamic
programming recursion, using a strongly convex regularizer. This allows to
relax both the optimal value and solution of the original combinatorial
problem, and turns a broad class of DP algorithms into differentiable
operators. Theoretically, we provide a new probabilistic perspective on
backpropagating through these DP operators, and relate them to inference in
graphical models. We derive two particular instantiations of our framework, a
smoothed Viterbi algorithm for sequence prediction and a smoothed DTW algorithm
for time-series alignment. We showcase these instantiations on two structured
prediction tasks and on structured and sparse attention for neural machine
translation.
| stat.ML cs.LG | dynamic programming dp solves a variety of structured combinatorial problems by iteratively breaking them down into smaller subproblems in spite of their versatility dp algorithms are usually nondifferentiable which hampers their use as a layer in neural networks trained by backpropagation to address this issue we propose to smooth the max operator in the dynamic programming recursion using a strongly convex regularizer this allows to relax both the optimal value and solution of the original combinatorial problem and turns a broad class of dp algorithms into differentiable operators theoretically we provide a new probabilistic perspective on backpropagating through these dp operators and relate them to inference in graphical models we derive two particular instantiations of our framework a smoothed viterbi algorithm for sequence prediction and a smoothed dtw algorithm for timeseries alignment we showcase these instantiations on two structured prediction tasks and on structured and sparse attention for neural machine translation | [['dynamic', 'programming', 'dp', 'solves', 'a', 'variety', 'of', 'structured', 'combinatorial', 'problems', 'by', 'iteratively', 'breaking', 'them', 'down', 'into', 'smaller', 'subproblems', 'in', 'spite', 'of', 'their', 'versatility', 'dp', 'algorithms', 'are', 'usually', 'nondifferentiable', 'which', 'hampers', 'their', 'use', 'as', 'a', 'layer', 'in', 'neural', 'networks', 'trained', 'by', 'backpropagation', 'to', 'address', 'this', 'issue', 'we', 'propose', 'to', 'smooth', 'the', 'max', 'operator', 'in', 'the', 'dynamic', 'programming', 'recursion', 'using', 'a', 'strongly', 'convex', 'regularizer', 'this', 'allows', 'to', 'relax', 'both', 'the', 'optimal', 'value', 'and', 'solution', 'of', 'the', 'original', 'combinatorial', 'problem', 'and', 'turns', 'a', 'broad', 'class', 'of', 'dp', 'algorithms', 'into', 'differentiable', 'operators', 'theoretically', 'we', 'provide', 'a', 'new', 'probabilistic', 'perspective', 'on', 'backpropagating', 'through', 'these', 'dp', 'operators', 'and', 'relate', 'them', 'to', 'inference', 'in', 'graphical', 'models', 'we', 'derive', 'two', 'particular', 'instantiations', 'of', 'our', 'framework', 'a', 'smoothed', 'viterbi', 'algorithm', 'for', 'sequence', 'prediction', 'and', 'a', 'smoothed', 'dtw', 'algorithm', 'for', 'timeseries', 'alignment', 'we', 'showcase', 'these', 'instantiations', 'on', 'two', 'structured', 'prediction', 'tasks', 'and', 'on', 'structured', 'and', 'sparse', 'attention', 'for', 'neural', 'machine', 'translation']] | [-0.04880634124162576, -0.01388849684388827, -0.06756057355873632, 0.12471902189893487, -0.14960600175765276, -0.2079704187915272, 0.0711332469174811, 0.4347161866897187, -0.3883698774325902, -0.3032578951524978, 0.08512737786718058, -0.20301302379262803, -0.21170638719363916, 0.16285109081589277, -0.1089428861082735, 0.14338863078606567, 0.08553716163721478, -0.038829629224476817, -0.1137926728164566, -0.24818332790588307, 0.30449699863964164, -0.02045266843086343, 0.2699105844506069, 0.01052134134960885, 0.13494600416068606, 0.027933251418000616, -0.008262120837974824, 0.027310799850484, -0.08614711717483495, 0.19458176803602437, 0.29782132170616904, 0.21052880863202675, 0.3644730942015419, -0.43764225990566985, -0.2003912013078059, 0.09141226371269155, 0.15068453291565218, 0.10997286185680809, -0.008569135558822298, -0.27632429638248407, 0.0965254434048266, -0.11836006802380307, 0.013109931364556812, -0.14160650879736766, -0.0377749625426896, -0.018758770189439226, -0.30757879380376496, 0.01651160917645752, 0.0942231110861488, 0.024992463413305237, -0.052937394347649366, -0.13357657496663217, 0.03687480118107174, 0.0542010684568583, 0.036747798258870444, 0.036300820734857624, 0.09450752772884258, -0.12859981456796163, -0.17231656441199808, 0.3464287444394057, -0.018285926037455682, -0.2564556885399664, 0.17825966764438822, 0.01501747717100214, -0.18778251941371338, 0.09400366430497722, 0.2855010555350894, 0.18293606491130315, -0.16768497085531817, 0.08414181351695604, -0.044406296310650295, 0.14218432151416427, 0.041309682174357557, -0.01919171494117241, 0.17737390924112514, 0.2096060664629693, 0.08739219164932209, 0.1920534699156091, -0.0586336492086662, -0.1451057330859418, -0.21871933070803987, -0.09119509560802322, -0.16367116940843052, -0.020427844962043477, -0.14436394401416583, -0.1827749427429567, 0.41695252615983125, 0.1691385612681212, 0.21915171847721895, 0.1852615903145541, 0.30929046308325714, 0.10242581119859553, 0.07911674410951075, 0.10232490179320143, 0.1605462706944634, 0.09080981618774105, 0.12682467732356478, -0.18474263033138846, 0.0865461208382683, 0.1253627707645149] |
1,802.03677 | The possibility of leptonic CP-violation measurement with JUNO | The existence of CP-violation in the leptonic sector is one of the most
important issues for modern science. Neutrino physics is a key to the solution
of this problem. JUNO (under construction) is the near future of neutrino
physics. However CP-violation is not a priority for the current scientific
program. We estimate the capability of $\delta_{\rm CP}$ measurement, assuming
a combination of the JUNO detector and a superconductive cyclotron as the
antineutrino source. This method of measuring CP-violation is an alternative to
conventional beam experiments. A significance level of 3$\sigma$ can be reached
for 22% of the $\delta_{\rm CP}$ range. The accuracy of measurement lies
between 8$^{\rm o}$ and 22$^{\rm o}$. It is shown that the dominant influence
on the result is the uncertainty in the mixing angle $\Theta_{23}$.
| hep-ph hep-ex | the existence of cpviolation in the leptonic sector is one of the most important issues for modern science neutrino physics is a key to the solution of this problem juno under construction is the near future of neutrino physics however cpviolation is not a priority for the current scientific program we estimate the capability of delta_rm cp measurement assuming a combination of the juno detector and a superconductive cyclotron as the antineutrino source this method of measuring cpviolation is an alternative to conventional beam experiments a significance level of 3sigma can be reached for 22 of the delta_rm cp range the accuracy of measurement lies between 8rm o and 22rm o it is shown that the dominant influence on the result is the uncertainty in the mixing angle theta_23 | [['the', 'existence', 'of', 'cpviolation', 'in', 'the', 'leptonic', 'sector', 'is', 'one', 'of', 'the', 'most', 'important', 'issues', 'for', 'modern', 'science', 'neutrino', 'physics', 'is', 'a', 'key', 'to', 'the', 'solution', 'of', 'this', 'problem', 'juno', 'under', 'construction', 'is', 'the', 'near', 'future', 'of', 'neutrino', 'physics', 'however', 'cpviolation', 'is', 'not', 'a', 'priority', 'for', 'the', 'current', 'scientific', 'program', 'we', 'estimate', 'the', 'capability', 'of', 'delta_rm', 'cp', 'measurement', 'assuming', 'a', 'combination', 'of', 'the', 'juno', 'detector', 'and', 'a', 'superconductive', 'cyclotron', 'as', 'the', 'antineutrino', 'source', 'this', 'method', 'of', 'measuring', 'cpviolation', 'is', 'an', 'alternative', 'to', 'conventional', 'beam', 'experiments', 'a', 'significance', 'level', 'of', '3sigma', 'can', 'be', 'reached', 'for', '22', 'of', 'the', 'delta_rm', 'cp', 'range', 'the', 'accuracy', 'of', 'measurement', 'lies', 'between', '8rm', 'o', 'and', '22rm', 'o', 'it', 'is', 'shown', 'that', 'the', 'dominant', 'influence', 'on', 'the', 'result', 'is', 'the', 'uncertainty', 'in', 'the', 'mixing', 'angle', 'theta_23']] | [-0.12441467834490373, 0.16101181578685714, -0.026090292852054272, 0.10716282200995948, -0.06458742132540359, -0.1161427927679967, 0.07261072110038164, 0.28924060363120346, -0.2532507026389371, -0.32786095019090605, 0.0954037322139353, -0.29178956710524107, -0.03809215693577561, 0.22056542868480492, 0.014344456771662992, 0.054126189755356616, 0.07159186091071876, -0.009949063254130442, -0.11446160706691444, -0.1829505729120831, 0.26175724734667716, 0.12523716079547656, 0.25259243241193624, 0.11731583794151151, 0.07466636788232664, -0.052875770855146324, -0.021623106879117185, -0.060620694118010444, -0.0770606504818772, 0.060136309390808204, 0.2670763148817905, 0.1917725589357374, 0.1877267000936838, -0.29533952876813563, -0.13471767554296968, 0.14326178483563914, 0.08926764292671352, 0.06649988141387354, -0.04667631697267034, -0.29199454210998216, 0.0585085260803638, -0.17305444027369393, -0.14295818836630372, 0.012793125057694062, -0.011305618886799776, -0.09174661360258712, -0.3125634425493001, 0.07304639583489633, -0.001302069020565859, 0.038155924396403494, 0.00813734634822711, -0.17892371356674983, 0.026420736642077912, 0.08043809123553855, 0.08499171704147733, 0.04895988985911452, 0.10633324247301203, -0.1499343863941094, -0.09902482990955197, 0.4456829439502123, -0.05796913714184202, -0.1573208876733863, 0.11680908191790298, -0.18912853670934604, -0.13815839563373677, 0.10316676002306242, 0.13221209426951963, 0.052023112055775166, -0.1641471470280211, 0.11011883671586799, -0.06845497379671464, 0.19652012974572505, 0.05132764052101519, 0.013031175515304009, 0.27573664951347565, 0.26884730186587735, 0.139054214487993, -0.013895327851623875, -0.18141261443798973, -0.024156118992196267, -0.3685398414413365, -0.1651258018581186, -0.14178984279405007, 0.0465787467728378, -0.053123797531656615, -0.09242677435981897, 0.42465408504471297, 0.16859788205041443, 0.12782339282449365, -0.04536259757686955, 0.3067875690036273, 0.0966752550570121, 0.035006169496869396, 0.012582124214503885, 0.34914642677447477, 0.14083225422903403, 0.12886341090509018, -0.2929974598196415, 0.12034139653682246, 0.0359993687318277] |
1,802.03678 | Boson-boson pure-dephasing model with non-Markovian properties | Understanding decoherence processes is crucial in the study of open quantum
systems. In this paper, we discuss the mechanism of pure-dephasing process with
a newly proposed boson-boson model, namely, a bosonic field coupled to another
bosonic bath in thermal equilibrium. Our model is fully solvable and can
reproduce the pure-dephasing process which is usually described by the
well-known spin-boson model, therefore offering a new perspective to
understanding decoherence processes in open quantum systems of high dimension.
We also show that this model admits a generically non-Markovian dynamics with
respect to various different non-Markovian measures.
| quant-ph | understanding decoherence processes is crucial in the study of open quantum systems in this paper we discuss the mechanism of puredephasing process with a newly proposed bosonboson model namely a bosonic field coupled to another bosonic bath in thermal equilibrium our model is fully solvable and can reproduce the puredephasing process which is usually described by the wellknown spinboson model therefore offering a new perspective to understanding decoherence processes in open quantum systems of high dimension we also show that this model admits a generically nonmarkovian dynamics with respect to various different nonmarkovian measures | [['understanding', 'decoherence', 'processes', 'is', 'crucial', 'in', 'the', 'study', 'of', 'open', 'quantum', 'systems', 'in', 'this', 'paper', 'we', 'discuss', 'the', 'mechanism', 'of', 'puredephasing', 'process', 'with', 'a', 'newly', 'proposed', 'bosonboson', 'model', 'namely', 'a', 'bosonic', 'field', 'coupled', 'to', 'another', 'bosonic', 'bath', 'in', 'thermal', 'equilibrium', 'our', 'model', 'is', 'fully', 'solvable', 'and', 'can', 'reproduce', 'the', 'puredephasing', 'process', 'which', 'is', 'usually', 'described', 'by', 'the', 'wellknown', 'spinboson', 'model', 'therefore', 'offering', 'a', 'new', 'perspective', 'to', 'understanding', 'decoherence', 'processes', 'in', 'open', 'quantum', 'systems', 'of', 'high', 'dimension', 'we', 'also', 'show', 'that', 'this', 'model', 'admits', 'a', 'generically', 'nonmarkovian', 'dynamics', 'with', 'respect', 'to', 'various', 'different', 'nonmarkovian', 'measures']] | [-0.11879308468493771, 0.18121087682393797, -0.09310275777936616, 0.07860011327288026, -0.008593759534167165, -0.23865542588557334, 0.01578753666105145, 0.33496441419652484, -0.2780161083457952, -0.23054064350373588, 0.022798640106091315, -0.24466930230722783, -0.17878761265819776, 0.18475385369891498, -0.05470782441106883, 0.040299334979437766, 0.05286006694238514, 0.0060085599271065375, 0.007373998518735963, -0.21917333375622935, 0.3244157200580106, 0.06372201398876991, 0.270464550228195, 0.0690652982311997, 0.10747847714501017, -0.02268865896745565, 0.025132021921231075, -0.01947742257703175, -0.12074705929920496, 0.056095208739861846, 0.23464158497394083, 0.056944417710257496, 0.2462517992950025, -0.41007306943944793, -0.28755244681056824, 0.10314312194067826, 0.15264935822453984, 0.1782799931626985, -0.014584525389240143, -0.30232113479894207, 0.00714453694192653, -0.19176211352509626, -0.15297828103970498, -0.11004816136877746, 0.004458036849602185, -0.05729158427021367, -0.2367920278121985, 0.08177917002064938, 0.12889846115115475, 0.004471443953391033, -0.03867715672946515, -0.01403626907577223, 0.03883778439225391, 0.09271569234725247, -0.020899001279216695, 0.016293797409161925, 0.15080132280932146, -0.1560956571211523, -0.17938031049128225, 0.38427201247813697, -0.10830606854064985, -0.21999948536184558, 0.2665015642154724, -0.12354505908715123, -0.14810921256232293, 0.07811556620761118, 0.15919673595418957, 0.07736734562414757, -0.2757667135150033, 0.12596946450371724, -0.022610284467326835, 0.1400096778896578, -0.06580484793224234, 0.08603881260855718, 0.20158758476634134, 0.22526670197777926, 0.0036067876548684656, 0.22017000667116743, 0.018649006418467676, -0.23663710959334958, -0.2875163896898541, -0.14494349172418106, -0.1471717819383249, 0.1087539765161482, -0.049462427979457796, -0.16374397056890613, 0.40712466113705265, 0.2207340998426476, 0.16803992242909016, 0.0028343133571399177, 0.27464375934226715, 0.1708950107252136, 0.015272966546422623, 0.05524053895707302, 0.17864660326232937, 0.14915951154383017, 0.0352660531297009, -0.29728615132873837, 0.026061454441081336, 0.012970463900351302] |
1,802.03679 | Searching for the light Higgsinos in MSSM at the future e-p colliders | The search of the light Higgsino {in the Minimal Supersymmetric Standard
Model (MSSM)} is a crucial test for the criteria of the naturalness in
supersymmetry. On the other hand, the direct production of light Higgsino is
also known as one of the most challenging SUSY searches at the current CERN
Large Hadron collider (LHC). The lack of visible leptons due to the compressed
spectrum and their small production rates limits their discovery potential in
both mono-jet plus MET as well as the weak boson fusion (WBF) production. The
signal $S/B$ ratio prediction is usually within the background systematic
uncertainties at the LHC. Without color exchange between the beams, the $e-p$
colliders are well-known to have the WBF feature. Therefore, we study the
search of the light Higgsinos at two future $e-p$ colliders at CERN, LHeC and
FCC-eh.~The light Higgsinos will be produced in pair through weak boson fusion
with controlled background at these colliders. We find the Higgsino of
95/145~GeV can be reached at 2$\sigma$ level at the future LHeC/FCC-eh with a
luminosity $3 ~\text{ab}^{-1}$ respectively.
| hep-ph | the search of the light higgsino in the minimal supersymmetric standard model mssm is a crucial test for the criteria of the naturalness in supersymmetry on the other hand the direct production of light higgsino is also known as one of the most challenging susy searches at the current cern large hadron collider lhc the lack of visible leptons due to the compressed spectrum and their small production rates limits their discovery potential in both monojet plus met as well as the weak boson fusion wbf production the signal sb ratio prediction is usually within the background systematic uncertainties at the lhc without color exchange between the beams the ep colliders are wellknown to have the wbf feature therefore we study the search of the light higgsinos at two future ep colliders at cern lhec and fccehthe light higgsinos will be produced in pair through weak boson fusion with controlled background at these colliders we find the higgsino of 95145gev can be reached at 2sigma level at the future lhecfcceh with a luminosity 3 textab1 respectively | [['the', 'search', 'of', 'the', 'light', 'higgsino', 'in', 'the', 'minimal', 'supersymmetric', 'standard', 'model', 'mssm', 'is', 'a', 'crucial', 'test', 'for', 'the', 'criteria', 'of', 'the', 'naturalness', 'in', 'supersymmetry', 'on', 'the', 'other', 'hand', 'the', 'direct', 'production', 'of', 'light', 'higgsino', 'is', 'also', 'known', 'as', 'one', 'of', 'the', 'most', 'challenging', 'susy', 'searches', 'at', 'the', 'current', 'cern', 'large', 'hadron', 'collider', 'lhc', 'the', 'lack', 'of', 'visible', 'leptons', 'due', 'to', 'the', 'compressed', 'spectrum', 'and', 'their', 'small', 'production', 'rates', 'limits', 'their', 'discovery', 'potential', 'in', 'both', 'monojet', 'plus', 'met', 'as', 'well', 'as', 'the', 'weak', 'boson', 'fusion', 'wbf', 'production', 'the', 'signal', 'sb', 'ratio', 'prediction', 'is', 'usually', 'within', 'the', 'background', 'systematic', 'uncertainties', 'at', 'the', 'lhc', 'without', 'color', 'exchange', 'between', 'the', 'beams', 'the', 'ep', 'colliders', 'are', 'wellknown', 'to', 'have', 'the', 'wbf', 'feature', 'therefore', 'we', 'study', 'the', 'search', 'of', 'the', 'light', 'higgsinos', 'at', 'two', 'future', 'ep', 'colliders', 'at', 'cern', 'lhec', 'and', 'fccehthe', 'light', 'higgsinos', 'will', 'be', 'produced', 'in', 'pair', 'through', 'weak', 'boson', 'fusion', 'with', 'controlled', 'background', 'at', 'these', 'colliders', 'we', 'find', 'the', 'higgsino', 'of', '95145gev', 'can', 'be', 'reached', 'at', '2sigma', 'level', 'at', 'the', 'future', 'lhecfcceh', 'with', 'a', 'luminosity', '3', 'textab1', 'respectively']] | [-0.05562624080790304, 0.21525832957378185, -0.05239380300018097, 0.16881395082831965, -0.055965336393618774, -0.18498833904128975, 0.01784597209121795, 0.3479743498818938, -0.2447184956305515, -0.2958288239530487, 0.0740943204415047, -0.3188069650521125, 0.057584154599943774, 0.17103043829650763, 0.054706131203659955, 0.09040032833278976, 0.10128906352991895, 0.009365413542513903, -0.027506255970008112, -0.26610110740371135, 0.2563412441371407, 0.11871606680548433, 0.22898449701919205, 0.14033703153920657, 0.04562450429381577, 0.03808119098219827, -0.031716767562701496, -0.1028538429786618, -0.03379466442217663, 0.09039269927404606, 0.2536283860392223, 0.11935786246402846, 0.1395274533599486, -0.32775852496727675, -0.11576242629718574, 0.20712086826231804, 0.1350767095586705, 0.0800540772538546, -0.08738020384170093, -0.29911348633764234, 0.1312857810535732, -0.19538855637595962, -0.08376936695533078, -0.0008125715119215105, -0.056682631338413565, -0.07771807199080254, -0.29845858136807013, 0.07255420791146054, -0.0678869001947564, 0.03271566786146534, 0.021774088152323585, -0.17957493935905483, -0.10965516467880178, -0.0273022546750531, 0.13035995156350788, 0.019339590651861988, 0.19358628178069184, -0.25433482365370486, -0.1800110510017486, 0.41422332209572627, -0.10361773927152329, -0.13160514620514963, 0.24583773061127073, -0.19276728593835854, -0.1526328134619647, 0.13342019199862043, 0.2626903272042794, 0.07080023116674382, -0.1729123731940511, 0.1549580054824655, 0.014768917458078075, 0.13923283376343376, 0.08037948536395897, 0.09854093357662246, 0.31282444369327816, 0.2504127924249782, 0.05749593409332797, 0.03644077183114838, -0.1416141227832484, -0.011507214413083703, -0.46866725761149985, -0.08816681151962005, -0.07736208474174723, -0.005757857925619263, -0.03751811255146399, -0.053407269188154465, 0.3636864283084439, 0.13574570603130354, 0.2681039308057829, -0.004122262841462013, 0.3241642808845816, 0.09099639694925096, 0.07865925658104529, 0.00570764932725942, 0.3913803145644723, 0.07350658987664935, 0.14611735222915004, -0.20776615949412217, 0.008093024995662487, 0.04204912968598995] |
1,802.0368 | RoadTracer: Automatic Extraction of Road Networks from Aerial Images | Mapping road networks is currently both expensive and labor-intensive.
High-resolution aerial imagery provides a promising avenue to automatically
infer a road network. Prior work uses convolutional neural networks (CNNs) to
detect which pixels belong to a road (segmentation), and then uses complex
post-processing heuristics to infer graph connectivity. We show that these
segmentation methods have high error rates because noisy CNN outputs are
difficult to correct. We propose RoadTracer, a new method to automatically
construct accurate road network maps from aerial images. RoadTracer uses an
iterative search process guided by a CNN-based decision function to derive the
road network graph directly from the output of the CNN. We compare our approach
with a segmentation method on fifteen cities, and find that at a 5% error rate,
RoadTracer correctly captures 45% more junctions across these cities.
| cs.CV | mapping road networks is currently both expensive and laborintensive highresolution aerial imagery provides a promising avenue to automatically infer a road network prior work uses convolutional neural networks cnns to detect which pixels belong to a road segmentation and then uses complex postprocessing heuristics to infer graph connectivity we show that these segmentation methods have high error rates because noisy cnn outputs are difficult to correct we propose roadtracer a new method to automatically construct accurate road network maps from aerial images roadtracer uses an iterative search process guided by a cnnbased decision function to derive the road network graph directly from the output of the cnn we compare our approach with a segmentation method on fifteen cities and find that at a 5 error rate roadtracer correctly captures 45 more junctions across these cities | [['mapping', 'road', 'networks', 'is', 'currently', 'both', 'expensive', 'and', 'laborintensive', 'highresolution', 'aerial', 'imagery', 'provides', 'a', 'promising', 'avenue', 'to', 'automatically', 'infer', 'a', 'road', 'network', 'prior', 'work', 'uses', 'convolutional', 'neural', 'networks', 'cnns', 'to', 'detect', 'which', 'pixels', 'belong', 'to', 'a', 'road', 'segmentation', 'and', 'then', 'uses', 'complex', 'postprocessing', 'heuristics', 'to', 'infer', 'graph', 'connectivity', 'we', 'show', 'that', 'these', 'segmentation', 'methods', 'have', 'high', 'error', 'rates', 'because', 'noisy', 'cnn', 'outputs', 'are', 'difficult', 'to', 'correct', 'we', 'propose', 'roadtracer', 'a', 'new', 'method', 'to', 'automatically', 'construct', 'accurate', 'road', 'network', 'maps', 'from', 'aerial', 'images', 'roadtracer', 'uses', 'an', 'iterative', 'search', 'process', 'guided', 'by', 'a', 'cnnbased', 'decision', 'function', 'to', 'derive', 'the', 'road', 'network', 'graph', 'directly', 'from', 'the', 'output', 'of', 'the', 'cnn', 'we', 'compare', 'our', 'approach', 'with', 'a', 'segmentation', 'method', 'on', 'fifteen', 'cities', 'and', 'find', 'that', 'at', 'a', '5', 'error', 'rate', 'roadtracer', 'correctly', 'captures', '45', 'more', 'junctions', 'across', 'these', 'cities']] | [-0.03673212047066988, -0.04355984112426759, -0.06803391102218517, 0.08611410444833315, -0.12968631759285926, -0.20032625564339537, 0.07278724338997293, 0.48529979854270267, -0.2533763353281689, -0.37073259238429646, 0.05369382963722779, -0.2546863042852945, -0.24344982208028712, 0.18577417218798978, -0.16378299102049182, 0.12237946338330706, 0.17542849048213274, 0.015400168396256589, -0.013151766354632046, -0.23440593249914754, 0.2668637768951831, 0.025585739762970693, 0.34516768013989485, -0.014022465966021021, 0.15329103834444174, -0.06711179987846494, -0.0685972369344974, -0.036814585147873946, -0.08101594247736675, 0.1982156910209192, 0.34238315900718724, 0.18660498848874812, 0.28959328195563067, -0.4529820766851858, -0.25248803187299657, 0.0945363724362795, 0.1449464493672605, 0.13429102630923606, 0.0313994416073439, -0.379016355763155, 0.12220162219126467, -0.14250833665244972, 0.022238499384925323, -0.13097227663146677, -0.01919974875377698, -0.024921234687617807, -0.31643597044188665, 0.01851745110212101, -0.02742863426381653, 0.03834385429336517, -0.0031931630922136483, -0.06927897233895405, -0.0003990515945824208, 0.21586047604473102, -0.04840703767538933, 0.1043591848195151, 0.17671257599291426, -0.16318577650796484, -0.11969245135163267, 0.328502993044202, -0.01305407446084751, -0.1859806333254609, 0.1861834327586823, -0.0057958025071356035, -0.1750425157275189, 0.1704790303638826, 0.24579050640006447, 0.11869578813375146, -0.19182937724722757, -0.07527862540403105, -0.04065737211904316, 0.1816220348942335, 0.05279930801372285, -0.05101606360188237, 0.18476207427404545, 0.26907704493927737, 0.11961916024598328, 0.13047073481914898, -0.22068437328540583, -0.006497115818611174, -0.1677526623148609, -0.09722265868902603, -0.18742780990346714, -0.002245490036525384, -0.1194057432034579, -0.16283435416752817, 0.40818228521729233, 0.27415690305470314, 0.21684609548085265, 0.17053214836826858, 0.37045549267765, -0.007870195505071294, 0.13561570976205445, 0.12753826883724995, 0.13981681526121165, 0.030883725128929923, 0.13535901920662985, -0.11562023234933062, 0.09654938795224384, 0.1035552294821375] |
1,802.03681 | On the boundary of the zero set of super-Brownian motion and its local
time | If $X(t,x)$ is the density of one-dimensional super-Brownian motion, we prove
that $\text{dim}(\partial\{x:X(t,x)>0\})=2-2\lambda_0\in(0,1)$ a.s. on
$\{X_t\neq 0\}$, where $-\lambda_0\in(-1,-1/2)$ is the lead eigenvalue of a
killed Ornstein-Uhlenbeck process. This confirms a conjecture of Mueller,
Mytnik and Perkins who proved the above with positive probability. To establish
this result we derive some new basic properties of a recently introduced
boundary local time and analyze the behaviour of $X(t,\cdot)$ near the upper
edge of its support. Numerical estimates of $\lambda_0$ suggest that the above
Hausdorff dimension is approximately $.224$.
| math.PR | if xtx is the density of onedimensional superbrownian motion we prove that textdimpartialxxtx022lambda_0in01 as on x_tneq 0 where lambda_0in112 is the lead eigenvalue of a killed ornsteinuhlenbeck process this confirms a conjecture of mueller mytnik and perkins who proved the above with positive probability to establish this result we derive some new basic properties of a recently introduced boundary local time and analyze the behaviour of xtcdot near the upper edge of its support numerical estimates of lambda_0 suggest that the above hausdorff dimension is approximately 224 | [['if', 'xtx', 'is', 'the', 'density', 'of', 'onedimensional', 'superbrownian', 'motion', 'we', 'prove', 'that', 'textdimpartialxxtx022lambda_0in01', 'as', 'on', 'x_tneq', '0', 'where', 'lambda_0in112', 'is', 'the', 'lead', 'eigenvalue', 'of', 'a', 'killed', 'ornsteinuhlenbeck', 'process', 'this', 'confirms', 'a', 'conjecture', 'of', 'mueller', 'mytnik', 'and', 'perkins', 'who', 'proved', 'the', 'above', 'with', 'positive', 'probability', 'to', 'establish', 'this', 'result', 'we', 'derive', 'some', 'new', 'basic', 'properties', 'of', 'a', 'recently', 'introduced', 'boundary', 'local', 'time', 'and', 'analyze', 'the', 'behaviour', 'of', 'xtcdot', 'near', 'the', 'upper', 'edge', 'of', 'its', 'support', 'numerical', 'estimates', 'of', 'lambda_0', 'suggest', 'that', 'the', 'above', 'hausdorff', 'dimension', 'is', 'approximately', '224']] | [-0.11032068766218733, 0.10479514864105058, -0.10128173577116735, 0.03285570913889037, -0.039060584359230044, -0.13007349821637912, 0.0568331324001662, 0.30726212632270106, -0.2451993096479585, -0.22427407420992132, 0.14778320381911583, -0.27375342360002, -0.16012215003909835, 0.16640112250875008, -0.08218965040104666, 0.06496022053621148, 0.03636169135121696, 0.07110929287162172, -0.006128459546086659, -0.23029139541448598, 0.31607876679893715, 0.036088001802114834, 0.21010019234381616, 0.09454130206301987, 0.11485212227239845, -0.005779556604663292, -0.037716573390391576, -0.0170618914942964, -0.20473404218115232, 0.10148523801780608, 0.18871927202022803, 0.07308968067651682, 0.30251932880246496, -0.34441399053636806, -0.19396350419721062, 0.12192828696871917, 0.11054300928645465, 0.024092053075486525, -0.012360329572840717, -0.3141487823372864, 0.15147999829699632, -0.10641796374132476, -0.26209394772907335, -0.018773373665220767, 0.0786159963021616, 0.03950514344790255, -0.31179198912199, 0.09879552801307964, 0.12680559183459683, 0.02053833015351444, -0.07643759148672268, -0.14414848944351796, -0.03682637737547777, 0.0859551671541756, 0.04781071784736375, 0.004343008447202842, 0.0795661595885653, -0.06440395383298936, -0.110472117965839, 0.2945903535562018, -0.0648654264633555, -0.15826056484435966, 0.165716990901449, -0.2126260932074882, -0.11790512476385717, 0.11198952676818134, 0.12483483672433768, 0.1247645245517144, -0.11976921988135002, 0.14559820477699256, -0.12205592152685017, 0.1066562633099545, 0.0975330822977675, -0.0027989833222993887, 0.10596163557415986, 0.1435299445874989, 0.147714599686484, 0.14247290417551994, -0.07019167380542102, -0.05009818368265966, -0.32634359122399825, -0.20208032434828668, -0.22665728217955813, 0.14016906359704234, -0.09759505383680148, -0.18028691108338535, 0.3465144899729864, 0.1645075397745493, 0.24680374594158436, 0.12279020145490586, 0.18844785636952932, 0.17948648984212967, -0.05592881452224879, 0.13299839365778557, 0.20154513609041572, 0.18755742080554547, 0.0687408528588039, -0.1842635836485908, 0.057805898750806786, 0.14062143141594546] |
1,802.03682 | Non-Equilibrium Strongly Hyperuniform Fluids of Circle Active Particles
with Large Local Density Fluctuations | Disordered hyperuniform structures are an exotic state of matter having
vanishing long-wavelength density fluctuations similar to perfect crystals but
without long-range order. Although its importance in materials science has been
brought to the fore in past decades, the rational design of experimentally
realizable disordered strongly hyperuniform microstructures remains
challenging. Here we find a new type of non-equilibrium fluid with strong
hyperuniformity in two-dimensional systems of chiral active particles, where
particles perform independent circular motions of the radius R with the same
handedness. This new hyperuniform fluid features a special length scale, i.e.,
the diameter of the circular trajectory of particles, below which large density
fluctuations are observed. By developing a dynamic mean-field theory, we show
that the large local density fluctuations can be explained as a
motility-induced microphase separation, while the Fickian diffusion at large
length scales and local center-of-mass-conserved noises are responsible for the
global hyperuniformity.
| cond-mat.soft | disordered hyperuniform structures are an exotic state of matter having vanishing longwavelength density fluctuations similar to perfect crystals but without longrange order although its importance in materials science has been brought to the fore in past decades the rational design of experimentally realizable disordered strongly hyperuniform microstructures remains challenging here we find a new type of nonequilibrium fluid with strong hyperuniformity in twodimensional systems of chiral active particles where particles perform independent circular motions of the radius r with the same handedness this new hyperuniform fluid features a special length scale ie the diameter of the circular trajectory of particles below which large density fluctuations are observed by developing a dynamic meanfield theory we show that the large local density fluctuations can be explained as a motilityinduced microphase separation while the fickian diffusion at large length scales and local centerofmassconserved noises are responsible for the global hyperuniformity | [['disordered', 'hyperuniform', 'structures', 'are', 'an', 'exotic', 'state', 'of', 'matter', 'having', 'vanishing', 'longwavelength', 'density', 'fluctuations', 'similar', 'to', 'perfect', 'crystals', 'but', 'without', 'longrange', 'order', 'although', 'its', 'importance', 'in', 'materials', 'science', 'has', 'been', 'brought', 'to', 'the', 'fore', 'in', 'past', 'decades', 'the', 'rational', 'design', 'of', 'experimentally', 'realizable', 'disordered', 'strongly', 'hyperuniform', 'microstructures', 'remains', 'challenging', 'here', 'we', 'find', 'a', 'new', 'type', 'of', 'nonequilibrium', 'fluid', 'with', 'strong', 'hyperuniformity', 'in', 'twodimensional', 'systems', 'of', 'chiral', 'active', 'particles', 'where', 'particles', 'perform', 'independent', 'circular', 'motions', 'of', 'the', 'radius', 'r', 'with', 'the', 'same', 'handedness', 'this', 'new', 'hyperuniform', 'fluid', 'features', 'a', 'special', 'length', 'scale', 'ie', 'the', 'diameter', 'of', 'the', 'circular', 'trajectory', 'of', 'particles', 'below', 'which', 'large', 'density', 'fluctuations', 'are', 'observed', 'by', 'developing', 'a', 'dynamic', 'meanfield', 'theory', 'we', 'show', 'that', 'the', 'large', 'local', 'density', 'fluctuations', 'can', 'be', 'explained', 'as', 'a', 'motilityinduced', 'microphase', 'separation', 'while', 'the', 'fickian', 'diffusion', 'at', 'large', 'length', 'scales', 'and', 'local', 'centerofmassconserved', 'noises', 'are', 'responsible', 'for', 'the', 'global', 'hyperuniformity']] | [-0.1768449346633781, 0.2802129030740566, -0.10004908589914135, 0.0411969783838698, -0.03628260249667482, -0.14134430603526074, -0.051551853825676265, 0.3447949072339712, -0.2896657110357734, -0.27250089433860697, 0.0454033638377776, -0.26434326131847263, -0.1397488174452893, 0.09906710825911531, 0.0120703017838261, 0.08682033482720526, -0.03185400642990453, -0.011870628216444221, -0.06650495994756356, -0.19362360504551548, 0.25680224665708534, 0.06055867349193113, 0.30450940362260714, 0.041334707458975585, 0.09006851993194998, -0.003041693972653314, 0.04018972963190395, 0.11830096069264086, -0.17715747189599015, 0.06046793933428365, 0.24584538559748292, -0.04388690307344292, 0.24087094963362363, -0.44920953552634135, -0.2826024006608848, 0.10111144588214077, 0.16244757596294918, 0.1471890289063744, -0.06861995506715922, -0.288645189746653, 0.07723141330842899, -0.1236735317881589, -0.19576987294697087, -0.08343704847925126, 0.07697906805687163, 0.06029200544604738, -0.21471017191971153, 0.15569370600382146, 0.07851634826670617, 0.06676359680060247, -0.03928995662773896, -0.08475080256713936, -0.02516161868578359, 0.0900008953399701, 0.028532557203019778, -0.01805994291598462, 0.18666416776289985, -0.17548945150497586, -0.09865220024550257, 0.39811274710379235, -0.027159517781636743, -0.14632850383370094, 0.21914228452178203, -0.17315756997463536, -0.11101734805660807, 0.21327164868923057, 0.18135013083021526, 0.09111933711252801, -0.12419184501448723, 0.06504599263290364, -0.06674846191731065, 0.21168140435275584, 0.044292075343809585, 0.07694861473681482, 0.29821076239650585, 0.19647561917432316, 0.07025683767717229, 0.11573351390519473, -0.09132853181435079, -0.13833210178434033, -0.2577657803433807, -0.11836287006416855, -0.227347432763303, 0.039986423824352454, -0.10687810224662328, -0.2104354866027628, 0.3421758021425762, 0.12476603397844385, 0.18219705000328384, 0.016628358166262968, 0.2355639561022032, 0.04515801863792697, 0.07267268238053338, 0.07959041763288416, 0.27239498564947956, 0.13809648039112862, 0.09254818769293033, -0.20076465063524265, 0.05938715067188166, 0.0021330341058847023] |
1,802.03683 | Abelian quotients of the categories of short exact sequences | We mainly investigate abelian quotients of the categories of short exact
sequences. The natural framework to consider the question is via identifying
quotients of morphism categories as modules categories. These ideas not only
can be used to recover the abelian quotients produced by cluster-tilting
subcategories of both exact categories and triangulated categories, but also
can be used to reach our goal. Let $(\mathcal{C},\mathcal{E})$ be an exact
category. We denote by $\mathcal{E}(\mathcal{C})$ the category of bounded
complexes whose objects are given by short exact sequences in $\mathcal{E}$ and
by $S\mathcal{E}(\mathcal{C})$ the full subcategory formed by split short exact
sequences. In general, $\mathcal{E}(\mathcal{C})$ is just an exact category,
but the quotient $\mathcal{E}(\mathcal{C})/[S\mathcal{E}(\mathcal{C})]$ turns
out to be abelian. In particular, if $(\mathcal{C},\mathcal{E})$ is Frobenius,
we present three equivalent abelian quotients of $\mathcal{E}(\mathcal{C})$ and
point out that the equivalences are actually given by left and right rotations.
The abelian quotient $\mathcal{E}(\mathcal{C})/[S\mathcal{E}(\mathcal{C})]$
admits some nice properties. We explicitly describe the abelian structure,
projective objects, injective objects and simple objects, which provide a new
viewpoint to understanding Hilton-Rees Theorem and Auslander-Reiten theory.
Furthermore, we present some analogous results both for $n$-exact versions and
for triangulated versions.
| math.RT math.RA | we mainly investigate abelian quotients of the categories of short exact sequences the natural framework to consider the question is via identifying quotients of morphism categories as modules categories these ideas not only can be used to recover the abelian quotients produced by clustertilting subcategories of both exact categories and triangulated categories but also can be used to reach our goal let mathcalcmathcale be an exact category we denote by mathcalemathcalc the category of bounded complexes whose objects are given by short exact sequences in mathcale and by smathcalemathcalc the full subcategory formed by split short exact sequences in general mathcalemathcalc is just an exact category but the quotient mathcalemathcalcsmathcalemathcalc turns out to be abelian in particular if mathcalcmathcale is frobenius we present three equivalent abelian quotients of mathcalemathcalc and point out that the equivalences are actually given by left and right rotations the abelian quotient mathcalemathcalcsmathcalemathcalc admits some nice properties we explicitly describe the abelian structure projective objects injective objects and simple objects which provide a new viewpoint to understanding hiltonrees theorem and auslanderreiten theory furthermore we present some analogous results both for nexact versions and for triangulated versions | [['we', 'mainly', 'investigate', 'abelian', 'quotients', 'of', 'the', 'categories', 'of', 'short', 'exact', 'sequences', 'the', 'natural', 'framework', 'to', 'consider', 'the', 'question', 'is', 'via', 'identifying', 'quotients', 'of', 'morphism', 'categories', 'as', 'modules', 'categories', 'these', 'ideas', 'not', 'only', 'can', 'be', 'used', 'to', 'recover', 'the', 'abelian', 'quotients', 'produced', 'by', 'clustertilting', 'subcategories', 'of', 'both', 'exact', 'categories', 'and', 'triangulated', 'categories', 'but', 'also', 'can', 'be', 'used', 'to', 'reach', 'our', 'goal', 'let', 'mathcalcmathcale', 'be', 'an', 'exact', 'category', 'we', 'denote', 'by', 'mathcalemathcalc', 'the', 'category', 'of', 'bounded', 'complexes', 'whose', 'objects', 'are', 'given', 'by', 'short', 'exact', 'sequences', 'in', 'mathcale', 'and', 'by', 'smathcalemathcalc', 'the', 'full', 'subcategory', 'formed', 'by', 'split', 'short', 'exact', 'sequences', 'in', 'general', 'mathcalemathcalc', 'is', 'just', 'an', 'exact', 'category', 'but', 'the', 'quotient', 'mathcalemathcalcsmathcalemathcalc', 'turns', 'out', 'to', 'be', 'abelian', 'in', 'particular', 'if', 'mathcalcmathcale', 'is', 'frobenius', 'we', 'present', 'three', 'equivalent', 'abelian', 'quotients', 'of', 'mathcalemathcalc', 'and', 'point', 'out', 'that', 'the', 'equivalences', 'are', 'actually', 'given', 'by', 'left', 'and', 'right', 'rotations', 'the', 'abelian', 'quotient', 'mathcalemathcalcsmathcalemathcalc', 'admits', 'some', 'nice', 'properties', 'we', 'explicitly', 'describe', 'the', 'abelian', 'structure', 'projective', 'objects', 'injective', 'objects', 'and', 'simple', 'objects', 'which', 'provide', 'a', 'new', 'viewpoint', 'to', 'understanding', 'hiltonrees', 'theorem', 'and', 'auslanderreiten', 'theory', 'furthermore', 'we', 'present', 'some', 'analogous', 'results', 'both', 'for', 'nexact', 'versions', 'and', 'for', 'triangulated', 'versions']] | [-0.11507500795977971, 0.06006777238351749, -0.0772602385340599, 0.149835206816719, -0.09452058589186078, -0.14820834938737174, -0.02683823461073541, 0.39836371741107396, -0.3786886900022466, -0.2233533161537101, 0.11358926100568766, -0.19267779192104886, -0.1107244361242059, 0.1786019693964952, -0.208157490037622, -0.09670551862287265, 0.08552804136002858, 0.09653849506851471, -0.05344352026041897, -0.29486565445599855, 0.4014122242994246, -0.024013173353347565, 0.22507600737635486, 0.03566756714836404, 0.11362941197860706, -0.011348638032007242, -0.02359722648817365, 0.043771149480455025, -0.15561799289645678, 0.11852481920880475, 0.3495937282224536, 0.08184103661727521, 0.16627755193653146, -0.39300362773925585, -0.08072705463173309, 0.2036217243500775, 0.15024262752887163, 0.048806810620746585, -0.022043395594703735, -0.3421859027847888, 0.1577013681845499, -0.2000462748911432, -0.08747401347594155, -0.11056703221934136, 0.08755761605276856, 0.03225722404757655, -0.22642545247486773, -0.0336751698765726, 0.10239585255609415, 0.09651229529070758, -0.09396256597697615, -0.06681293043776125, -0.05999244718627143, 0.12192545477701451, -0.017248726161372078, 0.0011233181933001165, 0.10299309569921705, -0.12317088808143331, -0.12564629234870525, 0.376604658952083, -0.039075880426593046, -0.2354251530887659, 0.1606158295330862, -0.10939622942262964, -0.12566062444019863, 0.13061752158557616, 0.01768626576860345, 0.19734963942669653, -0.07115670687660465, 0.16708290698889253, -0.1593821918371544, 0.08427214211867547, 0.10724387697810407, 0.0379616926960592, 0.1976104649284514, 0.09095832075478048, -0.007635943098394301, 0.18132165240459344, 0.025245893901834886, -0.03085135573341939, -0.33734934549698586, -0.12560610408188716, -0.055889979469269435, 0.13504141867639602, -0.06211039742214858, -0.14433483789694967, 0.38234458762591567, 0.11557282850750902, 0.17367205376766862, 0.14310824722664992, 0.2273763672239648, 0.03625881144781948, 0.04428975830688291, 0.04198980652376689, 0.12017264578432615, 0.22055923908958913, -0.08679310609686679, -0.06730060007483248, -0.011879989921781284, 0.23882676518335375] |
1,802.03684 | Ball Prolate Spheroidal Wave Functions In Arbitrary Dimensions | In this paper, we introduce the prolate spheroidal wave functions (PSWFs) of
real order $\alpha>-1$ on the unit ball in arbitrary dimension, termed as ball
PSWFs. They are eigenfunctions of both a weighted concentration integral
operator, and a Sturm-Liouville differential operator. Different from existing
works on multi-dimensional PSWFs, the ball PSWFs are defined as a
generalisation of orthogonal {\em ball polynomials} in primitive variables with
a tuning parameter $c>0$, through a "perturbation" of the Sturm-Liouville
equation of the ball polynomials. From this perspective, we can explore some
interesting intrinsic connections between the ball PSWFs and the finite Fourier
and Hankel transforms. We provide an efficient and accurate algorithm for
computing the ball PSWFs and the associated eigenvalues, and present various
numerical results to illustrate the efficiency of the method. Under this
uniform framework, we can recover the existing PSWFs by suitable variable
substitutions.
| math.NA | in this paper we introduce the prolate spheroidal wave functions pswfs of real order alpha1 on the unit ball in arbitrary dimension termed as ball pswfs they are eigenfunctions of both a weighted concentration integral operator and a sturmliouville differential operator different from existing works on multidimensional pswfs the ball pswfs are defined as a generalisation of orthogonal em ball polynomials in primitive variables with a tuning parameter c0 through a perturbation of the sturmliouville equation of the ball polynomials from this perspective we can explore some interesting intrinsic connections between the ball pswfs and the finite fourier and hankel transforms we provide an efficient and accurate algorithm for computing the ball pswfs and the associated eigenvalues and present various numerical results to illustrate the efficiency of the method under this uniform framework we can recover the existing pswfs by suitable variable substitutions | [['in', 'this', 'paper', 'we', 'introduce', 'the', 'prolate', 'spheroidal', 'wave', 'functions', 'pswfs', 'of', 'real', 'order', 'alpha1', 'on', 'the', 'unit', 'ball', 'in', 'arbitrary', 'dimension', 'termed', 'as', 'ball', 'pswfs', 'they', 'are', 'eigenfunctions', 'of', 'both', 'a', 'weighted', 'concentration', 'integral', 'operator', 'and', 'a', 'sturmliouville', 'differential', 'operator', 'different', 'from', 'existing', 'works', 'on', 'multidimensional', 'pswfs', 'the', 'ball', 'pswfs', 'are', 'defined', 'as', 'a', 'generalisation', 'of', 'orthogonal', 'em', 'ball', 'polynomials', 'in', 'primitive', 'variables', 'with', 'a', 'tuning', 'parameter', 'c0', 'through', 'a', 'perturbation', 'of', 'the', 'sturmliouville', 'equation', 'of', 'the', 'ball', 'polynomials', 'from', 'this', 'perspective', 'we', 'can', 'explore', 'some', 'interesting', 'intrinsic', 'connections', 'between', 'the', 'ball', 'pswfs', 'and', 'the', 'finite', 'fourier', 'and', 'hankel', 'transforms', 'we', 'provide', 'an', 'efficient', 'and', 'accurate', 'algorithm', 'for', 'computing', 'the', 'ball', 'pswfs', 'and', 'the', 'associated', 'eigenvalues', 'and', 'present', 'various', 'numerical', 'results', 'to', 'illustrate', 'the', 'efficiency', 'of', 'the', 'method', 'under', 'this', 'uniform', 'framework', 'we', 'can', 'recover', 'the', 'existing', 'pswfs', 'by', 'suitable', 'variable', 'substitutions']] | [-0.1274516283602851, 0.04088798842738444, -0.08517425119147434, 0.09718467833855274, -0.11375371574170211, -0.08525800505340413, -0.005744575536679607, 0.38696286906781313, -0.2781796187318705, -0.18835460287974692, 0.14504937123152317, -0.2961351978429756, -0.2061343022273736, 0.1919245342170442, -0.10190508091314272, 0.15534320702919593, 0.05303173630101072, 0.039852406582721815, -0.11971066500731073, -0.20649188498223942, 0.34742311509391227, 0.032189240714964956, 0.1981857555895601, 0.00015479691404567616, 0.08760991571405968, 0.01642122317326965, -0.041263351431832865, -0.027492132513308443, -0.1705706887129512, 0.15237576100923172, 0.25004415897248716, 0.12468162261542272, 0.3156658493876262, -0.4115316411105825, -0.16308252040583354, 0.12189491267049021, 0.19011575777011996, 0.0036543230119102693, -0.08320574252214934, -0.27946164765089127, 0.020840427180478623, -0.11912486387963792, -0.1865254256078954, -0.1212636132714814, 0.023457742364543094, 0.10887590468815574, -0.30866992312737485, 0.07359130034496734, 0.0707122833546173, 0.02554951569592984, -0.0909214812124122, -0.16980359422277425, 0.05216648878930202, 0.031257209090444334, 0.007802009282933248, 0.03937142067328356, 0.0899708638931592, -0.037519635396547145, -0.0755528570055128, 0.37650946785949846, -0.030037798336707056, -0.3064267606038105, 0.12057531145368736, -0.16495171478799694, -0.11351285355126524, 0.05680598413988531, 0.17844944675876337, 0.1476685449389832, -0.09072920403905682, 0.14582750742190184, -0.06372893515596137, 0.09543124979062305, 0.12833250037205596, 0.0287850179271512, 0.10522271431591752, 0.07064451246808928, 0.08757311997974253, 0.16636372761234278, -0.03891390342944321, -0.1130921236382654, -0.31862871481717886, -0.19181623034107165, -0.2434896998680555, 0.0075330038304022235, -0.17381586474012356, -0.22168649294758802, 0.3932794387146205, 0.05530598356186614, 0.21134685381752003, 0.0764390896172165, 0.2557099972089583, 0.16428530291602067, 0.0325038075460108, 0.04583404337583514, 0.13971988253488363, 0.16007974054957447, 0.08992464178228764, -0.182865150725482, -0.003535474458435824, 0.1594361174929809] |
1,802.03685 | Learning a SAT Solver from Single-Bit Supervision | We present NeuroSAT, a message passing neural network that learns to solve
SAT problems after only being trained as a classifier to predict
satisfiability. Although it is not competitive with state-of-the-art SAT
solvers, NeuroSAT can solve problems that are substantially larger and more
difficult than it ever saw during training by simply running for more
iterations. Moreover, NeuroSAT generalizes to novel distributions; after
training only on random SAT problems, at test time it can solve SAT problems
encoding graph coloring, clique detection, dominating set, and vertex cover
problems, all on a range of distributions over small random graphs.
| cs.AI cs.LG cs.LO | we present neurosat a message passing neural network that learns to solve sat problems after only being trained as a classifier to predict satisfiability although it is not competitive with stateoftheart sat solvers neurosat can solve problems that are substantially larger and more difficult than it ever saw during training by simply running for more iterations moreover neurosat generalizes to novel distributions after training only on random sat problems at test time it can solve sat problems encoding graph coloring clique detection dominating set and vertex cover problems all on a range of distributions over small random graphs | [['we', 'present', 'neurosat', 'a', 'message', 'passing', 'neural', 'network', 'that', 'learns', 'to', 'solve', 'sat', 'problems', 'after', 'only', 'being', 'trained', 'as', 'a', 'classifier', 'to', 'predict', 'satisfiability', 'although', 'it', 'is', 'not', 'competitive', 'with', 'stateoftheart', 'sat', 'solvers', 'neurosat', 'can', 'solve', 'problems', 'that', 'are', 'substantially', 'larger', 'and', 'more', 'difficult', 'than', 'it', 'ever', 'saw', 'during', 'training', 'by', 'simply', 'running', 'for', 'more', 'iterations', 'moreover', 'neurosat', 'generalizes', 'to', 'novel', 'distributions', 'after', 'training', 'only', 'on', 'random', 'sat', 'problems', 'at', 'test', 'time', 'it', 'can', 'solve', 'sat', 'problems', 'encoding', 'graph', 'coloring', 'clique', 'detection', 'dominating', 'set', 'and', 'vertex', 'cover', 'problems', 'all', 'on', 'a', 'range', 'of', 'distributions', 'over', 'small', 'random', 'graphs']] | [-0.04005739712203872, 0.05979606405622801, -0.04901505396131198, 0.09790676134301121, -0.1751104679139217, -0.26716805622456785, 0.053745348783380976, 0.4426599552436751, -0.3078217253395432, -0.38138588160580517, 0.11836664507887801, -0.27587614073037947, -0.10761640258893675, 0.22682587071057594, -0.10186618247677628, 0.10114175373954433, 0.1922173295075036, 0.0230205236953132, -0.07552621601510565, -0.36244597044275667, 0.2473041101867257, -0.02786520346333938, 0.2267959657771399, 0.02837533211544612, 0.12342485352134218, -0.0030588313452519326, 0.03629954557388318, 0.0806971078165997, -0.017386009408979514, 0.03995986748486757, 0.3450113360613242, 0.24478931680359706, 0.3325561557763389, -0.43610097473601295, -0.20042047469059424, 0.17112033364686127, 0.14407217163088903, 0.11701395733422143, 0.05040005399525992, -0.26073490121230786, 0.13448821965186875, -0.1075574868045063, 0.050305728249403894, -0.09449705260102542, 0.05490248344306435, -0.033043719282877464, -0.25760217210306424, -0.013088417790678084, 0.04861787240001924, -0.026341463973726695, 0.044818666407230257, -0.16247735778463776, 0.06453510529803569, 0.025092249762323895, -0.010061449487693608, 0.08125900043820848, 0.1130134649812339, -0.17452533280700255, -0.17613943719438144, 0.3759478510984657, -0.0006397748052686624, -0.16625956355651117, 0.1436617559781868, 0.008160570146972123, -0.17677671947440474, 0.1525546891557775, 0.23912711929986064, 0.18963776635272162, -0.12474940801324437, 0.026386727466086418, -0.09974428705338921, 0.22297307952159864, 0.11977355413576019, -0.10092888653696495, 0.1107171187236696, 0.2176420143305779, 0.16879619061186604, 0.16374458202484007, -0.01923245906696788, -0.08602668885236645, -0.1983584578681205, -0.027225873395040328, -0.22373566208336007, -0.01437147351903057, -0.15796885405143257, -0.17294045867236826, 0.3908072815737592, 0.22685144467716467, 0.14640698132665866, 0.20647881263676954, 0.2964522680077626, 0.08920263803141709, 0.1342650077214265, 0.16658639032108596, 0.14364223396975775, 0.09241400694008917, 0.09568084993432942, -0.14005017773561865, 0.1411192664729279, 0.08331677730774925] |
1,802.03686 | Physical renormalization condition for de Sitter QED | We considered a new renormalization condition for the vacuum expectation
values of the scalar and spinor currents induced by a homogeneous and constant
electric field background in de Sitter spacetime. Following a semiclassical
argument, the condition named maximal subtraction imposes the exponential
suppression on the massive charged particle limit of the renormalized currents.
The maximal subtraction changes the behaviors of the induced currents
previously obtained by the conventional minimal subtraction scheme. The maximal
subtraction is favored for a couple of physically decent predictions including
the identical asymptotic behavior of the scalar and spinor currents, the
removal of the infrared (IR) hyperconductivity from the scalar current, and the
finite current for the massless fermion.
| gr-qc hep-th | we considered a new renormalization condition for the vacuum expectation values of the scalar and spinor currents induced by a homogeneous and constant electric field background in de sitter spacetime following a semiclassical argument the condition named maximal subtraction imposes the exponential suppression on the massive charged particle limit of the renormalized currents the maximal subtraction changes the behaviors of the induced currents previously obtained by the conventional minimal subtraction scheme the maximal subtraction is favored for a couple of physically decent predictions including the identical asymptotic behavior of the scalar and spinor currents the removal of the infrared ir hyperconductivity from the scalar current and the finite current for the massless fermion | [['we', 'considered', 'a', 'new', 'renormalization', 'condition', 'for', 'the', 'vacuum', 'expectation', 'values', 'of', 'the', 'scalar', 'and', 'spinor', 'currents', 'induced', 'by', 'a', 'homogeneous', 'and', 'constant', 'electric', 'field', 'background', 'in', 'de', 'sitter', 'spacetime', 'following', 'a', 'semiclassical', 'argument', 'the', 'condition', 'named', 'maximal', 'subtraction', 'imposes', 'the', 'exponential', 'suppression', 'on', 'the', 'massive', 'charged', 'particle', 'limit', 'of', 'the', 'renormalized', 'currents', 'the', 'maximal', 'subtraction', 'changes', 'the', 'behaviors', 'of', 'the', 'induced', 'currents', 'previously', 'obtained', 'by', 'the', 'conventional', 'minimal', 'subtraction', 'scheme', 'the', 'maximal', 'subtraction', 'is', 'favored', 'for', 'a', 'couple', 'of', 'physically', 'decent', 'predictions', 'including', 'the', 'identical', 'asymptotic', 'behavior', 'of', 'the', 'scalar', 'and', 'spinor', 'currents', 'the', 'removal', 'of', 'the', 'infrared', 'ir', 'hyperconductivity', 'from', 'the', 'scalar', 'current', 'and', 'the', 'finite', 'current', 'for', 'the', 'massless', 'fermion']] | [-0.17884222775557598, 0.21359110179365473, -0.07536710977999378, 0.09050677474938432, -0.05203424043030338, -0.11458314111274956, 0.01677059006580539, 0.2718035160992459, -0.15341906044405548, -0.24746265030770967, 0.05183586115903526, -0.2540585697274161, -0.08737525912990744, 0.13342328341904433, 0.0022940892536621707, 0.05157434543405672, -0.01470812409704106, 0.05781467894372423, -0.08243278034888538, -0.20454573728230707, 0.3537768735776993, 0.043470238986532246, 0.32728143572082036, 0.0639282741446864, 0.13979563508100346, 0.0288148591402028, -0.06825090442429733, 0.016851318365506893, -0.10269758245388491, 0.07449314222147996, 0.13062184620483785, 0.04397430019535586, 0.1657785226671289, -0.389613954877827, -0.19797231119323885, 0.13464393469595673, 0.11844430782263522, 0.1376488650077542, -0.06569303746594825, -0.29696662351489067, 0.06068779955890063, -0.1546145725327717, -0.20511832970309904, -0.05713320753240414, -0.036492152194146366, -0.06521806769707628, -0.3176446372016737, 0.1062403968246901, 0.03319606503504699, 0.018118919439992942, -0.0792591178468305, -0.11042010437993877, -0.04566880255377134, 0.05879560671746731, 0.09968610154670886, 0.02884829730728839, 0.17437440278091, -0.21372200324472074, -0.11678879185419003, 0.3137588006798672, -0.17819214087655455, -0.22960648126076016, 0.10585345205463535, -0.1461499117693938, -0.05931829384206671, 0.14730274717249306, 0.04417629238110926, 0.15864040298321475, -0.16839498843569145, 0.18952259511802247, 0.0028306721314062585, 0.06750411161971567, 0.1290799950175317, 0.06599636872472094, 0.2313741551572045, 0.06246349890510329, 0.056366689981216876, 0.10899613875137494, -0.05014254728257986, -0.12417692455372452, -0.3948943125850529, -0.12929716390615278, -0.1339439470650612, 0.10662163777145005, -0.1508452528711631, -0.20420838079613066, 0.42262873355931146, 0.10879011616209704, 0.1621290581729428, 0.006706486472579758, 0.3245024198142861, 0.15040891118908087, 0.08859595134895526, 0.06426430207107214, 0.2921929543598893, 0.1490669134567467, 0.10929178692960898, -0.31632936405496, -0.058563544662191276, 0.10725437260368856] |
1,802.03687 | Computation of Transmission Eigenvalues for Elastic Waves | The goal of this paper is to develop numerical methods computing a few
smallest elasticity transmission eigenvalues, which are of practical importance
in inverse scattering theory. The problem is challenging since it is nonlinear,
non-self-adjoint, and of fourth order. We construct a nonlinear function whose
values are generalized eigenvalues of a series of self-adjoint fourth order
problems. The roots of the function are the transmission eigenvalues. Using an
$H^2$-conforming finite element for the self-adjoint fourth order eigenvalue
problems, we employ a secant method to compute the roots of the nonlinear
function. The convergence of the proposed method is proved. In addition, a
mixed finite element method is developed for the purpose of verification.
Numerical examples are presented to verify the theory and demonstrate the
effectiveness of the two methods.
| math.NA | the goal of this paper is to develop numerical methods computing a few smallest elasticity transmission eigenvalues which are of practical importance in inverse scattering theory the problem is challenging since it is nonlinear nonselfadjoint and of fourth order we construct a nonlinear function whose values are generalized eigenvalues of a series of selfadjoint fourth order problems the roots of the function are the transmission eigenvalues using an h2conforming finite element for the selfadjoint fourth order eigenvalue problems we employ a secant method to compute the roots of the nonlinear function the convergence of the proposed method is proved in addition a mixed finite element method is developed for the purpose of verification numerical examples are presented to verify the theory and demonstrate the effectiveness of the two methods | [['the', 'goal', 'of', 'this', 'paper', 'is', 'to', 'develop', 'numerical', 'methods', 'computing', 'a', 'few', 'smallest', 'elasticity', 'transmission', 'eigenvalues', 'which', 'are', 'of', 'practical', 'importance', 'in', 'inverse', 'scattering', 'theory', 'the', 'problem', 'is', 'challenging', 'since', 'it', 'is', 'nonlinear', 'nonselfadjoint', 'and', 'of', 'fourth', 'order', 'we', 'construct', 'a', 'nonlinear', 'function', 'whose', 'values', 'are', 'generalized', 'eigenvalues', 'of', 'a', 'series', 'of', 'selfadjoint', 'fourth', 'order', 'problems', 'the', 'roots', 'of', 'the', 'function', 'are', 'the', 'transmission', 'eigenvalues', 'using', 'an', 'h2conforming', 'finite', 'element', 'for', 'the', 'selfadjoint', 'fourth', 'order', 'eigenvalue', 'problems', 'we', 'employ', 'a', 'secant', 'method', 'to', 'compute', 'the', 'roots', 'of', 'the', 'nonlinear', 'function', 'the', 'convergence', 'of', 'the', 'proposed', 'method', 'is', 'proved', 'in', 'addition', 'a', 'mixed', 'finite', 'element', 'method', 'is', 'developed', 'for', 'the', 'purpose', 'of', 'verification', 'numerical', 'examples', 'are', 'presented', 'to', 'verify', 'the', 'theory', 'and', 'demonstrate', 'the', 'effectiveness', 'of', 'the', 'two', 'methods']] | [-0.11204072881432235, 0.01278764664751835, -0.07320015113656372, 0.047195269663045686, -0.08530922079559906, -0.08112306236253344, -0.050311404583585816, 0.325191286991733, -0.2985301463568742, -0.2382155769872804, 0.14672231061434618, -0.308206734030919, -0.1960985920745735, 0.19761026826463352, -0.037306132408710876, 0.16000804246158262, 0.057824840041801565, 0.05709663598415579, -0.08085477147106976, -0.264251699772223, 0.3416139033168208, -0.010314192934243311, 0.2410182657980093, 0.08416599358699119, 0.11384441023114925, -0.04955985669458155, -0.030815735838354327, -0.005031958872149157, -0.0960828265438737, 0.17032304736009488, 0.3040911398680029, 0.08542830258781134, 0.34837692964446637, -0.37204822217829003, -0.1733758290525699, 0.142360200925889, 0.12197810269679239, 0.09560717116272467, -0.03194003698574884, -0.2206675483188195, 0.14149849922504537, -0.16806300588009893, -0.18360996911980848, -0.09041842095221775, -0.0035785103159010874, 0.01924450871671817, -0.33349979811802855, 0.07264239586124471, 0.016803971605462042, 0.055318179533116574, -0.03684269335092038, -0.12537834005675805, 0.04813702999390373, 0.0884403499283705, 0.01562841595222726, -0.09809637350001366, 0.02394488251356538, -0.048115191141923155, -0.1162490137859948, 0.40524426626777926, -0.01775317896760336, -0.2501914432315632, 0.11746161098252664, -0.12535053661793413, -0.09205749329150648, 0.12565030724301127, 0.17759493449630664, 0.2118921984535779, -0.11773475289593863, 0.1295012493334465, -0.03634863645343702, 0.13788693520247705, 0.031133237511439378, -0.0508482676259307, 0.10834343410855116, 0.15076422500748968, 0.09577733872082922, 0.14478223586036254, -0.03987408556448397, -0.09953835964664932, -0.3390328752151293, -0.15596064032134851, -0.24955922600546088, -0.016245780173371468, -0.09733247887248411, -0.2194465893905523, 0.4433997969410216, 0.16513225813071394, 0.14018511128893427, 0.07223291213663886, 0.3024451222050531, 0.22596316023679205, 0.014828224139389142, 0.039744952163226314, 0.19955261768195634, 0.22532021750825956, 0.07051050114308217, -0.25397456650687167, 0.019867365192549752, 0.16804506198698005] |
1,802.03688 | On the Rates of Convergence from Surrogate Risk Minimizers to the Bayes
Optimal Classifier | We study the rates of convergence from empirical surrogate risk minimizers to
the Bayes optimal classifier. Specifically, we introduce the notion of
\emph{consistency intensity} to characterize a surrogate loss function and
exploit this notion to obtain the rate of convergence from an empirical
surrogate risk minimizer to the Bayes optimal classifier, enabling fair
comparisons of the excess risks of different surrogate risk minimizers. The
main result of the paper has practical implications including (1) showing that
hinge loss is superior to logistic and exponential loss in the sense that its
empirical minimizer converges faster to the Bayes optimal classifier and (2)
guiding to modify surrogate loss functions to accelerate the convergence to the
Bayes optimal classifier.
| stat.ML cs.LG | we study the rates of convergence from empirical surrogate risk minimizers to the bayes optimal classifier specifically we introduce the notion of emphconsistency intensity to characterize a surrogate loss function and exploit this notion to obtain the rate of convergence from an empirical surrogate risk minimizer to the bayes optimal classifier enabling fair comparisons of the excess risks of different surrogate risk minimizers the main result of the paper has practical implications including 1 showing that hinge loss is superior to logistic and exponential loss in the sense that its empirical minimizer converges faster to the bayes optimal classifier and 2 guiding to modify surrogate loss functions to accelerate the convergence to the bayes optimal classifier | [['we', 'study', 'the', 'rates', 'of', 'convergence', 'from', 'empirical', 'surrogate', 'risk', 'minimizers', 'to', 'the', 'bayes', 'optimal', 'classifier', 'specifically', 'we', 'introduce', 'the', 'notion', 'of', 'emphconsistency', 'intensity', 'to', 'characterize', 'a', 'surrogate', 'loss', 'function', 'and', 'exploit', 'this', 'notion', 'to', 'obtain', 'the', 'rate', 'of', 'convergence', 'from', 'an', 'empirical', 'surrogate', 'risk', 'minimizer', 'to', 'the', 'bayes', 'optimal', 'classifier', 'enabling', 'fair', 'comparisons', 'of', 'the', 'excess', 'risks', 'of', 'different', 'surrogate', 'risk', 'minimizers', 'the', 'main', 'result', 'of', 'the', 'paper', 'has', 'practical', 'implications', 'including', '1', 'showing', 'that', 'hinge', 'loss', 'is', 'superior', 'to', 'logistic', 'and', 'exponential', 'loss', 'in', 'the', 'sense', 'that', 'its', 'empirical', 'minimizer', 'converges', 'faster', 'to', 'the', 'bayes', 'optimal', 'classifier', 'and', '2', 'guiding', 'to', 'modify', 'surrogate', 'loss', 'functions', 'to', 'accelerate', 'the', 'convergence', 'to', 'the', 'bayes', 'optimal', 'classifier']] | [0.0108506108698403, -0.07504812075145811, -0.12746793934111966, 0.20042251816103718, -0.07504432047476414, -0.13474857290917686, 0.16495914891029, 0.42319220291643306, -0.33800244744834973, -0.24343589587179254, 0.08415351456717653, -0.3087884682021907, -0.17354566001750785, 0.14704923491256616, -0.17419233432457107, 0.18949368178537357, 0.07497481207748682, 0.011268676808585638, -0.08854827193687831, -0.3035017778235889, 0.30982539976208373, 0.13159411373259178, 0.33858831346653206, 0.025715554438146025, 0.12403754415472262, -0.006065214994154742, 0.052650504781671895, -0.04777398130631652, -0.1554023272219638, 0.20972082561989924, 0.25662905348721765, 0.23832770623266697, 0.45473018088297723, -0.32662304836036316, -0.16543647753684942, 0.18875424309376757, 0.11064184978925462, 0.03346926416069719, -0.003865097452693715, -0.19620938384544168, 0.07796683936010532, -0.18314769360686428, -0.11058498040074483, -0.15249539773403425, -0.08444911079503323, 0.10462185373361191, -0.3953260234516949, 0.1092702348491755, 0.06621514617240634, 0.043732028916189124, -0.10434183583731346, -0.13617752207812436, -0.025639672249812503, 0.09182969428165334, 0.15958121095197916, 0.0832142702119168, 0.1560678366202347, -0.11012201258262362, -0.12948196210521112, 0.279509913336871, -0.09194863913580775, -0.20976156659087103, 0.1668204265678751, -0.08909985525051839, -0.06511728088210883, 0.12644515807726842, 0.26906891025056867, 0.07018271213445555, -0.19288023898141168, -0.01808317156321899, -0.009924019767164156, 0.11529993638396263, 0.05121328735499289, -0.00964176474572641, 0.05079986713826656, 0.20135192921112194, 0.17131996271463917, 0.20580414830353752, -0.09841803510689401, -0.1072225618609709, -0.2997563370937032, -0.1377026139806699, -0.20083336011057012, 0.05290738455268779, -0.16492419574645062, -0.19995103395897254, 0.34530953481664944, 0.19002191027915427, 0.19037135571225322, 0.19719183518840322, 0.28388106580502515, 0.11004603943980203, 0.04086573075519168, 0.13136309303928131, 0.2722474664192775, 0.07958108006278053, -0.027548182205746657, -0.22295570849633678, 0.14582723822316218, 0.0856063265738816] |
1,802.03689 | Dual Control Memory Augmented Neural Networks for Treatment
Recommendations | Machine-assisted treatment recommendations hold a promise to reduce physician
time and decision errors. We formulate the task as a sequence-to-sequence
prediction model that takes the entire time-ordered medical history as input,
and predicts a sequence of future clinical procedures and medications. It is
built on the premise that an effective treatment plan may have long-term
dependencies from previous medical history. We approach the problem by using a
memory-augmented neural network, in particular, by leveraging the recent
differentiable neural computer that consists of a neural controller and an
external memory module. But differing from the original model, we use dual
controllers, one for encoding the history followed by another for decoding the
treatment sequences. In the encoding phase, the memory is updated as new input
is read; at the end of this phase, the memory holds not only the medical
history but also the information about the current illness. During the decoding
phase, the memory is write-protected. The decoding controller generates a
treatment sequence, one treatment option at a time. The resulting dual
controller write-protected memory-augmented neural network is demonstrated on
the MIMIC-III dataset on two tasks: procedure prediction and medication
prescription. The results show improved performance over both traditional
bag-of-words and sequence-to-sequence methods.
| cs.LG stat.ML | machineassisted treatment recommendations hold a promise to reduce physician time and decision errors we formulate the task as a sequencetosequence prediction model that takes the entire timeordered medical history as input and predicts a sequence of future clinical procedures and medications it is built on the premise that an effective treatment plan may have longterm dependencies from previous medical history we approach the problem by using a memoryaugmented neural network in particular by leveraging the recent differentiable neural computer that consists of a neural controller and an external memory module but differing from the original model we use dual controllers one for encoding the history followed by another for decoding the treatment sequences in the encoding phase the memory is updated as new input is read at the end of this phase the memory holds not only the medical history but also the information about the current illness during the decoding phase the memory is writeprotected the decoding controller generates a treatment sequence one treatment option at a time the resulting dual controller writeprotected memoryaugmented neural network is demonstrated on the mimiciii dataset on two tasks procedure prediction and medication prescription the results show improved performance over both traditional bagofwords and sequencetosequence methods | [['machineassisted', 'treatment', 'recommendations', 'hold', 'a', 'promise', 'to', 'reduce', 'physician', 'time', 'and', 'decision', 'errors', 'we', 'formulate', 'the', 'task', 'as', 'a', 'sequencetosequence', 'prediction', 'model', 'that', 'takes', 'the', 'entire', 'timeordered', 'medical', 'history', 'as', 'input', 'and', 'predicts', 'a', 'sequence', 'of', 'future', 'clinical', 'procedures', 'and', 'medications', 'it', 'is', 'built', 'on', 'the', 'premise', 'that', 'an', 'effective', 'treatment', 'plan', 'may', 'have', 'longterm', 'dependencies', 'from', 'previous', 'medical', 'history', 'we', 'approach', 'the', 'problem', 'by', 'using', 'a', 'memoryaugmented', 'neural', 'network', 'in', 'particular', 'by', 'leveraging', 'the', 'recent', 'differentiable', 'neural', 'computer', 'that', 'consists', 'of', 'a', 'neural', 'controller', 'and', 'an', 'external', 'memory', 'module', 'but', 'differing', 'from', 'the', 'original', 'model', 'we', 'use', 'dual', 'controllers', 'one', 'for', 'encoding', 'the', 'history', 'followed', 'by', 'another', 'for', 'decoding', 'the', 'treatment', 'sequences', 'in', 'the', 'encoding', 'phase', 'the', 'memory', 'is', 'updated', 'as', 'new', 'input', 'is', 'read', 'at', 'the', 'end', 'of', 'this', 'phase', 'the', 'memory', 'holds', 'not', 'only', 'the', 'medical', 'history', 'but', 'also', 'the', 'information', 'about', 'the', 'current', 'illness', 'during', 'the', 'decoding', 'phase', 'the', 'memory', 'is', 'writeprotected', 'the', 'decoding', 'controller', 'generates', 'a', 'treatment', 'sequence', 'one', 'treatment', 'option', 'at', 'a', 'time', 'the', 'resulting', 'dual', 'controller', 'writeprotected', 'memoryaugmented', 'neural', 'network', 'is', 'demonstrated', 'on', 'the', 'mimiciii', 'dataset', 'on', 'two', 'tasks', 'procedure', 'prediction', 'and', 'medication', 'prescription', 'the', 'results', 'show', 'improved', 'performance', 'over', 'both', 'traditional', 'bagofwords', 'and', 'sequencetosequence', 'methods']] | [-0.07203885435076256, 0.03080405362923584, -0.08373950702697956, 0.07043525142098543, -0.11093958002042595, -0.1748333185764369, 0.07084322637956351, 0.432240497981533, -0.2679794586396643, -0.2923677090275574, 0.12781340450053033, -0.23578873662601496, -0.18418380349250557, 0.2104914809962542, -0.1412158155793168, 0.07036226607911894, 0.1294317019867064, 0.07889435034970124, -0.04560030850104694, -0.30358882004388243, 0.24759085024729957, 0.07702239670474174, 0.3256733509519234, -0.018308955087014498, 0.14142272474985165, 0.04404344761932241, -0.03928167978760424, -0.04378824561187456, -0.038144978849850124, 0.09371205292191366, 0.2800319350377331, 0.22407913618500855, 0.3465131245452562, -0.4576561263592666, -0.2489034139041977, 0.05495432878384513, 0.0960742032999549, 0.1447497608479608, -0.028508219900632764, -0.2823154133230705, 0.059027933082921806, -0.20570722555746254, 0.015371434239147625, -0.07642262405945273, -0.017831735615733223, -0.04583684540310131, -0.29946617971362516, 0.02756102835522102, 0.08331708788981872, 0.03323045934967954, -0.08511788042473235, -0.10705658179372916, 0.0061552013577939255, 0.18471565947000837, 0.015708564406747155, 0.11349691472330539, 0.15221617360980125, -0.16915143582524889, -0.15477011491328918, 0.31973599934299, -0.017496769120366188, -0.17732607998158048, 0.1357931762562693, -0.032284808661696945, -0.13673744802110888, 0.08987155962784733, 0.18692360476251196, 0.08565470108761236, -0.18598808704879996, 0.02908402425982517, 0.0024434456652204684, 0.2027516163107962, 0.04355419202354448, -0.010000916099258392, 0.19603730423096108, 0.2525994978037094, -0.001664863909672707, 0.1294739069153321, -0.08343286147877904, -0.09604493304261286, -0.24901015644553554, -0.11005155924762705, -0.15076724617865872, 0.000725331205918839, -0.09693216210133121, -0.14699691084667746, 0.41394731551729913, 0.20714429064178977, 0.15013903386551392, 0.13023030552370796, 0.3513627574673574, 0.06128496885141404, 0.12239593738292028, 0.06602925441332226, 0.13570823463533313, 0.038577273748402155, 0.1552714834630884, -0.218598436993166, 0.1544864894323317, 0.0840214494308411] |
1,802.0369 | On the Generalization of Equivariance and Convolution in Neural Networks
to the Action of Compact Groups | Convolutional neural networks have been extremely successful in the image
recognition domain because they ensure equivariance to translations. There have
been many recent attempts to generalize this framework to other domains,
including graphs and data lying on manifolds. In this paper we give a rigorous,
theoretical treatment of convolution and equivariance in neural networks with
respect to not just translations, but the action of any compact group. Our main
result is to prove that (given some natural constraints) convolutional
structure is not just a sufficient, but also a necessary condition for
equivariance to the action of a compact group. Our exposition makes use of
concepts from representation theory and noncommutative harmonic analysis and
derives new generalized convolution formulae.
| stat.ML cs.LG | convolutional neural networks have been extremely successful in the image recognition domain because they ensure equivariance to translations there have been many recent attempts to generalize this framework to other domains including graphs and data lying on manifolds in this paper we give a rigorous theoretical treatment of convolution and equivariance in neural networks with respect to not just translations but the action of any compact group our main result is to prove that given some natural constraints convolutional structure is not just a sufficient but also a necessary condition for equivariance to the action of a compact group our exposition makes use of concepts from representation theory and noncommutative harmonic analysis and derives new generalized convolution formulae | [['convolutional', 'neural', 'networks', 'have', 'been', 'extremely', 'successful', 'in', 'the', 'image', 'recognition', 'domain', 'because', 'they', 'ensure', 'equivariance', 'to', 'translations', 'there', 'have', 'been', 'many', 'recent', 'attempts', 'to', 'generalize', 'this', 'framework', 'to', 'other', 'domains', 'including', 'graphs', 'and', 'data', 'lying', 'on', 'manifolds', 'in', 'this', 'paper', 'we', 'give', 'a', 'rigorous', 'theoretical', 'treatment', 'of', 'convolution', 'and', 'equivariance', 'in', 'neural', 'networks', 'with', 'respect', 'to', 'not', 'just', 'translations', 'but', 'the', 'action', 'of', 'any', 'compact', 'group', 'our', 'main', 'result', 'is', 'to', 'prove', 'that', 'given', 'some', 'natural', 'constraints', 'convolutional', 'structure', 'is', 'not', 'just', 'a', 'sufficient', 'but', 'also', 'a', 'necessary', 'condition', 'for', 'equivariance', 'to', 'the', 'action', 'of', 'a', 'compact', 'group', 'our', 'exposition', 'makes', 'use', 'of', 'concepts', 'from', 'representation', 'theory', 'and', 'noncommutative', 'harmonic', 'analysis', 'and', 'derives', 'new', 'generalized', 'convolution', 'formulae']] | [-0.07903597729627863, 0.02934677055100881, -0.11176979272642125, 0.07851839919921831, -0.16429124666788317, -0.14477883137257422, -0.008608374801874792, 0.4551650313976205, -0.26188245230212304, -0.2618659689881389, 0.13632801554453858, -0.21167683777383575, -0.21963401903571972, 0.18300040452188607, -0.18506916719725577, 0.06679920564105703, 0.10764117518802947, 0.08946518051848447, -0.10828429561944962, -0.2580043714783565, 0.3476163614620218, 0.013661039743564581, 0.28731284553769154, 0.06667927919958039, 0.1299131610835271, -0.058234119823328774, -0.0452995303864354, -0.028439637632661705, -0.08470354610650802, 0.17994730971690456, 0.2737702771674021, 0.13902204570368373, 0.2800633996484359, -0.46135331933402407, -0.24293759142806343, 0.12369203081520243, 0.11216898356027649, 0.12788495240669887, -0.04046426434859128, -0.31460667021130606, 0.12006123189940669, -0.16399216015381202, -0.07051864838606473, -0.16272113460384435, 0.034532577048008474, -0.00710614249741627, -0.2488411904092665, -0.00838240647863131, 0.16306354647691726, 0.09267740822949652, -0.05764507574929019, -0.07326379738811215, 0.025129843921542674, 0.14614896175956701, 0.03784747547627884, 0.08282430090752067, 0.07470068323299668, -0.13425189160773435, -0.09992307638433778, 0.3822501419206797, -0.021598388022601098, -0.2506494055269286, 0.20778008394132733, -0.1227006030868802, -0.23708213196862174, 0.07263572486038557, 0.16970756577458074, 0.12125350011638918, -0.15093272699534466, 0.07569517464163887, -0.07744367673235425, 0.15095385691245733, 0.0793218881649486, 0.03808351964847642, 0.12974833906233563, 0.154395522837827, 0.08708615371339828, 0.111791706380091, -0.006510763794136376, -0.07150608609367351, -0.29440591188337084, -0.11405624536860545, -0.15480780224236895, 0.04917543493058351, -0.052057718569550944, -0.17543030531003567, 0.40035922100799065, 0.1414689229785512, 0.19537333848933547, 0.14130726717886025, 0.2768251680753241, 0.06981146029715615, 0.14883082884095483, 0.07702410212418033, 0.17154130815174154, 0.1810791009397767, 0.07039371229275583, -0.06793515767183912, 0.03003834533185493, 0.1126784210535303] |
1,802.03691 | Tree-to-tree Neural Networks for Program Translation | Program translation is an important tool to migrate legacy code in one
language into an ecosystem built in a different language. In this work, we are
the first to employ deep neural networks toward tackling this problem. We
observe that program translation is a modular procedure, in which a sub-tree of
the source tree is translated into the corresponding target sub-tree at each
step. To capture this intuition, we design a tree-to-tree neural network to
translate a source tree into a target one. Meanwhile, we develop an attention
mechanism for the tree-to-tree model, so that when the decoder expands one
non-terminal in the target tree, the attention mechanism locates the
corresponding sub-tree in the source tree to guide the expansion of the
decoder. We evaluate the program translation capability of our tree-to-tree
model against several state-of-the-art approaches. Compared against other
neural translation models, we observe that our approach is consistently better
than the baselines with a margin of up to 15 points. Further, our approach can
improve the previous state-of-the-art program translation approaches by a
margin of 20 points on the translation of real-world projects.
| cs.AI cs.LG cs.PL | program translation is an important tool to migrate legacy code in one language into an ecosystem built in a different language in this work we are the first to employ deep neural networks toward tackling this problem we observe that program translation is a modular procedure in which a subtree of the source tree is translated into the corresponding target subtree at each step to capture this intuition we design a treetotree neural network to translate a source tree into a target one meanwhile we develop an attention mechanism for the treetotree model so that when the decoder expands one nonterminal in the target tree the attention mechanism locates the corresponding subtree in the source tree to guide the expansion of the decoder we evaluate the program translation capability of our treetotree model against several stateoftheart approaches compared against other neural translation models we observe that our approach is consistently better than the baselines with a margin of up to 15 points further our approach can improve the previous stateoftheart program translation approaches by a margin of 20 points on the translation of realworld projects | [['program', 'translation', 'is', 'an', 'important', 'tool', 'to', 'migrate', 'legacy', 'code', 'in', 'one', 'language', 'into', 'an', 'ecosystem', 'built', 'in', 'a', 'different', 'language', 'in', 'this', 'work', 'we', 'are', 'the', 'first', 'to', 'employ', 'deep', 'neural', 'networks', 'toward', 'tackling', 'this', 'problem', 'we', 'observe', 'that', 'program', 'translation', 'is', 'a', 'modular', 'procedure', 'in', 'which', 'a', 'subtree', 'of', 'the', 'source', 'tree', 'is', 'translated', 'into', 'the', 'corresponding', 'target', 'subtree', 'at', 'each', 'step', 'to', 'capture', 'this', 'intuition', 'we', 'design', 'a', 'treetotree', 'neural', 'network', 'to', 'translate', 'a', 'source', 'tree', 'into', 'a', 'target', 'one', 'meanwhile', 'we', 'develop', 'an', 'attention', 'mechanism', 'for', 'the', 'treetotree', 'model', 'so', 'that', 'when', 'the', 'decoder', 'expands', 'one', 'nonterminal', 'in', 'the', 'target', 'tree', 'the', 'attention', 'mechanism', 'locates', 'the', 'corresponding', 'subtree', 'in', 'the', 'source', 'tree', 'to', 'guide', 'the', 'expansion', 'of', 'the', 'decoder', 'we', 'evaluate', 'the', 'program', 'translation', 'capability', 'of', 'our', 'treetotree', 'model', 'against', 'several', 'stateoftheart', 'approaches', 'compared', 'against', 'other', 'neural', 'translation', 'models', 'we', 'observe', 'that', 'our', 'approach', 'is', 'consistently', 'better', 'than', 'the', 'baselines', 'with', 'a', 'margin', 'of', 'up', 'to', '15', 'points', 'further', 'our', 'approach', 'can', 'improve', 'the', 'previous', 'stateoftheart', 'program', 'translation', 'approaches', 'by', 'a', 'margin', 'of', '20', 'points', 'on', 'the', 'translation', 'of', 'realworld', 'projects']] | [-0.05256338065137734, 0.012497677055826235, -0.09462511935900594, 0.08752572778423594, -0.10133940108825226, -0.16724110041317103, 0.09242476206996503, 0.4186231186865149, -0.3169020918600664, -0.30146512649953366, 0.061982393542908736, -0.2845703983603901, -0.1401359059898233, 0.19050178126859907, -0.07753840609378106, 0.05977700289363998, 0.12871674271048728, 0.06637114053340377, -0.040956811134300726, -0.27503701603493175, 0.30692141564512576, 0.07844536728713335, 0.3256956806179841, 0.0208458588383085, 0.11743932024802307, -0.050641850832648376, -0.0073786388176518515, -0.03764261602159791, -0.05735256419248873, 0.15879442867684504, 0.26422148187406047, 0.23159262892110524, 0.30648630147648825, -0.40073307162100397, -0.20605374065202636, 0.06369802086312022, 0.1296644674991635, 0.16914527202968965, 0.002712745450883852, -0.2871327636411061, 0.10659331469419035, -0.18933715120058608, -0.02587017285310336, -0.05999810876375115, -0.015697058944686038, -0.05683022836487539, -0.23962598143875397, -0.07039380102745585, 0.14535561087918844, 0.03556487400185417, -0.03980651568571055, -0.12476561049351821, 0.0017598764832458787, 0.14870363041661, 0.048504833513367415, 0.16363473651502786, 0.10288059091245806, -0.13833219241944764, -0.16027132210737044, 0.3691042383566398, -0.07579352784865674, -0.21476228760580557, 0.18300011099089641, -0.042391585639199696, -0.18859927751048391, 0.10569433478789556, 0.23834760661041868, 0.10805059715954436, -0.1617969437971919, 0.030397461762500775, -0.041177417705389296, 0.19570414483597554, 0.043366491410730255, -0.05220171331704871, 0.2068798988805832, 0.2906376706625058, 0.054069770268491794, 0.2015227478982352, -0.1087718725468762, -0.08717590399917115, -0.23976001302032052, -0.11812191159036514, -0.12961564595131456, -0.052155884928730745, -0.07446600219637559, -0.13492946796421262, 0.42384038678294905, 0.22115466029106362, 0.20081279902165203, 0.1458141435220888, 0.3199447280651814, 0.0398480707345329, 0.159081621948831, 0.1097529494430165, 0.16981416812821015, 0.01130194577665345, 0.09125736909289216, -0.1795842467656208, 0.07483346275906581, 0.08689175225492264] |
1,802.03692 | Nearly Optimal Adaptive Procedure with Change Detection for
Piecewise-Stationary Bandit | Multi-armed bandit (MAB) is a class of online learning problems where a
learning agent aims to maximize its expected cumulative reward while repeatedly
selecting to pull arms with unknown reward distributions. We consider a
scenario where the reward distributions may change in a piecewise-stationary
fashion at unknown time steps. We show that by incorporating a simple
change-detection component with classic UCB algorithms to detect and adapt to
changes, our so-called M-UCB algorithm can achieve nearly optimal regret bound
on the order of $O(\sqrt{MKT\log T})$, where $T$ is the number of time steps,
$K$ is the number of arms, and $M$ is the number of stationary segments.
Comparison with the best available lower bound shows that our M-UCB is nearly
optimal in $T$ up to a logarithmic factor. We also compare M-UCB with the
state-of-the-art algorithms in numerical experiments using a public Yahoo!
dataset to demonstrate its superior performance.
| stat.ML cs.LG | multiarmed bandit mab is a class of online learning problems where a learning agent aims to maximize its expected cumulative reward while repeatedly selecting to pull arms with unknown reward distributions we consider a scenario where the reward distributions may change in a piecewisestationary fashion at unknown time steps we show that by incorporating a simple changedetection component with classic ucb algorithms to detect and adapt to changes our socalled mucb algorithm can achieve nearly optimal regret bound on the order of osqrtmktlog t where t is the number of time steps k is the number of arms and m is the number of stationary segments comparison with the best available lower bound shows that our mucb is nearly optimal in t up to a logarithmic factor we also compare mucb with the stateoftheart algorithms in numerical experiments using a public yahoo dataset to demonstrate its superior performance | [['multiarmed', 'bandit', 'mab', 'is', 'a', 'class', 'of', 'online', 'learning', 'problems', 'where', 'a', 'learning', 'agent', 'aims', 'to', 'maximize', 'its', 'expected', 'cumulative', 'reward', 'while', 'repeatedly', 'selecting', 'to', 'pull', 'arms', 'with', 'unknown', 'reward', 'distributions', 'we', 'consider', 'a', 'scenario', 'where', 'the', 'reward', 'distributions', 'may', 'change', 'in', 'a', 'piecewisestationary', 'fashion', 'at', 'unknown', 'time', 'steps', 'we', 'show', 'that', 'by', 'incorporating', 'a', 'simple', 'changedetection', 'component', 'with', 'classic', 'ucb', 'algorithms', 'to', 'detect', 'and', 'adapt', 'to', 'changes', 'our', 'socalled', 'mucb', 'algorithm', 'can', 'achieve', 'nearly', 'optimal', 'regret', 'bound', 'on', 'the', 'order', 'of', 'osqrtmktlog', 't', 'where', 't', 'is', 'the', 'number', 'of', 'time', 'steps', 'k', 'is', 'the', 'number', 'of', 'arms', 'and', 'm', 'is', 'the', 'number', 'of', 'stationary', 'segments', 'comparison', 'with', 'the', 'best', 'available', 'lower', 'bound', 'shows', 'that', 'our', 'mucb', 'is', 'nearly', 'optimal', 'in', 't', 'up', 'to', 'a', 'logarithmic', 'factor', 'we', 'also', 'compare', 'mucb', 'with', 'the', 'stateoftheart', 'algorithms', 'in', 'numerical', 'experiments', 'using', 'a', 'public', 'yahoo', 'dataset', 'to', 'demonstrate', 'its', 'superior', 'performance']] | [-0.10261202775291167, 0.0396400603424555, -0.08650009983954128, 0.04098714481117394, -0.12270631631329453, -0.162984627926228, 0.11996629634863368, 0.43898635507136785, -0.26601884601523684, -0.3630212268520457, 0.06783304050434888, -0.28866440539254623, -0.1348800414675834, 0.17337852985547464, -0.11223110567372875, 0.06487282986759024, 0.04192144443521745, 0.08925771006845495, -0.0320604140925709, -0.3328571265237089, 0.256236618329283, 0.07606798822858504, 0.24055090289702322, -0.03915310527837905, 0.1233502292449643, -0.032018714164285506, 0.013073733419363647, 0.025555302404804903, -0.11976192747197212, 0.07956700466798347, 0.3080448622666426, 0.16719962591558796, 0.3585977572472576, -0.34243644141674445, -0.14273277762960515, 0.13239187269858052, 0.12439885065212947, 0.07028998423931601, -0.02915804658392381, -0.2695998329238421, 0.08230398852476331, -0.12497359068049486, -0.03741185657591337, -0.04918607367760166, -0.005223486162278624, 0.017232631811108692, -0.3664526270677139, 0.022298497241505164, 0.039403535704426215, -0.023015244578828618, -0.024829578745894792, -0.14557063626759006, 0.06242192872692229, 0.12189609108518074, 0.07572379300598892, 0.08334290846345985, 0.14974426585297118, -0.14870510211683252, -0.21044026046585876, 0.32822209934317537, -0.1099037426245893, -0.14695373395628922, 0.16692823637593665, -0.10823179961049131, -0.10457751765010917, 0.13436395779796909, 0.2299017923801732, 0.1764058905501603, -0.11833903281220874, 0.06222289488698375, -0.09431934055910275, 0.1687650932284186, 0.050172624201988994, -0.009358650101918956, 0.092540570276197, 0.20616095628728773, 0.1555349519603005, 0.170341665013915, -0.075074828411991, -0.12836107981651007, -0.25170560865377894, -0.10939299018790653, -0.18204288583305872, -0.00725501563818175, -0.1027052099656133, -0.10916168803228762, 0.34385196243010485, 0.15233476041914376, 0.24221308625043453, 0.17706351900207146, 0.3348126400034038, 0.06925923738875711, 0.037238766654666994, 0.18089405050640608, 0.18243692533689596, 0.015717665016647987, 0.0410160821510897, -0.23743074166518793, 0.14460714729376087, 0.013376200378422631] |
1,802.03693 | Stable Cosmic Time Crystals | Cosmological time crystals are created when a scalar field moves periodically
through phase space in a spatially flat Friedmann-Robertson-Walker spacetime
due to the presence of a limit cycle. All such cosmological time crystals in
the literature suffer from gradient instabilities occurring at Null Energy
Condition violating phases where the square sound speed for cosmological
perturbations becomes negative. Here we present stable cosmological time
crystals. Our analysis suggests this new form of scalar matter--cosmic time
crystals--may be considered as a physically viable cosmological matter source.
| hep-th gr-qc | cosmological time crystals are created when a scalar field moves periodically through phase space in a spatially flat friedmannrobertsonwalker spacetime due to the presence of a limit cycle all such cosmological time crystals in the literature suffer from gradient instabilities occurring at null energy condition violating phases where the square sound speed for cosmological perturbations becomes negative here we present stable cosmological time crystals our analysis suggests this new form of scalar mattercosmic time crystalsmay be considered as a physically viable cosmological matter source | [['cosmological', 'time', 'crystals', 'are', 'created', 'when', 'a', 'scalar', 'field', 'moves', 'periodically', 'through', 'phase', 'space', 'in', 'a', 'spatially', 'flat', 'friedmannrobertsonwalker', 'spacetime', 'due', 'to', 'the', 'presence', 'of', 'a', 'limit', 'cycle', 'all', 'such', 'cosmological', 'time', 'crystals', 'in', 'the', 'literature', 'suffer', 'from', 'gradient', 'instabilities', 'occurring', 'at', 'null', 'energy', 'condition', 'violating', 'phases', 'where', 'the', 'square', 'sound', 'speed', 'for', 'cosmological', 'perturbations', 'becomes', 'negative', 'here', 'we', 'present', 'stable', 'cosmological', 'time', 'crystals', 'our', 'analysis', 'suggests', 'this', 'new', 'form', 'of', 'scalar', 'mattercosmic', 'time', 'crystalsmay', 'be', 'considered', 'as', 'a', 'physically', 'viable', 'cosmological', 'matter', 'source']] | [-0.20440623128968405, 0.21430649545055064, -0.0718227090972771, 0.05377627065740299, -0.10803404810452243, -0.16818751428821466, 0.005060832689107373, 0.33491018323636634, -0.24823397485448456, -0.26804933708768747, 0.11279921077771067, -0.21860719143935456, -0.059251524008265354, 0.14989312325899556, 0.027042736509451416, 0.02309740425609961, 0.011360444869596238, -0.0021728696869459095, -0.044008398990760124, -0.23281788190531477, 0.32714906196598326, 0.08793662872347163, 0.23337969470701023, -0.04521550119729576, 0.10083522373333392, -0.0800879459811102, -0.014449108363606217, 0.07551622128919074, -0.1731931340398704, -0.06762625133936725, 0.22987285464850862, 0.04990163298391896, 0.23497296956072494, -0.45575346547837664, -0.31063931422285374, 0.16609912108993385, 0.15638324463876282, 0.20599604253202858, -0.11666865394700592, -0.27898419868178304, 0.018678259871127766, -0.12153878796096074, -0.145965633987699, -0.04283283011442641, -0.01866285351144786, -0.06226420505880946, -0.22654335136048315, 0.18354845562063885, -0.037987179315944274, -0.014694186844635845, -0.08953085787049155, -0.02833799971267581, -0.008442587545709458, 0.016568738219353778, 0.12174122272877068, 0.03645539948171595, 0.14796919954895246, -0.11897269011441074, -0.0740916540863265, 0.4403856457551805, -0.12798485076395658, -0.1901266835686728, 0.12214087112806737, -0.1447601515841287, -0.12634498438593456, 0.1422261893578873, 0.15294529140995042, 0.11618762498539759, -0.12416870832793193, 0.13900961370275514, 0.021165423890257756, 0.19329172404903192, 0.1405727886424468, 0.06183614407484306, 0.32812887954911807, 0.13848713024167297, 0.0565383817500821, 0.106856613287918, -0.062030802500086746, -0.10316380463744991, -0.37789877028227215, -0.16659321706378605, -0.15826401578279484, 0.06594255793890802, -0.17170091480493727, -0.24024733413783153, 0.36286881064326026, 0.10678514049930793, 0.15421441803322877, 0.050461363637956176, 0.264031487903217, 0.05859353586395339, 0.010101210969080014, 0.10327525010400611, 0.28005831953558347, 0.08965453767024617, 0.17477996702442264, -0.19441424079080363, -0.012887911689354152, 0.010072690315499174] |
1,802.03694 | The Spectrum of the Universe | The cosmic background (CB) radiation, encompassing the sum of emission from
all sources outside our own Milky Way galaxy across the entire electromagnetic
spectrum, is a fundamental phenomenon in observational cosmology. Many
experiments have been conceived to measure it (or its constituents) since the
extragalactic Universe was first discovered; in addition to estimating the bulk
(cosmic monopole) spectrum, directional variations have also been detected over
a wide range of wavelengths. Here we gather the most recent of these
measurements and discuss the current status of our understanding of the CB from
radio to $\gamma$-ray energies. Using available data in the literature we piece
together the sky-averaged intensity spectrum, and discuss the emission
processes responsible for what is observed. We examine the effect of
perturbations to the continuum spectrum from atomic and molecular line
processes and comment on the detectability of these signals. We also discuss
how one could in principle obtain a complete census of the CB by measuring the
full spectrum of each spherical harmonic expansion coefficient. This set of
spectra of multipole moments effectively encodes the entire statistical history
of nuclear, atomic and molecular processes in the Universe.
| astro-ph.CO | the cosmic background cb radiation encompassing the sum of emission from all sources outside our own milky way galaxy across the entire electromagnetic spectrum is a fundamental phenomenon in observational cosmology many experiments have been conceived to measure it or its constituents since the extragalactic universe was first discovered in addition to estimating the bulk cosmic monopole spectrum directional variations have also been detected over a wide range of wavelengths here we gather the most recent of these measurements and discuss the current status of our understanding of the cb from radio to gammaray energies using available data in the literature we piece together the skyaveraged intensity spectrum and discuss the emission processes responsible for what is observed we examine the effect of perturbations to the continuum spectrum from atomic and molecular line processes and comment on the detectability of these signals we also discuss how one could in principle obtain a complete census of the cb by measuring the full spectrum of each spherical harmonic expansion coefficient this set of spectra of multipole moments effectively encodes the entire statistical history of nuclear atomic and molecular processes in the universe | [['the', 'cosmic', 'background', 'cb', 'radiation', 'encompassing', 'the', 'sum', 'of', 'emission', 'from', 'all', 'sources', 'outside', 'our', 'own', 'milky', 'way', 'galaxy', 'across', 'the', 'entire', 'electromagnetic', 'spectrum', 'is', 'a', 'fundamental', 'phenomenon', 'in', 'observational', 'cosmology', 'many', 'experiments', 'have', 'been', 'conceived', 'to', 'measure', 'it', 'or', 'its', 'constituents', 'since', 'the', 'extragalactic', 'universe', 'was', 'first', 'discovered', 'in', 'addition', 'to', 'estimating', 'the', 'bulk', 'cosmic', 'monopole', 'spectrum', 'directional', 'variations', 'have', 'also', 'been', 'detected', 'over', 'a', 'wide', 'range', 'of', 'wavelengths', 'here', 'we', 'gather', 'the', 'most', 'recent', 'of', 'these', 'measurements', 'and', 'discuss', 'the', 'current', 'status', 'of', 'our', 'understanding', 'of', 'the', 'cb', 'from', 'radio', 'to', 'gammaray', 'energies', 'using', 'available', 'data', 'in', 'the', 'literature', 'we', 'piece', 'together', 'the', 'skyaveraged', 'intensity', 'spectrum', 'and', 'discuss', 'the', 'emission', 'processes', 'responsible', 'for', 'what', 'is', 'observed', 'we', 'examine', 'the', 'effect', 'of', 'perturbations', 'to', 'the', 'continuum', 'spectrum', 'from', 'atomic', 'and', 'molecular', 'line', 'processes', 'and', 'comment', 'on', 'the', 'detectability', 'of', 'these', 'signals', 'we', 'also', 'discuss', 'how', 'one', 'could', 'in', 'principle', 'obtain', 'a', 'complete', 'census', 'of', 'the', 'cb', 'by', 'measuring', 'the', 'full', 'spectrum', 'of', 'each', 'spherical', 'harmonic', 'expansion', 'coefficient', 'this', 'set', 'of', 'spectra', 'of', 'multipole', 'moments', 'effectively', 'encodes', 'the', 'entire', 'statistical', 'history', 'of', 'nuclear', 'atomic', 'and', 'molecular', 'processes', 'in', 'the', 'universe']] | [-0.07783560438669826, 0.09308916284751735, -0.07704513878316471, 0.08911402674796255, -0.08980683033158512, -0.012579267886222193, 0.026277322469181137, 0.38253001539330733, -0.24196069583995267, -0.3027396845582284, 0.06937958806397786, -0.29174276319528486, -0.07257985551841557, 0.200285674049519, 0.03825217933412396, -0.005922640769092954, 0.018063423358437018, -0.0008454011814472707, -0.014042831793133365, -0.19837351646994264, 0.31129427918625113, 0.125741837705075, 0.25129332554581774, 0.05811527952012655, 0.06860506283915847, -0.030988204903214387, -0.10573230973248811, -0.01313440291161992, -0.1299804031420009, 0.11339340564843856, 0.2322776279769881, 0.1765169952885787, 0.18891177304291265, -0.39649292738299424, -0.2713654083591935, 0.13515651411818047, 0.1417768729568802, 0.1102671499413095, -0.039317871291361946, -0.27561648906649727, 0.05538771065552474, -0.15894736769413084, -0.14444161061883756, -0.016667737349818804, 0.024999837518522614, 0.03680236563699222, -0.17782921314386552, 0.08528601226219172, 0.02514495990900813, 0.044368931258979595, -0.09540718164552298, -0.10988642703251619, 0.002331178509140093, 0.14076626109523013, 0.04746652050433974, 0.0026571499827121826, 0.17211861195974051, -0.12515847674283004, -0.10658810279258576, 0.4164716209971199, -0.09310231150838694, -0.07141255765784177, 0.17687675690670546, -0.24938824248230576, -0.16887123242363725, 0.12693749994137568, 0.15968605595346735, 0.08862109349942521, -0.1833311450545137, 0.08927963254697571, -0.00841765273607483, 0.15888452627971816, 0.060450634937488326, 0.09473166886815115, 0.2983194125154497, 0.12214888211241678, 0.015354582997909013, 0.11646142092190291, -0.16302845425487153, -0.0503184455299848, -0.2874957810067204, -0.1069457636959238, -0.18038102598848604, 0.07307646377257218, -0.05545940250418713, -0.13588141233592882, 0.42344736619852485, 0.14711193308038148, 0.20877096588527294, -0.007852085448317475, 0.31889813285517066, 0.06676148286611638, 0.0626839291212443, 0.04579017289522055, 0.3105483818787003, 0.14621173169610924, 0.09971629458197735, -0.2116361810813511, 0.04107205890744042, -0.016957315589350305] |
1,802.03695 | The lamplighter group of rank two generated by a bireversible automaton | We construct a 4-state 2-letter bireversible automaton generating the
lamplighter group $(\mathbb Z_2^2)\wr\mathbb Z$ of rank two. The action of the
generators on the boundary of the tree can be induced by the affine
transformations on the ring $\mathbb Z_2[[t]]$ of formal power series over
$\mathbb Z_2$.
| math.GR | we construct a 4state 2letter bireversible automaton generating the lamplighter group mathbb z_22wrmathbb z of rank two the action of the generators on the boundary of the tree can be induced by the affine transformations on the ring mathbb z_2t of formal power series over mathbb z_2 | [['we', 'construct', 'a', '4state', '2letter', 'bireversible', 'automaton', 'generating', 'the', 'lamplighter', 'group', 'mathbb', 'z_22wrmathbb', 'z', 'of', 'rank', 'two', 'the', 'action', 'of', 'the', 'generators', 'on', 'the', 'boundary', 'of', 'the', 'tree', 'can', 'be', 'induced', 'by', 'the', 'affine', 'transformations', 'on', 'the', 'ring', 'mathbb', 'z_2t', 'of', 'formal', 'power', 'series', 'over', 'mathbb', 'z_2']] | [-0.2337481016147649, 0.147572576817449, -0.023533484007677307, -0.01970947558141273, -0.055049945934392185, -0.13439087653735085, 0.006335760102323864, 0.3754577406722566, -0.3607121464674887, -0.1275240823869472, 0.13564730558098984, -0.2601177778256976, -0.09887406768520242, 0.1640501281160497, -0.08221679097851334, 0.008434407979897831, -0.0759542183748082, 0.14908210629516322, -0.133695342456517, -0.3221955010060059, 0.32284801767167187, -0.05917301843368003, 0.2523749345184668, -0.06956760965935561, 0.14163598606524908, 0.007395899621769786, -0.03821270406732093, -0.04177547061977827, -0.14871482808223885, 0.05641821251534249, 0.2102011430846608, 0.052894828172967485, 0.13838596755395766, -0.404144751596386, -0.1741045428763913, 0.24239545858100706, 0.13873144330294884, -0.0033538924206210218, -0.01611250232520473, -0.33632107807890227, 0.10102587891742587, -0.2358585094385173, -0.07216784553399877, -0.004275108566102775, 0.05642353235389632, 0.01910245722240728, -0.28937423497099307, -0.02195107100693428, 0.10608231820894973, 0.15608771791195739, -0.0035974036132835822, -0.06314672489205132, -0.11399640514687433, 0.0882499758457846, -0.03903815409411555, 0.10026884557800772, 0.12742208953663384, -0.026841113181865734, -0.1767077235828923, 0.402177477741371, -0.08492261892103631, -0.23433961792160635, 0.11050808964722345, -0.1458750222708382, -0.193892160916458, 0.1277763108095235, 0.13242874488882397, 0.10753746933124089, -0.01707305026281139, 0.2859489686139252, -0.14705429956792732, 0.09995643411884489, 0.051955750616996185, -0.05441694698579933, 0.14600374741965663, 0.06320548711506568, 0.04352718922777769, 0.13366412352922413, 0.029203926481347044, -0.05448706205124441, -0.382443525524729, -0.15659659097234355, -0.13948725983905402, 0.16557032623044823, -0.14567216363249588, -0.1674392614716097, 0.46317811294094374, 0.0671342169035874, 0.1578614820255493, 0.16459031766482993, 0.17337196480239864, 0.09946635729916718, 0.07091693980011927, 0.038051637112284487, -0.04099362536900393, 0.14007280798851635, -0.13057674159063026, -0.2084814773508064, -0.013223855315869592, 0.27583438562958135] |
1,802.03696 | A novel numerical scheme for nonlinear electron-plasma oscillations | In this work, we suggest an easy-to-code higher-order finite volume
semi-discrete scheme to analyze the nonlinear behavior of the electron-plasma
oscillations by solving electron fluid equations numerically. The present
method employs a fourth-order accurate centrally weighted essentially
nonoscillatory reconstruction (CWENO4) polynomial for estimating the numerical
flux at the grid-cell interfaces, and a fourth-order Runge-Kutta method for the
time integration. The numerical implementation is validated by reproducing
earlier results for both non-dissipative and dissipative cold plasmas. The
stability of the present scheme is illustrated by evolving the nonlinear
electron plasma oscillations in a cold non-dissipative plasma for hundred
plasma periods, which also display a negligible numerical dissipation. The
fourth-order accuracy of the existing approach is also confirmed by evaluating
the convergence of errors for the nonlinear electron plasma oscillations in a
cold non-dissipative plasma.
| physics.plasm-ph | in this work we suggest an easytocode higherorder finite volume semidiscrete scheme to analyze the nonlinear behavior of the electronplasma oscillations by solving electron fluid equations numerically the present method employs a fourthorder accurate centrally weighted essentially nonoscillatory reconstruction cweno4 polynomial for estimating the numerical flux at the gridcell interfaces and a fourthorder rungekutta method for the time integration the numerical implementation is validated by reproducing earlier results for both nondissipative and dissipative cold plasmas the stability of the present scheme is illustrated by evolving the nonlinear electron plasma oscillations in a cold nondissipative plasma for hundred plasma periods which also display a negligible numerical dissipation the fourthorder accuracy of the existing approach is also confirmed by evaluating the convergence of errors for the nonlinear electron plasma oscillations in a cold nondissipative plasma | [['in', 'this', 'work', 'we', 'suggest', 'an', 'easytocode', 'higherorder', 'finite', 'volume', 'semidiscrete', 'scheme', 'to', 'analyze', 'the', 'nonlinear', 'behavior', 'of', 'the', 'electronplasma', 'oscillations', 'by', 'solving', 'electron', 'fluid', 'equations', 'numerically', 'the', 'present', 'method', 'employs', 'a', 'fourthorder', 'accurate', 'centrally', 'weighted', 'essentially', 'nonoscillatory', 'reconstruction', 'cweno4', 'polynomial', 'for', 'estimating', 'the', 'numerical', 'flux', 'at', 'the', 'gridcell', 'interfaces', 'and', 'a', 'fourthorder', 'rungekutta', 'method', 'for', 'the', 'time', 'integration', 'the', 'numerical', 'implementation', 'is', 'validated', 'by', 'reproducing', 'earlier', 'results', 'for', 'both', 'nondissipative', 'and', 'dissipative', 'cold', 'plasmas', 'the', 'stability', 'of', 'the', 'present', 'scheme', 'is', 'illustrated', 'by', 'evolving', 'the', 'nonlinear', 'electron', 'plasma', 'oscillations', 'in', 'a', 'cold', 'nondissipative', 'plasma', 'for', 'hundred', 'plasma', 'periods', 'which', 'also', 'display', 'a', 'negligible', 'numerical', 'dissipation', 'the', 'fourthorder', 'accuracy', 'of', 'the', 'existing', 'approach', 'is', 'also', 'confirmed', 'by', 'evaluating', 'the', 'convergence', 'of', 'errors', 'for', 'the', 'nonlinear', 'electron', 'plasma', 'oscillations', 'in', 'a', 'cold', 'nondissipative', 'plasma']] | [-0.1387048404131113, 0.11811453057552254, -0.07347723899654353, 0.05894850390243598, -0.007236896671890987, -0.12117716194850138, -0.037899779307543104, 0.32840834767645877, -0.21692333880954803, -0.2663574038094587, 0.08141171986459415, -0.25193356104996795, -0.07551584717337832, 0.25387894031309494, 0.007305020364914195, 0.11641203614911347, 0.0669827158792142, -0.06772697209662785, -0.07126905605951889, -0.2122022975095068, 0.27589421197207586, 0.08095688401072314, 0.2619677050970495, 0.0549420851113444, 0.13425404698037627, -0.09063036623587267, -0.07777058672703181, 0.031068879800538223, -0.10374469118599364, 0.04265208741664096, 0.23695837443863804, -0.016401530499217297, 0.29341232557569374, -0.4528159008301428, -0.2693177232453529, 0.01451015741313864, 0.16902277105008112, 0.13947088360543025, -0.11106119882033179, -0.2570928168610077, 0.01743578631915928, -0.17076537928854427, -0.16084765234898607, -0.11777692589605453, 0.017729553097689695, 0.05170816983974708, -0.29757746546282293, 0.1907851237580568, 0.041427154619613604, 0.02906723950537994, -0.07537959088486704, -0.04672833591713711, 0.002172041359837308, -0.013117383646948094, -0.00628347693771392, -0.016914646409339075, 0.11968143181024282, -0.0919912406119913, -0.07634741960580206, 0.39463561853732576, -0.10245862481833408, -0.22468689713224937, 0.15133901130563268, -0.142150500544107, -0.07337119992624855, 0.19552057717616358, 0.16210570716242673, 0.13821679819375277, -0.15940238905816592, 0.03438162713251641, -0.01952881405260555, 0.12997779459339764, 0.06759818428845117, -0.03236883140352526, 0.15333402180818445, 0.21905889599866263, 0.04011401922131578, 0.11223496008482692, -0.05460251051805575, -0.10456003360609016, -0.3177949723815828, -0.12724506814342793, -0.15336192561539286, -0.04144233773166144, -0.10155291473259268, -0.19271518279459665, 0.41786077257198817, 0.15896085983540892, 0.0860673894710613, 0.04081373277993848, 0.3863283055693363, 0.18410388685085557, -0.02765585290917167, 0.12139912109722156, 0.25348963594826107, 0.1726276514360286, 0.1412988517338156, -0.3492901880879689, 0.01518222432456572, 0.13090170326529804] |
1,802.03697 | Holographic Magnetic Susceptibility | The (2+1)-dimensional static magnetic susceptibility in strong-coupling is
studied via a Reissner-Nordstr\"{o}m-AdS geometry. The analyticity of the
susceptibility on the complex momentum $\mathfrak{q}$-plane in relation to the
Friedel-like oscillation in coordinate space is explored. In contrast to the
branch-cuts crossing the real momentum-axis for a Fermi liquid, we prove that
the holographic magnetic susceptibility remains an analytic function of the
complex momentum around the real axis in the limit of zero temperature, At zero
temperature, we located analytically two pairs of branch-cuts that are parallel
to the imaginary momentum-axis for large $|\text{Im}\ \mathfrak{q}|$ but become
warped with the end-points keeping away from the real and imaginary
momentum-axes. We conclude that these branch-cuts give rise to the exponential
decay behaviour of Friedel-like oscillation of magnetic susceptibility in
coordinate space. We also derived the analytical forms of the susceptibility in
large and small-momentum, respectively.
| hep-th | the 21dimensional static magnetic susceptibility in strongcoupling is studied via a reissnernordstromads geometry the analyticity of the susceptibility on the complex momentum mathfrakqplane in relation to the friedellike oscillation in coordinate space is explored in contrast to the branchcuts crossing the real momentumaxis for a fermi liquid we prove that the holographic magnetic susceptibility remains an analytic function of the complex momentum around the real axis in the limit of zero temperature at zero temperature we located analytically two pairs of branchcuts that are parallel to the imaginary momentumaxis for large textim mathfrakq but become warped with the endpoints keeping away from the real and imaginary momentumaxes we conclude that these branchcuts give rise to the exponential decay behaviour of friedellike oscillation of magnetic susceptibility in coordinate space we also derived the analytical forms of the susceptibility in large and smallmomentum respectively | [['the', '21dimensional', 'static', 'magnetic', 'susceptibility', 'in', 'strongcoupling', 'is', 'studied', 'via', 'a', 'reissnernordstromads', 'geometry', 'the', 'analyticity', 'of', 'the', 'susceptibility', 'on', 'the', 'complex', 'momentum', 'mathfrakqplane', 'in', 'relation', 'to', 'the', 'friedellike', 'oscillation', 'in', 'coordinate', 'space', 'is', 'explored', 'in', 'contrast', 'to', 'the', 'branchcuts', 'crossing', 'the', 'real', 'momentumaxis', 'for', 'a', 'fermi', 'liquid', 'we', 'prove', 'that', 'the', 'holographic', 'magnetic', 'susceptibility', 'remains', 'an', 'analytic', 'function', 'of', 'the', 'complex', 'momentum', 'around', 'the', 'real', 'axis', 'in', 'the', 'limit', 'of', 'zero', 'temperature', 'at', 'zero', 'temperature', 'we', 'located', 'analytically', 'two', 'pairs', 'of', 'branchcuts', 'that', 'are', 'parallel', 'to', 'the', 'imaginary', 'momentumaxis', 'for', 'large', 'textim', 'mathfrakq', 'but', 'become', 'warped', 'with', 'the', 'endpoints', 'keeping', 'away', 'from', 'the', 'real', 'and', 'imaginary', 'momentumaxes', 'we', 'conclude', 'that', 'these', 'branchcuts', 'give', 'rise', 'to', 'the', 'exponential', 'decay', 'behaviour', 'of', 'friedellike', 'oscillation', 'of', 'magnetic', 'susceptibility', 'in', 'coordinate', 'space', 'we', 'also', 'derived', 'the', 'analytical', 'forms', 'of', 'the', 'susceptibility', 'in', 'large', 'and', 'smallmomentum', 'respectively']] | [-0.2123069327570957, 0.1675293760187966, -0.07471614134281981, 0.0570804480601615, -0.07805181679356357, -0.08318797069891909, 0.024319158603801676, 0.3295177123306886, -0.2391926041480316, -0.2143550413336767, 0.07009686297396252, -0.3134041198865052, -0.10932870785894709, 0.19529667951544558, 0.04205897327957918, 0.014121913776287565, -0.046127040137830394, 0.0902052133789529, -0.12121781841615566, -0.2117050243946521, 0.34264601928357413, -0.0057105934120836145, 0.2776893660750078, 0.09235221695532833, 0.0606562410602751, 0.032780869678337723, 0.06398577911212393, 0.034676595239653725, -0.13294203282055314, 0.04043688245819531, 0.21780601973253963, 0.01705125464713606, 0.1536056255361578, -0.4035737161133168, -0.1454711254665871, 0.09618715291836069, 0.1802779370277742, 0.09099671028662419, -0.020843166330714535, -0.26363451981350133, 0.041548955112533724, -0.12005992548243291, -0.20322523860638772, -0.09822629642524365, 0.02592212194914295, -0.010332435988897012, -0.23491260741729345, 0.12510810805922476, 0.01529375892267495, 0.10551153283323282, -0.1121622009381679, -0.07752891326242167, -0.048916680670842747, 0.09409694581130601, 0.09993666495572234, 0.054127485739350646, 0.11336266258022869, -0.11408917411513951, -0.04544993822692313, 0.3085905159722366, -0.07548918662106861, -0.1869622353275401, 0.1578817772122262, -0.2624698730651289, -0.08506977789279452, 0.1428264763958725, 0.14980435691287983, 0.09744423704113865, -0.08704106840709953, 0.14212111765906835, -0.025823415491554508, 0.10335917591346779, 0.07808062211826336, 0.005035742935117172, 0.23694725086291632, 0.10552293766185344, 0.024084415899225227, 0.17761676260810075, -0.09756948913116872, -0.1301233859705752, -0.31491228253783093, -0.15660868842910597, -0.20138634533445904, 0.07683879851053159, -0.11040583172576009, -0.2191739326030918, 0.3873014274269234, 0.11863990044187539, 0.2560971466473479, 0.04227568703177183, 0.289977355867766, 0.13087327372024604, 0.09322306897956878, 0.10091657495138572, 0.25395811700761534, 0.1573221131609213, 0.14259697070372276, -0.29703054624184483, -0.02279868328174495, 0.029128594624310517] |
1,802.03698 | A Smooth Curve as a Fractal Under the Third Definition | It is commonly believed in the literature that smooth curves, such as
circles, are not fractal, and only non-smooth curves, such as coastlines, are
fractal. However, this paper demonstrates that a smooth curve can be fractal,
under the new, relaxed, third definition of fractal - a set or pattern is
fractal if the scaling of far more small things than large ones recurs at least
twice. The scaling can be rephrased as a hierarchy, consisting of numerous
smallest, a very few largest, and some in between the smallest and the largest.
The logarithmic spiral, as a smooth curve, is apparently fractal because it
bears the self-similar property, or the scaling of far more small squares than
large ones recurs multiple times, or the scaling of far more small bends than
large ones recurs multiple times. A half-circle or half-ellipse and the UK
coastline (before or after smooth processing) are fractal, if the scaling of
far more small bends than large ones recurs at least twice.
Keywords: Third definition of fractal, head/tail breaks, bends, ht-index,
scaling hierarchy
| math.GM | it is commonly believed in the literature that smooth curves such as circles are not fractal and only nonsmooth curves such as coastlines are fractal however this paper demonstrates that a smooth curve can be fractal under the new relaxed third definition of fractal a set or pattern is fractal if the scaling of far more small things than large ones recurs at least twice the scaling can be rephrased as a hierarchy consisting of numerous smallest a very few largest and some in between the smallest and the largest the logarithmic spiral as a smooth curve is apparently fractal because it bears the selfsimilar property or the scaling of far more small squares than large ones recurs multiple times or the scaling of far more small bends than large ones recurs multiple times a halfcircle or halfellipse and the uk coastline before or after smooth processing are fractal if the scaling of far more small bends than large ones recurs at least twice keywords third definition of fractal headtail breaks bends htindex scaling hierarchy | [['it', 'is', 'commonly', 'believed', 'in', 'the', 'literature', 'that', 'smooth', 'curves', 'such', 'as', 'circles', 'are', 'not', 'fractal', 'and', 'only', 'nonsmooth', 'curves', 'such', 'as', 'coastlines', 'are', 'fractal', 'however', 'this', 'paper', 'demonstrates', 'that', 'a', 'smooth', 'curve', 'can', 'be', 'fractal', 'under', 'the', 'new', 'relaxed', 'third', 'definition', 'of', 'fractal', 'a', 'set', 'or', 'pattern', 'is', 'fractal', 'if', 'the', 'scaling', 'of', 'far', 'more', 'small', 'things', 'than', 'large', 'ones', 'recurs', 'at', 'least', 'twice', 'the', 'scaling', 'can', 'be', 'rephrased', 'as', 'a', 'hierarchy', 'consisting', 'of', 'numerous', 'smallest', 'a', 'very', 'few', 'largest', 'and', 'some', 'in', 'between', 'the', 'smallest', 'and', 'the', 'largest', 'the', 'logarithmic', 'spiral', 'as', 'a', 'smooth', 'curve', 'is', 'apparently', 'fractal', 'because', 'it', 'bears', 'the', 'selfsimilar', 'property', 'or', 'the', 'scaling', 'of', 'far', 'more', 'small', 'squares', 'than', 'large', 'ones', 'recurs', 'multiple', 'times', 'or', 'the', 'scaling', 'of', 'far', 'more', 'small', 'bends', 'than', 'large', 'ones', 'recurs', 'multiple', 'times', 'a', 'halfcircle', 'or', 'halfellipse', 'and', 'the', 'uk', 'coastline', 'before', 'or', 'after', 'smooth', 'processing', 'are', 'fractal', 'if', 'the', 'scaling', 'of', 'far', 'more', 'small', 'bends', 'than', 'large', 'ones', 'recurs', 'at', 'least', 'twice', 'keywords', 'third', 'definition', 'of', 'fractal', 'headtail', 'breaks', 'bends', 'htindex', 'scaling', 'hierarchy']] | [-0.13915117265089233, 0.14722076940467987, -0.09916076052869702, 0.14394583236881073, -0.09982597170633146, -0.16094291235866218, 0.0013387882775940194, 0.3178703025085102, -0.2812952831515978, -0.2861455886721097, 0.15188270411320332, -0.3363649734863262, -0.14756087224593323, 0.24646442851597636, -0.042806579276448355, 0.036704718533551436, -0.005373940733529028, 0.02881766519048947, -0.05933657225191957, -0.2237544446359335, 0.3009124964518451, -0.005135268775475928, 0.24437356706515984, -0.005103061006781806, 0.045443777454583424, -0.07172646438007126, 0.0015842458208147757, 0.08484971044242554, -0.06443021478890455, 0.07420362334634209, 0.19087891608888777, 0.10385759868498506, 0.29162116787642584, -0.39936646706713685, -0.1909089207799099, 0.15426790273759042, 0.1940449849654246, 0.05886282330651864, 0.031124642119815187, -0.19682824847705918, 0.12598914129327682, -0.1059078731722648, -0.1978967741463633, -0.022905289720015966, 0.09709663382442348, 0.012539241673697814, -0.16942225329527075, 0.10276021284918332, 0.07045354450057292, 0.0874841654427007, 0.03248537107820398, -0.12162101745134456, -0.03845353909880565, 0.0806789548449411, 0.06138759701520782, 0.0559969220802873, 0.12042844013963964, -0.12648400779272934, -0.042456945517480416, 0.40011273358745136, -0.012521328443685418, -0.16454385726808987, 0.22201699080165133, -0.2247102194018769, -0.12271618362698147, 0.18206530274159607, 0.11419353297785802, 0.10780015290479293, -0.12785202079591737, 0.01298786401708514, -0.08396862508279496, 0.18415454595521008, 0.1649687642087068, 0.029063329207657397, 0.16775628700103054, 0.16234287495548227, 0.1220118466432838, 0.12451277674047341, -0.0694293387946084, -0.10340622288506778, -0.2789899867420063, -0.1069653716965996, -0.21377905373777337, 0.06933665928712192, -0.1648421933999601, -0.19703947936503174, 0.34593855096669546, 0.03440246495000761, 0.27024761492108135, 0.09486144302070312, 0.27201063728934133, 0.08600652123871326, 0.17949328369102388, 0.12642348246065493, 0.20139866288374686, 0.023629429876595606, 0.06365753271370783, -0.09781936029957115, 0.08700406484723348, 0.036554618132429134] |
1,802.03699 | PCA-Based Missing Information Imputation for Real-Time Crash Likelihood
Prediction Under Imbalanced Data | The real-time crash likelihood prediction has been an important research
topic. Various classifiers, such as support vector machine (SVM) and tree-based
boosting algorithms, have been proposed in traffic safety studies. However, few
research focuses on the missing data imputation in real-time crash likelihood
prediction, although missing values are commonly observed due to breakdown of
sensors or external interference. Besides, classifying imbalanced data is also
a difficult problem in real-time crash likelihood prediction, since it is hard
to distinguish crash-prone cases from non-crash cases which compose the
majority of the observed samples. In this paper, principal component analysis
(PCA) based approaches, including LS-PCA, PPCA, and VBPCA, are employed for
imputing missing values, while two kinds of solutions are developed to solve
the problem in imbalanced data. The results show that PPCA and VBPCA not only
outperform LS-PCA and other imputation methods (including mean imputation and
k-means clustering imputation), in terms of the root mean square error (RMSE),
but also help the classifiers achieve better predictive performance. The two
solutions, i.e., cost-sensitive learning and synthetic minority oversampling
technique (SMOTE), help improve the sensitivity by adjusting the classifiers to
pay more attention to the minority class.
| cs.LG stat.ML | the realtime crash likelihood prediction has been an important research topic various classifiers such as support vector machine svm and treebased boosting algorithms have been proposed in traffic safety studies however few research focuses on the missing data imputation in realtime crash likelihood prediction although missing values are commonly observed due to breakdown of sensors or external interference besides classifying imbalanced data is also a difficult problem in realtime crash likelihood prediction since it is hard to distinguish crashprone cases from noncrash cases which compose the majority of the observed samples in this paper principal component analysis pca based approaches including lspca ppca and vbpca are employed for imputing missing values while two kinds of solutions are developed to solve the problem in imbalanced data the results show that ppca and vbpca not only outperform lspca and other imputation methods including mean imputation and kmeans clustering imputation in terms of the root mean square error rmse but also help the classifiers achieve better predictive performance the two solutions ie costsensitive learning and synthetic minority oversampling technique smote help improve the sensitivity by adjusting the classifiers to pay more attention to the minority class | [['the', 'realtime', 'crash', 'likelihood', 'prediction', 'has', 'been', 'an', 'important', 'research', 'topic', 'various', 'classifiers', 'such', 'as', 'support', 'vector', 'machine', 'svm', 'and', 'treebased', 'boosting', 'algorithms', 'have', 'been', 'proposed', 'in', 'traffic', 'safety', 'studies', 'however', 'few', 'research', 'focuses', 'on', 'the', 'missing', 'data', 'imputation', 'in', 'realtime', 'crash', 'likelihood', 'prediction', 'although', 'missing', 'values', 'are', 'commonly', 'observed', 'due', 'to', 'breakdown', 'of', 'sensors', 'or', 'external', 'interference', 'besides', 'classifying', 'imbalanced', 'data', 'is', 'also', 'a', 'difficult', 'problem', 'in', 'realtime', 'crash', 'likelihood', 'prediction', 'since', 'it', 'is', 'hard', 'to', 'distinguish', 'crashprone', 'cases', 'from', 'noncrash', 'cases', 'which', 'compose', 'the', 'majority', 'of', 'the', 'observed', 'samples', 'in', 'this', 'paper', 'principal', 'component', 'analysis', 'pca', 'based', 'approaches', 'including', 'lspca', 'ppca', 'and', 'vbpca', 'are', 'employed', 'for', 'imputing', 'missing', 'values', 'while', 'two', 'kinds', 'of', 'solutions', 'are', 'developed', 'to', 'solve', 'the', 'problem', 'in', 'imbalanced', 'data', 'the', 'results', 'show', 'that', 'ppca', 'and', 'vbpca', 'not', 'only', 'outperform', 'lspca', 'and', 'other', 'imputation', 'methods', 'including', 'mean', 'imputation', 'and', 'kmeans', 'clustering', 'imputation', 'in', 'terms', 'of', 'the', 'root', 'mean', 'square', 'error', 'rmse', 'but', 'also', 'help', 'the', 'classifiers', 'achieve', 'better', 'predictive', 'performance', 'the', 'two', 'solutions', 'ie', 'costsensitive', 'learning', 'and', 'synthetic', 'minority', 'oversampling', 'technique', 'smote', 'help', 'improve', 'the', 'sensitivity', 'by', 'adjusting', 'the', 'classifiers', 'to', 'pay', 'more', 'attention', 'to', 'the', 'minority', 'class']] | [-0.029266903343476713, -0.0077354776668529515, -0.04795783825907262, 0.14167747489347599, -0.11479339140784392, -0.23498589683452897, 0.055132565113958566, 0.4174758699782034, -0.22586476678484457, -0.35571292919562536, 0.1503734943173495, -0.3120964867399728, -0.14880697865737602, 0.19045658387674733, -0.1324126982158595, 0.12496597999400345, 0.1375780316061053, 0.04783268243525217, -0.04133327514245274, -0.34221549983943833, 0.2594471761332627, 0.054546010967819615, 0.38958339014169857, -0.006626125712423248, 0.058054720245405755, 0.01533170890043232, -0.07073291165239, 0.02628141082217592, -0.02534144547009535, 0.12577966931139792, 0.34720766607751236, 0.1648940627780208, 0.3491977134154753, -0.36321008292849155, -0.2370492552947055, 0.169157583477035, 0.15835574271647815, 0.08285217126397951, -0.020680892070463704, -0.272712987728734, 0.0859110416755318, -0.18543564718949826, -0.008796127089497415, -0.147288645217641, -0.05056281665716558, 0.021086518069112454, -0.30743463167504587, 0.09770306456367178, 0.04253116190220487, 0.08179797938569112, -0.06740180860605448, -0.19124566013627547, 0.03483556086839018, 0.12422237624389496, 0.12484278386964047, 0.021300026481881975, 0.1061141048285595, -0.1699846348582217, -0.18761746519978376, 0.35407821943071927, -0.013957810736177093, -0.2231401546828528, 0.18274135519676107, -0.037212203118078255, -0.18091262983742784, 0.1265822733415568, 0.25123147806059815, 0.0756852791193833, -0.14617565392635445, -0.01831356212286219, 0.0037474241875547994, 0.13894942175210553, 0.024535944954085936, -0.04278632874372713, 0.1540252178984179, 0.20438336621334607, 0.027769409087882873, 0.10311442943744391, -0.16198782788396396, -0.08948005328915934, -0.16156313819018134, -0.07684236898537765, -0.18890712562789944, -0.060907330094546235, -0.10027696247948854, -0.19341971354182572, 0.3757056608793643, 0.24619002754185745, 0.19214222626265218, 0.06571320324772077, 0.37590306976493054, 0.06203466328294413, 0.09861390988814317, 0.10849448353636693, 0.22273932150044934, 0.07920168146634712, 0.098596146057776, -0.1728711240823341, 0.1392770343190158, 0.024898230046172566] |
1,802.037 | Stochastic Non-preemptive Co-flow Scheduling with Time-Indexed
Relaxation | Co-flows model a modern scheduling setting that is commonly found in a
variety of applications in distributed and cloud computing. A stochastic
co-flow task contains a set of parallel flows with randomly distributed sizes.
Further, many applications require non-preemptive scheduling of co-flow tasks.
This paper gives an approximation algorithm for stochastic non-preemptive
co-flow scheduling. The proposed approach uses a time-indexed linear
relaxation, and uses its solution to come up with a feasible schedule. This
algorithm is shown to achieve a competitive ratio of
$(2\log{m}+1)(1+\sqrt{m}\Delta)(1+m{\Delta}){(3+\Delta)}/{2}$ for zero-release
times, and $(2\log{m}+1)(1+\sqrt{m}\Delta)(1+m\Delta)(2+\Delta)$ for general
release times, where $\Delta$ represents the upper bound of squared coefficient
of variation of processing times, and $m$ is the number of servers.
| cs.DC cs.DS | coflows model a modern scheduling setting that is commonly found in a variety of applications in distributed and cloud computing a stochastic coflow task contains a set of parallel flows with randomly distributed sizes further many applications require nonpreemptive scheduling of coflow tasks this paper gives an approximation algorithm for stochastic nonpreemptive coflow scheduling the proposed approach uses a timeindexed linear relaxation and uses its solution to come up with a feasible schedule this algorithm is shown to achieve a competitive ratio of 2logm11sqrtmdelta1mdelta3delta2 for zerorelease times and 2logm11sqrtmdelta1mdelta2delta for general release times where delta represents the upper bound of squared coefficient of variation of processing times and m is the number of servers | [['coflows', 'model', 'a', 'modern', 'scheduling', 'setting', 'that', 'is', 'commonly', 'found', 'in', 'a', 'variety', 'of', 'applications', 'in', 'distributed', 'and', 'cloud', 'computing', 'a', 'stochastic', 'coflow', 'task', 'contains', 'a', 'set', 'of', 'parallel', 'flows', 'with', 'randomly', 'distributed', 'sizes', 'further', 'many', 'applications', 'require', 'nonpreemptive', 'scheduling', 'of', 'coflow', 'tasks', 'this', 'paper', 'gives', 'an', 'approximation', 'algorithm', 'for', 'stochastic', 'nonpreemptive', 'coflow', 'scheduling', 'the', 'proposed', 'approach', 'uses', 'a', 'timeindexed', 'linear', 'relaxation', 'and', 'uses', 'its', 'solution', 'to', 'come', 'up', 'with', 'a', 'feasible', 'schedule', 'this', 'algorithm', 'is', 'shown', 'to', 'achieve', 'a', 'competitive', 'ratio', 'of', '2logm11sqrtmdelta1mdelta3delta2', 'for', 'zerorelease', 'times', 'and', '2logm11sqrtmdelta1mdelta2delta', 'for', 'general', 'release', 'times', 'where', 'delta', 'represents', 'the', 'upper', 'bound', 'of', 'squared', 'coefficient', 'of', 'variation', 'of', 'processing', 'times', 'and', 'm', 'is', 'the', 'number', 'of', 'servers']] | [-0.18797216506314104, 0.049934943930926595, -0.06516384310298809, -0.0168736290327181, -0.05445541396552512, -0.16927572183713718, 0.060155831878325225, 0.36093142458346783, -0.28470041276467545, -0.33998740278184414, 0.10317783973280441, -0.2300078437269271, -0.11839142443427632, 0.234067744378269, -0.09151631812690883, 0.09134397245387689, 0.0813570643087161, 0.05114256075440763, -0.021870824674077263, -0.28734905294537005, 0.19927038407783854, 0.0275190983907328, 0.2972100933631966, 0.020440943765680532, 0.1252403836935939, -0.0187710379376202, -0.009877547436091746, 0.016873551654285408, -0.10229831761377706, 0.12452433953430873, 0.27982611755362236, 0.17104600601082853, 0.3161932284700441, -0.4111425139110636, -0.16470550791872246, 0.12496561836451292, 0.1366239719146334, 0.05103560887814105, -0.03452537986785509, -0.16931450228534034, 0.12045790051605117, -0.1616381528275507, -0.03763086385269825, -0.026588827916966366, 0.06258214486611856, 0.03831390502048774, -0.3718987263336375, 0.0552588762832923, 0.033091863814472884, -0.020075723188268522, -0.03428330095296071, -0.1358402470569336, 0.105546828789368, 0.08403729414567351, 0.022759835748631205, 0.06653393720389923, 0.11524120182205864, -0.09377264501794393, -0.15794446973365034, 0.43251523021440785, -0.03032220811960665, -0.1866059027662551, 0.16348682382135643, 0.01573300296818284, -0.1706840745781691, 0.13695601229597856, 0.2561588480330265, 0.15204963147606668, -0.15920503273069322, 0.0960135460088684, -0.06802031029485636, 0.1640007211952596, 0.06029777839645609, -0.005136633192730212, 0.10928383819456841, 0.2494734186964395, 0.19178444837578698, 0.15256674205548726, -0.05463350612275839, -0.15838663095423766, -0.23811533510567504, -0.1578575298174385, -0.19380018582278108, 0.041393587512576636, -0.10963730067213964, -0.15931854362632064, 0.3452619096969028, 0.12706932281185915, 0.19526959005072042, 0.134002665905198, 0.3369442583019803, 0.11222825022028897, 0.048301428963371494, 0.2092006330809405, 0.11089746933849948, 0.07924536019728859, 0.1480511684948159, -0.19387023831793182, 0.052505682461668514, 0.03090196062898817] |
1,802.03701 | Formal Ontology Learning from English IS-A Sentences | Ontology learning (OL) is the process of automatically generating an
ontological knowledge base from a plain text document. In this paper, we
propose a new ontology learning approach and tool, called DLOL, which generates
a knowledge base in the description logic (DL) SHOQ(D) from a collection of
factual non-negative IS-A sentences in English. We provide extensive
experimental results on the accuracy of DLOL, giving experimental comparisons
to three state-of-the-art existing OL tools, namely Text2Onto, FRED, and LExO.
Here, we use the standard OL accuracy measure, called lexical accuracy, and a
novel OL accuracy measure, called instance-based inference model. In our
experimental results, DLOL turns out to be about 21% and 46%, respectively,
better than the best of the other three approaches.
| cs.AI cs.CL | ontology learning ol is the process of automatically generating an ontological knowledge base from a plain text document in this paper we propose a new ontology learning approach and tool called dlol which generates a knowledge base in the description logic dl shoqd from a collection of factual nonnegative isa sentences in english we provide extensive experimental results on the accuracy of dlol giving experimental comparisons to three stateoftheart existing ol tools namely text2onto fred and lexo here we use the standard ol accuracy measure called lexical accuracy and a novel ol accuracy measure called instancebased inference model in our experimental results dlol turns out to be about 21 and 46 respectively better than the best of the other three approaches | [['ontology', 'learning', 'ol', 'is', 'the', 'process', 'of', 'automatically', 'generating', 'an', 'ontological', 'knowledge', 'base', 'from', 'a', 'plain', 'text', 'document', 'in', 'this', 'paper', 'we', 'propose', 'a', 'new', 'ontology', 'learning', 'approach', 'and', 'tool', 'called', 'dlol', 'which', 'generates', 'a', 'knowledge', 'base', 'in', 'the', 'description', 'logic', 'dl', 'shoqd', 'from', 'a', 'collection', 'of', 'factual', 'nonnegative', 'isa', 'sentences', 'in', 'english', 'we', 'provide', 'extensive', 'experimental', 'results', 'on', 'the', 'accuracy', 'of', 'dlol', 'giving', 'experimental', 'comparisons', 'to', 'three', 'stateoftheart', 'existing', 'ol', 'tools', 'namely', 'text2onto', 'fred', 'and', 'lexo', 'here', 'we', 'use', 'the', 'standard', 'ol', 'accuracy', 'measure', 'called', 'lexical', 'accuracy', 'and', 'a', 'novel', 'ol', 'accuracy', 'measure', 'called', 'instancebased', 'inference', 'model', 'in', 'our', 'experimental', 'results', 'dlol', 'turns', 'out', 'to', 'be', 'about', '21', 'and', '46', 'respectively', 'better', 'than', 'the', 'best', 'of', 'the', 'other', 'three', 'approaches']] | [-0.0414011752616395, -0.009615734644980608, -0.07559341798779093, 0.09257909956742129, -0.14515007819448197, -0.14844417023793363, 0.11026470836725462, 0.398002097007482, -0.23006591218437591, -0.3174158343732232, 0.032015444172796705, -0.3131654776521262, -0.1186453913878493, 0.17596744644032994, -0.07911182563759762, 0.06347344142674398, 0.10429021069670424, 0.06926297961011287, -0.04858510553476816, -0.24934345723262855, 0.26608661829274805, 0.028281908186383452, 0.3426549524311446, 0.04417396934718645, 0.11890610020623363, -0.04912201160987636, -0.07973144786479343, -0.017333766167686015, -0.09986018105370909, 0.21115052040095025, 0.305596010732081, 0.2678931483787586, 0.2999380801372942, -0.3633923252747089, -0.1441158149234888, 0.04243804014115712, 0.15431813703176855, 0.1064855261469072, -0.014725997109756563, -0.34597072402062284, 0.0758787486545679, -0.20261074632686024, 0.017462307610744687, -0.1464744215682462, -0.0032826687043978823, -0.004657841754192878, -0.27648962158788026, -0.004016486708732212, 0.14884557876688967, 0.11656781434504111, -0.04394801108542235, -0.15019403712260498, 0.08420984981730267, 0.08870244779068381, -0.008926770566941137, 0.10544040197303065, 0.07843387405243271, -0.11437318530598921, -0.1866394752898731, 0.3797236279185329, -0.09593098798334822, -0.22358508103433214, 0.18305010076792239, -0.015654316226787427, -0.13714102544516577, 0.08031874806426971, 0.1695351843289765, 0.08392763876614451, -0.15372281894087791, 0.04629056351924581, -0.05358532370858583, 0.24277518537803358, 0.06864658063042815, -0.001808783266411609, 0.16581497932275555, 0.27539423425063614, -0.01643937122577629, 0.12534563840482338, -0.08356937715791542, -0.08934442794435665, -0.2574310932061909, -0.15385117694469436, -0.15675610245181984, -0.014048509638239982, -0.10257440115111888, -0.1275763692287337, 0.3985389656535968, 0.2528733591854322, 0.18741240847401885, 0.10645060338365588, 0.3269091431646287, -0.0011306555986701815, 0.04722375821658731, 0.0739378749956416, 0.15829354799313455, 0.01466755335759215, 0.10351102651652544, -0.13094607200825728, 0.04561431056960728, 0.06308785752205476] |
1,802.03702 | Disentangling Entanglements in Biopolymer Solutions | Reptation theory has been highly successful in explaining the unusual
material properties of entangled polymer solutions. It reduces the complex
many-body dynamics to a single-polymer description where each polymer is
envisaged to be confined to a tube through which it moves in a snake-like
fashion. For flexible polymers, reptation theory has been amply confirmed by
both experiments and simulations. In contrast, for semiflexible polymers
experimental and numerical tests are either limited to the onset of reptation,
or were performed for tracer polymers in a fixed, static matrix. Here we report
Brownian dynamics simulations of entangled solutions of semiflexible polymers,
which show that curvilinear motion along a tube (reptation) is no longer the
dominant mode of dynamics. Instead, we find that polymers disentangle due to
correlated constraint release which leads to equilibration of internal bending
modes before polymers diffuse the full tube length. The physical mechanism
underlying terminal stress relaxation is rotational diffusion mediated by
disentanglement rather than curvilinear motion along a tube.
| cond-mat.soft cond-mat.stat-mech physics.bio-ph | reptation theory has been highly successful in explaining the unusual material properties of entangled polymer solutions it reduces the complex manybody dynamics to a singlepolymer description where each polymer is envisaged to be confined to a tube through which it moves in a snakelike fashion for flexible polymers reptation theory has been amply confirmed by both experiments and simulations in contrast for semiflexible polymers experimental and numerical tests are either limited to the onset of reptation or were performed for tracer polymers in a fixed static matrix here we report brownian dynamics simulations of entangled solutions of semiflexible polymers which show that curvilinear motion along a tube reptation is no longer the dominant mode of dynamics instead we find that polymers disentangle due to correlated constraint release which leads to equilibration of internal bending modes before polymers diffuse the full tube length the physical mechanism underlying terminal stress relaxation is rotational diffusion mediated by disentanglement rather than curvilinear motion along a tube | [['reptation', 'theory', 'has', 'been', 'highly', 'successful', 'in', 'explaining', 'the', 'unusual', 'material', 'properties', 'of', 'entangled', 'polymer', 'solutions', 'it', 'reduces', 'the', 'complex', 'manybody', 'dynamics', 'to', 'a', 'singlepolymer', 'description', 'where', 'each', 'polymer', 'is', 'envisaged', 'to', 'be', 'confined', 'to', 'a', 'tube', 'through', 'which', 'it', 'moves', 'in', 'a', 'snakelike', 'fashion', 'for', 'flexible', 'polymers', 'reptation', 'theory', 'has', 'been', 'amply', 'confirmed', 'by', 'both', 'experiments', 'and', 'simulations', 'in', 'contrast', 'for', 'semiflexible', 'polymers', 'experimental', 'and', 'numerical', 'tests', 'are', 'either', 'limited', 'to', 'the', 'onset', 'of', 'reptation', 'or', 'were', 'performed', 'for', 'tracer', 'polymers', 'in', 'a', 'fixed', 'static', 'matrix', 'here', 'we', 'report', 'brownian', 'dynamics', 'simulations', 'of', 'entangled', 'solutions', 'of', 'semiflexible', 'polymers', 'which', 'show', 'that', 'curvilinear', 'motion', 'along', 'a', 'tube', 'reptation', 'is', 'no', 'longer', 'the', 'dominant', 'mode', 'of', 'dynamics', 'instead', 'we', 'find', 'that', 'polymers', 'disentangle', 'due', 'to', 'correlated', 'constraint', 'release', 'which', 'leads', 'to', 'equilibration', 'of', 'internal', 'bending', 'modes', 'before', 'polymers', 'diffuse', 'the', 'full', 'tube', 'length', 'the', 'physical', 'mechanism', 'underlying', 'terminal', 'stress', 'relaxation', 'is', 'rotational', 'diffusion', 'mediated', 'by', 'disentanglement', 'rather', 'than', 'curvilinear', 'motion', 'along', 'a', 'tube']] | [-0.12749171770683684, 0.2158476483719251, -0.09723115118542387, 0.01676054868378596, -0.05628060148655219, -0.19937128217798877, -0.032862802782745594, 0.44057321164435076, -0.26680517688474076, -0.223280799816604, 0.0700726895003844, -0.2504602235132529, -0.12505961913057823, 0.14934805917329397, 0.028080514272858882, 0.053451322852691385, 0.08422816834515995, -0.02241128097564258, -0.01993713490837426, -0.1361311860382557, 0.16531126462440524, 0.08690624132344246, 0.27637343188276353, 0.05141896164378174, 0.09604312356110134, 0.0031338241253117166, 0.021514611485425706, 0.07849688795222728, -0.18591473671871045, 0.06267268443048966, 0.19439862657016443, -0.02118527726845149, 0.23513563439290144, -0.5147464665710743, -0.2749768071606709, 0.0628179410159197, 0.1860122430931639, 0.16223778155584528, -0.00766670310752679, -0.2314398552486558, 0.046699663677344815, -0.14107286503802938, -0.14554899007104982, -0.06750450493555148, 0.08318753074567167, 0.03788770708531417, -0.21902131991472418, 0.12175031658836905, 0.030781208247199286, 0.0714349715013264, -0.050522266493328374, -0.017605777934802995, -0.04126664297080335, 0.06520575610202174, 0.09090868492659618, 0.019281718779332293, 0.24742603252273926, -0.14015371931528522, -0.10693796728105273, 0.4071845382819941, -0.005050037642326465, -0.23128360809965265, 0.24094895765553287, -0.1228740014406036, -0.10008098018919061, 0.23199596344981988, 0.1075345451658287, 0.11931273983619003, -0.17805799564208696, 0.015693861938708312, -0.015965336772762698, 0.17963269611469895, 0.06586305987532538, -0.02374672396812749, 0.23373709854750355, 0.22152192216297542, 0.01512442360183707, 0.18415473326954437, -0.06919118634103165, -0.18943568409914957, -0.2449656117155596, -0.1791943820886153, -0.19519452911706062, 0.08238780601697479, -0.07143376634242789, -0.20660149219034837, 0.3493326381362693, 0.08524014712828729, 0.1585105034281258, 0.054896933626653745, 0.2380983776177199, 0.029886682647176914, 0.06662342282706285, 0.029633536408827814, 0.24812737180862898, 0.15742423014792925, 0.09489128274417678, -0.2627547878806514, 0.08986598619742801, 0.055339388518427485] |
1,802.03703 | Stochastic Spectral and Conjugate Descent Methods | The state-of-the-art methods for solving optimization problems in big
dimensions are variants of randomized coordinate descent (RCD). In this paper
we introduce a fundamentally new type of acceleration strategy for RCD based on
the augmentation of the set of coordinate directions by a few spectral or
conjugate directions. As we increase the number of extra directions to be
sampled from, the rate of the method improves, and interpolates between the
linear rate of RCD and a linear rate independent of the condition number. We
develop and analyze also inexact variants of these methods where the spectral
and conjugate directions are allowed to be approximate only. We motivate the
above development by proving several negative results which highlight the
limitations of RCD with importance sampling.
| math.OC | the stateoftheart methods for solving optimization problems in big dimensions are variants of randomized coordinate descent rcd in this paper we introduce a fundamentally new type of acceleration strategy for rcd based on the augmentation of the set of coordinate directions by a few spectral or conjugate directions as we increase the number of extra directions to be sampled from the rate of the method improves and interpolates between the linear rate of rcd and a linear rate independent of the condition number we develop and analyze also inexact variants of these methods where the spectral and conjugate directions are allowed to be approximate only we motivate the above development by proving several negative results which highlight the limitations of rcd with importance sampling | [['the', 'stateoftheart', 'methods', 'for', 'solving', 'optimization', 'problems', 'in', 'big', 'dimensions', 'are', 'variants', 'of', 'randomized', 'coordinate', 'descent', 'rcd', 'in', 'this', 'paper', 'we', 'introduce', 'a', 'fundamentally', 'new', 'type', 'of', 'acceleration', 'strategy', 'for', 'rcd', 'based', 'on', 'the', 'augmentation', 'of', 'the', 'set', 'of', 'coordinate', 'directions', 'by', 'a', 'few', 'spectral', 'or', 'conjugate', 'directions', 'as', 'we', 'increase', 'the', 'number', 'of', 'extra', 'directions', 'to', 'be', 'sampled', 'from', 'the', 'rate', 'of', 'the', 'method', 'improves', 'and', 'interpolates', 'between', 'the', 'linear', 'rate', 'of', 'rcd', 'and', 'a', 'linear', 'rate', 'independent', 'of', 'the', 'condition', 'number', 'we', 'develop', 'and', 'analyze', 'also', 'inexact', 'variants', 'of', 'these', 'methods', 'where', 'the', 'spectral', 'and', 'conjugate', 'directions', 'are', 'allowed', 'to', 'be', 'approximate', 'only', 'we', 'motivate', 'the', 'above', 'development', 'by', 'proving', 'several', 'negative', 'results', 'which', 'highlight', 'the', 'limitations', 'of', 'rcd', 'with', 'importance', 'sampling']] | [-0.09410519769129853, 0.06145740422465268, -0.04981579817831516, 0.01767835293937805, -0.0855406377306809, -0.1552701176316928, 0.06974711662793022, 0.3993409522058022, -0.32617248083284545, -0.27607970874035553, 0.1370072513912624, -0.2268456524808801, -0.13038256236975412, 0.22797581448873144, -0.08495309470491784, 0.0372685621738539, 0.05600764845392757, 0.007355456803775122, -0.11845412752365754, -0.2888162015062276, 0.31720425214640974, 0.0538460906339629, 0.2959059164634035, 0.013807051249914952, 0.12393820303822717, 0.000746158772193256, -0.05439480399006918, 0.06073391454053983, -0.10807716239346078, 0.17943051036995566, 0.22729467255093397, 0.19216833136183156, 0.3244515995555107, -0.39763006311090243, -0.16760987121867196, 0.14310100963789849, 0.17327261075843126, 0.12057461167569272, -0.06940067097386945, -0.2162723994378241, 0.10505887350037453, -0.10091508467937069, -0.09817397759123254, -0.09649481457628069, -0.059340692080196836, 0.10040600922319197, -0.2869837889072275, 0.08299085511539635, 0.06018415070889938, 0.04458851382256516, -0.032440068786062544, -0.15716528685973777, 0.060272989338338974, 0.05659736359244092, 0.10677646698370095, 0.02317447115426823, 0.09214230253916955, -0.09328861270407815, -0.15213321289423132, 0.3299518792379287, -0.04089800796786984, -0.239682964267089, 0.18906896543921903, -0.06669786302072386, -0.15285518750428193, 0.09457268137128032, 0.20225454031606205, 0.16462004077320377, -0.10155984622542746, 0.09318737893162536, 0.0033162101397230742, 0.10160081257439038, 0.06344618133810018, 0.022384174971751148, 0.11147363603513147, 0.13847028885427262, 0.15664062958451047, 0.12654502558589523, -0.10578310177774139, -0.11453437220845972, -0.29988089501256904, -0.17238653774162935, -0.16204984537175587, 0.0060627765713199494, -0.13227352000080095, -0.12328808090739674, 0.4233650348690008, 0.1799793722814009, 0.2329111676512947, 0.06905377340867304, 0.2854978164597865, 0.09547967467311068, 0.04039046473260368, 0.09956451238793952, 0.20543849395377742, 0.10127211807130446, 0.07310510926970071, -0.22498270976469822, 0.042225838916736744, 0.12247000265896561] |
1,802.03704 | TARM: A Turbo-type Algorithm for Affine Rank Minimization | The affine rank minimization (ARM) problem arises in many real-world
applications. The goal is to recover a low-rank matrix from a small amount of
noisy affine measurements. The original problem is NP-hard, and so directly
solving the problem is computationally prohibitive. Approximate low-complexity
solutions for ARM have recently attracted much research interest. In this
paper, we design an iterative algorithm for ARM based on message passing
principles. The proposed algorithm is termed turbo-type ARM (TARM), as inspired
by the recently developed turbo compressed sensing algorithm for sparse signal
recovery. We show that, when the linear operator for measurement is
right-orthogonally invariant (ROIL), a scalar function called state evolution
can be established to accurately predict the behaviour of the TARM algorithm.
We also show that TARM converges much faster than the counterpart algorithms
for low-rank matrix recovery. We further extend the TARM algorithm for matrix
completion, where the measurement operator corresponds to a random selection
matrix. We show that, although the state evolution is not accurate for matrix
completion, the TARM algorithm with carefully tuned parameters still
significantly outperforms its counterparts.
| cs.IT math.IT | the affine rank minimization arm problem arises in many realworld applications the goal is to recover a lowrank matrix from a small amount of noisy affine measurements the original problem is nphard and so directly solving the problem is computationally prohibitive approximate lowcomplexity solutions for arm have recently attracted much research interest in this paper we design an iterative algorithm for arm based on message passing principles the proposed algorithm is termed turbotype arm tarm as inspired by the recently developed turbo compressed sensing algorithm for sparse signal recovery we show that when the linear operator for measurement is rightorthogonally invariant roil a scalar function called state evolution can be established to accurately predict the behaviour of the tarm algorithm we also show that tarm converges much faster than the counterpart algorithms for lowrank matrix recovery we further extend the tarm algorithm for matrix completion where the measurement operator corresponds to a random selection matrix we show that although the state evolution is not accurate for matrix completion the tarm algorithm with carefully tuned parameters still significantly outperforms its counterparts | [['the', 'affine', 'rank', 'minimization', 'arm', 'problem', 'arises', 'in', 'many', 'realworld', 'applications', 'the', 'goal', 'is', 'to', 'recover', 'a', 'lowrank', 'matrix', 'from', 'a', 'small', 'amount', 'of', 'noisy', 'affine', 'measurements', 'the', 'original', 'problem', 'is', 'nphard', 'and', 'so', 'directly', 'solving', 'the', 'problem', 'is', 'computationally', 'prohibitive', 'approximate', 'lowcomplexity', 'solutions', 'for', 'arm', 'have', 'recently', 'attracted', 'much', 'research', 'interest', 'in', 'this', 'paper', 'we', 'design', 'an', 'iterative', 'algorithm', 'for', 'arm', 'based', 'on', 'message', 'passing', 'principles', 'the', 'proposed', 'algorithm', 'is', 'termed', 'turbotype', 'arm', 'tarm', 'as', 'inspired', 'by', 'the', 'recently', 'developed', 'turbo', 'compressed', 'sensing', 'algorithm', 'for', 'sparse', 'signal', 'recovery', 'we', 'show', 'that', 'when', 'the', 'linear', 'operator', 'for', 'measurement', 'is', 'rightorthogonally', 'invariant', 'roil', 'a', 'scalar', 'function', 'called', 'state', 'evolution', 'can', 'be', 'established', 'to', 'accurately', 'predict', 'the', 'behaviour', 'of', 'the', 'tarm', 'algorithm', 'we', 'also', 'show', 'that', 'tarm', 'converges', 'much', 'faster', 'than', 'the', 'counterpart', 'algorithms', 'for', 'lowrank', 'matrix', 'recovery', 'we', 'further', 'extend', 'the', 'tarm', 'algorithm', 'for', 'matrix', 'completion', 'where', 'the', 'measurement', 'operator', 'corresponds', 'to', 'a', 'random', 'selection', 'matrix', 'we', 'show', 'that', 'although', 'the', 'state', 'evolution', 'is', 'not', 'accurate', 'for', 'matrix', 'completion', 'the', 'tarm', 'algorithm', 'with', 'carefully', 'tuned', 'parameters', 'still', 'significantly', 'outperforms', 'its', 'counterparts']] | [-0.06748211445558942, 0.014893323790724783, -0.07555476762877589, 0.0481780890769095, -0.12005970259249378, -0.1839561061174975, 0.012093137335581601, 0.4238988968459994, -0.325282355990219, -0.2597623442017128, 0.15787534114480897, -0.2345072756040046, -0.24818705749342196, 0.16301187442803985, -0.10018504318896304, 0.12423191667407531, 0.09785012811490366, 0.05204239367308577, -0.12510306673943836, -0.24929154039559404, 0.2416650209277659, 0.07644078791013323, 0.2858455351650652, -0.024459664534589046, 0.138021969499349, 0.032937575119882406, -0.003393083169213967, 0.0025953963697165922, -0.06287203330524217, 0.09305068837535002, 0.2885176007128373, 0.21874179216781944, 0.29981927696636385, -0.40326431526519946, -0.187402764976213, 0.15578745859099574, 0.17066631183810427, 0.13286871419371932, -0.06895797715190108, -0.2733057782399269, 0.1325058091426624, -0.15345993584163847, -0.056816753177914056, -0.07297725493763312, -0.007039901658531613, -0.06095235631343375, -0.34954398850324364, 0.050422999124779114, 0.006500727629152995, -0.026582624271428316, -0.04181797361705097, -0.15258079324129528, 0.10712709253538777, 0.06074784933069454, 0.017581614530468727, 0.05870325507313599, 0.14904770450509583, -0.0914431005896833, -0.11039396896997593, 0.368911256783464, -0.04041770826464354, -0.21838525329125272, 0.11012645805348757, -0.04721072708319329, -0.1578294879866743, 0.16017398575655697, 0.18667095612075305, 0.14176181926450226, -0.11953896224890179, 0.1071200286600022, -0.08734677603279942, 0.16902514581118575, 0.007357851153480287, 0.01757908761605955, 0.08633069435312424, 0.16982491851066175, 0.15651022305769657, 0.14941324878109913, -0.051141486928295975, -0.10411933330777154, -0.19638691421891197, -0.11467022987223542, -0.2527764532008742, -0.00806847433786868, -0.09199065839329909, -0.14024944821492968, 0.3847997560992502, 0.17611279493208262, 0.20127959851845262, 0.11922433929978295, 0.33934963525932155, 0.11578843845028347, 0.05703514129324984, 0.1419155873018814, 0.2235884581668972, 0.14066059082443041, 0.06792232446523587, -0.21864830623407, 0.11618718475344057, 0.11400827775405867] |
1,802.03705 | The Gaussian wave packets transform for the semi-classical Schr\"odinger
equation with vector potentials | In this paper, we reformulate the semi-classical Schr\"odinger equation in
the presence of electromagnetic field by the Gaussian wave packets transform.
With this approach, the highly oscillatory Schr\"odinger equation is
equivalently transformed into another Schr\"odinger type wave equation, the $w$
equation, which is essentially not oscillatory and thus requires much less
computational effort. We propose two numerical methods to solve the $w$
equation, where the Hamiltonian is either divided into the kinetic, the
potential and the convection part, or into the kinetic and the
potential-convection part. The convection, or the potential-convection part is
treated by a semi-Lagrangian method, while the kinetic part is solved by the
Fourier spectral method. The numerical methods are proved to be unconditionally
stable, spectrally accurate in space and second order accurate in time, and in
principle they can be extended to higher order schemes in time. Various one
dimensional and multidimensional numerical tests are provided to justify the
properties of the proposed methods.
| math.NA | in this paper we reformulate the semiclassical schrodinger equation in the presence of electromagnetic field by the gaussian wave packets transform with this approach the highly oscillatory schrodinger equation is equivalently transformed into another schrodinger type wave equation the w equation which is essentially not oscillatory and thus requires much less computational effort we propose two numerical methods to solve the w equation where the hamiltonian is either divided into the kinetic the potential and the convection part or into the kinetic and the potentialconvection part the convection or the potentialconvection part is treated by a semilagrangian method while the kinetic part is solved by the fourier spectral method the numerical methods are proved to be unconditionally stable spectrally accurate in space and second order accurate in time and in principle they can be extended to higher order schemes in time various one dimensional and multidimensional numerical tests are provided to justify the properties of the proposed methods | [['in', 'this', 'paper', 'we', 'reformulate', 'the', 'semiclassical', 'schrodinger', 'equation', 'in', 'the', 'presence', 'of', 'electromagnetic', 'field', 'by', 'the', 'gaussian', 'wave', 'packets', 'transform', 'with', 'this', 'approach', 'the', 'highly', 'oscillatory', 'schrodinger', 'equation', 'is', 'equivalently', 'transformed', 'into', 'another', 'schrodinger', 'type', 'wave', 'equation', 'the', 'w', 'equation', 'which', 'is', 'essentially', 'not', 'oscillatory', 'and', 'thus', 'requires', 'much', 'less', 'computational', 'effort', 'we', 'propose', 'two', 'numerical', 'methods', 'to', 'solve', 'the', 'w', 'equation', 'where', 'the', 'hamiltonian', 'is', 'either', 'divided', 'into', 'the', 'kinetic', 'the', 'potential', 'and', 'the', 'convection', 'part', 'or', 'into', 'the', 'kinetic', 'and', 'the', 'potentialconvection', 'part', 'the', 'convection', 'or', 'the', 'potentialconvection', 'part', 'is', 'treated', 'by', 'a', 'semilagrangian', 'method', 'while', 'the', 'kinetic', 'part', 'is', 'solved', 'by', 'the', 'fourier', 'spectral', 'method', 'the', 'numerical', 'methods', 'are', 'proved', 'to', 'be', 'unconditionally', 'stable', 'spectrally', 'accurate', 'in', 'space', 'and', 'second', 'order', 'accurate', 'in', 'time', 'and', 'in', 'principle', 'they', 'can', 'be', 'extended', 'to', 'higher', 'order', 'schemes', 'in', 'time', 'various', 'one', 'dimensional', 'and', 'multidimensional', 'numerical', 'tests', 'are', 'provided', 'to', 'justify', 'the', 'properties', 'of', 'the', 'proposed', 'methods']] | [-0.09700685506686568, 0.08531154966793764, -0.0967924458703074, 0.07182121704234025, -0.08753823784765047, -0.12176579758465195, -0.028399319363346037, 0.34359159220296603, -0.2985764846148996, -0.26482175121036095, 0.12243761950118753, -0.24389314667608303, -0.12553122377721593, 0.19494359972230038, 0.0003393895100229062, 0.07758773574665284, 0.06632616942246947, 0.01842300995038106, -0.05832365858861102, -0.24380964301645947, 0.31852743816442597, 0.010797552913666153, 0.2275911423449333, -0.0016594032304755484, 0.09432588196478975, -0.0465496107398604, -0.04937176383398951, 0.013465763585909138, -0.09476028673517971, 0.10116512133614518, 0.24217648504791447, 0.056623793145916305, 0.3327552732259322, -0.4749291546863671, -0.25925869171698696, 0.08470057875353795, 0.17850684680384943, 0.12337141118731755, -0.007327549780408542, -0.30752394300622815, 0.04772766868924149, -0.13101855375899527, -0.1414956742664799, -0.09190589501761282, -0.013199507260324959, 0.011285478344339376, -0.2720038004201622, 0.12707668404805306, 0.060366783320951536, -0.04528664992764019, -0.09511048395712024, -0.08430575792832921, -0.012495837846729092, 0.0495910071917117, 0.04151152648503343, 0.015523375996287005, 0.01789707436154668, -0.09752079866922987, -0.056208871612444714, 0.4240503367752983, -0.07571789329365576, -0.3013956631199481, 0.15320935325983626, -0.1335878495294123, -0.06623959004019316, 0.18088293612266007, 0.15379708375220594, 0.14478980709846395, -0.14107058560236907, 0.09159558848851027, 0.03051394001503911, 0.16565312564713308, 0.04430297158586864, -0.01316574757369474, 0.12070247256017935, 0.14045226253951207, 0.060955877672546566, 0.11017135947268122, -0.04793492245535629, -0.11428250489272894, -0.29470841181822693, -0.1810441018022128, -0.21035706957515615, 0.03702903096778661, -0.04981780129804601, -0.1453572339617098, 0.4043735107160711, 0.1349116956694977, 0.11941117743173471, 0.010660961259138556, 0.33818110678261387, 0.24320693256763312, 0.02846151252332418, 0.09363095557543999, 0.21507233020682365, 0.15998578849487388, 0.13852316674549514, -0.23651776183265985, -0.0008614898796599263, 0.16061751758799148] |
1,802.03706 | FDM-Structured Preamble Optimization for Channel Estimation in
MIMO-OQAM/FBMC Systems | In this paper, we consider the problem of preamble design in multiple-input
multiple-output (MIMO) systems employing offset quadrature amplitude modulation
based filter bank multicarrier (OQAM/FBMC) and propose a preamble optimization
method for the frequency division multiplexing (FDM)-structured preamble.
Specifically, we formulate an optimization problem to determine the frequency
division multiplexed preambles, where the objective is to minimize the mean
square error (MSE) of the channel estimation, subject to the constraint on the
transmit energy. For two transmit antennas, we find the relationship between
preambles and the intrinsic interference from neighboring symbols to achieve
the minimum channel estimation MSE, and derive the optimal closed-form
solution. For more than two transmit antennas, the constrained preamble
optimization problem is nonconvex quadratic. Therefore, we convert the original
optimization problem into a quadratically constrained quadratic program (QCQP)
and obtain the suboptimal solution by relaxing the nonconvex constraint.
Simulation results demonstrate that, in terms of MSE and bit error rate (BER)
performances, the proposed method outperforms the conventional FDM preamble
design method at all signal-to-noise ratio (SNR) regimes and outperforms the
interference approximation method-complex (IAM-C) preamble design method at low
to medium SNR regimes with lower preamble overhead.
| cs.IT math.IT | in this paper we consider the problem of preamble design in multipleinput multipleoutput mimo systems employing offset quadrature amplitude modulation based filter bank multicarrier oqamfbmc and propose a preamble optimization method for the frequency division multiplexing fdmstructured preamble specifically we formulate an optimization problem to determine the frequency division multiplexed preambles where the objective is to minimize the mean square error mse of the channel estimation subject to the constraint on the transmit energy for two transmit antennas we find the relationship between preambles and the intrinsic interference from neighboring symbols to achieve the minimum channel estimation mse and derive the optimal closedform solution for more than two transmit antennas the constrained preamble optimization problem is nonconvex quadratic therefore we convert the original optimization problem into a quadratically constrained quadratic program qcqp and obtain the suboptimal solution by relaxing the nonconvex constraint simulation results demonstrate that in terms of mse and bit error rate ber performances the proposed method outperforms the conventional fdm preamble design method at all signaltonoise ratio snr regimes and outperforms the interference approximation methodcomplex iamc preamble design method at low to medium snr regimes with lower preamble overhead | [['in', 'this', 'paper', 'we', 'consider', 'the', 'problem', 'of', 'preamble', 'design', 'in', 'multipleinput', 'multipleoutput', 'mimo', 'systems', 'employing', 'offset', 'quadrature', 'amplitude', 'modulation', 'based', 'filter', 'bank', 'multicarrier', 'oqamfbmc', 'and', 'propose', 'a', 'preamble', 'optimization', 'method', 'for', 'the', 'frequency', 'division', 'multiplexing', 'fdmstructured', 'preamble', 'specifically', 'we', 'formulate', 'an', 'optimization', 'problem', 'to', 'determine', 'the', 'frequency', 'division', 'multiplexed', 'preambles', 'where', 'the', 'objective', 'is', 'to', 'minimize', 'the', 'mean', 'square', 'error', 'mse', 'of', 'the', 'channel', 'estimation', 'subject', 'to', 'the', 'constraint', 'on', 'the', 'transmit', 'energy', 'for', 'two', 'transmit', 'antennas', 'we', 'find', 'the', 'relationship', 'between', 'preambles', 'and', 'the', 'intrinsic', 'interference', 'from', 'neighboring', 'symbols', 'to', 'achieve', 'the', 'minimum', 'channel', 'estimation', 'mse', 'and', 'derive', 'the', 'optimal', 'closedform', 'solution', 'for', 'more', 'than', 'two', 'transmit', 'antennas', 'the', 'constrained', 'preamble', 'optimization', 'problem', 'is', 'nonconvex', 'quadratic', 'therefore', 'we', 'convert', 'the', 'original', 'optimization', 'problem', 'into', 'a', 'quadratically', 'constrained', 'quadratic', 'program', 'qcqp', 'and', 'obtain', 'the', 'suboptimal', 'solution', 'by', 'relaxing', 'the', 'nonconvex', 'constraint', 'simulation', 'results', 'demonstrate', 'that', 'in', 'terms', 'of', 'mse', 'and', 'bit', 'error', 'rate', 'ber', 'performances', 'the', 'proposed', 'method', 'outperforms', 'the', 'conventional', 'fdm', 'preamble', 'design', 'method', 'at', 'all', 'signaltonoise', 'ratio', 'snr', 'regimes', 'and', 'outperforms', 'the', 'interference', 'approximation', 'methodcomplex', 'iamc', 'preamble', 'design', 'method', 'at', 'low', 'to', 'medium', 'snr', 'regimes', 'with', 'lower', 'preamble', 'overhead']] | [-0.250047530371453, -0.05001651329671694, -0.0279738767211266, 0.05190656441350547, -0.08021484137896821, -0.2680729457048422, 0.11159048349648576, 0.39027892866053004, -0.2819557906502481, -0.28779714316763777, 0.11397164048530418, -0.21551023789265372, -0.1893548051791979, 0.15522580437530625, -0.13110687772426358, 0.09128048353917659, 0.06296775237894914, -0.005514718067059492, -0.11143314906648617, -0.28224378610723355, 0.2161759896032968, 0.14281975052151036, 0.37843901719006295, -0.04383981353640457, 0.1560821589868902, 0.053978926102145317, 0.0022219180716498894, -0.08000913652730116, -0.12870119209730277, 0.04913005080480287, 0.33978642800951653, 0.2028540782655213, 0.311899513300964, -0.3617184829917994, -0.20639210931976584, 0.11325304638445774, 0.2001602701679308, 0.06372180297113757, -0.019575351908412253, -0.2210341748246487, 0.10289620804015864, -0.1922320933130748, 0.014193216404392127, 0.06275078728101513, -0.12776864388898174, 0.03445281626463451, -0.41263759436402864, 0.09739098818031476, -0.06153795470728507, -0.00952510165169518, -0.08227930765442966, -0.20894027613796928, 0.11869255853618713, 0.06482754488094175, 0.031430515888558226, -0.006868819963741809, 0.08444412622571071, -0.04808599957725667, -0.08318386662371112, 0.3446440475242351, -0.012108312346715545, -0.3035894298945811, 0.083816886514777, -0.07953920842772548, -0.036060352289573626, 0.21659971481595347, 0.3021309654614789, 0.06849250910516352, -0.17416739290297784, 0.009156225092660765, 0.015919926323670338, 0.2289509412020128, 0.13053803055353977, 0.16447292776788247, 0.13169177183064018, 0.17498003381417143, 0.20884443081647872, 0.18719632952459195, -0.15812648274499844, -0.10575918981154013, -0.20762393180716862, -0.06427679929456258, -0.24960200117524475, -0.0349652026643719, -0.12273051802943921, -0.07369801248522832, 0.3545846123139354, 0.1577241234530873, 0.07539995212078174, 0.1989651288913979, 0.4379206423330656, 0.17473365470613453, 0.015844011236851578, 0.11926514880503825, 0.24080458547959618, 0.12420096393412058, 0.09105274741825192, -0.30845651634785526, -0.007578637838571709, 0.036398718512537794] |
1,802.03707 | The Need for Speed of AI Applications: Performance Comparison of Native
vs. Browser-based Algorithm Implementations | AI applications pose increasing demands on performance, so it is not
surprising that the era of client-side distributed software is becoming
important. On top of many AI applications already using mobile hardware, and
even browsers for computationally demanding AI applications, we are already
witnessing the emergence of client-side (federated) machine learning
algorithms, driven by the interests of large corporations and startups alike.
Apart from mathematical and algorithmic concerns, this trend especially demands
new levels of computational efficiency from client environments. Consequently,
this paper deals with the question of state-of-the-art performance by
presenting a comparison study between native code and different browser-based
implementations: JavaScript, ASM.js as well as WebAssembly on a representative
mix of algorithms. Our results show that current efforts in runtime
optimization push the boundaries well towards (and even beyond) native binary
performance. We analyze the results obtained and speculate on the reasons
behind some surprises, rounding the paper off by outlining future possibilities
as well as some of our own research efforts.
| cs.AI cs.SE stat.ML | ai applications pose increasing demands on performance so it is not surprising that the era of clientside distributed software is becoming important on top of many ai applications already using mobile hardware and even browsers for computationally demanding ai applications we are already witnessing the emergence of clientside federated machine learning algorithms driven by the interests of large corporations and startups alike apart from mathematical and algorithmic concerns this trend especially demands new levels of computational efficiency from client environments consequently this paper deals with the question of stateoftheart performance by presenting a comparison study between native code and different browserbased implementations javascript asmjs as well as webassembly on a representative mix of algorithms our results show that current efforts in runtime optimization push the boundaries well towards and even beyond native binary performance we analyze the results obtained and speculate on the reasons behind some surprises rounding the paper off by outlining future possibilities as well as some of our own research efforts | [['ai', 'applications', 'pose', 'increasing', 'demands', 'on', 'performance', 'so', 'it', 'is', 'not', 'surprising', 'that', 'the', 'era', 'of', 'clientside', 'distributed', 'software', 'is', 'becoming', 'important', 'on', 'top', 'of', 'many', 'ai', 'applications', 'already', 'using', 'mobile', 'hardware', 'and', 'even', 'browsers', 'for', 'computationally', 'demanding', 'ai', 'applications', 'we', 'are', 'already', 'witnessing', 'the', 'emergence', 'of', 'clientside', 'federated', 'machine', 'learning', 'algorithms', 'driven', 'by', 'the', 'interests', 'of', 'large', 'corporations', 'and', 'startups', 'alike', 'apart', 'from', 'mathematical', 'and', 'algorithmic', 'concerns', 'this', 'trend', 'especially', 'demands', 'new', 'levels', 'of', 'computational', 'efficiency', 'from', 'client', 'environments', 'consequently', 'this', 'paper', 'deals', 'with', 'the', 'question', 'of', 'stateoftheart', 'performance', 'by', 'presenting', 'a', 'comparison', 'study', 'between', 'native', 'code', 'and', 'different', 'browserbased', 'implementations', 'javascript', 'asmjs', 'as', 'well', 'as', 'webassembly', 'on', 'a', 'representative', 'mix', 'of', 'algorithms', 'our', 'results', 'show', 'that', 'current', 'efforts', 'in', 'runtime', 'optimization', 'push', 'the', 'boundaries', 'well', 'towards', 'and', 'even', 'beyond', 'native', 'binary', 'performance', 'we', 'analyze', 'the', 'results', 'obtained', 'and', 'speculate', 'on', 'the', 'reasons', 'behind', 'some', 'surprises', 'rounding', 'the', 'paper', 'off', 'by', 'outlining', 'future', 'possibilities', 'as', 'well', 'as', 'some', 'of', 'our', 'own', 'research', 'efforts']] | [-0.09704908544038672, 0.031712822550084306, -0.03216559548078605, 0.06070951488232467, -0.10577522483569138, -0.18996187208061358, 0.08740274829750244, 0.4026027230330084, -0.25849441944326207, -0.3610959090633182, 0.15916384362101713, -0.2690999272489557, -0.17879952613062725, 0.2783696555923642, -0.12485016823889165, 0.07382988581070449, 0.11585759791430575, -0.019580142612273737, -0.03498649823467997, -0.2892236366481861, 0.28511459487504554, 0.07465772989217373, 0.301868029261042, 0.09192895237640364, 0.02337326136587696, -0.022786154219718854, -0.04675903999269372, 0.009601865940522857, -0.06838870315169049, 0.16020924074571047, 0.3295110453398637, 0.2419522328499425, 0.36570505580932994, -0.45682101315114554, -0.1549242135852848, 0.03320292587727081, 0.17500156474373554, 0.10301306017226591, -0.12384005584477209, -0.29920390466151464, 0.07330309338164913, -0.209952115796779, -0.08760093638077861, -0.1105972815251046, 0.007965236858226268, 0.03133550877313743, -0.16399318448029368, -0.0505489632185611, 0.057020129290943196, 0.09738153800873722, -0.00478627654530744, -0.16328829351284474, 0.035886822606255184, 0.16250712368012657, 0.1037237540482992, 0.016101356209596483, 0.1747306220250477, -0.2014868027905411, -0.1856223221942101, 0.39662439294341134, 0.0060796812347068295, -0.11036577490839834, 0.25497360062563973, -0.042591063825345436, -0.19928900172604566, 0.04738238658301714, 0.20666268992056025, 0.07275791163440927, -0.12655723244860406, 0.10790476054819187, 0.03849191138969462, 0.15552406688930648, 0.05488091875392966, 0.04762680046885025, 0.22915692471830948, 0.23065962293185294, 0.06334136651861538, 0.12235547407961837, 0.014815403548887045, -0.12387832884659718, -0.21777538993827453, -0.15472415372695228, -0.15486281912876065, 0.01522502610284236, -0.0552026407770804, -0.13666083943524693, 0.35811317026637857, 0.23209303037956266, 0.143181019212778, 0.06631224577474158, 0.38263155053165265, 0.007378907776267336, 0.08992007174869864, 0.13871051742916746, 0.18465410359097337, 0.002495109070966974, 0.19493215397304128, -0.14661823982009436, 0.11886586685290151, -0.03826939693095571] |
1,802.03708 | A Time-Varying Network for Cryptocurrencies | Cryptocurrencies return cross-predictability and technological similarity
yield information on risk propagation and market segmentation. To investigate
these effects, we build a time-varying network for cryptocurrencies, based on
the evolution of return cross-predictability and technological similarities. We
develop a dynamic covariate-assisted spectral clustering method to consistently
estimate the latent community structure of cryptocurrencies network that
accounts for both sets of information. We demonstrate that investors can
achieve better risk diversification by investing in cryptocurrencies from
different communities. A cross-sectional portfolio that implements an
inter-crypto momentum trading strategy earns a 1.08% daily return. By
dissecting the portfolio returns on behavioral factors, we confirm that our
results are not driven by behavioral mechanisms.
| stat.ME econ.EM q-fin.PM q-fin.RM stat.AP | cryptocurrencies return crosspredictability and technological similarity yield information on risk propagation and market segmentation to investigate these effects we build a timevarying network for cryptocurrencies based on the evolution of return crosspredictability and technological similarities we develop a dynamic covariateassisted spectral clustering method to consistently estimate the latent community structure of cryptocurrencies network that accounts for both sets of information we demonstrate that investors can achieve better risk diversification by investing in cryptocurrencies from different communities a crosssectional portfolio that implements an intercrypto momentum trading strategy earns a 108 daily return by dissecting the portfolio returns on behavioral factors we confirm that our results are not driven by behavioral mechanisms | [['cryptocurrencies', 'return', 'crosspredictability', 'and', 'technological', 'similarity', 'yield', 'information', 'on', 'risk', 'propagation', 'and', 'market', 'segmentation', 'to', 'investigate', 'these', 'effects', 'we', 'build', 'a', 'timevarying', 'network', 'for', 'cryptocurrencies', 'based', 'on', 'the', 'evolution', 'of', 'return', 'crosspredictability', 'and', 'technological', 'similarities', 'we', 'develop', 'a', 'dynamic', 'covariateassisted', 'spectral', 'clustering', 'method', 'to', 'consistently', 'estimate', 'the', 'latent', 'community', 'structure', 'of', 'cryptocurrencies', 'network', 'that', 'accounts', 'for', 'both', 'sets', 'of', 'information', 'we', 'demonstrate', 'that', 'investors', 'can', 'achieve', 'better', 'risk', 'diversification', 'by', 'investing', 'in', 'cryptocurrencies', 'from', 'different', 'communities', 'a', 'crosssectional', 'portfolio', 'that', 'implements', 'an', 'intercrypto', 'momentum', 'trading', 'strategy', 'earns', 'a', '108', 'daily', 'return', 'by', 'dissecting', 'the', 'portfolio', 'returns', 'on', 'behavioral', 'factors', 'we', 'confirm', 'that', 'our', 'results', 'are', 'not', 'driven', 'by', 'behavioral', 'mechanisms']] | [-0.06328916910026118, 0.03279135031660988, -0.12136047208142058, 0.14557093953731182, -0.10591935060448318, -0.11518451120749564, 0.12597505124198777, 0.4646643249091701, -0.2659191849563166, -0.27788781689612685, 0.1184343701983567, -0.30661309144903565, -0.1995072063721203, 0.1802433214855389, -0.1355889037677966, 0.004194244067837423, 0.05858480834149729, -0.04079952342957954, 0.04661059524063195, -0.2812397106763881, 0.3005536513611953, 0.0639112992788813, 0.3535752220201158, 0.05113721592786992, 0.12786375870492972, -0.025509316865877013, -0.08312514233272349, 0.03318711383938441, -0.128864536742151, 0.1967235467109446, 0.3052579301157009, 0.22802641224899442, 0.4121713217578515, -0.4264728158155334, -0.19880685890006405, 0.10359571499436676, 0.049454343716274496, 0.04069473392495485, -0.005783498129441847, -0.29513491949536536, 0.025303610913873276, -0.22689308929387655, -0.035389442667016914, -0.17281088586156823, -0.00027263069212018885, 0.02931084734862061, -0.28696736342885104, 0.04780962852822077, -0.00564412866222942, 0.04783695350318416, -0.07179940021031092, -0.11483102587539111, -0.04261890277222983, 0.17067938634394625, 0.10283395446941396, -0.07289262537852095, 0.211306866911179, -0.10629218951668416, -0.2332003561379475, 0.33463673549486656, -0.06737522736287493, -0.125034005885996, 0.11584800633462582, -0.10297512261182827, -0.13046782790187084, 0.10509328632484947, 0.25732397606648577, 0.0023447450976078962, -0.21087299290419964, -0.02115267124973568, -0.02652381918454003, 0.20293549164502978, 0.04687054234635189, 0.005324055910737158, 0.20388825442076217, 0.20936102757804861, 0.11902594070383304, 0.07345587784907494, -0.058986156014725566, -0.1571655649883307, -0.17409646140289642, -0.09907637513351461, -0.13665507949679812, 0.04045785173447911, -0.18197936980256693, -0.16533822184167454, 0.429194931532735, 0.20353837178967824, 0.13630947316605074, 0.10506469444763437, 0.2666951127907383, 0.03605352965005125, 0.04358519009688747, 0.13637816714923653, 0.17863914224745653, -0.03236460029669802, 0.14311783224187583, -0.18940448028984191, 0.21678574640895718, -0.001656316762581189] |
1,802.03709 | Considerations for a Multi-beam Multi-purpose Survey with FAST | Having achieved 'first-light' right before the opening ceremony on September
25, 2016, the Five-hundred-meter Aperture Spherical radio Telescope (FAST) is
being busily commissioned. Its innovative design requires ~1000 points to be
measured and driven instead of just the two axes of motion, e.g. Azimuth and
Elevation for most of the conventional antennae, to realize pointing and
tracking. We have devised a survey plan to utilized the full sensitivity of
FAST, while minimizing the complexities in operation the system. The 19-beam L
band focal plan array will be rotated to specific angles and taking continuous
data streams while the surface shape and the focal cabin stay fixed. Such a
survey will cover the northern sky in about 220 full days. Our aim is to obtain
data for pulsar search, HI (neutral hydrogen) galaxies, HI imaging, and radio
transients, simultaneously, through multiple backends. These data sets could be
a significant contribution to all related fields in radio astronomy and remain
relevant for decades.
| astro-ph.IM astro-ph.GA | having achieved firstlight right before the opening ceremony on september 25 2016 the fivehundredmeter aperture spherical radio telescope fast is being busily commissioned its innovative design requires 1000 points to be measured and driven instead of just the two axes of motion eg azimuth and elevation for most of the conventional antennae to realize pointing and tracking we have devised a survey plan to utilized the full sensitivity of fast while minimizing the complexities in operation the system the 19beam l band focal plan array will be rotated to specific angles and taking continuous data streams while the surface shape and the focal cabin stay fixed such a survey will cover the northern sky in about 220 full days our aim is to obtain data for pulsar search hi neutral hydrogen galaxies hi imaging and radio transients simultaneously through multiple backends these data sets could be a significant contribution to all related fields in radio astronomy and remain relevant for decades | [['having', 'achieved', 'firstlight', 'right', 'before', 'the', 'opening', 'ceremony', 'on', 'september', '25', '2016', 'the', 'fivehundredmeter', 'aperture', 'spherical', 'radio', 'telescope', 'fast', 'is', 'being', 'busily', 'commissioned', 'its', 'innovative', 'design', 'requires', '1000', 'points', 'to', 'be', 'measured', 'and', 'driven', 'instead', 'of', 'just', 'the', 'two', 'axes', 'of', 'motion', 'eg', 'azimuth', 'and', 'elevation', 'for', 'most', 'of', 'the', 'conventional', 'antennae', 'to', 'realize', 'pointing', 'and', 'tracking', 'we', 'have', 'devised', 'a', 'survey', 'plan', 'to', 'utilized', 'the', 'full', 'sensitivity', 'of', 'fast', 'while', 'minimizing', 'the', 'complexities', 'in', 'operation', 'the', 'system', 'the', '19beam', 'l', 'band', 'focal', 'plan', 'array', 'will', 'be', 'rotated', 'to', 'specific', 'angles', 'and', 'taking', 'continuous', 'data', 'streams', 'while', 'the', 'surface', 'shape', 'and', 'the', 'focal', 'cabin', 'stay', 'fixed', 'such', 'a', 'survey', 'will', 'cover', 'the', 'northern', 'sky', 'in', 'about', '220', 'full', 'days', 'our', 'aim', 'is', 'to', 'obtain', 'data', 'for', 'pulsar', 'search', 'hi', 'neutral', 'hydrogen', 'galaxies', 'hi', 'imaging', 'and', 'radio', 'transients', 'simultaneously', 'through', 'multiple', 'backends', 'these', 'data', 'sets', 'could', 'be', 'a', 'significant', 'contribution', 'to', 'all', 'related', 'fields', 'in', 'radio', 'astronomy', 'and', 'remain', 'relevant', 'for', 'decades']] | [-0.10993224660123815, 0.1030445542623056, -0.022150746281840838, 0.04380368132406147, -0.1287365762036643, -0.11392296542180702, 0.03918678849877324, 0.44581569405272603, -0.22181419080952763, -0.3460089633794269, 0.17573717476407183, -0.2832360073516611, -0.05486739156185649, 0.24618289561040002, -0.03429932819017267, 0.028710133480853984, 0.07615003063037876, -0.0847758512623841, -0.05115756593004335, -0.24060677446605042, 0.21146350619528675, 0.1290290431585163, 0.24706806375907037, -0.022968709049746395, 0.13367471469100564, -0.009683154088270385, -0.0941165577783977, -0.03256971371010877, -0.07422111859123107, 0.06315025287913159, 0.30206848696107047, 0.17041714499355293, 0.2105425260728225, -0.4123378415504703, -0.13940738802048144, 0.09611841129444657, 0.13961224506083453, 0.026644140374992277, -0.020757407056953524, -0.31791158268461006, 0.05326587141607888, -0.14986694772960618, -0.17500557585008208, 0.022676740794850048, 0.019151959105511197, 0.04238642105992767, -0.20695516888226848, 0.006037008424755186, -0.017495415609300836, 0.09588373740807583, -0.07138582676052466, -0.11981134149755235, 0.006613275060226442, 0.16455894406826702, -0.008007950505634654, 0.10003566936939023, 0.14262055096623955, -0.09929212842835114, -0.0415048821552773, 0.39078529953112595, -0.001168356983544072, -0.07536583340406651, 0.17949778086112927, -0.20778063830803148, -0.1109485718421638, 0.18324530565587338, 0.21394544015056455, 0.06282451390288771, -0.17528108581755078, 0.024029685066398087, 0.02072489056736231, 0.19740622083700146, 0.10605308002996025, 0.030196054512634872, 0.2955857120803557, 0.1412090029236424, 0.12281348786927992, 0.09982456521101994, -0.2541861635298119, -0.02481542183959391, -0.22754452062981728, -0.10876378338871291, -0.13613722403897555, 0.031512347904299534, -0.051577416186864865, -0.08662948401761242, 0.4104078122982173, 0.11965886123225573, 0.1622675905848155, 0.036579112077015453, 0.3385465764586115, 0.024822368352397463, 0.13102623213781045, 0.07352309557172702, 0.2731565278605558, 0.07191588209097972, 0.15612270258716307, -0.1582512455272081, 0.013476240848831367, -0.03324084529158426] |
1,802.0371 | Simultaneous 13 cm/3 cm single-pulse observations of PSR B0329+54 | We have investigated the mode-changing properties of PSR B0329+54 using 31
epochs of simultaneous 13 cm/3 cm single-pulse observations obtained with
Shanghai Tian Ma 65 m telescope. The pulsar was found in the abnormal emission
mode 17 times, accounting for ~13% of the 41.6 hours total observation time.
Single pulse analyses indicate that mode changes took place simultaneously at
13 cm/3 cm within a few rotational periods. We detected occasional bright and
narrow pulses whose peak flux densities were 10 times higher than that of the
integrated profile in both bands. At 3 cm, about 0.66% and 0.27% of single
pulses were bright in the normal mode and abnormal mode respectively, but at 13
cm the occurrence rate was only about 0.007%. We divided the pulsar radiation
window into three components (C1, C2 and C3) corresponding to the main peaks of
the integrated profile. The bright pulses preferentially occurred at pulse
phases corresponding to the peaks of C2 and C3. Fluctuation spectra showed that
C2 had excess red noise in the normal mode, but broad quasi-periodic features
with central frequencies around 0.12 cycles/period in the abnormal mode. At 3
cm, C3 had a stronger quasi-periodic modulation centered around 0.06
cycles/period in the abnormal mode. Although there were some asymmetries in the
two-dimensional fluctuation spectra, we found no clear evidence for systematic
subpulse drifting. Consistent with previous low-frequency observations, we
found a very low nulling probability for B0329+54 with upper limits of 0.13%
and 1.68% at 13 cm/3 cm respectively.
| astro-ph.HE | we have investigated the modechanging properties of psr b032954 using 31 epochs of simultaneous 13 cm3 cm singlepulse observations obtained with shanghai tian ma 65 m telescope the pulsar was found in the abnormal emission mode 17 times accounting for 13 of the 416 hours total observation time single pulse analyses indicate that mode changes took place simultaneously at 13 cm3 cm within a few rotational periods we detected occasional bright and narrow pulses whose peak flux densities were 10 times higher than that of the integrated profile in both bands at 3 cm about 066 and 027 of single pulses were bright in the normal mode and abnormal mode respectively but at 13 cm the occurrence rate was only about 0007 we divided the pulsar radiation window into three components c1 c2 and c3 corresponding to the main peaks of the integrated profile the bright pulses preferentially occurred at pulse phases corresponding to the peaks of c2 and c3 fluctuation spectra showed that c2 had excess red noise in the normal mode but broad quasiperiodic features with central frequencies around 012 cyclesperiod in the abnormal mode at 3 cm c3 had a stronger quasiperiodic modulation centered around 006 cyclesperiod in the abnormal mode although there were some asymmetries in the twodimensional fluctuation spectra we found no clear evidence for systematic subpulse drifting consistent with previous lowfrequency observations we found a very low nulling probability for b032954 with upper limits of 013 and 168 at 13 cm3 cm respectively | [['we', 'have', 'investigated', 'the', 'modechanging', 'properties', 'of', 'psr', 'b032954', 'using', '31', 'epochs', 'of', 'simultaneous', '13', 'cm3', 'cm', 'singlepulse', 'observations', 'obtained', 'with', 'shanghai', 'tian', 'ma', '65', 'm', 'telescope', 'the', 'pulsar', 'was', 'found', 'in', 'the', 'abnormal', 'emission', 'mode', '17', 'times', 'accounting', 'for', '13', 'of', 'the', '416', 'hours', 'total', 'observation', 'time', 'single', 'pulse', 'analyses', 'indicate', 'that', 'mode', 'changes', 'took', 'place', 'simultaneously', 'at', '13', 'cm3', 'cm', 'within', 'a', 'few', 'rotational', 'periods', 'we', 'detected', 'occasional', 'bright', 'and', 'narrow', 'pulses', 'whose', 'peak', 'flux', 'densities', 'were', '10', 'times', 'higher', 'than', 'that', 'of', 'the', 'integrated', 'profile', 'in', 'both', 'bands', 'at', '3', 'cm', 'about', '066', 'and', '027', 'of', 'single', 'pulses', 'were', 'bright', 'in', 'the', 'normal', 'mode', 'and', 'abnormal', 'mode', 'respectively', 'but', 'at', '13', 'cm', 'the', 'occurrence', 'rate', 'was', 'only', 'about', '0007', 'we', 'divided', 'the', 'pulsar', 'radiation', 'window', 'into', 'three', 'components', 'c1', 'c2', 'and', 'c3', 'corresponding', 'to', 'the', 'main', 'peaks', 'of', 'the', 'integrated', 'profile', 'the', 'bright', 'pulses', 'preferentially', 'occurred', 'at', 'pulse', 'phases', 'corresponding', 'to', 'the', 'peaks', 'of', 'c2', 'and', 'c3', 'fluctuation', 'spectra', 'showed', 'that', 'c2', 'had', 'excess', 'red', 'noise', 'in', 'the', 'normal', 'mode', 'but', 'broad', 'quasiperiodic', 'features', 'with', 'central', 'frequencies', 'around', '012', 'cyclesperiod', 'in', 'the', 'abnormal', 'mode', 'at', '3', 'cm', 'c3', 'had', 'a', 'stronger', 'quasiperiodic', 'modulation', 'centered', 'around', '006', 'cyclesperiod', 'in', 'the', 'abnormal', 'mode', 'although', 'there', 'were', 'some', 'asymmetries', 'in', 'the', 'twodimensional', 'fluctuation', 'spectra', 'we', 'found', 'no', 'clear', 'evidence', 'for', 'systematic', 'subpulse', 'drifting', 'consistent', 'with', 'previous', 'lowfrequency', 'observations', 'we', 'found', 'a', 'very', 'low', 'nulling', 'probability', 'for', 'b032954', 'with', 'upper', 'limits', 'of', '013', 'and', '168', 'at', '13', 'cm3', 'cm', 'respectively']] | [-0.13987111403542732, 0.1594089569294399, -0.03838547739682923, 0.055914479560456296, -0.003678514868179374, -0.12858302951394487, 0.08031487378512363, 0.44252152506427966, -0.12591069622937617, -0.36225546672110737, 0.10937904609534098, -0.31512722467425325, 0.0011320105897119413, 0.21388539386939573, -0.014416532835127551, -0.03284122133137364, 0.03642793731605597, -0.02253847947977634, -0.049226882398790237, -0.1570744927978918, 0.16482376474024624, 0.043938021259457775, 0.249544762423722, 0.003080236808460975, 0.08554259396388161, -0.0696167253506434, -0.027644204173749878, -0.07263655432590438, -0.12036034219041311, 0.008457446166179624, 0.22818458546989934, 0.025778480679850634, 0.18693260343835844, -0.38363858980507504, -0.19177468308117543, 0.08214482160941189, 0.14135709812410782, -0.011530892546420637, -0.002166833430679462, -0.2805248950702338, 0.10853395725860589, -0.11794015909978735, -0.17721447058923182, 0.09512966866029977, 0.1167372586959709, 0.01045258014806007, -0.21071104778105068, 0.17390009928456987, 0.026550571243198557, 0.11495387086987416, -0.11212958894511647, -0.1585189437037447, -0.04855282595503683, 0.03038482855428538, 0.04289104200466932, 0.07513344815935985, 0.14189552450019993, -0.04836135932459487, -0.06381402490660548, 0.3208419714153175, -0.12889788121529167, 0.023038204220172605, 0.15867089794247377, -0.2845961866148692, -0.17464760136941396, 0.2983293082142769, 0.11918418540530706, 0.06700871569217137, -0.10420604684057377, -0.04954969922025492, 0.02554358491817346, 0.2598284285228986, 0.1590483321059827, 0.044790763648788666, 0.2631577007031362, 0.09398191353223223, 0.004347553693231992, 0.08963746069515735, -0.2842590523665009, -0.0003969757893096339, -0.2686696328366032, -0.053731096973020566, -0.09143445053600201, 0.06883487806123821, -0.09989737254166353, -0.04193508485226085, 0.42910086375808243, 0.05369458687802784, 0.20598645779096356, 0.020469774411961076, 0.2187598675851397, 0.14364029037170414, 0.0701424714445555, 0.11525043699822506, 0.3089366115405562, 0.14453066330919653, 0.14546561550333914, -0.17449091208404918, -0.012153025695805246, -0.0788834894039227] |
1,802.03711 | Kazhdan-Lusztig polynomials of fan matroids, wheel matroids and whirl
matroids | The Kazhdan-Lusztig polynomial of a matroid was introduced by Elias,
Proudfoot and Wakefield, whose properties need to be further explored. In this
paper we prove that the Kazhdan-Lusztig polynomials of fan matroids coincide
with Motzkin polynomials, which was recently conjectured by Gedeon. As a
byproduct, we determine the Kazhdan-Lusztig polynomials of graphic matroids of
squares of paths. We further obtain explicit formulas of the Kazhdan-Lusztig
polynomials of wheel matroids and whirl matroids. We prove the real-rootedness
of the Kazhdan-Lusztig polynomials of these matroids, which provides positive
evidence for a conjecture due to Gedeon, Proudfoot and Young. Based on the
results on the Kazhdan-Lusztig polynomials, we also determine the
$Z$-polynomials of fan matroids, wheel matroids and whirl matroids, and prove
their real-rootedness, which provides further evidence in support of a
conjecture of Proudfoot, Xu, and Young.
| math.CO | the kazhdanlusztig polynomial of a matroid was introduced by elias proudfoot and wakefield whose properties need to be further explored in this paper we prove that the kazhdanlusztig polynomials of fan matroids coincide with motzkin polynomials which was recently conjectured by gedeon as a byproduct we determine the kazhdanlusztig polynomials of graphic matroids of squares of paths we further obtain explicit formulas of the kazhdanlusztig polynomials of wheel matroids and whirl matroids we prove the realrootedness of the kazhdanlusztig polynomials of these matroids which provides positive evidence for a conjecture due to gedeon proudfoot and young based on the results on the kazhdanlusztig polynomials we also determine the zpolynomials of fan matroids wheel matroids and whirl matroids and prove their realrootedness which provides further evidence in support of a conjecture of proudfoot xu and young | [['the', 'kazhdanlusztig', 'polynomial', 'of', 'a', 'matroid', 'was', 'introduced', 'by', 'elias', 'proudfoot', 'and', 'wakefield', 'whose', 'properties', 'need', 'to', 'be', 'further', 'explored', 'in', 'this', 'paper', 'we', 'prove', 'that', 'the', 'kazhdanlusztig', 'polynomials', 'of', 'fan', 'matroids', 'coincide', 'with', 'motzkin', 'polynomials', 'which', 'was', 'recently', 'conjectured', 'by', 'gedeon', 'as', 'a', 'byproduct', 'we', 'determine', 'the', 'kazhdanlusztig', 'polynomials', 'of', 'graphic', 'matroids', 'of', 'squares', 'of', 'paths', 'we', 'further', 'obtain', 'explicit', 'formulas', 'of', 'the', 'kazhdanlusztig', 'polynomials', 'of', 'wheel', 'matroids', 'and', 'whirl', 'matroids', 'we', 'prove', 'the', 'realrootedness', 'of', 'the', 'kazhdanlusztig', 'polynomials', 'of', 'these', 'matroids', 'which', 'provides', 'positive', 'evidence', 'for', 'a', 'conjecture', 'due', 'to', 'gedeon', 'proudfoot', 'and', 'young', 'based', 'on', 'the', 'results', 'on', 'the', 'kazhdanlusztig', 'polynomials', 'we', 'also', 'determine', 'the', 'zpolynomials', 'of', 'fan', 'matroids', 'wheel', 'matroids', 'and', 'whirl', 'matroids', 'and', 'prove', 'their', 'realrootedness', 'which', 'provides', 'further', 'evidence', 'in', 'support', 'of', 'a', 'conjecture', 'of', 'proudfoot', 'xu', 'and', 'young']] | [-0.16150648294499628, 0.08708379925056188, -0.07095512967142793, 0.03170208945197778, -0.1432638049401619, -0.14434411554010929, 0.056152489200165426, 0.309105402438177, -0.3404258978311662, -0.2209553176433676, 0.07769814166865588, -0.16285906056011165, -0.22271573622193602, 0.17146224569943216, -0.1840520047301349, 0.04020459097292688, 0.0705778663167385, -0.01411148631186397, -0.04990632737020927, -0.35143200671386526, 0.29136503150743753, 0.05333731144114777, 0.15161958614157306, 0.09526265935489425, 0.11984311954842673, -0.007361985663710921, -0.02849517943104729, -0.021951688094823448, -0.21811527339596068, 0.16478561056363913, 0.29562802651414166, 0.16885586113893186, 0.17146071997919568, -0.3989693309283919, -0.03060221474410759, 0.14355561008883846, 0.159485140732593, 0.02559101570966757, -0.016923770198115595, -0.21409017387087698, 0.08462198568439042, -0.1514780431020039, -0.20190396030192023, -0.06609551331235303, 0.04968306493979913, 0.12115500207162566, -0.334796197567549, -0.0263457513713985, 0.17501520086769703, 0.17167269799996304, -0.02723544019067453, -0.21539017912690286, -0.02138314919408273, 0.045079644207187276, -0.05827202749335104, 0.0661736898219075, -0.030185897452584296, -0.09105311505048087, -0.24310373100279659, 0.3496217281730087, 0.048602361304478515, -0.20779358780494442, 0.1028890836958049, -0.20998793906635707, -0.20653439618785072, 0.08138220267784264, 0.08575166924684136, 0.12378256826971969, -0.0335132423279531, 0.08875346233533626, -0.2780589399341908, -0.010841786999393392, 0.2260497315476338, -0.0266200658865273, 0.15818189756461867, -0.01721528049523908, 0.030029772529033598, 0.23839690489435775, 0.05764896893804824, 0.021751962308944377, -0.23350626327511337, -0.24045845532996787, -0.13993610832840203, 0.0627134321326459, -0.1628048528565732, -0.2011112658927838, 0.38586122976460807, 0.10020916722369967, 0.10928036963774099, 0.188662753436128, 0.15882463026964277, 0.04175456373831602, 0.06203517714963743, 0.07666010693129566, 0.17966799960920105, 0.35107683291382813, 0.031162592678986214, -0.13042169967321335, 0.08545634305725495, 0.2999432034307608] |
1,802.03712 | Syntax and Semantics of Italian Poetry in the First Half of the 20th
Century | In this paper we study, analyse and comment rhetorical figures present in
some of most interesting poetry of the first half of the twentieth century.
These figures are at first traced back to some famous poet of the past and then
compared to classical Latin prose. Linguistic theory is then called in to show
how they can be represented in syntactic structures and classified as
noncanonical structures, by positioning discontinuous or displaced linguistic
elements in Spec XP projections at various levels of constituency. Then we
introduce LFG (Lexical Functional Grammar) as the theory that allows us to
connect syntactic noncanonical structures with informational structure and
psycholinguistic theories for complexity evaluation. We end up with two
computational linguistics experiments and then evaluate the results. The first
one uses best online parsers of Italian to parse poetic structures; the second
one uses Getarun, the system created at Ca Foscari Computational Linguistics
Laboratory. As will be shown, the first approach is unable to cope with these
structures due to the use of only statistical probabilistic information. On the
contrary, the second one, being a symbolic rule based system, is by far
superior and allows also to complete both semantic an pragmatic analysis.
| cs.CL | in this paper we study analyse and comment rhetorical figures present in some of most interesting poetry of the first half of the twentieth century these figures are at first traced back to some famous poet of the past and then compared to classical latin prose linguistic theory is then called in to show how they can be represented in syntactic structures and classified as noncanonical structures by positioning discontinuous or displaced linguistic elements in spec xp projections at various levels of constituency then we introduce lfg lexical functional grammar as the theory that allows us to connect syntactic noncanonical structures with informational structure and psycholinguistic theories for complexity evaluation we end up with two computational linguistics experiments and then evaluate the results the first one uses best online parsers of italian to parse poetic structures the second one uses getarun the system created at ca foscari computational linguistics laboratory as will be shown the first approach is unable to cope with these structures due to the use of only statistical probabilistic information on the contrary the second one being a symbolic rule based system is by far superior and allows also to complete both semantic an pragmatic analysis | [['in', 'this', 'paper', 'we', 'study', 'analyse', 'and', 'comment', 'rhetorical', 'figures', 'present', 'in', 'some', 'of', 'most', 'interesting', 'poetry', 'of', 'the', 'first', 'half', 'of', 'the', 'twentieth', 'century', 'these', 'figures', 'are', 'at', 'first', 'traced', 'back', 'to', 'some', 'famous', 'poet', 'of', 'the', 'past', 'and', 'then', 'compared', 'to', 'classical', 'latin', 'prose', 'linguistic', 'theory', 'is', 'then', 'called', 'in', 'to', 'show', 'how', 'they', 'can', 'be', 'represented', 'in', 'syntactic', 'structures', 'and', 'classified', 'as', 'noncanonical', 'structures', 'by', 'positioning', 'discontinuous', 'or', 'displaced', 'linguistic', 'elements', 'in', 'spec', 'xp', 'projections', 'at', 'various', 'levels', 'of', 'constituency', 'then', 'we', 'introduce', 'lfg', 'lexical', 'functional', 'grammar', 'as', 'the', 'theory', 'that', 'allows', 'us', 'to', 'connect', 'syntactic', 'noncanonical', 'structures', 'with', 'informational', 'structure', 'and', 'psycholinguistic', 'theories', 'for', 'complexity', 'evaluation', 'we', 'end', 'up', 'with', 'two', 'computational', 'linguistics', 'experiments', 'and', 'then', 'evaluate', 'the', 'results', 'the', 'first', 'one', 'uses', 'best', 'online', 'parsers', 'of', 'italian', 'to', 'parse', 'poetic', 'structures', 'the', 'second', 'one', 'uses', 'getarun', 'the', 'system', 'created', 'at', 'ca', 'foscari', 'computational', 'linguistics', 'laboratory', 'as', 'will', 'be', 'shown', 'the', 'first', 'approach', 'is', 'unable', 'to', 'cope', 'with', 'these', 'structures', 'due', 'to', 'the', 'use', 'of', 'only', 'statistical', 'probabilistic', 'information', 'on', 'the', 'contrary', 'the', 'second', 'one', 'being', 'a', 'symbolic', 'rule', 'based', 'system', 'is', 'by', 'far', 'superior', 'and', 'allows', 'also', 'to', 'complete', 'both', 'semantic', 'an', 'pragmatic', 'analysis']] | [-0.034285762727255864, 0.04245861453368496, -0.08796468708985651, 0.10367814389407294, -0.15044645372267604, -0.11454887657667401, 0.0490325534920714, 0.3717499364990041, -0.30368874535061474, -0.312936818051367, 0.06928452587483196, -0.2978958530272629, -0.1778110044731801, 0.17780815646747306, -0.10992953491392475, 0.017274504140383437, 0.05233704937896148, 0.07939902516696508, -0.055543690921648924, -0.2655366418060615, 0.31010132752179265, 0.0711960675369778, 0.2614060070242752, 0.011812809623097102, 0.09849023721819072, -0.06863909027997764, -0.06881501177960515, 0.023362673816701332, -0.099929613509367, 0.16595096496609868, 0.3066829189677075, 0.21263064947073834, 0.2959835754487626, -0.4464864601584407, -0.1458737408709216, 0.03685583620743476, 0.11811001171821227, 0.11505853845430586, 0.022705450076680764, -0.3028724759741483, 0.09922535565142818, -0.17616361228578964, -0.026196690667467902, -0.12039379965984333, -0.012653808269016256, 0.0060785447275691525, -0.16846180135569758, -0.0028270669436604636, 0.0630846836244886, 0.09007202677409812, -0.024605727126363306, -0.13173023657282332, -0.007160281416780415, 0.14855876585721572, 0.026615689726083108, 0.02400066366780852, 0.07745934008835782, -0.10663093810130311, -0.17904794591285175, 0.416042786072656, -0.048508782100480825, -0.17577039672718928, 0.21013518211285248, -0.1190945134606912, -0.19559089541801625, 0.07675307548396894, 0.1636883875279484, 0.07909350445834437, -0.14855490308300756, 0.05412668487007451, -0.01921624439262648, 0.19824652980155014, 0.1315101485162841, 0.01282359142244089, 0.17980428380409474, 0.17777575887881483, -0.003735962711501545, 0.1482012929007184, -0.04054549533366252, -0.09658561367186987, -0.2685508064519103, -0.1649013194302806, -0.1411911524090027, -0.018321039901483746, -0.050880586852034115, -0.15654086760823793, 0.3870013606478475, 0.20323707240953956, 0.16642609483746784, 0.05772796480415323, 0.29097273274263374, 0.053298861034767615, 0.0722393534018606, 0.0640392789964654, 0.17646930091671625, 0.0949678976859349, 0.12607240411665688, -0.13633163019495917, 0.07025616955447016, 0.08120572191199493] |
1,802.03713 | $\mathcal{G}$-SGD: Optimizing ReLU Neural Networks in its Positively
Scale-Invariant Space | It is well known that neural networks with rectified linear units (ReLU)
activation functions are positively scale-invariant. Conventional algorithms
like stochastic gradient descent optimize the neural networks in the vector
space of weights, which is, however, not positively scale-invariant. This
mismatch may lead to problems during the optimization process. Then, a natural
question is: \emph{can we construct a new vector space that is positively
scale-invariant and sufficient to represent ReLU neural networks so as to
better facilitate the optimization process }? In this paper, we provide our
positive answer to this question. First, we conduct a formal study on the
positive scaling operators which forms a transformation group, denoted as
$\mathcal{G}$. We show that the value of a path (i.e. the product of the
weights along the path) in the neural network is invariant to positive scaling
and prove that the value vector of all the paths is sufficient to represent the
neural networks under mild conditions. Second, we show that one can identify
some basis paths out of all the paths and prove that the linear span of their
value vectors (denoted as $\mathcal{G}$-space) is an invariant space with lower
dimension under the positive scaling group. Finally, we design stochastic
gradient descent algorithm in $\mathcal{G}$-space (abbreviated as
$\mathcal{G}$-SGD) to optimize the value vector of the basis paths of neural
networks with little extra cost by leveraging back-propagation. Our experiments
show that $\mathcal{G}$-SGD significantly outperforms the conventional SGD
algorithm in optimizing ReLU networks on benchmark datasets.
| stat.ML cs.LG | it is well known that neural networks with rectified linear units relu activation functions are positively scaleinvariant conventional algorithms like stochastic gradient descent optimize the neural networks in the vector space of weights which is however not positively scaleinvariant this mismatch may lead to problems during the optimization process then a natural question is emphcan we construct a new vector space that is positively scaleinvariant and sufficient to represent relu neural networks so as to better facilitate the optimization process in this paper we provide our positive answer to this question first we conduct a formal study on the positive scaling operators which forms a transformation group denoted as mathcalg we show that the value of a path ie the product of the weights along the path in the neural network is invariant to positive scaling and prove that the value vector of all the paths is sufficient to represent the neural networks under mild conditions second we show that one can identify some basis paths out of all the paths and prove that the linear span of their value vectors denoted as mathcalgspace is an invariant space with lower dimension under the positive scaling group finally we design stochastic gradient descent algorithm in mathcalgspace abbreviated as mathcalgsgd to optimize the value vector of the basis paths of neural networks with little extra cost by leveraging backpropagation our experiments show that mathcalgsgd significantly outperforms the conventional sgd algorithm in optimizing relu networks on benchmark datasets | [['it', 'is', 'well', 'known', 'that', 'neural', 'networks', 'with', 'rectified', 'linear', 'units', 'relu', 'activation', 'functions', 'are', 'positively', 'scaleinvariant', 'conventional', 'algorithms', 'like', 'stochastic', 'gradient', 'descent', 'optimize', 'the', 'neural', 'networks', 'in', 'the', 'vector', 'space', 'of', 'weights', 'which', 'is', 'however', 'not', 'positively', 'scaleinvariant', 'this', 'mismatch', 'may', 'lead', 'to', 'problems', 'during', 'the', 'optimization', 'process', 'then', 'a', 'natural', 'question', 'is', 'emphcan', 'we', 'construct', 'a', 'new', 'vector', 'space', 'that', 'is', 'positively', 'scaleinvariant', 'and', 'sufficient', 'to', 'represent', 'relu', 'neural', 'networks', 'so', 'as', 'to', 'better', 'facilitate', 'the', 'optimization', 'process', 'in', 'this', 'paper', 'we', 'provide', 'our', 'positive', 'answer', 'to', 'this', 'question', 'first', 'we', 'conduct', 'a', 'formal', 'study', 'on', 'the', 'positive', 'scaling', 'operators', 'which', 'forms', 'a', 'transformation', 'group', 'denoted', 'as', 'mathcalg', 'we', 'show', 'that', 'the', 'value', 'of', 'a', 'path', 'ie', 'the', 'product', 'of', 'the', 'weights', 'along', 'the', 'path', 'in', 'the', 'neural', 'network', 'is', 'invariant', 'to', 'positive', 'scaling', 'and', 'prove', 'that', 'the', 'value', 'vector', 'of', 'all', 'the', 'paths', 'is', 'sufficient', 'to', 'represent', 'the', 'neural', 'networks', 'under', 'mild', 'conditions', 'second', 'we', 'show', 'that', 'one', 'can', 'identify', 'some', 'basis', 'paths', 'out', 'of', 'all', 'the', 'paths', 'and', 'prove', 'that', 'the', 'linear', 'span', 'of', 'their', 'value', 'vectors', 'denoted', 'as', 'mathcalgspace', 'is', 'an', 'invariant', 'space', 'with', 'lower', 'dimension', 'under', 'the', 'positive', 'scaling', 'group', 'finally', 'we', 'design', 'stochastic', 'gradient', 'descent', 'algorithm', 'in', 'mathcalgspace', 'abbreviated', 'as', 'mathcalgsgd', 'to', 'optimize', 'the', 'value', 'vector', 'of', 'the', 'basis', 'paths', 'of', 'neural', 'networks', 'with', 'little', 'extra', 'cost', 'by', 'leveraging', 'backpropagation', 'our', 'experiments', 'show', 'that', 'mathcalgsgd', 'significantly', 'outperforms', 'the', 'conventional', 'sgd', 'algorithm', 'in', 'optimizing', 'relu', 'networks', 'on', 'benchmark', 'datasets']] | [-0.11954256166951321, 0.06907553437193209, -0.046011467921234575, 0.07595712432975765, -0.10095119349952185, -0.16098422680800797, 0.01847452414753418, 0.43725354108124725, -0.34650053830693683, -0.2416449155700992, 0.0844008270453051, -0.24735504825668567, -0.2635119261482877, 0.18183025745752257, -0.08709056300634742, 0.086161799753506, 0.08714842583396747, 0.061327254284811845, -0.08019959730703839, -0.297248541391131, 0.33495155868907384, 0.06205937353878657, 0.29228065678022835, 0.00992739719244037, 0.14605814459249647, -0.040398489111933965, 0.01593465339131576, 0.018477595466429644, -0.0877410945400373, 0.13882381939309885, 0.23563438232966866, 0.18022279172683622, 0.33092021621392725, -0.4015372771503118, -0.22168779149419662, 0.18822466539986107, 0.12759968270310992, 0.06676273809750013, 0.012509364670498057, -0.23280399322463394, 0.12789400839304776, -0.10202587298523341, -0.031736001005218485, -0.11827466103511078, -0.009204789296689123, 0.033260300512043026, -0.30998573111586614, 0.024727784292392613, 0.07583923648059353, 0.016836137058700268, -0.06052694032239221, -0.12419036594490014, -0.015663034832819955, 0.09691416218643042, 0.030077868694233116, 0.0904805714589847, 0.1229103350385355, -0.13248944470052187, -0.1593560774441561, 0.33017088343192247, -0.09619895723301539, -0.25143164636652254, 0.13191857469109702, -0.06986231616450883, -0.14578342021160848, 0.07106923793647361, 0.21612872263702615, 0.12064677399304924, -0.13562842124408397, 0.05210357817798984, -0.09456969428946616, 0.14235883912929484, 0.0429749882227405, 0.007649821258262109, 0.12903415060804285, 0.1719255200529247, 0.1468708857322011, 0.15216452952598017, -0.03224868881632091, -0.0911985657163857, -0.2795371738382271, -0.15185789506944258, -0.1780815198795321, 0.04003276554796375, -0.11637536017206078, -0.1881083889760046, 0.3941170834256066, 0.16128002219259568, 0.25752253911971923, 0.16788452683128727, 0.2666003593548947, 0.12659498139553127, 0.12341308342466803, 0.12127022686147776, 0.19166133901323154, 0.09611633876280636, 0.10337014832626641, -0.17455213781070889, 0.07757005010658094, 0.09623980776627096] |
1,802.03714 | Lightweight Classification of IoT Malware based on Image Recognition | The Internet of Things (IoT) is an extension of the traditional Internet,
which allows a very large number of smart devices, such as home appliances,
network cameras, sensors and controllers to connect to one another to share
information and improve user experiences. Current IoT devices are typically
micro-computers for domain-specific computations rather than traditional
functionspecific embedded devices. Therefore, many existing attacks, targeted
at traditional computers connected to the Internet, may also be directed at IoT
devices. For example, DDoS attacks have become very common in IoT environments,
as these environments currently lack basic security monitoring and protection
mechanisms, as shown by the recent Mirai and Brickerbot IoT botnets. In this
paper, we propose a novel light-weight approach for detecting DDos malware in
IoT environments.We firstly extract one-channel gray-scale images converted
from binaries, and then utilize a lightweight convolutional neural network for
classifying IoT malware families. The experimental results show that the
proposed system can achieve 94.0% accuracy for the classification of goodware
and DDoS malware, and 81.8% accuracy for the classification of goodware and two
main malware families.
| cs.CR cs.CV | the internet of things iot is an extension of the traditional internet which allows a very large number of smart devices such as home appliances network cameras sensors and controllers to connect to one another to share information and improve user experiences current iot devices are typically microcomputers for domainspecific computations rather than traditional functionspecific embedded devices therefore many existing attacks targeted at traditional computers connected to the internet may also be directed at iot devices for example ddos attacks have become very common in iot environments as these environments currently lack basic security monitoring and protection mechanisms as shown by the recent mirai and brickerbot iot botnets in this paper we propose a novel lightweight approach for detecting ddos malware in iot environmentswe firstly extract onechannel grayscale images converted from binaries and then utilize a lightweight convolutional neural network for classifying iot malware families the experimental results show that the proposed system can achieve 940 accuracy for the classification of goodware and ddos malware and 818 accuracy for the classification of goodware and two main malware families | [['the', 'internet', 'of', 'things', 'iot', 'is', 'an', 'extension', 'of', 'the', 'traditional', 'internet', 'which', 'allows', 'a', 'very', 'large', 'number', 'of', 'smart', 'devices', 'such', 'as', 'home', 'appliances', 'network', 'cameras', 'sensors', 'and', 'controllers', 'to', 'connect', 'to', 'one', 'another', 'to', 'share', 'information', 'and', 'improve', 'user', 'experiences', 'current', 'iot', 'devices', 'are', 'typically', 'microcomputers', 'for', 'domainspecific', 'computations', 'rather', 'than', 'traditional', 'functionspecific', 'embedded', 'devices', 'therefore', 'many', 'existing', 'attacks', 'targeted', 'at', 'traditional', 'computers', 'connected', 'to', 'the', 'internet', 'may', 'also', 'be', 'directed', 'at', 'iot', 'devices', 'for', 'example', 'ddos', 'attacks', 'have', 'become', 'very', 'common', 'in', 'iot', 'environments', 'as', 'these', 'environments', 'currently', 'lack', 'basic', 'security', 'monitoring', 'and', 'protection', 'mechanisms', 'as', 'shown', 'by', 'the', 'recent', 'mirai', 'and', 'brickerbot', 'iot', 'botnets', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'lightweight', 'approach', 'for', 'detecting', 'ddos', 'malware', 'in', 'iot', 'environmentswe', 'firstly', 'extract', 'onechannel', 'grayscale', 'images', 'converted', 'from', 'binaries', 'and', 'then', 'utilize', 'a', 'lightweight', 'convolutional', 'neural', 'network', 'for', 'classifying', 'iot', 'malware', 'families', 'the', 'experimental', 'results', 'show', 'that', 'the', 'proposed', 'system', 'can', 'achieve', '940', 'accuracy', 'for', 'the', 'classification', 'of', 'goodware', 'and', 'ddos', 'malware', 'and', '818', 'accuracy', 'for', 'the', 'classification', 'of', 'goodware', 'and', 'two', 'main', 'malware', 'families']] | [-0.17879671693596969, -0.002274819798499679, -0.019146327147609554, 0.04900041944611902, -0.11922043235707944, -0.24433646019579927, 0.039929872829154854, 0.37153503208273003, -0.24257862811315467, -0.34975415221097966, 0.12544522933140714, -0.33344677633704123, -0.17188258953022093, 0.27358042504585517, -0.18269304005265108, 0.08965381101271222, 0.050609238673297856, 0.015079856864758767, 0.01728335300834839, -0.2877699505664747, 0.3050490057794377, -0.014416262713811275, 0.37321671876865864, 0.05137587306407196, 0.04326536611452783, -0.03672191592936129, -0.011747911090920255, -0.05205195834886664, -0.025822002751779524, 0.14822867389408534, 0.41715882543410937, 0.21095366584433412, 0.3227248944842193, -0.4604193127597682, -0.22283471428619867, 0.09530640253400303, 0.19729769285814572, 0.09976012051712049, -0.08053265128877353, -0.38405247453325003, 0.19535307585134765, -0.30860021530481224, -0.07370798528923346, -0.09553023312896998, 0.01436111474950766, 0.05447858299190888, -0.20198087656998806, -0.06617892767214718, -0.01930431450785942, 0.05857705036495728, -0.005367223789190492, -0.06593876386481994, 0.01640759176701646, 0.16854904933345757, 0.02885247525141081, -0.030666684854209467, 0.2345078539351975, -0.16687234920126767, -0.15725420086528175, 0.322670581894768, 0.04953291642951543, -0.10255701627333606, 0.21096197173888373, 0.048129010061860426, -0.16217780583908528, 0.0708210560395938, 0.2712453173907389, 0.11272433032453674, -0.22335381193128837, -0.0377693533896077, 0.032845794174301605, 0.17123820289270952, 0.046932895327865314, 0.08656179274707525, 0.20714829891221598, 0.2599838419727431, 0.12669981039884573, 0.08714564208207776, -0.09325221098631366, -0.025271989055909216, -0.15460433896673334, -0.15364644934148106, -0.1776730721017388, 0.02804021554766223, -0.0816243349604933, -0.15190942305591967, 0.38519545345546, 0.2479632610848057, 0.13604167678964918, 0.09441955891353163, 0.43333516643509606, -0.03837801641400967, 0.16599280492466112, 0.1365980389051732, 0.16198311232040974, -0.009698212195706385, 0.206311762483727, -0.08330230362877376, 0.12696572544105453, -0.01796728008775972] |
1,802.03715 | Defect-Free Carbon Nanotube Coils | Carbon nanotubes are promising building blocks for various nanoelectronic
components. A highly desirable geometry for such applications is a coil.
However, coiled nanotube structures reported so far were inherently defective
or had no free ends accessible for contacting. Here we demonstrate the
spontaneous self-coiling of single-wall carbon nanotubes into defect-free coils
of up to more than 70 turns with identical diameter and chirality, and free
ends. We characterize the structure, formation mechanism, and electrical
properties of these coils by different microscopies, molecular dynamics
simulations, Raman spectroscopy, and electrical and magnetic measurements. The
coils are highly conductive, as expected for defect-free carbon nanotubes, but
adjacent nanotube segments in the coil are more highly coupled than in regular
bundles of single-wall carbon nanotubes, owing to their perfect crystal
momentum matching, which enables tunneling between the turns. Although this
behavior does not yet enable the performance of these nanotube coils as
inductive devices, it does point a clear path for their realization. Hence,
this study represents a major step toward the production of many different
nanotube coil devices, including inductors, electromagnets, transformers, and
dynamos.
| cond-mat.mes-hall | carbon nanotubes are promising building blocks for various nanoelectronic components a highly desirable geometry for such applications is a coil however coiled nanotube structures reported so far were inherently defective or had no free ends accessible for contacting here we demonstrate the spontaneous selfcoiling of singlewall carbon nanotubes into defectfree coils of up to more than 70 turns with identical diameter and chirality and free ends we characterize the structure formation mechanism and electrical properties of these coils by different microscopies molecular dynamics simulations raman spectroscopy and electrical and magnetic measurements the coils are highly conductive as expected for defectfree carbon nanotubes but adjacent nanotube segments in the coil are more highly coupled than in regular bundles of singlewall carbon nanotubes owing to their perfect crystal momentum matching which enables tunneling between the turns although this behavior does not yet enable the performance of these nanotube coils as inductive devices it does point a clear path for their realization hence this study represents a major step toward the production of many different nanotube coil devices including inductors electromagnets transformers and dynamos | [['carbon', 'nanotubes', 'are', 'promising', 'building', 'blocks', 'for', 'various', 'nanoelectronic', 'components', 'a', 'highly', 'desirable', 'geometry', 'for', 'such', 'applications', 'is', 'a', 'coil', 'however', 'coiled', 'nanotube', 'structures', 'reported', 'so', 'far', 'were', 'inherently', 'defective', 'or', 'had', 'no', 'free', 'ends', 'accessible', 'for', 'contacting', 'here', 'we', 'demonstrate', 'the', 'spontaneous', 'selfcoiling', 'of', 'singlewall', 'carbon', 'nanotubes', 'into', 'defectfree', 'coils', 'of', 'up', 'to', 'more', 'than', '70', 'turns', 'with', 'identical', 'diameter', 'and', 'chirality', 'and', 'free', 'ends', 'we', 'characterize', 'the', 'structure', 'formation', 'mechanism', 'and', 'electrical', 'properties', 'of', 'these', 'coils', 'by', 'different', 'microscopies', 'molecular', 'dynamics', 'simulations', 'raman', 'spectroscopy', 'and', 'electrical', 'and', 'magnetic', 'measurements', 'the', 'coils', 'are', 'highly', 'conductive', 'as', 'expected', 'for', 'defectfree', 'carbon', 'nanotubes', 'but', 'adjacent', 'nanotube', 'segments', 'in', 'the', 'coil', 'are', 'more', 'highly', 'coupled', 'than', 'in', 'regular', 'bundles', 'of', 'singlewall', 'carbon', 'nanotubes', 'owing', 'to', 'their', 'perfect', 'crystal', 'momentum', 'matching', 'which', 'enables', 'tunneling', 'between', 'the', 'turns', 'although', 'this', 'behavior', 'does', 'not', 'yet', 'enable', 'the', 'performance', 'of', 'these', 'nanotube', 'coils', 'as', 'inductive', 'devices', 'it', 'does', 'point', 'a', 'clear', 'path', 'for', 'their', 'realization', 'hence', 'this', 'study', 'represents', 'a', 'major', 'step', 'toward', 'the', 'production', 'of', 'many', 'different', 'nanotube', 'coil', 'devices', 'including', 'inductors', 'electromagnets', 'transformers', 'and', 'dynamos']] | [-0.16516423813041506, 0.18671055357327632, 0.013899399442016147, -0.03975434591961352, -0.06060101351597243, -0.21158347455137927, 0.04410128129594442, 0.5154920855174876, -0.2212092172417518, -0.292368941122873, 0.036437711876351385, -0.2799046220568319, -0.1277179904657209, 0.2293571994937439, -0.004058543684530175, 0.033599643709345, 0.08268137116019716, -0.037615978001202977, -0.007261777891673976, -0.1464095496721307, 0.19875700235522042, 0.08029230375541374, 0.3856458578413973, 0.08001723257669559, 0.05950241123274383, -0.044615449611511496, 0.06360522142850743, 0.06345196798857715, -0.14053315553594278, 0.11487005348317325, 0.2611108142416924, -0.06879097401267953, 0.2056450134479544, -0.551943201582051, -0.18495063518380953, 0.05398958225511403, 0.19225532786537466, 0.14373953101005302, -0.024726192390436254, -0.2127826849923521, 0.11517888216379409, -0.11331775484917064, -0.10731621252149731, -0.08418309500816071, 0.029930232908938908, 0.03939896769394788, -0.18583543150743936, 0.0015379527053381835, 0.053253519118556546, 0.06335171512243203, -0.045027508092041695, -0.13196066507888543, -0.06271775568537931, 0.10686774875179658, 0.008577966779315223, -0.043406728177797047, 0.28958864263905626, -0.1377262154872167, -0.09009870447011457, 0.38287980045942177, 0.026652775935589387, -0.12470523634822005, 0.1945130610282326, -0.11542921582909507, -0.06862037033877438, 0.16207185106921113, 0.07148994406032014, 0.1363051335663638, -0.20217786687976008, -0.01501908385156033, 0.02751819277440922, 0.14254819932603924, 0.12775681741380443, 0.07376195565577492, 0.3093962070660281, 0.22593028492734044, 0.04856776951504192, 0.16608788798718402, -0.09459096104061852, -0.030988988549345068, -0.19386573648581462, -0.22596234423464112, -0.14628028120949035, 0.12323881796595136, -0.04838777040082884, -0.24510196798817357, 0.36243422109142154, 0.08298195590937717, 0.1454938365612179, -0.011387381570077397, 0.29586110745246214, 0.0034211069972823476, 0.15372861803302335, -0.0030200501722801062, 0.2549196311298551, 0.2291410177040638, 0.07788075025115783, -0.1858133192290552, 0.06576814618828293, -0.05395800292867029] |
1,802.03716 | Bimodal logics with contingency and accident | Contingency and accident are two important notions in philosophy and
philosophical logic. Their meanings are so close that they are mixed sometimes,
in both everyday discourse and academic research. This indicates that it is
necessary to study them in a unified framework. However, there has been no
logical research on them together. In this paper, we propose a language of a
bimodal logic with these two concepts, investigate its model-theoretical
properties such as expressivity and frame definability. We axiomatize this
logic over various classes of frames, whose completeness proofs are shown with
the help of a crucial schema. The interactions between contingency and accident
can sharpen our understanding of both notions. Then we extend the logic to a
dynamic case: public announcements. By finding the required reduction axioms,
we obtain a complete axiomatization, which gives us a good application to Moore
sentences.
| math.LO cs.LO | contingency and accident are two important notions in philosophy and philosophical logic their meanings are so close that they are mixed sometimes in both everyday discourse and academic research this indicates that it is necessary to study them in a unified framework however there has been no logical research on them together in this paper we propose a language of a bimodal logic with these two concepts investigate its modeltheoretical properties such as expressivity and frame definability we axiomatize this logic over various classes of frames whose completeness proofs are shown with the help of a crucial schema the interactions between contingency and accident can sharpen our understanding of both notions then we extend the logic to a dynamic case public announcements by finding the required reduction axioms we obtain a complete axiomatization which gives us a good application to moore sentences | [['contingency', 'and', 'accident', 'are', 'two', 'important', 'notions', 'in', 'philosophy', 'and', 'philosophical', 'logic', 'their', 'meanings', 'are', 'so', 'close', 'that', 'they', 'are', 'mixed', 'sometimes', 'in', 'both', 'everyday', 'discourse', 'and', 'academic', 'research', 'this', 'indicates', 'that', 'it', 'is', 'necessary', 'to', 'study', 'them', 'in', 'a', 'unified', 'framework', 'however', 'there', 'has', 'been', 'no', 'logical', 'research', 'on', 'them', 'together', 'in', 'this', 'paper', 'we', 'propose', 'a', 'language', 'of', 'a', 'bimodal', 'logic', 'with', 'these', 'two', 'concepts', 'investigate', 'its', 'modeltheoretical', 'properties', 'such', 'as', 'expressivity', 'and', 'frame', 'definability', 'we', 'axiomatize', 'this', 'logic', 'over', 'various', 'classes', 'of', 'frames', 'whose', 'completeness', 'proofs', 'are', 'shown', 'with', 'the', 'help', 'of', 'a', 'crucial', 'schema', 'the', 'interactions', 'between', 'contingency', 'and', 'accident', 'can', 'sharpen', 'our', 'understanding', 'of', 'both', 'notions', 'then', 'we', 'extend', 'the', 'logic', 'to', 'a', 'dynamic', 'case', 'public', 'announcements', 'by', 'finding', 'the', 'required', 'reduction', 'axioms', 'we', 'obtain', 'a', 'complete', 'axiomatization', 'which', 'gives', 'us', 'a', 'good', 'application', 'to', 'moore', 'sentences']] | [-0.07904190486534761, 0.03928810988985736, -0.10442538814894645, 0.150637902429288, -0.1580826582938013, -0.11804445031177725, 0.08353885164948403, 0.4112908305915099, -0.26003554368942555, -0.31938024533545256, 0.07953568631176457, -0.25763011164635313, -0.15651967069527634, 0.16502436537715331, -0.16720119224612037, 0.02927890977072923, 0.033268278894263884, 0.06741810641513848, -0.0632802866994482, -0.267503989145527, 0.29321913525435916, -0.015069081551316654, 0.2769887218904406, 0.07827976148929709, 0.07076846901655302, -0.0026025181852648376, -0.046664321486851276, 0.04627823106236231, -0.12519098583883098, 0.17296245825988515, 0.38411900650342584, 0.24041752930579732, 0.34649599776406526, -0.43134870149955995, -0.15210758524448414, 0.10262282532443043, 0.06659390628551015, 0.11477883620774636, 0.0023493174042119843, -0.3077202315989908, 0.07193847053723645, -0.19952390419358623, -0.04178754968280104, -0.13326402015747948, 0.05206592580382253, 0.012819275323918062, -0.19963138604751446, -0.03293893932246826, 0.1905243741413972, 0.13041915129345488, -0.043023502356192414, -0.07175191396086568, 0.029437904614253416, 0.13303296842848436, 0.03943211033212309, 0.0028786021743861722, 0.07346164195513039, -0.09272367134280371, -0.18160683706625771, 0.3848409550690787, 0.029868395141535768, -0.19134856361082533, 0.21054697127088012, -0.0853328590845348, -0.18128333596224097, 0.027965659892160287, 0.1293524253824857, 0.07306195863745582, -0.1478773945070226, 0.06838589217177671, -0.06613453590101234, 0.17170194954886822, 0.1155100775305444, 0.07064026166130723, 0.23605187510838732, 0.1904571638098249, 0.011997035399577777, 0.14914908657886716, 0.030961232887446538, -0.12382876161407207, -0.32074582528218, -0.16180543563145042, -0.0658036030625636, -0.0007856533893188921, -0.05539360966705176, -0.15380713542407662, 0.3813333421934094, 0.2108047458205477, 0.1430320732400451, 0.11015269854581508, 0.2816465910471661, 0.04720800142148247, 0.07110958487208618, 0.04146496671199484, 0.18243338793358752, 0.14076053708772057, 0.12182507418919171, -0.10940497836858874, 0.10622997440948663, 0.05149640832063545] |
1,802.03717 | Localized peaking regimes for quasilinear parabolic equations | This paper deals with the asymptotic behavior as $t\rightarrow T<\infty$ of
all weak (energy) solutions of a class of equations with the following model
representative: \begin{equation*}
(|u|^{p-1}u)_t-\Delta_p(u)+b(t,x)|u|^{\lambda-1}u=0 \quad
(t,x)\in(0,T)\times\Omega,\,\Omega\in{R}^n,\,n>1, \end{equation*} with
prescribed global energy function \begin{equation*}
E(t):=\int_{\Omega}|u(t,x)|^{p+1}dx+
\int_0^t\int_{\Omega}|\nabla_xu(\tau,x)|^{p+1}dxd\tau \rightarrow\infty\ \text{
as }t\rightarrow T. \end{equation*} Here
$\Delta_p(u)=\sum_{i=1}^n\left(|\nabla_xu|^{p-1}u_{x_i}\right)_{x_i}$, $p>0$,
$\lambda>p$, $\Omega$ is a bounded smooth domain, $b(t,x)\geq0$. Particularly,
in the case \begin{equation*} E(t)\leq
F_\mu(t)=\exp\left(\omega(T-t)^{-\frac1{p+\mu}}\right)\quad\forall\,t<T,\,\mu>0,\,\omega>0,
\end{equation*} it is proved that solution $u$ remains uniformly bounded as
$t\rightarrow T$ in an arbitrary subdomain
$\Omega_0\subset\Omega:\overline{\Omega}_0\subset\Omega$ and the sharp upper
estimate of $u(t,x)$ when $t\rightarrow T$ has been obtained depending on
$\mu>0$ and $s=dist(x,\partial\Omega)$. In the case $b(t,x)>0$
$\forall\,(t,x)\in(0,T)\times\Omega$ sharp sufficient conditions on
degeneration of $b(t,x)$ near $t=T$ that guarantee mentioned above boundedness
for arbitrary (even large) solution have been found and the sharp upper
estimate of a final profile of solution when $t\rightarrow T$ has been
obtained.
| math.AP | this paper deals with the asymptotic behavior as trightarrow tinfty of all weak energy solutions of a class of equations with the following model representative beginequation up1u_tdelta_pubtxulambda1u0 quad txin0ttimesomegaomegainrnn1 endequation with prescribed global energy function beginequation etint_omegautxp1dx int_0tint_omeganabla_xutauxp1dxdtau rightarrowinfty text as trightarrow t endequation here delta_pusum_i1nleftnabla_xup1u_x_iright_x_i p0 lambdap omega is a bounded smooth domain btxgeq0 particularly in the case beginequation etleq f_mutexpleftomegattfrac1pmurightquadforallttmu0omega0 endequation it is proved that solution u remains uniformly bounded as trightarrow t in an arbitrary subdomain omega_0subsetomegaoverlineomega_0subsetomega and the sharp upper estimate of utx when trightarrow t has been obtained depending on mu0 and sdistxpartialomega in the case btx0 foralltxin0ttimesomega sharp sufficient conditions on degeneration of btx near tt that guarantee mentioned above boundedness for arbitrary even large solution have been found and the sharp upper estimate of a final profile of solution when trightarrow t has been obtained | [['this', 'paper', 'deals', 'with', 'the', 'asymptotic', 'behavior', 'as', 'trightarrow', 'tinfty', 'of', 'all', 'weak', 'energy', 'solutions', 'of', 'a', 'class', 'of', 'equations', 'with', 'the', 'following', 'model', 'representative', 'beginequation', 'up1u_tdelta_pubtxulambda1u0', 'quad', 'txin0ttimesomegaomegainrnn1', 'endequation', 'with', 'prescribed', 'global', 'energy', 'function', 'beginequation', 'etint_omegautxp1dx', 'int_0tint_omeganabla_xutauxp1dxdtau', 'rightarrowinfty', 'text', 'as', 'trightarrow', 't', 'endequation', 'here', 'delta_pusum_i1nleftnabla_xup1u_x_iright_x_i', 'p0', 'lambdap', 'omega', 'is', 'a', 'bounded', 'smooth', 'domain', 'btxgeq0', 'particularly', 'in', 'the', 'case', 'beginequation', 'etleq', 'f_mutexpleftomegattfrac1pmurightquadforallttmu0omega0', 'endequation', 'it', 'is', 'proved', 'that', 'solution', 'u', 'remains', 'uniformly', 'bounded', 'as', 'trightarrow', 't', 'in', 'an', 'arbitrary', 'subdomain', 'omega_0subsetomegaoverlineomega_0subsetomega', 'and', 'the', 'sharp', 'upper', 'estimate', 'of', 'utx', 'when', 'trightarrow', 't', 'has', 'been', 'obtained', 'depending', 'on', 'mu0', 'and', 'sdistxpartialomega', 'in', 'the', 'case', 'btx0', 'foralltxin0ttimesomega', 'sharp', 'sufficient', 'conditions', 'on', 'degeneration', 'of', 'btx', 'near', 'tt', 'that', 'guarantee', 'mentioned', 'above', 'boundedness', 'for', 'arbitrary', 'even', 'large', 'solution', 'have', 'been', 'found', 'and', 'the', 'sharp', 'upper', 'estimate', 'of', 'a', 'final', 'profile', 'of', 'solution', 'when', 'trightarrow', 't', 'has', 'been', 'obtained']] | [-0.1693779608458707, 0.0818099901196769, -0.0141910458132909, 0.025087641464112652, -0.033682954271914055, -0.20807249829500118, -0.009752011611766203, 0.3080250540364335, -0.2933204265325579, -0.19479950856531167, 0.16063513508944538, -0.3589641977961794, -0.03724952931569193, 0.18295495162046166, -0.05033839878960306, 0.11933369819743146, 0.0270535686081773, 0.14153065256603803, -0.05344364377012377, -0.1971455087791062, 0.29080937955642244, -0.10357446237360589, 0.203758987903878, 0.09161638129255485, 0.09057796201562039, -0.05882013354535776, 0.10116664574566858, -0.02140053080880076, -0.28609022188219435, -0.05856265486680142, 0.2449602173918588, 0.05243236847303609, 0.29374672491672155, -0.3409990558955278, -0.16136492968035707, 0.2010997452822919, 0.22237593030116257, -0.019641517056996457, -0.011689342091833988, -0.2908714468349198, 0.15438355792839017, -0.06877538807803893, -0.1912512960950382, -0.05137647650353895, 0.08781525102188058, 0.07982151443316451, -0.37497717791898105, 0.11953582791327179, 0.12897011217970458, 0.01895913248659531, -0.11496836096688196, -0.1724593527703937, -0.05371693582522846, 0.06823826365338155, 0.0764007751326937, 0.15193944161612086, 0.017359112195656386, -0.1459140330677468, 0.037507727486259156, 0.2929322009209458, -0.15509425690362075, -0.2158378283173301, 0.08942207011646584, -0.2104528254033102, -0.1535845019833277, 0.0912041765112716, 0.12631209900705784, 0.22130810949979848, -0.1440892064891034, 0.25516590647593157, -0.05986453496445795, 0.12444564659958919, 0.13589172951080872, 0.0055639514297900995, 0.04200883669323707, 0.1343463304388614, 0.13989981352031686, 0.13225902175488136, -0.011454243096078653, -0.02602082103284659, -0.3883052982091335, -0.13215191577177296, -0.1613938148775074, 0.15760103975180964, -0.08429183210888326, -0.17060056032314327, 0.27916216757148504, 0.05901757041027926, 0.2548847487018593, 0.10229651672225304, 0.21016023557576288, 0.19215198462866317, -0.057083074472673974, 0.0991870691743857, 0.14198843400946726, 0.12075313618619933, 0.16628157057379947, -0.19814362583987644, 0.083414675294642, 0.11500000209038373] |
1,802.03718 | Parametrization of quantum states and the quantum state discrimination
problem | A discrimination problem consists of $N$ linearly independent pure quantum
states $\Phi=\{\ket{\phi_i}\}$ and the corresponding occurrence probabilities
$\eta=\{\eta_i\}$. To any such problem we associate, up to a permutation over
the probabilities $\{\eta_i\}$, a unique pair of density matrices
$\boldsymbol{\rho_{_{T}}}$ and $\boldsymbol{\eta_{{p}}}$ defined on the
$N$-dimensional Hilbert space $\mathcal{H}_N$. The first one,
$\boldsymbol{\rho_{_{T}}}$, provides a new parametrization of a generic
full-rank density matrix in terms of the parameters of the discrimination
problem, i.e. the mutual overlaps $\gamma_{ij}=\bra{\phi_i}\phi_j\rangle$ and
the occurrence probabilities $\{\eta_i\}$. The second one is defined as a
diagonal density matrix $\boldsymbol{\eta_p}$ with the diagonal entries given
by the probabilities $\{\eta_i\}$ with the ordering induced by the permutation
$p$ of the probabilities. $\boldsymbol{\rho_{_{T}}}$ and
$\boldsymbol{\eta_{{p}}}$ capture information about the quantum and classical
versions of the discrimination problem, respectively. In this sense, when the
set $\Phi$ can be discriminated unambiguously with probability one, i.e. when
the states to be discriminated are mutually orthogonal and can be distinguished
by a classical observer, then $\boldsymbol{\rho_{_{T}}}\rightarrow
\boldsymbol{\eta_{{p}}}$. Moreover, if the set lacks its independency and
cannot be discriminated anymore the distinguishability of the pair, measured by
the fidelity $F(\boldsymbol{\rho_{_{T}}}, \boldsymbol{\eta_{{p}}})$, becomes
minimum. This enables one to associate to each discrimination problem a measure
of discriminability defined by the fidelity $F(\boldsymbol{\rho_{_{T}}},
\boldsymbol{\eta_{{p}}})$. This quantity, has the advantage of being easy to
calculate and in this respect it can find useful applications in estimating the
extent to which the set is discriminable.
| quant-ph | a discrimination problem consists of n linearly independent pure quantum states phiketphi_i and the corresponding occurrence probabilities etaeta_i to any such problem we associate up to a permutation over the probabilities eta_i a unique pair of density matrices boldsymbolrho__t and boldsymboleta_p defined on the ndimensional hilbert space mathcalh_n the first one boldsymbolrho__t provides a new parametrization of a generic fullrank density matrix in terms of the parameters of the discrimination problem ie the mutual overlaps gamma_ijbraphi_iphi_jrangle and the occurrence probabilities eta_i the second one is defined as a diagonal density matrix boldsymboleta_p with the diagonal entries given by the probabilities eta_i with the ordering induced by the permutation p of the probabilities boldsymbolrho__t and boldsymboleta_p capture information about the quantum and classical versions of the discrimination problem respectively in this sense when the set phi can be discriminated unambiguously with probability one ie when the states to be discriminated are mutually orthogonal and can be distinguished by a classical observer then boldsymbolrho__trightarrow boldsymboleta_p moreover if the set lacks its independency and cannot be discriminated anymore the distinguishability of the pair measured by the fidelity fboldsymbolrho__t boldsymboleta_p becomes minimum this enables one to associate to each discrimination problem a measure of discriminability defined by the fidelity fboldsymbolrho__t boldsymboleta_p this quantity has the advantage of being easy to calculate and in this respect it can find useful applications in estimating the extent to which the set is discriminable | [['a', 'discrimination', 'problem', 'consists', 'of', 'n', 'linearly', 'independent', 'pure', 'quantum', 'states', 'phiketphi_i', 'and', 'the', 'corresponding', 'occurrence', 'probabilities', 'etaeta_i', 'to', 'any', 'such', 'problem', 'we', 'associate', 'up', 'to', 'a', 'permutation', 'over', 'the', 'probabilities', 'eta_i', 'a', 'unique', 'pair', 'of', 'density', 'matrices', 'boldsymbolrho__t', 'and', 'boldsymboleta_p', 'defined', 'on', 'the', 'ndimensional', 'hilbert', 'space', 'mathcalh_n', 'the', 'first', 'one', 'boldsymbolrho__t', 'provides', 'a', 'new', 'parametrization', 'of', 'a', 'generic', 'fullrank', 'density', 'matrix', 'in', 'terms', 'of', 'the', 'parameters', 'of', 'the', 'discrimination', 'problem', 'ie', 'the', 'mutual', 'overlaps', 'gamma_ijbraphi_iphi_jrangle', 'and', 'the', 'occurrence', 'probabilities', 'eta_i', 'the', 'second', 'one', 'is', 'defined', 'as', 'a', 'diagonal', 'density', 'matrix', 'boldsymboleta_p', 'with', 'the', 'diagonal', 'entries', 'given', 'by', 'the', 'probabilities', 'eta_i', 'with', 'the', 'ordering', 'induced', 'by', 'the', 'permutation', 'p', 'of', 'the', 'probabilities', 'boldsymbolrho__t', 'and', 'boldsymboleta_p', 'capture', 'information', 'about', 'the', 'quantum', 'and', 'classical', 'versions', 'of', 'the', 'discrimination', 'problem', 'respectively', 'in', 'this', 'sense', 'when', 'the', 'set', 'phi', 'can', 'be', 'discriminated', 'unambiguously', 'with', 'probability', 'one', 'ie', 'when', 'the', 'states', 'to', 'be', 'discriminated', 'are', 'mutually', 'orthogonal', 'and', 'can', 'be', 'distinguished', 'by', 'a', 'classical', 'observer', 'then', 'boldsymbolrho__trightarrow', 'boldsymboleta_p', 'moreover', 'if', 'the', 'set', 'lacks', 'its', 'independency', 'and', 'can', 'not', 'be', 'discriminated', 'anymore', 'the', 'distinguishability', 'of', 'the', 'pair', 'measured', 'by', 'the', 'fidelity', 'fboldsymbolrho__t', 'boldsymboleta_p', 'becomes', 'minimum', 'this', 'enables', 'one', 'to', 'associate', 'to', 'each', 'discrimination', 'problem', 'a', 'measure', 'of', 'discriminability', 'defined', 'by', 'the', 'fidelity', 'fboldsymbolrho__t', 'boldsymboleta_p', 'this', 'quantity', 'has', 'the', 'advantage', 'of', 'being', 'easy', 'to', 'calculate', 'and', 'in', 'this', 'respect', 'it', 'can', 'find', 'useful', 'applications', 'in', 'estimating', 'the', 'extent', 'to', 'which', 'the', 'set', 'is', 'discriminable']] | [-0.10945681453525245, 0.1603663902053432, -0.06319863135519224, 0.04944205794834181, -0.02368071811370455, -0.1476049318695965, 0.06004289285888597, 0.3223756107802047, -0.31300723281370485, -0.26670071473813844, 0.08308647773949251, -0.2736220262517338, -0.09726358468652384, 0.13421059183340955, -0.07089928931201853, 0.047233649837689726, 0.04680746892322, 0.13627113946169228, -0.1060593762945029, -0.23061191679726384, 0.32633489848505626, 0.027225789404373407, 0.2636634224140815, 0.01133450132984168, 0.11140392811815718, 0.03986825854658629, -0.008772801880238908, 0.022384423187916728, -0.09459212542817932, 0.11086994276212697, 0.25543390691897216, 0.18233857781535445, 0.24585759013617065, -0.33208538663525183, -0.15462824561858945, 0.19102637430333463, 0.10603907807640434, 0.07219676273014171, 0.0333020749246879, -0.3161516618568176, 0.09063424663094086, -0.1531761460191695, -0.11310125107260106, -0.05401361170849759, 0.021624317299977783, -0.017757741480388424, -0.3125218304853838, 0.05069871382481415, 0.044073632706382045, -0.01062090252626897, 0.0043241910407626075, -0.09639089455368458, -0.01703124384907804, 0.13224857720245056, -0.0019119398676471792, 0.040391651134901715, 0.09695759670303941, -0.08978692700308284, -0.1333546564310539, 0.3627270839027899, -0.04442256879241879, -0.264921719164011, 0.12813968752869667, -0.14803602994980042, -0.07655507326730854, 0.11120030630754864, 0.10149879654409824, 0.09034288700799019, -0.12368017373439247, 0.0766998503812754, -0.057832187754747126, 0.16603543135101678, 0.08331842395352014, 0.058011873992103516, 0.2055175292539487, 0.07436413383786668, 0.08954637904487171, 0.14484387583117447, -0.06494949741825236, -0.06609687494573654, -0.30167563256376234, -0.17708178820870654, -0.2277390866719783, 0.06739154738255371, -0.09336725928774305, -0.14521696568099837, 0.4086256481130563, 0.1001535721170591, 0.23867874956403523, 0.0459887688113699, 0.24673357424910838, 0.15225368188067945, 0.029687176735212952, 0.0586024059035142, 0.1796915110490926, 0.15181483082106392, -0.01717539907573446, -0.2137077057299968, 0.12433231391569043, 0.061398142260334] |
1,802.03719 | Encoding and avoiding 2-connected patterns in polygon dissections and
outerplanar graphs | Let $\Delta =\{ \delta_1,\delta_2,...,\delta_m \} $ be a finite set of
2-connected patterns, i.e. graphs up to vertex relabelling. We study the
generating function $D_{\Delta }(z,u_1,u_2,...,u_m),$ which counts polygon
dissections and marks subgraph copies of $\delta_i$ with the variable $u_i$. We
prove that this is always algebraic, through an explicit combinatorial
decomposition depending on $\Delta $. The decomposition also gives a defining
system for $D_{\Delta }(z,\mathbf{0})$, which encodes polygon dissections that
restrict these patterns as subgraphs. In this way, we are able to extract
normal limit laws for the patterns when they are encoded, and perform
asymptotic enumeration of the resulting classes when they are avoided. The
results can be directly transferred in the case of labelled outerplanar graphs.
We give examples and compute the relevant constants when the patterns are small
cycles or dissections.
| math.CO | let delta delta_1delta_2delta_m be a finite set of 2connected patterns ie graphs up to vertex relabelling we study the generating function d_delta zu_1u_2u_m which counts polygon dissections and marks subgraph copies of delta_i with the variable u_i we prove that this is always algebraic through an explicit combinatorial decomposition depending on delta the decomposition also gives a defining system for d_delta zmathbf0 which encodes polygon dissections that restrict these patterns as subgraphs in this way we are able to extract normal limit laws for the patterns when they are encoded and perform asymptotic enumeration of the resulting classes when they are avoided the results can be directly transferred in the case of labelled outerplanar graphs we give examples and compute the relevant constants when the patterns are small cycles or dissections | [['let', 'delta', 'delta_1delta_2delta_m', 'be', 'a', 'finite', 'set', 'of', '2connected', 'patterns', 'ie', 'graphs', 'up', 'to', 'vertex', 'relabelling', 'we', 'study', 'the', 'generating', 'function', 'd_delta', 'zu_1u_2u_m', 'which', 'counts', 'polygon', 'dissections', 'and', 'marks', 'subgraph', 'copies', 'of', 'delta_i', 'with', 'the', 'variable', 'u_i', 'we', 'prove', 'that', 'this', 'is', 'always', 'algebraic', 'through', 'an', 'explicit', 'combinatorial', 'decomposition', 'depending', 'on', 'delta', 'the', 'decomposition', 'also', 'gives', 'a', 'defining', 'system', 'for', 'd_delta', 'zmathbf0', 'which', 'encodes', 'polygon', 'dissections', 'that', 'restrict', 'these', 'patterns', 'as', 'subgraphs', 'in', 'this', 'way', 'we', 'are', 'able', 'to', 'extract', 'normal', 'limit', 'laws', 'for', 'the', 'patterns', 'when', 'they', 'are', 'encoded', 'and', 'perform', 'asymptotic', 'enumeration', 'of', 'the', 'resulting', 'classes', 'when', 'they', 'are', 'avoided', 'the', 'results', 'can', 'be', 'directly', 'transferred', 'in', 'the', 'case', 'of', 'labelled', 'outerplanar', 'graphs', 'we', 'give', 'examples', 'and', 'compute', 'the', 'relevant', 'constants', 'when', 'the', 'patterns', 'are', 'small', 'cycles', 'or', 'dissections']] | [-0.14668014612107072, 0.1516397517053747, -0.07054670311481459, 0.06711103377438121, -0.11522072528896388, -0.13036205505341059, 0.07783750667658751, 0.35708852361130994, -0.3259356749476865, -0.2996101320604794, 0.10659367924199614, -0.3179286210688588, -0.1510213851233857, 0.16421066762086411, -0.09568877262699971, -0.023550989145405765, 0.10011869608547386, 0.06985603388784511, -0.03294686665225299, -0.25245268929211306, 0.3075406877032947, -0.06463033434556564, 0.20415831194986822, 0.036939246849215124, 0.09495045084986486, 0.0014354315080709057, -0.0050321820672252215, 0.04991266963952512, -0.18929348592484985, 0.08862531864542689, 0.27690915691346163, 0.13408574306413357, 0.16733095832751133, -0.4197801254285878, -0.11352449972400791, 0.21624779335979838, 0.18471458923431783, 0.1118635000584618, 0.038883540970346075, -0.22629441739081813, 0.13690616056555882, -0.08331455651568831, -0.11543050208638306, -0.12890023180347043, 0.05241682563791983, 0.059372675955273735, -0.2887187567212095, 0.00843703859368361, 0.08948982493529911, 0.040813045285176486, 0.0331467867417814, -0.1291363778163941, -0.026358242286733002, 0.15285755819400038, -0.014629045981564559, 0.025264909974794136, 0.07417079197034582, -0.10428212240913126, -0.11278736138774548, 0.38200039250659756, 0.019772418396314606, -0.25830698682693765, 0.10221678941161372, -0.14794338270075968, -0.16651224825545796, 0.09764370096127095, 0.1331854112449946, 0.17019453450302535, -0.10216010426290723, 0.0827143822666585, -0.09982714735451736, 0.13271331559917598, 0.14999390760203823, 0.007761198437947314, 0.16606830417731544, 0.06502879897379898, 0.10380206619447563, 0.21488682406925363, -0.010776351007734775, -0.04517046653927537, -0.3269239274377469, -0.07555536546351505, -0.16548031273850938, 0.062467880776239326, -0.19090374040354163, -0.21278156594962638, 0.4085479749337537, 0.08056126877818315, 0.22016987781535136, 0.12240439210290788, 0.21258779017080087, 0.12424250554079208, 0.06449450983927818, 0.1150124901359959, 0.09827024867990986, 0.1250525450323039, -0.009773031470103888, -0.16535438589562546, 0.06566880087484606, 0.147030834979887] |
1,802.0372 | Double Minimum Variance Beamforming Method to Enhance Photoacoustic
Imaging | One of the common algorithms used to reconstruct photoacoustic (PA) images is
the non-adaptive Delay-and-Sum (DAS) beamformer. However, the quality of the
reconstructed PA images obtained by DAS is not satisfying due to its high level
of sidelobes and wide mainlobe. In contrast, adaptive beamformers, such as
minimum variance (MV), result in an improved image compared to DAS. In this
paper, a novel beamforming method, called Double MV (D-MV) is proposed to
enhance the image quality compared to the MV. It is shown that there is a
summation procedure between the weighted subarrays in the output of the MV
beamformer. This summation can be interpreted as the non-adaptive DAS
beamformer. It is proposed to replace the existing DAS with the MV algorithm to
reduce the contribution of the off-axis signals caused by the DAS beamformer
between the weighted subarrays. The numerical results show that the proposed
technique improves the full-width-half-maximum (FWHM) and signal-to-noise ratio
(SNR) for about 28.83 \mu m and 4.8 dB in average, respectively, compared to MV
beamformer. Also, quantitative evaluation of the experimental results indicates
that the proposed D-MV leads to 0.15 mm and 1.96 dB improvement in FWHM and
SNR, in comparison with MV beamformer.
| eess.SP cs.IT math.IT | one of the common algorithms used to reconstruct photoacoustic pa images is the nonadaptive delayandsum das beamformer however the quality of the reconstructed pa images obtained by das is not satisfying due to its high level of sidelobes and wide mainlobe in contrast adaptive beamformers such as minimum variance mv result in an improved image compared to das in this paper a novel beamforming method called double mv dmv is proposed to enhance the image quality compared to the mv it is shown that there is a summation procedure between the weighted subarrays in the output of the mv beamformer this summation can be interpreted as the nonadaptive das beamformer it is proposed to replace the existing das with the mv algorithm to reduce the contribution of the offaxis signals caused by the das beamformer between the weighted subarrays the numerical results show that the proposed technique improves the fullwidthhalfmaximum fwhm and signaltonoise ratio snr for about 2883 mu m and 48 db in average respectively compared to mv beamformer also quantitative evaluation of the experimental results indicates that the proposed dmv leads to 015 mm and 196 db improvement in fwhm and snr in comparison with mv beamformer | [['one', 'of', 'the', 'common', 'algorithms', 'used', 'to', 'reconstruct', 'photoacoustic', 'pa', 'images', 'is', 'the', 'nonadaptive', 'delayandsum', 'das', 'beamformer', 'however', 'the', 'quality', 'of', 'the', 'reconstructed', 'pa', 'images', 'obtained', 'by', 'das', 'is', 'not', 'satisfying', 'due', 'to', 'its', 'high', 'level', 'of', 'sidelobes', 'and', 'wide', 'mainlobe', 'in', 'contrast', 'adaptive', 'beamformers', 'such', 'as', 'minimum', 'variance', 'mv', 'result', 'in', 'an', 'improved', 'image', 'compared', 'to', 'das', 'in', 'this', 'paper', 'a', 'novel', 'beamforming', 'method', 'called', 'double', 'mv', 'dmv', 'is', 'proposed', 'to', 'enhance', 'the', 'image', 'quality', 'compared', 'to', 'the', 'mv', 'it', 'is', 'shown', 'that', 'there', 'is', 'a', 'summation', 'procedure', 'between', 'the', 'weighted', 'subarrays', 'in', 'the', 'output', 'of', 'the', 'mv', 'beamformer', 'this', 'summation', 'can', 'be', 'interpreted', 'as', 'the', 'nonadaptive', 'das', 'beamformer', 'it', 'is', 'proposed', 'to', 'replace', 'the', 'existing', 'das', 'with', 'the', 'mv', 'algorithm', 'to', 'reduce', 'the', 'contribution', 'of', 'the', 'offaxis', 'signals', 'caused', 'by', 'the', 'das', 'beamformer', 'between', 'the', 'weighted', 'subarrays', 'the', 'numerical', 'results', 'show', 'that', 'the', 'proposed', 'technique', 'improves', 'the', 'fullwidthhalfmaximum', 'fwhm', 'and', 'signaltonoise', 'ratio', 'snr', 'for', 'about', '2883', 'mu', 'm', 'and', '48', 'db', 'in', 'average', 'respectively', 'compared', 'to', 'mv', 'beamformer', 'also', 'quantitative', 'evaluation', 'of', 'the', 'experimental', 'results', 'indicates', 'that', 'the', 'proposed', 'dmv', 'leads', 'to', '015', 'mm', 'and', '196', 'db', 'improvement', 'in', 'fwhm', 'and', 'snr', 'in', 'comparison', 'with', 'mv', 'beamformer']] | [-0.08601887786852186, -0.02917860316786267, -0.06166446768449404, 0.0253597749174858, -0.02667774252088076, -0.15721697180096678, 0.059560195861697834, 0.4115384011260285, -0.21925227808761388, -0.33937406133691866, 0.04878587204665788, -0.26978661451282815, -0.14645965770588973, 0.1884621860571767, -0.17478606833762783, 0.06161651821033655, 0.08175177585296145, -0.017265591952931043, -0.07741612474546399, -0.26472531975335883, 0.17890388200330973, 0.15092278097349046, 0.34620194240641694, -0.008245837280348917, 0.1385747476401341, 0.012833008593259539, -0.04980984575175985, 0.013665012661929257, -0.05375678543332378, 0.061668793179431754, 0.29262611710281583, 0.17452909171127307, 0.20997544198885476, -0.2973759704966791, -0.14893960454688412, 0.08285373435285523, 0.14508741359599636, 0.022171790772421877, -0.001026172619125801, -0.2522895289538194, 0.18891064854263884, -0.17896258880632307, -0.05431184166078292, 0.015038219102554201, -0.07038760642361963, 0.03707522126417794, -0.35575745838118633, 0.09827729514844619, 0.03360755151914592, 0.009128929251552228, -0.049211375125749364, -0.2530427537086284, 0.03449684361828931, 0.07433625124277893, -0.0013806410438039496, 0.11995577363396208, 0.05952626115516128, -0.10051829134343407, -0.10982460002578683, 0.346152873756598, -0.06134126723297034, -0.18518944807238316, 0.1408051010958345, -0.1284725443698728, -0.009301213238706542, 0.23122575431219747, 0.1445903131672785, 0.04808529606322996, -0.15222761706547372, 0.007213296364915637, 0.008577123740641165, 0.2148959582680883, 0.1554223382143519, 0.05374033129703834, 0.08246448493782599, 0.15520502655677984, 0.07166227981466894, 0.14217979910411407, -0.19020988255485907, -0.004006736174146247, -0.18810966888521025, -0.11309915753643042, -0.19552371254712625, -0.003006305261184555, -0.11342051912802002, -0.11842529102267776, 0.36137696449181544, 0.18681779677684807, 0.17433441332050004, 0.07352128074546556, 0.38454233257839426, 0.12688281587307487, 0.10483468896545582, 0.06545726170566812, 0.262925444670424, 0.155203845911196, 0.14354074300891584, -0.23901155636407173, 0.003983403960869989, 0.01670979559257739] |
1,802.03721 | Lack of superconductivity in the phase diagram of single-crystalline
Eu(Fe1-xCox)2As2 grown by transition metal arsenide flux | The interplay of magnetism and superconductivity (SC) has been a focus of
interest in condensed matter physics for decades. EuFe2As2 has been identified
as a potential platform to investigate interactions between structural,
magnetic, electronic effects as well as coexistence of magnetism and SC with
similar transition temperatures. However, there are obvious inconsistencies in
the reported phase diagrams of Eu(Fe1-xCox)2As2 crystals grown by different
methods. For transition metal arsenide (TMA)-flux-grown crystals, even the
existence of SC is open for dispute. Here we re-examine the phase diagram of
single-crystalline Eu(Fe1-xCox)2As2 grown by TMA flux. We found that the
lattice parameter c shrinks linearly with Co doping, almost twice as fast as
that of the tin-flux-grown crystals. With Co doping, the spin-density-wave
(SDW) order of Fe sublattice is quickly suppressed, being detected only up to x
= 0.08. The magnetic ordering temperature of the Eu2+ sublattice (TEu) shows a
systematic evolution with Co doping, first going down and reaching a minimum at
x = 0.08, then increasing continuously up to x = 0.24. Over the whole
composition range investigated, no signature of SC is observed.
| cond-mat.supr-con | the interplay of magnetism and superconductivity sc has been a focus of interest in condensed matter physics for decades eufe2as2 has been identified as a potential platform to investigate interactions between structural magnetic electronic effects as well as coexistence of magnetism and sc with similar transition temperatures however there are obvious inconsistencies in the reported phase diagrams of eufe1xcox2as2 crystals grown by different methods for transition metal arsenide tmafluxgrown crystals even the existence of sc is open for dispute here we reexamine the phase diagram of singlecrystalline eufe1xcox2as2 grown by tma flux we found that the lattice parameter c shrinks linearly with co doping almost twice as fast as that of the tinfluxgrown crystals with co doping the spindensitywave sdw order of fe sublattice is quickly suppressed being detected only up to x 008 the magnetic ordering temperature of the eu2 sublattice teu shows a systematic evolution with co doping first going down and reaching a minimum at x 008 then increasing continuously up to x 024 over the whole composition range investigated no signature of sc is observed | [['the', 'interplay', 'of', 'magnetism', 'and', 'superconductivity', 'sc', 'has', 'been', 'a', 'focus', 'of', 'interest', 'in', 'condensed', 'matter', 'physics', 'for', 'decades', 'eufe2as2', 'has', 'been', 'identified', 'as', 'a', 'potential', 'platform', 'to', 'investigate', 'interactions', 'between', 'structural', 'magnetic', 'electronic', 'effects', 'as', 'well', 'as', 'coexistence', 'of', 'magnetism', 'and', 'sc', 'with', 'similar', 'transition', 'temperatures', 'however', 'there', 'are', 'obvious', 'inconsistencies', 'in', 'the', 'reported', 'phase', 'diagrams', 'of', 'eufe1xcox2as2', 'crystals', 'grown', 'by', 'different', 'methods', 'for', 'transition', 'metal', 'arsenide', 'tmafluxgrown', 'crystals', 'even', 'the', 'existence', 'of', 'sc', 'is', 'open', 'for', 'dispute', 'here', 'we', 'reexamine', 'the', 'phase', 'diagram', 'of', 'singlecrystalline', 'eufe1xcox2as2', 'grown', 'by', 'tma', 'flux', 'we', 'found', 'that', 'the', 'lattice', 'parameter', 'c', 'shrinks', 'linearly', 'with', 'co', 'doping', 'almost', 'twice', 'as', 'fast', 'as', 'that', 'of', 'the', 'tinfluxgrown', 'crystals', 'with', 'co', 'doping', 'the', 'spindensitywave', 'sdw', 'order', 'of', 'fe', 'sublattice', 'is', 'quickly', 'suppressed', 'being', 'detected', 'only', 'up', 'to', 'x', '008', 'the', 'magnetic', 'ordering', 'temperature', 'of', 'the', 'eu2', 'sublattice', 'teu', 'shows', 'a', 'systematic', 'evolution', 'with', 'co', 'doping', 'first', 'going', 'down', 'and', 'reaching', 'a', 'minimum', 'at', 'x', '008', 'then', 'increasing', 'continuously', 'up', 'to', 'x', '024', 'over', 'the', 'whole', 'composition', 'range', 'investigated', 'no', 'signature', 'of', 'sc', 'is', 'observed']] | [-0.15148487901262475, 0.21598698637884972, 0.006061506628303521, 0.02238637240443084, -0.01573362081222194, -0.14315503461570558, 0.14045858136667622, 0.4124869500526285, -0.254360362968939, -0.32977507325247096, 0.027488824305003563, -0.356383127691803, -0.04701688827809978, 0.13148593188047747, 0.08077570802063844, -0.010880651829848435, -0.08227251316973214, -0.0476515222104703, -0.19705708541033926, -0.23276328908458435, 0.2752834889632623, 0.023619221587860062, 0.2915443561071435, 0.08201317853783652, 0.03590087740653126, -0.07302434094471194, 0.10749960281605975, 0.044129613463340676, -0.16420340586999907, -0.02421880415232989, 0.2898865765392107, -0.025520518319523434, 0.20560432892124364, -0.3742214550032664, -0.2311917980287703, 0.03693440213462727, 0.15902397953405303, 0.09308888979445575, -0.10664584103834915, -0.24427182528342906, 0.0742589860146939, -0.12565965870412404, -0.12232820301890204, -0.05980748239915166, 0.027401612554597905, -0.009524871848423645, -0.20326702274634675, 0.08606852775460667, 0.06150675638997138, 0.14511883127803016, -0.07172694747184277, -0.17569075388528702, -0.11935283218794582, 0.04266785967195312, 0.06881082034932902, 0.14634996181417068, 0.12453270161861164, -0.06309131844663772, -0.08386431667180258, 0.38434630063083547, -0.043373529661162674, 0.014215013783130438, 0.1658212089079753, -0.20456342791643856, -0.10545903189360338, 0.19911230910611524, 0.08388553972824314, 0.08086896362309318, -0.12454948618239854, 0.1023667489910514, 0.011020228669236777, 0.23040240425826972, 0.055178355417703676, 0.07681570841672983, 0.25525362283717523, 0.23537583293730005, 0.047212858763286625, 0.11320447566324456, -0.11991613975786578, -0.03665698611698413, -0.18033683580467424, -0.16836236239184682, -0.183278325228231, 0.05147763376129465, -0.05276733563693653, -0.20086380851712857, 0.34465478830523577, 0.13369309139506375, 0.18967476751083787, -0.10333375599219512, 0.1962566756200056, 0.05141995042644041, 0.0694255168348456, 0.02476438336695234, 0.25029977056392505, 0.1897091370004908, 0.1434454100113099, -0.2584171725836935, 0.1189214676621207, -0.0008319059444728208] |
1,802.03722 | Influence of pulsatile blood flow on allometry of aortic wall shear
stress | Shear stress plays an important role in the creation and evolution of
atherosclerosis. An key element for in-vivo measurements and extrapolations is
the dependence of shear stress on body mass. In the case of a Poiseuille
modeling of the blood flow, P. Weinberg and C. Ethier have shown that shear
stress on the aortic endothelium varies like body mass to the power
$-\frac{3}{8}$, and is therefore 20-fold higher in mice than in men. However,
by considering a more physiological oscillating Poiseuille + Womersley
combinated flow in the aorta, we show that results differ notably: at larger
masses ($M>10 \ kg$) shear stress varies as body mass to the power
$-\frac{1}{8}$ and modifies the man to mouse ratio to 1:8. The allometry and
values of temporal gradient of shear stress also change: $\partial\tau/\partial
t$ varies as $M^{-3/8}$ instead of $M^{-5/8}$ at larger masses, and the 1:150
ratio from man to mouse becomes 1:61. Lastly, we show that the unsteady
component of blood flow does not influence the constant allometry of peak
velocity on body mass: $u_{max} \propto M^{0}$. This work extends our knowledge
on the dependence of hemodynamic parameters on body mass and paves the way for
a more precise extrapolation of in-vivo measurements to humans and bigger
mammals.
| physics.bio-ph physics.flu-dyn q-bio.TO | shear stress plays an important role in the creation and evolution of atherosclerosis an key element for invivo measurements and extrapolations is the dependence of shear stress on body mass in the case of a poiseuille modeling of the blood flow p weinberg and c ethier have shown that shear stress on the aortic endothelium varies like body mass to the power frac38 and is therefore 20fold higher in mice than in men however by considering a more physiological oscillating poiseuille womersley combinated flow in the aorta we show that results differ notably at larger masses m10 kg shear stress varies as body mass to the power frac18 and modifies the man to mouse ratio to 18 the allometry and values of temporal gradient of shear stress also change partialtaupartial t varies as m38 instead of m58 at larger masses and the 1150 ratio from man to mouse becomes 161 lastly we show that the unsteady component of blood flow does not influence the constant allometry of peak velocity on body mass u_max propto m0 this work extends our knowledge on the dependence of hemodynamic parameters on body mass and paves the way for a more precise extrapolation of invivo measurements to humans and bigger mammals | [['shear', 'stress', 'plays', 'an', 'important', 'role', 'in', 'the', 'creation', 'and', 'evolution', 'of', 'atherosclerosis', 'an', 'key', 'element', 'for', 'invivo', 'measurements', 'and', 'extrapolations', 'is', 'the', 'dependence', 'of', 'shear', 'stress', 'on', 'body', 'mass', 'in', 'the', 'case', 'of', 'a', 'poiseuille', 'modeling', 'of', 'the', 'blood', 'flow', 'p', 'weinberg', 'and', 'c', 'ethier', 'have', 'shown', 'that', 'shear', 'stress', 'on', 'the', 'aortic', 'endothelium', 'varies', 'like', 'body', 'mass', 'to', 'the', 'power', 'frac38', 'and', 'is', 'therefore', '20fold', 'higher', 'in', 'mice', 'than', 'in', 'men', 'however', 'by', 'considering', 'a', 'more', 'physiological', 'oscillating', 'poiseuille', 'womersley', 'combinated', 'flow', 'in', 'the', 'aorta', 'we', 'show', 'that', 'results', 'differ', 'notably', 'at', 'larger', 'masses', 'm10', 'kg', 'shear', 'stress', 'varies', 'as', 'body', 'mass', 'to', 'the', 'power', 'frac18', 'and', 'modifies', 'the', 'man', 'to', 'mouse', 'ratio', 'to', '18', 'the', 'allometry', 'and', 'values', 'of', 'temporal', 'gradient', 'of', 'shear', 'stress', 'also', 'change', 'partialtaupartial', 't', 'varies', 'as', 'm38', 'instead', 'of', 'm58', 'at', 'larger', 'masses', 'and', 'the', '1150', 'ratio', 'from', 'man', 'to', 'mouse', 'becomes', '161', 'lastly', 'we', 'show', 'that', 'the', 'unsteady', 'component', 'of', 'blood', 'flow', 'does', 'not', 'influence', 'the', 'constant', 'allometry', 'of', 'peak', 'velocity', 'on', 'body', 'mass', 'u_max', 'propto', 'm0', 'this', 'work', 'extends', 'our', 'knowledge', 'on', 'the', 'dependence', 'of', 'hemodynamic', 'parameters', 'on', 'body', 'mass', 'and', 'paves', 'the', 'way', 'for', 'a', 'more', 'precise', 'extrapolation', 'of', 'invivo', 'measurements', 'to', 'humans', 'and', 'bigger', 'mammals']] | [-0.10250416441675331, 0.16445983002076991, -0.06643483284653376, 0.0107172696538832, -0.05098793211180975, -0.08287500523233621, -0.006298763645204282, 0.3321136479717818, -0.21550185761027185, -0.3085002074257867, 0.06169187588937636, -0.29647212677478496, -0.1311917791355143, 0.23292901678619407, -0.09966207830244583, 0.023494622367621506, 0.03057271765030939, 0.059270154747023886, -0.029908377457050477, -0.15353117896806412, 0.27089015619931883, 0.05431026349415873, 0.30052786139716015, 0.06979318755439086, 0.07416062834465156, -0.015044636201426978, -0.025238439777294303, 0.02522396525448202, -0.19109141472711932, 0.051183546837972535, 0.17863991541778185, 0.0655000211963762, 0.25670897152440825, -0.39622692291689393, -0.21350328545696978, 0.08871374738467212, 0.15440165130928676, 0.06363429242311654, -0.0003109915808159028, -0.19548127766915294, 0.07392451372965801, -0.15477642882845855, -0.11522343543491852, -0.015346993291105079, 0.10108560943367458, -0.003235837410660553, -0.2881501039771345, 0.21660011712018526, 0.04090451854880493, 0.12767876813298848, -0.12227976073336322, -0.13861200203289195, -0.08843654966198534, 0.14849371481271884, 0.1271844544081423, 0.07030824734714103, 0.2677256854085049, -0.17921230198451235, -0.012146362082774538, 0.36760082893479284, -0.05470051517167491, -0.17092407290998957, 0.17680874626650153, -0.17431839195651805, -0.10020450680599649, 0.1186889020892063, 0.20876289741136134, 0.07314621686179301, -0.09142511844229285, -0.030376722658396523, -0.015964724838106643, 0.19461514723791493, 0.12240916782342322, -0.09105470982878146, 0.16972307637817974, 0.18080156868425115, 0.04733830444182795, 0.07570211487617066, -0.12237091073628036, -0.04425406492848899, -0.24563877578216173, -0.14780565079631247, -0.12519010956892468, 0.05634658754058931, -0.13652452920258937, -0.13556372532710353, 0.35593872650591013, 0.11856281432198675, 0.20453238073853997, 0.0957469696566315, 0.2892938730408355, 0.04554202259889352, 0.1027840896311336, 0.06308139468967398, 0.28342696907007975, 0.13688268861272326, 0.1559398208611119, -0.2722496905889694, 0.09002371585817251, 0.010820769910045927] |
1,802.03723 | Asymptotic uniformity of the quantization error for Moran measures on
$\mathbb{R}^1$ | Let $E$ be a Moran set on $\mathbb{R}^1$ associated with a closed interval
$J$ and two sequences $(n_k)_{k=1}^\infty$ and
$(\mathcal{C}_k=(c_{k,j})_{j=1}^{n_k})_{k\geq1}$. Let $\mu$ be the infinite
product measure (Moran measure) on $E$ associated with a sequence
$(\mathcal{P}_k)_{k\geq1}$ of positive probability vectors with
$\mathcal{P}_k=(p_{k,j})_{j=1}^{n_k},k\geq 1$. We assume that \[
\inf_{k\geq1}\min_{1\leq j\leq n_k}c_{k,j}>0,\;\inf_{k\geq1}\min_{1\leq j\leq
n_k}p_{k,j}>0. \] For every $n\geq 1$, let $\alpha_n$ be an $n$ optimal set in
the quantization for $\mu$ of order $r\in(0,\infty)$ and
$\{P_a(\alpha_n)\}_{a\in\alpha_n}$ an arbitrary Voronoi partition with respect
to $\alpha_n$. For every $a\in\alpha_n$, we write
$I_a(\alpha,\mu):=\int_{P_a(\alpha_n)}d(x,\alpha_n)^rd\mu(x)$ and \[
\underline{J}(\alpha_n,\mu):=\min_{a\in\alpha_n}I_a(\alpha,\mu),\;
\overline{J}(\alpha_n,\mu):=\max_{a\in\alpha_n}I_a(\alpha,\mu). \] We show that
$\underline{J}(\alpha_n,\mu),\overline{J}(\alpha_n,\mu)$ and
$e^r_{n,r}(\mu)-e^r_{n+1,r}(\mu)$ are of the same order as
$\frac{1}{n}e^r_{n,r}(\mu)$, where $e^r_{n,r}(\mu):=\int
d(x,\alpha_n)^rd\mu(x)$ is the $n$th quantization error for $\mu$ of order $r$.
In particular, for the class of Moran measures on $\mathbb{R}^1$, our result
shows that a weaker version of Gersho's conjecture holds.
| math.FA | let e be a moran set on mathbbr1 associated with a closed interval j and two sequences n_k_k1infty and mathcalc_kc_kj_j1n_k_kgeq1 let mu be the infinite product measure moran measure on e associated with a sequence mathcalp_k_kgeq1 of positive probability vectors with mathcalp_kp_kj_j1n_kkgeq 1 we assume that inf_kgeq1min_1leq jleq n_kc_kj0inf_kgeq1min_1leq jleq n_kp_kj0 for every ngeq 1 let alpha_n be an n optimal set in the quantization for mu of order rin0infty and p_aalpha_n_ainalpha_n an arbitrary voronoi partition with respect to alpha_n for every ainalpha_n we write i_aalphamuint_p_aalpha_ndxalpha_nrdmux and underlinejalpha_nmumin_ainalpha_ni_aalphamu overlinejalpha_nmumax_ainalpha_ni_aalphamu we show that underlinejalpha_nmuoverlinejalpha_nmu and er_nrmuer_n1rmu are of the same order as frac1ner_nrmu where er_nrmuint dxalpha_nrdmux is the nth quantization error for mu of order r in particular for the class of moran measures on mathbbr1 our result shows that a weaker version of gershos conjecture holds | [['let', 'e', 'be', 'a', 'moran', 'set', 'on', 'mathbbr1', 'associated', 'with', 'a', 'closed', 'interval', 'j', 'and', 'two', 'sequences', 'n_k_k1infty', 'and', 'mathcalc_kc_kj_j1n_k_kgeq1', 'let', 'mu', 'be', 'the', 'infinite', 'product', 'measure', 'moran', 'measure', 'on', 'e', 'associated', 'with', 'a', 'sequence', 'mathcalp_k_kgeq1', 'of', 'positive', 'probability', 'vectors', 'with', 'mathcalp_kp_kj_j1n_kkgeq', '1', 'we', 'assume', 'that', 'inf_kgeq1min_1leq', 'jleq', 'n_kc_kj0inf_kgeq1min_1leq', 'jleq', 'n_kp_kj0', 'for', 'every', 'ngeq', '1', 'let', 'alpha_n', 'be', 'an', 'n', 'optimal', 'set', 'in', 'the', 'quantization', 'for', 'mu', 'of', 'order', 'rin0infty', 'and', 'p_aalpha_n_ainalpha_n', 'an', 'arbitrary', 'voronoi', 'partition', 'with', 'respect', 'to', 'alpha_n', 'for', 'every', 'ainalpha_n', 'we', 'write', 'i_aalphamuint_p_aalpha_ndxalpha_nrdmux', 'and', 'underlinejalpha_nmumin_ainalpha_ni_aalphamu', 'overlinejalpha_nmumax_ainalpha_ni_aalphamu', 'we', 'show', 'that', 'underlinejalpha_nmuoverlinejalpha_nmu', 'and', 'er_nrmuer_n1rmu', 'are', 'of', 'the', 'same', 'order', 'as', 'frac1ner_nrmu', 'where', 'er_nrmuint', 'dxalpha_nrdmux', 'is', 'the', 'nth', 'quantization', 'error', 'for', 'mu', 'of', 'order', 'r', 'in', 'particular', 'for', 'the', 'class', 'of', 'moran', 'measures', 'on', 'mathbbr1', 'our', 'result', 'shows', 'that', 'a', 'weaker', 'version', 'of', 'gershos', 'conjecture', 'holds']] | [-0.14360894503382346, 0.1238373578596414, -0.03092705844513451, 0.01984296075825114, 0.013153439888264984, -0.16876871693772652, 0.02125405397673603, 0.3458177657982257, -0.24975750292651355, -0.20887829953814313, 0.08206049915558349, -0.30050438549175545, -0.0921251652626476, 0.16271707838168367, -0.09032188027631491, -0.02776911391702015, 0.024837824139588825, 0.12558637366940578, -0.01314175731386058, -0.24520372768553594, 0.3394157407572493, -0.0395189814735204, 0.1839979115090197, 0.016425473297325275, 0.12574895376844022, 0.01715013696035991, 0.009390627422059575, 0.04596633659093641, -0.2063114560121297, 0.08184251203444243, 0.21967753476152818, 0.13399144082407777, 0.2873889674898237, -0.30847025855667504, -0.12443257028741452, 0.2330069203977473, 0.14867875424291319, -0.024602300215822954, 0.023109428267343902, -0.25405901137273756, 0.20238408509952327, -0.1455733497190522, -0.12279291183998188, -0.0421432171909449, 0.13362181072006935, 0.049537289833339555, -0.4110088489095991, 0.0075665278360247615, 0.09049172330414876, 0.03762888943310827, -0.05730703341541812, -0.15420657750607158, -0.024013477379533774, 0.09681444393742519, -0.014695609161087001, 0.13111485821718816, 0.012637313923914918, -0.0035868020184958976, -0.15306869426276534, 0.3677914146644374, -0.10895011892037777, -0.2842395953678836, 0.10666343567815299, -0.2169484146172181, -0.16901018620701508, 0.07869411117668884, 0.1229150050416744, 0.12569158164939534, -0.05039930044052501, 0.18715010706558435, -0.08666179942617115, 0.1468764926927785, 0.106794016478428, 0.009007466788170859, 0.12770298478814462, 0.08279545256518758, 0.1537706813736198, 0.12569196998083498, -0.04806913801294286, -0.015166480715076128, -0.35596672079215447, -0.19569068020015645, -0.21704313140750553, 0.18075793167420973, -0.15240552662811144, -0.15598852979019284, 0.3110972211230546, 0.09184504892521848, 0.23195758250852425, 0.17899009086346876, 0.16102494838026662, 0.14643636943680274, -0.021355060201797945, 0.08137925307576856, 0.01672843542570869, 0.13889200819345812, -0.019139187623901915, -0.16752250572123253, 0.030720511598822973, 0.12083278352705142] |
1,802.03724 | Photoacoustic Image Formation Based on Sparse Regularization of Minimum
Variance Beamformer | Delay-and-Sum (DAS) is the most common algorithm used in photoacoustic (PA)
image formation. However, this algorithm results in a reconstructed image with
a wide mainlobe and high level of sidelobes. Minimum variance (MV), as an
adaptive beamformer, overcomes these limitations and improves the image
resolution and contrast. In this paper, a novel algorithm, named
modified-sparse-MV (MS-MV) is proposed in which a L1-norm constraint is added
to the MV minimization problem after some modifications, in order to suppress
the sidelobes more efficiently, compared to MV. The added constraint can be
interpreted as the sparsity of the output of the MV beamformed signals. Since
the final minimization problem is convex, it can be solved efficiently using a
simple iterative algorithm. The numerical results show that the proposed
method, MS-MV beamformer, improves the signal-to-noise (SNR) about 19.48 dB, in
average, compared to MV. Also, the experimental results, using a wire-target
phantom, show that MS-MV leads to SNR improvement of about 2.64 dB in
comparison with the MV.
| eess.SP | delayandsum das is the most common algorithm used in photoacoustic pa image formation however this algorithm results in a reconstructed image with a wide mainlobe and high level of sidelobes minimum variance mv as an adaptive beamformer overcomes these limitations and improves the image resolution and contrast in this paper a novel algorithm named modifiedsparsemv msmv is proposed in which a l1norm constraint is added to the mv minimization problem after some modifications in order to suppress the sidelobes more efficiently compared to mv the added constraint can be interpreted as the sparsity of the output of the mv beamformed signals since the final minimization problem is convex it can be solved efficiently using a simple iterative algorithm the numerical results show that the proposed method msmv beamformer improves the signaltonoise snr about 1948 db in average compared to mv also the experimental results using a wiretarget phantom show that msmv leads to snr improvement of about 264 db in comparison with the mv | [['delayandsum', 'das', 'is', 'the', 'most', 'common', 'algorithm', 'used', 'in', 'photoacoustic', 'pa', 'image', 'formation', 'however', 'this', 'algorithm', 'results', 'in', 'a', 'reconstructed', 'image', 'with', 'a', 'wide', 'mainlobe', 'and', 'high', 'level', 'of', 'sidelobes', 'minimum', 'variance', 'mv', 'as', 'an', 'adaptive', 'beamformer', 'overcomes', 'these', 'limitations', 'and', 'improves', 'the', 'image', 'resolution', 'and', 'contrast', 'in', 'this', 'paper', 'a', 'novel', 'algorithm', 'named', 'modifiedsparsemv', 'msmv', 'is', 'proposed', 'in', 'which', 'a', 'l1norm', 'constraint', 'is', 'added', 'to', 'the', 'mv', 'minimization', 'problem', 'after', 'some', 'modifications', 'in', 'order', 'to', 'suppress', 'the', 'sidelobes', 'more', 'efficiently', 'compared', 'to', 'mv', 'the', 'added', 'constraint', 'can', 'be', 'interpreted', 'as', 'the', 'sparsity', 'of', 'the', 'output', 'of', 'the', 'mv', 'beamformed', 'signals', 'since', 'the', 'final', 'minimization', 'problem', 'is', 'convex', 'it', 'can', 'be', 'solved', 'efficiently', 'using', 'a', 'simple', 'iterative', 'algorithm', 'the', 'numerical', 'results', 'show', 'that', 'the', 'proposed', 'method', 'msmv', 'beamformer', 'improves', 'the', 'signaltonoise', 'snr', 'about', '1948', 'db', 'in', 'average', 'compared', 'to', 'mv', 'also', 'the', 'experimental', 'results', 'using', 'a', 'wiretarget', 'phantom', 'show', 'that', 'msmv', 'leads', 'to', 'snr', 'improvement', 'of', 'about', '264', 'db', 'in', 'comparison', 'with', 'the', 'mv']] | [-0.0686203676548735, -0.03255731343822711, -0.0842955942162844, 0.06241346888981211, -0.060499286709033366, -0.15249470612776975, 0.04142077211819109, 0.4000719285904333, -0.2702645476646093, -0.34750064112306367, 0.09996199834466186, -0.23497405237992483, -0.16585013700043497, 0.18839245604528285, -0.17666884247739256, 0.05984011051270745, 0.10030622149537677, 0.018047876038982825, -0.10694129065399063, -0.28457582166041334, 0.1765010451863697, 0.128136607316934, 0.28087699041913256, 0.024330776731520776, 0.14096791034941475, -0.009638060062503773, -0.004076529868472756, 0.04907273736273859, -0.05096598220405246, 0.09183959033700174, 0.2850237275256655, 0.1803392326356443, 0.2790514961073598, -0.3352211201163523, -0.19266739840607838, 0.09184928500647742, 0.1577988757217657, 0.09127242488006666, -0.036790757133369045, -0.23955216391749132, 0.17012526140176187, -0.1582909590318982, -0.03955598947437811, -0.004523594452331037, -0.1004054708566311, 0.0196108725286186, -0.33786938673219546, 0.11175578839786242, 0.04915409088648993, -0.0009552505255842501, -0.07294788787375701, -0.2060471473524541, 0.03866930939885645, 0.04890204404560746, 0.010422321522117027, 0.10342259999765283, 0.0867760617520226, -0.1317977448268308, -0.11764428126654285, 0.3624058228808861, -0.06913472024189662, -0.19265821452703943, 0.13253920535025604, -0.08412140940367444, -0.06056911840840626, 0.2210641717631084, 0.16219046393100836, 0.08748030095172624, -0.14911585765679372, 0.032057178679902244, -0.009791833177163192, 0.21112081733035162, 0.13733071866416674, 0.012646558984508453, 0.09213778098896602, 0.18520861342435052, 0.0981289568054347, 0.17399520690244355, -0.1613356313006481, -0.011034109683970183, -0.2123468814662692, -0.09826028094758377, -0.1930306151772112, -0.017685301456189045, -0.11404532318668043, -0.08887776609601601, 0.3780223514793292, 0.2016958239905399, 0.2052240090793216, 0.067288939384715, 0.3803664088032088, 0.13324442149162796, 0.07329248698668246, 0.0830897826178605, 0.24117297023921158, 0.13213045597133552, 0.10220341693304273, -0.2346677701417471, 0.027433257478580702, 0.01609406321012398] |
1,802.03725 | A Generative Model for Dynamic Networks with Applications | Networks observed in real world like social networks, collaboration networks
etc., exhibit temporal dynamics, i.e. nodes and edges appear and/or disappear
over time. In this paper, we propose a generative, latent space based,
statistical model for such networks (called dynamic networks). We consider the
case where the number of nodes is fixed, but the presence of edges can vary
over time. Our model allows the number of communities in the network to be
different at different time steps. We use a neural network based methodology to
perform approximate inference in the proposed model and its simplified version.
Experiments done on synthetic and real world networks for the task of community
detection and link prediction demonstrate the utility and effectiveness of our
model as compared to other similar existing approaches.
| cs.SI cs.LG stat.ML | networks observed in real world like social networks collaboration networks etc exhibit temporal dynamics ie nodes and edges appear andor disappear over time in this paper we propose a generative latent space based statistical model for such networks called dynamic networks we consider the case where the number of nodes is fixed but the presence of edges can vary over time our model allows the number of communities in the network to be different at different time steps we use a neural network based methodology to perform approximate inference in the proposed model and its simplified version experiments done on synthetic and real world networks for the task of community detection and link prediction demonstrate the utility and effectiveness of our model as compared to other similar existing approaches | [['networks', 'observed', 'in', 'real', 'world', 'like', 'social', 'networks', 'collaboration', 'networks', 'etc', 'exhibit', 'temporal', 'dynamics', 'ie', 'nodes', 'and', 'edges', 'appear', 'andor', 'disappear', 'over', 'time', 'in', 'this', 'paper', 'we', 'propose', 'a', 'generative', 'latent', 'space', 'based', 'statistical', 'model', 'for', 'such', 'networks', 'called', 'dynamic', 'networks', 'we', 'consider', 'the', 'case', 'where', 'the', 'number', 'of', 'nodes', 'is', 'fixed', 'but', 'the', 'presence', 'of', 'edges', 'can', 'vary', 'over', 'time', 'our', 'model', 'allows', 'the', 'number', 'of', 'communities', 'in', 'the', 'network', 'to', 'be', 'different', 'at', 'different', 'time', 'steps', 'we', 'use', 'a', 'neural', 'network', 'based', 'methodology', 'to', 'perform', 'approximate', 'inference', 'in', 'the', 'proposed', 'model', 'and', 'its', 'simplified', 'version', 'experiments', 'done', 'on', 'synthetic', 'and', 'real', 'world', 'networks', 'for', 'the', 'task', 'of', 'community', 'detection', 'and', 'link', 'prediction', 'demonstrate', 'the', 'utility', 'and', 'effectiveness', 'of', 'our', 'model', 'as', 'compared', 'to', 'other', 'similar', 'existing', 'approaches']] | [-0.10717610996613611, 0.011420086101997037, -0.019543300135523196, 0.056905958166187126, -0.0738174691922645, -0.14849510487625214, 0.06553162264099792, 0.43608942799732203, -0.2578953635200223, -0.35615034615115604, 0.0622321595870998, -0.2593165211788561, -0.24228805650021995, 0.15696042006142263, -0.05632379191454731, 0.06854433346812273, 0.10830151826836341, 0.07656640381833842, 0.0070227942855436674, -0.26342533845923727, 0.3178981541648738, 0.046899789539996045, 0.34492334035629507, 0.02559408147696608, 0.08799476294540041, -0.0015607320364246996, -0.05378894125068084, 0.05778001994052505, -0.05017010934737533, 0.1157628090460171, 0.26567327656400525, 0.179634490414963, 0.29602413399274957, -0.49209804048891675, -0.27253764709854833, 0.17524295564480993, 0.13933712786944338, 0.09336536010193039, 0.034185455645463436, -0.31843208641990617, 0.07580034998462123, -0.1793688411080791, -0.03092585672270651, -0.11336561102896582, -0.032482205204261365, 0.013247529687287733, -0.2528838077632263, 0.04803211809598025, 0.006212950601105311, 0.04778085767594708, -0.017322163965260654, -0.09992283594238666, -0.004040954547912576, 0.17037235207263698, 0.026596768695117488, 0.0033956823560098806, 0.12644382964733036, -0.13898762789114502, -0.18722652921330385, 0.37469135797329883, -0.06254682689905167, -0.1899298219833263, 0.20984161083357294, -0.05081516014079946, -0.17274938341836596, 0.05986029018337528, 0.28565644668487383, 0.12618033657420802, -0.10959443490584056, 0.028620574938750632, -0.06135143951130237, 0.1445705570035087, 0.020987600902124315, -0.000561982140580351, 0.15609683379054415, 0.2643801218797561, 0.03814086188425043, 0.12359999381538206, -0.12959563914260488, -0.13569977450682674, -0.20548076462722564, -0.10383396684517, -0.20994511726601123, -0.031568305400857165, -0.1317400917181404, -0.1485805218649465, 0.4524287720023142, 0.2261463491672058, 0.23896727831348372, 0.1549884517290882, 0.3096536444066915, 0.045862243064072765, 0.08608796783585766, 0.09733979403927503, 0.16191357331956888, 0.0344785800431097, 0.1603623796633423, -0.14240152723798455, 0.11409140490275238, 0.004420792350054596] |
1,802.03726 | Event Structures for Petri nets with Persistence | Event structures are a well-accepted model of concurrency. In a seminal paper
by Nielsen, Plotkin and Winskel, they are used to establish a bridge between
the theory of domains and the approach to concurrency proposed by Petri. A
basic role is played by an unfolding construction that maps (safe) Petri nets
into a subclass of event structures, called prime event structures, where each
event has a uniquely determined set of causes. Prime event structures, in turn,
can be identified with their domain of configurations. At a categorical level,
this is nicely formalised by Winskel as a chain of coreflections.
Contrary to prime event structures, general event structures allow for the
presence of disjunctive causes, i.e., events can be enabled by distinct minimal
sets of events. In this paper, we extend the connection between Petri nets and
event structures in order to include disjunctive causes. In particular, we show
that, at the level of nets, disjunctive causes are well accounted for by
persistent places. These are places where tokens, once generated, can be used
several times without being consumed and where multiple tokens are interpreted
collectively, i.e., their histories are inessential. Generalising the work on
ordinary nets, Petri nets with persistence are related to a new subclass of
general event structures, called locally connected, by means of a chain of
coreflections relying on an unfolding construction.
| cs.LO | event structures are a wellaccepted model of concurrency in a seminal paper by nielsen plotkin and winskel they are used to establish a bridge between the theory of domains and the approach to concurrency proposed by petri a basic role is played by an unfolding construction that maps safe petri nets into a subclass of event structures called prime event structures where each event has a uniquely determined set of causes prime event structures in turn can be identified with their domain of configurations at a categorical level this is nicely formalised by winskel as a chain of coreflections contrary to prime event structures general event structures allow for the presence of disjunctive causes ie events can be enabled by distinct minimal sets of events in this paper we extend the connection between petri nets and event structures in order to include disjunctive causes in particular we show that at the level of nets disjunctive causes are well accounted for by persistent places these are places where tokens once generated can be used several times without being consumed and where multiple tokens are interpreted collectively ie their histories are inessential generalising the work on ordinary nets petri nets with persistence are related to a new subclass of general event structures called locally connected by means of a chain of coreflections relying on an unfolding construction | [['event', 'structures', 'are', 'a', 'wellaccepted', 'model', 'of', 'concurrency', 'in', 'a', 'seminal', 'paper', 'by', 'nielsen', 'plotkin', 'and', 'winskel', 'they', 'are', 'used', 'to', 'establish', 'a', 'bridge', 'between', 'the', 'theory', 'of', 'domains', 'and', 'the', 'approach', 'to', 'concurrency', 'proposed', 'by', 'petri', 'a', 'basic', 'role', 'is', 'played', 'by', 'an', 'unfolding', 'construction', 'that', 'maps', 'safe', 'petri', 'nets', 'into', 'a', 'subclass', 'of', 'event', 'structures', 'called', 'prime', 'event', 'structures', 'where', 'each', 'event', 'has', 'a', 'uniquely', 'determined', 'set', 'of', 'causes', 'prime', 'event', 'structures', 'in', 'turn', 'can', 'be', 'identified', 'with', 'their', 'domain', 'of', 'configurations', 'at', 'a', 'categorical', 'level', 'this', 'is', 'nicely', 'formalised', 'by', 'winskel', 'as', 'a', 'chain', 'of', 'coreflections', 'contrary', 'to', 'prime', 'event', 'structures', 'general', 'event', 'structures', 'allow', 'for', 'the', 'presence', 'of', 'disjunctive', 'causes', 'ie', 'events', 'can', 'be', 'enabled', 'by', 'distinct', 'minimal', 'sets', 'of', 'events', 'in', 'this', 'paper', 'we', 'extend', 'the', 'connection', 'between', 'petri', 'nets', 'and', 'event', 'structures', 'in', 'order', 'to', 'include', 'disjunctive', 'causes', 'in', 'particular', 'we', 'show', 'that', 'at', 'the', 'level', 'of', 'nets', 'disjunctive', 'causes', 'are', 'well', 'accounted', 'for', 'by', 'persistent', 'places', 'these', 'are', 'places', 'where', 'tokens', 'once', 'generated', 'can', 'be', 'used', 'several', 'times', 'without', 'being', 'consumed', 'and', 'where', 'multiple', 'tokens', 'are', 'interpreted', 'collectively', 'ie', 'their', 'histories', 'are', 'inessential', 'generalising', 'the', 'work', 'on', 'ordinary', 'nets', 'petri', 'nets', 'with', 'persistence', 'are', 'related', 'to', 'a', 'new', 'subclass', 'of', 'general', 'event', 'structures', 'called', 'locally', 'connected', 'by', 'means', 'of', 'a', 'chain', 'of', 'coreflections', 'relying', 'on', 'an', 'unfolding', 'construction']] | [-0.14636934346791047, 0.11914543606871221, -0.06351785666878439, 0.12365636290568445, -0.10819667072552774, -0.10077175168941419, 0.036000797378623654, 0.3632540026245018, -0.286189373679873, -0.308888947295232, 0.09992870549309171, -0.2654583045961206, -0.14271478734496568, 0.1884804894723412, -0.11778605595541497, 0.00799208859913051, 0.05551649706024263, 0.05267864419457813, 0.006227838139877551, -0.22602234344049874, 0.3403098823523356, 0.039319324371301465, 0.21855559569990468, 0.008140646985007657, 0.11470741442947958, 0.026528067332692445, -0.021359271134198127, 0.07432910066304935, -0.07661798823864148, 0.11560810228188832, 0.3040547504586478, 0.14938421578043037, 0.2255604781396687, -0.4573437650791473, -0.17880216378278824, 0.12774763012511864, 0.12122060255328607, 0.08518408213923168, 0.004590845505913927, -0.2826641406532791, 0.14485029966880877, -0.20127161666336987, -0.05529398296442297, -0.06214515060393347, 0.01840379348335167, 0.052558072581887244, -0.22762693682187496, -0.004009403385635879, 0.13640182650725668, 0.08588138113833137, -0.0006607099922580852, -0.04649585373770808, -0.05334839976703127, 0.09519688123216231, -0.0071392628079694175, 0.007406023415064232, 0.08076349161565304, -0.0785790824310647, -0.21856600245460867, 0.35974185046843354, -0.0013786828823180663, -0.18543110147778255, 0.19735120689185956, -0.08062840765342116, -0.15462332743271773, 0.11848633528855215, 0.1518595079249806, 0.12340137533843518, -0.16942048959434033, 0.07669647711329163, -0.009768311815957229, 0.13339393463658375, 0.11771656070732409, 0.011883799678439068, 0.26941729564219713, 0.1831365552244501, 0.028216540229817233, 0.14942427676015843, -0.03955512051987979, -0.119773829171641, -0.3094664640375413, -0.12574824396132803, -0.10229451999792623, 0.007842868516842525, -0.027361329327492665, -0.1877764911390841, 0.35684716581056514, 0.10593496621962308, 0.2297480465264784, 0.09084948057929675, 0.20948328398168087, 0.09455905917520997, 0.12506482588696397, 0.060761171478985083, 0.14027220748985808, 0.10290353579343194, 0.034540028913567465, -0.10925271786749363, 0.12836500339623955, 0.10955937363828222] |
1,802.03727 | Separation choosability and dense bipartite induced subgraphs | We study a restricted form of list colouring, for which every pair of lists
that correspond to adjacent vertices may not share more than one colour. The
optimal list size such that a proper list colouring is always possible given
this restriction, we call separation choosability. We show for bipartite graphs
that separation choosability increases with (the logarithm of) the minimum
degree. This strengthens results of Molloy and Thron and, partially, of Alon.
One attempt to drop the bipartiteness assumption precipitates a natural class
of Ramsey-type questions, of independent interest. For example, does every
triangle-free graph of minimum degree $d$ contain a bipartite induced subgraph
of minimum degree $\Omega(\log d)$ as $d\to\infty$?
| math.CO cs.DM | we study a restricted form of list colouring for which every pair of lists that correspond to adjacent vertices may not share more than one colour the optimal list size such that a proper list colouring is always possible given this restriction we call separation choosability we show for bipartite graphs that separation choosability increases with the logarithm of the minimum degree this strengthens results of molloy and thron and partially of alon one attempt to drop the bipartiteness assumption precipitates a natural class of ramseytype questions of independent interest for example does every trianglefree graph of minimum degree d contain a bipartite induced subgraph of minimum degree omegalog d as dtoinfty | [['we', 'study', 'a', 'restricted', 'form', 'of', 'list', 'colouring', 'for', 'which', 'every', 'pair', 'of', 'lists', 'that', 'correspond', 'to', 'adjacent', 'vertices', 'may', 'not', 'share', 'more', 'than', 'one', 'colour', 'the', 'optimal', 'list', 'size', 'such', 'that', 'a', 'proper', 'list', 'colouring', 'is', 'always', 'possible', 'given', 'this', 'restriction', 'we', 'call', 'separation', 'choosability', 'we', 'show', 'for', 'bipartite', 'graphs', 'that', 'separation', 'choosability', 'increases', 'with', 'the', 'logarithm', 'of', 'the', 'minimum', 'degree', 'this', 'strengthens', 'results', 'of', 'molloy', 'and', 'thron', 'and', 'partially', 'of', 'alon', 'one', 'attempt', 'to', 'drop', 'the', 'bipartiteness', 'assumption', 'precipitates', 'a', 'natural', 'class', 'of', 'ramseytype', 'questions', 'of', 'independent', 'interest', 'for', 'example', 'does', 'every', 'trianglefree', 'graph', 'of', 'minimum', 'degree', 'd', 'contain', 'a', 'bipartite', 'induced', 'subgraph', 'of', 'minimum', 'degree', 'omegalog', 'd', 'as', 'dtoinfty']] | [-0.1872647446195645, 0.1339574622688815, -0.02337916968722961, 0.04700361766299466, -0.13601928869736316, -0.1755799290611841, 0.10305368017205703, 0.37969841244505786, -0.2600642077325444, -0.34775425006435917, 0.05468736677643652, -0.31743652807615164, -0.13139355351865692, 0.07969878995416886, -0.13549611401062325, 0.010755268222835315, 0.12931242507017618, 0.07871254219207913, 0.03650903572633979, -0.29913665694065067, 0.28146061649437926, -0.03498309107297765, 0.17658987905971507, 0.11766459165041201, 0.05583005144580966, 0.07501154424556132, 0.007569666540283444, 0.10409564159272122, -0.19138495740578168, 0.070428232323528, 0.23855745520475985, 0.21234832280651972, 0.26653088020559934, -0.30844430259717875, -0.14307256079752864, 0.24726762573534092, 0.09556397646831881, 0.09056685137017796, 0.014398167128482393, -0.14620035934370076, 0.13021701331100693, -0.11317880805225806, -0.13615146896336228, 0.038740062221352546, 0.13677690526570327, 0.003103030028536783, -0.2809778104211936, -0.00039284093821022125, 0.1742005388909352, 0.05288809448913006, 0.07251535800501838, -0.18357096433672787, -0.04914519251490544, 0.0917284959931359, -0.0701533669177609, 0.09428417780561306, 0.03520511407467503, -0.10891697147495247, -0.18097471541425744, 0.37385957644853207, -0.003979531302450466, -0.1256689490858532, 0.13816925872275274, -0.124355862964876, -0.2203030944731706, 0.13038393307942897, 0.11055193854761976, 0.13809347694041207, -0.08014040154687661, 0.03865858587232651, -0.16651978118378402, 0.17438267239153252, 0.19741908896581403, 0.08280189830527108, 0.1298275782854554, 0.11658430521077078, 0.19116937934346165, 0.20933125057698426, 0.019623125437647104, 0.0032647825506241395, -0.32576634833822027, -0.12710019695181732, -0.24801356020699522, 0.08782265289599829, -0.19662009805298503, -0.20113657571242324, 0.37615278678172864, 0.10845238527170815, 0.19382530341889442, 0.10216823111425453, 0.1672266768541054, 0.02661706277597529, 0.06498565761181194, 0.1673619913802083, 0.11704621495612498, 0.16648802312036942, -0.050278571322061386, -0.19007855775167368, 0.11634402669109736, 0.1263546039470904] |
1,802.03728 | Strongly suppressed superconducting proximity effect and ferromagnetism
in trilayers of $\rm Bi_2Se_3$ / $\rm SrRuO_3$ / underdoped $\rm
YBa_2Cu_3O_x$: A possible new platform for Majorana nano-electronics | We report properties of topological insulator - ferromagnet - superconductor
trilayers comprised of thin films of 20 nm thick $\rm Bi_2Se_3$ on 10 nm $\rm
SrRuO_3$ on 30 nm $\rm YBa_2Cu_3O_x$. As deposited trilayers are underdoped and
have a superconductive transition with $\rm T_c$ onset at 75 K, zero resistance
at 65 K, $\rm T_{Cueri}$ at 150 K and $\rm T^*$ of about 200 K. Further
reannealing under vacuum yields the 60 K phase of $\rm YBa_2Cu_3O_x$ which
still has zero resistance below about 40 K. Only when $10\times 100$
micro-bridges were patterned in the trilayer, some of the bridges showed
resistive behavior all the way down to low temperatures. Magnetoresistance
versus temperature of the superconductive ones showed the typical peak due to
flux flow against pinning below $\rm T_c$, while the resistive ones showed only
the broad leading edge of such a peak. All this indicates clearly weak-link
superconductivity in the resistive bridges between superconductive $\rm
YBa_2Cu_3O_x$ grains via the topological and ferromagnetic cap layers.
Comparing our results to those of a reference trilayer with the topological
$\rm Bi_2Se_3$ layer substituted by a non-superconducting highly overdoped $\rm
La_{1.65}Sr_{0.35}CuO_4$, indicates that the superconductive proximity effect
as well as ferromagnetism in the topological trilayer are actually strongly
suppressed compared to the non-topological reference trilayer. This strong
suppression is likely to originate in strong proximity induced edge currents in
the SRO/YBCO layer that can lead to Majorana bound states, a possible signature
of which is observed in the present study as zero bias conductance peaks.
| cond-mat.supr-con | we report properties of topological insulator ferromagnet superconductor trilayers comprised of thin films of 20 nm thick rm bi_2se_3 on 10 nm rm srruo_3 on 30 nm rm yba_2cu_3o_x as deposited trilayers are underdoped and have a superconductive transition with rm t_c onset at 75 k zero resistance at 65 k rm t_cueri at 150 k and rm t of about 200 k further reannealing under vacuum yields the 60 k phase of rm yba_2cu_3o_x which still has zero resistance below about 40 k only when 10times 100 microbridges were patterned in the trilayer some of the bridges showed resistive behavior all the way down to low temperatures magnetoresistance versus temperature of the superconductive ones showed the typical peak due to flux flow against pinning below rm t_c while the resistive ones showed only the broad leading edge of such a peak all this indicates clearly weaklink superconductivity in the resistive bridges between superconductive rm yba_2cu_3o_x grains via the topological and ferromagnetic cap layers comparing our results to those of a reference trilayer with the topological rm bi_2se_3 layer substituted by a nonsuperconducting highly overdoped rm la_165sr_035cuo_4 indicates that the superconductive proximity effect as well as ferromagnetism in the topological trilayer are actually strongly suppressed compared to the nontopological reference trilayer this strong suppression is likely to originate in strong proximity induced edge currents in the sroybco layer that can lead to majorana bound states a possible signature of which is observed in the present study as zero bias conductance peaks | [['we', 'report', 'properties', 'of', 'topological', 'insulator', 'ferromagnet', 'superconductor', 'trilayers', 'comprised', 'of', 'thin', 'films', 'of', '20', 'nm', 'thick', 'rm', 'bi_2se_3', 'on', '10', 'nm', 'rm', 'srruo_3', 'on', '30', 'nm', 'rm', 'yba_2cu_3o_x', 'as', 'deposited', 'trilayers', 'are', 'underdoped', 'and', 'have', 'a', 'superconductive', 'transition', 'with', 'rm', 't_c', 'onset', 'at', '75', 'k', 'zero', 'resistance', 'at', '65', 'k', 'rm', 't_cueri', 'at', '150', 'k', 'and', 'rm', 't', 'of', 'about', '200', 'k', 'further', 'reannealing', 'under', 'vacuum', 'yields', 'the', '60', 'k', 'phase', 'of', 'rm', 'yba_2cu_3o_x', 'which', 'still', 'has', 'zero', 'resistance', 'below', 'about', '40', 'k', 'only', 'when', '10times', '100', 'microbridges', 'were', 'patterned', 'in', 'the', 'trilayer', 'some', 'of', 'the', 'bridges', 'showed', 'resistive', 'behavior', 'all', 'the', 'way', 'down', 'to', 'low', 'temperatures', 'magnetoresistance', 'versus', 'temperature', 'of', 'the', 'superconductive', 'ones', 'showed', 'the', 'typical', 'peak', 'due', 'to', 'flux', 'flow', 'against', 'pinning', 'below', 'rm', 't_c', 'while', 'the', 'resistive', 'ones', 'showed', 'only', 'the', 'broad', 'leading', 'edge', 'of', 'such', 'a', 'peak', 'all', 'this', 'indicates', 'clearly', 'weaklink', 'superconductivity', 'in', 'the', 'resistive', 'bridges', 'between', 'superconductive', 'rm', 'yba_2cu_3o_x', 'grains', 'via', 'the', 'topological', 'and', 'ferromagnetic', 'cap', 'layers', 'comparing', 'our', 'results', 'to', 'those', 'of', 'a', 'reference', 'trilayer', 'with', 'the', 'topological', 'rm', 'bi_2se_3', 'layer', 'substituted', 'by', 'a', 'nonsuperconducting', 'highly', 'overdoped', 'rm', 'la_165sr_035cuo_4', 'indicates', 'that', 'the', 'superconductive', 'proximity', 'effect', 'as', 'well', 'as', 'ferromagnetism', 'in', 'the', 'topological', 'trilayer', 'are', 'actually', 'strongly', 'suppressed', 'compared', 'to', 'the', 'nontopological', 'reference', 'trilayer', 'this', 'strong', 'suppression', 'is', 'likely', 'to', 'originate', 'in', 'strong', 'proximity', 'induced', 'edge', 'currents', 'in', 'the', 'sroybco', 'layer', 'that', 'can', 'lead', 'to', 'majorana', 'bound', 'states', 'a', 'possible', 'signature', 'of', 'which', 'is', 'observed', 'in', 'the', 'present', 'study', 'as', 'zero', 'bias', 'conductance', 'peaks']] | [-0.18336133744225896, 0.2349538877892736, 0.009662500693417725, -0.009201910172123462, -0.010776694578629347, -0.1613985438265034, 0.10068803085971834, 0.38399648892828414, -0.2291367670667598, -0.3344700411525405, -0.0007867263827187519, -0.37321564980271843, -0.030850004337187254, 0.18601358221043954, 0.04409180978977782, -0.009663084837337655, -0.0753598419297862, -0.027254366781797275, -0.11672071013022252, -0.20760951693087154, 0.25174900966756525, -0.016332242383448888, 0.3581412218608743, 0.09622314856753819, -0.011960346084613833, -0.10296929108276785, 0.16577561296364893, 0.033501218046782716, -0.1736204573331751, -0.02960578837308041, 0.2919743277250804, -0.14800158317478734, 0.17213917504470314, -0.4141511601816502, -0.17317648196025873, -0.017175666068778222, 0.12466635946710143, 0.06370056472857663, -0.024422154223547324, -0.2755212420672779, 0.19663143920009926, -0.11112843205750499, -0.06880981281339642, -0.016393476573284715, -0.0003462442001628299, -0.07299600019060533, -0.21249166467990313, 0.13233431837157225, 0.09893277395589863, 0.12337811960512021, -0.03057402850789649, -0.19025634149945672, -0.12441941791011261, -0.01809531069140517, 0.044069547966618335, 0.09970940246562203, 0.20161816761490978, -0.10020561456669032, -0.0725595113138796, 0.3007497542663083, -0.10104569384401979, 0.025063109913917875, 0.16391215162471898, -0.20239779610569858, -0.01251146113668989, 0.20616089309107571, 0.06464452559368745, 0.11074601745232, -0.09795911736241138, 0.058352946140779925, -0.03985929074922517, 0.20805652015617176, 0.08600248557782071, 0.09362006558465862, 0.23810764555744227, 0.20468425088150863, 0.048190231226345207, 0.144915982175594, -0.16103245970800578, 0.03040653614927226, -0.2409936373855265, -0.15889390256192965, -0.1454877870827688, 0.1271124206804445, -0.07848042899569273, -0.17866820062326658, 0.3436193252094991, 0.15303839946864173, 0.24425080785107228, -0.03945515974943015, 0.20839825933123188, 0.06003744385417385, 0.10966723930886796, 0.07050805972352053, 0.2396736502702087, 0.21592227397524122, 0.13995757426005917, -0.2616607119224124, 0.09044832118783117, -0.059973324704192386] |
1,802.03729 | The three point gauge algebra $\mathcal V\ltimes \mathfrak{sl}(2,
\mathcal R) \oplus\left(\Omega_{\mathcal R}/d{\mathcal R}\right)$ and an
action on a Fock space | The three point current algebra $\mathfrak{sl}(2,\mathcal R)$ where $\mathcal
R=\mathbb C[t,t^{-1},u\,|\,u^2=t^2+4t ]$ and three-point Virasoro algebra both
act on a previously constructed Fock space. In this paper we prove that the
semi-direct product, i.e. the gauge algebra acts on the Fock space as well.
| math.RT | the three point current algebra mathfraksl2mathcal r where mathcal rmathbb ctt1uu2t24t and threepoint virasoro algebra both act on a previously constructed fock space in this paper we prove that the semidirect product ie the gauge algebra acts on the fock space as well | [['the', 'three', 'point', 'current', 'algebra', 'mathfraksl2mathcal', 'r', 'where', 'mathcal', 'rmathbb', 'ctt1uu2t24t', 'and', 'threepoint', 'virasoro', 'algebra', 'both', 'act', 'on', 'a', 'previously', 'constructed', 'fock', 'space', 'in', 'this', 'paper', 'we', 'prove', 'that', 'the', 'semidirect', 'product', 'ie', 'the', 'gauge', 'algebra', 'acts', 'on', 'the', 'fock', 'space', 'as', 'well']] | [-0.16356026004182128, 0.13013540839821827, -0.00809511181148814, 0.019853343082614605, -0.12126698993464433, -0.07318620337173343, -0.05602783902559611, 0.349777058584661, -0.32174143867521754, -0.13981402642661478, 0.14865797514766, -0.2297269783278064, -0.14337989524370287, 0.14839342927060475, -0.06697829405879374, -0.05572781066705541, 0.040862249528489464, 0.13550752916986622, -0.10693890609914755, -0.24792689843693885, 0.44583176757867743, -0.013061124365776777, 0.2902565726147192, -0.03887141709465806, 0.15620466034359684, 0.07956265396915557, -0.0207562768695558, -0.060011193271237995, -0.14085942786843544, 0.02689417183580922, 0.2521261481295635, 0.08158650493998898, 0.17417372608693635, -0.39463847037404776, -0.08219949880660307, 0.17655071220928575, 0.20390329291907752, -0.02493763476519323, 0.022947953593712753, -0.32411710413672573, -0.043176664607372225, -0.30495786094447463, -0.03736687857351016, -0.0973360212406189, 0.03612501210555798, -0.10812197830073716, -0.2836335076518902, -0.004138085059821606, 0.03161905994695589, 0.03864072369434303, -0.0865735000499138, -0.14561271392626735, -0.17636951486716365, 0.06695672675467483, -0.06934895599260926, 0.15180494202437197, 0.1698603726719029, -0.06769811727174717, -0.14820657143505608, 0.3508206601368218, -0.061029377416139695, -0.2896440348974088, 0.11021362443840722, -0.220185219060357, -0.21384725183611963, -0.06300160420558802, 0.06293500202321788, 0.13664214499294758, -0.007219930202132318, 0.304097998295286, -0.1445686241566408, 0.019340437249899502, 0.0828653666667822, 0.07945988162579697, 0.11271828912743707, 0.08056736657986553, 0.07394615289323576, 0.1397841369687784, 0.06236836428913038, -0.040454173437887576, -0.43667682805439323, -0.20605147995690748, -0.16154406769428312, 0.13378556938160482, -0.10879734145987086, -0.1697260888702259, 0.38921008443051, 0.10963702588001402, 0.20109835639595985, 0.07907465647724343, 0.2252180062506984, 0.1140218426604051, 0.14646178256811165, 0.07493112604247361, 0.12508902530662896, 0.17338487823925366, -0.033129247643689554, -0.14963277499617372, -0.13067006361784367, 0.2551393694948496] |
1,802.0373 | Rederiving the Upper Bound for Halving Edges using Cardano's Formula | In this paper we rederive an old upper bound on the number of halving edges
present in the halving graph of an arbitrary set of $n$ points in 2-dimensions
which are placed in general position. We provide a different analysis of an
identity discovered by Andrejak et al, to rederive this upper bound of
$O(n^{4/3})$. In the original paper of Andrejak et al. the proof is based on a
naive analysis whereas in this paper we obtain the same upper bound by
tightening the analysis thereby opening a new door to derive these upper bounds
using the identity. Our analysis is based on a result of Cardano for finding
the roots of a cubic equation. We believe that our technique has the potential
to derive improved bounds on the number of halving edges.
| cs.CG | in this paper we rederive an old upper bound on the number of halving edges present in the halving graph of an arbitrary set of n points in 2dimensions which are placed in general position we provide a different analysis of an identity discovered by andrejak et al to rederive this upper bound of on43 in the original paper of andrejak et al the proof is based on a naive analysis whereas in this paper we obtain the same upper bound by tightening the analysis thereby opening a new door to derive these upper bounds using the identity our analysis is based on a result of cardano for finding the roots of a cubic equation we believe that our technique has the potential to derive improved bounds on the number of halving edges | [['in', 'this', 'paper', 'we', 'rederive', 'an', 'old', 'upper', 'bound', 'on', 'the', 'number', 'of', 'halving', 'edges', 'present', 'in', 'the', 'halving', 'graph', 'of', 'an', 'arbitrary', 'set', 'of', 'n', 'points', 'in', '2dimensions', 'which', 'are', 'placed', 'in', 'general', 'position', 'we', 'provide', 'a', 'different', 'analysis', 'of', 'an', 'identity', 'discovered', 'by', 'andrejak', 'et', 'al', 'to', 'rederive', 'this', 'upper', 'bound', 'of', 'on43', 'in', 'the', 'original', 'paper', 'of', 'andrejak', 'et', 'al', 'the', 'proof', 'is', 'based', 'on', 'a', 'naive', 'analysis', 'whereas', 'in', 'this', 'paper', 'we', 'obtain', 'the', 'same', 'upper', 'bound', 'by', 'tightening', 'the', 'analysis', 'thereby', 'opening', 'a', 'new', 'door', 'to', 'derive', 'these', 'upper', 'bounds', 'using', 'the', 'identity', 'our', 'analysis', 'is', 'based', 'on', 'a', 'result', 'of', 'cardano', 'for', 'finding', 'the', 'roots', 'of', 'a', 'cubic', 'equation', 'we', 'believe', 'that', 'our', 'technique', 'has', 'the', 'potential', 'to', 'derive', 'improved', 'bounds', 'on', 'the', 'number', 'of', 'halving', 'edges']] | [-0.1294041549971768, 0.05324359588937759, -0.0997077449676332, 0.002997003178439238, -0.09074262826781691, -0.07544441025291804, 0.1446736851175678, 0.2522535057203446, -0.19032620611238002, -0.39870675078785145, 0.09883742998283043, -0.2546785428572645, -0.17428578374701204, 0.22994241144024688, -0.08586482269305537, 0.012122884584690323, 0.03289407636358879, 0.04209868541500133, -0.05479773217705541, -0.2948425639438965, 0.2943460195616798, 0.05459292279200927, 0.24479848683193212, 0.09958567235704141, 0.0489875839895192, 0.029101918652326666, -0.054567204503953914, -0.02608017315590427, -0.19677094690607663, 0.19706994574872477, 0.1739204866928937, 0.13574055917845426, 0.23891919738975645, -0.41327339823123155, -0.15245130014755115, 0.09553865275793631, 0.16898530745480694, 0.12568954789552497, -0.05810986108942853, -0.2595510609583033, 0.08604458282268002, -0.10740254503383323, -0.15671660458555317, -0.018987514602930376, 0.03248296999763555, -0.002706055998631561, -0.280600068984084, 0.033577938226428426, 0.11837692443594222, 0.04174846820870969, -0.037024887598596, -0.15583915759201467, 0.04393866525443967, 0.08206515812194189, -0.0071935707326438135, 0.04663447136430866, 0.017864416783519146, -0.08524284723840427, -0.12415895604116145, 0.29899681326826566, -0.09534036779584264, -0.17458124012146004, 0.1428091029622343, -0.10334291707607474, -0.1725386000835543, 0.07462133074584523, 0.1966657294067092, 0.14743611633151998, -0.15517393952655031, 0.12618270858709935, -0.15421658858855944, 0.13891514743685382, 0.09498328413060717, 0.010619464048223556, 0.11451116451666556, 0.1451374893729888, 0.12464640284568526, 0.19484858505626898, -0.06549502658934994, -0.042453717235084766, -0.3154322471938857, -0.16450670767772788, -0.21443152192709897, 0.041899431052525304, -0.10640463917978278, -0.17750050813379123, 0.3729328237134494, 0.18822043455554216, 0.2597708379110421, 0.09624767406640987, 0.2864023936265468, 0.17058365456220065, 0.012891911742906619, 0.12684707910916967, 0.25232342372556, 0.1169031209166638, 0.01835669681984391, -0.16336033248363901, 0.06670864730653929, 0.1525002409462312] |
1,802.03731 | Robust Private Information Retrieval from Coded Systems with Byzantine
and Colluding Servers | A private information retrieval (PIR) scheme on coded storage systems with
colluding, byzantine, and non-responsive servers is presented. Furthermore, the
scheme can also be used for symmetric PIR in the same setting.
An explicit scheme using an $[n,k]$ generalized Reed-Solomon storage code is
designed, protecting against $t$-collusion and handling up to $b$ byzantine and
$r$ non-responsive servers, when $n\geq n'= (\nu +1) k+t+2b+r-1$, for some
integer $\nu \geq 1$. This scheme achieves a PIR rate of
$1-\frac{k+2b+t+r-1}{n'}$. In the case where the capacity is known, namely when
$k=1$, it is asymptotically capacity achieving as the number of files grows.
| cs.IT math.IT | a private information retrieval pir scheme on coded storage systems with colluding byzantine and nonresponsive servers is presented furthermore the scheme can also be used for symmetric pir in the same setting an explicit scheme using an nk generalized reedsolomon storage code is designed protecting against tcollusion and handling up to b byzantine and r nonresponsive servers when ngeq n nu 1 kt2br1 for some integer nu geq 1 this scheme achieves a pir rate of 1frack2btr1n in the case where the capacity is known namely when k1 it is asymptotically capacity achieving as the number of files grows | [['a', 'private', 'information', 'retrieval', 'pir', 'scheme', 'on', 'coded', 'storage', 'systems', 'with', 'colluding', 'byzantine', 'and', 'nonresponsive', 'servers', 'is', 'presented', 'furthermore', 'the', 'scheme', 'can', 'also', 'be', 'used', 'for', 'symmetric', 'pir', 'in', 'the', 'same', 'setting', 'an', 'explicit', 'scheme', 'using', 'an', 'nk', 'generalized', 'reedsolomon', 'storage', 'code', 'is', 'designed', 'protecting', 'against', 'tcollusion', 'and', 'handling', 'up', 'to', 'b', 'byzantine', 'and', 'r', 'nonresponsive', 'servers', 'when', 'ngeq', 'n', 'nu', '1', 'kt2br1', 'for', 'some', 'integer', 'nu', 'geq', '1', 'this', 'scheme', 'achieves', 'a', 'pir', 'rate', 'of', '1frack2btr1n', 'in', 'the', 'case', 'where', 'the', 'capacity', 'is', 'known', 'namely', 'when', 'k1', 'it', 'is', 'asymptotically', 'capacity', 'achieving', 'as', 'the', 'number', 'of', 'files', 'grows']] | [-0.26527490082905086, 0.06115863571449154, 0.027197981127149735, 0.009700706537842052, 0.005999045678133068, -0.37377361659309827, 0.10650052531855181, 0.3159698879656692, -0.2979990801929186, -0.27308193495264277, 0.13991497142463535, -0.3145858146356962, -0.07073876704695674, 0.17485124297672883, -0.1462400067054356, 0.09393163673424472, -0.033163790557106644, 0.11484270712632376, 0.011887953655483821, -0.39030305098276585, 0.25494412665527005, 0.11751152533664329, 0.2606330007693032, 0.018807034498119417, 0.03913959537749179, 0.00992375731584616, 0.01564841721362124, -0.04509879638499115, -0.12478168121803417, 0.046979204344097525, 0.32872802104247967, 0.2028478489325304, 0.21219869687532386, -0.31928607694438443, -0.17124266703225052, 0.14681725348661226, 0.16896294946976317, 0.13154187433732054, -0.053005820461597374, -0.21784812650245536, 0.1962620540483234, -0.2442389786010608, -0.0401696803116162, -0.07764411354825522, 0.056511651438389286, 0.00674684460197265, -0.42072645827041316, -0.021713170681626554, 0.04210635559866205, 0.04903185317380121, -0.02346284759308522, -0.11127081794741873, 0.051353046767568834, 0.12151679878600892, -0.021433206882647937, 0.0750923732642453, 0.061883244054115494, -0.07488759673772923, -0.10778095038646522, 0.38454846090947586, -0.02171102721816472, -0.22831355780363083, 0.08328045477295139, -0.04142917455950131, -0.11372757714222341, 0.13896296203165548, 0.1731540522305295, 0.1652614434933639, -0.08312676296585171, 0.10907719511487812, -0.08116696587724921, 0.2450768436768461, 0.09721805580193177, 0.10437827679561451, 0.07378195534693077, 0.1266052263090387, 0.1223553773046054, 0.19513493153378172, -0.07477922869293252, -0.10309752976172604, -0.2601613445525193, -0.179249629911889, -0.23297834030624168, 0.046799796533984285, -0.16629390204085817, -0.04928662879198479, 0.23944873715466505, 0.10836284962230518, 0.12852693703219606, 0.13291934054723242, 0.3764979394036345, 0.006122209644672694, 0.062036391709625605, 0.2857651601273877, 0.07017818905933382, 0.06327559734442427, 0.09089842741923349, -0.18988855326218376, 0.07446904236955258, 0.032135563485401995] |
1,802.03732 | Nef anti-canonical divisors and rationally connected fibrations | We study the Iitaka-Kodaira dimension of nef relative anti-canonical
divisors. As a consequence, we prove that given a complex projective variety
with klt singularities, if the anti-canonical divisor is nef, then the
dimension of a general fibre of the maximal rationally connected fibration is
at least the Iitaka-Kodaira dimension of the anti-canonical divisor.
| math.AG | we study the iitakakodaira dimension of nef relative anticanonical divisors as a consequence we prove that given a complex projective variety with klt singularities if the anticanonical divisor is nef then the dimension of a general fibre of the maximal rationally connected fibration is at least the iitakakodaira dimension of the anticanonical divisor | [['we', 'study', 'the', 'iitakakodaira', 'dimension', 'of', 'nef', 'relative', 'anticanonical', 'divisors', 'as', 'a', 'consequence', 'we', 'prove', 'that', 'given', 'a', 'complex', 'projective', 'variety', 'with', 'klt', 'singularities', 'if', 'the', 'anticanonical', 'divisor', 'is', 'nef', 'then', 'the', 'dimension', 'of', 'a', 'general', 'fibre', 'of', 'the', 'maximal', 'rationally', 'connected', 'fibration', 'is', 'at', 'least', 'the', 'iitakakodaira', 'dimension', 'of', 'the', 'anticanonical', 'divisor']] | [-0.25971955400617686, 0.01574292802708406, -0.08494661486360665, 0.08740486835093036, -0.10645940164834553, -0.27504350740791245, -0.04558512704063426, 0.2892087781253983, -0.3189247514979512, -0.05089103414074463, 0.06107042357325554, -0.2894668964230839, -0.1950624576842814, 0.16957453090478392, -0.2463845902980835, -0.00012548705197724643, 0.048799771482271014, 0.10859994298102808, -0.11248081901987247, -0.37786883590560333, 0.5767974697199523, -0.11024568704705612, 0.20955629555471972, 0.20551525494631598, 0.20999676938734801, -0.037554958890027856, 0.10167474997248135, 0.021938082926413593, -0.14913745201264128, 0.1653982092553348, 0.36828120257340224, 0.1251173259453008, 0.1532144207854335, -0.3181270584464073, -0.12834025428210402, 0.3444117501962419, 0.11524662373624012, -0.02664127666503191, 0.06033742474848587, -0.15631752095970453, 0.0963247303540508, -0.11068536436148718, -0.37416250541733176, -0.07045392133295536, 0.06246992120263623, 0.025484901510507744, -0.16581474467381543, -0.11457800916304775, 0.05454736304832919, 0.23885337643179239, 0.10631589374194543, -0.0529274422762112, -0.20610270118706076, -0.07824571353757717, 0.03934918649896395, 0.06952586749513798, 0.1026335141128477, -0.12137222721004019, -0.054130826775422865, 0.3397265910079666, -0.0982728916786465, -0.2216978357630033, 0.0874985770925003, -0.17282681148864476, -0.08891957669117141, 0.210995015606065, 0.09292249167885851, 0.25702951603806484, 0.08854063339166197, 0.19446494130819453, -0.1569025593755, 0.07450237797171462, 0.1427988146760446, -0.008282354196268773, 0.08614743087787692, 0.17376770593189433, 0.13803555724192776, 0.05354214876013644, -0.07262264403934572, 0.032622329580287136, -0.4430779510853337, -0.2858036076284799, -0.15562193097510174, 0.3120056322100116, -0.2102612846293578, -0.1540788560923116, 0.41343011792895257, -0.033977068723270706, 0.2820004092931163, 0.18364373442954293, 0.30550835604834203, -0.008974865537739414, 0.049050410369447635, 0.04404495566782048, 0.15569442824697963, 0.22973450821112185, -0.15049634343378393, -0.12917225103934898, -0.008081274287428195, 0.24916323656946712] |
1,802.03733 | Zero limit of entropic relaxation time for the Shliomis model of
ferrofluids | We construct solutions for the Shilomis model of ferrofluids in a critical
space, uniformly in the entropic relaxation time $ \tau \in\left(0,
\tau_0\right) $. This allows us to study the convergence when $ \tau\to 0 $ for
such solutions.
| math.AP | we construct solutions for the shilomis model of ferrofluids in a critical space uniformly in the entropic relaxation time tau inleft0 tau_0right this allows us to study the convergence when tauto 0 for such solutions | [['we', 'construct', 'solutions', 'for', 'the', 'shilomis', 'model', 'of', 'ferrofluids', 'in', 'a', 'critical', 'space', 'uniformly', 'in', 'the', 'entropic', 'relaxation', 'time', 'tau', 'inleft0', 'tau_0right', 'this', 'allows', 'us', 'to', 'study', 'the', 'convergence', 'when', 'tauto', '0', 'for', 'such', 'solutions']] | [-0.09495930263074115, 0.11618106500827707, -0.10179104772396386, 0.08626383576120134, -0.029466030129697174, -0.1363586999796098, 0.05599280458409339, 0.2969896288122982, -0.3067971473792568, -0.20440160285215825, 0.09858426784194307, -0.2872446191981908, -0.08661926945205778, 0.18826164607162355, -2.7593938284553587e-05, 0.13068218086846173, 0.0066446892014937475, 0.006844141491455957, -0.060124584240838885, -0.19075158596388064, 0.2710247593058739, -0.01491694524884224, 0.22285632544662803, 0.02402887211064808, 0.05834910916746594, -0.020467773345444584, 0.055311651856754906, 0.006038295191501675, -0.293023429781897, 0.06485352167510428, 0.22191898699384183, 0.09593670355388895, 0.2819659118540585, -0.3868524022400379, -0.16561850532889366, 0.19754046073649079, 0.1947588312032167, 0.11583939124830067, -0.004101922735571861, -0.2546825271565467, 0.10434671861003153, -0.1288476325571537, -0.15093543124385178, -0.15487336448859423, 0.06884731771424413, 0.036758712252776604, -0.35450858244439587, 0.06805861463362817, 0.05424353654962033, -0.023577015061164275, -0.14645330599341833, -0.03502366706379689, 0.08791558933444321, 0.1071871248395837, 0.13133992009898066, 0.058762080589076504, 0.026763503279653378, -0.11305529635137646, -0.08931575287715532, 0.3734337647911161, -0.10284678296011407, -0.28391315741464496, 0.18291634085471742, -0.20606447756290436, -0.1649106835538987, 0.11855011252919212, 0.20406554729561321, 0.18200448124844115, -0.1266840537086864, 0.1678401256504003, -0.008362539098015986, 0.13615668582497165, 0.022446346352808177, 0.019670027104439214, 0.12446790299145505, 0.1914763783206581, 0.15145446098176762, 0.17733769526239485, -0.06512219323485624, -0.11400266556302086, -0.33046300045680255, -0.23278831026982516, -0.1174573865137063, 0.12428421431104653, -0.1469738220621366, -0.15431633789557964, 0.40001616593508516, 0.16427016508532688, 0.2024976776447147, 0.13494565425207838, 0.22115147800650448, 0.12158459854981629, 0.0068545986141543835, 0.08346368817728944, 0.2204272346352809, 0.09010611893609166, 0.14606433227891102, -0.24136382463620976, 0.057659093483380275, 0.10456448706099764] |
1,802.03734 | The Use of Presence Data in Modelling Demand for Transportation | We consider the applicability of the data from operators of cellular systems
to modelling demand for transportation. While individual-level data may contain
precise paths of movement, stringent privacy rules prohibit their use without
consent. Presence data aggregate the individual-level data to information on
the numbers of transactions at each base transceiver station (BTS) per each
time period. Our work is aimed at demonstrating value of such aggregate data
for mobility management while maintaining privacy of users. In particular,
given mobile subscriber activity aggregated to short time intervals for a zone,
a convex optimisation problem estimates most likely transitions between zones.
We demonstrate the method on presence data from Warsaw, Poland, and compare
with official demand estimates obtained with classical econometric methods.
| math.OC cs.DS | we consider the applicability of the data from operators of cellular systems to modelling demand for transportation while individuallevel data may contain precise paths of movement stringent privacy rules prohibit their use without consent presence data aggregate the individuallevel data to information on the numbers of transactions at each base transceiver station bts per each time period our work is aimed at demonstrating value of such aggregate data for mobility management while maintaining privacy of users in particular given mobile subscriber activity aggregated to short time intervals for a zone a convex optimisation problem estimates most likely transitions between zones we demonstrate the method on presence data from warsaw poland and compare with official demand estimates obtained with classical econometric methods | [['we', 'consider', 'the', 'applicability', 'of', 'the', 'data', 'from', 'operators', 'of', 'cellular', 'systems', 'to', 'modelling', 'demand', 'for', 'transportation', 'while', 'individuallevel', 'data', 'may', 'contain', 'precise', 'paths', 'of', 'movement', 'stringent', 'privacy', 'rules', 'prohibit', 'their', 'use', 'without', 'consent', 'presence', 'data', 'aggregate', 'the', 'individuallevel', 'data', 'to', 'information', 'on', 'the', 'numbers', 'of', 'transactions', 'at', 'each', 'base', 'transceiver', 'station', 'bts', 'per', 'each', 'time', 'period', 'our', 'work', 'is', 'aimed', 'at', 'demonstrating', 'value', 'of', 'such', 'aggregate', 'data', 'for', 'mobility', 'management', 'while', 'maintaining', 'privacy', 'of', 'users', 'in', 'particular', 'given', 'mobile', 'subscriber', 'activity', 'aggregated', 'to', 'short', 'time', 'intervals', 'for', 'a', 'zone', 'a', 'convex', 'optimisation', 'problem', 'estimates', 'most', 'likely', 'transitions', 'between', 'zones', 'we', 'demonstrate', 'the', 'method', 'on', 'presence', 'data', 'from', 'warsaw', 'poland', 'and', 'compare', 'with', 'official', 'demand', 'estimates', 'obtained', 'with', 'classical', 'econometric', 'methods']] | [-0.15069511747526482, 0.001694909962710024, -0.01617340768941424, 0.07151733756484849, -0.09780278441319165, -0.1681062328159686, 0.18577801929555895, 0.3649353184544843, -0.24462950354430454, -0.34209130779832353, 0.1413938800211657, -0.355990735513797, -0.06790755768999272, 0.2007614089414662, -0.12839564100323506, 0.04756584823081531, 0.11459881280672021, 0.04341643911686318, 0.006629004808958651, -0.2571599610757914, 0.2768469043105503, 0.07556536501227332, 0.3541870162906972, 0.031217341784634128, 0.07614824910405715, 0.04764451464053151, -0.07915728973452779, -0.036534051657154044, -0.09641200794130256, 0.16667996666274873, 0.34523198990442805, 0.18887958760673473, 0.33380293896929786, -0.4826792558301086, -0.204000912552838, 0.09206140209913008, 0.08502239467141272, 0.06422402533079105, -0.02048033027340127, -0.2832714800669019, 0.05054220261460186, -0.16092012115092255, -0.086832159866525, -0.042421578775998975, -0.003685450335302629, 0.06687869833231988, -0.3088243145607258, 0.06723474786609165, -0.04298932305806555, 0.14179964799218434, -0.08727684874310782, -0.0941405103903664, -0.0789072099853738, 0.1957050814285628, 0.08484555755584108, -0.06716619176532272, 0.13562886762502027, -0.09611580248013878, -0.15112810087782785, 0.39336016032198245, 0.003309029141009962, -0.15455325202215925, 0.16213738977185582, -0.12636653884229335, -0.16137272967141092, 0.11692545855464029, 0.2620207590834153, 0.05741355822167613, -0.19810780192425181, 0.004663357603044272, 0.0060826215839152, 0.17220196480697314, 0.05694366838352, 0.04314692074255941, 0.20243072445689092, 0.20493839477758455, 0.12226502863451653, 0.047179004308298106, -0.1013345201384307, -0.11442318873495357, -0.2376754655183316, -0.09323941360512548, -0.16691979039691326, 0.004259561450212948, -0.10930077479524472, -0.09155096941673743, 0.33815200548726787, 0.1855412152550599, 0.16213589608462428, 0.12601739820477761, 0.3415434789066472, 0.06006408377823782, 0.08786974214019797, 0.11199283364713808, 0.11924678039513836, 0.002142622233714816, 0.1861214534425723, -0.1712691410298436, 0.1276435773619566, 0.01665004052814435] |
1,802.03735 | Structural Estimation of Behavioral Heterogeneity | We develop a behavioral asset pricing model in which agents trade in a market
with information friction. Profit-maximizing agents switch between trading
strategies in response to dynamic market conditions. Due to noisy private
information about the fundamental value, the agents form different evaluations
about heterogeneous strategies. We exploit a thin set---a small
sub-population---to pointly identify this nonlinear model, and estimate the
structural parameters using extended method of moments. Based on the estimated
parameters, the model produces return time series that emulate the moments of
the real data. These results are robust across different sample periods and
estimation methods.
| q-fin.TR econ.EM | we develop a behavioral asset pricing model in which agents trade in a market with information friction profitmaximizing agents switch between trading strategies in response to dynamic market conditions due to noisy private information about the fundamental value the agents form different evaluations about heterogeneous strategies we exploit a thin seta small subpopulationto pointly identify this nonlinear model and estimate the structural parameters using extended method of moments based on the estimated parameters the model produces return time series that emulate the moments of the real data these results are robust across different sample periods and estimation methods | [['we', 'develop', 'a', 'behavioral', 'asset', 'pricing', 'model', 'in', 'which', 'agents', 'trade', 'in', 'a', 'market', 'with', 'information', 'friction', 'profitmaximizing', 'agents', 'switch', 'between', 'trading', 'strategies', 'in', 'response', 'to', 'dynamic', 'market', 'conditions', 'due', 'to', 'noisy', 'private', 'information', 'about', 'the', 'fundamental', 'value', 'the', 'agents', 'form', 'different', 'evaluations', 'about', 'heterogeneous', 'strategies', 'we', 'exploit', 'a', 'thin', 'seta', 'small', 'subpopulationto', 'pointly', 'identify', 'this', 'nonlinear', 'model', 'and', 'estimate', 'the', 'structural', 'parameters', 'using', 'extended', 'method', 'of', 'moments', 'based', 'on', 'the', 'estimated', 'parameters', 'the', 'model', 'produces', 'return', 'time', 'series', 'that', 'emulate', 'the', 'moments', 'of', 'the', 'real', 'data', 'these', 'results', 'are', 'robust', 'across', 'different', 'sample', 'periods', 'and', 'estimation', 'methods']] | [-0.09391943705365217, 0.04678643503090522, -0.11316346173104345, 0.09455147446715273, -0.10811035688918007, -0.16522948491910938, 0.12240863073141857, 0.4241658189566806, -0.29659137772008154, -0.31243024056311697, 0.12370986654544443, -0.25737223555097444, -0.1580575856866441, 0.1587038625657442, -0.0971433477679966, 0.029258586446909856, 0.02507726560725132, -0.0033133169296585643, 0.013242516344083318, -0.2687456603598548, 0.27288845047676585, 0.003824936959669382, 0.3080610300918731, -0.03641539113596082, 0.12820565884006405, 0.007823939100489952, -0.048916265834122896, 0.006884404422180523, -0.16619464821307398, 0.1536067605484277, 0.2951929223757664, 0.0984030229592463, 0.33962755850128207, -0.4681553444918336, -0.16917653397346535, 0.11770716933339524, 0.012236526767082978, 0.08205221681540327, 0.03120130637519954, -0.28665395082983497, 0.02842206190204403, -0.18428845527281132, -0.06813367397990078, -0.1266505318635609, -0.017714512165791046, 0.053919860326762624, -0.3500420936112884, 0.06446322448512849, -0.003952862277704601, 0.05890415026806295, -0.11041962396120653, -0.11081322280612464, 0.003919043039786629, 0.18904026588522052, 0.09399489016504958, -0.085091033555121, 0.18196737415564712, -0.13018170875269183, -0.16225938117228603, 0.3389426011708565, -0.052998254581325455, -0.1873469248530455, 0.15086247626701757, -0.1153780840941181, -0.0947653647356977, 0.11105843864303704, 0.26945691714354325, 0.08321866549279851, -0.20831345988942, -0.0007327228922804352, -0.0376527066740285, 0.23358858294280557, 0.029013422865925047, 0.008749570906123457, 0.1791166131636904, 0.17063246729473272, 0.09076061404387777, 0.0990246487854165, -0.057306992852924545, -0.19239835145223574, -0.22483176994986329, -0.08510567871538417, -0.1605190544457097, 0.007319688864906008, -0.18356520890150327, -0.14659575865759203, 0.3895606342193787, 0.2138809777146283, 0.1658878962674256, 0.08793657561515526, 0.3242370166250718, 0.0934883181907935, 0.03309188789959686, 0.11321250792146505, 0.1541234431497287, 0.036724053614307195, 0.12769521805618447, -0.21056205938414982, 0.19599925322108902, -0.019325896639202256] |
1,802.03736 | On a Riemannian manifold with a circulant structure whose third power is
the identity | It is studied a 3-dimensional Riemannian manifold equipped with a tensor
structure of type (1,1), whose third power is the identity. This structure has
a circulant matrix with respect to some basis, i.e. the structure is circulant.
On such a manifold a fundamental tensor by the metric and by the covariant
derivative of the circulant structure is defined. An important characteristic
identity for this tensor is obtained. It is established that the image of the
fundamental tensor with respect to the usual conformal transformation satisfies
the same identity. A Lie group as a manifold of the considered type is
constructed and some of its geometrical characteristics are found.
| math.DG | it is studied a 3dimensional riemannian manifold equipped with a tensor structure of type 11 whose third power is the identity this structure has a circulant matrix with respect to some basis ie the structure is circulant on such a manifold a fundamental tensor by the metric and by the covariant derivative of the circulant structure is defined an important characteristic identity for this tensor is obtained it is established that the image of the fundamental tensor with respect to the usual conformal transformation satisfies the same identity a lie group as a manifold of the considered type is constructed and some of its geometrical characteristics are found | [['it', 'is', 'studied', 'a', '3dimensional', 'riemannian', 'manifold', 'equipped', 'with', 'a', 'tensor', 'structure', 'of', 'type', '11', 'whose', 'third', 'power', 'is', 'the', 'identity', 'this', 'structure', 'has', 'a', 'circulant', 'matrix', 'with', 'respect', 'to', 'some', 'basis', 'ie', 'the', 'structure', 'is', 'circulant', 'on', 'such', 'a', 'manifold', 'a', 'fundamental', 'tensor', 'by', 'the', 'metric', 'and', 'by', 'the', 'covariant', 'derivative', 'of', 'the', 'circulant', 'structure', 'is', 'defined', 'an', 'important', 'characteristic', 'identity', 'for', 'this', 'tensor', 'is', 'obtained', 'it', 'is', 'established', 'that', 'the', 'image', 'of', 'the', 'fundamental', 'tensor', 'with', 'respect', 'to', 'the', 'usual', 'conformal', 'transformation', 'satisfies', 'the', 'same', 'identity', 'a', 'lie', 'group', 'as', 'a', 'manifold', 'of', 'the', 'considered', 'type', 'is', 'constructed', 'and', 'some', 'of', 'its', 'geometrical', 'characteristics', 'are', 'found']] | [-0.17495313795559383, 0.07131218437131827, -0.06772931958699634, 0.04519572089258064, -0.13893584720790386, -0.13265233693851364, -0.09004002622721062, 0.36004566872725263, -0.3141359945724684, -0.2206871153806181, 0.16206863600139818, -0.24953381037684502, -0.20977662081174828, 0.11886960556471927, -0.043451326850724094, 0.01360591403930879, 0.02883646979117421, 0.18034896308435472, -0.14019841609169142, -0.19481010528505538, 0.4296510933932883, 0.07012711617992157, 0.2680330301087384, 0.003855954217552035, 0.16451818818502403, -0.029336588325181597, -0.023367051358541682, 0.04481496111731286, -0.05596149907938121, 0.1544396061627022, 0.2034458056161249, 0.12263162612820182, 0.20564769800424715, -0.3537291777923841, -0.19762223898605616, 0.09278573648986856, 0.06202375861660888, 0.012503642001387628, -0.03257599788937821, -0.27490781843920964, 0.1444961368235656, -0.14947974933656277, -0.16207173111615703, -0.07399973753382694, 0.025350083648744557, -0.03669175809611463, -0.25266752838096757, 0.025732285228952132, 0.08550204835073263, 0.030250334333956103, -0.0605248898964082, -0.10663404648571655, -0.026306843669671152, 0.11444572466684298, 0.01607159421891319, 0.07626947745059927, 0.07960125100712671, -0.07839394032661975, -0.08408679755370098, 0.42569595022575446, -0.053871243010723484, -0.2835897591171993, 0.10659651811821041, -0.10850609571638482, -0.14098431713689394, 0.0806573584395496, 0.06799321648388824, 0.12071514664286817, -0.12366042906392573, 0.1710206711033135, -0.0737919232385509, 0.11644816528833299, 0.040051155865916774, -0.0015855795074323261, 0.11270788649131579, 0.12292364123277366, 0.09885737878977563, 0.14208466831284264, -0.0045743147148405786, -0.06611159086848299, -0.31879803965178627, -0.20092806689596424, -0.22322235381472166, 0.1396378906340235, -0.15403886670133538, -0.20434390174880349, 0.434869786284657, -0.00813467053255105, 0.19941668647246574, 0.04295250796712935, 0.2499387706802399, 0.11906669210724498, 0.13409275396002662, 0.05457606394688978, 0.19805586840407663, 0.26809894692376945, 0.043728948823021106, -0.164392834243093, 0.0344448197003523, 0.127748868061678] |
1,802.03737 | Probing shear-induced rearrangements in Fourier Space. I. Dynamic Light
Scattering | Understanding the microscopic origin of the rheological behavior of soft
matter is a long-lasting endeavour. While early efforts concentrated mainly on
the relationship between rheology and structure, current research focuses on
the role of microscopic dynamics. We present in two companion papers a thorough
discussion of how Fourier space-based methods may be coupled to rheology to
shed light on the relationship between the microscopic dynamics and the
mechanical response of soft systems. In this first companion paper, we report a
theoretical, numerical and experimental investigation of dynamic light
scattering coupled to rheology. While in ideal solids and simple viscous fluids
the displacement field under a shear deformation is purely affine, additional
non-affine displacements arise in many situations of great interest, for
example in elastically heterogeneous materials or due to plastic
rearrangements. We show how affine and non-affine displacements can be
separately resolved by dynamic light scattering, and discuss in detail the
effect of several non-idealities in typical experiments.
| cond-mat.soft | understanding the microscopic origin of the rheological behavior of soft matter is a longlasting endeavour while early efforts concentrated mainly on the relationship between rheology and structure current research focuses on the role of microscopic dynamics we present in two companion papers a thorough discussion of how fourier spacebased methods may be coupled to rheology to shed light on the relationship between the microscopic dynamics and the mechanical response of soft systems in this first companion paper we report a theoretical numerical and experimental investigation of dynamic light scattering coupled to rheology while in ideal solids and simple viscous fluids the displacement field under a shear deformation is purely affine additional nonaffine displacements arise in many situations of great interest for example in elastically heterogeneous materials or due to plastic rearrangements we show how affine and nonaffine displacements can be separately resolved by dynamic light scattering and discuss in detail the effect of several nonidealities in typical experiments | [['understanding', 'the', 'microscopic', 'origin', 'of', 'the', 'rheological', 'behavior', 'of', 'soft', 'matter', 'is', 'a', 'longlasting', 'endeavour', 'while', 'early', 'efforts', 'concentrated', 'mainly', 'on', 'the', 'relationship', 'between', 'rheology', 'and', 'structure', 'current', 'research', 'focuses', 'on', 'the', 'role', 'of', 'microscopic', 'dynamics', 'we', 'present', 'in', 'two', 'companion', 'papers', 'a', 'thorough', 'discussion', 'of', 'how', 'fourier', 'spacebased', 'methods', 'may', 'be', 'coupled', 'to', 'rheology', 'to', 'shed', 'light', 'on', 'the', 'relationship', 'between', 'the', 'microscopic', 'dynamics', 'and', 'the', 'mechanical', 'response', 'of', 'soft', 'systems', 'in', 'this', 'first', 'companion', 'paper', 'we', 'report', 'a', 'theoretical', 'numerical', 'and', 'experimental', 'investigation', 'of', 'dynamic', 'light', 'scattering', 'coupled', 'to', 'rheology', 'while', 'in', 'ideal', 'solids', 'and', 'simple', 'viscous', 'fluids', 'the', 'displacement', 'field', 'under', 'a', 'shear', 'deformation', 'is', 'purely', 'affine', 'additional', 'nonaffine', 'displacements', 'arise', 'in', 'many', 'situations', 'of', 'great', 'interest', 'for', 'example', 'in', 'elastically', 'heterogeneous', 'materials', 'or', 'due', 'to', 'plastic', 'rearrangements', 'we', 'show', 'how', 'affine', 'and', 'nonaffine', 'displacements', 'can', 'be', 'separately', 'resolved', 'by', 'dynamic', 'light', 'scattering', 'and', 'discuss', 'in', 'detail', 'the', 'effect', 'of', 'several', 'nonidealities', 'in', 'typical', 'experiments']] | [-0.14475115803600866, 0.17140723272415373, -0.13019615496638454, 0.015761697025309447, -0.1014711134359712, -0.0985445995414276, -0.00855931598041796, 0.38401929994078376, -0.30526542986589894, -0.2672357584196555, 0.07972703701993332, -0.2786896065897249, -0.23877745827724803, 0.18355552302533465, -0.06073453226657231, 0.06212612497915007, 0.03613374395593647, -0.05029974935305175, -0.044198333675150844, -0.19552529993897327, 0.27385284402407706, 0.04897748346770583, 0.28459987708049106, 0.08077187243888827, 0.0465233942753152, 0.031547896118976085, -0.049160869739053745, 0.0447047867729694, -0.14895195058912417, 0.11136378509381527, 0.25323390591111555, 0.01720586221346844, 0.24619026114881226, -0.5133925901513688, -0.2458583026346338, 0.07267849716723343, 0.12509775619152225, 0.08423316107968552, -0.05930810974825386, -0.2398258128050196, -0.023406612466507933, -0.11974106531861368, -0.1302272270675277, -0.09917636988596118, 0.050657749671895715, 0.03408125383982765, -0.1815417744974529, 0.13034830053625746, 0.061955801763165085, 0.09899611236480406, -0.10042417920312455, -0.05331195314426588, 0.028059733863566305, 0.07979896992792765, 0.08647620672937718, -0.034816003926216234, 0.1964770282377029, -0.18380994658145017, -0.07822023586464362, 0.42549862943683997, -0.015463474253781988, -0.1771683530540123, 0.23517892005134233, -0.16194090038785547, -0.12794548799460637, 0.14686297635323828, 0.23658307013396598, 0.08085101464014689, -0.1784961463804681, 0.030702643527478403, -0.0017560552569884289, 0.16013615156075905, 0.014005599720285663, 0.028792926522201705, 0.2686081350297679, 0.24573419913885336, -0.0278301779037088, 0.150494673895013, -0.07342115018225372, -0.10707569157091688, -0.30838090144805136, -0.12440535746503008, -0.14335997575375287, 0.05808827258894055, -0.056317169397009856, -0.13300850321951357, 0.37229109591144266, 0.13799747647024999, 0.16677182190093695, -0.02071161291567915, 0.2824077293323942, 0.007748012327076278, -0.006346122302775142, -0.0040668938250009775, 0.3281472245425788, 0.161171859996747, 0.10758110752942253, -0.2724788235382566, 0.06335816625210963, 0.020616439318496594] |
1,802.03738 | Efficient Machine Learning Representations of Surface Code with
Boundaries, Defects, Domain Walls and Twists | Machine learning representations of many-body quantum states have recently
been introduced as an ansatz to describe the ground states and unitary
evolutions of many-body quantum systems. We explore one of the most important
representations, restricted Boltzmann machine (RBM) representation, in
stabilizer formalism. We give the general method of constructing RBM
representation for stabilizer code states and find the exact RBM representation
for several types of stabilizer groups with the number of hidden neurons equal
or less than the number of visible neurons, which indicates that the
representation is extremely efficient. Then we analyze the surface code with
boundaries, defects, domain walls and twists in full detail and find that all
the models can be efficiently represented via RBM ansatz states. Besides, the
case for Kitaev's $D(\Zb_d)$ model, which is a generalized model of surface
code, is also investigated.
| quant-ph cond-mat.str-el | machine learning representations of manybody quantum states have recently been introduced as an ansatz to describe the ground states and unitary evolutions of manybody quantum systems we explore one of the most important representations restricted boltzmann machine rbm representation in stabilizer formalism we give the general method of constructing rbm representation for stabilizer code states and find the exact rbm representation for several types of stabilizer groups with the number of hidden neurons equal or less than the number of visible neurons which indicates that the representation is extremely efficient then we analyze the surface code with boundaries defects domain walls and twists in full detail and find that all the models can be efficiently represented via rbm ansatz states besides the case for kitaevs dzb_d model which is a generalized model of surface code is also investigated | [['machine', 'learning', 'representations', 'of', 'manybody', 'quantum', 'states', 'have', 'recently', 'been', 'introduced', 'as', 'an', 'ansatz', 'to', 'describe', 'the', 'ground', 'states', 'and', 'unitary', 'evolutions', 'of', 'manybody', 'quantum', 'systems', 'we', 'explore', 'one', 'of', 'the', 'most', 'important', 'representations', 'restricted', 'boltzmann', 'machine', 'rbm', 'representation', 'in', 'stabilizer', 'formalism', 'we', 'give', 'the', 'general', 'method', 'of', 'constructing', 'rbm', 'representation', 'for', 'stabilizer', 'code', 'states', 'and', 'find', 'the', 'exact', 'rbm', 'representation', 'for', 'several', 'types', 'of', 'stabilizer', 'groups', 'with', 'the', 'number', 'of', 'hidden', 'neurons', 'equal', 'or', 'less', 'than', 'the', 'number', 'of', 'visible', 'neurons', 'which', 'indicates', 'that', 'the', 'representation', 'is', 'extremely', 'efficient', 'then', 'we', 'analyze', 'the', 'surface', 'code', 'with', 'boundaries', 'defects', 'domain', 'walls', 'and', 'twists', 'in', 'full', 'detail', 'and', 'find', 'that', 'all', 'the', 'models', 'can', 'be', 'efficiently', 'represented', 'via', 'rbm', 'ansatz', 'states', 'besides', 'the', 'case', 'for', 'kitaevs', 'dzb_d', 'model', 'which', 'is', 'a', 'generalized', 'model', 'of', 'surface', 'code', 'is', 'also', 'investigated']] | [-0.07568337908354554, 0.15456628363443978, -0.09866175876019427, 0.0974852533417883, -0.04520081614150944, -0.20328842701023295, 0.024036818955528692, 0.36541854625527004, -0.28781661573189044, -0.27448864999723477, 0.06451147644998112, -0.2472111819189613, -0.17397749254201286, 0.1768495484618946, -0.013186811928358608, 0.08250612432534814, 0.10852283761449104, 0.07534849839828854, -0.08013033075937934, -0.2500575386144112, 0.31991688848004074, 0.01170343360574712, 0.30257284185121747, -0.017683081719752428, 0.07980087425994829, 0.004376262511351031, 0.041787128773157614, -0.03895342829263341, -0.08249814101432393, 0.17106658979709918, 0.2672550777311619, 0.10580656793729885, 0.22327586846004654, -0.4442321655279311, -0.2632480388282914, 0.10685204545437038, 0.16453260415485196, 0.2096166734559883, 0.005635489321340991, -0.2878289393533402, 0.09737231529718876, -0.21096468973823274, -0.0920089443424975, -0.16607415089451702, 0.026778596432974738, -0.057993081894560455, -0.20987131893226918, 0.029120588346926605, 0.06659184350040707, 0.0796186047653756, -0.08528301980258067, -0.11096967081539333, -0.031091162700369192, 0.10665638007080849, -0.030040297820402757, 0.008250180424537755, 0.08708371282181274, -0.1709399116939328, -0.14556972842058508, 0.36295169406318967, -0.02591937775844725, -0.24578540596132079, 0.19552041096000994, -0.07030961984754915, -0.12368618118420352, 0.06285806179019439, 0.16452833513192233, 0.12029494958705385, -0.12206336072761648, 0.11554922549441511, -0.05381433946338829, 0.16037334849034865, 0.036893457322157104, 0.04918734031775286, 0.16716783201146912, 0.1281601056714889, 0.009481951548466391, 0.19588369860426, -0.07875439404326416, -0.10902419253286437, -0.27904278451889536, -0.1732963476231312, -0.22350167805570292, 0.023147375465635837, -0.05341364434762198, -0.19807289512726023, 0.4471958659752442, 0.1310460597419445, 0.16409232802893015, 0.06790238476093233, 0.21583115694412186, 0.11388107316813222, 0.09726658504265938, 0.15326991913089, 0.15749705538372882, 0.17511007218302166, -0.036305490527709906, -0.2123765293576748, 0.03084297006759439, 0.10266232327388151] |
1,802.03739 | Dark matter: an efficient catalyst for intermediate-mass-ratio-inspiral
events | Gravitational waves (GWs) can be produced if a stellar compact object, such
as a black hole (BH) or neutron star, inspirals into an intermediate-massive
black hole (IMBH) of $(10^3 \sim 10^5)\,M_\odot$. Such a system may be produced
in the center of a globular cluster (GC) or a nuclear star cluster (NSC), and
is known as an intermediate- or extreme-mass-ratio inspiral (IMRI or EMRI).
Motivated by the recent suggestions that dark matter minispikes could form
around IMBHs, we study the effect of dynamical friction against DM on the
merger rate of IMRIs/EMRIs. We find that the merger timescale of IMBHs with BHs
and NSs would be shortened by two to three orders of magnitude. As a result,
the event rate of IMRIs/EMRIs are enhanced by orders of magnitude relative to
that in the case of no DM minispikes. In the most extreme case where IMBHs are
small and the DM minispikes have a steep density profile, all the BH in GCs and
NSCs might be exhausted so that the mergers with NSs would dominate the current
IMRIs/EMRIs. Our results suggest that the mass function of the IMBHs below
$10^4 \,M_\odot$ would bear imprints of the distribution of DM minispikes
because these low-mass IMBHs can grow efficiently in the presence of DM
minispikes by merging with BHs and NSs. Future space-based GW detectors, like
LISA, Taiji, and Tianqin, can measure the IMRI/EMRI rate and hence constrain
the distribution of DM around IMBHs.
| gr-qc astro-ph.HE | gravitational waves gws can be produced if a stellar compact object such as a black hole bh or neutron star inspirals into an intermediatemassive black hole imbh of 103 sim 105m_odot such a system may be produced in the center of a globular cluster gc or a nuclear star cluster nsc and is known as an intermediate or extrememassratio inspiral imri or emri motivated by the recent suggestions that dark matter minispikes could form around imbhs we study the effect of dynamical friction against dm on the merger rate of imrisemris we find that the merger timescale of imbhs with bhs and nss would be shortened by two to three orders of magnitude as a result the event rate of imrisemris are enhanced by orders of magnitude relative to that in the case of no dm minispikes in the most extreme case where imbhs are small and the dm minispikes have a steep density profile all the bh in gcs and nscs might be exhausted so that the mergers with nss would dominate the current imrisemris our results suggest that the mass function of the imbhs below 104 m_odot would bear imprints of the distribution of dm minispikes because these lowmass imbhs can grow efficiently in the presence of dm minispikes by merging with bhs and nss future spacebased gw detectors like lisa taiji and tianqin can measure the imriemri rate and hence constrain the distribution of dm around imbhs | [['gravitational', 'waves', 'gws', 'can', 'be', 'produced', 'if', 'a', 'stellar', 'compact', 'object', 'such', 'as', 'a', 'black', 'hole', 'bh', 'or', 'neutron', 'star', 'inspirals', 'into', 'an', 'intermediatemassive', 'black', 'hole', 'imbh', 'of', '103', 'sim', '105m_odot', 'such', 'a', 'system', 'may', 'be', 'produced', 'in', 'the', 'center', 'of', 'a', 'globular', 'cluster', 'gc', 'or', 'a', 'nuclear', 'star', 'cluster', 'nsc', 'and', 'is', 'known', 'as', 'an', 'intermediate', 'or', 'extrememassratio', 'inspiral', 'imri', 'or', 'emri', 'motivated', 'by', 'the', 'recent', 'suggestions', 'that', 'dark', 'matter', 'minispikes', 'could', 'form', 'around', 'imbhs', 'we', 'study', 'the', 'effect', 'of', 'dynamical', 'friction', 'against', 'dm', 'on', 'the', 'merger', 'rate', 'of', 'imrisemris', 'we', 'find', 'that', 'the', 'merger', 'timescale', 'of', 'imbhs', 'with', 'bhs', 'and', 'nss', 'would', 'be', 'shortened', 'by', 'two', 'to', 'three', 'orders', 'of', 'magnitude', 'as', 'a', 'result', 'the', 'event', 'rate', 'of', 'imrisemris', 'are', 'enhanced', 'by', 'orders', 'of', 'magnitude', 'relative', 'to', 'that', 'in', 'the', 'case', 'of', 'no', 'dm', 'minispikes', 'in', 'the', 'most', 'extreme', 'case', 'where', 'imbhs', 'are', 'small', 'and', 'the', 'dm', 'minispikes', 'have', 'a', 'steep', 'density', 'profile', 'all', 'the', 'bh', 'in', 'gcs', 'and', 'nscs', 'might', 'be', 'exhausted', 'so', 'that', 'the', 'mergers', 'with', 'nss', 'would', 'dominate', 'the', 'current', 'imrisemris', 'our', 'results', 'suggest', 'that', 'the', 'mass', 'function', 'of', 'the', 'imbhs', 'below', '104', 'm_odot', 'would', 'bear', 'imprints', 'of', 'the', 'distribution', 'of', 'dm', 'minispikes', 'because', 'these', 'lowmass', 'imbhs', 'can', 'grow', 'efficiently', 'in', 'the', 'presence', 'of', 'dm', 'minispikes', 'by', 'merging', 'with', 'bhs', 'and', 'nss', 'future', 'spacebased', 'gw', 'detectors', 'like', 'lisa', 'taiji', 'and', 'tianqin', 'can', 'measure', 'the', 'imriemri', 'rate', 'and', 'hence', 'constrain', 'the', 'distribution', 'of', 'dm', 'around', 'imbhs']] | [-0.13543695295969937, 0.18328857092514622, -0.07464612423438408, 0.1679451567146179, -0.1011018222003053, -0.021533248568573287, 0.017375003425677202, 0.32314618068813467, -0.13395696453054565, -0.3524086746956109, 0.08032931387765434, -0.3106152966860136, -0.024310838520745105, 0.2637634038180892, -0.002726003988918743, -0.01937511222481837, 0.08612793925214388, -0.001101895103963661, -0.07919665916324067, -0.28016014265288136, 0.3325787071025615, 0.07608731416108624, 0.07534652694701276, -0.034734566002367184, 0.05122857913569738, -0.05997319012260743, -0.0009993994939744971, -0.033624491166268866, -0.12309480463725123, 0.0016987799242076515, 0.2571604922063119, 0.18291508472450546, 0.2111027331771446, -0.417108060846643, -0.21801042028753453, 0.12775355437039845, 0.22788392337892502, 0.09232027284646598, -0.14372393513287351, -0.3132229871233481, 0.14698686621872276, -0.3233700172671713, -0.13106056033179678, 0.04989729124164232, 0.05743179553289212, 0.04935172676677703, -0.22161446989486658, 0.16830173710743004, 0.07103501942116991, -0.13408002363046373, -0.1008216401641978, -0.07214530320447445, -0.05101385573217466, 0.013399431760574858, 0.10670561504269713, 0.07377605860425494, 0.26090960069579, -0.14085774567508175, -0.07950592455824362, 0.37813024658994226, -0.06922176516094639, -0.04248391815839203, 0.22868897489692908, -0.2376849700688973, -0.14577205427318313, 0.0806118260920983, 0.1829480987123046, 0.15741956476258526, -0.1282922634971815, 0.006411539891658733, 0.0391800791287218, 0.231631243776795, 0.10272598968600566, 0.06315861337976024, 0.4662049327154788, 0.12939510169092208, 0.05211736685128797, 0.039467916750372485, -0.15703590630327652, -0.005791854590691907, -0.18867861798469554, -0.10702910454978846, -0.13604792184878342, 0.11463896112972442, -0.16498901662432586, -0.10414539043748727, 0.26502565838197817, 0.10014023106968006, 0.2147939095023248, 0.008251710845523797, 0.26136412627013034, 0.09439302200430061, 0.07657204675455295, 0.09863819842612581, 0.35642676635267345, 0.12836496262016187, 0.007236368374540529, -0.2292380682777255, 0.06422519841315186, -0.021684731089385328] |
1,802.0374 | Metamaterial analogue of Ising model | The interaction between microscopic particles has always been a fascinating
and intriguing area of science. Direct interrogation of such interactions is
often difficult or impossible. Structured electromagnetic systems offer a rich
toolkit for mimicking and reproducing the key dynamics that governs the
microscopic interactions, and thus provide an avenue to explore and interpret
the microscopic phenomena. In particular, metamaterials offer the freedom to
artificially tailor light-matter coupling and to control the interaction
between unit cells in the metamaterial array. Here we demonstrate a terahertz
metamaterial that mimics spin-related interactions of microscopic particles in
a 2D lattice via complex electromagnetic multipole interactions within the
metamaterial array. Fano resonances featured by distinct mode properties due to
strong nearest-neighbor interactions are discussed that draw parallels with the
2D Ising model. Interestingly, a hyperfine Fano splitting spectrum is observed
by manipulating the 2D interactions without applying external magnetic or
electric fields, which provides a passive multispectral platform for
applications in super-resolution imaging, biosensing, and selective thermal
emission. The dynamic approach to reproduce the static interaction between
microscopic particles would enable more profound significance in exploring the
unknown physical world by the macroscopic analogues.
| physics.optics | the interaction between microscopic particles has always been a fascinating and intriguing area of science direct interrogation of such interactions is often difficult or impossible structured electromagnetic systems offer a rich toolkit for mimicking and reproducing the key dynamics that governs the microscopic interactions and thus provide an avenue to explore and interpret the microscopic phenomena in particular metamaterials offer the freedom to artificially tailor lightmatter coupling and to control the interaction between unit cells in the metamaterial array here we demonstrate a terahertz metamaterial that mimics spinrelated interactions of microscopic particles in a 2d lattice via complex electromagnetic multipole interactions within the metamaterial array fano resonances featured by distinct mode properties due to strong nearestneighbor interactions are discussed that draw parallels with the 2d ising model interestingly a hyperfine fano splitting spectrum is observed by manipulating the 2d interactions without applying external magnetic or electric fields which provides a passive multispectral platform for applications in superresolution imaging biosensing and selective thermal emission the dynamic approach to reproduce the static interaction between microscopic particles would enable more profound significance in exploring the unknown physical world by the macroscopic analogues | [['the', 'interaction', 'between', 'microscopic', 'particles', 'has', 'always', 'been', 'a', 'fascinating', 'and', 'intriguing', 'area', 'of', 'science', 'direct', 'interrogation', 'of', 'such', 'interactions', 'is', 'often', 'difficult', 'or', 'impossible', 'structured', 'electromagnetic', 'systems', 'offer', 'a', 'rich', 'toolkit', 'for', 'mimicking', 'and', 'reproducing', 'the', 'key', 'dynamics', 'that', 'governs', 'the', 'microscopic', 'interactions', 'and', 'thus', 'provide', 'an', 'avenue', 'to', 'explore', 'and', 'interpret', 'the', 'microscopic', 'phenomena', 'in', 'particular', 'metamaterials', 'offer', 'the', 'freedom', 'to', 'artificially', 'tailor', 'lightmatter', 'coupling', 'and', 'to', 'control', 'the', 'interaction', 'between', 'unit', 'cells', 'in', 'the', 'metamaterial', 'array', 'here', 'we', 'demonstrate', 'a', 'terahertz', 'metamaterial', 'that', 'mimics', 'spinrelated', 'interactions', 'of', 'microscopic', 'particles', 'in', 'a', '2d', 'lattice', 'via', 'complex', 'electromagnetic', 'multipole', 'interactions', 'within', 'the', 'metamaterial', 'array', 'fano', 'resonances', 'featured', 'by', 'distinct', 'mode', 'properties', 'due', 'to', 'strong', 'nearestneighbor', 'interactions', 'are', 'discussed', 'that', 'draw', 'parallels', 'with', 'the', '2d', 'ising', 'model', 'interestingly', 'a', 'hyperfine', 'fano', 'splitting', 'spectrum', 'is', 'observed', 'by', 'manipulating', 'the', '2d', 'interactions', 'without', 'applying', 'external', 'magnetic', 'or', 'electric', 'fields', 'which', 'provides', 'a', 'passive', 'multispectral', 'platform', 'for', 'applications', 'in', 'superresolution', 'imaging', 'biosensing', 'and', 'selective', 'thermal', 'emission', 'the', 'dynamic', 'approach', 'to', 'reproduce', 'the', 'static', 'interaction', 'between', 'microscopic', 'particles', 'would', 'enable', 'more', 'profound', 'significance', 'in', 'exploring', 'the', 'unknown', 'physical', 'world', 'by', 'the', 'macroscopic', 'analogues']] | [-0.1595219690907037, 0.18003580928233479, -0.045317266818269024, 0.06681165168746793, -0.11511837176131036, -0.18827342374555806, -0.0025604722637032704, 0.40615446115572934, -0.24189515371939965, -0.3322610822974374, -0.02077327438607989, -0.27026841830506565, -0.21768810468709382, 0.18869035030350523, 0.06041856394420383, 0.020647181173362745, -0.007484682290827136, -0.05773398802334211, 0.005561473266906524, -0.10526228758488614, 0.27303222517566705, 0.055510909231281075, 0.31042489198297657, 0.09857111216754352, 0.10246887800613881, 0.037756860394168784, 0.05404001650112193, 0.014199107865650188, -0.09321323722023019, 0.12578379375879806, 0.24540218665164762, 0.010842694212293263, 0.2374117130902719, -0.4785100784763773, -0.2634373896297316, 0.058921605728014755, 0.17659639417737102, 0.15221654721868358, -0.11366585535023463, -0.31194192318433017, -0.019725537543534916, -0.11127648127718617, -0.1553294876240509, -0.13978133128004927, 0.010448506182039935, 0.015402758909172561, -0.252096176629137, 0.03619978793714412, 0.038046750735254986, 0.07627837338223659, -0.06403978105644306, -0.04396220390307939, 0.024180316868873817, 0.13685023118175133, -0.01819606373337881, -0.020884428609399094, 0.15465852778042155, -0.17238207833062877, -0.14470538349881296, 0.42755427996987705, -0.02676268078007356, -0.15989801468741563, 0.23686536269449682, -0.14168398984259478, -0.056029641500639694, 0.16760635278655817, 0.197331997594259, 0.051399990632913256, -0.18431042983176965, 0.07857164082045928, 0.007447180656036214, 0.18012599655791683, 0.03767426538009507, 0.10842979374334276, 0.29876889531357737, 0.21245885911217777, 0.002558327794922565, 0.13851619026624898, -0.04725587179529525, -0.09505979634609527, -0.20631069598335122, -0.13905019420519393, -0.20293754523065036, 0.08181028958242485, -0.08628231287233547, -0.16928503152830576, 0.39297558217575507, 0.18264304022317032, 0.16191135976640952, -0.054459612379860745, 0.2974649167979363, 0.023387933796069647, 0.09854280727880972, -0.017571855794697527, 0.31997665239586714, 0.17421963174147384, 0.0964941904564738, -0.2499098139617927, 0.021736126104813246, -0.018794006521434144] |
1,802.03741 | Power-law/exponential transport of electromagnetic field in
one-dimensional metallic nanoparticle arrays | Based on the coupled-dipole analysis and finite-difference time-domain
simulation, we have investigated the surface plasmon propagation in
one-dimensional metallic nanoparticle (NP) chains. Our systematic studies
reveal that the interplay between the localized plasmon excitation and the
lattice collective behavior leads to two phases (I and II) of different
electromagnetic (EM) field transport properties. In phase I, the EM field
decays follow the power-law. In phase II, the EM field shows the exponential
decay in the short distance regime and the power-law decay in the long distance
regime. Moreover, universal power-law exponents have been found in the long
propagation distance. The two different EM field propagation behaviors can be
transformed to each other by tuning the parameters of the excitation fields
and/or those of the NP chains. The EM field transport mechanisms we have found
are very useful in the design of plasmonic waveguide with both strong field
confinement and efficient field/energy transfer, which has important
applications in integrated nanophotonic circuits.
| cond-mat.mes-hall | based on the coupleddipole analysis and finitedifference timedomain simulation we have investigated the surface plasmon propagation in onedimensional metallic nanoparticle np chains our systematic studies reveal that the interplay between the localized plasmon excitation and the lattice collective behavior leads to two phases i and ii of different electromagnetic em field transport properties in phase i the em field decays follow the powerlaw in phase ii the em field shows the exponential decay in the short distance regime and the powerlaw decay in the long distance regime moreover universal powerlaw exponents have been found in the long propagation distance the two different em field propagation behaviors can be transformed to each other by tuning the parameters of the excitation fields andor those of the np chains the em field transport mechanisms we have found are very useful in the design of plasmonic waveguide with both strong field confinement and efficient fieldenergy transfer which has important applications in integrated nanophotonic circuits | [['based', 'on', 'the', 'coupleddipole', 'analysis', 'and', 'finitedifference', 'timedomain', 'simulation', 'we', 'have', 'investigated', 'the', 'surface', 'plasmon', 'propagation', 'in', 'onedimensional', 'metallic', 'nanoparticle', 'np', 'chains', 'our', 'systematic', 'studies', 'reveal', 'that', 'the', 'interplay', 'between', 'the', 'localized', 'plasmon', 'excitation', 'and', 'the', 'lattice', 'collective', 'behavior', 'leads', 'to', 'two', 'phases', 'i', 'and', 'ii', 'of', 'different', 'electromagnetic', 'em', 'field', 'transport', 'properties', 'in', 'phase', 'i', 'the', 'em', 'field', 'decays', 'follow', 'the', 'powerlaw', 'in', 'phase', 'ii', 'the', 'em', 'field', 'shows', 'the', 'exponential', 'decay', 'in', 'the', 'short', 'distance', 'regime', 'and', 'the', 'powerlaw', 'decay', 'in', 'the', 'long', 'distance', 'regime', 'moreover', 'universal', 'powerlaw', 'exponents', 'have', 'been', 'found', 'in', 'the', 'long', 'propagation', 'distance', 'the', 'two', 'different', 'em', 'field', 'propagation', 'behaviors', 'can', 'be', 'transformed', 'to', 'each', 'other', 'by', 'tuning', 'the', 'parameters', 'of', 'the', 'excitation', 'fields', 'andor', 'those', 'of', 'the', 'np', 'chains', 'the', 'em', 'field', 'transport', 'mechanisms', 'we', 'have', 'found', 'are', 'very', 'useful', 'in', 'the', 'design', 'of', 'plasmonic', 'waveguide', 'with', 'both', 'strong', 'field', 'confinement', 'and', 'efficient', 'fieldenergy', 'transfer', 'which', 'has', 'important', 'applications', 'in', 'integrated', 'nanophotonic', 'circuits']] | [-0.1748692356646643, 0.18431971644749864, -0.10144496226566843, 0.06595568097327487, -0.04998768900404684, -0.16869389253552072, -0.00920670870837057, 0.44523565972704093, -0.2680101624864619, -0.2800997789774556, 0.017403858384932393, -0.26252924350555984, -0.14577730223536492, 0.17791865551262162, 0.08577372416330035, 0.06150561513627508, 0.005827866631443612, -0.036785145425528756, -0.03303628869325621, -0.14531443045357265, 0.2662642898299964, 0.045679090569319666, 0.3379704883176601, 0.04336282153963111, 0.002012953435769305, 0.015182595953228883, 0.02410604482574854, 0.027700705770985223, -0.14759852919692093, 0.07023782928590663, 0.21098400198534364, 0.02282391058979556, 0.21530894781462848, -0.4686405376996845, -0.24464117249590345, 0.05712343028280884, 0.19553497536398937, 0.11303146143545746, -0.07850601611062302, -0.26789459234278185, 0.021519596825237387, -0.10473704665055265, -0.09724684761895333, -0.026100031269015743, 0.026870223437435926, 0.08002893344819313, -0.23238576324656607, 0.05407297868368914, 0.05143718214858382, 0.05202468767092796, -0.02907855366356671, -0.10408930078265258, 0.029333604518615174, 0.09875942143262365, 0.07066483884118498, 0.0048237851522571875, 0.133534991365741, -0.12637696861638686, -0.12059520647744648, 0.3303007505717687, -0.08406495745002758, -0.13808687031742012, 0.2100553263488109, -0.15783568164652023, -0.0379395889423904, 0.17923130748968105, 0.17369251872150926, 0.09178648838424124, -0.14988572056572594, 0.0962229906795983, 0.030175941664492712, 0.15923874073032493, 0.03688816034846241, 0.10976668827643152, 0.19922291487455368, 0.15008658111910336, -0.011158791924390243, 0.1306180012816185, -0.1106394000526052, -0.10015788616146892, -0.2732664050330641, -0.1351467612432316, -0.17828890874661737, 0.04750482310264488, -0.09688766917261091, -0.1926386227045441, 0.4334165202773875, 0.12234748902628781, 0.1617073725356022, 0.006065645633498207, 0.22578231919906103, 0.14218986026317, 0.07067675179423531, 0.0847507969295748, 0.3351573442807421, 0.15728705438232282, 0.09703438175638439, -0.3002564335154602, 0.027071934238483662, -0.0016255430819001049] |
1,802.03742 | On a linearization trick | In several situations, mainly involving a self-adjoint set of unitary
generators of a $C^*$-algebra, we show that any matrix polynomial in the
generators and the unit that is in the open unit ball can be written as a
product of matrix polynomials of degree 1 also in the open unit ball.
| math.OA math.FA math.PR | in several situations mainly involving a selfadjoint set of unitary generators of a calgebra we show that any matrix polynomial in the generators and the unit that is in the open unit ball can be written as a product of matrix polynomials of degree 1 also in the open unit ball | [['in', 'several', 'situations', 'mainly', 'involving', 'a', 'selfadjoint', 'set', 'of', 'unitary', 'generators', 'of', 'a', 'calgebra', 'we', 'show', 'that', 'any', 'matrix', 'polynomial', 'in', 'the', 'generators', 'and', 'the', 'unit', 'that', 'is', 'in', 'the', 'open', 'unit', 'ball', 'can', 'be', 'written', 'as', 'a', 'product', 'of', 'matrix', 'polynomials', 'of', 'degree', '1', 'also', 'in', 'the', 'open', 'unit', 'ball']] | [-0.14635913081321061, 0.12835575755247297, -0.013521874560883232, 0.00028623399717331516, -0.013548131173878325, -0.09312536663321011, -0.0030865435506783278, 0.3754895786188689, -0.3432587042962219, -0.16772363976776308, 0.17655007133041234, -0.29201804488605143, -0.1324213442630043, 0.2001886621994131, -0.12179711818987247, 0.07296312804899964, 0.10363832485003799, 0.1314157682525761, -0.10561901152101985, -0.2694138888561842, 0.36495150249524444, -0.016323445072653247, 0.12033673107404919, 0.05633768877562355, 0.11738617776655684, -0.019072468264722357, 0.029887358201485054, -0.013593816910596454, -0.049302085642029495, 0.12122622178867459, 0.2661941780471334, 0.16112001937832318, 0.2623231188923705, -0.4319702035875297, -0.12605718722311304, 0.1688613954420183, 0.1448759715091072, -0.026313703178482896, -0.045024670550928396, -0.19656618846142115, 0.06033316544969292, -0.19409110868953433, -0.1439392346907042, -0.03529370869235957, 0.06189079241206249, 0.017855489046732877, -0.3203362240364738, 0.0075608867662274, 0.08716139701359413, 0.07766415680959529, -0.02690626618762811, -0.10784501045504037, 0.028366206236658434, 0.1117973693683013, -0.055466359321429744, 0.07819681671247178, 0.12913058973008804, -0.05209956564666594, -0.1361103367936962, 0.3954653077046661, -0.043077403058608375, -0.3214952477856594, 0.08925959330015615, -0.2544958035406821, -0.1649321451344911, 0.03888921485300742, 0.15534364923323488, 0.09406162287090339, -0.1239671066001642, 0.2116444685265842, -0.15848174457456551, 0.1333359237988571, 0.07882014915858414, 0.014676393260814104, 0.10936140318802905, 0.0570572873613998, 0.06912972949737427, 0.17515131830940864, 0.06497394563812836, -0.08074979524255968, -0.3729474113194966, -0.23175376193488345, -0.2399292815403611, 0.10707919451170693, -0.13393937813673926, -0.1943692597104054, 0.4350532340798892, 0.06748467205347967, 0.24363000018923892, 0.007242057563773557, 0.2028722497178059, 0.10954807133341948, 0.11442263148651988, 0.0900219285075425, 0.09416787508948177, 0.15196649752119007, -0.010052450476031677, -0.158269054247249, -0.018723879977330275, 0.13178437334649704] |
1,802.03743 | Morrey meets Muckenhoupt: A note on Nakai's generalized Morrey spaces
and applications | The goal of this paper is to extend Nakai's generalized Morrey spaces to a
wider function class, the one-sided Muckenhoupt weighted case. Morrey matching
Muckenhoupt enables us to study the weak and strong type boundedness of
one-sided sublinear operators satisfying certain size conditions on the
one-sided weighted Morrey spaces. We also establish one-sided Fefferman-Stein
inequalities on one-sided weighted Morrey spaces in this paper. Meanwhile, the
boundedness and compactness of Riemann-Liouville integral operators on locally
one-sided weighted Morrey space are considered. As applications, we establish
the existence and uniqueness of solutions to a Cauchy type problem associated
with fractional differential equations.
| math.FA | the goal of this paper is to extend nakais generalized morrey spaces to a wider function class the onesided muckenhoupt weighted case morrey matching muckenhoupt enables us to study the weak and strong type boundedness of onesided sublinear operators satisfying certain size conditions on the onesided weighted morrey spaces we also establish onesided feffermanstein inequalities on onesided weighted morrey spaces in this paper meanwhile the boundedness and compactness of riemannliouville integral operators on locally onesided weighted morrey space are considered as applications we establish the existence and uniqueness of solutions to a cauchy type problem associated with fractional differential equations | [['the', 'goal', 'of', 'this', 'paper', 'is', 'to', 'extend', 'nakais', 'generalized', 'morrey', 'spaces', 'to', 'a', 'wider', 'function', 'class', 'the', 'onesided', 'muckenhoupt', 'weighted', 'case', 'morrey', 'matching', 'muckenhoupt', 'enables', 'us', 'to', 'study', 'the', 'weak', 'and', 'strong', 'type', 'boundedness', 'of', 'onesided', 'sublinear', 'operators', 'satisfying', 'certain', 'size', 'conditions', 'on', 'the', 'onesided', 'weighted', 'morrey', 'spaces', 'we', 'also', 'establish', 'onesided', 'feffermanstein', 'inequalities', 'on', 'onesided', 'weighted', 'morrey', 'spaces', 'in', 'this', 'paper', 'meanwhile', 'the', 'boundedness', 'and', 'compactness', 'of', 'riemannliouville', 'integral', 'operators', 'on', 'locally', 'onesided', 'weighted', 'morrey', 'space', 'are', 'considered', 'as', 'applications', 'we', 'establish', 'the', 'existence', 'and', 'uniqueness', 'of', 'solutions', 'to', 'a', 'cauchy', 'type', 'problem', 'associated', 'with', 'fractional', 'differential', 'equations']] | [-0.1327273941691965, 0.026035736449994146, -0.02065999258309603, 0.20955015546060168, -0.18590838281670585, -0.1162102538975887, 0.01774146463954821, 0.3601051533035934, -0.38326422264799476, -0.12748811724595727, 0.19784365488332697, -0.25177582319825886, -0.07738767080940306, 0.18116925472393633, -0.20143432073295117, 0.08949046186637133, 0.025481834085658194, -0.01658686826005578, -0.16201581104658544, -0.2753137917886488, 0.48546412111027165, -0.05621380255790427, 0.22600184883456678, 0.05915036608465016, 0.04515334564028308, 0.020738019021227957, -0.04539385402575135, -0.027577787242189514, -0.26946529247565193, 0.19085322341299615, 0.22886799715459347, 0.021190500913653522, 0.3989163899421692, -0.333917807135731, -0.15008125649765133, 0.292722671283409, 0.08393677447340452, -0.12534137186594307, -0.02214047430898063, -0.38851201173849403, 0.09016348257195204, -0.11611558614298702, -0.19262776375748217, -0.08113427357748151, -0.027471599457785486, 0.1443824961851351, -0.385711079556495, 0.14163791645056334, 0.12671787115745248, -0.027530167589429767, -0.22867208511102943, -0.06390085592865943, 0.03899981441791169, 0.013172856690362096, -0.03436690484639257, 0.007055096168769524, 0.0083523969957605, -0.042880410314537584, -0.13972933708690108, 0.29931259382516145, -0.06126170662231743, -0.2945031888852827, 0.08891038465313614, -0.19598221057560294, -0.16001866415608673, -0.00918392856605351, 0.15232373349368572, 0.19409512400627135, -0.13339358654804528, 0.16797337417316158, -0.1043807159177959, 0.04071266392245889, 0.12162619665730745, 0.183488315558061, -0.030188851542770862, 0.06663713957183064, 0.29458034785464404, 0.1968933739210479, 0.007725611056084745, -0.10838392448204104, -0.4036576085165143, -0.18558314962079747, -0.12406456351978705, 0.08872879286296666, -0.1576634656493843, -0.24846070874482393, 0.3162567726802081, 0.05771325454115868, 0.10697885561734438, 0.2052860923949629, 0.1189190408680588, 0.1370730891439598, 0.02432740991935134, 0.028892007633112372, 0.1776646518986672, 0.2558766424492933, 0.191360443350859, -0.11994772553443908, 0.0550996158272028, 0.3216079026274383] |
1,802.03744 | Denotational semantics for guarded dependent type theory | We present a new model of Guarded Dependent Type Theory (GDTT), a type theory
with guarded recursion and multiple clocks in which one can program with, and
reason about coinductive types. Productivity of recursively defined coinductive
programs and proofs is encoded in types using guarded recursion, and can
therefore be checked modularly, unlike the syntactic checks implemented in
modern proof assistants.
The model is based on a category of covariant presheaves over a category of
time objects, and quantification over clocks is modelled using a presheaf of
clocks. To model the clock irrelevance axiom, crucial for programming with
coinductive types, types must be interpreted as presheaves orthogonal to the
object of clocks. In the case of dependent types, this translates to a lifting
condition similar to the one found in homotopy theoretic models of type theory,
but here with an additional requirement of uniqueness of lifts. Since the
universes defined by the standard Hofmann-Streicher construction in this model
do not satisfy this property, the universes in GDTT must be indexed by contexts
of clock variables. We show how to model these universes in such a way that
inclusions of clock contexts give rise to inclusions of universes commuting
with type operations on the nose.
| cs.LO | we present a new model of guarded dependent type theory gdtt a type theory with guarded recursion and multiple clocks in which one can program with and reason about coinductive types productivity of recursively defined coinductive programs and proofs is encoded in types using guarded recursion and can therefore be checked modularly unlike the syntactic checks implemented in modern proof assistants the model is based on a category of covariant presheaves over a category of time objects and quantification over clocks is modelled using a presheaf of clocks to model the clock irrelevance axiom crucial for programming with coinductive types types must be interpreted as presheaves orthogonal to the object of clocks in the case of dependent types this translates to a lifting condition similar to the one found in homotopy theoretic models of type theory but here with an additional requirement of uniqueness of lifts since the universes defined by the standard hofmannstreicher construction in this model do not satisfy this property the universes in gdtt must be indexed by contexts of clock variables we show how to model these universes in such a way that inclusions of clock contexts give rise to inclusions of universes commuting with type operations on the nose | [['we', 'present', 'a', 'new', 'model', 'of', 'guarded', 'dependent', 'type', 'theory', 'gdtt', 'a', 'type', 'theory', 'with', 'guarded', 'recursion', 'and', 'multiple', 'clocks', 'in', 'which', 'one', 'can', 'program', 'with', 'and', 'reason', 'about', 'coinductive', 'types', 'productivity', 'of', 'recursively', 'defined', 'coinductive', 'programs', 'and', 'proofs', 'is', 'encoded', 'in', 'types', 'using', 'guarded', 'recursion', 'and', 'can', 'therefore', 'be', 'checked', 'modularly', 'unlike', 'the', 'syntactic', 'checks', 'implemented', 'in', 'modern', 'proof', 'assistants', 'the', 'model', 'is', 'based', 'on', 'a', 'category', 'of', 'covariant', 'presheaves', 'over', 'a', 'category', 'of', 'time', 'objects', 'and', 'quantification', 'over', 'clocks', 'is', 'modelled', 'using', 'a', 'presheaf', 'of', 'clocks', 'to', 'model', 'the', 'clock', 'irrelevance', 'axiom', 'crucial', 'for', 'programming', 'with', 'coinductive', 'types', 'types', 'must', 'be', 'interpreted', 'as', 'presheaves', 'orthogonal', 'to', 'the', 'object', 'of', 'clocks', 'in', 'the', 'case', 'of', 'dependent', 'types', 'this', 'translates', 'to', 'a', 'lifting', 'condition', 'similar', 'to', 'the', 'one', 'found', 'in', 'homotopy', 'theoretic', 'models', 'of', 'type', 'theory', 'but', 'here', 'with', 'an', 'additional', 'requirement', 'of', 'uniqueness', 'of', 'lifts', 'since', 'the', 'universes', 'defined', 'by', 'the', 'standard', 'hofmannstreicher', 'construction', 'in', 'this', 'model', 'do', 'not', 'satisfy', 'this', 'property', 'the', 'universes', 'in', 'gdtt', 'must', 'be', 'indexed', 'by', 'contexts', 'of', 'clock', 'variables', 'we', 'show', 'how', 'to', 'model', 'these', 'universes', 'in', 'such', 'a', 'way', 'that', 'inclusions', 'of', 'clock', 'contexts', 'give', 'rise', 'to', 'inclusions', 'of', 'universes', 'commuting', 'with', 'type', 'operations', 'on', 'the', 'nose']] | [-0.125078538175514, 0.09222573539526878, -0.0999900790280089, 0.08735287972677756, -0.10973277351740986, -0.17910441859703272, 0.05553610012648636, 0.3424572342722287, -0.33027329180261183, -0.2834812380979067, 0.08791325049098636, -0.17996439922903779, -0.0885881803656832, 0.18315713917274543, -0.16160975929046867, -0.027543886541733013, 0.02454045079671434, 0.06351964094267763, -0.04341494762570955, -0.24561407000487073, 0.33971960253995187, -0.010260102795574612, 0.22994725158509555, -0.012162467428102283, 0.10698352956767607, 0.007106498310461714, -0.03671675731297215, 0.0730479552589467, -0.09105675961046504, 0.13479523973658755, 0.2950505553615164, 0.19277664404729464, 0.23167607820537767, -0.4659424614381467, -0.16765991056190568, 0.11156456470902404, 0.12168387146758403, 0.10565669010588302, 0.03107343629585221, -0.31351027482537913, 0.05293387950058531, -0.19916397272586236, -0.10514595212066188, -0.08966822283379183, 0.026197387469849856, 0.047411065138050636, -0.23047924535652953, -0.00798381485613843, 0.11732201672530747, 0.1095625783025466, -0.08596825691770414, -0.04592800999216258, -0.020812499293314267, 0.07474483502512623, -0.006845141987527349, -0.007638475464271574, 0.0941026543652446, -0.06594140541377326, -0.1928314396800712, 0.39172460403958026, -0.06367039691262277, -0.21576383003731042, 0.18805258010520962, -0.0779728560015706, -0.19355077538731064, 0.03940586439044825, 0.07833524691996169, 0.1291523782325349, -0.14910042207926658, 0.11897864271835035, -0.04023668673715274, 0.20538618568367706, 0.1211097242426485, 0.08268295292710436, 0.22136552884183788, 0.15731208517762094, 0.015645556620395573, 0.11465805779346563, 0.05747439543111021, -0.10420156979424136, -0.36443806739938056, -0.1515885835900281, -0.0772960229049634, 0.02025987087467082, -0.09183500903758067, -0.21985423752551742, 0.34330406677656866, 0.15857055042572135, 0.12237555244387004, 0.10648498000184836, 0.2635898229533008, 0.10148705711434572, 0.13888905734842266, 0.010372836493171311, 0.14683294140738365, 0.15615263910564994, 0.09230414523428829, -0.1163912088383136, 0.09616908081692502, 0.17246971598349217] |
1,802.03745 | Geant4 simulation of the ELIMED transport and dosimetry beam line for
high-energy laser-driven ion beam multidisciplinary applications | The ELIMED (MEDical and multidisciplinary application at ELI Beamlines) beam
line is being developed at INFN-LNS with the aim of transporting and selecting
in energy proton and ion beams accelerated by laser-matter interaction at ELI
Beamlines in Prague. It will be a section of the ELIMAIA (ELI Multidisciplinary
Applications of laser-Ions Acceleration) beam line, dedicated to applications,
including the medical one, of laser-accelerated ion beams [1,2]. A Monte Carlo
model has been developed to support the design of the beam line in terms of
particle transport efficiency, to optimize the transport parameters at the
irradiation point in air and, furthermore, to predict beam parameters in order
to deliver dose distributions of clinical relevance. The application has been
developed using the Geant4 [3] Monte Carlo toolkit and has been designed in a
modular way in order to easily switch on/off geometrical components according
to different experimental setups and users requirements, as reported in [4],
describing the early-stage code and simulations. The application has been
delivered to ELI Beamlines and will be available for future ELIMAIA's users as
ready-to-use tool useful during experiment preparation and analysis. The final
version of the developed application will be described in detail in this
contribution, together with the final results, in terms of energy spectra and
transmission efficiency along the in-vacuum beam line, obtained by performing
end-to-end simulations.
| physics.acc-ph physics.app-ph | the elimed medical and multidisciplinary application at eli beamlines beam line is being developed at infnlns with the aim of transporting and selecting in energy proton and ion beams accelerated by lasermatter interaction at eli beamlines in prague it will be a section of the elimaia eli multidisciplinary applications of laserions acceleration beam line dedicated to applications including the medical one of laseraccelerated ion beams 12 a monte carlo model has been developed to support the design of the beam line in terms of particle transport efficiency to optimize the transport parameters at the irradiation point in air and furthermore to predict beam parameters in order to deliver dose distributions of clinical relevance the application has been developed using the geant4 3 monte carlo toolkit and has been designed in a modular way in order to easily switch onoff geometrical components according to different experimental setups and users requirements as reported in 4 describing the earlystage code and simulations the application has been delivered to eli beamlines and will be available for future elimaias users as readytouse tool useful during experiment preparation and analysis the final version of the developed application will be described in detail in this contribution together with the final results in terms of energy spectra and transmission efficiency along the invacuum beam line obtained by performing endtoend simulations | [['the', 'elimed', 'medical', 'and', 'multidisciplinary', 'application', 'at', 'eli', 'beamlines', 'beam', 'line', 'is', 'being', 'developed', 'at', 'infnlns', 'with', 'the', 'aim', 'of', 'transporting', 'and', 'selecting', 'in', 'energy', 'proton', 'and', 'ion', 'beams', 'accelerated', 'by', 'lasermatter', 'interaction', 'at', 'eli', 'beamlines', 'in', 'prague', 'it', 'will', 'be', 'a', 'section', 'of', 'the', 'elimaia', 'eli', 'multidisciplinary', 'applications', 'of', 'laserions', 'acceleration', 'beam', 'line', 'dedicated', 'to', 'applications', 'including', 'the', 'medical', 'one', 'of', 'laseraccelerated', 'ion', 'beams', '12', 'a', 'monte', 'carlo', 'model', 'has', 'been', 'developed', 'to', 'support', 'the', 'design', 'of', 'the', 'beam', 'line', 'in', 'terms', 'of', 'particle', 'transport', 'efficiency', 'to', 'optimize', 'the', 'transport', 'parameters', 'at', 'the', 'irradiation', 'point', 'in', 'air', 'and', 'furthermore', 'to', 'predict', 'beam', 'parameters', 'in', 'order', 'to', 'deliver', 'dose', 'distributions', 'of', 'clinical', 'relevance', 'the', 'application', 'has', 'been', 'developed', 'using', 'the', 'geant4', '3', 'monte', 'carlo', 'toolkit', 'and', 'has', 'been', 'designed', 'in', 'a', 'modular', 'way', 'in', 'order', 'to', 'easily', 'switch', 'onoff', 'geometrical', 'components', 'according', 'to', 'different', 'experimental', 'setups', 'and', 'users', 'requirements', 'as', 'reported', 'in', '4', 'describing', 'the', 'earlystage', 'code', 'and', 'simulations', 'the', 'application', 'has', 'been', 'delivered', 'to', 'eli', 'beamlines', 'and', 'will', 'be', 'available', 'for', 'future', 'elimaias', 'users', 'as', 'readytouse', 'tool', 'useful', 'during', 'experiment', 'preparation', 'and', 'analysis', 'the', 'final', 'version', 'of', 'the', 'developed', 'application', 'will', 'be', 'described', 'in', 'detail', 'in', 'this', 'contribution', 'together', 'with', 'the', 'final', 'results', 'in', 'terms', 'of', 'energy', 'spectra', 'and', 'transmission', 'efficiency', 'along', 'the', 'invacuum', 'beam', 'line', 'obtained', 'by', 'performing', 'endtoend', 'simulations']] | [-0.037323209967618, 0.10817421331719726, -0.07820980895925826, 0.04153702350615293, -0.03340618597309387, -0.14476386280255094, -0.014081869766205856, 0.44258450614897227, -0.1947930428442981, -0.36766837060733465, 0.09143794607958508, -0.28756619557373037, -0.017576615813128447, 0.25491397393228693, -0.006904785363259939, 0.11727914256428223, 0.08851746228681621, -0.025748573523441995, -0.01839449213243115, -0.21774528899343273, 0.25191628960508067, 0.2178966837909517, 0.31456426839043017, 0.0918157958727834, 0.09621472012063642, 0.02867224130676974, -0.03157140437963231, -0.012093075695577122, -0.12035806451690781, 0.11074484536133775, 0.3246254077955008, 0.13409149327204314, 0.23161473290550463, -0.4388736054523412, -0.22094240715116298, 0.04462182027909375, 0.15164367568042608, 0.07561225678457734, -0.09085455256697952, -0.24558886115806638, 0.05501455733196921, -0.207734633745506, -0.1713118154551287, -0.051611152498923035, -0.0344076030033239, 0.075185414719814, -0.2687434857677019, -0.055328179259758886, -0.055116940544194054, 0.08561592208103537, -0.012748723013386335, -0.12906404207684868, 0.01695383587903386, 0.10683617368020083, 0.034143574040814584, 0.06149144698716187, 0.1649829002584271, -0.10646027046332665, -0.13283322458881713, 0.3793096364269657, -0.01950072572745998, -0.14851667985550787, 0.17262281298769827, -0.12215125782910836, -0.10113804356767497, 0.16202965313264323, 0.21346477141236425, 0.08114879673994103, -0.18528994989000397, 0.03771280183475128, 0.06113302674349568, 0.13289524909216882, 0.09039897089204622, -0.0212610145377149, 0.19111679969440906, 0.20838339264085942, 0.006065610690444757, 0.14174377868005925, -0.12352720254160669, -0.044845203420471984, -0.2720196826197634, -0.18251320000293605, -0.14206614693530104, 0.02123914911772697, 0.02150686355929826, -0.06238340578734054, 0.40110947635909117, 0.16518705782006332, 0.11463301731358974, -0.05801575965517192, 0.3359334934930052, 0.08195207098262906, 0.06645049886145724, 0.024557100350481517, 0.226057653899578, 0.09807262208094204, 0.17342165192170494, -0.20382222453337334, 0.05742582104408071, 0.006863458338407202] |
1,802.03746 | Conserving symmetries in Bose-Einstein condensate dynamics requires
many-body theory | We explain from first principles why satisfying conservation laws in Bose
Einstein condensate dynamics requires many-body theory. For the
Gross-Pitaevskii mean-field we show analytically and numerically that
conservation laws are violated. We provide examples for angular momentum and
linear momentum conservation. Arbitrarily large violations occur despite
negligible depletion and interaction energy. For the case of angular momentum
we show through extensive many-body simulations how the conservation law can be
gradually restored on the many-body level. Implications are discussed.
| cond-mat.quant-gas | we explain from first principles why satisfying conservation laws in bose einstein condensate dynamics requires manybody theory for the grosspitaevskii meanfield we show analytically and numerically that conservation laws are violated we provide examples for angular momentum and linear momentum conservation arbitrarily large violations occur despite negligible depletion and interaction energy for the case of angular momentum we show through extensive manybody simulations how the conservation law can be gradually restored on the manybody level implications are discussed | [['we', 'explain', 'from', 'first', 'principles', 'why', 'satisfying', 'conservation', 'laws', 'in', 'bose', 'einstein', 'condensate', 'dynamics', 'requires', 'manybody', 'theory', 'for', 'the', 'grosspitaevskii', 'meanfield', 'we', 'show', 'analytically', 'and', 'numerically', 'that', 'conservation', 'laws', 'are', 'violated', 'we', 'provide', 'examples', 'for', 'angular', 'momentum', 'and', 'linear', 'momentum', 'conservation', 'arbitrarily', 'large', 'violations', 'occur', 'despite', 'negligible', 'depletion', 'and', 'interaction', 'energy', 'for', 'the', 'case', 'of', 'angular', 'momentum', 'we', 'show', 'through', 'extensive', 'manybody', 'simulations', 'how', 'the', 'conservation', 'law', 'can', 'be', 'gradually', 'restored', 'on', 'the', 'manybody', 'level', 'implications', 'are', 'discussed']] | [-0.16946408584212455, 0.20426563116220328, -0.11370727192395581, 0.17232753942983273, -0.033028877186459284, -0.14468713861722976, 0.006759529854230679, 0.31392792526345986, -0.23776998521330264, -0.30013055897628266, 0.004228144410985689, -0.28959065307236204, -0.12860244082716796, 0.14528436082391402, 0.01564506894404379, 0.1136329293800279, 0.05911184524675497, -0.07335053539039411, -0.0757513405271591, -0.2046324688081558, 0.35080197025448656, 0.03906707537288849, 0.2827758481248449, 0.1410107201216026, 0.1314833891661599, -0.016571764440204088, 0.03401246695265842, 0.0662138947369292, -0.15383633924993306, -0.012984288971309956, 0.22263672674531476, 0.05779081180046957, 0.22765953803005126, -0.5221807561241664, -0.19143034490004468, 0.06926308525129198, 0.18131274615641302, 0.19265329899290243, -0.09658978007530841, -0.272516217855856, 0.012321827574991263, -0.21675580971611616, -0.22411570069977108, -0.23664643188031056, 0.024479985750543002, 0.06614648277023569, -0.21601590889697084, 0.20965775228941289, 0.06473674783960749, 0.05926067432245383, -0.10192203102036355, -0.0533879065217498, -0.06547112538455388, 0.0661427051631901, 0.07955666387449757, -0.08717823163897265, 0.11658603839504604, -0.12243857413070658, -0.0691139653731042, 0.4274785086178245, -0.02390445198995085, -0.26353292339123213, 0.15121367609408948, -0.18725142278111515, -0.13642373515400463, 0.10222715784150821, 0.14436416234224078, 0.06527850966356197, -0.1211304673865342, 0.1170119566772766, -0.012407149092700237, 0.16175948150563413, 0.0372689402817438, 0.07428179536826718, 0.2519089426869192, 0.11512719054754154, 0.034918783041529164, 0.09206311267543918, -0.03676564728494924, -0.2398907684434492, -0.3707617938709565, -0.11400050271036796, -0.24096692795268235, 0.11284072195531991, -0.05250104664745054, -0.015480512777009072, 0.30911182863816905, 0.17319720279640302, 0.14018812918892273, 0.10670975532430486, 0.2687598435411182, 0.21338545276711768, 0.032893577739835166, 0.09392341854860813, 0.3066055767524701, 0.14448119550704575, 0.1438193125769687, -0.3101522761414974, -0.035993644567684106, 0.07798652462243365] |
1,802.03747 | Bounds for the first non-zero Steklov eigenvalue | Let $\Omega$ be a star-shaped bounded domain in $(\mathbb{S}^{n}, ds^{2})$
with smooth boundary. In this article, we give a sharp lower bound for the
first non-zero eigenvalue of the Steklov eigenvalue problem in $\Omega.$ This
result is the generalization of a result given by Kuttler and Sigillito for a
star-shaped bounded domain in $\mathbb{R}^2.$ Further we also obtain a two
sided bound for the first non-zero eigenvalue of the Steklov problem on the
ball in $\mathbb{R}^n$ with rotationally invariant metric and with bounded
radial curvature.
| math.DG | let omega be a starshaped bounded domain in mathbbsn ds2 with smooth boundary in this article we give a sharp lower bound for the first nonzero eigenvalue of the steklov eigenvalue problem in omega this result is the generalization of a result given by kuttler and sigillito for a starshaped bounded domain in mathbbr2 further we also obtain a two sided bound for the first nonzero eigenvalue of the steklov problem on the ball in mathbbrn with rotationally invariant metric and with bounded radial curvature | [['let', 'omega', 'be', 'a', 'starshaped', 'bounded', 'domain', 'in', 'mathbbsn', 'ds2', 'with', 'smooth', 'boundary', 'in', 'this', 'article', 'we', 'give', 'a', 'sharp', 'lower', 'bound', 'for', 'the', 'first', 'nonzero', 'eigenvalue', 'of', 'the', 'steklov', 'eigenvalue', 'problem', 'in', 'omega', 'this', 'result', 'is', 'the', 'generalization', 'of', 'a', 'result', 'given', 'by', 'kuttler', 'and', 'sigillito', 'for', 'a', 'starshaped', 'bounded', 'domain', 'in', 'mathbbr2', 'further', 'we', 'also', 'obtain', 'a', 'two', 'sided', 'bound', 'for', 'the', 'first', 'nonzero', 'eigenvalue', 'of', 'the', 'steklov', 'problem', 'on', 'the', 'ball', 'in', 'mathbbrn', 'with', 'rotationally', 'invariant', 'metric', 'and', 'with', 'bounded', 'radial', 'curvature']] | [-0.16668354512824277, 0.07834184061946525, -0.046673594788271225, -0.009863371014251329, -0.10145389095747046, -0.13070080759158978, -0.011373416304455273, 0.3045142386108637, -0.26385763398415985, -0.20629667874336952, 0.15540143198727274, -0.29371406282076523, -0.12783751896183407, 0.14851651179681843, -0.12653222961151706, 0.10004185676752102, 0.07397981933207207, 0.12906161003879138, -0.044693760673648546, -0.19229368107127293, 0.4193994009401649, -0.12889022914515363, 0.1595661509227717, 0.17110970236050585, 0.05220434380628701, -0.08961489682440602, 0.037051567992117874, 0.01336088502458075, -0.2665890779490361, 0.16787574116772572, 0.24253948779577122, 0.054782436068524565, 0.291200540826789, -0.38028959275799845, -0.15819448981797213, 0.21326116706422044, 0.15411539287638984, -0.011734239690537964, -0.049335005769361964, -0.3412109493787977, 0.12002116859713126, -0.04266254273464992, -0.2066662422924613, 0.017541713890663925, 0.05675556413119748, -0.037609962546931844, -0.29655541099297505, 0.13342482410059478, 0.16467966693675234, 0.02123444176565196, -0.15447056735311412, -0.14309682587017528, 0.02565497596792522, 0.04052787097281821, -0.008992442176566414, 0.11980508445412852, -0.020815759897232056, -0.027971329184115996, -0.0649499204176079, 0.3391054076408701, -0.14798151226049022, -0.3504192680563955, 0.0344286641394276, -0.24446580520764524, -0.10893014977530886, 0.057836113697183986, 0.1935561595129825, 0.20297745154017494, -0.06803864792787603, 0.19915450166860996, -0.11134539294982373, 0.07821295152479295, 0.16631066722662322, -0.043483069321761526, 0.08214988861055601, 0.11411975444449733, 0.25423184071024435, 0.20197933077274466, -0.032970154336431905, -0.029883218330464194, -0.3981021900794336, -0.13890386690729342, -0.2770677648340574, 0.11587671360688373, -0.12993172953048043, -0.21293484938463994, 0.35441942512989044, -0.03097068998474805, 0.2411754203162023, 0.15347692975774407, 0.25642969572384444, 0.1303483439897675, -0.036557525684613554, 0.13086354746372394, 0.14366032390500463, 0.17342970582623302, 0.0813559261206094, -0.18060975774451868, -0.040612778443443985, 0.13881955757737852] |
1,802.03748 | Binary Pebbling Algorithms for In-Place Reversal of One-Way Hash Chains | We present optimal binary pebbling algorithms for in-place reversal (backward
traversal) of one-way hash chains. For a hash chain of length $2^k$, the number
of hashes performed in each output round does not exceed $\lceil k/2 \rceil$,
whereas the number of hash values stored (pebbles) throughout is at most $k$.
We introduce a framework for rigorous comparison of explicit binary pebbling
algorithms, including simple speed-1 binary pebbling, Jakobsson's speed-2
binary pebbling, and our optimal binary pebbling algorithm. Explicit schedules
describe for each pebble exactly how many hashes need to be performed in each
round. The optimal schedule turns out to be essentially unique and exhibits a
nice recursive structure, which allows for fully optimized implementations that
can readily be deployed. In particular, we develop the first in-place
implementations with minimal storage overhead (essentially, storing only hash
values), and fast implementations with minimal computational overhead.
| cs.CR cs.DS | we present optimal binary pebbling algorithms for inplace reversal backward traversal of oneway hash chains for a hash chain of length 2k the number of hashes performed in each output round does not exceed lceil k2 rceil whereas the number of hash values stored pebbles throughout is at most k we introduce a framework for rigorous comparison of explicit binary pebbling algorithms including simple speed1 binary pebbling jakobssons speed2 binary pebbling and our optimal binary pebbling algorithm explicit schedules describe for each pebble exactly how many hashes need to be performed in each round the optimal schedule turns out to be essentially unique and exhibits a nice recursive structure which allows for fully optimized implementations that can readily be deployed in particular we develop the first inplace implementations with minimal storage overhead essentially storing only hash values and fast implementations with minimal computational overhead | [['we', 'present', 'optimal', 'binary', 'pebbling', 'algorithms', 'for', 'inplace', 'reversal', 'backward', 'traversal', 'of', 'oneway', 'hash', 'chains', 'for', 'a', 'hash', 'chain', 'of', 'length', '2k', 'the', 'number', 'of', 'hashes', 'performed', 'in', 'each', 'output', 'round', 'does', 'not', 'exceed', 'lceil', 'k2', 'rceil', 'whereas', 'the', 'number', 'of', 'hash', 'values', 'stored', 'pebbles', 'throughout', 'is', 'at', 'most', 'k', 'we', 'introduce', 'a', 'framework', 'for', 'rigorous', 'comparison', 'of', 'explicit', 'binary', 'pebbling', 'algorithms', 'including', 'simple', 'speed1', 'binary', 'pebbling', 'jakobssons', 'speed2', 'binary', 'pebbling', 'and', 'our', 'optimal', 'binary', 'pebbling', 'algorithm', 'explicit', 'schedules', 'describe', 'for', 'each', 'pebble', 'exactly', 'how', 'many', 'hashes', 'need', 'to', 'be', 'performed', 'in', 'each', 'round', 'the', 'optimal', 'schedule', 'turns', 'out', 'to', 'be', 'essentially', 'unique', 'and', 'exhibits', 'a', 'nice', 'recursive', 'structure', 'which', 'allows', 'for', 'fully', 'optimized', 'implementations', 'that', 'can', 'readily', 'be', 'deployed', 'in', 'particular', 'we', 'develop', 'the', 'first', 'inplace', 'implementations', 'with', 'minimal', 'storage', 'overhead', 'essentially', 'storing', 'only', 'hash', 'values', 'and', 'fast', 'implementations', 'with', 'minimal', 'computational', 'overhead']] | [-0.16991368844999488, 0.10294052284105239, -0.06946004468762705, 0.05001539256587188, -0.11369399522953, -0.2925699836217818, 0.14290831968393045, 0.42480907597783824, -0.28391965113808104, -0.3302693786033502, 0.09126586617335532, -0.23382411878203052, -0.09740871440698491, 0.20083545648380585, -0.1033320533613681, 0.14682249604920025, 0.13006609107255407, 0.041958134545422826, -0.027925421792604294, -0.3491588531578858, 0.20608520732056482, 0.06319276378192801, 0.198358899636313, -0.04866168437631312, 0.10313440803834732, 0.04938927289727639, 0.01885481655650528, 0.0003456836830533988, -0.1572775626243922, 0.07815739320894928, 0.31316925813476987, 0.20326026706751568, 0.246287938827444, -0.45887051351659053, -0.1062003881249458, 0.14295473314181023, 0.17399710192219586, 0.14940494225040105, -0.055222257819845744, -0.12212821332727895, 0.1423328706890622, -0.18049765137479978, -0.025438243571127242, -0.0655423171904123, 0.04400909544094234, 0.023259112796356493, -0.2836544573631514, -0.07006525084936119, 0.06319333244807002, -0.016095703191137112, 0.034954926036612016, -0.14394326471386754, 0.007001405157452674, 0.12177133122591156, -0.06781536442597548, 0.024084597508958045, 0.10364886921506825, -0.040732347782939035, -0.18523798981377632, 0.3470222997274382, 0.01660595319716009, -0.17959806087083374, 0.0933180501435203, -0.06526771435474461, -0.18715408322209795, 0.16198931712366588, 0.18529719287357854, 0.16680802758915206, -0.10572453683402376, 0.06319728011722801, -0.06839079069013292, 0.23735195894045294, 0.15528143486602508, 0.04773060825210831, 0.16757811956001933, 0.14510973423871323, 0.1188376486009971, 0.21359881082490245, -0.03063973396870387, -0.11510974827225828, -0.2713840216446126, -0.15836947843273905, -0.21310862084249602, -0.0007828146809380145, -0.15742957691056406, -0.17300691444373933, 0.3520542796113337, 0.14176834451017972, 0.1739517112216311, 0.17720288875866153, 0.343964613584392, 0.04912748251107013, 0.11091249345980109, 0.24230163046720285, 0.10852659555772941, 0.042058820353246276, 0.049371123694524115, -0.2051471085584861, 0.13760706587489827, 0.14827256776798675] |
1,802.03749 | Locality Optimized Unstructured Mesh Algorithms on GPUs | Unstructured-mesh based numerical algorithms such as finite volume and finite
element algorithms form an important class of applications for many scientific
and engineering domains. The key difficulty in achieving higher performance
from these applications is the indirect accesses that lead to data-races when
parallelized. Current methods for handling such data-races lead to reduced
parallelism and suboptimal performance. Particularly on modern many-core
architectures, such as GPUs, that has increasing core/thread counts, reducing
data movement and exploiting memory locality is vital for gaining good
performance.
In this work we present novel locality-exploiting optimizations for the
efficient execution of unstructured-mesh algorithms on GPUs. Building on a
two-layered coloring strategy for handling data races, we introduce novel
reordering and partitioning techniques to further improve efficient execution.
The new optimizations are then applied to several well established
unstructured-mesh applications, investigating their performance on NVIDIA's
latest P100 and V100 GPUs. We demonstrate significant speedups
($1.1\text{--}1.75\times$) compared to the state-of-the-art. A range of
performance metrics are benchmarked including runtime, memory transactions,
achieved bandwidth performance, GPU occupancy and data reuse factors and are
used to understand and explain the key factors impacting performance. The
optimized algorithms are implemented as an open-source software library and we
illustrate its use for improving performance of existing or new
unstructured-mesh applications.
| cs.MS cs.DC | unstructuredmesh based numerical algorithms such as finite volume and finite element algorithms form an important class of applications for many scientific and engineering domains the key difficulty in achieving higher performance from these applications is the indirect accesses that lead to dataraces when parallelized current methods for handling such dataraces lead to reduced parallelism and suboptimal performance particularly on modern manycore architectures such as gpus that has increasing corethread counts reducing data movement and exploiting memory locality is vital for gaining good performance in this work we present novel localityexploiting optimizations for the efficient execution of unstructuredmesh algorithms on gpus building on a twolayered coloring strategy for handling data races we introduce novel reordering and partitioning techniques to further improve efficient execution the new optimizations are then applied to several well established unstructuredmesh applications investigating their performance on nvidias latest p100 and v100 gpus we demonstrate significant speedups 11text175times compared to the stateoftheart a range of performance metrics are benchmarked including runtime memory transactions achieved bandwidth performance gpu occupancy and data reuse factors and are used to understand and explain the key factors impacting performance the optimized algorithms are implemented as an opensource software library and we illustrate its use for improving performance of existing or new unstructuredmesh applications | [['unstructuredmesh', 'based', 'numerical', 'algorithms', 'such', 'as', 'finite', 'volume', 'and', 'finite', 'element', 'algorithms', 'form', 'an', 'important', 'class', 'of', 'applications', 'for', 'many', 'scientific', 'and', 'engineering', 'domains', 'the', 'key', 'difficulty', 'in', 'achieving', 'higher', 'performance', 'from', 'these', 'applications', 'is', 'the', 'indirect', 'accesses', 'that', 'lead', 'to', 'dataraces', 'when', 'parallelized', 'current', 'methods', 'for', 'handling', 'such', 'dataraces', 'lead', 'to', 'reduced', 'parallelism', 'and', 'suboptimal', 'performance', 'particularly', 'on', 'modern', 'manycore', 'architectures', 'such', 'as', 'gpus', 'that', 'has', 'increasing', 'corethread', 'counts', 'reducing', 'data', 'movement', 'and', 'exploiting', 'memory', 'locality', 'is', 'vital', 'for', 'gaining', 'good', 'performance', 'in', 'this', 'work', 'we', 'present', 'novel', 'localityexploiting', 'optimizations', 'for', 'the', 'efficient', 'execution', 'of', 'unstructuredmesh', 'algorithms', 'on', 'gpus', 'building', 'on', 'a', 'twolayered', 'coloring', 'strategy', 'for', 'handling', 'data', 'races', 'we', 'introduce', 'novel', 'reordering', 'and', 'partitioning', 'techniques', 'to', 'further', 'improve', 'efficient', 'execution', 'the', 'new', 'optimizations', 'are', 'then', 'applied', 'to', 'several', 'well', 'established', 'unstructuredmesh', 'applications', 'investigating', 'their', 'performance', 'on', 'nvidias', 'latest', 'p100', 'and', 'v100', 'gpus', 'we', 'demonstrate', 'significant', 'speedups', '11text175times', 'compared', 'to', 'the', 'stateoftheart', 'a', 'range', 'of', 'performance', 'metrics', 'are', 'benchmarked', 'including', 'runtime', 'memory', 'transactions', 'achieved', 'bandwidth', 'performance', 'gpu', 'occupancy', 'and', 'data', 'reuse', 'factors', 'and', 'are', 'used', 'to', 'understand', 'and', 'explain', 'the', 'key', 'factors', 'impacting', 'performance', 'the', 'optimized', 'algorithms', 'are', 'implemented', 'as', 'an', 'opensource', 'software', 'library', 'and', 'we', 'illustrate', 'its', 'use', 'for', 'improving', 'performance', 'of', 'existing', 'or', 'new', 'unstructuredmesh', 'applications']] | [-0.10822193534339516, -0.024835754783673763, -0.021120192568966197, 0.06066948480427139, -0.11027189319754399, -0.16684094259235105, 0.04981804883799253, 0.44899457511356444, -0.2625104645967881, -0.3757851128195168, 0.12860724109098387, -0.21478220419867813, -0.1259308316625058, 0.3097617353563586, -0.1206355626280623, 0.13882979242672502, 0.1544475500569091, -0.026598084916912235, -0.09399104286937464, -0.3225348425743134, 0.21211291167283775, 0.11206939101029297, 0.3421333846195321, 0.09264449353185165, 0.07352795188405067, -0.03213900390750213, -0.03364660786871699, 0.001989592174158513, -0.07085113760398405, 0.1671551568026754, 0.30132246990371675, 0.2072839141389337, 0.3120569230862034, -0.4518467488637063, -0.16799331535935602, 0.056445107695836466, 0.1565247959101593, 0.05539693525264455, -0.09447275750899634, -0.2542595191546761, 0.10990778046425034, -0.20653757990283655, -0.03057340789220106, -0.20579136254772254, -0.028608773471064216, 0.050232788125161555, -0.26265513065985396, -0.016573343195418998, 0.023383817762629246, 0.06936669415676767, 0.006625643242444409, -0.1988054480193436, 0.07360069822741545, 0.164816969965649, 0.01106710077231768, 0.019954774273306275, 0.14638345576206774, -0.13515972873411883, -0.2080024691610552, 0.3984656410915687, -0.022499876022248448, -0.18666569679270237, 0.2221241576350701, 0.03509964178162582, -0.1811369679737113, 0.08367603466149817, 0.2681287754580234, 0.06845285099912977, -0.12359656316480538, 0.07260896293028231, 0.08103664120426401, 0.18069366266181267, 0.07117046971886772, 0.07627220318123734, 0.1265426214978786, 0.26887592107387603, 0.06098070941177124, 0.13789505667241914, -0.054789245355811006, -0.09732011785771408, -0.18120995031904827, -0.18673716831779405, -0.17164557167889496, -0.04569443015752415, -0.11869772398339706, -0.1548020928053782, 0.3699857593159128, 0.2252869522651133, 0.11802520774286783, 0.08372191384488951, 0.39444756792921537, 0.03971560700012154, 0.1563613738839795, 0.1708290090070115, 0.1239735782739833, 0.024146108178295267, 0.13226386094132428, -0.21578245088333733, 0.06678248172200926, -0.009191470160216852] |
1,802.0375 | FD-MobileNet: Improved MobileNet with a Fast Downsampling Strategy | We present Fast-Downsampling MobileNet (FD-MobileNet), an efficient and
accurate network for very limited computational budgets (e.g., 10-140 MFLOPs).
Our key idea is applying an aggressive downsampling strategy to MobileNet
framework. In FD-MobileNet, we perform 32$\times$ downsampling within 12
layers, only half the layers in the original MobileNet. This design brings
three advantages: (i) It remarkably reduces the computational cost. (ii) It
increases the information capacity and achieves significant performance
improvements. (iii) It is engineering-friendly and provides fast actual
inference speed. Experiments on ILSVRC 2012 and PASCAL VOC 2007 datasets
demonstrate that FD-MobileNet consistently outperforms MobileNet and achieves
comparable results with ShuffleNet under different computational budgets, for
instance, surpassing MobileNet by 5.5% on the ILSVRC 2012 top-1 accuracy and
3.6% on the VOC 2007 mAP under a complexity of 12 MFLOPs. On an ARM-based
device, FD-MobileNet achieves 1.11$\times$ inference speedup over MobileNet and
1.82$\times$ over ShuffleNet under the same complexity.
| cs.CV | we present fastdownsampling mobilenet fdmobilenet an efficient and accurate network for very limited computational budgets eg 10140 mflops our key idea is applying an aggressive downsampling strategy to mobilenet framework in fdmobilenet we perform 32times downsampling within 12 layers only half the layers in the original mobilenet this design brings three advantages i it remarkably reduces the computational cost ii it increases the information capacity and achieves significant performance improvements iii it is engineeringfriendly and provides fast actual inference speed experiments on ilsvrc 2012 and pascal voc 2007 datasets demonstrate that fdmobilenet consistently outperforms mobilenet and achieves comparable results with shufflenet under different computational budgets for instance surpassing mobilenet by 55 on the ilsvrc 2012 top1 accuracy and 36 on the voc 2007 map under a complexity of 12 mflops on an armbased device fdmobilenet achieves 111times inference speedup over mobilenet and 182times over shufflenet under the same complexity | [['we', 'present', 'fastdownsampling', 'mobilenet', 'fdmobilenet', 'an', 'efficient', 'and', 'accurate', 'network', 'for', 'very', 'limited', 'computational', 'budgets', 'eg', '10140', 'mflops', 'our', 'key', 'idea', 'is', 'applying', 'an', 'aggressive', 'downsampling', 'strategy', 'to', 'mobilenet', 'framework', 'in', 'fdmobilenet', 'we', 'perform', '32times', 'downsampling', 'within', '12', 'layers', 'only', 'half', 'the', 'layers', 'in', 'the', 'original', 'mobilenet', 'this', 'design', 'brings', 'three', 'advantages', 'i', 'it', 'remarkably', 'reduces', 'the', 'computational', 'cost', 'ii', 'it', 'increases', 'the', 'information', 'capacity', 'and', 'achieves', 'significant', 'performance', 'improvements', 'iii', 'it', 'is', 'engineeringfriendly', 'and', 'provides', 'fast', 'actual', 'inference', 'speed', 'experiments', 'on', 'ilsvrc', '2012', 'and', 'pascal', 'voc', '2007', 'datasets', 'demonstrate', 'that', 'fdmobilenet', 'consistently', 'outperforms', 'mobilenet', 'and', 'achieves', 'comparable', 'results', 'with', 'shufflenet', 'under', 'different', 'computational', 'budgets', 'for', 'instance', 'surpassing', 'mobilenet', 'by', '55', 'on', 'the', 'ilsvrc', '2012', 'top1', 'accuracy', 'and', '36', 'on', 'the', 'voc', '2007', 'map', 'under', 'a', 'complexity', 'of', '12', 'mflops', 'on', 'an', 'armbased', 'device', 'fdmobilenet', 'achieves', '111times', 'inference', 'speedup', 'over', 'mobilenet', 'and', '182times', 'over', 'shufflenet', 'under', 'the', 'same', 'complexity']] | [-0.060535728178714235, -0.03937731321938161, 0.0012825865151794397, 0.011233681287418744, -0.03468236047136661, -0.1637155104983496, 0.10099871683553219, 0.42882195566717074, -0.16634185253068395, -0.40971675809881053, 0.08290775408426121, -0.2750960391282729, -0.13311704796378512, 0.28862488123090707, -0.19448255529875982, 0.06267567858584736, 0.18872819775045682, -0.03476003954212551, -0.1089529199800805, -0.39702091438134446, 0.14408372535150218, 0.11730130853718274, 0.3919007182185066, 0.06426131841766469, 0.18686385533440705, -0.05216167711219049, 0.009673177027813324, -0.038411347559902, -0.04190772976942579, 0.09907920779468976, 0.19268497337000318, 0.16787041941887304, 0.2940073829424912, -0.37083239349447294, -0.14322053025833853, 0.0020609102100261475, 0.08781197127973428, 0.024601652345254105, -0.004349890219251791, -0.30101254974070885, 0.10161871877690293, -0.20186840771850556, 0.08210607531021209, -0.14281536399048742, 0.01167276419048542, -0.0510752130593237, -0.2947939720247196, 0.09230615435748629, 0.06953201554907001, 0.06073938957447416, -0.028936762040583035, -0.2044068111476731, 0.036480370885054646, 0.11926028333055748, -0.05942338412270358, 0.09304526819104379, 0.1306734920770595, -0.16687939734013163, -0.15759234638064973, 0.3446278067637388, -0.09307248271166105, -0.14783939675823465, 0.19810879616105087, -0.01874118129888626, -0.1303936569189592, 0.14891736042105325, 0.17207657608278543, 0.06955608529236473, -0.06569258294591349, 0.07593389466278931, -0.04255890383780615, 0.2355627259367133, 0.0948284547887615, -0.023334467072320515, 0.04736940314266065, 0.30422441594498806, 0.07379530310911471, 0.11121563244154932, -0.20320415467642605, -0.09536110365158107, -0.16801236072325543, -0.14360865728029812, -0.13204853053919155, 0.0060701169685958185, -0.16793198232494744, -0.05068681161684839, 0.39900454584738776, 0.24172465943999283, 0.16991040185540404, 0.15617817216425214, 0.3195043363694535, -0.0027185052972963104, 0.10922154422318371, 0.20289289916001182, 0.22355218945798297, -0.0029574422092393856, 0.12675061495615847, -0.19394399694084152, 0.03075982538396365, 0.00782756950093867] |
1,802.03751 | Artificial intelligence meets minority game: toward optimal resource
allocation | Resource allocation systems provide the fundamental support for the normal
functioning and well being of the modern society, and can be modeled as
minority games. A ubiquitous dynamical phenomenon is the emergence of herding,
where a vast majority of the users concentrate on a small number of resources,
leading to a low efficiency in resource allocation. To devise strategies to
prevent herding is thus of high interest. Previous works focused on control
strategies that rely on external interventions, such as pinning control where a
fraction of users are forced to choose a certain action. Is it possible to
eliminate herding without any external control? The main point of this paper is
to provide an affirmative answer through exploiting artificial intelligence
(AI). In particular, we demonstrate that, when agents are empowered with
reinforced learning in that they get familiar with the unknown game environment
gradually and attempt to deliver the optimal actions to maximize the payoff,
herding can effectively be eliminated. Computations reveal the striking
phenomenon that, regardless of the initial state, the system evolves
persistently and relentlessly toward the optimal state in which all resources
are used efficiently. However, the evolution process is not without
interruptions: there are large fluctuations that occur but only intermittently
in time. The statistical distribution of the time between two successive
fluctuating events is found to depend on the parity of the evolution, i.e.,
whether the number of time steps in between is odd or even. We develop a
physical analysis and derive mean-field equations to gain an understanding of
these phenomena. As minority game dynamics and the phenomenon of herding are
common in social, economic, and political systems, and since AI is becoming
increasingly widespread, we expect our AI empowered minority game system to
have broad applications.
| physics.soc-ph | resource allocation systems provide the fundamental support for the normal functioning and well being of the modern society and can be modeled as minority games a ubiquitous dynamical phenomenon is the emergence of herding where a vast majority of the users concentrate on a small number of resources leading to a low efficiency in resource allocation to devise strategies to prevent herding is thus of high interest previous works focused on control strategies that rely on external interventions such as pinning control where a fraction of users are forced to choose a certain action is it possible to eliminate herding without any external control the main point of this paper is to provide an affirmative answer through exploiting artificial intelligence ai in particular we demonstrate that when agents are empowered with reinforced learning in that they get familiar with the unknown game environment gradually and attempt to deliver the optimal actions to maximize the payoff herding can effectively be eliminated computations reveal the striking phenomenon that regardless of the initial state the system evolves persistently and relentlessly toward the optimal state in which all resources are used efficiently however the evolution process is not without interruptions there are large fluctuations that occur but only intermittently in time the statistical distribution of the time between two successive fluctuating events is found to depend on the parity of the evolution ie whether the number of time steps in between is odd or even we develop a physical analysis and derive meanfield equations to gain an understanding of these phenomena as minority game dynamics and the phenomenon of herding are common in social economic and political systems and since ai is becoming increasingly widespread we expect our ai empowered minority game system to have broad applications | [['resource', 'allocation', 'systems', 'provide', 'the', 'fundamental', 'support', 'for', 'the', 'normal', 'functioning', 'and', 'well', 'being', 'of', 'the', 'modern', 'society', 'and', 'can', 'be', 'modeled', 'as', 'minority', 'games', 'a', 'ubiquitous', 'dynamical', 'phenomenon', 'is', 'the', 'emergence', 'of', 'herding', 'where', 'a', 'vast', 'majority', 'of', 'the', 'users', 'concentrate', 'on', 'a', 'small', 'number', 'of', 'resources', 'leading', 'to', 'a', 'low', 'efficiency', 'in', 'resource', 'allocation', 'to', 'devise', 'strategies', 'to', 'prevent', 'herding', 'is', 'thus', 'of', 'high', 'interest', 'previous', 'works', 'focused', 'on', 'control', 'strategies', 'that', 'rely', 'on', 'external', 'interventions', 'such', 'as', 'pinning', 'control', 'where', 'a', 'fraction', 'of', 'users', 'are', 'forced', 'to', 'choose', 'a', 'certain', 'action', 'is', 'it', 'possible', 'to', 'eliminate', 'herding', 'without', 'any', 'external', 'control', 'the', 'main', 'point', 'of', 'this', 'paper', 'is', 'to', 'provide', 'an', 'affirmative', 'answer', 'through', 'exploiting', 'artificial', 'intelligence', 'ai', 'in', 'particular', 'we', 'demonstrate', 'that', 'when', 'agents', 'are', 'empowered', 'with', 'reinforced', 'learning', 'in', 'that', 'they', 'get', 'familiar', 'with', 'the', 'unknown', 'game', 'environment', 'gradually', 'and', 'attempt', 'to', 'deliver', 'the', 'optimal', 'actions', 'to', 'maximize', 'the', 'payoff', 'herding', 'can', 'effectively', 'be', 'eliminated', 'computations', 'reveal', 'the', 'striking', 'phenomenon', 'that', 'regardless', 'of', 'the', 'initial', 'state', 'the', 'system', 'evolves', 'persistently', 'and', 'relentlessly', 'toward', 'the', 'optimal', 'state', 'in', 'which', 'all', 'resources', 'are', 'used', 'efficiently', 'however', 'the', 'evolution', 'process', 'is', 'not', 'without', 'interruptions', 'there', 'are', 'large', 'fluctuations', 'that', 'occur', 'but', 'only', 'intermittently', 'in', 'time', 'the', 'statistical', 'distribution', 'of', 'the', 'time', 'between', 'two', 'successive', 'fluctuating', 'events', 'is', 'found', 'to', 'depend', 'on', 'the', 'parity', 'of', 'the', 'evolution', 'ie', 'whether', 'the', 'number', 'of', 'time', 'steps', 'in', 'between', 'is', 'odd', 'or', 'even', 'we', 'develop', 'a', 'physical', 'analysis', 'and', 'derive', 'meanfield', 'equations', 'to', 'gain', 'an', 'understanding', 'of', 'these', 'phenomena', 'as', 'minority', 'game', 'dynamics', 'and', 'the', 'phenomenon', 'of', 'herding', 'are', 'common', 'in', 'social', 'economic', 'and', 'political', 'systems', 'and', 'since', 'ai', 'is', 'becoming', 'increasingly', 'widespread', 'we', 'expect', 'our', 'ai', 'empowered', 'minority', 'game', 'system', 'to', 'have', 'broad', 'applications']] | [-0.13447169356648858, 0.13338779464513842, -0.08803423238543114, 0.07629020331583926, -0.10194066948447827, -0.1734572577519889, 0.09046780780067432, 0.38112291034291984, -0.27463063461556647, -0.3322459406095458, 0.11145404027894126, -0.2550920331723505, -0.17413269457011563, 0.14963203319904644, -0.10625963539493814, -0.0029706474736892322, 0.026678988980224718, 0.050386825481663323, 0.04575222486184287, -0.2723097290845265, 0.3157794255297035, 0.045876960184980574, 0.2926870392581429, 0.028952980291657784, 0.07972231115015468, -0.0053205070691342135, -0.005368430054795836, 0.020307288691580275, -0.05519376537560842, 0.08014479728332966, 0.3164333981476127, 0.16350382878588124, 0.38138732555681526, -0.454212934376335, -0.2092269558805985, 0.13403825496510943, 0.16044318971205057, 0.11643593841901449, -0.03820428281304118, -0.2606887850122139, 0.0769680659525071, -0.17101356613214538, -0.10277717129355964, -0.09278896282730567, 0.022257982162002206, 0.048070086953556, -0.2671895512799278, 0.01928300487271704, 0.05200129591153836, 0.06622175821707085, -0.046165365214799706, -0.08732967623573037, -0.015250787122648705, 0.20417493403255113, 0.05775921163307796, -0.005445950874365841, 0.15706331226317655, -0.17045440818914195, -0.15064501083128587, 0.3981184868663295, 0.0018031461018935455, -0.17779432833811576, 0.21631400687890223, -0.11326155378626272, -0.11471593072288272, 0.11227174601342796, 0.20976411120768607, 0.08626913518780753, -0.13190348096591786, 0.01022146634668916, -0.01820457041416152, 0.18614164669451672, 0.016072875961944233, 0.055226539128138956, 0.20561926119401416, 0.177811287542163, 0.1128088629025006, 0.09989542354123966, -0.006629530601870943, -0.17609826872008455, -0.2263280546019305, -0.12446411938721207, -0.16553296728429953, 0.07167383976271352, -0.053530553803594824, -0.16304195403842947, 0.33386099323512725, 0.19338811895374602, 0.17129341647690066, 0.03845708455243577, 0.2878445451475248, 0.11877122567589124, 0.05178256905017859, 0.08914913567924974, 0.2187229158601536, 0.03614846815942364, 0.1315173626130005, -0.2244922370465517, 0.14018409910129856, -0.020296272249183532] |
1,802.03752 | Supervised classification of Dermatological diseases by Deep learning | This paper introduces a deep-learning based efficient classifier for common
dermatological conditions, aimed at people without easy access to skin
specialists. We report approximately 80% accuracy, in a situation where primary
care doctors have attained 57% success rate, according to recent literature.
The rationale of its design is centered on deploying and updating it on
handheld devices in near future. Dermatological diseases are common in every
population and have a wide spectrum in severity. With a shortage of
dermatological expertise being observed in several countries, machine learning
solutions can augment medical services and advise regarding existence of common
diseases. The paper implements supervised classification of nine distinct
conditions which have high occurrence in East Asian countries. Our current
attempt establishes that deep learning based techniques are viable avenues for
preliminary information to aid patients.
| stat.ML cs.CV cs.LG | this paper introduces a deeplearning based efficient classifier for common dermatological conditions aimed at people without easy access to skin specialists we report approximately 80 accuracy in a situation where primary care doctors have attained 57 success rate according to recent literature the rationale of its design is centered on deploying and updating it on handheld devices in near future dermatological diseases are common in every population and have a wide spectrum in severity with a shortage of dermatological expertise being observed in several countries machine learning solutions can augment medical services and advise regarding existence of common diseases the paper implements supervised classification of nine distinct conditions which have high occurrence in east asian countries our current attempt establishes that deep learning based techniques are viable avenues for preliminary information to aid patients | [['this', 'paper', 'introduces', 'a', 'deeplearning', 'based', 'efficient', 'classifier', 'for', 'common', 'dermatological', 'conditions', 'aimed', 'at', 'people', 'without', 'easy', 'access', 'to', 'skin', 'specialists', 'we', 'report', 'approximately', '80', 'accuracy', 'in', 'a', 'situation', 'where', 'primary', 'care', 'doctors', 'have', 'attained', '57', 'success', 'rate', 'according', 'to', 'recent', 'literature', 'the', 'rationale', 'of', 'its', 'design', 'is', 'centered', 'on', 'deploying', 'and', 'updating', 'it', 'on', 'handheld', 'devices', 'in', 'near', 'future', 'dermatological', 'diseases', 'are', 'common', 'in', 'every', 'population', 'and', 'have', 'a', 'wide', 'spectrum', 'in', 'severity', 'with', 'a', 'shortage', 'of', 'dermatological', 'expertise', 'being', 'observed', 'in', 'several', 'countries', 'machine', 'learning', 'solutions', 'can', 'augment', 'medical', 'services', 'and', 'advise', 'regarding', 'existence', 'of', 'common', 'diseases', 'the', 'paper', 'implements', 'supervised', 'classification', 'of', 'nine', 'distinct', 'conditions', 'which', 'have', 'high', 'occurrence', 'in', 'east', 'asian', 'countries', 'our', 'current', 'attempt', 'establishes', 'that', 'deep', 'learning', 'based', 'techniques', 'are', 'viable', 'avenues', 'for', 'preliminary', 'information', 'to', 'aid', 'patients']] | [-0.07663342945230778, 0.03148483578289456, -0.04690078166904234, 0.05679563994505512, -0.14298991822470813, -0.1986869506489263, 0.10488766757771373, 0.42905347387014486, -0.1757763389507986, -0.30232397160048025, 0.14375493742713233, -0.2932723408022812, -0.16290414075144746, 0.20750102232705103, -0.1815137598809522, 0.05040041495543738, 0.09606944557640758, 0.039113528595597885, -0.004536983412829464, -0.28927244184149514, 0.28236323358741267, 0.056600147018812025, 0.3707174552107619, 0.056002502548577845, 0.0656130810462828, -0.021197214773022083, -0.04395419914221544, -0.05958870914292308, -0.0834395777410328, 0.16807197705050236, 0.41398185038410906, 0.21698206032751433, 0.4116644480668787, -0.41032893029575884, -0.218645091439639, 0.0938249811974924, 0.15219866269643403, 0.06699047669500752, -0.07155469884407888, -0.2882513028235911, 0.08541104732969178, -0.19995280645732114, -0.12328312800553846, -0.07861102999313109, -0.0037910110662941502, 0.004953817954398135, -0.24603282138288243, 0.0611605477422031, -0.0286140614084955, 0.16164512994504576, -0.06397291236965823, -0.16250471144900727, 0.05733959184813577, 0.18564252537473647, 0.06333697094310965, 0.04163095696808409, 0.1352513499463276, -0.16579488117365973, -0.14826412922216217, 0.33110670892716343, 0.026105287820170287, -0.12872202565142912, 0.22835075853256953, -0.08447295549949423, -0.17743757633673055, 0.10682155792653533, 0.23902147909306656, 0.08370731401981772, -0.22185063218948112, -0.004860453833669507, 0.015436060254031153, 0.1261157002690971, 0.07918267033181028, -0.010757622555760083, 0.24301639563445723, 0.2570760270733553, 0.025087147044997885, 0.06999197699921901, -0.1113653476454262, -0.052909132590128194, -0.20042462307955886, -0.1122359947245846, -0.11084672033355863, 0.006492415526464804, -0.05032318893356558, -0.11224127980426941, 0.3837464894098577, 0.23121337973123499, 0.1279230692715787, 0.033339540695653425, 0.30492004636786324, -0.002291577844706767, 0.09894662400804904, 0.09283493506485846, 0.19277930392887194, 0.003993749264071682, 0.16551171697036765, -0.1382982770568316, 0.13804932662041305, -0.033241875007498395] |
1,802.03753 | Sample Efficient Deep Reinforcement Learning for Dialogue Systems with
Large Action Spaces | In spoken dialogue systems, we aim to deploy artificial intelligence to build
automated dialogue agents that can converse with humans. A part of this effort
is the policy optimisation task, which attempts to find a policy describing how
to respond to humans, in the form of a function taking the current state of the
dialogue and returning the response of the system. In this paper, we
investigate deep reinforcement learning approaches to solve this problem.
Particular attention is given to actor-critic methods, off-policy reinforcement
learning with experience replay, and various methods aimed at reducing the bias
and variance of estimators. When combined, these methods result in the
previously proposed ACER algorithm that gave competitive results in gaming
environments. These environments however are fully observable and have a
relatively small action set so in this paper we examine the application of ACER
to dialogue policy optimisation. We show that this method beats the current
state-of-the-art in deep learning approaches for spoken dialogue systems. This
not only leads to a more sample efficient algorithm that can train faster, but
also allows us to apply the algorithm in more difficult environments than
before. We thus experiment with learning in a very large action space, which
has two orders of magnitude more actions than previously considered. We find
that ACER trains significantly faster than the current state-of-the-art.
| cs.CL cs.AI cs.LG stat.ML | in spoken dialogue systems we aim to deploy artificial intelligence to build automated dialogue agents that can converse with humans a part of this effort is the policy optimisation task which attempts to find a policy describing how to respond to humans in the form of a function taking the current state of the dialogue and returning the response of the system in this paper we investigate deep reinforcement learning approaches to solve this problem particular attention is given to actorcritic methods offpolicy reinforcement learning with experience replay and various methods aimed at reducing the bias and variance of estimators when combined these methods result in the previously proposed acer algorithm that gave competitive results in gaming environments these environments however are fully observable and have a relatively small action set so in this paper we examine the application of acer to dialogue policy optimisation we show that this method beats the current stateoftheart in deep learning approaches for spoken dialogue systems this not only leads to a more sample efficient algorithm that can train faster but also allows us to apply the algorithm in more difficult environments than before we thus experiment with learning in a very large action space which has two orders of magnitude more actions than previously considered we find that acer trains significantly faster than the current stateoftheart | [['in', 'spoken', 'dialogue', 'systems', 'we', 'aim', 'to', 'deploy', 'artificial', 'intelligence', 'to', 'build', 'automated', 'dialogue', 'agents', 'that', 'can', 'converse', 'with', 'humans', 'a', 'part', 'of', 'this', 'effort', 'is', 'the', 'policy', 'optimisation', 'task', 'which', 'attempts', 'to', 'find', 'a', 'policy', 'describing', 'how', 'to', 'respond', 'to', 'humans', 'in', 'the', 'form', 'of', 'a', 'function', 'taking', 'the', 'current', 'state', 'of', 'the', 'dialogue', 'and', 'returning', 'the', 'response', 'of', 'the', 'system', 'in', 'this', 'paper', 'we', 'investigate', 'deep', 'reinforcement', 'learning', 'approaches', 'to', 'solve', 'this', 'problem', 'particular', 'attention', 'is', 'given', 'to', 'actorcritic', 'methods', 'offpolicy', 'reinforcement', 'learning', 'with', 'experience', 'replay', 'and', 'various', 'methods', 'aimed', 'at', 'reducing', 'the', 'bias', 'and', 'variance', 'of', 'estimators', 'when', 'combined', 'these', 'methods', 'result', 'in', 'the', 'previously', 'proposed', 'acer', 'algorithm', 'that', 'gave', 'competitive', 'results', 'in', 'gaming', 'environments', 'these', 'environments', 'however', 'are', 'fully', 'observable', 'and', 'have', 'a', 'relatively', 'small', 'action', 'set', 'so', 'in', 'this', 'paper', 'we', 'examine', 'the', 'application', 'of', 'acer', 'to', 'dialogue', 'policy', 'optimisation', 'we', 'show', 'that', 'this', 'method', 'beats', 'the', 'current', 'stateoftheart', 'in', 'deep', 'learning', 'approaches', 'for', 'spoken', 'dialogue', 'systems', 'this', 'not', 'only', 'leads', 'to', 'a', 'more', 'sample', 'efficient', 'algorithm', 'that', 'can', 'train', 'faster', 'but', 'also', 'allows', 'us', 'to', 'apply', 'the', 'algorithm', 'in', 'more', 'difficult', 'environments', 'than', 'before', 'we', 'thus', 'experiment', 'with', 'learning', 'in', 'a', 'very', 'large', 'action', 'space', 'which', 'has', 'two', 'orders', 'of', 'magnitude', 'more', 'actions', 'than', 'previously', 'considered', 'we', 'find', 'that', 'acer', 'trains', 'significantly', 'faster', 'than', 'the', 'current', 'stateoftheart']] | [-0.05415300577158534, 0.041375264038870554, -0.09907710740150624, 0.08006396774837388, -0.12733348501603967, -0.1518305188771588, 0.06171533500988688, 0.46430765724669926, -0.23569889565420257, -0.33764359814578443, 0.06569310964550823, -0.23864348716476583, -0.2042785635752595, 0.21346892268217332, -0.13823300805527533, 0.0531157589008021, 0.0982953417271526, 0.045336946616400316, -0.04786861492968227, -0.31700779314699995, 0.2949458423390099, 0.040147855566478347, 0.3048800304594696, -0.009829573145328348, 0.12064191474080203, -0.05437139148047119, 0.007213958682108152, 0.004336477785487137, -0.06895850065158134, 0.15709012068365388, 0.36383908260780734, 0.19016521801386915, 0.3819452017011129, -0.4225906658239468, -0.17736745535734322, 0.1306276524840382, 0.16219588725790046, 0.1535335049031077, -0.026030042661798203, -0.309260516423281, 0.0755430080921644, -0.21324501095878404, -0.016580326910727895, -0.13268070432854473, 0.0007394643441978591, -0.03670600712672085, -0.27531765075818104, -0.008579936257648102, 0.09047328342575028, 0.017320790517456087, -0.06809029527527442, -0.09967481856069406, 0.08154313041016276, 0.14924627736029675, 0.06915724901492903, 0.08577993662919298, 0.139263094194555, -0.1900053714650512, -0.15383693226091064, 0.34576755948364735, -0.07226604028940858, -0.1921604799916926, 0.24232740738928202, -0.081690389512633, -0.14658050618923765, 0.09411887416716314, 0.2505607739834307, 0.15267688093389564, -0.17097683437305633, 0.007910644699247227, -0.028570489928694317, 0.18067549641198175, 0.008740581688732159, -0.029165277347352872, 0.13778325039246056, 0.24346452622022896, 0.10456044240771153, 0.12383203896602006, -0.035671747865932135, -0.1150803795144914, -0.16429740152501338, -0.11380754660652123, -0.13497003331371152, 0.00404971789036441, -0.02698114021726145, -0.13140532968674407, 0.35833893721555715, 0.3001702446636698, 0.17624801156766745, 0.12767473173185748, 0.360679840944674, 0.07468553592776932, 0.10357717141814973, 0.11352167701355971, 0.2217715827480894, 0.00032061864538410586, 0.15616802821528886, -0.21162758661212708, 0.10943208127428732, 0.03730034864937778] |
1,802.03754 | Partial immunization of trees | For a graph $G$ and an integer-valued function $\tau$ on its vertex set, a
dynamic monopoly is a set of vertices of $G$ such that iteratively adding to it
vertices $u$ of $G$ that have at least $\tau(u)$ neighbors in it eventually
yields the vertex set of $G$. We study the problem of maximizing the minimum
order of a dynamic monopoly by increasing the threshold values of individual
vertices subject to vertex-dependent lower and upper bounds, and fixing the
total increase. We solve this problem efficiently for trees, which extends a
result of Khoshkhah and Zaker (On the largest dynamic monopolies of graphs with
a given average threshold, Canadian Mathematical Bulletin 58 (2015) 306-316).
| math.CO | for a graph g and an integervalued function tau on its vertex set a dynamic monopoly is a set of vertices of g such that iteratively adding to it vertices u of g that have at least tauu neighbors in it eventually yields the vertex set of g we study the problem of maximizing the minimum order of a dynamic monopoly by increasing the threshold values of individual vertices subject to vertexdependent lower and upper bounds and fixing the total increase we solve this problem efficiently for trees which extends a result of khoshkhah and zaker on the largest dynamic monopolies of graphs with a given average threshold canadian mathematical bulletin 58 2015 306316 | [['for', 'a', 'graph', 'g', 'and', 'an', 'integervalued', 'function', 'tau', 'on', 'its', 'vertex', 'set', 'a', 'dynamic', 'monopoly', 'is', 'a', 'set', 'of', 'vertices', 'of', 'g', 'such', 'that', 'iteratively', 'adding', 'to', 'it', 'vertices', 'u', 'of', 'g', 'that', 'have', 'at', 'least', 'tauu', 'neighbors', 'in', 'it', 'eventually', 'yields', 'the', 'vertex', 'set', 'of', 'g', 'we', 'study', 'the', 'problem', 'of', 'maximizing', 'the', 'minimum', 'order', 'of', 'a', 'dynamic', 'monopoly', 'by', 'increasing', 'the', 'threshold', 'values', 'of', 'individual', 'vertices', 'subject', 'to', 'vertexdependent', 'lower', 'and', 'upper', 'bounds', 'and', 'fixing', 'the', 'total', 'increase', 'we', 'solve', 'this', 'problem', 'efficiently', 'for', 'trees', 'which', 'extends', 'a', 'result', 'of', 'khoshkhah', 'and', 'zaker', 'on', 'the', 'largest', 'dynamic', 'monopolies', 'of', 'graphs', 'with', 'a', 'given', 'average', 'threshold', 'canadian', 'mathematical', 'bulletin', '58', '2015', '306316']] | [-0.14415725066351728, 0.09691419366546299, -0.0281337250930232, 0.007215854695050029, -0.11106150539440883, -0.09808442992082722, 0.15574359316546638, 0.32789175862421255, -0.27803033885655104, -0.3716444209530564, 0.09007593040325183, -0.35657514588538186, -0.13332194720839594, 0.10074356591396101, -0.04533853133519491, 0.03737581077242597, 0.09795211047471107, 0.11545364422773993, 0.025026792060449585, -0.27968173269900864, 0.28157523538086665, 0.022502260995810635, 0.1755743772819269, 0.08430285397749226, 0.13970590619420684, 0.044603837997996595, 0.0024741235071675735, 0.09545521516990554, -0.16593564098330135, 0.08344679613239006, 0.2239269179036119, 0.176129142241972, 0.30784208585113826, -0.36552683102084443, -0.13557908231778457, 0.19388793353075245, 0.0640099736786372, 0.021945557648290856, 0.051979131329603294, -0.2079499999463961, 0.14780746628782032, -0.16152731839332496, -0.0827117390712505, 0.05392052505064655, 0.13542633975209953, 0.01086335653346871, -0.32120363238091404, -0.0033805644924139924, 0.06604648617134001, 0.031827292687979084, 0.006025614442412851, -0.17680852909295544, -0.06025897509519111, 0.1192313486517214, -0.03110481819834325, 0.12017453678984295, 0.07525527644650759, -0.14311990644237413, -0.12918139566239473, 0.34823872519841603, -0.050635300888176506, -0.14537160318797906, 0.12577405428463542, -0.1359714863503033, -0.14340983733098517, 0.12737737296501528, 0.20512946012958483, 0.16122744282757914, -0.14388644202771755, 0.10047358087146538, -0.10666048428597483, 0.10975928774086742, 0.09474451610868848, -0.006790134105579676, 0.13618427928671376, 0.16914938689368936, 0.20431697005112362, 0.1814344245604835, -0.00014121418290242955, 0.004422109024515291, -0.2961614492038886, -0.057308326810933986, -0.20230885277091115, 0.04677784827806324, -0.16448671155061723, -0.18049231292323317, 0.4229422122709923, 0.12347759164634857, 0.22839117286777175, 0.10965949187143328, 0.22081884874349778, 0.15352152122395965, 0.043938747685306145, 0.1526939652415479, 0.15652869641780853, 0.12828652893386042, -0.001487849867558694, -0.21551570775163537, 0.08815506313138784, 0.12325139185581524] |
1,802.03755 | Scattering of fermions in the Yukawa theory coupled to Unimodular
Gravity | We compute the lowest order gravitational UV divergent radiative corrections
to the S matrix element of the $fermion + fermion\rightarrow fermion + fermion$
scattering process in the massive Yukawa theory, coupled either to Unimodular
Gravity or to General Relativity. We show that both Unimodular Gravity and
General Relativity give rise to the same UV divergent contribution in
Dimensional Regularization. This is a nontrivial result, since in the classical
action of Unimodular Gravity coupled to the Yukawa theory, the graviton field
does not couple neither to the mass operator nor to the Yukawa operator. This
is unlike the General Relativity case. The agreement found points in the
direction that Unimodular Gravity and General Relativity give rise to the same
quantum theory when coupled to matter, as long as the Cosmological Constant
vanishes. Along the way we have come across another unexpected cancellation of
UV divergences for both Unimodular Gravity and General Relativity, resulting in
the UV finiteness of the one-loop and $\kappa g^2$ order of the vertex
involving two fermions and one graviton only.
| hep-th gr-qc | we compute the lowest order gravitational uv divergent radiative corrections to the s matrix element of the fermion fermionrightarrow fermion fermion scattering process in the massive yukawa theory coupled either to unimodular gravity or to general relativity we show that both unimodular gravity and general relativity give rise to the same uv divergent contribution in dimensional regularization this is a nontrivial result since in the classical action of unimodular gravity coupled to the yukawa theory the graviton field does not couple neither to the mass operator nor to the yukawa operator this is unlike the general relativity case the agreement found points in the direction that unimodular gravity and general relativity give rise to the same quantum theory when coupled to matter as long as the cosmological constant vanishes along the way we have come across another unexpected cancellation of uv divergences for both unimodular gravity and general relativity resulting in the uv finiteness of the oneloop and kappa g2 order of the vertex involving two fermions and one graviton only | [['we', 'compute', 'the', 'lowest', 'order', 'gravitational', 'uv', 'divergent', 'radiative', 'corrections', 'to', 'the', 's', 'matrix', 'element', 'of', 'the', 'fermion', 'fermionrightarrow', 'fermion', 'fermion', 'scattering', 'process', 'in', 'the', 'massive', 'yukawa', 'theory', 'coupled', 'either', 'to', 'unimodular', 'gravity', 'or', 'to', 'general', 'relativity', 'we', 'show', 'that', 'both', 'unimodular', 'gravity', 'and', 'general', 'relativity', 'give', 'rise', 'to', 'the', 'same', 'uv', 'divergent', 'contribution', 'in', 'dimensional', 'regularization', 'this', 'is', 'a', 'nontrivial', 'result', 'since', 'in', 'the', 'classical', 'action', 'of', 'unimodular', 'gravity', 'coupled', 'to', 'the', 'yukawa', 'theory', 'the', 'graviton', 'field', 'does', 'not', 'couple', 'neither', 'to', 'the', 'mass', 'operator', 'nor', 'to', 'the', 'yukawa', 'operator', 'this', 'is', 'unlike', 'the', 'general', 'relativity', 'case', 'the', 'agreement', 'found', 'points', 'in', 'the', 'direction', 'that', 'unimodular', 'gravity', 'and', 'general', 'relativity', 'give', 'rise', 'to', 'the', 'same', 'quantum', 'theory', 'when', 'coupled', 'to', 'matter', 'as', 'long', 'as', 'the', 'cosmological', 'constant', 'vanishes', 'along', 'the', 'way', 'we', 'have', 'come', 'across', 'another', 'unexpected', 'cancellation', 'of', 'uv', 'divergences', 'for', 'both', 'unimodular', 'gravity', 'and', 'general', 'relativity', 'resulting', 'in', 'the', 'uv', 'finiteness', 'of', 'the', 'oneloop', 'and', 'kappa', 'g2', 'order', 'of', 'the', 'vertex', 'involving', 'two', 'fermions', 'and', 'one', 'graviton', 'only']] | [-0.14148932024014785, 0.18131410180974533, -0.07129931917194934, 0.1317861033429461, -0.12330385941792937, -0.18743883320678245, -0.030988571722306967, 0.2945017332019394, -0.21534504138261956, -0.2576001321677776, 0.021751981798340293, -0.2845929381930653, -0.15572682274368538, 0.10659962363458951, -0.04773323656991124, -0.003226994206745397, 0.0050245691748226394, 0.09016873196096105, -0.10659548295661807, -0.28418043445357505, 0.34726346561082583, 0.04882711861830424, 0.18868334951317486, 0.07351409113308524, 0.07602237893049331, -0.006081119061940733, -0.02124717715607189, 0.016489271247102057, -0.10197415313972777, 0.0556305492967915, 0.20796306476216106, 0.027300670751206138, 0.18648896668318604, -0.4192621420301935, -0.22270622314775693, 0.10518473749158576, 0.11212939979398952, 0.1637419454041211, -0.04102109912508989, -0.23316753684570465, 0.03311197550912552, -0.16310338556821294, -0.16862889934358571, -0.033432480781886945, -0.020162937700447133, -0.15144088576712153, -0.27548595347907395, 0.08333371222662904, 0.01863633171271752, -0.028066677786409856, -0.020675095014602823, -0.07651058665120646, -0.038814594415838226, 0.08086092026222853, 0.15737190350927824, 0.0733562153586022, 0.08711678938227979, -0.14518545142786665, -0.09572450851692874, 0.4555268536814872, -0.14654640874291278, -0.20296002277994857, 0.19527232463416808, -0.22565234045991125, -0.1486686632311081, 0.1022046887288418, 0.11702001290121937, 0.14246800774502952, -0.14487843159218114, 0.21605446137426257, -0.015225444690269582, 0.11065024829962675, 0.11562410280765856, 0.06981996582433246, 0.2677052064141368, 0.02405918494469541, 0.05954692620811436, 0.05039159390417969, 0.006927672488724484, -0.12481977747041074, -0.40159497745335104, -0.13786887324360364, -0.13719677358098767, 0.09972065307768335, -0.1546575678343823, -0.2334952915826922, 0.3538032736410113, 0.14654243803541997, 0.09201892173629911, 0.09199380575086893, 0.25942559806931326, 0.13833686580559623, 0.11662341253695023, 0.051851752901668935, 0.30622092395856537, 0.19682014172045884, 0.06621040504477979, -0.2891539387048825, -0.1023279524709591, 0.13194744307547807] |
1,802.03756 | New Proposals of a Stress Measure in a Capital and its Robust Estimator | In this paper a novel approach for a measurement of stresses in a capital,
which induce the capital flows between economic systems, is proposed. The
proposals appeal to an apparatus offered by the statistical theory of shape. We
propose a stress functional basing on a concept of mean shape determined by
representative particles of a capital carrier. We also propose methods of
describing changes in an amount and a structure of stresses in a capital
appealing, among others, to a Bookstein's pair of thin plain spline
deformation, and a measure of a shape variability. We apply our approach to an
indirect verification of the hypothesis according to which a capital flow
between economic systems is related to an activity of an inner force related to
stresses in a capital. We indicate, that the stresses create a phenomenon
analogous to the heat, which may be interpreted in terms of a positive economic
external effect, which attracts a capital from environment of a system to the
system. For empirical studies we propose robust approach to estimate the stress
functional basing on the data depth concept. In the empirical research we use
data on five branch stock indexes from Warsaw Stock Exchange. The studied
period involves the financial crisis of 2007.
| q-fin.EC | in this paper a novel approach for a measurement of stresses in a capital which induce the capital flows between economic systems is proposed the proposals appeal to an apparatus offered by the statistical theory of shape we propose a stress functional basing on a concept of mean shape determined by representative particles of a capital carrier we also propose methods of describing changes in an amount and a structure of stresses in a capital appealing among others to a booksteins pair of thin plain spline deformation and a measure of a shape variability we apply our approach to an indirect verification of the hypothesis according to which a capital flow between economic systems is related to an activity of an inner force related to stresses in a capital we indicate that the stresses create a phenomenon analogous to the heat which may be interpreted in terms of a positive economic external effect which attracts a capital from environment of a system to the system for empirical studies we propose robust approach to estimate the stress functional basing on the data depth concept in the empirical research we use data on five branch stock indexes from warsaw stock exchange the studied period involves the financial crisis of 2007 | [['in', 'this', 'paper', 'a', 'novel', 'approach', 'for', 'a', 'measurement', 'of', 'stresses', 'in', 'a', 'capital', 'which', 'induce', 'the', 'capital', 'flows', 'between', 'economic', 'systems', 'is', 'proposed', 'the', 'proposals', 'appeal', 'to', 'an', 'apparatus', 'offered', 'by', 'the', 'statistical', 'theory', 'of', 'shape', 'we', 'propose', 'a', 'stress', 'functional', 'basing', 'on', 'a', 'concept', 'of', 'mean', 'shape', 'determined', 'by', 'representative', 'particles', 'of', 'a', 'capital', 'carrier', 'we', 'also', 'propose', 'methods', 'of', 'describing', 'changes', 'in', 'an', 'amount', 'and', 'a', 'structure', 'of', 'stresses', 'in', 'a', 'capital', 'appealing', 'among', 'others', 'to', 'a', 'booksteins', 'pair', 'of', 'thin', 'plain', 'spline', 'deformation', 'and', 'a', 'measure', 'of', 'a', 'shape', 'variability', 'we', 'apply', 'our', 'approach', 'to', 'an', 'indirect', 'verification', 'of', 'the', 'hypothesis', 'according', 'to', 'which', 'a', 'capital', 'flow', 'between', 'economic', 'systems', 'is', 'related', 'to', 'an', 'activity', 'of', 'an', 'inner', 'force', 'related', 'to', 'stresses', 'in', 'a', 'capital', 'we', 'indicate', 'that', 'the', 'stresses', 'create', 'a', 'phenomenon', 'analogous', 'to', 'the', 'heat', 'which', 'may', 'be', 'interpreted', 'in', 'terms', 'of', 'a', 'positive', 'economic', 'external', 'effect', 'which', 'attracts', 'a', 'capital', 'from', 'environment', 'of', 'a', 'system', 'to', 'the', 'system', 'for', 'empirical', 'studies', 'we', 'propose', 'robust', 'approach', 'to', 'estimate', 'the', 'stress', 'functional', 'basing', 'on', 'the', 'data', 'depth', 'concept', 'in', 'the', 'empirical', 'research', 'we', 'use', 'data', 'on', 'five', 'branch', 'stock', 'indexes', 'from', 'warsaw', 'stock', 'exchange', 'the', 'studied', 'period', 'involves', 'the', 'financial', 'crisis', 'of', '2007']] | [-0.09316486234277271, 0.061000301406827336, -0.1489615308003869, 0.061926093782581716, -0.047704011578661734, -0.056532840575159025, 0.08294059189850833, 0.3594491991083979, -0.27502924861281813, -0.29443671834398655, 0.08907896476507565, -0.2572624852547899, -0.17504594095106404, 0.19863378874966559, -0.13681533331375406, 0.023932295718684722, 0.017330852964812, 0.01520047346714902, -0.01094739327031741, -0.20145118894428915, 0.3114450339684578, 0.08127183457434398, 0.3266192564059157, 0.06604885226869191, 0.11429107850327512, -0.024617075185619907, -0.04038270064902375, 0.051363832983974275, -0.13552530615266153, 0.20540768715892813, 0.22428401532371478, 0.10620843758356673, 0.3591248829900242, -0.4523480861011335, -0.20797113022780506, 0.09445052605475511, 0.03911450333051959, 0.08184129312737948, -0.03040092309727671, -0.260409875979854, 0.01071473526439949, -0.233153334301379, -0.12124525790624681, -0.0760216399125197, 0.04980142965039985, -0.004320431419688723, -0.29832619585935927, 0.08563472400405354, 0.050593930987218295, 0.09251962369462534, -0.09856003137971252, -0.0655674967467155, -0.036691150167992945, 0.12314448493675122, 0.11263321349757233, -0.020639305705416066, 0.1673198346597489, -0.13330535928871717, -0.1325398314685745, 0.36419930738275463, -0.06462714854618849, -0.19245583092371185, 0.16360839044198322, -0.09729890602951248, -0.11401745373752094, 0.09358464361838817, 0.23659378105036663, 0.06119432975650554, -0.18236556907262033, 0.013351424137728767, -0.03470515073299552, 0.1852456678401292, 0.022094816961528166, -0.044166885343366775, 0.22466261314446387, 0.1901061339303851, 0.08328840572382482, 0.14914288084699823, -0.07749426201917231, -0.10149584130658476, -0.2838191724008912, -0.16978775358934334, -0.18381298756550835, 0.04086343677379, -0.08153626705609275, -0.1880328412446675, 0.4005602242735525, 0.16211639963155658, 0.18607908632642262, 0.02443994599780302, 0.26008693437015523, 0.084003128226653, 0.0738839064210857, 0.05964257149588191, 0.22684950579086022, 0.08751347299512242, 0.13994936210983197, -0.20245581461512596, 0.11368658225578458, 0.043260536103729826] |
1,802.03757 | Complementability and maximality in different contexts: ergodic theory,
Brownian and poly-adic filtrations | The notions of complementability and maximality were introduced in 1974 by
Ornstein and Weiss in the context of the automorphisms of a probability space,
in 2008 by Brossard and Leuridan in the context of the Brownian filtrations,
and in 2017 by Leuridan in the context of the poly-adic filtrations indexed by
the non-positive integers. We present here some striking analogies and also
some differences existing between these three contexts.
| math.PR | the notions of complementability and maximality were introduced in 1974 by ornstein and weiss in the context of the automorphisms of a probability space in 2008 by brossard and leuridan in the context of the brownian filtrations and in 2017 by leuridan in the context of the polyadic filtrations indexed by the nonpositive integers we present here some striking analogies and also some differences existing between these three contexts | [['the', 'notions', 'of', 'complementability', 'and', 'maximality', 'were', 'introduced', 'in', '1974', 'by', 'ornstein', 'and', 'weiss', 'in', 'the', 'context', 'of', 'the', 'automorphisms', 'of', 'a', 'probability', 'space', 'in', '2008', 'by', 'brossard', 'and', 'leuridan', 'in', 'the', 'context', 'of', 'the', 'brownian', 'filtrations', 'and', 'in', '2017', 'by', 'leuridan', 'in', 'the', 'context', 'of', 'the', 'polyadic', 'filtrations', 'indexed', 'by', 'the', 'nonpositive', 'integers', 'we', 'present', 'here', 'some', 'striking', 'analogies', 'and', 'also', 'some', 'differences', 'existing', 'between', 'these', 'three', 'contexts']] | [-0.06973619217222388, 0.1434541060871473, -0.06791558238028576, 0.07350290363485162, -0.012954400682991201, -0.03515914692825666, 0.040700952307264684, 0.329051643497113, -0.31867985833774914, -0.2934292429691237, 0.10723995933464418, -0.26639481449048175, -0.20759822527179495, 0.17972067870538344, -0.18592751529208865, 0.021174633875489235, 0.008965030467758575, 0.007014952755222718, -0.06506984208174275, -0.29056433547344623, 0.3962318225566185, 0.029911190680595057, 0.19537184481283254, 0.04297620098981442, 0.08309249011058868, 0.005575245584953915, -0.11904978086805028, 0.05464900157257392, -0.18933736134292276, 0.14340258934041203, 0.25883136661441036, 0.10062492545694113, 0.2981929255254341, -0.3733634641394019, -0.17968158162848064, 0.1339486401499898, 0.044398023420592035, 0.005349797027354891, -0.029448716012253004, -0.36699689975516364, 0.04915296365365838, -0.1576707521894467, -0.04992561232806607, -0.06704049250534312, 0.08643380402954239, 0.06563624016460821, -0.19155228911249927, 0.07750829722278992, 0.15058287515333205, 0.14556138565989607, -0.06277589384240634, -0.11355377138225418, -0.0020871940139455328, 0.08325565068022997, 0.04957153607216297, -0.04743789402753905, 0.013100057988512244, -0.090784377679511, -0.21405412094441778, 0.3433421049972601, -0.08015355448040998, -0.19019640482623468, 0.16816478823734957, -0.17410688765459892, -0.17623683904071874, 0.03922805689261154, 0.08434088219126518, 0.09675854262472554, -0.10570122167524515, 0.18475976331198277, -0.09298170634517164, 0.011936546698438398, 0.16889901040121913, -0.0018172254503676386, 0.15498343366903788, 0.06008942308130138, 0.00033005991611968386, 0.1358903003997649, -0.017855117549047325, -0.11327911337668245, -0.31241454442285677, -0.19899305145284443, -0.12532323648250013, -0.0024018998286037736, -0.09039960772563725, -0.0870830868935269, 0.4089823327323591, 0.14713584218230663, 0.21403927173797097, 0.047257477728029094, 0.20292778911816917, 0.0398186042192251, -0.012717590441532207, 0.05061107870388889, 0.17881718545774647, 0.1951976716130351, 0.1115383922094197, -0.13558826223015785, 0.05478544414720752, 0.15437158722091804] |
1,802.03758 | Photoexcitation Cascade and Quantum-Relativistic Jets in Graphene | In Dirac materials linear band dispersion blocks momentum-conserving
interband transitions, creating a bottleneck for electron-hole pair production
and carrier multiplication in the photoexcitation cascade. Here we show that
the decays are unblocked and the bottleneck is relieved by subtle many-body
effects involving multiple off-shell e-h pairs. The decays result from a
collective behavior due to emission of many soft pairs. We discuss
characteristic signatures of the off-shell pathways, in particular the sharp
angular distribution of secondary carriers, resembling relativistic jets in
high-energy physics. The jets can be directly probed using solid-state
equivalent of particle detectors. Collinear scattering enhances carrier
multiplication, allowing for emission of as many as ${\sim}10$ secondary
carriers per single absorbed photon.
| cond-mat.mes-hall | in dirac materials linear band dispersion blocks momentumconserving interband transitions creating a bottleneck for electronhole pair production and carrier multiplication in the photoexcitation cascade here we show that the decays are unblocked and the bottleneck is relieved by subtle manybody effects involving multiple offshell eh pairs the decays result from a collective behavior due to emission of many soft pairs we discuss characteristic signatures of the offshell pathways in particular the sharp angular distribution of secondary carriers resembling relativistic jets in highenergy physics the jets can be directly probed using solidstate equivalent of particle detectors collinear scattering enhances carrier multiplication allowing for emission of as many as sim10 secondary carriers per single absorbed photon | [['in', 'dirac', 'materials', 'linear', 'band', 'dispersion', 'blocks', 'momentumconserving', 'interband', 'transitions', 'creating', 'a', 'bottleneck', 'for', 'electronhole', 'pair', 'production', 'and', 'carrier', 'multiplication', 'in', 'the', 'photoexcitation', 'cascade', 'here', 'we', 'show', 'that', 'the', 'decays', 'are', 'unblocked', 'and', 'the', 'bottleneck', 'is', 'relieved', 'by', 'subtle', 'manybody', 'effects', 'involving', 'multiple', 'offshell', 'eh', 'pairs', 'the', 'decays', 'result', 'from', 'a', 'collective', 'behavior', 'due', 'to', 'emission', 'of', 'many', 'soft', 'pairs', 'we', 'discuss', 'characteristic', 'signatures', 'of', 'the', 'offshell', 'pathways', 'in', 'particular', 'the', 'sharp', 'angular', 'distribution', 'of', 'secondary', 'carriers', 'resembling', 'relativistic', 'jets', 'in', 'highenergy', 'physics', 'the', 'jets', 'can', 'be', 'directly', 'probed', 'using', 'solidstate', 'equivalent', 'of', 'particle', 'detectors', 'collinear', 'scattering', 'enhances', 'carrier', 'multiplication', 'allowing', 'for', 'emission', 'of', 'as', 'many', 'as', 'sim10', 'secondary', 'carriers', 'per', 'single', 'absorbed', 'photon']] | [-0.14102265321273813, 0.28015285978714627, -0.039195132371867406, 0.12432121695121423, -0.03555740220186284, -0.16346985610659448, 0.030422229723179747, 0.3810513762985928, -0.31060363643132805, -0.2713095448919359, -0.08003968796937873, -0.3484525062476199, -0.07711109450381053, 0.18161470703310906, 0.06000376769276172, 0.028021464769712144, 0.04294682467323646, -0.08163416771659333, -0.04180338946293647, -0.11527488169897544, 0.297611829122169, 0.041746922550118415, 0.2534989950925177, 0.12457731298146475, 0.04432754651153166, 0.06986031615534764, 0.0071971093558730855, -0.06321834214440171, -0.038902867216070024, 0.05731722069577428, 0.2729381073017098, -0.005245774949639382, 0.17471952277379674, -0.435026368436714, -0.22291277370644375, 0.057936627846701366, 0.2339594935990151, 0.1152209951521894, -0.08701353618597384, -0.2532707161123031, 0.024488651365237802, -0.1827189905381059, -0.07942595248306661, -0.026866531808321412, -0.016162277664989233, -0.0024876293119680333, -0.2535319061328967, 0.12864052675043544, 0.029756520125247016, -0.014451610441156254, -0.02378518108825869, -0.08243214112110109, -0.06303137869231011, 0.050092900755994936, 0.06956981083892874, -0.006272284320833646, 0.24099233762459144, -0.16098991390154288, -0.17775446634837672, 0.38981177568386655, -0.04637019958330743, -0.09770023855053935, 0.20691071646778206, -0.18224318597155312, -0.10404117069444047, 0.27209036200094905, 0.16365835859783387, 0.1131029807464138, -0.16745693950603405, 0.04688573506019454, 0.018865375395602825, 0.12297147290021378, 0.09140705407123294, 0.18643308791184895, 0.26347823530893055, 0.14213302181911117, -0.008063942386989334, 0.11443737338975138, -0.13660448605578654, -0.04009683127719255, -0.3079958399027594, -0.1572087731624937, -0.19704283086435967, 0.0946065657200259, -0.04188720154828237, -0.12141489316586797, 0.39593127177080567, 0.08617834453144226, 0.20708004682194114, -0.037788344220372666, 0.28637432888264586, 0.14841421796294876, 0.07408673465793152, 0.05378567851087274, 0.25997616889480124, 0.1460094017246248, 0.08495360217874118, -0.27123381324283974, 0.032246905709861926, 0.03080507153808548] |
1,802.03759 | Multi-set Canonical Correlation Analysis simply explained | There are a multitude of methods to perform multi-set correlated component
analysis (MCCA), including some that require iterative solutions. The methods
differ on the criterion they optimize and the constraints placed on the
solutions. This note focuses perhaps on the simplest version, which can be
solved in a single step as the eigenvectors of matrix ${\bf D}^{-1} {\bf R}$.
Here ${\bf R}$ is the covariance matrix of the concatenated data, and ${\bf D}$
is its block-diagonal. This note shows that this solution maximizes inter-set
correlation (ISC) without further constraints. It also relates the solution to
a two step procedure, which first whitens each dataset using PCA, and then
performs an additional PCA on the concatenated and whitened data. Both these
solutions are known, although a clear derivation and simple implementation are
hard to find. This short note aims to remedy this.
| stat.ML | there are a multitude of methods to perform multiset correlated component analysis mcca including some that require iterative solutions the methods differ on the criterion they optimize and the constraints placed on the solutions this note focuses perhaps on the simplest version which can be solved in a single step as the eigenvectors of matrix bf d1 bf r here bf r is the covariance matrix of the concatenated data and bf d is its blockdiagonal this note shows that this solution maximizes interset correlation isc without further constraints it also relates the solution to a two step procedure which first whitens each dataset using pca and then performs an additional pca on the concatenated and whitened data both these solutions are known although a clear derivation and simple implementation are hard to find this short note aims to remedy this | [['there', 'are', 'a', 'multitude', 'of', 'methods', 'to', 'perform', 'multiset', 'correlated', 'component', 'analysis', 'mcca', 'including', 'some', 'that', 'require', 'iterative', 'solutions', 'the', 'methods', 'differ', 'on', 'the', 'criterion', 'they', 'optimize', 'and', 'the', 'constraints', 'placed', 'on', 'the', 'solutions', 'this', 'note', 'focuses', 'perhaps', 'on', 'the', 'simplest', 'version', 'which', 'can', 'be', 'solved', 'in', 'a', 'single', 'step', 'as', 'the', 'eigenvectors', 'of', 'matrix', 'bf', 'd1', 'bf', 'r', 'here', 'bf', 'r', 'is', 'the', 'covariance', 'matrix', 'of', 'the', 'concatenated', 'data', 'and', 'bf', 'd', 'is', 'its', 'blockdiagonal', 'this', 'note', 'shows', 'that', 'this', 'solution', 'maximizes', 'interset', 'correlation', 'isc', 'without', 'further', 'constraints', 'it', 'also', 'relates', 'the', 'solution', 'to', 'a', 'two', 'step', 'procedure', 'which', 'first', 'whitens', 'each', 'dataset', 'using', 'pca', 'and', 'then', 'performs', 'an', 'additional', 'pca', 'on', 'the', 'concatenated', 'and', 'whitened', 'data', 'both', 'these', 'solutions', 'are', 'known', 'although', 'a', 'clear', 'derivation', 'and', 'simple', 'implementation', 'are', 'hard', 'to', 'find', 'this', 'short', 'note', 'aims', 'to', 'remedy', 'this']] | [-0.12261836827197607, 0.002222815481553693, -0.09663788770847287, 0.04987030270994899, -0.09300264270302463, -0.18517511083863358, 0.03316576607898538, 0.390458211342388, -0.27782364296772294, -0.27534795812238666, 0.15062064307177084, -0.27463416877724495, -0.18374137474382493, 0.15272418985552821, -0.06792376003829194, 0.036942489243340385, 0.08823904571460282, 0.03794889359285804, -0.11381727927413947, -0.26160571146310563, 0.2747426464466761, 0.04802100142465693, 0.26327919488911455, 0.013192149384462453, 0.09386375151959153, 0.002744168723464435, -0.06389896948128304, -0.006630375201926164, -0.09859035596144568, 0.10453078472016276, 0.23814708150176872, 0.18684981240897525, 0.2567142193331152, -0.40603666167362784, -0.13752664792754338, 0.11101581952584154, 0.1609915230482658, 0.11046013625706909, 0.008236459682609701, -0.23009239058571715, 0.08355680629544963, -0.13003184896371994, -0.052234232950384284, -0.10482629982866876, 0.019123037474507346, -0.01739332721244993, -0.3148231691423249, 0.06729608437798568, 0.10516813885195987, 0.006026649203627033, -0.030313565778044047, -0.14127212942492032, 0.0246677426258036, 0.07114882665811807, 0.04734696787682936, 0.05882178540985556, 0.0840395531247218, -0.06027018499283239, -0.08331939785085711, 0.3691423750971279, -0.03674949874857057, -0.24018488465048743, 0.17313956218591647, -0.04965458386940948, -0.17592803963149586, 0.09123797746414834, 0.14791901833675009, 0.13616844350207888, -0.16674009658369823, 0.07950408565968685, -0.08079561089819416, 0.19104591447939265, 0.030466492684122097, 0.019297288737345673, 0.1588566553058988, 0.13191118244418598, 0.07808300918166308, 0.12308253574346899, -0.08667055525691479, -0.05029062810849319, -0.32432806055583324, -0.11742166792709671, -0.22774824924793438, 0.019934719267420152, -0.09133799223785358, -0.16255694800155593, 0.39904142569433504, 0.15787759827819806, 0.20538357934577667, 0.07004193720037898, 0.2777390371684434, 0.11010473194376875, 0.041766037754978697, 0.10853054554446052, 0.209830807491597, 0.10918216133516626, 0.07793541335837638, -0.1882721051501097, 0.043040439559159975, 0.06850967998946654] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.