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1,802.0966 | Computational Red Teaming in a Sudoku Solving Context: Neural Network
Based Skill Representation and Acquisition | In this paper we provide an insight into the skill representation, where
skill representation is seen as an essential part of the skill assessment stage
in the Computational Red Teaming process. Skill representation is demonstrated
in the context of Sudoku puzzle, for which the real human skills used in Sudoku
solving, along with their acquisition, are represented computationally in a
cognitively plausible manner, by using feed-forward neural networks with
back-propagation, and supervised learning. The neural network based skills are
then coupled with a hard-coded constraint propagation computational Sudoku
solver, in which the solving sequence is kept hard-coded, and the skills are
represented through neural networks. The paper demonstrates that the modified
solver can achieve different levels of proficiency, depending on the amount of
skills acquired through the neural networks. Results are encouraging for
developing more complex skill and skill acquisition models usable in general
frameworks related to the skill assessment aspect of Computational Red Teaming.
| cs.LG cs.NE | in this paper we provide an insight into the skill representation where skill representation is seen as an essential part of the skill assessment stage in the computational red teaming process skill representation is demonstrated in the context of sudoku puzzle for which the real human skills used in sudoku solving along with their acquisition are represented computationally in a cognitively plausible manner by using feedforward neural networks with backpropagation and supervised learning the neural network based skills are then coupled with a hardcoded constraint propagation computational sudoku solver in which the solving sequence is kept hardcoded and the skills are represented through neural networks the paper demonstrates that the modified solver can achieve different levels of proficiency depending on the amount of skills acquired through the neural networks results are encouraging for developing more complex skill and skill acquisition models usable in general frameworks related to the skill assessment aspect of computational red teaming | [['in', 'this', 'paper', 'we', 'provide', 'an', 'insight', 'into', 'the', 'skill', 'representation', 'where', 'skill', 'representation', 'is', 'seen', 'as', 'an', 'essential', 'part', 'of', 'the', 'skill', 'assessment', 'stage', 'in', 'the', 'computational', 'red', 'teaming', 'process', 'skill', 'representation', 'is', 'demonstrated', 'in', 'the', 'context', 'of', 'sudoku', 'puzzle', 'for', 'which', 'the', 'real', 'human', 'skills', 'used', 'in', 'sudoku', 'solving', 'along', 'with', 'their', 'acquisition', 'are', 'represented', 'computationally', 'in', 'a', 'cognitively', 'plausible', 'manner', 'by', 'using', 'feedforward', 'neural', 'networks', 'with', 'backpropagation', 'and', 'supervised', 'learning', 'the', 'neural', 'network', 'based', 'skills', 'are', 'then', 'coupled', 'with', 'a', 'hardcoded', 'constraint', 'propagation', 'computational', 'sudoku', 'solver', 'in', 'which', 'the', 'solving', 'sequence', 'is', 'kept', 'hardcoded', 'and', 'the', 'skills', 'are', 'represented', 'through', 'neural', 'networks', 'the', 'paper', 'demonstrates', 'that', 'the', 'modified', 'solver', 'can', 'achieve', 'different', 'levels', 'of', 'proficiency', 'depending', 'on', 'the', 'amount', 'of', 'skills', 'acquired', 'through', 'the', 'neural', 'networks', 'results', 'are', 'encouraging', 'for', 'developing', 'more', 'complex', 'skill', 'and', 'skill', 'acquisition', 'models', 'usable', 'in', 'general', 'frameworks', 'related', 'to', 'the', 'skill', 'assessment', 'aspect', 'of', 'computational', 'red', 'teaming']] | [-0.01893076276812222, 0.06082239226577053, -0.0788627776617725, 0.06106883115328768, -0.13675612123202413, -0.1834485156942279, 0.004482746186606106, 0.44916320440149116, -0.25161771321849474, -0.37952264380911666, 0.06205868669710452, -0.21564276146311914, -0.24938463346672154, 0.19420672947120282, -0.14037486664470164, 0.0558410135135355, 0.15330843044625175, 0.04975797228624053, -0.026404656528780657, -0.27558157648891213, 0.2631623927804251, 0.04096781050846461, 0.2896661033703675, 0.005030883671415429, 0.1300417706430439, -0.057821641347160745, -0.015203938276634642, -0.022671002462776677, -0.0015127999875638183, 0.19352170205224425, 0.3741015736549959, 0.24808181172477142, 0.3839294671832073, -0.4795126321695505, -0.1820750621906031, 0.07548406581514545, 0.1860060373381261, 0.05530842871164843, -0.026655188623173613, -0.3216423038152918, 0.04874726449469886, -0.14210618151156532, -0.018099521536139713, -0.12526489259795315, -0.04801733092434945, -0.03829541340950997, -0.27951740931959884, 0.005898768930966335, 0.04907143921028041, 0.13152163952228524, -0.02774243807840732, -0.14618143682563378, 0.014740083883366277, 0.20502737924877193, 0.021363913247384313, 0.036216969487647854, 0.11046977785956716, -0.22840250247578708, -0.1396744919249848, 0.3714294016601578, -0.009545724808929427, -0.2597267458455697, 0.16460466941240273, -0.015202616692723466, -0.147957584586355, 0.08686174530265553, 0.2345231713246434, 0.10240070232220234, -0.16398910319793128, -0.010996908635546964, 0.014765057027820617, 0.2040031242364597, 0.03592412761983371, -0.049369976419257, 0.19192177489279738, 0.30493692272613127, 0.016714629365672026, 0.12023390010900555, -0.026338583055222707, -0.12007598851867501, -0.20882928790975241, -0.12518625880606593, -0.1743799427118633, -0.02019727162325815, -0.08484430520376567, -0.1570773841332524, 0.3969896627770316, 0.1581556650329261, 0.15404024117611229, 0.1373916879671836, 0.3503623046701954, 0.10967378181840984, 0.08575013734310144, 0.07774124794279134, 0.16651081998622225, 0.05774879492969522, 0.18304672458419396, -0.18363038629533784, 0.13864493488874888, 0.06741233206233911] |
1,802.09661 | Cloth Manipulation Using Random-Forest-Based Imitation Learning | We present a novel approach for robust manipulation of high-DOF deformable
objects such as cloth. Our approach uses a random forest-based controller that
maps the observed visual features of the cloth to an optimal control action of
the manipulator. The topological structure of this random forest-based
controller is determined automatically based on the training data consisting
visual features and optimal control actions. This enables us to integrate the
overall process of training data classification and controller optimization
into an imitation learning (IL) approach. Our approach enables learning of
robust control policy for cloth manipulation with guarantees on convergence.We
have evaluated our approach on different multi-task cloth manipulation
benchmarks such as flattening, folding and twisting. In practice, our approach
works well with different deformable features learned based on the specific
task or deep learning. Moreover, our controller outperforms a simple or
piecewise linear controller in terms of robustness to noise. In addition, our
approach is easy to implement and does not require much parameter tuning.
| cs.RO | we present a novel approach for robust manipulation of highdof deformable objects such as cloth our approach uses a random forestbased controller that maps the observed visual features of the cloth to an optimal control action of the manipulator the topological structure of this random forestbased controller is determined automatically based on the training data consisting visual features and optimal control actions this enables us to integrate the overall process of training data classification and controller optimization into an imitation learning il approach our approach enables learning of robust control policy for cloth manipulation with guarantees on convergencewe have evaluated our approach on different multitask cloth manipulation benchmarks such as flattening folding and twisting in practice our approach works well with different deformable features learned based on the specific task or deep learning moreover our controller outperforms a simple or piecewise linear controller in terms of robustness to noise in addition our approach is easy to implement and does not require much parameter tuning | [['we', 'present', 'a', 'novel', 'approach', 'for', 'robust', 'manipulation', 'of', 'highdof', 'deformable', 'objects', 'such', 'as', 'cloth', 'our', 'approach', 'uses', 'a', 'random', 'forestbased', 'controller', 'that', 'maps', 'the', 'observed', 'visual', 'features', 'of', 'the', 'cloth', 'to', 'an', 'optimal', 'control', 'action', 'of', 'the', 'manipulator', 'the', 'topological', 'structure', 'of', 'this', 'random', 'forestbased', 'controller', 'is', 'determined', 'automatically', 'based', 'on', 'the', 'training', 'data', 'consisting', 'visual', 'features', 'and', 'optimal', 'control', 'actions', 'this', 'enables', 'us', 'to', 'integrate', 'the', 'overall', 'process', 'of', 'training', 'data', 'classification', 'and', 'controller', 'optimization', 'into', 'an', 'imitation', 'learning', 'il', 'approach', 'our', 'approach', 'enables', 'learning', 'of', 'robust', 'control', 'policy', 'for', 'cloth', 'manipulation', 'with', 'guarantees', 'on', 'convergencewe', 'have', 'evaluated', 'our', 'approach', 'on', 'different', 'multitask', 'cloth', 'manipulation', 'benchmarks', 'such', 'as', 'flattening', 'folding', 'and', 'twisting', 'in', 'practice', 'our', 'approach', 'works', 'well', 'with', 'different', 'deformable', 'features', 'learned', 'based', 'on', 'the', 'specific', 'task', 'or', 'deep', 'learning', 'moreover', 'our', 'controller', 'outperforms', 'a', 'simple', 'or', 'piecewise', 'linear', 'controller', 'in', 'terms', 'of', 'robustness', 'to', 'noise', 'in', 'addition', 'our', 'approach', 'is', 'easy', 'to', 'implement', 'and', 'does', 'not', 'require', 'much', 'parameter', 'tuning']] | [-0.035533852829523614, -0.0053486558321243485, -0.1207656732223288, -0.006022446418476653, -0.16159376475754325, -0.2089500959499802, 0.047815591095449646, 0.47013429929416606, -0.26697338670720716, -0.3513748193948181, 0.06857787926489933, -0.20755266255636248, -0.235299142593935, 0.23884533101727076, -0.18844644736749994, 0.1331760108105244, 0.08632011240865303, 0.0035390396505319997, -0.040901500390316904, -0.2383302127209669, 0.2871327592357079, 0.01483917666118495, 0.3320875760322105, -0.014972605371127832, 0.20548671243020955, 0.03313431792258302, 0.008910945654515338, -0.02023872716832289, -0.050624789220384145, 0.1865887210755809, 0.2883862655501287, 0.16103692660451027, 0.3181140249512198, -0.3904485644692658, -0.20706206448718997, 0.041718492952912495, 0.12695492970174396, 0.11888892470681868, -0.05166086429684349, -0.33124356556889467, 0.08492345807708206, -0.16468345371583487, -0.011516993693961688, -0.19828325953545975, -0.059813003152883126, -0.01651290992126326, -0.3343458154479447, -0.0171651495563472, 0.10187233274622585, 0.0715696735641822, -0.10133322168775817, -0.07567275318094284, 0.0028313105037447318, 0.1817746421299372, -0.01080150258648095, 0.03246910755231154, 0.2243521953104464, -0.14034156047344848, -0.1772929985530423, 0.35722559866455433, -0.025733258773749865, -0.24290161735026103, 0.20838594377795064, 0.009356791567788717, -0.12273992030549954, 0.09920765196138913, 0.2479735996939836, 0.16706580729252357, -0.13807756956588146, 0.013746437103133306, -0.023726009268476483, 0.20692788893528327, -0.009689777332466622, -0.03979854669244789, 0.14004346026244083, 0.2820556220752787, 0.1068040664733439, 0.14080476399476818, -0.08997495801822265, -0.10127743834092573, -0.2543933914025868, -0.08539604478475689, -0.16842933800757115, -0.044883777045961214, -0.11537837765595242, -0.17298541084343305, 0.41162976752281005, 0.21629700435340143, 0.20594220960147083, 0.12500377110651253, 0.3804810601543704, 0.03096585769057731, 0.10892542218503777, 0.08181681487662146, 0.19613771213138578, 0.008172349175838239, 0.10043646271220563, -0.2525661953816339, 0.10227341732107377, 0.03021067369245764] |
1,802.09662 | Directional Statistics-based Deep Metric Learning for Image
Classification and Retrieval | Deep distance metric learning (DDML), which is proposed to learn image
similarity metrics in an end-to-end manner based on the convolution neural
network, has achieved encouraging results in many computer vision
tasks.$L2$-normalization in the embedding space has been used to improve the
performance of several DDML methods. However, the commonly used Euclidean
distance is no longer an accurate metric for $L2$-normalized embedding space,
i.e., a hyper-sphere. Another challenge of current DDML methods is that their
loss functions are usually based on rigid data formats, such as the triplet
tuple. Thus, an extra process is needed to prepare data in specific formats. In
addition, their losses are obtained from a limited number of samples, which
leads to a lack of the global view of the embedding space. In this paper, we
replace the Euclidean distance with the cosine similarity to better utilize the
$L2$-normalization, which is able to attenuate the curse of dimensionality.
More specifically, a novel loss function based on the von Mises-Fisher
distribution is proposed to learn a compact hyper-spherical embedding space.
Moreover, a new efficient learning algorithm is developed to better capture the
global structure of the embedding space. Experiments for both classification
and retrieval tasks on several standard datasets show that our method achieves
state-of-the-art performance with a simpler training procedure. Furthermore, we
demonstrate that, even with a small number of convolutional layers, our model
can still obtain significantly better classification performance than the
widely used softmax loss.
| cs.CV | deep distance metric learning ddml which is proposed to learn image similarity metrics in an endtoend manner based on the convolution neural network has achieved encouraging results in many computer vision tasksl2normalization in the embedding space has been used to improve the performance of several ddml methods however the commonly used euclidean distance is no longer an accurate metric for l2normalized embedding space ie a hypersphere another challenge of current ddml methods is that their loss functions are usually based on rigid data formats such as the triplet tuple thus an extra process is needed to prepare data in specific formats in addition their losses are obtained from a limited number of samples which leads to a lack of the global view of the embedding space in this paper we replace the euclidean distance with the cosine similarity to better utilize the l2normalization which is able to attenuate the curse of dimensionality more specifically a novel loss function based on the von misesfisher distribution is proposed to learn a compact hyperspherical embedding space moreover a new efficient learning algorithm is developed to better capture the global structure of the embedding space experiments for both classification and retrieval tasks on several standard datasets show that our method achieves stateoftheart performance with a simpler training procedure furthermore we demonstrate that even with a small number of convolutional layers our model can still obtain significantly better classification performance than the widely used softmax loss | [['deep', 'distance', 'metric', 'learning', 'ddml', 'which', 'is', 'proposed', 'to', 'learn', 'image', 'similarity', 'metrics', 'in', 'an', 'endtoend', 'manner', 'based', 'on', 'the', 'convolution', 'neural', 'network', 'has', 'achieved', 'encouraging', 'results', 'in', 'many', 'computer', 'vision', 'tasksl2normalization', 'in', 'the', 'embedding', 'space', 'has', 'been', 'used', 'to', 'improve', 'the', 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1,802.09663 | Killing boundary data for anti-de Sitter-like spacetimes | Given an initial-boundary value problem for an anti-de Sitter-like spacetime,
we analyse conditions on the conformal boundary ensuring the existence of
Killing vectors in the spacetime arising from this problem. This analysis makes
use of a system of conformal wave equations describing the propagation of the
Killing equation first considered by Paetz. We identify an obstruction tensor
constructed from Killing vector candidate and the Cotton tensor of the
conformal boundary whose vanishing is a necessary condition for the existence
of Killing vectors in the spacetime. This obstruction tensor vanishes if the
conformal boundary is conformally flat.
| gr-qc | given an initialboundary value problem for an antide sitterlike spacetime we analyse conditions on the conformal boundary ensuring the existence of killing vectors in the spacetime arising from this problem this analysis makes use of a system of conformal wave equations describing the propagation of the killing equation first considered by paetz we identify an obstruction tensor constructed from killing vector candidate and the cotton tensor of the conformal boundary whose vanishing is a necessary condition for the existence of killing vectors in the spacetime this obstruction tensor vanishes if the conformal boundary is conformally flat | [['given', 'an', 'initialboundary', 'value', 'problem', 'for', 'an', 'antide', 'sitterlike', 'spacetime', 'we', 'analyse', 'conditions', 'on', 'the', 'conformal', 'boundary', 'ensuring', 'the', 'existence', 'of', 'killing', 'vectors', 'in', 'the', 'spacetime', 'arising', 'from', 'this', 'problem', 'this', 'analysis', 'makes', 'use', 'of', 'a', 'system', 'of', 'conformal', 'wave', 'equations', 'describing', 'the', 'propagation', 'of', 'the', 'killing', 'equation', 'first', 'considered', 'by', 'paetz', 'we', 'identify', 'an', 'obstruction', 'tensor', 'constructed', 'from', 'killing', 'vector', 'candidate', 'and', 'the', 'cotton', 'tensor', 'of', 'the', 'conformal', 'boundary', 'whose', 'vanishing', 'is', 'a', 'necessary', 'condition', 'for', 'the', 'existence', 'of', 'killing', 'vectors', 'in', 'the', 'spacetime', 'this', 'obstruction', 'tensor', 'vanishes', 'if', 'the', 'conformal', 'boundary', 'is', 'conformally', 'flat']] | [-0.2254685170482844, 0.11517238826415148, -0.05463246048990792, 0.018603942777796572, -0.15873081259148117, -0.11565951236722564, -0.1282290822576518, 0.2694370137905935, -0.24651607917621732, -0.16327872903760485, 0.14959592499387023, -0.24597068348278603, -0.18761676417974135, 0.0527985255199989, -0.03189698001369834, 0.08397437692231809, 0.010395889112260193, 0.1352281767006692, -0.12422779282496776, -0.22864397700565556, 0.4671179083622216, 0.019167630564576637, 0.320040041852432, 0.03296233152893061, 0.22393734070161977, 0.00241234010172775, 0.007735417030441265, -0.00875108093896415, -0.17230421397349951, 0.0696946682704341, 0.23123916133772582, 0.13057519963088757, 0.21822796156425284, -0.4204862905899063, -0.1860069281877562, 0.12451456648705062, 0.11910386625580334, 0.13881426797888707, -0.00717346996558869, -0.3431172671262175, 0.1062162912179095, -0.06456050796987256, -0.24176205118904667, -0.04910000730887987, -0.0016333350116231788, -0.13398182127275504, -0.2406025438879927, 0.13236840968602337, 0.07077173282353517, 0.039654683288669425, -0.23963834777775142, -0.02073368306082557, -0.09423553295831273, 0.07148463899890582, 0.12634307939879363, 0.02500510360308302, 0.06194104980386328, -0.15276397329337973, -0.09402033791169136, 0.33922974892387475, -0.08975119419968298, -0.35246204423553235, 0.08961998053321925, -0.10377183009010575, -0.10580140726233367, 0.10435941546650913, 0.1352392486781658, 0.21051435785193462, -0.1704180695329948, 0.1848688173431583, -0.059240543628978536, 0.0564665748582532, 0.14570468264476708, -0.05586691624678982, 0.22262289661254422, 0.07035229298344348, 0.1313349953464543, 0.1858824278897373, -0.004321947635617107, -0.07131550984922796, -0.48180892450424534, -0.221706123285306, -0.15795721444495334, 0.17381429087481592, -0.20798339126228407, -0.24710964780145636, 0.37024645691659924, 0.12158505514465408, 0.14257789624086095, 0.05146495199490649, 0.19721244807199886, 0.12037601591631149, 0.054399192663064845, 0.13244068829226308, 0.2524653121169346, 0.21697601663618116, 0.11858050614925257, -0.20195578841776296, -0.06636354242800735, 0.1701182391261682] |
1,802.09664 | Thermal tuning capabilities of semiconductor metasurface resonators | Metasurfaces exploit the ability to engineer the optical phase, amplitude and
polarization at subwavelength dimensions providing unprecedented control of
light. The realization of the all dielectric approach to metasurfaces has led
to the demonstration of extensive flat optical elements and functionalities
with low losses. However, to reach their ultimate potential, metasurfaces must
move beyond static operation and incorporate active tunability and
reconfigurable functions. The central challenge is achieving large tunability
in subwavelength resonator elements which require large optical effects in
response to external stimuli. Here we study the thermal tunability of
high-index silicon and germanium semiconductor resonators over a large
temperature range. We demonstrate thermal tuning of Mie resonances due to the
normal positive thermo-optic effect (dn/dT >0) over a wide infrared range. We
show that at higher temperatures and long wavelengths the sign of the
thermo-optic coefficient is reversed (dn/dT<0) culminating in a negative
induced index due to thermal excitation of free carriers. We also demonstrate
the tuning of high order Mie resonances by several linewidths with a
temperature swing of {\Delta}T<100K. Finally, we exploit the larger
thermo-optic coefficient at NIR wavelengths in Si metasurfaces to realize
optical switching and tunable metafilters.
| physics.optics | metasurfaces exploit the ability to engineer the optical phase amplitude and polarization at subwavelength dimensions providing unprecedented control of light the realization of the all dielectric approach to metasurfaces has led to the demonstration of extensive flat optical elements and functionalities with low losses however to reach their ultimate potential metasurfaces must move beyond static operation and incorporate active tunability and reconfigurable functions the central challenge is achieving large tunability in subwavelength resonator elements which require large optical effects in response to external stimuli here we study the thermal tunability of highindex silicon and germanium semiconductor resonators over a large temperature range we demonstrate thermal tuning of mie resonances due to the normal positive thermooptic effect dndt 0 over a wide infrared range we show that at higher temperatures and long wavelengths the sign of the thermooptic coefficient is reversed dndt0 culminating in a negative induced index due to thermal excitation of free carriers we also demonstrate the tuning of high order mie resonances by several linewidths with a temperature swing of deltat100k finally we exploit the larger thermooptic coefficient at nir wavelengths in si metasurfaces to realize optical switching and tunable metafilters | [['metasurfaces', 'exploit', 'the', 'ability', 'to', 'engineer', 'the', 'optical', 'phase', 'amplitude', 'and', 'polarization', 'at', 'subwavelength', 'dimensions', 'providing', 'unprecedented', 'control', 'of', 'light', 'the', 'realization', 'of', 'the', 'all', 'dielectric', 'approach', 'to', 'metasurfaces', 'has', 'led', 'to', 'the', 'demonstration', 'of', 'extensive', 'flat', 'optical', 'elements', 'and', 'functionalities', 'with', 'low', 'losses', 'however', 'to', 'reach', 'their', 'ultimate', 'potential', 'metasurfaces', 'must', 'move', 'beyond', 'static', 'operation', 'and', 'incorporate', 'active', 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1,802.09665 | Polynomial Treedepth Bounds in Linear Colorings | Low-treedepth colorings are an important tool for algorithms that exploit
structure in classes of bounded expansion; they guarantee subgraphs that use
few colors have bounded treedepth. These colorings have an implicit tradeoff
between the total number of colors used and the treedepth bound, and prior
empirical work suggests that the former dominates the run time of existing
algorithms in practice. We introduce $p$-linear colorings as an alternative to
the commonly used $p$-centered colorings. They can be efficiently computed in
bounded expansion classes and use at most as many colors as $p$-centered
colorings. Although a set of $k<p$ colors from a $p$-centered coloring induces
a subgraph of treedepth at most $k$, the same number of colors from a
$p$-linear coloring may induce subgraphs of larger treedepth. We establish a
polynomial upper bound on the treedepth in general graphs, and give tighter
bounds in trees and interval graphs via constructive coloring algorithms. We
also give a co-NP-completeness reduction for recognizing $p$-linear colorings
and discuss ways to overcome this limitation in practice. This preprint extends
results that appeared in [9]; for full proofs omitted from [9], see previous
versions of this preprint.
| cs.DS | lowtreedepth colorings are an important tool for algorithms that exploit structure in classes of bounded expansion they guarantee subgraphs that use few colors have bounded treedepth these colorings have an implicit tradeoff between the total number of colors used and the treedepth bound and prior empirical work suggests that the former dominates the run time of existing algorithms in practice we introduce plinear colorings as an alternative to the commonly used pcentered colorings they can be efficiently computed in bounded expansion classes and use at most as many colors as pcentered colorings although a set of kp colors from a pcentered coloring induces a subgraph of treedepth at most k the same number of colors from a plinear coloring may induce subgraphs of larger treedepth we establish a polynomial upper bound on the treedepth in general graphs and give tighter bounds in trees and interval graphs via constructive coloring algorithms we also give a conpcompleteness reduction for recognizing plinear colorings and discuss ways to overcome this limitation in practice this preprint extends results that appeared in 9 for full proofs omitted from 9 see previous versions of this preprint | [['lowtreedepth', 'colorings', 'are', 'an', 'important', 'tool', 'for', 'algorithms', 'that', 'exploit', 'structure', 'in', 'classes', 'of', 'bounded', 'expansion', 'they', 'guarantee', 'subgraphs', 'that', 'use', 'few', 'colors', 'have', 'bounded', 'treedepth', 'these', 'colorings', 'have', 'an', 'implicit', 'tradeoff', 'between', 'the', 'total', 'number', 'of', 'colors', 'used', 'and', 'the', 'treedepth', 'bound', 'and', 'prior', 'empirical', 'work', 'suggests', 'that', 'the', 'former', 'dominates', 'the', 'run', 'time', 'of', 'existing', 'algorithms', 'in', 'practice', 'we', 'introduce', 'plinear', 'colorings', 'as', 'an', 'alternative', 'to', 'the', 'commonly', 'used', 'pcentered', 'colorings', 'they', 'can', 'be', 'efficiently', 'computed', 'in', 'bounded', 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1,802.09666 | High-resolution Observations of Low-luminosity Gigahertz-Peaked Spectrum
and Compact Steep Spectrum Sources | We present Very Long Baseline Interferometry observations of a faint and
low-luminosity ($L_{\rm 1.4 GHz} < 10^{27}~\mbox{W Hz}^{-1}$) Gigahertz-Peaked
Spectrum (GPS) and Compact Steep Spectrum (CSS) sample. We select eight sources
from deep radio observations that have radio spectra characteristic of a GPS or
CSS source and an angular size of $\theta \lesssim 2$ arcsec, and detect six of
them with the Australian Long Baseline Array. We determine their linear sizes,
and model their radio spectra using Synchrotron Self Absorption (SSA) and Free
Free Absorption (FFA) models. We derive statistical model ages, based on a
fitted scaling relation, and spectral ages, based on the radio spectrum, which
are generally consistent with the hypothesis that GPS and CSS sources are young
and evolving. We resolve the morphology of one CSS source with a radio
luminosity of $10^{25}~\mbox{W Hz}^{-1}$, and find what appear to be two
hotspots spanning 1.7 kpc. We find that our sources follow the turnover-linear
size relation, and that both homogenous SSA and an inhomogeneous FFA model can
account for the spectra with observable turnovers. All but one of the FFA
models do not require a spectral break to account for the radio spectrum, while
all but one of the alternative SSA and power law models do require a spectral
break to account for the radio spectrum. We conclude that our low-luminosity
sample is similar to brighter samples in terms of their spectral shape,
turnover frequencies, linear sizes, and ages, but cannot test for a difference
in morphology.
| astro-ph.GA | we present very long baseline interferometry observations of a faint and lowluminosity l_rm 14 ghz 1027mboxw hz1 gigahertzpeaked spectrum gps and compact steep spectrum css sample we select eight sources from deep radio observations that have radio spectra characteristic of a gps or css source and an angular size of theta lesssim 2 arcsec and detect six of them with the australian long baseline array we determine their linear sizes and model their radio spectra using synchrotron self absorption ssa and free free absorption ffa models we derive statistical model ages based on a fitted scaling relation and spectral ages based on the radio spectrum which are generally consistent with the hypothesis that gps and css sources are young and evolving we resolve the morphology of one css source with a radio luminosity of 1025mboxw hz1 and find what appear to be two hotspots spanning 17 kpc we find that our sources follow the turnoverlinear size relation and that both homogenous ssa and an inhomogeneous ffa model can account for the spectra with observable turnovers all but one of the ffa models do not require a spectral break to account for the radio spectrum while all but one of the alternative ssa and power law models do require a spectral break to account for the radio spectrum we conclude that our lowluminosity sample is similar to brighter samples in terms of their spectral shape turnover frequencies linear sizes and ages but cannot test for a difference in morphology | [['we', 'present', 'very', 'long', 'baseline', 'interferometry', 'observations', 'of', 'a', 'faint', 'and', 'lowluminosity', 'l_rm', '14', 'ghz', '1027mboxw', 'hz1', 'gigahertzpeaked', 'spectrum', 'gps', 'and', 'compact', 'steep', 'spectrum', 'css', 'sample', 'we', 'select', 'eight', 'sources', 'from', 'deep', 'radio', 'observations', 'that', 'have', 'radio', 'spectra', 'characteristic', 'of', 'a', 'gps', 'or', 'css', 'source', 'and', 'an', 'angular', 'size', 'of', 'theta', 'lesssim', 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1,802.09667 | Sufficient variable screening via directional regression with censored
response | We in this paper propose a directional regression based approach for
ultrahigh dimensional sufficient variable screening with censored responses.
The new method is designed in a model-free manner and thus can be adapted to
various complex model structures. Under some commonly used assumptions, we show
that the proposed method enjoys the sure screening property when the dimension
p diverges at an exponential rate of the sample size n. To improve the marginal
screening method, the corresponding iterative screening algorithm and stability
screening algorithm are further equipped. We demonstrate the effectiveness of
the proposed method through simulation studies and a real data analysis.
| stat.ME | we in this paper propose a directional regression based approach for ultrahigh dimensional sufficient variable screening with censored responses the new method is designed in a modelfree manner and thus can be adapted to various complex model structures under some commonly used assumptions we show that the proposed method enjoys the sure screening property when the dimension p diverges at an exponential rate of the sample size n to improve the marginal screening method the corresponding iterative screening algorithm and stability screening algorithm are further equipped we demonstrate the effectiveness of the proposed method through simulation studies and a real data analysis | [['we', 'in', 'this', 'paper', 'propose', 'a', 'directional', 'regression', 'based', 'approach', 'for', 'ultrahigh', 'dimensional', 'sufficient', 'variable', 'screening', 'with', 'censored', 'responses', 'the', 'new', 'method', 'is', 'designed', 'in', 'a', 'modelfree', 'manner', 'and', 'thus', 'can', 'be', 'adapted', 'to', 'various', 'complex', 'model', 'structures', 'under', 'some', 'commonly', 'used', 'assumptions', 'we', 'show', 'that', 'the', 'proposed', 'method', 'enjoys', 'the', 'sure', 'screening', 'property', 'when', 'the', 'dimension', 'p', 'diverges', 'at', 'an', 'exponential', 'rate', 'of', 'the', 'sample', 'size', 'n', 'to', 'improve', 'the', 'marginal', 'screening', 'method', 'the', 'corresponding', 'iterative', 'screening', 'algorithm', 'and', 'stability', 'screening', 'algorithm', 'are', 'further', 'equipped', 'we', 'demonstrate', 'the', 'effectiveness', 'of', 'the', 'proposed', 'method', 'through', 'simulation', 'studies', 'and', 'a', 'real', 'data', 'analysis']] | [-0.040903199123967365, 0.0187704103233295, -0.130139447123214, 0.07596466034723848, -0.06875954363860336, -0.1656523773802773, 0.0531321403664062, 0.41492049834307504, -0.25592667720846685, -0.2824595456157683, 0.11139745525467921, -0.22913659185025037, -0.22509589364213467, 0.19243014710453138, -0.053556446488216225, 0.1181547795970212, 0.058338912391085546, 0.02509699076843247, -0.051457753740524984, -0.3121542658236827, 0.2850856276653597, 0.0731003283997815, 0.3766711530293904, 0.0421281508780678, 0.11542273628840442, 0.042314810080307665, -0.02253967822516821, 0.06588854235779568, -0.09739412786702993, 0.12037021893204428, 0.20853035111783766, 0.13376860844437033, 0.335989893322774, -0.3777338711783266, -0.19458654150366783, 0.11723265133104195, 0.1461808906238088, 0.09157843829370012, -0.06774703454335823, -0.27089025724140525, 0.1390043108030131, -0.1538900018135524, -0.1354770012857283, -0.1544295703152231, -0.0708832328239748, 0.008067544115999458, -0.39273790087477833, 0.079017603153582, 0.05438957105883781, 0.02111481735482812, -0.09429536005892955, -0.10332682934662729, 0.06435534514043954, 0.059562619992671074, 0.07261345951073785, -0.02173694918233463, 0.11942047881893814, -0.0557639478719662, -0.11920085961715884, 0.32635399365030665, -0.06752907993801523, -0.23196447782181934, 0.21812390026353373, -0.09370320801413161, -0.11194966800109137, 0.12411084263950732, 0.2321614908127516, 0.1674400414842382, -0.16258662877739613, 0.09500226934324019, -0.030351560941769506, 0.15221603654151528, 0.010607397958736721, 0.010852081979643189, 0.09844214103969873, 0.23237488341207305, 0.07543178465201374, 0.15520623539387265, -0.12478135849175719, -0.024630790843409214, -0.2950445070187105, -0.1425185346446347, -0.18073431649884464, -0.019695961795400316, -0.13759846042104948, -0.15853182591643988, 0.3711188773113285, 0.23762413915235311, 0.18302101525021533, 0.07988758437225923, 0.32584620262587477, 0.10100405966102913, 0.07856290193968544, 0.07175917523436867, 0.16001880795874077, 0.08294667499413823, 0.053472593139090085, -0.24808295650462456, 0.10795070000184591, 0.08255955572787892] |
1,802.09668 | Propagation of chaos for the Keller-Segel equation over bounded domains | In this paper we rigorously justify the propagation of chaos for the
parabolic-elliptic Keller-Segel equation over bounded convex domains. The
boundary condition under consideration is the no-flux condition. As
intermediate steps, we establish the well-posedness of the associated
stochastic equation as well as the well-posedness of the Keller-Segel equation
for bounded weak solutions.
| math.AP math.DS math.PR | in this paper we rigorously justify the propagation of chaos for the parabolicelliptic kellersegel equation over bounded convex domains the boundary condition under consideration is the noflux condition as intermediate steps we establish the wellposedness of the associated stochastic equation as well as the wellposedness of the kellersegel equation for bounded weak solutions | [['in', 'this', 'paper', 'we', 'rigorously', 'justify', 'the', 'propagation', 'of', 'chaos', 'for', 'the', 'parabolicelliptic', 'kellersegel', 'equation', 'over', 'bounded', 'convex', 'domains', 'the', 'boundary', 'condition', 'under', 'consideration', 'is', 'the', 'noflux', 'condition', 'as', 'intermediate', 'steps', 'we', 'establish', 'the', 'wellposedness', 'of', 'the', 'associated', 'stochastic', 'equation', 'as', 'well', 'as', 'the', 'wellposedness', 'of', 'the', 'kellersegel', 'equation', 'for', 'bounded', 'weak', 'solutions']] | [-0.17722842383708032, 0.04005430104597559, -0.041305229138090926, 0.09334781632389662, -0.07626012740832455, -0.1330170714349117, -0.021541902266073762, 0.21170430328204948, -0.36054418584384584, -0.15662057014217354, 0.2125082871292384, -0.25549615466613584, -0.12681370950523624, 0.12696235609363835, -0.07763069914653897, 0.17230087227873364, 0.06980949842353475, -0.00617483008723214, -0.04072232105119048, -0.21792441613550456, 0.3945274417517039, -0.111238735042653, 0.23275801028511575, 0.07102383389730745, 0.1880635565744256, -0.018873124497608758, 0.0992018891990466, -0.0035677793312747525, -0.24139481867259405, 0.014763182301495998, 0.22278070945363, 0.058118574619996095, 0.3488046760266682, -0.4684107322245836, -0.2762536139420743, 0.11895308859716609, 0.1820751961385436, 0.0984110969276923, -0.010782323074790667, -0.3542879339096681, 0.06943390316347468, -0.07555689381540946, -0.2870458525095908, 0.017960732310729206, -0.016930003105750623, 0.1325648356369644, -0.32457989707307994, 0.19449152744744183, 0.15562147287133518, 0.05120572275569979, -0.2773190355169991, -0.014052215181642546, -0.026468737617591925, 0.04374445356288046, 0.07948940998944894, -0.00773569052371214, -0.005651744873315658, -0.14883912201390936, -0.033665267118024374, 0.3562525579143526, -0.09879527003767918, -0.3424427004636459, 0.1757896290213432, -0.11637854219561461, -0.11455078586443977, 0.06321823412447043, 0.16756512822126443, 0.16090790467020474, -0.18011518591962192, 0.19848153065398055, -0.10581328874269395, 0.09929509590959774, 0.11596412512139892, 0.012872737586357683, -0.0277824711827737, 0.22128637739509907, 0.20992825645953417, 0.19034182519282936, 0.005042010464679169, -0.17718014655248174, -0.4253531274614188, -0.15133476078088554, -0.1498298817226347, 0.10521659785705917, -0.13207164187124878, -0.19563968992739353, 0.35337526038429645, 0.15514894258582368, 0.13354802388205844, 0.14610801422792785, 0.24367537778222337, 0.22050589429574824, -0.07257998256750826, 0.056312566333151653, 0.2064273939380106, 0.20620103686705302, 0.2220210655886715, -0.22841558267169124, 0.09706790168014057, 0.17583799446693552] |
1,802.09669 | A Multi-Disciplinary Review of Knowledge Acquisition Methods: From Human
to Autonomous Eliciting Agents | This paper offers a multi-disciplinary review of knowledge acquisition
methods in human activity systems. The review captures the degree of
involvement of various types of agencies in the knowledge acquisition process,
and proposes a classification with three categories of methods: the human
agent, the human-inspired agent, and the autonomous machine agent methods. In
the first two categories, the acquisition of knowledge is seen as a cognitive
task analysis exercise, while in the third category knowledge acquisition is
treated as an autonomous knowledge-discovery endeavour. The motivation for this
classification stems from the continuous change over time of the structure,
meaning and purpose of human activity systems, which are seen as the factor
that fuelled researchers' and practitioners' efforts in knowledge acquisition
for more than a century.
We show through this review that the KA field is increasingly active due to
the higher and higher pace of change in human activity, and conclude by
discussing the emergence of a fourth category of knowledge acquisition methods,
which are based on red-teaming and co-evolution.
| cs.AI | this paper offers a multidisciplinary review of knowledge acquisition methods in human activity systems the review captures the degree of involvement of various types of agencies in the knowledge acquisition process and proposes a classification with three categories of methods the human agent the humaninspired agent and the autonomous machine agent methods in the first two categories the acquisition of knowledge is seen as a cognitive task analysis exercise while in the third category knowledge acquisition is treated as an autonomous knowledgediscovery endeavour the motivation for this classification stems from the continuous change over time of the structure meaning and purpose of human activity systems which are seen as the factor that fuelled researchers and practitioners efforts in knowledge acquisition for more than a century we show through this review that the ka field is increasingly active due to the higher and higher pace of change in human activity and conclude by discussing the emergence of a fourth category of knowledge acquisition methods which are based on redteaming and coevolution | [['this', 'paper', 'offers', 'a', 'multidisciplinary', 'review', 'of', 'knowledge', 'acquisition', 'methods', 'in', 'human', 'activity', 'systems', 'the', 'review', 'captures', 'the', 'degree', 'of', 'involvement', 'of', 'various', 'types', 'of', 'agencies', 'in', 'the', 'knowledge', 'acquisition', 'process', 'and', 'proposes', 'a', 'classification', 'with', 'three', 'categories', 'of', 'methods', 'the', 'human', 'agent', 'the', 'humaninspired', 'agent', 'and', 'the', 'autonomous', 'machine', 'agent', 'methods', 'in', 'the', 'first', 'two', 'categories', 'the', 'acquisition', 'of', 'knowledge', 'is', 'seen', 'as', 'a', 'cognitive', 'task', 'analysis', 'exercise', 'while', 'in', 'the', 'third', 'category', 'knowledge', 'acquisition', 'is', 'treated', 'as', 'an', 'autonomous', 'knowledgediscovery', 'endeavour', 'the', 'motivation', 'for', 'this', 'classification', 'stems', 'from', 'the', 'continuous', 'change', 'over', 'time', 'of', 'the', 'structure', 'meaning', 'and', 'purpose', 'of', 'human', 'activity', 'systems', 'which', 'are', 'seen', 'as', 'the', 'factor', 'that', 'fuelled', 'researchers', 'and', 'practitioners', 'efforts', 'in', 'knowledge', 'acquisition', 'for', 'more', 'than', 'a', 'century', 'we', 'show', 'through', 'this', 'review', 'that', 'the', 'ka', 'field', 'is', 'increasingly', 'active', 'due', 'to', 'the', 'higher', 'and', 'higher', 'pace', 'of', 'change', 'in', 'human', 'activity', 'and', 'conclude', 'by', 'discussing', 'the', 'emergence', 'of', 'a', 'fourth', 'category', 'of', 'knowledge', 'acquisition', 'methods', 'which', 'are', 'based', 'on', 'redteaming', 'and', 'coevolution']] | [-0.07773355953603252, 0.03214895701767957, -0.048345317089808215, 0.03413087162478708, -0.10713415211510091, -0.10169302687669794, 0.02877742661387726, 0.38374221446879564, -0.24021227535836043, -0.34785204422881916, 0.12230963345168025, -0.2422995474535994, -0.18972972438981137, 0.19901712372666225, -0.13371839910923017, -0.019925430904896485, 0.07538550912535616, 0.09515069636316704, -0.04157057251515133, -0.2473193905939947, 0.3386118541294265, 0.036054568914031346, 0.31117812485899776, 0.0033939978373902185, 0.10531818473689436, 0.00042501408495895917, -0.10508208540600858, -0.038719576261688156, -0.057631167579442956, 0.20215457097427653, 0.3477487920317799, 0.22160883080713184, 0.37799310356300947, -0.4173944865552975, -0.2137666731751302, 0.06489859359239095, 0.13815721155316124, 0.09000192728195716, -0.03643389987190035, -0.30153686113633393, 0.038825240142787584, -0.22232742824841503, -0.06990805507077658, -0.06732872283707063, 0.03216924912010741, -0.011320310401234088, -0.22630987012754694, 0.013215909423750071, 0.10962311889133639, 0.15666199230777456, -0.11056845043813587, -0.08371446240648982, 0.02402581450310425, 0.21604349555092908, 0.08892269246955818, 0.046719134596752976, 0.16171128392895862, -0.2096653635671828, -0.18587472532886923, 0.39049151015379246, -0.01835099256701748, -0.15240386522020258, 0.21800847086983377, -0.12116163644047144, -0.15348141864662812, 0.11646538186774012, 0.1934040873754947, 0.0977326752313058, -0.18465444759966063, 0.03082521365147494, 0.03768770108442931, 0.17225604249480447, 0.018184430858430762, -0.004674936744517514, 0.20667543590423607, 0.2705384048056744, 0.046587580346524535, 0.07645148780873223, -0.04308049183011809, -0.09032744856917166, -0.24372804294606404, -0.164837058001597, -0.15510961379567606, 0.03613038259001249, -0.020461324684912966, -0.10818151547919981, 0.4035667193432649, 0.18156067074908475, 0.1600049595913983, 0.045472654360180186, 0.33891570794263054, 0.023555431561059475, 0.07834710486488239, 0.03884776459606309, 0.20094709332278443, 0.05365634456393309, 0.1796676408827937, -0.17292313908165807, 0.13234655397675288, 0.03116012257080348] |
1,802.0967 | Single-View Food Portion Estimation: Learning Image-to-Energy Mappings
Using Generative Adversarial Networks | Due to the growing concern of chronic diseases and other health problems
related to diet, there is a need to develop accurate methods to estimate an
individual's food and energy intake. Measuring accurate dietary intake is an
open research problem. In particular, accurate food portion estimation is
challenging since the process of food preparation and consumption impose large
variations on food shapes and appearances. In this paper, we present a food
portion estimation method to estimate food energy (kilocalories) from food
images using Generative Adversarial Networks (GAN). We introduce the concept of
an "energy distribution" for each food image. To train the GAN, we design a
food image dataset based on ground truth food labels and segmentation masks for
each food image as well as energy information associated with the food image.
Our goal is to learn the mapping of the food image to the food energy. We can
then estimate food energy based on the energy distribution. We show that an
average energy estimation error rate of 10.89% can be obtained by learning the
image-to-energy mapping.
| cs.CV | due to the growing concern of chronic diseases and other health problems related to diet there is a need to develop accurate methods to estimate an individuals food and energy intake measuring accurate dietary intake is an open research problem in particular accurate food portion estimation is challenging since the process of food preparation and consumption impose large variations on food shapes and appearances in this paper we present a food portion estimation method to estimate food energy kilocalories from food images using generative adversarial networks gan we introduce the concept of an energy distribution for each food image to train the gan we design a food image dataset based on ground truth food labels and segmentation masks for each food image as well as energy information associated with the food image our goal is to learn the mapping of the food image to the food energy we can then estimate food energy based on the energy distribution we show that an average energy estimation error rate of 1089 can be obtained by learning the imagetoenergy mapping | [['due', 'to', 'the', 'growing', 'concern', 'of', 'chronic', 'diseases', 'and', 'other', 'health', 'problems', 'related', 'to', 'diet', 'there', 'is', 'a', 'need', 'to', 'develop', 'accurate', 'methods', 'to', 'estimate', 'an', 'individuals', 'food', 'and', 'energy', 'intake', 'measuring', 'accurate', 'dietary', 'intake', 'is', 'an', 'open', 'research', 'problem', 'in', 'particular', 'accurate', 'food', 'portion', 'estimation', 'is', 'challenging', 'since', 'the', 'process', 'of', 'food', 'preparation', 'and', 'consumption', 'impose', 'large', 'variations', 'on', 'food', 'shapes', 'and', 'appearances', 'in', 'this', 'paper', 'we', 'present', 'a', 'food', 'portion', 'estimation', 'method', 'to', 'estimate', 'food', 'energy', 'kilocalories', 'from', 'food', 'images', 'using', 'generative', 'adversarial', 'networks', 'gan', 'we', 'introduce', 'the', 'concept', 'of', 'an', 'energy', 'distribution', 'for', 'each', 'food', 'image', 'to', 'train', 'the', 'gan', 'we', 'design', 'a', 'food', 'image', 'dataset', 'based', 'on', 'ground', 'truth', 'food', 'labels', 'and', 'segmentation', 'masks', 'for', 'each', 'food', 'image', 'as', 'well', 'as', 'energy', 'information', 'associated', 'with', 'the', 'food', 'image', 'our', 'goal', 'is', 'to', 'learn', 'the', 'mapping', 'of', 'the', 'food', 'image', 'to', 'the', 'food', 'energy', 'we', 'can', 'then', 'estimate', 'food', 'energy', 'based', 'on', 'the', 'energy', 'distribution', 'we', 'show', 'that', 'an', 'average', 'energy', 'estimation', 'error', 'rate', 'of', '1089', 'can', 'be', 'obtained', 'by', 'learning', 'the', 'imagetoenergy', 'mapping']] | [0.0046457569820008105, 0.041136129727653625, -0.03012020612933806, 0.12761846673979432, -0.08242283883105431, -0.12160580324541245, 0.04055409833190164, 0.4529439103561786, -0.2502630402453776, -0.35713688298527685, 0.13655511447760676, -0.30558830723166464, -0.1258029878907837, 0.1800143213197589, -0.20870327897902047, 0.05892026937965836, 0.1326133204145091, 0.05921727958401399, 0.04371144585976643, -0.2602473707217723, 0.299694566066776, 0.07535310110343355, 0.3724229875579476, 0.09503953225910663, 0.17932324156431215, -0.02141545003878751, -0.011493903771042823, -0.06606942197840128, -0.13566162752008365, 0.2219863035137366, 0.32876493125488715, 0.19085516985239728, 0.3434921234766287, -0.4076073611368026, -0.2134120459899506, 0.1824767152007137, 0.11125490152343576, 0.12172313122211822, -0.05900141859626663, -0.3083911160698959, 0.04685238349118403, -0.18082969691604375, -0.04726435384180929, -0.08436523867305368, -0.020752813078330032, 0.034408516766769544, -0.2710961542757494, 0.10209013096189924, -0.017914517123052583, 0.08623389519751072, -0.14692970282797302, -0.09536360826476344, -0.08533771029008286, 0.24377909710098591, 0.09052233879038665, 0.046235034532978066, 0.21106374726231608, -0.22762834846042096, -0.076193136244214, 0.3602292744017073, -0.015656933426590903, -0.20033893625152163, 0.13838651690831674, -0.014301404407513993, -0.14977946754811067, 0.13078210123415504, 0.23093676389860254, 0.058899269431297266, -0.1946939966348665, -0.04236243095681337, -0.016959474879716125, 0.21313333589783204, 0.037189467971080116, -0.060054844407298205, 0.17820212878819022, 0.24075294647764947, 0.12817766370085468, 0.17245543634219626, -0.1629388192552142, -0.03255158098148448, -0.16177077734576803, -0.1575957919834348, -0.1918422744077231, 0.03163451946739639, -0.08191631330667795, -0.18170757510940477, 0.42156586992953504, 0.2062641577755234, 0.17685229513528092, 0.07306189944701535, 0.32043255666536946, 0.018783543963384417, 0.056812024361320906, 0.03378430762128638, 0.1074537332355976, -0.023561791608642253, 0.12710664785600134, -0.15801333951763807, 0.14088279117830096, 0.040029463396806804] |
1,802.09671 | Energy Levels, Lifetimes and Transition rates for P-like ions from Cr X
to Zn XVI from large-scale Relativistic Multiconfiguration Calculations | The fully relativistic multiconfiguration Dirac--Hartree--Fock method is used
to compute excitation energies and lifetimes for the 143 lowest states of the
$3s^23p^3$, $3s3p^4$, $3s^23p^23d$, $3s3p^33d$, $3p^5$, $3s^23p3d^2$
configurations in P-like ions from Cr X to Zn XVI. Multipole (E1, M1, E2, M2)
transition rates, line strengths, oscillator strengths, and branching fractions
among these states are also given. Valence-valence and core-valence electron
correlation effects are systematically accounted for using large basis function
expansions. Computed excitation energies are compared with the NIST ASD and
CHIANTI compiled values and previous calculations. The mean average absolute
difference, removing obvious outliers, between computed and observed energies
for the 41 lowest identified levels in Fe XII is only 0.057 \%, implying that
the computed energies are accurate enough to aid identification of new emission
lines from the sun and other astrophysical sources. The amount of energy and
transition data of high accuracy is significantly increased for several P-like
ions of astrophysics interest, where experimental data are still very scarce.
| physics.atom-ph | the fully relativistic multiconfiguration dirachartreefock method is used to compute excitation energies and lifetimes for the 143 lowest states of the 3s23p3 3s3p4 3s23p23d 3s3p33d 3p5 3s23p3d2 configurations in plike ions from cr x to zn xvi multipole e1 m1 e2 m2 transition rates line strengths oscillator strengths and branching fractions among these states are also given valencevalence and corevalence electron correlation effects are systematically accounted for using large basis function expansions computed excitation energies are compared with the nist asd and chianti compiled values and previous calculations the mean average absolute difference removing obvious outliers between computed and observed energies for the 41 lowest identified levels in fe xii is only 0057 implying that the computed energies are accurate enough to aid identification of new emission lines from the sun and other astrophysical sources the amount of energy and transition data of high accuracy is significantly increased for several plike ions of astrophysics interest where experimental data are still very scarce | [['the', 'fully', 'relativistic', 'multiconfiguration', 'dirachartreefock', 'method', 'is', 'used', 'to', 'compute', 'excitation', 'energies', 'and', 'lifetimes', 'for', 'the', '143', 'lowest', 'states', 'of', 'the', '3s23p3', '3s3p4', '3s23p23d', '3s3p33d', '3p5', '3s23p3d2', 'configurations', 'in', 'plike', 'ions', 'from', 'cr', 'x', 'to', 'zn', 'xvi', 'multipole', 'e1', 'm1', 'e2', 'm2', 'transition', 'rates', 'line', 'strengths', 'oscillator', 'strengths', 'and', 'branching', 'fractions', 'among', 'these', 'states', 'are', 'also', 'given', 'valencevalence', 'and', 'corevalence', 'electron', 'correlation', 'effects', 'are', 'systematically', 'accounted', 'for', 'using', 'large', 'basis', 'function', 'expansions', 'computed', 'excitation', 'energies', 'are', 'compared', 'with', 'the', 'nist', 'asd', 'and', 'chianti', 'compiled', 'values', 'and', 'previous', 'calculations', 'the', 'mean', 'average', 'absolute', 'difference', 'removing', 'obvious', 'outliers', 'between', 'computed', 'and', 'observed', 'energies', 'for', 'the', '41', 'lowest', 'identified', 'levels', 'in', 'fe', 'xii', 'is', 'only', '0057', 'implying', 'that', 'the', 'computed', 'energies', 'are', 'accurate', 'enough', 'to', 'aid', 'identification', 'of', 'new', 'emission', 'lines', 'from', 'the', 'sun', 'and', 'other', 'astrophysical', 'sources', 'the', 'amount', 'of', 'energy', 'and', 'transition', 'data', 'of', 'high', 'accuracy', 'is', 'significantly', 'increased', 'for', 'several', 'plike', 'ions', 'of', 'astrophysics', 'interest', 'where', 'experimental', 'data', 'are', 'still', 'very', 'scarce']] | [-0.052072230268604934, 0.16645679748498474, 0.05012911098301455, 0.14176801746269202, 0.03862903943688721, -0.13077782486583206, 0.05832541754297248, 0.4315067170140375, -0.1525536140688001, -0.35209428441894663, -0.005564321898766289, -0.34110627480586814, 0.021522713450278945, 0.1904251790905051, 0.07724335625957532, 0.01551334945902367, 0.07302880972908561, -0.011461399104090253, -0.09122928552430384, -0.16316210756884372, 0.23989827826450086, 0.10318305206953719, 0.2735915500552032, 0.0729739181452674, 0.0137582977597489, -0.08296962673360612, -0.007666649314675741, -0.0042330600042489305, -0.09698139968541174, 0.12259885167612569, 0.3030259477813983, 0.05783806040372913, 0.18345788811707192, -0.3836365411900411, -0.17654625527749052, 0.06362106944404684, 0.14209381087125533, 0.12812958296483298, -0.0354578291676986, -0.2898387995171865, 0.04657901949575467, -0.16552968865414713, -0.10825739359589899, -0.0969101728035054, 0.086473647465004, 0.057293828925307676, -0.2817350170563218, 0.1130008341974036, -0.04973744593077238, 0.11077150610933832, -0.13575364834670522, -0.2621943579785004, -0.10005212732394979, 0.11373233751862481, 0.037149178675393676, 0.04522049252057276, 0.13622153699576, -0.07074886828566053, -0.06981280324706261, 0.39370428249358563, -0.05278575682573637, -0.10615968610498176, 0.17692901008720896, -0.19527069787245693, -0.15078705937859668, 0.2549251181601434, 0.11380248610226876, 0.10923030741281428, -0.11014477367317126, 0.049874925343794334, 0.07656277146095493, 0.18720265729263852, 0.06119296552945569, 0.058636982402479526, 0.15414038982693176, 0.03280483903274367, -0.03733635322149297, 0.04696727750335737, -0.18026157678549837, -0.06091506493123616, -0.254843730695255, -0.08845743303886795, -0.16895308132671935, 0.025580946066873562, -0.05143045488919968, -0.11204252721835224, 0.354860749297366, 0.11607776170560888, 0.19719451139117503, 0.0030046247381859334, 0.2519979117746661, 0.15265114537208893, 0.03169331726007116, 0.0804783670842695, 0.2934415384083037, 0.17656119840640788, 0.06604887037330372, -0.24884174761486946, 0.03464112132218604, 0.05023085240758125] |
1,802.09672 | Phenomenological approach to study the degree of the itinerancy of the
$5f$ electrons in actinide ferromagnets with spin fluctuation theory | Actinide compounds with 5f electrons have been attracting much attention
because of their interesting magnetic and electronic properties such as heavy
fermion state, unconventional superconductivity, co-existence of the
superconductivity and magnetism. Recently, we have reported a phenomenological
analysis on 80 actinide ferromagnets with the spin fluctuation theory
originally developed to explain the ferromagnetic properties of itinerant
ferromagnets in the 3d transition metals and their intermetallics (N. Tateiwa
et al., Phys. Rev. B 96, 035125 (2017)). Our study suggests the itinerancy of
the $5f$ electrons in most of the actinide ferromagnets and the applicability
of the spin fluctuation theory to actinide 5f system. In this paper, we present
a new analysis for the spin fluctuation parameter obtained with a different
theoretical formula not used in the reference. We also discuss the results of
the analysis from different points of views.
| cond-mat.str-el | actinide compounds with 5f electrons have been attracting much attention because of their interesting magnetic and electronic properties such as heavy fermion state unconventional superconductivity coexistence of the superconductivity and magnetism recently we have reported a phenomenological analysis on 80 actinide ferromagnets with the spin fluctuation theory originally developed to explain the ferromagnetic properties of itinerant ferromagnets in the 3d transition metals and their intermetallics n tateiwa et al phys rev b 96 035125 2017 our study suggests the itinerancy of the 5f electrons in most of the actinide ferromagnets and the applicability of the spin fluctuation theory to actinide 5f system in this paper we present a new analysis for the spin fluctuation parameter obtained with a different theoretical formula not used in the reference we also discuss the results of the analysis from different points of views | [['actinide', 'compounds', 'with', '5f', 'electrons', 'have', 'been', 'attracting', 'much', 'attention', 'because', 'of', 'their', 'interesting', 'magnetic', 'and', 'electronic', 'properties', 'such', 'as', 'heavy', 'fermion', 'state', 'unconventional', 'superconductivity', 'coexistence', 'of', 'the', 'superconductivity', 'and', 'magnetism', 'recently', 'we', 'have', 'reported', 'a', 'phenomenological', 'analysis', 'on', '80', 'actinide', 'ferromagnets', 'with', 'the', 'spin', 'fluctuation', 'theory', 'originally', 'developed', 'to', 'explain', 'the', 'ferromagnetic', 'properties', 'of', 'itinerant', 'ferromagnets', 'in', 'the', '3d', 'transition', 'metals', 'and', 'their', 'intermetallics', 'n', 'tateiwa', 'et', 'al', 'phys', 'rev', 'b', '96', '035125', '2017', 'our', 'study', 'suggests', 'the', 'itinerancy', 'of', 'the', '5f', 'electrons', 'in', 'most', 'of', 'the', 'actinide', 'ferromagnets', 'and', 'the', 'applicability', 'of', 'the', 'spin', 'fluctuation', 'theory', 'to', 'actinide', '5f', 'system', 'in', 'this', 'paper', 'we', 'present', 'a', 'new', 'analysis', 'for', 'the', 'spin', 'fluctuation', 'parameter', 'obtained', 'with', 'a', 'different', 'theoretical', 'formula', 'not', 'used', 'in', 'the', 'reference', 'we', 'also', 'discuss', 'the', 'results', 'of', 'the', 'analysis', 'from', 'different', 'points', 'of', 'views']] | [-0.09714958080482008, 0.16934659866366428, -0.03571380946137335, 0.06707451557588723, -0.029000672312669347, -0.11451365646528269, 0.11501296224710329, 0.3194050395361863, -0.17822469738936322, -0.3121317325065425, -0.07284598149683165, -0.3705102777769924, -0.15114533379538983, 0.1526443873282414, 0.008381641230316482, 0.035263399550509035, -0.041104279662671404, -0.04306904114006708, -0.13836613596514866, -0.22921943263677153, 0.25297942696193204, 0.028836286336561476, 0.3237378210389474, 0.0969764885418387, -0.011112609105454623, 0.017712571659881243, 0.09836539666276371, 0.0006010261620732322, -0.14986714460225642, 0.10426303549446976, 0.2737369784592664, -0.033248984118235174, 0.19070244977669115, -0.45484448700174823, -0.2371997128146282, 0.0256533914235542, 0.10532020501104063, 0.14403380056213844, -0.0964740758672765, -0.32413930695274495, 0.04115664936008229, -0.2133688836061544, -0.13071653443267164, -0.14622753585243356, 0.0435532685301766, 0.026219975029496287, -0.22828861640131884, 0.10316300622429665, 0.09723370508257084, 0.15165138185915092, -0.10115395973443284, -0.18089469060203925, -0.06892675786461357, 0.016863478016550314, 0.11710632033646107, 0.0483022346313152, 0.09708458480452174, -0.06896615465529317, -0.14408898925698915, 0.3747799350623635, 0.009223681262127408, -0.06825099702910993, 0.21902808592911216, -0.19047851268154825, -0.15607710503399427, 0.0993933012250109, 0.13934098985602916, 0.12131856172683014, -0.1506275319210861, 0.12773330735238403, -0.03627278853842206, 0.12592633216695834, -0.01639639991807981, 0.11657439072724378, 0.2287589991853262, 0.1969453483833459, -0.061729208971171276, 0.09726897195366252, -0.1150029294995888, -0.07407759330311345, -0.20318758418189659, -0.19760846426926446, -0.2306993399490265, 0.05182382200291613, -0.02790881236770487, -0.17333294079382566, 0.4403156703473001, 0.19461177789565662, 0.16328309272564406, -0.12775100355940885, 0.17937478189106923, 0.06353459737695538, 0.013999993034277408, 0.06314361578636411, 0.29609280216602096, 0.19500565090709351, 0.1571156041919375, -0.2749075139889602, 0.06881316637188412, 0.04937810981578693] |
1,802.09673 | The maximum negative hypergeometric distribution | An urn contains a known number of balls of two different colors. We describe
the random variable counting the smallest number of draws needed in order to
observe at least $\,c\,$ of both colors when sampling without replacement for a
pre-specified value of $\,c=1,2,\ldots\,$. This distribution is the finite
sample analogy to the maximum negative binomial distribution described by
Zhang, Burtness, and Zelterman (2000). We describe the modes, approximating
distributions, and estimation of the contents of the urn.
| math.ST stat.ME stat.TH | an urn contains a known number of balls of two different colors we describe the random variable counting the smallest number of draws needed in order to observe at least c of both colors when sampling without replacement for a prespecified value of c12ldots this distribution is the finite sample analogy to the maximum negative binomial distribution described by zhang burtness and zelterman 2000 we describe the modes approximating distributions and estimation of the contents of the urn | [['an', 'urn', 'contains', 'a', 'known', 'number', 'of', 'balls', 'of', 'two', 'different', 'colors', 'we', 'describe', 'the', 'random', 'variable', 'counting', 'the', 'smallest', 'number', 'of', 'draws', 'needed', 'in', 'order', 'to', 'observe', 'at', 'least', 'c', 'of', 'both', 'colors', 'when', 'sampling', 'without', 'replacement', 'for', 'a', 'prespecified', 'value', 'of', 'c12ldots', 'this', 'distribution', 'is', 'the', 'finite', 'sample', 'analogy', 'to', 'the', 'maximum', 'negative', 'binomial', 'distribution', 'described', 'by', 'zhang', 'burtness', 'and', 'zelterman', '2000', 'we', 'describe', 'the', 'modes', 'approximating', 'distributions', 'and', 'estimation', 'of', 'the', 'contents', 'of', 'the', 'urn']] | [-0.0803657898397528, 0.17196748830706624, -0.08860498076721438, 0.053793118701402194, -0.07056084037513326, -0.12405754835957564, 0.09347044341082342, 0.3499423429541486, -0.22796167158766797, -0.35532590430720074, 0.06734551018024304, -0.318101651776631, -0.03330366339497758, 0.08229673870741144, -0.14784387373488003, 0.04148950649572438, -0.006700111406021996, 0.03909261826131689, -0.00033494879148508375, -0.30340854578810794, 0.2897305915279216, -0.013558291670817294, 0.2562010178563038, -0.0383026136183425, 0.1158911220324961, 0.061385788832251965, -0.07883723582275898, 0.035764652328859815, -0.15631486706651662, 0.08093307206505224, 0.2028268949361518, 0.13436065050528237, 0.3035500978156434, -0.3161619641892972, -0.17827580803024926, 0.1680079020489326, 0.11963141856463871, 0.08375386534699876, -0.03895139393984879, -0.1586896356526076, 0.10791202602099235, -0.1373847099358069, -0.15782406670041382, 0.006896399473158741, 0.04903315798085379, 0.07818072647052376, -0.3156399919504398, 0.0015120511433403742, 0.07001119478311586, 0.03848767847337417, 0.02613987475878706, -0.21395275327622107, -0.009456395324760754, 0.12125951111030238, 0.021004933211339737, -0.010738237667522443, 0.05665603001896096, -0.14527152932829554, -0.1102861929868691, 0.35243606824721946, -0.05290886348781274, -0.17322166724816748, 0.15236663589205005, -0.17187199910097806, -0.10216047049892184, 0.12530257875148795, 0.1484642960253711, 0.13938236229832432, -0.11840948191610023, 0.03578966902425332, -0.06436661855734296, 0.11609157558536697, 0.11171684037330315, 0.0028712623262483823, 0.15129070602798542, 0.13052897074713224, 0.06203965848850969, 0.17109439660960465, -0.11592770317618392, -0.11088132879108582, -0.3318531090687764, -0.13859301986859032, -0.28523768903074886, 0.04791116379936667, -0.17788424412375256, -0.21567694885705255, 0.389011040170628, 0.13876130529005373, 0.2633031070918629, 0.10698736758020364, 0.2371417286830317, 0.12647215700953415, -0.002806614549818302, 0.09202328840834334, 0.11768398925625279, 0.15735427683868788, 0.008914445968050706, -0.19651495417163364, 0.08607390294108834, 0.07622412033072722] |
1,802.09674 | Hydrodynamic limits for long-range asymmetric interacting particle
systems | We consider the hydrodynamic scaling behavior of the mass density with
respect to a general class of mass conservative interacting particle systems on
${\mathbb Z}^n$, where the jump rates are asymmetric and long-range of order
$\|x\|^{-(n+\alpha)}$ for a particle displacement of order $\|x\|$. Two types
of evolution equations are identified depending on the strength of the
long-range asymmetry. When $0<\alpha<1$, we find a new integro-partial
differential hydrodynamic equation, in an anomalous space-time scale. On the
other hand, when $\alpha\geq 1$, we derive a Burgers hydrodynamic equation, as
in the finite-range setting, in Euler scale.
| math.PR | we consider the hydrodynamic scaling behavior of the mass density with respect to a general class of mass conservative interacting particle systems on mathbb zn where the jump rates are asymmetric and longrange of order xnalpha for a particle displacement of order x two types of evolution equations are identified depending on the strength of the longrange asymmetry when 0alpha1 we find a new integropartial differential hydrodynamic equation in an anomalous spacetime scale on the other hand when alphageq 1 we derive a burgers hydrodynamic equation as in the finiterange setting in euler scale | [['we', 'consider', 'the', 'hydrodynamic', 'scaling', 'behavior', 'of', 'the', 'mass', 'density', 'with', 'respect', 'to', 'a', 'general', 'class', 'of', 'mass', 'conservative', 'interacting', 'particle', 'systems', 'on', 'mathbb', 'zn', 'where', 'the', 'jump', 'rates', 'are', 'asymmetric', 'and', 'longrange', 'of', 'order', 'xnalpha', 'for', 'a', 'particle', 'displacement', 'of', 'order', 'x', 'two', 'types', 'of', 'evolution', 'equations', 'are', 'identified', 'depending', 'on', 'the', 'strength', 'of', 'the', 'longrange', 'asymmetry', 'when', '0alpha1', 'we', 'find', 'a', 'new', 'integropartial', 'differential', 'hydrodynamic', 'equation', 'in', 'an', 'anomalous', 'spacetime', 'scale', 'on', 'the', 'other', 'hand', 'when', 'alphageq', '1', 'we', 'derive', 'a', 'burgers', 'hydrodynamic', 'equation', 'as', 'in', 'the', 'finiterange', 'setting', 'in', 'euler', 'scale']] | [-0.1680839572651708, 0.14743780185845606, -0.05621611648189657, 0.07894085930224429, -0.043069447098458384, -0.1479370958677077, -0.06213553880955627, 0.29235041669589723, -0.26681256452525787, -0.2620562809362185, 0.06116286594732764, -0.30923250978168576, -0.07692385970198727, 0.16339812004205553, 0.03572374743785947, 0.04542808978511219, -0.03160327260798596, 0.0752207125299313, -0.09849022929259438, -0.21097823797398188, 0.37957916155140453, -0.03033064281260793, 0.20046654912306272, 0.014397912738012506, 0.12687061988609902, -0.0296715498416427, 0.005892197814512443, 0.03473450597177478, -0.20235574610055762, 0.014397349347300987, 0.14596377822763704, -0.05359316235804494, 0.23172589712479014, -0.41681639087247724, -0.21255932882071493, 0.10204336361741607, 0.16784556241002568, 0.11174850219345474, -0.051597274055932354, -0.28215771995514555, 0.029314833556975613, -0.16977808557133725, -0.19178974052811873, -0.02573552705406984, 0.07575645855568508, 0.11833235163469502, -0.3233173109115438, 0.17961021250688491, 0.07210010129641345, 0.04033325252679246, -0.07971218297198573, -0.09165952190078121, -0.04142897072783176, 0.04846971193043654, 0.05122425680994948, -0.008824383894457145, 0.12064404325421027, -0.15278759880110304, -0.07670537667210273, 0.3979864542253633, -0.1057041923124145, -0.2620541558581147, 0.1852680625384079, -0.1873209640938551, -0.14959560750805317, 0.12030830307606052, 0.2297858723260938, 0.12785842488618923, -0.13957172289070863, 0.11822330840167272, -0.023680774917320766, 0.1658566013830615, 0.032802023895164116, 0.010827762518756766, 0.14551083107498733, 0.16738773337466287, 0.07265155820889359, 0.08164198959972016, -0.09327227010006492, -0.15112854647351073, -0.34507364914455313, -0.16284354930251133, -0.14700511915787579, 0.10015102139267912, -0.14973327414454035, -0.16388235666709852, 0.3276645735976227, 0.1559131871314442, 0.18550824638495736, 0.0838704717177105, 0.21007337043695945, 0.175405479703802, -0.007604491986096539, 0.04682588494541322, 0.19422326173554075, 0.13089247380799435, 0.1065790689837663, -0.264808933379406, 0.03294716288949898, 0.12391939207024753] |
1,802.09675 | Generic HKT geometries in the harmonic superspace approach | We explain how a generic HKT geometry can be derived using the language of N
= 4 supersymmetric quantum mechanics. To this end, one should consider a
Lagrangian involving several (4,4,0) multiplets defined in harmonic superspace
and subject to nontrivial harmonic constraints. Conjecturally, this general
construction worked out earlier by Delduc and Ivanov gives a complete
classification of all HKT geometries. Each such geometry is generated by two
different functions (potentials) of a special type that depend on harmonic
superfields and on harmonics.
Given these two potentials, one can derive the vielbeins, metric, connections
and curvatures, but this is not so simple: one should solve rather complicated
differential equations. We illustrate the general construction by giving a
detailed derivation of the metric for the hyper-Kaehler Taub-NUT manifold. In
the generic case, we arrive at an HKT geometry. In this paper, we give a simple
proof of this assertion.
| hep-th math-ph math.MP | we explain how a generic hkt geometry can be derived using the language of n 4 supersymmetric quantum mechanics to this end one should consider a lagrangian involving several 440 multiplets defined in harmonic superspace and subject to nontrivial harmonic constraints conjecturally this general construction worked out earlier by delduc and ivanov gives a complete classification of all hkt geometries each such geometry is generated by two different functions potentials of a special type that depend on harmonic superfields and on harmonics given these two potentials one can derive the vielbeins metric connections and curvatures but this is not so simple one should solve rather complicated differential equations we illustrate the general construction by giving a detailed derivation of the metric for the hyperkaehler taubnut manifold in the generic case we arrive at an hkt geometry in this paper we give a simple proof of this assertion | [['we', 'explain', 'how', 'a', 'generic', 'hkt', 'geometry', 'can', 'be', 'derived', 'using', 'the', 'language', 'of', 'n', '4', 'supersymmetric', 'quantum', 'mechanics', 'to', 'this', 'end', 'one', 'should', 'consider', 'a', 'lagrangian', 'involving', 'several', '440', 'multiplets', 'defined', 'in', 'harmonic', 'superspace', 'and', 'subject', 'to', 'nontrivial', 'harmonic', 'constraints', 'conjecturally', 'this', 'general', 'construction', 'worked', 'out', 'earlier', 'by', 'delduc', 'and', 'ivanov', 'gives', 'a', 'complete', 'classification', 'of', 'all', 'hkt', 'geometries', 'each', 'such', 'geometry', 'is', 'generated', 'by', 'two', 'different', 'functions', 'potentials', 'of', 'a', 'special', 'type', 'that', 'depend', 'on', 'harmonic', 'superfields', 'and', 'on', 'harmonics', 'given', 'these', 'two', 'potentials', 'one', 'can', 'derive', 'the', 'vielbeins', 'metric', 'connections', 'and', 'curvatures', 'but', 'this', 'is', 'not', 'so', 'simple', 'one', 'should', 'solve', 'rather', 'complicated', 'differential', 'equations', 'we', 'illustrate', 'the', 'general', 'construction', 'by', 'giving', 'a', 'detailed', 'derivation', 'of', 'the', 'metric', 'for', 'the', 'hyperkaehler', 'taubnut', 'manifold', 'in', 'the', 'generic', 'case', 'we', 'arrive', 'at', 'an', 'hkt', 'geometry', 'in', 'this', 'paper', 'we', 'give', 'a', 'simple', 'proof', 'of', 'this', 'assertion']] | [-0.14921553251903732, 0.08707041422716504, -0.08233092426873591, 0.10608426715979087, -0.14670256943106144, -0.19053369422196126, -0.04916113197999899, 0.3348458165138149, -0.20820333231335544, -0.25543961696149337, 0.06997038007058128, -0.22775348902008413, -0.2113080314870569, 0.17065941113155006, -0.11474814252978584, -0.02080898825395979, 0.024375728442377988, 0.06340909883265897, -0.10903775418766451, -0.2828954557213476, 0.3800494589773165, 0.0009635139033388422, 0.1953101334515262, 0.06379691764190049, 0.1262902207846823, 0.007859331364014826, -0.024628887857392836, 0.011062007875745596, -0.1497143589922478, 0.14190628481585355, 0.24371503007623563, 0.10115534326277015, 0.17248507182360912, -0.43583538464973776, -0.20203998131751952, 0.10854670670212938, 0.12841140798476786, 0.12204832063835798, -0.011965128430006963, -0.2547049577265572, 0.02564984907674901, -0.14903268488211127, -0.1766833616068213, -0.11542991416126515, 0.004524523085046585, -0.043568649636518186, -0.21664776399075908, 0.007241003992998985, 0.11259192714173043, 0.06289202656571558, -0.05242645659889443, -0.07570313925373362, -0.022169323652336488, 0.057725912077213025, 0.012782084065818919, 0.03051263462992854, 0.0908781704492867, -0.06446637429746793, -0.11718317687029944, 0.3849566231107935, -0.047176692885074284, -0.3241952563300222, 0.14463442349711395, -0.11635051810239651, -0.1977970146536067, 0.07756180318506421, 0.13140827126572935, 0.16742269941257173, -0.16338737075831614, 0.1351848363188938, -0.05250278704793376, 0.11009187239291919, 0.12162343979033889, -0.01919020839640554, 0.19615546593024413, 0.0835721752650681, 0.06187801977039828, 0.15636281591450454, 0.025634828315046775, -0.11399293580364918, -0.39367260201042203, -0.1479569443340768, -0.12257198853890228, 0.13908889692850476, -0.11329582799186448, -0.1562610887795636, 0.4305492483560934, 0.05835231568594622, 0.21275392696134696, 0.07710600159365405, 0.2539036543659714, 0.11753828843206572, 0.03587816607050256, 0.027374134459184345, 0.24561875582146805, 0.157986910321566, 0.0606703566114868, -0.12739947838645402, -0.08537391442362041, 0.15097453729661348] |
1,802.09676 | Variational Integrators for Inertial Magnetohydrodynamics | Recently, an extended version of magnetohydrodynamics that incorporates
electron inertia, dubbed inertial magnetohydrodynamics, has been proposed. This
model features a noncanonical Hamiltonian formulation with a number of
conserved quantities, including the total energy and modified versions of
magnetic and cross helicity. In this work, a variational integrator is
presented which preserves these conservation laws to machine accuracy. As long
as effects due to finite electron mass are neglected, the scheme preserves the
magnetic field line topology so that unphysical reconnection is absent. Only
when effects of finite electron mass are added, magnetic reconnection takes
place. The excellent conservation properties of the method are illustrated by
numerical examples in 2D.
| physics.comp-ph math.NA physics.plasm-ph | recently an extended version of magnetohydrodynamics that incorporates electron inertia dubbed inertial magnetohydrodynamics has been proposed this model features a noncanonical hamiltonian formulation with a number of conserved quantities including the total energy and modified versions of magnetic and cross helicity in this work a variational integrator is presented which preserves these conservation laws to machine accuracy as long as effects due to finite electron mass are neglected the scheme preserves the magnetic field line topology so that unphysical reconnection is absent only when effects of finite electron mass are added magnetic reconnection takes place the excellent conservation properties of the method are illustrated by numerical examples in 2d | [['recently', 'an', 'extended', 'version', 'of', 'magnetohydrodynamics', 'that', 'incorporates', 'electron', 'inertia', 'dubbed', 'inertial', 'magnetohydrodynamics', 'has', 'been', 'proposed', 'this', 'model', 'features', 'a', 'noncanonical', 'hamiltonian', 'formulation', 'with', 'a', 'number', 'of', 'conserved', 'quantities', 'including', 'the', 'total', 'energy', 'and', 'modified', 'versions', 'of', 'magnetic', 'and', 'cross', 'helicity', 'in', 'this', 'work', 'a', 'variational', 'integrator', 'is', 'presented', 'which', 'preserves', 'these', 'conservation', 'laws', 'to', 'machine', 'accuracy', 'as', 'long', 'as', 'effects', 'due', 'to', 'finite', 'electron', 'mass', 'are', 'neglected', 'the', 'scheme', 'preserves', 'the', 'magnetic', 'field', 'line', 'topology', 'so', 'that', 'unphysical', 'reconnection', 'is', 'absent', 'only', 'when', 'effects', 'of', 'finite', 'electron', 'mass', 'are', 'added', 'magnetic', 'reconnection', 'takes', 'place', 'the', 'excellent', 'conservation', 'properties', 'of', 'the', 'method', 'are', 'illustrated', 'by', 'numerical', 'examples', 'in', '2d']] | [-0.14556211433928767, 0.16059556637088013, -0.0540718466701379, 0.11453129220412138, -0.07326003942433573, -0.12344498667062832, -0.06936857678474637, 0.3224241260199919, -0.23204431410690923, -0.34875280538215003, 0.011114261269039654, -0.23638640416768986, -0.10028195207930007, 0.1887931934485229, -0.030263677136887105, 0.07392784478911839, 0.06542283070162622, -0.003503840100532825, -0.07663656543051704, -0.20221845857017254, 0.2782617063697325, 0.09867537747897687, 0.2784812109322723, 0.07410504278906305, 0.17401366235705418, -0.0421564912513206, -0.009187267542124615, 0.10145415691231642, -0.10255566510703487, 0.00559206947752642, 0.15884852029998367, 0.020197827625302, 0.25593974445562023, -0.45266626006282795, -0.2626548527201655, 0.01972325583022737, 0.1665174841027442, 0.12165923427188034, -0.07679803074773299, -0.24815660336165937, 0.05394885627287995, -0.2114262058476516, -0.12418231831590107, -0.13112358065373306, 0.007102908755635518, 0.03571674251638421, -0.2819784059394322, 0.1179993970505466, 0.0826606313706538, 0.060076209297830904, -0.09573840097430239, -0.08070888221605656, -0.09522009967856211, 0.05159564580636979, 0.12228619700848817, 0.02109753657901369, 0.1456727167044621, -0.10809846200185631, -0.11396971391513944, 0.4186168957433296, -0.014156994324416743, -0.2535240463570717, 0.14906538243046663, -0.1060882546071715, -0.15070280312013667, 0.17442871289703687, 0.14354041703643466, 0.11088425701125226, -0.15880166145253588, 0.12804839453860742, -0.06690190192482887, 0.10828335757939778, 0.010543237752152965, 0.03279809425627693, 0.197717691523903, 0.13805022134462697, 0.03711610365394127, 0.0974328045801627, -0.12503414358431048, -0.15179376248612042, -0.3203488578934462, -0.14809060399954574, -0.19427094900544836, 0.04955921522469832, -0.03494207105153975, -0.17468940833190438, 0.3804219994495274, 0.17810280210500873, 0.14197957061162783, -0.021786612769323956, 0.34469379406473644, 0.17019129952697784, 0.10534056387158162, 0.10343105865454455, 0.23999929430877465, 0.20780337658505715, 0.12008292835479209, -0.25305838479180903, 0.014553503299969326, 0.15189262305241114] |
1,802.09677 | Influence of the aggregate state on band structure and optical
properties of C60 computed with different methods | C60 and C60 based molecules are efficient acceptor and electron transport
layers for planar perovskite solar cells. While properties of these molecules
are well studied by ab initiomethods, those of solid C60, specifically its
optical absorption properties, are not. We present a combined Density
Functional Theory - Density Functional Tight Binding study of the effect of
solid state packing on bandstructure and optical absorption of C60. The valence
and conduction band edge energies of solid C60 differ on the order of 0.1 eV
from single molecule frontier orbital energies. We show that calculations of
optical properties using linear response TD-DFT(B) or the imaginary part of the
dielectric constant (dipole approximation) can result in unrealistically large
redshift in the presence of intermolecular interactions compared to available
experimental data. We show that optical spectra computed from the
frequency-dependent real polarizability better reproduce the effect of C60
aggregation on optical absorption and may be more suited to study effects of
molecular aggregation.
| cond-mat.mtrl-sci | c60 and c60 based molecules are efficient acceptor and electron transport layers for planar perovskite solar cells while properties of these molecules are well studied by ab initiomethods those of solid c60 specifically its optical absorption properties are not we present a combined density functional theory density functional tight binding study of the effect of solid state packing on bandstructure and optical absorption of c60 the valence and conduction band edge energies of solid c60 differ on the order of 01 ev from single molecule frontier orbital energies we show that calculations of optical properties using linear response tddftb or the imaginary part of the dielectric constant dipole approximation can result in unrealistically large redshift in the presence of intermolecular interactions compared to available experimental data we show that optical spectra computed from the frequencydependent real polarizability better reproduce the effect of c60 aggregation on optical absorption and may be more suited to study effects of molecular aggregation | [['c60', 'and', 'c60', 'based', 'molecules', 'are', 'efficient', 'acceptor', 'and', 'electron', 'transport', 'layers', 'for', 'planar', 'perovskite', 'solar', 'cells', 'while', 'properties', 'of', 'these', 'molecules', 'are', 'well', 'studied', 'by', 'ab', 'initiomethods', 'those', 'of', 'solid', 'c60', 'specifically', 'its', 'optical', 'absorption', 'properties', 'are', 'not', 'we', 'present', 'a', 'combined', 'density', 'functional', 'theory', 'density', 'functional', 'tight', 'binding', 'study', 'of', 'the', 'effect', 'of', 'solid', 'state', 'packing', 'on', 'bandstructure', 'and', 'optical', 'absorption', 'of', 'c60', 'the', 'valence', 'and', 'conduction', 'band', 'edge', 'energies', 'of', 'solid', 'c60', 'differ', 'on', 'the', 'order', 'of', '01', 'ev', 'from', 'single', 'molecule', 'frontier', 'orbital', 'energies', 'we', 'show', 'that', 'calculations', 'of', 'optical', 'properties', 'using', 'linear', 'response', 'tddftb', 'or', 'the', 'imaginary', 'part', 'of', 'the', 'dielectric', 'constant', 'dipole', 'approximation', 'can', 'result', 'in', 'unrealistically', 'large', 'redshift', 'in', 'the', 'presence', 'of', 'intermolecular', 'interactions', 'compared', 'to', 'available', 'experimental', 'data', 'we', 'show', 'that', 'optical', 'spectra', 'computed', 'from', 'the', 'frequencydependent', 'real', 'polarizability', 'better', 'reproduce', 'the', 'effect', 'of', 'c60', 'aggregation', 'on', 'optical', 'absorption', 'and', 'may', 'be', 'more', 'suited', 'to', 'study', 'effects', 'of', 'molecular', 'aggregation']] | [-0.08726299126042278, 0.13053528751857627, -0.02038252982792925, 0.030368058070255693, -0.016399989414746595, -0.10921682596538856, 0.08767422954299765, 0.480853967855026, -0.24255152306501654, -0.29692022173790034, -0.025345505483650194, -0.31734345174412343, -0.12543882799074743, 0.12877745254285586, 0.0709270187727751, 0.044139253147240064, 0.05315723117725674, -0.07187987180058933, -0.03471191861779076, -0.16122093214801733, 0.24122808480659014, 0.06047185843181648, 0.2382307131492954, 0.13481640966110833, -0.001150091415253367, 0.015264906324327561, 0.038668262305117815, 0.03691897556707738, -0.15045933675144763, 0.18040948021551892, 0.2429683368822121, -0.056662598396443824, 0.19828559434824403, -0.5079811306278796, -0.23163194992360037, -0.003062227248528581, 0.11154708214946518, 0.13381208778228493, -0.05581079073551342, -0.22648333254786338, 0.004659562366109958, -0.13375945274486759, -0.12379687326622142, -0.09355223434680635, 0.01224286897570654, 0.09576233715644984, -0.22600651828121324, 0.13982752828627446, -0.026922118990195643, 0.0676004809121565, -0.16831193082064247, -0.2069950868541695, -0.09032509249196073, 0.06936986369057113, -0.014790901190536037, -0.013744208371492138, 0.2346683775088127, -0.09838317780441065, -0.08448634781966662, 0.44602327127080815, -0.0824117867630509, -0.08522312551333457, 0.19065085676599555, -0.1985487251328957, -0.09531576173219854, 0.21155870782662253, 0.13895943171584202, 0.12240257901050577, -0.13730855581237916, 0.06666009146000917, -0.020280244637126472, 0.20686028951298516, 0.07424321366402849, 0.12107549565636617, 0.20543274127101158, 0.15667355541365258, 0.007477500375099243, 0.11185310441914614, -0.14098334398378684, -0.026712837732830057, -0.19001694313683518, -0.14923055519373601, -0.24186993625228573, 0.06813143019923706, -0.0750102718818783, -0.186391088147618, 0.3673810115926395, 0.08731599952091292, 0.1377875489230226, -0.009396098340582696, 0.28382508639412324, 0.09087018156720764, 0.0657731995036956, 0.006073665772905799, 0.29551173089321253, 0.15837485052698594, 0.053215542189765035, -0.28818493623844094, 0.07510668247534781, 0.011455900685351555] |
1,802.09678 | Log-H\"older Continuity of the Lyapunov Exponent for Jacobi Operators
with Potentials Given by the Skew-Shift | In this paper we study one-dimensional Jacobi operators on the lattice with a
potential given by the skew shift. We show that the large deviation theorem
takes place for Diophantine frequency and sufficiently large disorder.
Combining the large deviation theorem with the avalanche principle, we prove
the log-H\"older continuity of the Lyapunov exponent.
| math.FA | in this paper we study onedimensional jacobi operators on the lattice with a potential given by the skew shift we show that the large deviation theorem takes place for diophantine frequency and sufficiently large disorder combining the large deviation theorem with the avalanche principle we prove the logholder continuity of the lyapunov exponent | [['in', 'this', 'paper', 'we', 'study', 'onedimensional', 'jacobi', 'operators', 'on', 'the', 'lattice', 'with', 'a', 'potential', 'given', 'by', 'the', 'skew', 'shift', 'we', 'show', 'that', 'the', 'large', 'deviation', 'theorem', 'takes', 'place', 'for', 'diophantine', 'frequency', 'and', 'sufficiently', 'large', 'disorder', 'combining', 'the', 'large', 'deviation', 'theorem', 'with', 'the', 'avalanche', 'principle', 'we', 'prove', 'the', 'logholder', 'continuity', 'of', 'the', 'lyapunov', 'exponent']] | [-0.18220243522159332, 0.1307531693458276, -0.10551198585978094, 0.07276975264649768, -0.03463763556605697, -0.12032536985704077, 0.07762272852991339, 0.2917096750494444, -0.3058916241422577, -0.17927248368285736, 0.09730836768186528, -0.26823428849566655, -0.16067075047571705, 0.20226749377149456, -0.0786327180751371, 0.07314605362502472, 0.05254452714239651, 0.016308317874681275, -0.07497489960196446, -0.19302818239754382, 0.3776998924759199, -0.03526085210120622, 0.27615878446343933, 0.09831603373980748, 0.12628507278508172, 0.06627478475137702, -0.009169278995854393, 0.02849242942548304, -0.1946426351025606, 0.12054347009661626, 0.1796099785363899, 0.009127931129011625, 0.27907261835797775, -0.3565087173626108, -0.16330923820090182, 0.1858668732632584, 0.07756107423085508, 0.10489080805893776, -0.05887510182713773, -0.30658261390086616, 0.10743863190049832, -0.15064646655096198, -0.20618339293232224, -0.0666628830345734, 0.02509281698192628, 0.087753859045476, -0.31624925375547047, 0.10512941965903595, 0.1368106854552368, 0.11563703648851446, -0.06392877348610815, -0.07712553545200038, 0.049725837249941424, 0.07932117083197776, 0.06415172525734272, 0.0021306160477183337, 0.09283399074953401, -0.02903972040281965, -0.0728213367720117, 0.3414055273938432, -0.12210818408232815, -0.18017309949786034, 0.08359302678760493, -0.24297133286676878, -0.17016307508818945, 0.08479938248418412, 0.15869638242952103, 0.061555753549877204, -0.09336327355934905, 0.1618014086764921, -0.07958219611999702, 0.1598069116529209, 0.10373720538995738, 0.03483629765270172, 0.11221655535529244, 0.11350322947046666, 0.12473537194331721, 0.1667745300691645, -0.08771330330362719, -0.10942720743071921, -0.33540323938963545, -0.12073277824839472, -0.24791812225473378, 0.13603447254676865, -0.18769526929690125, -0.1913176692038212, 0.3662912640874362, 0.14550031836689362, 0.17055152869730625, 0.19134978248017295, 0.19560899061836162, 0.23354328843712244, 0.07726969103820903, 0.061196196086283, 0.2184223273180355, 0.1511281760066818, 0.12204771945340875, -0.2041470984629584, 0.007612887796295702, 0.15138280070123245] |
1,802.09679 | A guide to Brownian motion and related stochastic processes | This is a guide to the mathematical theory of Brownian motion and related
stochastic processes, with indications of how this theory is related to other
branches of mathematics, most notably the classical theory of partial
differential equations associated with the Laplace and heat operators, and
various generalizations thereof. As a typical reader, we have in mind a
student, familiar with the basic concepts of probability based on measure
theory, at the level of the graduate texts of Billingsley and Durrett , and who
wants a broader perspective on the theory of Brownian motion and related
stochastic processes than can be found in these texts.
| math.PR | this is a guide to the mathematical theory of brownian motion and related stochastic processes with indications of how this theory is related to other branches of mathematics most notably the classical theory of partial differential equations associated with the laplace and heat operators and various generalizations thereof as a typical reader we have in mind a student familiar with the basic concepts of probability based on measure theory at the level of the graduate texts of billingsley and durrett and who wants a broader perspective on the theory of brownian motion and related stochastic processes than can be found in these texts | [['this', 'is', 'a', 'guide', 'to', 'the', 'mathematical', 'theory', 'of', 'brownian', 'motion', 'and', 'related', 'stochastic', 'processes', 'with', 'indications', 'of', 'how', 'this', 'theory', 'is', 'related', 'to', 'other', 'branches', 'of', 'mathematics', 'most', 'notably', 'the', 'classical', 'theory', 'of', 'partial', 'differential', 'equations', 'associated', 'with', 'the', 'laplace', 'and', 'heat', 'operators', 'and', 'various', 'generalizations', 'thereof', 'as', 'a', 'typical', 'reader', 'we', 'have', 'in', 'mind', 'a', 'student', 'familiar', 'with', 'the', 'basic', 'concepts', 'of', 'probability', 'based', 'on', 'measure', 'theory', 'at', 'the', 'level', 'of', 'the', 'graduate', 'texts', 'of', 'billingsley', 'and', 'durrett', 'and', 'who', 'wants', 'a', 'broader', 'perspective', 'on', 'the', 'theory', 'of', 'brownian', 'motion', 'and', 'related', 'stochastic', 'processes', 'than', 'can', 'be', 'found', 'in', 'these', 'texts']] | [-0.0160744203937249, 0.10945732001830073, -0.1204953038764358, 0.10620553859337731, -0.12471586520313421, -0.13771549873596545, 0.039486321972149595, 0.29698975412265477, -0.2960897444993782, -0.2965936961050317, 0.09766765340407678, -0.3275615465103929, -0.20600528403827287, 0.19652006912578657, -0.12811475438834394, 0.03829919156215484, 0.008098978101664666, 0.10030638813086361, -0.02991745775583589, -0.21113609122021973, 0.317011337661754, 0.04786829554557222, 0.23492575187272238, 0.022560504219919734, 0.10156563989528754, -0.009006457778543812, -0.08725933062853021, 0.031237992125753206, -0.1338908141840575, 0.17687069543284697, 0.2769771536215416, 0.11048408191271343, 0.31519285741361597, -0.46420611808917406, -0.19006228379823847, 0.02960541866972898, 0.07635403188675624, 0.10051488177822586, -0.0056803581390746875, -0.31812865033890436, 0.03857052352424096, -0.13402037782757317, -0.1356163758929204, -0.040696128886373875, 0.02109433721425464, 0.07261827165821513, -0.19736761915795867, 0.08088132976418705, 0.09788732464850239, 0.08680582974440626, -0.02066575041610422, -0.1356009681058089, 0.00012010657703232708, 0.11364540168382589, 0.07243598810198165, 0.01776579767606872, 0.12974960564463897, -0.16604366617783614, -0.20514907498021148, 0.4010394602760817, -0.059480131774020686, -0.2368591005724032, 0.2313923326917716, -0.16691977055562499, -0.15052810903566266, 0.06362246068700858, 0.18381618754938245, 0.13730155248240142, -0.16877123904278846, 0.08990793016589997, -0.019914862347169986, 0.10670006141807993, 0.06720152983749375, 0.023251185745217846, 0.1804881594369857, 0.13158611833904554, 0.03342311086757018, 0.0961005670799494, -0.005063944031118225, -0.1885594326360784, -0.3195984004951507, -0.1717932346249813, -0.1044642018534026, 0.06639680318823717, -0.06220063571513006, -0.16505293960110012, 0.373913924887921, 0.17695643922519752, 0.1265501439734136, 0.04319543424017221, 0.21294884242623754, 0.1810759106928989, -0.0039837054119364005, 0.009246822319997168, 0.13476850929245063, 0.1975344419603697, 0.15105678207123452, -0.14690718035557243, 0.04469925112732984, 0.07168269026753249] |
1,802.0968 | Multi-Observation Regression | Recent work introduced loss functions which measure the error of a prediction
based on multiple simultaneous observations or outcomes. In this paper, we
explore the theoretical and practical questions that arise when using such
multi-observation losses for regression on data sets of $(x,y)$ pairs. When a
loss depends on only one observation, the average empirical loss decomposes by
applying the loss to each pair, but for the multi-observation case, empirical
loss is not even well-defined, and the possibility of statistical guarantees is
unclear without several $(x,y)$ pairs with exactly the same $x$ value. We
propose four algorithms formalizing the concept of empirical risk minimization
for this problem, two of which have statistical guarantees in settings allowing
both slow and fast convergence rates, but which are out-performed empirically
by the other two. Empirical results demonstrate practicality of these
algorithms in low-dimensional settings, while lower bounds demonstrate
intrinsic difficulty in higher dimensions. Finally, we demonstrate the
potential benefit of the algorithms over natural baselines that use traditional
single-observation losses via both lower bounds and simulations.
| cs.LG | recent work introduced loss functions which measure the error of a prediction based on multiple simultaneous observations or outcomes in this paper we explore the theoretical and practical questions that arise when using such multiobservation losses for regression on data sets of xy pairs when a loss depends on only one observation the average empirical loss decomposes by applying the loss to each pair but for the multiobservation case empirical loss is not even welldefined and the possibility of statistical guarantees is unclear without several xy pairs with exactly the same x value we propose four algorithms formalizing the concept of empirical risk minimization for this problem two of which have statistical guarantees in settings allowing both slow and fast convergence rates but which are outperformed empirically by the other two empirical results demonstrate practicality of these algorithms in lowdimensional settings while lower bounds demonstrate intrinsic difficulty in higher dimensions finally we demonstrate the potential benefit of the algorithms over natural baselines that use traditional singleobservation losses via both lower bounds and simulations | [['recent', 'work', 'introduced', 'loss', 'functions', 'which', 'measure', 'the', 'error', 'of', 'a', 'prediction', 'based', 'on', 'multiple', 'simultaneous', 'observations', 'or', 'outcomes', 'in', 'this', 'paper', 'we', 'explore', 'the', 'theoretical', 'and', 'practical', 'questions', 'that', 'arise', 'when', 'using', 'such', 'multiobservation', 'losses', 'for', 'regression', 'on', 'data', 'sets', 'of', 'xy', 'pairs', 'when', 'a', 'loss', 'depends', 'on', 'only', 'one', 'observation', 'the', 'average', 'empirical', 'loss', 'decomposes', 'by', 'applying', 'the', 'loss', 'to', 'each', 'pair', 'but', 'for', 'the', 'multiobservation', 'case', 'empirical', 'loss', 'is', 'not', 'even', 'welldefined', 'and', 'the', 'possibility', 'of', 'statistical', 'guarantees', 'is', 'unclear', 'without', 'several', 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0.10211106880668139, 0.03087473444797662] |
1,802.09681 | On Euler Emulation of Observer-Based Stabilizers for Nonlinear
Time-Delay Systems | In this paper, we deal with the problem of the stabilization in the
sample-and-hold sense, by emulation of continuous-time, observer-based, global
stabilizers. Fully nonlinear time-delay systems are studied. Sufficient
conditions are provided such that the Euler approximation of continuous-time,
observer-based, global stabilizers, for nonlinear time-delay systems, yields
stabilization in the sample-and-hold sense. Submitted (in an extended version)
to Automatica.
| cs.SY | in this paper we deal with the problem of the stabilization in the sampleandhold sense by emulation of continuoustime observerbased global stabilizers fully nonlinear timedelay systems are studied sufficient conditions are provided such that the euler approximation of continuoustime observerbased global stabilizers for nonlinear timedelay systems yields stabilization in the sampleandhold sense submitted in an extended version to automatica | [['in', 'this', 'paper', 'we', 'deal', 'with', 'the', 'problem', 'of', 'the', 'stabilization', 'in', 'the', 'sampleandhold', 'sense', 'by', 'emulation', 'of', 'continuoustime', 'observerbased', 'global', 'stabilizers', 'fully', 'nonlinear', 'timedelay', 'systems', 'are', 'studied', 'sufficient', 'conditions', 'are', 'provided', 'such', 'that', 'the', 'euler', 'approximation', 'of', 'continuoustime', 'observerbased', 'global', 'stabilizers', 'for', 'nonlinear', 'timedelay', 'systems', 'yields', 'stabilization', 'in', 'the', 'sampleandhold', 'sense', 'submitted', 'in', 'an', 'extended', 'version', 'to', 'automatica']] | [-0.20974080362436126, 0.0165135500327609, -0.048654611403974944, 0.02182935945239802, -0.02174418750692601, -0.1853023650345661, -0.0510065208043177, 0.3410238728432332, -0.31711408031820243, -0.2088003178182358, 0.17478220226337848, -0.170172146343926, -0.1981298780794871, 0.2122891996750387, -0.16196232267765928, 0.15266830398369644, 0.057059314638628796, -0.012129100386874151, -0.03393586902973889, -0.2786955535727537, 0.30614507155713894, 0.038883898361838594, 0.19112678566726587, -0.07280470553974984, 0.15943474685615402, 0.025850169534274076, -0.0005049244776936406, 0.039093684594509966, -0.12437637314514624, 0.04054050090509641, 0.27810588535868513, 0.05492823454156771, 0.3190307070706355, -0.4188639542119483, -0.21086780449091377, 0.13132968095083863, 0.12112399275903984, 0.12942471243125403, -0.05347379956836418, -0.3462893486622784, 0.11974558584644633, -0.17248759671288022, -0.1506567164797778, -0.06622039815568823, -0.021007047753023395, 0.0644574133458279, -0.32013031619332605, 0.052492876694995465, 0.10302220870567075, 0.06784988963439809, -0.11660154334316819, -0.005342462857774758, 0.005724494313915907, 0.08304222947838953, -0.07972170901879416, -0.026816889367429382, 0.047055160445240087, -0.07561939449238954, -0.1429746830007219, 0.33391990582064046, -0.0696548420651737, -0.2619453236713248, 0.18216794690559224, -0.04977956564970693, -0.1856280151060072, 0.11691157594007456, 0.20174406569893077, 0.090038989465368, -0.19524474258897667, 0.12564361933618784, -0.01608718151889615, 0.1747682196940532, 0.013312554318394702, 0.04668866673295023, 0.08931954784350375, 0.17966946241272203, 0.179812808592125, 0.15510255030072215, 0.04404279921732653, -0.14342080598097232, -0.29780266307673214, -0.08854860182401676, -0.1024502305653325, 0.03399967686352083, -0.012204766597093667, -0.18591231617571438, 0.36449086418280663, 0.13651142482472173, 0.0932873808857748, 0.10020198770088412, 0.28268616287416576, 0.15890174890548717, -0.05290430848155234, 0.08076347009736602, 0.29281167359628035, 0.15585905395969116, 0.11155059291207689, -0.2576897091595298, 0.061712152806063326, 0.17332040628228904] |
1,802.09682 | Probability Maximization via Minkowski Functionals: Convex
Representations and Tractable Resolution | In this paper, we consider the maximization of a probability $\mathbb{P}\{
\zeta \mid \zeta \in \mathbf{K}(\mathbf x)\}$ over a closed and convex set
$\mathcal X$, a special case of the chance-constrained optimization problem. We
define $\mathbf{K}(\mathbf x)$ as $\mathbf{K}(\mathbf x) \triangleq \{ \zeta
\in \mathcal{K} \mid c(\mathbf{x},\zeta) \geq 0 \}$ where $\zeta$ is uniformly
distributed on a convex and compact set $\mathcal{K}$ and $c(\mathbf{x},\zeta)$
is defined as either {$c(\mathbf{x},\zeta) \triangleq 1-|\zeta^T\mathbf{x}|^m$,
$m\geq 0$} (Setting A) or $c(\mathbf{x},\zeta) \triangleq T\mathbf{x} -\zeta$
(Setting B). We show that in either setting, $\mathbb{P}\{ \zeta \mid \zeta \in
\mathbf{K(x)}\}$ can be expressed as the expectation of a suitably defined
function $F(\mathbf{x},\xi)$ with respect to an appropriately defined Gaussian
density (or its variant), i.e. $\mathbb{E}_{\tilde p} [F(\mathbf x,\xi)]$. We
then develop a convex representation of the original problem requiring the
minimization of ${g(\mathbb{E}[F(\mathbf{x},\xi)])}$ over $\mathcal X$ where
$g$ is an appropriately defined smooth convex function. Traditional stochastic
approximation schemes cannot contend with the minimization of
${g(\mathbb{E}[F(\cdot,\xi)])}$ over $\mathcal X$, since conditionally unbiased
sampled gradients are unavailable. We then develop a regularized
variance-reduced stochastic approximation (r-VRSA) scheme that obviates the
need for such unbiasedness by combining iterative regularization with
variance-reduction. Notably, (r-VRSA) is characterized by both almost-sure
convergence guarantees, a convergence rate of $\mathcal{O}(1/k^{1/2-a})$ in
expected sub-optimality where $a > 0$, and a sample complexity of
$\mathcal{O}(1/\epsilon^{6+\delta})$ where $\delta > 0$.
| math.OC | in this paper we consider the maximization of a probability mathbbp zeta mid zeta in mathbfkmathbf x over a closed and convex set mathcal x a special case of the chanceconstrained optimization problem we define mathbfkmathbf x as mathbfkmathbf x triangleq zeta in mathcalk mid cmathbfxzeta geq 0 where zeta is uniformly distributed on a convex and compact set mathcalk and cmathbfxzeta is defined as either cmathbfxzeta triangleq 1zetatmathbfxm mgeq 0 setting a or cmathbfxzeta triangleq tmathbfx zeta setting b we show that in either setting mathbbp zeta mid zeta in mathbfkx can be expressed as the expectation of a suitably defined function fmathbfxxi with respect to an appropriately defined gaussian density or its variant ie mathbbe_tilde p fmathbf xxi we then develop a convex representation of the original problem requiring the minimization of gmathbbefmathbfxxi over mathcal x where g is an appropriately defined smooth convex function traditional stochastic approximation schemes cannot contend with the minimization of gmathbbefcdotxi over mathcal x since conditionally unbiased sampled gradients are unavailable we then develop a regularized variancereduced stochastic approximation rvrsa scheme that obviates the need for such unbiasedness by combining iterative regularization with variancereduction notably rvrsa is characterized by both almostsure convergence guarantees a convergence rate of mathcalo1k12a in expected suboptimality where a 0 and a sample complexity of mathcalo1epsilon6delta where delta 0 | [['in', 'this', 'paper', 'we', 'consider', 'the', 'maximization', 'of', 'a', 'probability', 'mathbbp', 'zeta', 'mid', 'zeta', 'in', 'mathbfkmathbf', 'x', 'over', 'a', 'closed', 'and', 'convex', 'set', 'mathcal', 'x', 'a', 'special', 'case', 'of', 'the', 'chanceconstrained', 'optimization', 'problem', 'we', 'define', 'mathbfkmathbf', 'x', 'as', 'mathbfkmathbf', 'x', 'triangleq', 'zeta', 'in', 'mathcalk', 'mid', 'cmathbfxzeta', 'geq', '0', 'where', 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1,802.09683 | The double-peaked radio light curve of PTF11qcj | We present continued radio follow-up observations of PTF11qcj, a highly
energetic broad-lined Type Ic supernova (SN), with a radio peak luminosity
comparable to that of the $\gamma$-ray burst (GRB) associated SN 1998bw. The
latest observations, carried out with the Karl G. Jansky Very Large Array
(VLA), extend up to $\sim$5 years after the PTF11qcj optical discovery. The
radio light curve shows a double-peak profile, possibly associated with density
variations in the circumstellar medium (CSM), or with the presence of an
off-axis GRB jet. Optical spectra of PTF11qcj taken during both peaks of the
radio light curve do not show the broad H$\alpha$ features typically expected
from H-rich circumstellar interaction. Modeling of the second radio peak within
the CSM interaction scenario requires a flatter density profile and an enhanced
progenitor mass-loss rate compared to those required to model the first peak.
Although our radio data alone cannot rule out the alternative scenario of an
off-axis GRB powering the second radio peak, the implied off-axis GRB
parameters are unusual compared to typical values found for cosmological long
GRBs. Deep X-ray observations carried out around the time of the second radio
peak could have helped distinguish between the density variation and off-axis
GRB scenarios. Future VLBA measurements of the PTF11qcj radio ejecta may
unambiguously rule out the off-axis GRB jet scenario.
| astro-ph.SR astro-ph.HE | we present continued radio followup observations of ptf11qcj a highly energetic broadlined type ic supernova sn with a radio peak luminosity comparable to that of the gammaray burst grb associated sn 1998bw the latest observations carried out with the karl g jansky very large array vla extend up to sim5 years after the ptf11qcj optical discovery the radio light curve shows a doublepeak profile possibly associated with density variations in the circumstellar medium csm or with the presence of an offaxis grb jet optical spectra of ptf11qcj taken during both peaks of the radio light curve do not show the broad halpha features typically expected from hrich circumstellar interaction modeling of the second radio peak within the csm interaction scenario requires a flatter density profile and an enhanced progenitor massloss rate compared to those required to model the first peak although our radio data alone cannot rule out the alternative scenario of an offaxis grb powering the second radio peak the implied offaxis grb parameters are unusual compared to typical values found for cosmological long grbs deep xray observations carried out around the time of the second radio peak could have helped distinguish between the density variation and offaxis grb scenarios future vlba measurements of the ptf11qcj radio ejecta may unambiguously rule out the offaxis grb jet scenario | [['we', 'present', 'continued', 'radio', 'followup', 'observations', 'of', 'ptf11qcj', 'a', 'highly', 'energetic', 'broadlined', 'type', 'ic', 'supernova', 'sn', 'with', 'a', 'radio', 'peak', 'luminosity', 'comparable', 'to', 'that', 'of', 'the', 'gammaray', 'burst', 'grb', 'associated', 'sn', '1998bw', 'the', 'latest', 'observations', 'carried', 'out', 'with', 'the', 'karl', 'g', 'jansky', 'very', 'large', 'array', 'vla', 'extend', 'up', 'to', 'sim5', 'years', 'after', 'the', 'ptf11qcj', 'optical', 'discovery', 'the', 'radio', 'light', 'curve', 'shows', 'a', 'doublepeak', 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1,802.09684 | Network Representation Using Graph Root Distributions | Exchangeable random graphs serve as an important probabilistic framework for
the statistical analysis of network data. In this work we develop an
alternative parameterization for a large class of exchangeable random graphs,
where the nodes are independent random vectors in a linear space equipped with
an indefinite inner product, and the edge probability between two nodes equals
the inner product of the corresponding node vectors. Therefore, the
distribution of exchangeable random graphs in this subclass can be represented
by a node sampling distribution on this linear space, which we call the graph
root distribution. We study existence and identifiability of such
representations, the topological relationship between the graph root
distribution and the exchangeable random graph sampling distribution, and
estimation of graph root distributions.
| math.ST stat.ME stat.TH | exchangeable random graphs serve as an important probabilistic framework for the statistical analysis of network data in this work we develop an alternative parameterization for a large class of exchangeable random graphs where the nodes are independent random vectors in a linear space equipped with an indefinite inner product and the edge probability between two nodes equals the inner product of the corresponding node vectors therefore the distribution of exchangeable random graphs in this subclass can be represented by a node sampling distribution on this linear space which we call the graph root distribution we study existence and identifiability of such representations the topological relationship between the graph root distribution and the exchangeable random graph sampling distribution and estimation of graph root distributions | [['exchangeable', 'random', 'graphs', 'serve', 'as', 'an', 'important', 'probabilistic', 'framework', 'for', 'the', 'statistical', 'analysis', 'of', 'network', 'data', 'in', 'this', 'work', 'we', 'develop', 'an', 'alternative', 'parameterization', 'for', 'a', 'large', 'class', 'of', 'exchangeable', 'random', 'graphs', 'where', 'the', 'nodes', 'are', 'independent', 'random', 'vectors', 'in', 'a', 'linear', 'space', 'equipped', 'with', 'an', 'indefinite', 'inner', 'product', 'and', 'the', 'edge', 'probability', 'between', 'two', 'nodes', 'equals', 'the', 'inner', 'product', 'of', 'the', 'corresponding', 'node', 'vectors', 'therefore', 'the', 'distribution', 'of', 'exchangeable', 'random', 'graphs', 'in', 'this', 'subclass', 'can', 'be', 'represented', 'by', 'a', 'node', 'sampling', 'distribution', 'on', 'this', 'linear', 'space', 'which', 'we', 'call', 'the', 'graph', 'root', 'distribution', 'we', 'study', 'existence', 'and', 'identifiability', 'of', 'such', 'representations', 'the', 'topological', 'relationship', 'between', 'the', 'graph', 'root', 'distribution', 'and', 'the', 'exchangeable', 'random', 'graph', 'sampling', 'distribution', 'and', 'estimation', 'of', 'graph', 'root', 'distributions']] | [-0.13818778174482588, 0.13426358518188317, -0.07081941637869288, 0.0734901963695278, -0.09955508682907112, -0.10215733895869547, 0.05103419297109774, 0.3876583808957319, -0.3235313131973693, -0.2654674371204725, 0.09198397600444079, -0.27378750896853643, -0.1704383334674971, 0.0748894194035026, -0.08407361602705972, 0.07709453482847146, 0.08930211439274433, 0.08900758119042569, -0.03302531798816914, -0.20093903421685555, 0.35908973760092705, 0.043319389731358224, 0.2823715251908312, -0.06027961198270806, 0.10768645444631243, 0.11044409587918742, -0.04098715211408652, 0.02899300547295848, -0.11784025511280369, 0.1426489021992538, 0.2784566578636991, 0.1547316642599611, 0.26980477846530454, -0.3687466763232539, -0.1769339361084186, 0.2197609612097343, 0.12743526643020955, 0.0361381647417443, 0.0018759496932152688, -0.27611488483967334, 0.07761610589346023, -0.19756634871104384, -0.07123496471639208, -0.016144831437708403, 0.011906223386768403, 0.06675952665197353, -0.3225358685675433, 0.016356629009048145, 0.0973161149531512, 0.055711612536958076, 0.019800339572744945, -0.13818208673378315, 0.00449892933048853, 0.12497837293696235, -0.041659893089435934, 0.016000258166539837, 0.0855841071125332, -0.07732734864206636, -0.16151059742608084, 0.3100765221487216, -0.032124837807462954, -0.2667206908174889, 0.126668151789837, -0.11297855812798792, -0.21391638787841893, 0.07511313436022861, 0.2331160262711649, 0.07490915028242076, -0.13311002381539683, 0.06773347611826791, -0.10933211538183495, 0.07565070882087528, 0.05403989693907097, 0.029482101574843007, 0.19021490223826917, 0.15181140928355052, 0.13661089606916274, 0.1915837116492155, -0.07832257742463512, -0.1080554142138614, -0.3120907218369648, -0.1610758226455712, -0.30167983247277635, 0.03566435954014854, -0.24889335056674114, -0.26566758980535393, 0.42176886330684266, 0.11486320555157112, 0.2533972416209375, 0.13744780043522425, 0.21551057881092636, 0.09751513326536804, 0.008770670075484408, 0.1415832205240168, 0.0659789639942507, 0.1961195977287352, -0.011749732455738434, -0.10499396440156591, 0.13892290296744766, 0.07063866602219035] |
1,802.09685 | Preservation of Indigenous Culture among Indigenous Migrants through
Social Media: the Igorot Peoples | The value and relevance of indigenous knowledge towards sustainability of
human societies drives for its preservation. This work explored the use of
Facebook groups to promote indigenous knowledge among Igorot peoples in the
diaspora. The virtual communities help intensify the connection of Igorot
migrants to their traditional culture despite the challenges of assimilation to
a different society. A survey of posts on 20 Facebook groups identified and
classified the indigenous cultural elements conveyed through social media. A
subsequent survey of 56 Igorot migrants revealed that popular social media has
a significant role in the exchange, revitalization, practice, and learning of
indigenous culture; inciting an effective medium to leverage preservation
strategies.
| cs.CY | the value and relevance of indigenous knowledge towards sustainability of human societies drives for its preservation this work explored the use of facebook groups to promote indigenous knowledge among igorot peoples in the diaspora the virtual communities help intensify the connection of igorot migrants to their traditional culture despite the challenges of assimilation to a different society a survey of posts on 20 facebook groups identified and classified the indigenous cultural elements conveyed through social media a subsequent survey of 56 igorot migrants revealed that popular social media has a significant role in the exchange revitalization practice and learning of indigenous culture inciting an effective medium to leverage preservation strategies | [['the', 'value', 'and', 'relevance', 'of', 'indigenous', 'knowledge', 'towards', 'sustainability', 'of', 'human', 'societies', 'drives', 'for', 'its', 'preservation', 'this', 'work', 'explored', 'the', 'use', 'of', 'facebook', 'groups', 'to', 'promote', 'indigenous', 'knowledge', 'among', 'igorot', 'peoples', 'in', 'the', 'diaspora', 'the', 'virtual', 'communities', 'help', 'intensify', 'the', 'connection', 'of', 'igorot', 'migrants', 'to', 'their', 'traditional', 'culture', 'despite', 'the', 'challenges', 'of', 'assimilation', 'to', 'a', 'different', 'society', 'a', 'survey', 'of', 'posts', 'on', '20', 'facebook', 'groups', 'identified', 'and', 'classified', 'the', 'indigenous', 'cultural', 'elements', 'conveyed', 'through', 'social', 'media', 'a', 'subsequent', 'survey', 'of', '56', 'igorot', 'migrants', 'revealed', 'that', 'popular', 'social', 'media', 'has', 'a', 'significant', 'role', 'in', 'the', 'exchange', 'revitalization', 'practice', 'and', 'learning', 'of', 'indigenous', 'culture', 'inciting', 'an', 'effective', 'medium', 'to', 'leverage', 'preservation', 'strategies']] | [-0.0956190624253147, 0.06502236975475997, -0.06797028062865137, 0.09530101562426849, -0.17099612324540928, -0.057916164988075086, 0.11819364681988108, 0.39765561571852726, -0.2560825458685444, -0.3161706056657501, 0.07091527589046481, -0.32706123686141586, -0.20360243521969426, 0.11548099789810791, -0.09212958998496933, -0.09304606072678738, 0.045985939372754234, 0.031638078321702776, 0.05923225963276557, -0.2969802229622887, 0.325795641109686, 0.056716950371099466, 0.3650784185092727, 0.07801856654272839, 0.10685366466218098, -0.01922907533907247, -0.13823042944158342, -0.04695626234805042, -0.08746360164295766, 0.21939432063055309, 0.38447009987959807, 0.2326668043197556, 0.4456480812196704, -0.4326921155845577, -0.20678756083890965, 0.07976155191321264, 0.16216375775719907, 0.04806841519576582, -0.05430403118635613, -0.3669845542447133, 0.026124604111960666, -0.23423977126155726, -0.14328621083193205, -0.03390751691873778, 0.03253498219207607, 0.005651783134618943, -0.11485763864210723, 0.0316816881793784, 0.009522443628520704, 0.18516273617913778, -0.0657575221742842, -0.1397991583005271, -0.04516782017255371, 0.29492163962938567, 0.10567652135664089, -0.041239318624138835, 0.193328263068741, -0.2086153785549951, -0.13578776323808017, 0.4015197266401215, -0.002737259077416225, -0.0660510600830259, 0.20188132475807585, -0.06104058631780473, -0.13827592374926265, 0.05833290590142662, 0.26221986349502746, 0.023468632109209218, -0.1697551222602752, -0.02085728154382774, -0.020884939071468333, 0.1697607381121171, 0.08178597844036466, -0.007125950704159384, 0.1984624407285909, 0.19335439638658003, 0.05619398320771076, 0.0313507131470198, 0.017600987802936948, -0.11614983292211863, -0.12694954417899929, -0.18235861794885502, -0.08923605081032623, 0.04386876666050574, -0.10607351849916581, -0.13491224759173664, 0.35918998411771924, 0.12507545287636193, 0.08213376361580396, -0.018531483818184247, 0.21922288354147565, -0.10412078680131923, 0.10960731675890698, 0.047479400809176946, 0.19081507549959828, 0.0641579503108832, 0.2707507868297398, -0.15777000055479054, 0.16116958740590648, -0.04047498728190972] |
1,802.09686 | A note on passing from a quasi-symmetric function expansion to a Schur
function expansion of a symmetric function | Egge, Loehr and Warrington gave in \cite{ELW} a combinatorial formula that
permits to convert the expansion of a symmetric function, homogeneous of degree
$n$, in terms of Gessel's fundamental quasisymmetric functions into an
expansion in terms of Schur functions. Surprisingly the Egge, Loehr and
Warrington result may be shown to be simply equivalent to replacing the Gessel
fundamental by a Schur function indexed by the same composition. In this paper
we give a direct proof of the validity of this replacement. This interpretation
of the result in \cite{ELW} has already been successfully applied to Schur
positivity problems.
| math.CO | egge loehr and warrington gave in citeelw a combinatorial formula that permits to convert the expansion of a symmetric function homogeneous of degree n in terms of gessels fundamental quasisymmetric functions into an expansion in terms of schur functions surprisingly the egge loehr and warrington result may be shown to be simply equivalent to replacing the gessel fundamental by a schur function indexed by the same composition in this paper we give a direct proof of the validity of this replacement this interpretation of the result in citeelw has already been successfully applied to schur positivity problems | [['egge', 'loehr', 'and', 'warrington', 'gave', 'in', 'citeelw', 'a', 'combinatorial', 'formula', 'that', 'permits', 'to', 'convert', 'the', 'expansion', 'of', 'a', 'symmetric', 'function', 'homogeneous', 'of', 'degree', 'n', 'in', 'terms', 'of', 'gessels', 'fundamental', 'quasisymmetric', 'functions', 'into', 'an', 'expansion', 'in', 'terms', 'of', 'schur', 'functions', 'surprisingly', 'the', 'egge', 'loehr', 'and', 'warrington', 'result', 'may', 'be', 'shown', 'to', 'be', 'simply', 'equivalent', 'to', 'replacing', 'the', 'gessel', 'fundamental', 'by', 'a', 'schur', 'function', 'indexed', 'by', 'the', 'same', 'composition', 'in', 'this', 'paper', 'we', 'give', 'a', 'direct', 'proof', 'of', 'the', 'validity', 'of', 'this', 'replacement', 'this', 'interpretation', 'of', 'the', 'result', 'in', 'citeelw', 'has', 'already', 'been', 'successfully', 'applied', 'to', 'schur', 'positivity', 'problems']] | [-0.08554275646119526, 0.056021828026860024, -0.1338577875769452, 0.05239132994810413, -0.11207021582675608, -0.06784489477347387, 0.03975596725082907, 0.28908512630548916, -0.2885190748070416, -0.24592822463202632, 0.0734380446607247, -0.17205295663228945, -0.19228646828989057, 0.19935846732635248, -0.12441592407657912, 0.017520228043002517, -0.009128670558627499, -0.011212856949944245, -0.07944553752642701, -0.29507923153180043, 0.2808300730649774, 0.05449467608214993, 0.22727726167558054, 0.12186467084102333, 0.07729851262840001, 0.04210352862841989, -0.052587173317902185, -0.0022953843697905542, -0.13366787769919028, 0.13382146385449328, 0.27082529682788603, 0.15236314610711385, 0.25006921822695355, -0.37246138712293225, -0.11484343529629865, 0.1417573847415808, 0.1895247407110506, 0.031152299075926607, -0.025687205409140962, -0.25527161948971056, 0.0711166720298168, -0.21736871828953122, -0.16897642984986305, -0.04886330726409429, 0.061906531815858264, 0.05063474660151099, -0.28894024340337826, 0.040729000693873356, 0.1319115820340812, 0.037770377565175296, -0.008931975605848588, -0.14851369240174167, 0.03663338071323539, 0.08552400304347668, 0.0002558949513752994, 0.07727667581486075, 0.002358300861363348, -0.09699331418807178, -0.15225779871015171, 0.35130498989632253, -0.03307923438321603, -0.23232604250507918, 0.11743390979735475, -0.1585362947055776, -0.16603472203408418, 0.1019668905236023, 0.06504093405643577, 0.13014320900761767, -0.12342990600552999, 0.14711436964448935, -0.14315785818586224, 0.07954842756428805, 0.19574691624821802, -0.013917443729741009, 0.13279671901653178, 0.0121557827793846, 0.037488551349624206, 0.24073203499306386, 0.1049297292961886, -0.052231976897210666, -0.2748441843610061, -0.20940371513562767, -0.20514607733409657, 0.12018277133373838, -0.11216123930337887, -0.22204892992771133, 0.41653685005087604, 0.06370705180482841, 0.1860250652130497, 0.08313452485752733, 0.22617571391165256, 0.16187389240060981, 0.09381235288456083, -0.018105834928390227, 0.17677878263945643, 0.24438441943769393, 0.06775121767269937, -0.1376218905170007, 0.08118582675233484, 0.23452802939634573] |
1,802.09687 | Simpler Specifications and Easier Proofs of Distributed Algorithms Using
History Variables | This paper studies specifications and proofs of distributed algorithms when
only message history variables are used, using the Basic Paxos and Multi-Paxos
algorithms for distributed consensus as precise case studies. We show that not
using and maintaining other state variables yields simpler specifications that
are more declarative and easier to understand. It also allows easier proofs to
be developed by needing fewer invariants and facilitating proof derivations.
Furthermore, the proofs are mechanically checked more efficiently.
We show that specifications in TLA+, Lamport's temporal logic of actions, and
proofs in TLAPS, the TLA+ Proof System (TLAPS) are reduced by a quarter or more
for single-value Paxos and by about half or more for multi-value Paxos. Overall
we need about half as many manually written invariants and proof obligations.
Our proof for Basic Paxos takes about 25% less time for TLAPS to check, and our
proofs for Multi-Paxos are checked within 1.5 minutes whereas prior proofs fail
to be checked by TLAPS.
| cs.DC cs.LO | this paper studies specifications and proofs of distributed algorithms when only message history variables are used using the basic paxos and multipaxos algorithms for distributed consensus as precise case studies we show that not using and maintaining other state variables yields simpler specifications that are more declarative and easier to understand it also allows easier proofs to be developed by needing fewer invariants and facilitating proof derivations furthermore the proofs are mechanically checked more efficiently we show that specifications in tla lamports temporal logic of actions and proofs in tlaps the tla proof system tlaps are reduced by a quarter or more for singlevalue paxos and by about half or more for multivalue paxos overall we need about half as many manually written invariants and proof obligations our proof for basic paxos takes about 25 less time for tlaps to check and our proofs for multipaxos are checked within 15 minutes whereas prior proofs fail to be checked by tlaps | [['this', 'paper', 'studies', 'specifications', 'and', 'proofs', 'of', 'distributed', 'algorithms', 'when', 'only', 'message', 'history', 'variables', 'are', 'used', 'using', 'the', 'basic', 'paxos', 'and', 'multipaxos', 'algorithms', 'for', 'distributed', 'consensus', 'as', 'precise', 'case', 'studies', 'we', 'show', 'that', 'not', 'using', 'and', 'maintaining', 'other', 'state', 'variables', 'yields', 'simpler', 'specifications', 'that', 'are', 'more', 'declarative', 'and', 'easier', 'to', 'understand', 'it', 'also', 'allows', 'easier', 'proofs', 'to', 'be', 'developed', 'by', 'needing', 'fewer', 'invariants', 'and', 'facilitating', 'proof', 'derivations', 'furthermore', 'the', 'proofs', 'are', 'mechanically', 'checked', 'more', 'efficiently', 'we', 'show', 'that', 'specifications', 'in', 'tla', 'lamports', 'temporal', 'logic', 'of', 'actions', 'and', 'proofs', 'in', 'tlaps', 'the', 'tla', 'proof', 'system', 'tlaps', 'are', 'reduced', 'by', 'a', 'quarter', 'or', 'more', 'for', 'singlevalue', 'paxos', 'and', 'by', 'about', 'half', 'or', 'more', 'for', 'multivalue', 'paxos', 'overall', 'we', 'need', 'about', 'half', 'as', 'many', 'manually', 'written', 'invariants', 'and', 'proof', 'obligations', 'our', 'proof', 'for', 'basic', 'paxos', 'takes', 'about', '25', 'less', 'time', 'for', 'tlaps', 'to', 'check', 'and', 'our', 'proofs', 'for', 'multipaxos', 'are', 'checked', 'within', '15', 'minutes', 'whereas', 'prior', 'proofs', 'fail', 'to', 'be', 'checked', 'by', 'tlaps']] | [-0.09408586680874578, 0.029982439717423405, -0.1053805404168088, 0.11611097262284602, -0.13402849525446073, -0.2327956277615158, 0.07978803886289824, 0.3961112222634256, -0.20756243273208383, -0.3573120093322359, 0.16965474058815744, -0.21564031365132905, -0.09002880473562982, 0.26304740878695154, -0.1021794029235025, 0.06063057326828129, 0.07849936630955198, -0.009575847027008422, -0.05167749772517709, -0.3103733738360461, 0.2348189808326424, 0.017570618496392854, 0.19215480687562375, 0.021752299039508215, 0.05201490870676935, 0.044684669458365536, -0.03730947330477648, -0.005499116861028597, -0.09139759526365196, 0.10848805475397967, 0.2997722823127333, 0.21381271950085648, 0.2610412363195792, -0.4901566893560812, -0.09773307968280279, 0.0421924175490858, 0.1827818788442528, 0.12836014086460637, 0.032217533535367694, -0.3029819078888977, 0.1647451641736552, -0.16566383992612826, -0.09218935273529497, -0.17204351475229487, 0.01757806496170815, 0.02746657228562981, -0.2103253912719083, 0.0036054349284313503, 0.15470212283544243, 0.1060203387576621, 0.009787474821132491, -0.13891646642514388, -0.008719374469364993, 0.09713455299151974, 0.002216469630366191, -0.013916364661417902, 0.1335468277306063, -0.0391673911435646, -0.14973120966897113, 0.35172717839595863, 0.038871210020442956, -0.19415862373662093, 0.17868942760615028, -0.04188436326803639, -0.16288793398998677, 0.07406621109694242, 0.08614576972322538, 0.14884066714830624, -0.17436978984524104, 0.005845258300178102, -0.02068832958539133, 0.2740426780539565, 0.10050620442343643, 0.04883674071461428, 0.1269708350824658, 0.12345930504816352, 0.0625770418668253, 0.12145968032891688, 0.08367451004160102, -0.15126446529611712, -0.2756644193665124, -0.1742513078432239, -0.11147126791474875, 0.009770071658658707, -0.07261662301743854, -0.11564723559422418, 0.3623138827650109, 0.19595271740108727, 0.09263996570371091, 0.1769254964485299, 0.32922783197718675, 0.051420572091592474, 0.10375942211248912, 0.11867452762671746, 0.1547302564897109, 0.11367200697859517, 0.1405826538160909, -0.06894353253428562, 0.15138174702588003, 0.08731390707107493] |
1,802.09688 | The last 5 Gyr of Galactic chemical evolution based on H II region
abundances derived from a temperature independent method | Most of the chemical evolution models are not very reliable for the last
5~Gyr of galactic evolution; this is mainly because abundance gradients found
in the literature show a big dispersion for young objects; a big culprit of
this is the dispersion found in HII region gradients. Part of this dispersion
arises from two different methods used to determine O/H in HII regions: the
direct method (DM), based on forbidden lines; and the temperature independent
method (TIM), based on permitted lines; the differences between these two
methods are about 0.25~dex. We present two chemical evolution models of our
galaxy to fit the O/H gradients of HII regions, one obtained from the DM and
the other obtained from the TIM. We find that the model based on the TIM
produces an excellent fit to the observational stellar constraints (B-stars,
Cepheids, and the Sun), while the model based on the DM fails to reproduce
them. Moreover the TIM model reproduces the flattening observed in the 3-6 kpc
galactocentric range; this flattening is attained with an inside-out star
formation quenching in the inner disk starting ~ 9 Gyr ago.
| astro-ph.GA | most of the chemical evolution models are not very reliable for the last 5gyr of galactic evolution this is mainly because abundance gradients found in the literature show a big dispersion for young objects a big culprit of this is the dispersion found in hii region gradients part of this dispersion arises from two different methods used to determine oh in hii regions the direct method dm based on forbidden lines and the temperature independent method tim based on permitted lines the differences between these two methods are about 025dex we present two chemical evolution models of our galaxy to fit the oh gradients of hii regions one obtained from the dm and the other obtained from the tim we find that the model based on the tim produces an excellent fit to the observational stellar constraints bstars cepheids and the sun while the model based on the dm fails to reproduce them moreover the tim model reproduces the flattening observed in the 36 kpc galactocentric range this flattening is attained with an insideout star formation quenching in the inner disk starting 9 gyr ago | [['most', 'of', 'the', 'chemical', 'evolution', 'models', 'are', 'not', 'very', 'reliable', 'for', 'the', 'last', '5gyr', 'of', 'galactic', 'evolution', 'this', 'is', 'mainly', 'because', 'abundance', 'gradients', 'found', 'in', 'the', 'literature', 'show', 'a', 'big', 'dispersion', 'for', 'young', 'objects', 'a', 'big', 'culprit', 'of', 'this', 'is', 'the', 'dispersion', 'found', 'in', 'hii', 'region', 'gradients', 'part', 'of', 'this', 'dispersion', 'arises', 'from', 'two', 'different', 'methods', 'used', 'to', 'determine', 'oh', 'in', 'hii', 'regions', 'the', 'direct', 'method', 'dm', 'based', 'on', 'forbidden', 'lines', 'and', 'the', 'temperature', 'independent', 'method', 'tim', 'based', 'on', 'permitted', 'lines', 'the', 'differences', 'between', 'these', 'two', 'methods', 'are', 'about', '025dex', 'we', 'present', 'two', 'chemical', 'evolution', 'models', 'of', 'our', 'galaxy', 'to', 'fit', 'the', 'oh', 'gradients', 'of', 'hii', 'regions', 'one', 'obtained', 'from', 'the', 'dm', 'and', 'the', 'other', 'obtained', 'from', 'the', 'tim', 'we', 'find', 'that', 'the', 'model', 'based', 'on', 'the', 'tim', 'produces', 'an', 'excellent', 'fit', 'to', 'the', 'observational', 'stellar', 'constraints', 'bstars', 'cepheids', 'and', 'the', 'sun', 'while', 'the', 'model', 'based', 'on', 'the', 'dm', 'fails', 'to', 'reproduce', 'them', 'moreover', 'the', 'tim', 'model', 'reproduces', 'the', 'flattening', 'observed', 'in', 'the', '36', 'kpc', 'galactocentric', 'range', 'this', 'flattening', 'is', 'attained', 'with', 'an', 'insideout', 'star', 'formation', 'quenching', 'in', 'the', 'inner', 'disk', 'starting', '9', 'gyr', 'ago']] | [-0.04740182301029563, 0.04239602945634869, -0.08935956126810492, 0.09706751045431136, -0.06445055975817848, -0.049421563861038964, 0.02769544806356567, 0.4120889843416375, -0.20572736597984928, -0.35176501979396957, 0.03109103090230476, -0.24962623704828926, -0.047009784317885314, 0.20716154617760835, -0.02440983480537889, -0.04155596431621627, 0.03185021201198971, -0.049031461742580745, -0.05164154375261451, -0.2673564963420299, 0.310037099685822, 0.03743924681990835, 0.19539121707580429, 0.0009865708595277062, 0.03811430012794664, -0.12403916571213788, -0.07884966269437525, -0.02032439805869315, -0.1680942352447813, 0.12481286518678472, 0.20554424818731826, 0.11075026731135015, 0.19479409682790974, -0.37688617016616704, -0.2460648157457645, 0.07955588319754178, 0.18722933966767144, 0.0916884004478217, -0.07326529680222675, -0.2446186618527045, 0.05272605295758694, -0.15315909300163086, -0.13809307011196742, 0.07633794358100843, 0.032909785758867556, -0.005018287519861416, -0.2270568070706685, 0.13477395595730962, 0.01694331110228558, 0.09657188205400834, -0.09459093327483012, -0.15661968423204647, -0.058162464670887266, 0.11106593985286717, 0.035783815066128766, 0.03865024409684781, 0.17084010256001272, -0.1093731080848925, -0.0387543465187018, 0.39907657964708837, -0.07941076747054074, -0.04228340569078117, 0.24408630869112205, -0.1748573177418596, -0.1644754414194943, 0.10832366415526012, 0.09579857640421471, 0.1072658981542682, -0.14296034044661635, 0.06197188450558413, -0.015017004638306193, 0.2020120309917508, 0.04100973208409709, -0.013994151717476623, 0.27825123563006116, 0.10485810078680516, 0.0521876121946686, 0.06573003627756309, -0.16979665558020635, -0.11088137631430417, -0.25967624684625834, -0.10043939191822869, -0.119693406352874, -0.013130966061647554, -0.14165206991562407, -0.13563552921688235, 0.34809136081713477, 0.14541797818918084, 0.2651594183942605, 0.035884946233567756, 0.308898979274405, 0.07694036857212415, 0.10469920119177079, 0.12925862000147637, 0.3102074373815511, 0.17840174550845012, 0.10799212664038547, -0.2671435463330331, 0.10659351026689684, 0.016096659936010838] |
1,802.09689 | Adaptive sliding mode control without knowledge of uncertainty bounds | This paper proposes a new adaptation methodology to find the control inputs
for a class of nonlinear systems with time-varying bounded uncertainties. The
proposed method does not require any prior knowledge of the uncertainties
including their bounds. The main idea is developed under the structure of
adaptive sliding mode control; an update law decreases the gain inside and
increases the gain outside a vicinity of the sliding surface. The semi-global
stability of the closed-loop system and the adaptation error are guaranteed by
Lyapunov theory. The simulation results show that the proposed adaptation
methodology can reduce the magnitude of the controller gain to the minimum
possible value and smooth out the chattering.
| math.OC cs.SY | this paper proposes a new adaptation methodology to find the control inputs for a class of nonlinear systems with timevarying bounded uncertainties the proposed method does not require any prior knowledge of the uncertainties including their bounds the main idea is developed under the structure of adaptive sliding mode control an update law decreases the gain inside and increases the gain outside a vicinity of the sliding surface the semiglobal stability of the closedloop system and the adaptation error are guaranteed by lyapunov theory the simulation results show that the proposed adaptation methodology can reduce the magnitude of the controller gain to the minimum possible value and smooth out the chattering | [['this', 'paper', 'proposes', 'a', 'new', 'adaptation', 'methodology', 'to', 'find', 'the', 'control', 'inputs', 'for', 'a', 'class', 'of', 'nonlinear', 'systems', 'with', 'timevarying', 'bounded', 'uncertainties', 'the', 'proposed', 'method', 'does', 'not', 'require', 'any', 'prior', 'knowledge', 'of', 'the', 'uncertainties', 'including', 'their', 'bounds', 'the', 'main', 'idea', 'is', 'developed', 'under', 'the', 'structure', 'of', 'adaptive', 'sliding', 'mode', 'control', 'an', 'update', 'law', 'decreases', 'the', 'gain', 'inside', 'and', 'increases', 'the', 'gain', 'outside', 'a', 'vicinity', 'of', 'the', 'sliding', 'surface', 'the', 'semiglobal', 'stability', 'of', 'the', 'closedloop', 'system', 'and', 'the', 'adaptation', 'error', 'are', 'guaranteed', 'by', 'lyapunov', 'theory', 'the', 'simulation', 'results', 'show', 'that', 'the', 'proposed', 'adaptation', 'methodology', 'can', 'reduce', 'the', 'magnitude', 'of', 'the', 'controller', 'gain', 'to', 'the', 'minimum', 'possible', 'value', 'and', 'smooth', 'out', 'the', 'chattering']] | [-0.14121295510464021, 0.03857722873539928, -0.09758594779817907, -0.002612910256511322, -0.08864205646085309, -0.12217644823144551, 0.08394624522325021, 0.3240195134432298, -0.29762455883125466, -0.32073226703649704, 0.1338966791706814, -0.1931942743375092, -0.18311134907878465, 0.19891646066428842, -0.14400757165407543, 0.11992623629300175, 0.045603954239521884, 0.038197367525500084, -0.07699983273181846, -0.2359567626981434, 0.296654878716983, 0.07494989502335991, 0.32397019896663615, 0.023345691405198966, 0.12111553373150863, -0.008413097949128027, -0.038102578338202055, -0.0008248737467838837, -0.14659100134369576, 0.10639682288810208, 0.21135430487695042, 0.12643972810290688, 0.3674191704443614, -0.3707068475248577, -0.2359614356563569, 0.10812094816015111, 0.13230801214724108, 0.10898500823138936, -0.04034533687271513, -0.27848778470410956, 0.1235288330479651, -0.15983927480012244, -0.15164004979017484, -0.061554145917447435, -0.051472541578281836, 0.04348121676803776, -0.32657755555024975, 0.04017196569658883, 0.1013380753879041, 0.02470038886609915, -0.09866473045586063, -0.08602315645459369, -0.02782144287164818, 0.1467940765244232, 0.017744307295075274, 0.0039004160737333535, 0.18537151551729925, -0.07714173367020448, -0.11836343616045811, 0.32206465626504643, -0.03422760233694167, -0.2272591284635636, 0.14648204641878135, -0.09204332666840774, -0.04313336692143206, 0.17920599997815517, 0.20462193309019008, 0.10281182225587251, -0.13652183720894442, 0.06023592010050224, 0.018435501082389203, 0.21703297029478005, 0.01255610285259716, 0.012609724949642614, 0.14296603332869373, 0.2060708245849824, 0.15761700955530009, 0.12958678725880343, -0.09043075286716155, -0.12622676905599078, -0.33417676419841946, -0.0900588450483508, -0.14708494005786665, -0.04684032387137392, -0.11592334197157142, -0.15204214114540568, 0.3912598610025, 0.16539952575505987, 0.13855875081693134, 0.12499221500537887, 0.3512983999743655, 0.12940642559850538, 0.07144118160605095, 0.10273965023592249, 0.2810672999502302, 0.10274901725184005, 0.11293495925529315, -0.3131698744501583, 0.11176101525465178, 0.03681932098212807] |
1,802.0969 | Binary Star Fractions from the LAMOST DR4 | Stellar systems composed of single, double, triple or high-order systems are
rightfully regarded as the fundamental building blocks of the Milky Way. Binary
stars play an important role in formation and evolution of the Galaxy. Through
comparing the radial velocity variations from multi-epoch observations, we
analyze the binary fraction of dwarf stars observed with the LAMOST. Effects of
different model assumptions such as orbital period distributions on the
estimate of binary fractions, are investigated. The results based on log-normal
distribution of orbital periods reproduce the previous complete analyses better
than the power-law distribution. We find that the binary fraction increases
with $T_{\rm eff}$ and decreases with [Fe/H]. We first investigate the relation
between $\alpha$-elements and binary fraction in such a large sample as the
LAMOST. The old stars with high [$\alpha$/Fe] dominate higher binary fraction
than young stars with low [$\alpha$/Fe]. At the same mass, former forming stars
possess a higher binary fraction than newly forming ones, which may be related
with the evolution of the Galaxy.
| astro-ph.SR astro-ph.GA | stellar systems composed of single double triple or highorder systems are rightfully regarded as the fundamental building blocks of the milky way binary stars play an important role in formation and evolution of the galaxy through comparing the radial velocity variations from multiepoch observations we analyze the binary fraction of dwarf stars observed with the lamost effects of different model assumptions such as orbital period distributions on the estimate of binary fractions are investigated the results based on lognormal distribution of orbital periods reproduce the previous complete analyses better than the powerlaw distribution we find that the binary fraction increases with t_rm eff and decreases with feh we first investigate the relation between alphaelements and binary fraction in such a large sample as the lamost the old stars with high alphafe dominate higher binary fraction than young stars with low alphafe at the same mass former forming stars possess a higher binary fraction than newly forming ones which may be related with the evolution of the galaxy | [['stellar', 'systems', 'composed', 'of', 'single', 'double', 'triple', 'or', 'highorder', 'systems', 'are', 'rightfully', 'regarded', 'as', 'the', 'fundamental', 'building', 'blocks', 'of', 'the', 'milky', 'way', 'binary', 'stars', 'play', 'an', 'important', 'role', 'in', 'formation', 'and', 'evolution', 'of', 'the', 'galaxy', 'through', 'comparing', 'the', 'radial', 'velocity', 'variations', 'from', 'multiepoch', 'observations', 'we', 'analyze', 'the', 'binary', 'fraction', 'of', 'dwarf', 'stars', 'observed', 'with', 'the', 'lamost', 'effects', 'of', 'different', 'model', 'assumptions', 'such', 'as', 'orbital', 'period', 'distributions', 'on', 'the', 'estimate', 'of', 'binary', 'fractions', 'are', 'investigated', 'the', 'results', 'based', 'on', 'lognormal', 'distribution', 'of', 'orbital', 'periods', 'reproduce', 'the', 'previous', 'complete', 'analyses', 'better', 'than', 'the', 'powerlaw', 'distribution', 'we', 'find', 'that', 'the', 'binary', 'fraction', 'increases', 'with', 't_rm', 'eff', 'and', 'decreases', 'with', 'feh', 'we', 'first', 'investigate', 'the', 'relation', 'between', 'alphaelements', 'and', 'binary', 'fraction', 'in', 'such', 'a', 'large', 'sample', 'as', 'the', 'lamost', 'the', 'old', 'stars', 'with', 'high', 'alphafe', 'dominate', 'higher', 'binary', 'fraction', 'than', 'young', 'stars', 'with', 'low', 'alphafe', 'at', 'the', 'same', 'mass', 'former', 'forming', 'stars', 'possess', 'a', 'higher', 'binary', 'fraction', 'than', 'newly', 'forming', 'ones', 'which', 'may', 'be', 'related', 'with', 'the', 'evolution', 'of', 'the', 'galaxy']] | [-0.08240057567614102, 0.16162800755497125, -0.06983511304638967, 0.08586612630992414, -0.07857238202534259, -0.04143893127580603, 0.05581858160370169, 0.36283490202294855, -0.17500066509593032, -0.3839507657465731, 0.010867788516330773, -0.30801672649776846, -0.049176935812196634, 0.2176916058911401, -0.024734273681160577, -0.015426744534048492, 0.10847818708287073, -0.0320109660084733, -0.09624141921891557, -0.2893336578857845, 0.3215662173224156, 0.06963556557670682, 0.1550280566990911, -0.12268431807176662, 0.02600157339248561, -0.03663731395813475, -0.06272037317338511, -0.026859816478866483, -0.14156312558579176, 0.036459183523955635, 0.21339581242879618, 0.10686344703280194, 0.20144084029033513, -0.33678345991734066, -0.19591596749092557, 0.07370215937603979, 0.21011570596810944, 0.04396838289587954, -0.09257600469999908, -0.2048930107179505, 0.09720815860591048, -0.22536117455804955, -0.17356371742458512, 0.03561970065096895, 0.04529715629997189, 0.09623090390737787, -0.2106006225169508, 0.16316475701995173, 0.055412812571147246, 0.1052511665178184, -0.12738655965976015, -0.19734001118818043, -0.09844611453807015, 0.12000707731983752, 0.017412855383984654, 0.055263701137601436, 0.12537240070251826, -0.11863170426009881, -0.01799446319280092, 0.422581253405995, -0.12263853833611572, -0.0558901561265895, 0.21023973731273884, -0.21271969993392417, -0.17803024598010425, 0.08438552987293346, 0.19839668716722264, 0.1606232650092842, -0.1268818430563513, -0.03782120214940417, -0.011184163268900918, 0.22222185426971647, 0.052455936251821635, 0.09649670057707678, 0.3597307772581984, 0.15170527597008174, 0.0015484337167937063, 0.09415410669913661, -0.19763089306262172, -0.11109158734395029, -0.19410625398145084, -0.1113315773528337, -0.10769092484131947, 0.059636447071355715, -0.17025697080972313, -0.1513031752282352, 0.3002889730359712, 0.06963407791228017, 0.27667914844302094, 0.06625228038567961, 0.2606965831653801, 0.122535586758645, 0.13303220189222856, 0.09905437829564075, 0.2681502358497171, 0.1933077342604694, 0.0547143821569695, -0.25702113959196576, 0.14332116733466882, -0.005947403241685051] |
1,802.09691 | Link Prediction Based on Graph Neural Networks | Link prediction is a key problem for network-structured data. Link prediction
heuristics use some score functions, such as common neighbors and Katz index,
to measure the likelihood of links. They have obtained wide practical uses due
to their simplicity, interpretability, and for some of them, scalability.
However, every heuristic has a strong assumption on when two nodes are likely
to link, which limits their effectiveness on networks where these assumptions
fail. In this regard, a more reasonable way should be learning a suitable
heuristic from a given network instead of using predefined ones. By extracting
a local subgraph around each target link, we aim to learn a function mapping
the subgraph patterns to link existence, thus automatically learning a
`heuristic' that suits the current network. In this paper, we study this
heuristic learning paradigm for link prediction. First, we develop a novel
$\gamma$-decaying heuristic theory. The theory unifies a wide range of
heuristics in a single framework, and proves that all these heuristics can be
well approximated from local subgraphs. Our results show that local subgraphs
reserve rich information related to link existence. Second, based on the
$\gamma$-decaying theory, we propose a new algorithm to learn heuristics from
local subgraphs using a graph neural network (GNN). Its experimental results
show unprecedented performance, working consistently well on a wide range of
problems.
| cs.LG stat.ML | link prediction is a key problem for networkstructured data link prediction heuristics use some score functions such as common neighbors and katz index to measure the likelihood of links they have obtained wide practical uses due to their simplicity interpretability and for some of them scalability however every heuristic has a strong assumption on when two nodes are likely to link which limits their effectiveness on networks where these assumptions fail in this regard a more reasonable way should be learning a suitable heuristic from a given network instead of using predefined ones by extracting a local subgraph around each target link we aim to learn a function mapping the subgraph patterns to link existence thus automatically learning a heuristic that suits the current network in this paper we study this heuristic learning paradigm for link prediction first we develop a novel gammadecaying heuristic theory the theory unifies a wide range of heuristics in a single framework and proves that all these heuristics can be well approximated from local subgraphs our results show that local subgraphs reserve rich information related to link existence second based on the gammadecaying theory we propose a new algorithm to learn heuristics from local subgraphs using a graph neural network gnn its experimental results show unprecedented performance working consistently well on a wide range of problems | [['link', 'prediction', 'is', 'a', 'key', 'problem', 'for', 'networkstructured', 'data', 'link', 'prediction', 'heuristics', 'use', 'some', 'score', 'functions', 'such', 'as', 'common', 'neighbors', 'and', 'katz', 'index', 'to', 'measure', 'the', 'likelihood', 'of', 'links', 'they', 'have', 'obtained', 'wide', 'practical', 'uses', 'due', 'to', 'their', 'simplicity', 'interpretability', 'and', 'for', 'some', 'of', 'them', 'scalability', 'however', 'every', 'heuristic', 'has', 'a', 'strong', 'assumption', 'on', 'when', 'two', 'nodes', 'are', 'likely', 'to', 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1,802.09692 | A perturbation approach for Paneitz energy on standard three sphere | We present another proof of the sharp inequality for Paneitz operator on the
standard three sphere, in the spirit of subcritical approximation for the
classical Yamabe problem. To solve the perturbed problem, we use a
symmetrization process which only works for extremal functions. This gives a
new example of symmetrization for higher order variational problems.
| math.AP math.DG | we present another proof of the sharp inequality for paneitz operator on the standard three sphere in the spirit of subcritical approximation for the classical yamabe problem to solve the perturbed problem we use a symmetrization process which only works for extremal functions this gives a new example of symmetrization for higher order variational problems | [['we', 'present', 'another', 'proof', 'of', 'the', 'sharp', 'inequality', 'for', 'paneitz', 'operator', 'on', 'the', 'standard', 'three', 'sphere', 'in', 'the', 'spirit', 'of', 'subcritical', 'approximation', 'for', 'the', 'classical', 'yamabe', 'problem', 'to', 'solve', 'the', 'perturbed', 'problem', 'we', 'use', 'a', 'symmetrization', 'process', 'which', 'only', 'works', 'for', 'extremal', 'functions', 'this', 'gives', 'a', 'new', 'example', 'of', 'symmetrization', 'for', 'higher', 'order', 'variational', 'problems']] | [-0.09310671685856174, 0.008858743360774083, -0.061393129215999084, 0.1407180090637584, -0.12213871106505395, -0.15435006457634948, 0.028707061322744597, 0.2624487061392177, -0.29657846892421896, -0.24618973271413283, 0.14377216654406352, -0.27947327870536937, -0.16585344990546053, 0.20601865043016998, -0.08116100164638325, 0.11139057202433998, 0.06506257375532931, 0.040093548257242546, -0.12046744815835898, -0.23458385108546778, 0.3986289606852965, -0.028159529580311343, 0.21751850040798837, 0.09920893184502017, 0.10855973859063604, 0.03941376155919649, 0.04907821508293802, -0.016057206470180642, -0.18600727591494268, 0.1791782829529521, 0.19480294681746851, 0.09665980471128767, 0.3022830670191483, -0.39629929106343875, -0.20642802989618345, 0.14618959731676362, 0.14722403259101238, 0.09805667592339556, -0.0611671204615215, -0.24419012186540798, 0.04662053503773429, -0.0950817222029648, -0.20158270252021876, -0.06273465240374207, -0.03198731266470118, -0.03396852670068091, -0.30215128629722376, 0.13874430870637297, 0.14745722335170616, -0.024361830975183033, -0.09615632153370164, -0.1130900920919058, 0.10304905542553487, 0.04292567905715921, 0.019406398927094413, 0.03880513275931166, 0.048047624570740896, -0.05475819963877174, -0.15502308367497541, 0.33420316385613247, -0.04669216562443498, -0.260742818123915, 0.1276544123549353, -0.09954954529689117, -0.22148013257167556, 0.061483265442604365, 0.180497429181229, 0.21804714632982558, -0.11894525604491885, 0.11897814797914841, -0.07717957073314623, 0.08431095558811318, 0.1301815347068689, -0.051816560751335186, 0.03191542482342232, 0.10317819909277287, 0.21802577219734137, 0.21005164110525087, -0.007808070227673108, -0.1457351861182939, -0.3481827613304962, -0.19452119374817067, -0.20213817816905, 0.09659374789334833, -0.13227712644094772, -0.21901451030492106, 0.3818847634787248, 0.09500048947414722, 0.16132025749168613, 0.09077804290308532, 0.25991844258863817, 0.18070413558320567, 0.015053226583933627, 0.05948057591237805, 0.236279524337839, 0.17127295556393538, 0.13878579563884572, -0.14351503303359178, -0.014502124344422058, 0.2403853388249197] |
1,802.09693 | Demazure construction for Z^n-graded Krull domains | For a Mori dream space X, the Cox ring Cox(X) is a Noetherian Z^n-graded
normal domain for some n > 0. Let C(Cox(X)) be the cone (in R^n) which is
spanned by the vectors a \in Z^n such that Cox(X)_a \neq 0. Then C(Cox(X)) is
decomposed into a union of chambers. Berchtold and Hausen proved the existence
of such decompositions for affine integral domains over an algebraically closed
field. We shall give an elementary algebraic proof to this result in the case
where the homogeneous component of degree 0 is a field.
Using such decompositions, we develop the Demazure construction for
Z^n-graded Krull domains. That is, under an assumption, we show that a
Z^n-graded Krull domain is isomorphic to the multi-section ring R(X; D_1,
\ldots, D_n) for certain normal projective variety X and Q-divisors D_1,...,D_n
on X.
| math.AC math.AG | for a mori dream space x the cox ring coxx is a noetherian zngraded normal domain for some n 0 let ccoxx be the cone in rn which is spanned by the vectors a in zn such that coxx_a neq 0 then ccoxx is decomposed into a union of chambers berchtold and hausen proved the existence of such decompositions for affine integral domains over an algebraically closed field we shall give an elementary algebraic proof to this result in the case where the homogeneous component of degree 0 is a field using such decompositions we develop the demazure construction for zngraded krull domains that is under an assumption we show that a zngraded krull domain is isomorphic to the multisection ring rx d_1 ldots d_n for certain normal projective variety x and qdivisors d_1d_n on x | [['for', 'a', 'mori', 'dream', 'space', 'x', 'the', 'cox', 'ring', 'coxx', 'is', 'a', 'noetherian', 'zngraded', 'normal', 'domain', 'for', 'some', 'n', '0', 'let', 'ccoxx', 'be', 'the', 'cone', 'in', 'rn', 'which', 'is', 'spanned', 'by', 'the', 'vectors', 'a', 'in', 'zn', 'such', 'that', 'coxx_a', 'neq', '0', 'then', 'ccoxx', 'is', 'decomposed', 'into', 'a', 'union', 'of', 'chambers', 'berchtold', 'and', 'hausen', 'proved', 'the', 'existence', 'of', 'such', 'decompositions', 'for', 'affine', 'integral', 'domains', 'over', 'an', 'algebraically', 'closed', 'field', 'we', 'shall', 'give', 'an', 'elementary', 'algebraic', 'proof', 'to', 'this', 'result', 'in', 'the', 'case', 'where', 'the', 'homogeneous', 'component', 'of', 'degree', '0', 'is', 'a', 'field', 'using', 'such', 'decompositions', 'we', 'develop', 'the', 'demazure', 'construction', 'for', 'zngraded', 'krull', 'domains', 'that', 'is', 'under', 'an', 'assumption', 'we', 'show', 'that', 'a', 'zngraded', 'krull', 'domain', 'is', 'isomorphic', 'to', 'the', 'multisection', 'ring', 'rx', 'd_1', 'ldots', 'd_n', 'for', 'certain', 'normal', 'projective', 'variety', 'x', 'and', 'qdivisors', 'd_1d_n', 'on', 'x']] | [-0.20117314358128968, 0.0723988031416163, -0.0766487625977871, 0.010819720476072027, -0.07319431734151405, -0.14530393525395388, -0.05925647536236228, 0.3717732791873542, -0.37931454613466153, -0.08983293659702847, 0.11328553051289143, -0.2242610335639311, -0.07960479570575638, 0.19674658011927298, -0.11822242417132878, -0.10443133657276066, -0.024542746231115114, 0.09469891934316944, -0.07197790695389619, -0.29838503442817566, 0.3740022696667548, -0.11721366626972501, 0.23091147125303518, 0.027806926714027104, 0.13560866997012813, 0.021331448774700137, 0.04302721103004208, 0.006372804257614806, -0.19954344118978593, 0.08347580179388663, 0.34043191564375197, 0.1347249998238333, 0.21068017234210856, -0.3737433289855041, -0.11624672928111536, 0.22503569560958017, 0.19393197526082848, -0.04998942346146302, -0.0029619557590745953, -0.2553793931023613, 0.14021748709351275, -0.14228899034975312, -0.17787269010053328, -0.06969646895022104, 0.11674167811405355, 0.021276517638894307, -0.32550253205452906, -0.038055607907925594, 0.14209716551175172, 0.14738237236231339, -0.04430734472627977, -0.13644034988299775, -0.018377753644899436, 0.010014026224697855, -0.04929358137870264, 0.11771216454464152, 0.047955904483608196, -0.06707738878586414, -0.09438686025201935, 0.3167643673068872, -0.07454340287597117, -0.2724082137204029, 0.1150033175676292, -0.19686897430272604, -0.09906087295773129, 0.13856944657692855, 0.054725748846646056, 0.18228899486800373, -0.006139140089296482, 0.2416477426383856, -0.17770005108534612, 0.09240556977491712, 0.09668383743105964, -0.008555323883862884, 0.12054149800855102, 0.11593026550006912, 0.09273231715346672, 0.11057015244097618, -0.015380874543387274, 0.0274152093193014, -0.39477613226821023, -0.23510852458055137, -0.1752026810339003, 0.2144693485990336, -0.10069448401720199, -0.15948957983037512, 0.3624954104501133, 0.017113007485132777, 0.18963426494596977, 0.058947567356164764, 0.2235264986626465, 0.014566826761107553, 0.028987082726830107, 0.05823049254920051, 0.04966031519848691, 0.19903318124830327, -0.035631604662877646, -0.11580351010938598, 0.007908054094789832, 0.1771005684206488] |
1,802.09694 | Remarks on $G_{2}$-manifolds with boundary | This article is based on a lecture at the Journal of Differential Geometry
Conference, Harvard 2017. We discuss closed and torsion-free $G_{2}$-structures
on a 7-manifold with boundary, with prescribed $3$-form on the boundary. Much
of the article is based on an observation that there is an intrinsic notion of
"mean convexity" for such boundary data. When the boundary data is mean convex,
classical arguments from Riemannian geometry can be applied. Another theme is a
connection with the maximal submanifold equation, in spaces of indefinite
signature.
| math.DG | this article is based on a lecture at the journal of differential geometry conference harvard 2017 we discuss closed and torsionfree g_2structures on a 7manifold with boundary with prescribed 3form on the boundary much of the article is based on an observation that there is an intrinsic notion of mean convexity for such boundary data when the boundary data is mean convex classical arguments from riemannian geometry can be applied another theme is a connection with the maximal submanifold equation in spaces of indefinite signature | [['this', 'article', 'is', 'based', 'on', 'a', 'lecture', 'at', 'the', 'journal', 'of', 'differential', 'geometry', 'conference', 'harvard', '2017', 'we', 'discuss', 'closed', 'and', 'torsionfree', 'g_2structures', 'on', 'a', '7manifold', 'with', 'boundary', 'with', 'prescribed', '3form', 'on', 'the', 'boundary', 'much', 'of', 'the', 'article', 'is', 'based', 'on', 'an', 'observation', 'that', 'there', 'is', 'an', 'intrinsic', 'notion', 'of', 'mean', 'convexity', 'for', 'such', 'boundary', 'data', 'when', 'the', 'boundary', 'data', 'is', 'mean', 'convex', 'classical', 'arguments', 'from', 'riemannian', 'geometry', 'can', 'be', 'applied', 'another', 'theme', 'is', 'a', 'connection', 'with', 'the', 'maximal', 'submanifold', 'equation', 'in', 'spaces', 'of', 'indefinite', 'signature']] | [-0.1619974322617054, 0.07001281894832466, -0.1328601039987167, 0.038978157877264656, -0.18123309005270985, -0.1112120508983293, -0.044306319009731795, 0.3347699739915483, -0.25557302906013585, -0.2605295825256583, 0.17328681142124183, -0.29905072892194284, -0.17560620651142123, 0.20225987169782028, -0.20320574970477645, -0.00022265654714668498, 0.08380905871882158, 0.10904742062968366, -0.11261186756138854, -0.25492761509821693, 0.452449473145637, 0.012995762673809247, 0.2761802381671527, 0.10915220787146074, 0.15229700741577237, -0.012268088692251374, -0.03630362403962542, 0.03450991870725856, -0.17268942490755923, 0.13693264776512104, 0.23702586840509493, 0.08478022692588102, 0.24486386836232507, -0.42825032582177835, -0.15276081558755217, 0.09912355312091463, 0.06298106232219759, 0.01876627195169396, -0.025442365672001067, -0.29378514436676223, 0.05723973393221112, -0.06207426342127078, -0.13465657371151096, 0.02553418220623451, 0.03875023470095852, -0.03312301029834677, -0.20815630233024848, 0.05619111234212623, 0.06479911440435578, 0.1589844250394141, -0.1027721322271699, -0.07646427941029234, -0.02133751631823971, 0.0187646808092455, 0.034545818554675756, 0.10688764961326823, 0.07157116986482459, -0.06254803242764491, -0.13053791310419055, 0.3564631678711842, -0.07413003274294383, -0.28464910922681586, 0.13228985896772322, -0.12068139858105603, -0.12716719667591592, 0.08657429333474925, 0.1887638254748548, 0.14818779346807037, -0.13594672248565237, 0.17670083359801483, -0.08123031539623352, 0.12959647141397, 0.06380665587699588, -0.05225784481119584, 0.1649703517665758, 0.14844694780459738, 0.13929817222387475, 0.10762881853425985, -0.0385864548604278, -0.08987433416974347, -0.40447238670552477, -0.1937057183322716, -0.18054548433488782, 0.1236315288416603, -0.09389781644002891, -0.20324113947503708, 0.33933182730175115, 0.04772091084091431, 0.1719991511090056, 0.04192501342691043, 0.24291379389298312, 0.11463497521300965, 0.01843426504638046, 0.12062251155319459, 0.18598135354764322, 0.2020787778584396, 0.07586369908907835, -0.1261360169689664, 0.0005555164288072025, 0.1421157231225687] |
1,802.09695 | User Association for Offloading in Heterogeneous Network Based on Matern
Cluster Process | Future mobile networks are converging toward heterogeneous multi-tier
networks, where various classes of base stations (BS) are deployed based on
user demand. So it is quite necessary to utilize the BSs resources rationally
when BSs are sufficient. In this paper, we develop a more realistic model that
fully considering the inter-tier dependence and the dependence between users
and BSs, where the macro base stations (MBSs) are distributed according to a
homogeneous Poisson point process (PPP) and the small base stations (SBSs)
follows a Matern cluster process (MCP) whose parent points are located in the
positions of the MBSs in order to offload the users from the over-loaded MBSs.
We also assume the users are just randomly located in the circles centered at
the MBSs. Under this model, we derive the association probability and the
average ergodic rate by stochastic geometry. An interesting result that the
density of MBS and the radius of the clusters jointly affect the association
probabilities in a joint form is obtained. We also observe that using the
clustered SBSs results in aggressive offloading compared with previous cellular
networks.
| eess.SP | future mobile networks are converging toward heterogeneous multitier networks where various classes of base stations bs are deployed based on user demand so it is quite necessary to utilize the bss resources rationally when bss are sufficient in this paper we develop a more realistic model that fully considering the intertier dependence and the dependence between users and bss where the macro base stations mbss are distributed according to a homogeneous poisson point process ppp and the small base stations sbss follows a matern cluster process mcp whose parent points are located in the positions of the mbss in order to offload the users from the overloaded mbss we also assume the users are just randomly located in the circles centered at the mbss under this model we derive the association probability and the average ergodic rate by stochastic geometry an interesting result that the density of mbs and the radius of the clusters jointly affect the association probabilities in a joint form is obtained we also observe that using the clustered sbss results in aggressive offloading compared with previous cellular networks | [['future', 'mobile', 'networks', 'are', 'converging', 'toward', 'heterogeneous', 'multitier', 'networks', 'where', 'various', 'classes', 'of', 'base', 'stations', 'bs', 'are', 'deployed', 'based', 'on', 'user', 'demand', 'so', 'it', 'is', 'quite', 'necessary', 'to', 'utilize', 'the', 'bss', 'resources', 'rationally', 'when', 'bss', 'are', 'sufficient', 'in', 'this', 'paper', 'we', 'develop', 'a', 'more', 'realistic', 'model', 'that', 'fully', 'considering', 'the', 'intertier', 'dependence', 'and', 'the', 'dependence', 'between', 'users', 'and', 'bss', 'where', 'the', 'macro', 'base', 'stations', 'mbss', 'are', 'distributed', 'according', 'to', 'a', 'homogeneous', 'poisson', 'point', 'process', 'ppp', 'and', 'the', 'small', 'base', 'stations', 'sbss', 'follows', 'a', 'matern', 'cluster', 'process', 'mcp', 'whose', 'parent', 'points', 'are', 'located', 'in', 'the', 'positions', 'of', 'the', 'mbss', 'in', 'order', 'to', 'offload', 'the', 'users', 'from', 'the', 'overloaded', 'mbss', 'we', 'also', 'assume', 'the', 'users', 'are', 'just', 'randomly', 'located', 'in', 'the', 'circles', 'centered', 'at', 'the', 'mbss', 'under', 'this', 'model', 'we', 'derive', 'the', 'association', 'probability', 'and', 'the', 'average', 'ergodic', 'rate', 'by', 'stochastic', 'geometry', 'an', 'interesting', 'result', 'that', 'the', 'density', 'of', 'mbs', 'and', 'the', 'radius', 'of', 'the', 'clusters', 'jointly', 'affect', 'the', 'association', 'probabilities', 'in', 'a', 'joint', 'form', 'is', 'obtained', 'we', 'also', 'observe', 'that', 'using', 'the', 'clustered', 'sbss', 'results', 'in', 'aggressive', 'offloading', 'compared', 'with', 'previous', 'cellular', 'networks']] | [-0.2112862168891857, 0.05766311398994211, -0.03309543234562235, 0.06527258502137556, -0.04446041675484074, -0.1918093036389449, 0.19383812057632174, 0.3885045417809634, -0.25717756517390095, -0.25052733774358343, 0.04939116821317309, -0.2867297742638614, -0.1484735746315302, 0.08967496124531173, -0.08253577089315833, -0.03217749991505356, 0.061525314527878454, 0.09066783063175095, -0.008425953846609036, -0.24761985543127693, 0.35081681054006175, 0.10562253903960911, 0.3750824952052886, -0.01737304605386261, 0.01694914292298503, -0.03940698997741872, -0.034569896813891415, 0.004942431297192572, -0.07144346344456617, 0.10104250344914732, 0.3204451126269075, 0.1207094215455332, 0.25995260229971323, -0.46931570087774444, -0.1979970083684548, 0.10904564192150157, 0.17433062153545356, 0.008521368583807578, -0.007285946332558524, -0.3064294556810797, 0.16262365802757922, -0.198703574333954, -0.09645270810917961, 0.03746185305395296, -0.04302044124547187, 0.15052246609395678, -0.3300417836161924, 0.009319230504423523, -0.032213911682797164, 0.022176848036226826, -0.04306866127132837, -0.1268982600374659, -0.015096125526195084, 0.2020919090899662, 0.028047399992918963, -0.03191003123052664, 0.15915026632137597, -0.07298423520322624, -0.06798035153929799, 0.3727364649095542, 0.024848098431043533, -0.2293834582247495, 0.19926457820142937, -0.13125364257503752, -0.1442838422160923, 0.12561827815383428, 0.22811213375458106, 0.10504910352404465, -0.20359110727736401, 0.03040974717017949, -0.051772329910238696, 0.12710166397100892, 0.07625801812033527, 0.04979703086492309, 0.23888282135134092, 0.21089327152035517, 0.1542982165752859, 0.08882375909041122, -0.15808241415236676, -0.15533538717711934, -0.24015994286829873, -0.08918476719690671, -0.20539941969276457, 0.013188198586199228, -0.09923183139383852, -0.09210881752033646, 0.31721600271367395, 0.10005165609418527, 0.1897281268278935, 0.10653139600673547, 0.31696636336957934, 0.09618506952448605, 0.05211857736755449, 0.17780348308164381, 0.13384803804205309, 0.09025627185442167, 0.1446320707167775, -0.16307049274705554, 0.04918615647545596, -0.027165467459401422] |
1,802.09696 | Stacked lensing estimators and their covariance matrices: Excess surface
mass density vs. Lensing shear | Stacked lensing is a powerful means of measuring the average mass
distribution around large-scale structure tracers. There are two stacked
lensing estimators used in the literature, denoted as $\Delta\Sigma$ and
$\gamma_+$, which are related as $\Delta\Sigma=\Sigma_{\rm cr}\gamma_+$, where
$\Sigma_{\rm cr}(z_l,z_s)$ is the critical surface mass density for each
lens-source pair ($z_l$ and $z_s$ are lens and source redshifts, respectively).
In this paper we derive a formula for the covariance matrix of
$\Delta\Sigma$-estimator focusing on `weight' function to improve the
signal-to-noise ($S/N$). We assume that the lensing fields and the distribution
of lensing objects obey the Gaussian statistics. With this formula, we show
that, if background galaxy shapes are weighted by an amount of $\Sigma_{\rm
cr}^{-2}(z_l,z_s)$, the $\Delta\Sigma$-estimator maximizes the $S/N$ in the
shot noise limited regime. We also show that the $\Delta\Sigma$-estimator with
the weight $\Sigma_{\rm cr}^{-2}$ gives a greater $(S/N)^2$ than that of the
$\gamma_+$-estimator by about 5--25\% for lensing objects at redshifts
comparable with or higher than the median of source galaxy redshifts for
hypothetical Subaru HSC and DES surveys. However, for low-redshift lenses such
as $z_l<0.3$, the $\gamma_+$-estimator has higher $(S/N)^2$ than
$\Delta\Sigma$. We also discuss that the $(S/N)^2$ for $\Delta\Sigma$ at large
separations in the sample variance limited regime can be boosted, by up to a
factor of 1.5, if one adopts a weight of $\Sigma_{\rm cr}^{-\alpha}$ with
$\alpha>2$. Our formula allows one to explore how the combination of the
different estimators can approach an optimal estimator in all regimes of
redshifts and separation scales.
| astro-ph.CO | stacked lensing is a powerful means of measuring the average mass distribution around largescale structure tracers there are two stacked lensing estimators used in the literature denoted as deltasigma and gamma_ which are related as deltasigmasigma_rm crgamma_ where sigma_rm crz_lz_s is the critical surface mass density for each lenssource pair z_l and z_s are lens and source redshifts respectively in this paper we derive a formula for the covariance matrix of deltasigmaestimator focusing on weight function to improve the signaltonoise sn we assume that the lensing fields and the distribution of lensing objects obey the gaussian statistics with this formula we show that if background galaxy shapes are weighted by an amount of sigma_rm cr2z_lz_s the deltasigmaestimator maximizes the sn in the shot noise limited regime we also show that the deltasigmaestimator with the weight sigma_rm cr2 gives a greater sn2 than that of the gamma_estimator by about 525 for lensing objects at redshifts comparable with or higher than the median of source galaxy redshifts for hypothetical subaru hsc and des surveys however for lowredshift lenses such as z_l03 the gamma_estimator has higher sn2 than deltasigma we also discuss that the sn2 for deltasigma at large separations in the sample variance limited regime can be boosted by up to a factor of 15 if one adopts a weight of sigma_rm cralpha with alpha2 our formula allows one to explore how the combination of the different estimators can approach an optimal estimator in all regimes of redshifts and separation scales | [['stacked', 'lensing', 'is', 'a', 'powerful', 'means', 'of', 'measuring', 'the', 'average', 'mass', 'distribution', 'around', 'largescale', 'structure', 'tracers', 'there', 'are', 'two', 'stacked', 'lensing', 'estimators', 'used', 'in', 'the', 'literature', 'denoted', 'as', 'deltasigma', 'and', 'gamma_', 'which', 'are', 'related', 'as', 'deltasigmasigma_rm', 'crgamma_', 'where', 'sigma_rm', 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1,802.09697 | Convolutional Neural Network Achieves Human-level Accuracy in Music
Genre Classification | Music genre classification is one example of content-based analysis of music
signals. Traditionally, human-engineered features were used to automatize this
task and 61% accuracy has been achieved in the 10-genre classification.
However, it's still below the 70% accuracy that humans could achieve in the
same task. Here, we propose a new method that combines knowledge of human
perception study in music genre classification and the neurophysiology of the
auditory system. The method works by training a simple convolutional neural
network (CNN) to classify a short segment of the music signal. Then, the genre
of a music is determined by splitting it into short segments and then combining
CNN's predictions from all short segments. After training, this method achieves
human-level (70%) accuracy and the filters learned in the CNN resemble the
spectrotemporal receptive field (STRF) in the auditory system.
| cs.SD cs.LG eess.AS | music genre classification is one example of contentbased analysis of music signals traditionally humanengineered features were used to automatize this task and 61 accuracy has been achieved in the 10genre classification however its still below the 70 accuracy that humans could achieve in the same task here we propose a new method that combines knowledge of human perception study in music genre classification and the neurophysiology of the auditory system the method works by training a simple convolutional neural network cnn to classify a short segment of the music signal then the genre of a music is determined by splitting it into short segments and then combining cnns predictions from all short segments after training this method achieves humanlevel 70 accuracy and the filters learned in the cnn resemble the spectrotemporal receptive field strf in the auditory system | [['music', 'genre', 'classification', 'is', 'one', 'example', 'of', 'contentbased', 'analysis', 'of', 'music', 'signals', 'traditionally', 'humanengineered', 'features', 'were', 'used', 'to', 'automatize', 'this', 'task', 'and', '61', 'accuracy', 'has', 'been', 'achieved', 'in', 'the', '10genre', 'classification', 'however', 'its', 'still', 'below', 'the', '70', 'accuracy', 'that', 'humans', 'could', 'achieve', 'in', 'the', 'same', 'task', 'here', 'we', 'propose', 'a', 'new', 'method', 'that', 'combines', 'knowledge', 'of', 'human', 'perception', 'study', 'in', 'music', 'genre', 'classification', 'and', 'the', 'neurophysiology', 'of', 'the', 'auditory', 'system', 'the', 'method', 'works', 'by', 'training', 'a', 'simple', 'convolutional', 'neural', 'network', 'cnn', 'to', 'classify', 'a', 'short', 'segment', 'of', 'the', 'music', 'signal', 'then', 'the', 'genre', 'of', 'a', 'music', 'is', 'determined', 'by', 'splitting', 'it', 'into', 'short', 'segments', 'and', 'then', 'combining', 'cnns', 'predictions', 'from', 'all', 'short', 'segments', 'after', 'training', 'this', 'method', 'achieves', 'humanlevel', '70', 'accuracy', 'and', 'the', 'filters', 'learned', 'in', 'the', 'cnn', 'resemble', 'the', 'spectrotemporal', 'receptive', 'field', 'strf', 'in', 'the', 'auditory', 'system']] | [-0.04290431682431303, 0.0005382735843715422, -0.0950764963430736, 0.07027978217229247, -0.11963068961289108, -0.18519543515011558, -0.007920335135970484, 0.46840305514085817, -0.24431902392055183, -0.3448582875460167, 0.06387721094121362, -0.2705322935259627, -0.24468200163135087, 0.1860308839514961, -0.14938162896878032, 0.06802239664102672, 0.15337392615123568, 0.11515779978157405, -0.04839449204668841, -0.30860175308172233, 0.23462058924248114, 0.025662456149481896, 0.3565512795518289, -0.011886925592347431, 0.15965813064014903, -0.048103142779676575, -0.05567554215325371, -0.04774098407891442, -0.023552165939690894, 0.15570979446441496, 0.33521478840232116, 0.21468533810248652, 0.33670441672781154, -0.3658482032307588, -0.2183190468383734, 0.058174664097297116, 0.1634030657054716, 0.12902666189920103, 0.003269880503306494, -0.37261171556790085, 0.13452814172213787, -0.14672686675946942, 0.04631401764858952, -0.09085634267916355, -0.01570285353997914, -0.0096096021032495, -0.22297287244873587, 0.05542908202829387, 0.12338964356219068, 0.12488128533860778, -0.06646292874853209, -0.08938857828616165, 0.0401408050349667, 0.2065398468677064, 0.02705875053481363, 0.08783028587555129, 0.13653869379435063, -0.21993072990752646, -0.14441225845503675, 0.36066784301895977, -0.09222475668117541, -0.17220632633025695, 0.16584192664252922, -0.03196466100566527, -0.12034254908726058, 0.1385889521522639, 0.21742090503668057, 0.08638117790413911, -0.17806130645604915, -0.03723562615478466, -0.034746000803459215, 0.2394933304064633, 0.10432086599073098, -0.03446582666776307, 0.19450974109007374, 0.29247372284504203, -0.0647987300694427, 0.12247763055732802, -0.14423593276467941, 0.0032150714986902825, -0.15863332572959787, -0.09756819385459975, -0.20643875009195387, -0.030408488109755768, -0.09923106068291578, -0.1145786347470301, 0.4816541685996687, 0.20369327015599564, 0.1859565110575846, 0.12124210599850972, 0.33488823460784795, -0.0028611576143542632, 0.12973785515607553, 0.05888098094232298, 0.19883723012240165, -0.0019009599191657104, 0.16097568558325293, -0.16051408770213396, 0.06268712266704396, 0.07836162394703612] |
1,802.09698 | Thermodynamic properties of the $S=1/2$ twisted triangular spin tube | Thermodynamic properties of the twisted three-leg spin tube under magnetic
field are studied by the finite-$T$ density-matrix renormalization group
method. The specific heat, spin, and chiral susceptibilities of the infinite
system are calculated for both the original and its low-energy effective
models. The obtained results show that the presence of the chirality is
observed as a clear peak in the specific heat at low temperature and the
contribution of the chirality dominates the low-temperature part of the
specific heat as the exchange coupling along the spin tube decreases. The peak
structures in the specific heat, spin, and chiral susceptibilities are strongly
modified near the quantum phase transition where the critical behaviors of the
spin and chirality correlations change. These results confirm that the
chirality plays a major role in characteristic low-energy behaviors of the
frustrated spin systems.
| cond-mat.str-el | thermodynamic properties of the twisted threeleg spin tube under magnetic field are studied by the finitet densitymatrix renormalization group method the specific heat spin and chiral susceptibilities of the infinite system are calculated for both the original and its lowenergy effective models the obtained results show that the presence of the chirality is observed as a clear peak in the specific heat at low temperature and the contribution of the chirality dominates the lowtemperature part of the specific heat as the exchange coupling along the spin tube decreases the peak structures in the specific heat spin and chiral susceptibilities are strongly modified near the quantum phase transition where the critical behaviors of the spin and chirality correlations change these results confirm that the chirality plays a major role in characteristic lowenergy behaviors of the frustrated spin systems | [['thermodynamic', 'properties', 'of', 'the', 'twisted', 'threeleg', 'spin', 'tube', 'under', 'magnetic', 'field', 'are', 'studied', 'by', 'the', 'finitet', 'densitymatrix', 'renormalization', 'group', 'method', 'the', 'specific', 'heat', 'spin', 'and', 'chiral', 'susceptibilities', 'of', 'the', 'infinite', 'system', 'are', 'calculated', 'for', 'both', 'the', 'original', 'and', 'its', 'lowenergy', 'effective', 'models', 'the', 'obtained', 'results', 'show', 'that', 'the', 'presence', 'of', 'the', 'chirality', 'is', 'observed', 'as', 'a', 'clear', 'peak', 'in', 'the', 'specific', 'heat', 'at', 'low', 'temperature', 'and', 'the', 'contribution', 'of', 'the', 'chirality', 'dominates', 'the', 'lowtemperature', 'part', 'of', 'the', 'specific', 'heat', 'as', 'the', 'exchange', 'coupling', 'along', 'the', 'spin', 'tube', 'decreases', 'the', 'peak', 'structures', 'in', 'the', 'specific', 'heat', 'spin', 'and', 'chiral', 'susceptibilities', 'are', 'strongly', 'modified', 'near', 'the', 'quantum', 'phase', 'transition', 'where', 'the', 'critical', 'behaviors', 'of', 'the', 'spin', 'and', 'chirality', 'correlations', 'change', 'these', 'results', 'confirm', 'that', 'the', 'chirality', 'plays', 'a', 'major', 'role', 'in', 'characteristic', 'lowenergy', 'behaviors', 'of', 'the', 'frustrated', 'spin', 'systems']] | [-0.2022647643053945, 0.2405895443733469, -0.021067704488761232, 0.04625498941661042, -0.04039286824799802, -0.09860235879564808, 0.018584629145185768, 0.3603736511737543, -0.24956333735277095, -0.26248833898754015, 0.06260503151192309, -0.32672071658129237, -0.11847111929452768, 0.17860616518551634, 0.09827513349697972, 0.010943436950536949, -0.04088033867972719, 0.08656754451939823, -0.12753734635325134, -0.153419283171096, 0.30554037400093065, 0.029750392285352367, 0.3388313867515429, 0.1439678052718153, 0.05832157600467114, 0.023002969123164775, 0.06956332734357702, 0.024306275762862314, -0.1279973422903032, 0.0269017613520098, 0.1976126786095422, -0.0906427778358007, 0.14264685816954087, -0.41460875859552054, -0.22709478298712005, 0.025645955260095263, 0.11474528598401995, 0.1148354405414884, -0.04024483792375039, -0.24972893175308722, 0.013776778522199088, -0.14597460410020646, -0.17183497247972737, -0.1148677222689029, -0.028421704343819215, 0.01384190218455165, -0.20850754121359247, 0.15670592026053384, 0.09211633174279094, 0.06490928125669704, -0.08079539944781466, -0.13141167480889435, -0.11039700194595069, 0.14171666203977634, 0.07816696699783478, 0.02391208983604273, 0.19546999861350298, -0.18589956150560158, -0.11984923916501775, 0.3430378159752836, -0.07698798318815003, -0.12890818393551304, 0.14589385335829896, -0.18342740876246652, -0.11412835946768848, 0.1268277316163872, 0.100041855490311, 0.10197211291817744, -0.13063441402190468, 0.06374436650356366, -0.014977312908528278, 0.11120766200070833, -0.014284606564137405, 0.060041771929738294, 0.2810321388915725, 0.14239599688758692, 0.02188015297517507, 0.1576240916709232, -0.11732765535201986, -0.14017731286449372, -0.28614466367493363, -0.1548838080960686, -0.21122230376953083, 0.043223017395004955, -0.1237366267807746, -0.16976293455469457, 0.4428682128497719, 0.1482750984511243, 0.17801973805592877, -0.03870944557439563, 0.24456685122415206, 0.15438941995108527, 0.09242685320132826, 0.0529003285762113, 0.25948479632085636, 0.2178587385191562, 0.1537605105205881, -0.40164164979568256, 0.043602730575812994, 0.03825194990248793] |
1,802.09699 | A foliated Hitchin-Kobayashi correspondence | We prove an analogue of the Hitchin-Kobayashi correspondence for compact,
oriented, taut Riemannian foliated manifolds with transverse Hermitian
structure. In particular, our Hitchin-Kobayashi theorem holds on any compact
Sasakian manifold. We define the notion of stability for foliated Hermitian
vector bundles with transverse holomorphic structure and prove that such
bundles admit a basic Hermitian-Einstein connection if and only if they are
polystable. Our proof is obtained by adapting the proof by Uhlenbeck and Yau to
the foliated setting. We relate the transverse Hermitian-Einstein equations to
higher dimensional instanton equations and in particular we look at the
relation to higher contact instantons on Sasaki manifolds. For foliations of
complex codimension 1, we obtain a transverse Narasimhan-Seshadri theorem. We
also demonstrate that the weak Uhlenbeck compactness theorem fails in general
for basic connections on a foliated bundle. This shows that not every result in
gauge theory carries over to the foliated setting.
| math.DG math.AG | we prove an analogue of the hitchinkobayashi correspondence for compact oriented taut riemannian foliated manifolds with transverse hermitian structure in particular our hitchinkobayashi theorem holds on any compact sasakian manifold we define the notion of stability for foliated hermitian vector bundles with transverse holomorphic structure and prove that such bundles admit a basic hermitianeinstein connection if and only if they are polystable our proof is obtained by adapting the proof by uhlenbeck and yau to the foliated setting we relate the transverse hermitianeinstein equations to higher dimensional instanton equations and in particular we look at the relation to higher contact instantons on sasaki manifolds for foliations of complex codimension 1 we obtain a transverse narasimhanseshadri theorem we also demonstrate that the weak uhlenbeck compactness theorem fails in general for basic connections on a foliated bundle this shows that not every result in gauge theory carries over to the foliated setting | [['we', 'prove', 'an', 'analogue', 'of', 'the', 'hitchinkobayashi', 'correspondence', 'for', 'compact', 'oriented', 'taut', 'riemannian', 'foliated', 'manifolds', 'with', 'transverse', 'hermitian', 'structure', 'in', 'particular', 'our', 'hitchinkobayashi', 'theorem', 'holds', 'on', 'any', 'compact', 'sasakian', 'manifold', 'we', 'define', 'the', 'notion', 'of', 'stability', 'for', 'foliated', 'hermitian', 'vector', 'bundles', 'with', 'transverse', 'holomorphic', 'structure', 'and', 'prove', 'that', 'such', 'bundles', 'admit', 'a', 'basic', 'hermitianeinstein', 'connection', 'if', 'and', 'only', 'if', 'they', 'are', 'polystable', 'our', 'proof', 'is', 'obtained', 'by', 'adapting', 'the', 'proof', 'by', 'uhlenbeck', 'and', 'yau', 'to', 'the', 'foliated', 'setting', 'we', 'relate', 'the', 'transverse', 'hermitianeinstein', 'equations', 'to', 'higher', 'dimensional', 'instanton', 'equations', 'and', 'in', 'particular', 'we', 'look', 'at', 'the', 'relation', 'to', 'higher', 'contact', 'instantons', 'on', 'sasaki', 'manifolds', 'for', 'foliations', 'of', 'complex', 'codimension', '1', 'we', 'obtain', 'a', 'transverse', 'narasimhanseshadri', 'theorem', 'we', 'also', 'demonstrate', 'that', 'the', 'weak', 'uhlenbeck', 'compactness', 'theorem', 'fails', 'in', 'general', 'for', 'basic', 'connections', 'on', 'a', 'foliated', 'bundle', 'this', 'shows', 'that', 'not', 'every', 'result', 'in', 'gauge', 'theory', 'carries', 'over', 'to', 'the', 'foliated', 'setting']] | [-0.21403376724881432, 0.08248180626590813, -0.10236780859840412, 0.1465293396015962, -0.1413480804612239, -0.18517662500031293, -0.053332796960603446, 0.3642920991778374, -0.24362850919365883, -0.170746761035795, 0.05921306738319496, -0.2237415001168847, -0.1974443691968918, 0.17851286738800506, -0.17489865441806615, -0.011797998370602726, 0.0749434612163653, 0.06543610778792451, -0.11138321195341026, -0.26216331382359687, 0.49414946024927, -0.05072513890142242, 0.24030647094671925, 0.13952735230321803, 0.18096211563795805, 0.0540813544683624, 0.016386953278755147, 0.015092881244296828, -0.19106114281879855, 0.12743304487511825, 0.25656227144102256, 0.034587874114513396, 0.16485788225817183, -0.3698533889548465, -0.19012082296113172, 0.1855448315447817, 0.09740773867194852, 0.017250926624595497, 0.008142910895403475, -0.3150292781771471, 0.13712536464445294, -0.07741783547215164, -0.2260083014894432, -0.1546304972890842, 0.021606026788552602, -0.022775738127529623, -0.1677594079923195, 0.018964433786265243, 0.18519956337908905, 0.07510080728059014, -0.10409140288829803, -0.027058047455890726, -0.10970280442542087, 0.019790052957832812, 0.027381350728683175, 0.09200621576979756, 0.10230063518160022, -0.018722317267529435, -0.15149711531897386, 0.2992999153584242, -0.1072608998666207, -0.32501999437188106, 0.10946807922174533, -0.15606119277887046, -0.22740097067939738, 0.0951041379213954, 0.12823064778000115, 0.2021875973472682, -0.008648169637502482, 0.16664538179989904, -0.09666372529231011, 0.060125937958558404, 0.13861685651975372, -0.032210328974373016, 0.11802625163768729, 0.11276913216337561, 0.14788623803450415, 0.09031187471468001, 0.01306959292696168, -0.11087908200919629, -0.37485275202120344, -0.25652791067647435, -0.09300708963380505, 0.23958165298691408, -0.14715280614133613, -0.17847519831421474, 0.3541202887520194, 0.02139045563953308, 0.21350068340698877, 0.16041477779547372, 0.22354555369199564, 0.03747542744968087, 0.02461023237556219, 0.11875961197850605, 0.2206383591114233, 0.28078106000088154, 0.06182602019282058, -0.06261503393451373, -0.098134279527391, 0.22780042419520516] |
1,802.097 | Robust GANs against Dishonest Adversaries | Robustness of deep learning models is a property that has recently gained
increasing attention. We explore a notion of robustness for generative
adversarial models that is pertinent to their internal interactive structure,
and show that, perhaps surprisingly, the GAN in its original form is not
robust. Our notion of robustness relies on a perturbed discriminator, or noisy,
adversarial interference with its feedback. We explore, theoretically and
empirically, the effect of model and training properties on this robustness. In
particular, we show theoretical conditions for robustness that are supported by
empirical evidence. We also test the effect of regularization. Our results
suggest variations of GANs that are indeed more robust to noisy attacks and
have more stable training behavior, requiring less regularization in general.
Inspired by our theoretical results, we further extend our framework to obtain
a class of models related to WGAN, with good empirical performance. Overall,
our results suggest a new perspective on understanding and designing GAN models
from the viewpoint of their internal robustness.
| cs.LG stat.ML | robustness of deep learning models is a property that has recently gained increasing attention we explore a notion of robustness for generative adversarial models that is pertinent to their internal interactive structure and show that perhaps surprisingly the gan in its original form is not robust our notion of robustness relies on a perturbed discriminator or noisy adversarial interference with its feedback we explore theoretically and empirically the effect of model and training properties on this robustness in particular we show theoretical conditions for robustness that are supported by empirical evidence we also test the effect of regularization our results suggest variations of gans that are indeed more robust to noisy attacks and have more stable training behavior requiring less regularization in general inspired by our theoretical results we further extend our framework to obtain a class of models related to wgan with good empirical performance overall our results suggest a new perspective on understanding and designing gan models from the viewpoint of their internal robustness | [['robustness', 'of', 'deep', 'learning', 'models', 'is', 'a', 'property', 'that', 'has', 'recently', 'gained', 'increasing', 'attention', 'we', 'explore', 'a', 'notion', 'of', 'robustness', 'for', 'generative', 'adversarial', 'models', 'that', 'is', 'pertinent', 'to', 'their', 'internal', 'interactive', 'structure', 'and', 'show', 'that', 'perhaps', 'surprisingly', 'the', 'gan', 'in', 'its', 'original', 'form', 'is', 'not', 'robust', 'our', 'notion', 'of', 'robustness', 'relies', 'on', 'a', 'perturbed', 'discriminator', 'or', 'noisy', 'adversarial', 'interference', 'with', 'its', 'feedback', 'we', 'explore', 'theoretically', 'and', 'empirically', 'the', 'effect', 'of', 'model', 'and', 'training', 'properties', 'on', 'this', 'robustness', 'in', 'particular', 'we', 'show', 'theoretical', 'conditions', 'for', 'robustness', 'that', 'are', 'supported', 'by', 'empirical', 'evidence', 'we', 'also', 'test', 'the', 'effect', 'of', 'regularization', 'our', 'results', 'suggest', 'variations', 'of', 'gans', 'that', 'are', 'indeed', 'more', 'robust', 'to', 'noisy', 'attacks', 'and', 'have', 'more', 'stable', 'training', 'behavior', 'requiring', 'less', 'regularization', 'in', 'general', 'inspired', 'by', 'our', 'theoretical', 'results', 'we', 'further', 'extend', 'our', 'framework', 'to', 'obtain', 'a', 'class', 'of', 'models', 'related', 'to', 'wgan', 'with', 'good', 'empirical', 'performance', 'overall', 'our', 'results', 'suggest', 'a', 'new', 'perspective', 'on', 'understanding', 'and', 'designing', 'gan', 'models', 'from', 'the', 'viewpoint', 'of', 'their', 'internal', 'robustness']] | [-0.0412727090984538, 0.021768659900267977, -0.11196552941306348, 0.09331011692628668, -0.10277826541120254, -0.15022404572270048, 0.05777887237280697, 0.4495967413910317, -0.23753986066678562, -0.3187759898109249, 0.056265976218961136, -0.24413683130518052, -0.2743016367915636, 0.2121571819887059, -0.1653364666917148, 0.08191187803125773, 0.10541257848093533, -0.004613546459621425, -0.07435142611159035, -0.2884485345622749, 0.3422925559024001, 0.08310656496221958, 0.33166990712767536, 0.05218283689289118, 0.06133370233015213, -0.06840255173871361, -0.007717101206352194, 0.040654093420542554, -0.08717391645457456, 0.1800675289144358, 0.19373672689054883, 0.17468958941333176, 0.3481354670197961, -0.4076157746253064, -0.2783231577802315, 0.07701056792277348, 0.08871742916933026, 0.13204412868089346, -0.13463049690559625, -0.324069131614573, 0.15188118300599843, -0.15389505853309823, -0.059915800315204513, -0.18047283432328604, -0.02498203383040536, -0.008831197478882011, -0.3044579365218468, 0.04215065584113367, 0.1431835174829845, 0.048149412006970094, -0.06125383567575545, -0.09917461880025487, -0.038679660910863924, 0.09766109301975132, 0.061478705261132666, 0.01124588306993246, 0.0940950983119792, -0.16268114367337247, -0.14107776528255206, 0.3264004352547408, -0.04898174506253058, -0.2265220469664025, 0.22414101518028562, -0.06460044138184019, -0.1453090868525611, 0.059568993222664096, 0.21756880966026382, 0.12259053566818495, -0.10117549830746096, 0.03377544938085926, -0.04827987658580855, 0.14890263225891662, -0.021435380587915342, 0.06504515768765158, 0.14915286803040204, 0.23357711687469462, 0.03446297218086176, 0.18601273718228317, -0.07374653221439031, -0.1196270779235266, -0.24254284091910952, -0.07770341320569257, -0.16992569134952165, 0.03339453622937576, -0.09332433879311991, -0.13308754642998957, 0.4006045505401667, 0.25547468980931376, 0.2391485812448257, 0.12698164581691465, 0.32366263067506884, 0.04657237632382459, 0.04857676137198066, 0.06042734542805477, 0.2804094435568585, 0.09559782734140754, 0.05842853414388486, -0.20384736860827374, 0.14009069007294006, -0.011984519553875708] |
1,802.09701 | On the distribution of the maximum of cubic exponential sums | In this paper, we investigate the distribution of the maximum of partial sums
of certain cubic exponential sums, commonly known as "Birch sums". Our main
theorem gives upper and lower bounds (of nearly the same order of magnitude)
for the distribution of large values of this maximum, that hold in a wide
uniform range. This improves a recent result of Kowalski and Sawin. The proofs
use a blend of probabilistic methods, harmonic analysis techniques, and deep
tools from algebraic geometry. The results can also be generalized to other
types of $\ell$-adic trace functions. In particular, the lower bound of our
result also holds for partial sums of Kloosterman sums. As an application, we
show that there exist $x\in [1, p]$ and $a\in \mathbb{F}_p^{\times}$ such that
$|\sum_{n\leq x} \exp(2\pi i (n^3+an)/p)|\ge (2/\pi+o(1)) \sqrt{p}\log\log p$.
The uniformity of our results suggests that this bound is optimal, up to the
value of the constant.
| math.NT | in this paper we investigate the distribution of the maximum of partial sums of certain cubic exponential sums commonly known as birch sums our main theorem gives upper and lower bounds of nearly the same order of magnitude for the distribution of large values of this maximum that hold in a wide uniform range this improves a recent result of kowalski and sawin the proofs use a blend of probabilistic methods harmonic analysis techniques and deep tools from algebraic geometry the results can also be generalized to other types of elladic trace functions in particular the lower bound of our result also holds for partial sums of kloosterman sums as an application we show that there exist xin 1 p and ain mathbbf_ptimes such that sum_nleq x exp2pi i n3anpge 2pio1 sqrtploglog p the uniformity of our results suggests that this bound is optimal up to the value of the constant | [['in', 'this', 'paper', 'we', 'investigate', 'the', 'distribution', 'of', 'the', 'maximum', 'of', 'partial', 'sums', 'of', 'certain', 'cubic', 'exponential', 'sums', 'commonly', 'known', 'as', 'birch', 'sums', 'our', 'main', 'theorem', 'gives', 'upper', 'and', 'lower', 'bounds', 'of', 'nearly', 'the', 'same', 'order', 'of', 'magnitude', 'for', 'the', 'distribution', 'of', 'large', 'values', 'of', 'this', 'maximum', 'that', 'hold', 'in', 'a', 'wide', 'uniform', 'range', 'this', 'improves', 'a', 'recent', 'result', 'of', 'kowalski', 'and', 'sawin', 'the', 'proofs', 'use', 'a', 'blend', 'of', 'probabilistic', 'methods', 'harmonic', 'analysis', 'techniques', 'and', 'deep', 'tools', 'from', 'algebraic', 'geometry', 'the', 'results', 'can', 'also', 'be', 'generalized', 'to', 'other', 'types', 'of', 'elladic', 'trace', 'functions', 'in', 'particular', 'the', 'lower', 'bound', 'of', 'our', 'result', 'also', 'holds', 'for', 'partial', 'sums', 'of', 'kloosterman', 'sums', 'as', 'an', 'application', 'we', 'show', 'that', 'there', 'exist', 'xin', '1', 'p', 'and', 'ain', 'mathbbf_ptimes', 'such', 'that', 'sum_nleq', 'x', 'exp2pi', 'i', 'n3anpge', '2pio1', 'sqrtploglog', 'p', 'the', 'uniformity', 'of', 'our', 'results', 'suggests', 'that', 'this', 'bound', 'is', 'optimal', 'up', 'to', 'the', 'value', 'of', 'the', 'constant']] | [-0.1334648661081824, 0.05897228156676204, -0.10175516975200358, 0.06069103198682864, -0.04496833179271906, -0.08693451497930328, 0.07254525194199428, 0.29295714969142667, -0.2818045185350284, -0.2856089835435882, 0.0953071334303319, -0.2678607171275527, -0.14473733444370934, 0.2563565493611669, -0.08092975858410166, 0.05334729718280771, 0.024358710832579213, 0.02703708822750864, -0.10204033058992512, -0.3132637390816534, 0.3179376086132047, -0.029462642042081162, 0.25156504511078065, 0.11183807936597716, 0.06171239805848312, 0.018336776118549343, -0.004643647881174409, -0.02951771648902748, -0.18933278482153262, 0.1638884422187599, 0.254765905128364, 0.1377978503961286, 0.2656192188906307, -0.3588989574487346, -0.1647996455242203, 0.15827987616570238, 0.1373202716034988, 0.04490123950951808, -0.012541244662291295, -0.21056973009694344, 0.12748873311824896, -0.15901757511971015, -0.15137613028589939, -0.05415509912701374, 0.03861703783764529, 0.10694562345019516, -0.31518655006043816, 0.07765856983944006, 0.17801803129574134, 0.058785332492481905, -0.05008844256942236, -0.21373020160260509, 0.044418877882669, 0.10281831233815693, 0.05921061470871791, 0.04086241123779375, 0.0349112261634169, -0.0943913419063933, -0.11204071605036892, 0.31636207979298325, -0.1199001611219845, -0.15374921187380883, 0.12806433015794028, -0.17902665691783753, -0.1776596246211714, 0.10861694250048164, 0.14220810859036204, 0.17991829704417772, -0.051063767464428735, 0.1226662356245986, -0.1435248665605999, 0.1350488079887991, 0.1167523806625222, 0.042104402215635356, 0.10141628220633327, 0.06430464293147009, 0.11175994793381039, 0.1418230526642465, -0.03376845602336264, -0.036902359818939016, -0.34985942464019804, -0.1766641403971605, -0.1769436178980647, 0.09893145654555033, -0.1579195201299405, -0.18237941106073433, 0.33709234135647026, 0.1344635544904835, 0.19057627998896548, 0.12418949221437042, 0.2530667938896128, 0.15038034188123797, 0.02923353695439653, 0.05070439350689609, 0.18803766373870578, 0.1816249022738555, 0.03096817770494601, -0.12111881023274446, 0.05136222722137825, 0.09573550213669502] |
1,802.09702 | Drinfeld realisations and vertex operator representations of quantum
affine superalgebras | Drinfeld realisations are constructed for the quantum affine superalgebras of
the series ${\rm\mathfrak{osp}}(1|2n)^{(1)}$,${\rm\mathfrak{sl}}(1|2n)^{(2)}$
and ${\rm\mathfrak{osp}}(2|2n)^{(2)}$. By using the realisations, we develop
vertex operator representations and classify the finite dimensional irreducible
representations for these quantum affine superalgebras.
| math.QA | drinfeld realisations are constructed for the quantum affine superalgebras of the series rmmathfrakosp12n1rmmathfraksl12n2 and rmmathfrakosp22n2 by using the realisations we develop vertex operator representations and classify the finite dimensional irreducible representations for these quantum affine superalgebras | [['drinfeld', 'realisations', 'are', 'constructed', 'for', 'the', 'quantum', 'affine', 'superalgebras', 'of', 'the', 'series', 'rmmathfrakosp12n1rmmathfraksl12n2', 'and', 'rmmathfrakosp22n2', 'by', 'using', 'the', 'realisations', 'we', 'develop', 'vertex', 'operator', 'representations', 'and', 'classify', 'the', 'finite', 'dimensional', 'irreducible', 'representations', 'for', 'these', 'quantum', 'affine', 'superalgebras']] | [-0.10131314676254988, 0.12128601584802656, -0.022286676308687997, 0.02559291845297112, -0.10801753598977537, -0.17924879483111641, -0.0997756395406802, 0.37625553020659613, -0.34137898398672833, -0.13638035131289677, 0.12172046116114978, -0.26185680372530923, -0.18747359788154855, 0.19962966348975897, -0.10645314867553465, 0.018394465626710477, 0.03832388677469948, 0.12436130796285237, -0.15245199817068436, -0.37028395800906067, 0.4716757393496878, -0.04252772833741106, 0.2479517506709432, -0.10744335102465223, 0.22326832007178488, 0.06749839009717107, -0.03012019067126162, -0.08010652466841481, -0.13966651196481988, 0.16202542706228354, 0.4346484636874212, 0.011461529086398728, 0.1064757713363232, -0.39530495115939307, -0.12222542093299768, 0.19940943914629958, 0.19467793272205575, 0.10752634479499915, -0.016586885020575103, -0.33712296867195296, 0.05492714617182227, -0.23410051863859682, -0.11867961338173379, -0.16585622793611357, 0.030586832312538344, -0.07600968331098557, -0.2337062610861133, 0.0030535753706798833, 0.02081489793079741, 0.17965114151593298, -0.12425114459577291, -0.1322357486385633, 0.0013094365678946761, 0.10270779505919884, -0.16381590523044853, -0.06165914978448521, 0.10505506437381401, -0.1266822426689888, -0.29514582712641535, 0.31060821519178505, 0.06077205743092824, -0.26687145211240826, 0.11814310631769545, -0.12094764905872152, -0.16927924928912783, 0.011156073278364013, 0.07435905341716374, 0.06686226212803055, -0.07630190998315811, 0.25613539402633356, -0.04181910996489665, -0.1286988564123235, 0.062268393401823496, -0.00982853737385834, 0.17068212095867186, 0.022439567810472322, -0.017459776909912333, 0.14594820418449886, 0.029719827313195255, -0.06451844588360366, -0.4332391748971799, -0.17099829730303848, -0.08498054960578241, 0.1538956443888738, -0.1642341339979526, -0.16892585870535934, 0.4993011872558033, 0.11137913207708419, 0.1933862490250784, 0.19376244245316177, 0.14130830370328007, 0.16455251855008743, 0.16978766467860518, 0.0905858619029031, 0.05856407392660484, 0.302068174823516, -0.11835323361789479, -0.15348735588828705, -0.145300660871298, 0.29518594713333773] |
1,802.09703 | Boosting Cooperative Coevolution for Large Scale Optimization with a
Fine-Grained Computation Resource Allocation Strategy | Cooperative coevolution (CC) has shown great potential in solving large scale
optimization problems (LSOPs). However, traditional CC algorithms often waste
part of computation resource (CR) as they equally allocate CR among all the
subproblems. The recently developed contribution-based CC (CBCC) algorithms
improve the traditional ones to a certain extent by adaptively allocating CR
according to some heuristic rules. Different from existing works, this study
explicitly constructs a mathematical model for the CR allocation (CRA) problem
in CC and proposes a novel fine-grained CRA (FCRA) strategy by fully
considering both the theoretically optimal solution of the CRA model and the
evolution characteristics of CC. FCRA takes a single iteration as a basic CRA
unit and always selects the subproblem which is most likely to make the largest
contribution to the total fitness improvement to undergo a new iteration, where
the contribution of a subproblem at a new iteration is estimated according to
its current contribution, current evolution status as well as the estimation
for its current contribution. We verified the efficiency of FCRA by combining
it with SHADE which is an excellent differential evolution variant but has
never been employed in the CC framework. Experimental results on two benchmark
suites for LSOPs demonstrate that FCRA significantly outperforms existing CRA
strategies and the resultant CC algorithm is highly competitive in solving
LSOPs.
| cs.NE | cooperative coevolution cc has shown great potential in solving large scale optimization problems lsops however traditional cc algorithms often waste part of computation resource cr as they equally allocate cr among all the subproblems the recently developed contributionbased cc cbcc algorithms improve the traditional ones to a certain extent by adaptively allocating cr according to some heuristic rules different from existing works this study explicitly constructs a mathematical model for the cr allocation cra problem in cc and proposes a novel finegrained cra fcra strategy by fully considering both the theoretically optimal solution of the cra model and the evolution characteristics of cc fcra takes a single iteration as a basic cra unit and always selects the subproblem which is most likely to make the largest contribution to the total fitness improvement to undergo a new iteration where the contribution of a subproblem at a new iteration is estimated according to its current contribution current evolution status as well as the estimation for its current contribution we verified the efficiency of fcra by combining it with shade which is an excellent differential evolution variant but has never been employed in the cc framework experimental results on two benchmark suites for lsops demonstrate that fcra significantly outperforms existing cra strategies and the resultant cc algorithm is highly competitive in solving lsops | [['cooperative', 'coevolution', 'cc', 'has', 'shown', 'great', 'potential', 'in', 'solving', 'large', 'scale', 'optimization', 'problems', 'lsops', 'however', 'traditional', 'cc', 'algorithms', 'often', 'waste', 'part', 'of', 'computation', 'resource', 'cr', 'as', 'they', 'equally', 'allocate', 'cr', 'among', 'all', 'the', 'subproblems', 'the', 'recently', 'developed', 'contributionbased', 'cc', 'cbcc', 'algorithms', 'improve', 'the', 'traditional', 'ones', 'to', 'a', 'certain', 'extent', 'by', 'adaptively', 'allocating', 'cr', 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1,802.09704 | The twisted mean square and critical zeros of Dirichlet $L$-functions | In this work, we obtain an asymptotic formula for the twisted mean square of
a Dirichlet $L$-function with a longer mollifier, whose coefficients are also
more general than before. As an application we obtain that, for every Dirichlet
$L$-function, more than 41.72\% of zeros are on the critical line and more than
40.74\% of zeros are simple and on the critical line. These proportions also
improve previous results which were proved only for the Riemann zeta-function.
| math.NT | in this work we obtain an asymptotic formula for the twisted mean square of a dirichlet lfunction with a longer mollifier whose coefficients are also more general than before as an application we obtain that for every dirichlet lfunction more than 4172 of zeros are on the critical line and more than 4074 of zeros are simple and on the critical line these proportions also improve previous results which were proved only for the riemann zetafunction | [['in', 'this', 'work', 'we', 'obtain', 'an', 'asymptotic', 'formula', 'for', 'the', 'twisted', 'mean', 'square', 'of', 'a', 'dirichlet', 'lfunction', 'with', 'a', 'longer', 'mollifier', 'whose', 'coefficients', 'are', 'also', 'more', 'general', 'than', 'before', 'as', 'an', 'application', 'we', 'obtain', 'that', 'for', 'every', 'dirichlet', 'lfunction', 'more', 'than', '4172', 'of', 'zeros', 'are', 'on', 'the', 'critical', 'line', 'and', 'more', 'than', '4074', 'of', 'zeros', 'are', 'simple', 'and', 'on', 'the', 'critical', 'line', 'these', 'proportions', 'also', 'improve', 'previous', 'results', 'which', 'were', 'proved', 'only', 'for', 'the', 'riemann', 'zetafunction']] | [-0.10703480454609043, 0.04268696961509321, -0.10943771234566443, 0.08706211562629936, -0.10612124354137402, -0.1425410701378592, 0.023033513205040147, 0.3638840029751392, -0.14337548284521817, -0.2269649675030163, 0.15899994546443372, -0.2792680657615787, -0.1371732212443787, 0.30173701283178833, -0.034841537947374344, 0.05241378022995042, 0.033384437369501314, 0.1287255251816915, -0.12488319387337374, -0.30969764260379107, 0.3462871653824358, 0.017355881386289473, 0.20447888369917086, 0.07729418922711997, 0.0032537701512123213, -0.01946149719266319, 0.024893150211458926, -0.08760747947043886, -0.1487113664354279, 0.14353040424420646, 0.21280493073802637, 0.0028064389786634004, 0.2528084248892571, -0.41327139926809314, -0.19283715255656525, 0.16738137714319715, 0.17714989558474994, 0.00819008376320677, 0.05585338742381091, -0.24195488034992627, 0.14651454779270448, -0.13141132530903346, -0.1465627524242001, -0.0541850363615116, 0.044793109385002604, 0.03783921463917451, -0.2938662292435765, 0.08916608174867609, 0.05773842158898907, 0.15161979782983268, -0.09200423049103272, -0.23367683323388183, -0.0012604529099342855, 0.07061652926878244, 0.07446299004368484, 0.03455790911654109, 0.04835576782122524, -0.14017589496583432, -0.05873079968640875, 0.3102477051219658, -0.04637907520775211, -0.23034828898840046, 0.11644700260244702, -0.17226335872577406, -0.14889940183217587, 0.10902726375742962, 0.10049916450914584, 0.20063471849272518, -0.09290386857537669, 0.03151342211946796, -0.12504602862923334, 0.135186214618826, 0.15366060879253046, -0.06563165933000978, 0.18143134832835608, 0.058577917320163625, 0.12901580739937918, 0.15706391288519003, -0.05777129280307379, -0.09540997587732579, -0.3119216357406817, -0.22688750100420102, -0.182563772951988, 0.0880092773709054, -0.13136307963156324, -0.21620513725486634, 0.3750241339868425, 0.15211110308423245, 0.2106078786187266, 0.1741892896166782, 0.2180607442891127, 0.20743476900756114, 0.04952402238881117, 0.08472628283657525, 0.1455889115673735, 0.12662261129222124, 0.04703327719318239, -0.10574387209980111, 0.05681862023438474, 0.12004516690381263] |
1,802.09705 | Enabling Multiple Access for Non-Line-of-Sight Light-to-Camera
Communications | Light-to-Camera Communications (LCC) have emerged as a new wireless
communication technology with great potential to benefit a broad range of
applications. However, the existing LCC systems either require cameras directly
facing to the lights or can only communicate over a single link, resulting in
low throughputs and being fragile to ambient illuminant interference. We
present HYCACO, a novel LCC system, which enables multiple light emitting
diodes (LEDs) with an unaltered camera to communicate via the non-line-of-sight
(NLoS) links. Different from other NLoS LCC systems, the proposed scheme is
resilient to the complex indoor luminous environment. HYCACO can decode the
messages by exploring the mixed reflected optical signals transmitted from
multiple LEDs. By further exploiting the rolling shutter mechanism, we present
the optimal optical frequencies and camera exposure duration selection strategy
to achieve the best performance. We built a hardware prototype to demonstrate
the efficiency of the proposed scheme under different application scenarios.
The experimental results show that the system throughput reaches 4.5 kbps on
iPhone 6s with three transmitters. With the robustness, improved system
throughput and ease of use, HYCACO has great potentials to be used in a wide
range of applications such as advertising, tagging objects, and device
certifications.
| cs.ET cs.NI eess.SP | lighttocamera communications lcc have emerged as a new wireless communication technology with great potential to benefit a broad range of applications however the existing lcc systems either require cameras directly facing to the lights or can only communicate over a single link resulting in low throughputs and being fragile to ambient illuminant interference we present hycaco a novel lcc system which enables multiple light emitting diodes leds with an unaltered camera to communicate via the nonlineofsight nlos links different from other nlos lcc systems the proposed scheme is resilient to the complex indoor luminous environment hycaco can decode the messages by exploring the mixed reflected optical signals transmitted from multiple leds by further exploiting the rolling shutter mechanism we present the optimal optical frequencies and camera exposure duration selection strategy to achieve the best performance we built a hardware prototype to demonstrate the efficiency of the proposed scheme under different application scenarios the experimental results show that the system throughput reaches 45 kbps on iphone 6s with three transmitters with the robustness improved system throughput and ease of use hycaco has great potentials to be used in a wide range of applications such as advertising tagging objects and device certifications | [['lighttocamera', 'communications', 'lcc', 'have', 'emerged', 'as', 'a', 'new', 'wireless', 'communication', 'technology', 'with', 'great', 'potential', 'to', 'benefit', 'a', 'broad', 'range', 'of', 'applications', 'however', 'the', 'existing', 'lcc', 'systems', 'either', 'require', 'cameras', 'directly', 'facing', 'to', 'the', 'lights', 'or', 'can', 'only', 'communicate', 'over', 'a', 'single', 'link', 'resulting', 'in', 'low', 'throughputs', 'and', 'being', 'fragile', 'to', 'ambient', 'illuminant', 'interference', 'we', 'present', 'hycaco', 'a', 'novel', 'lcc', 'system', 'which', 'enables', 'multiple', 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1,802.09706 | Phenotype-based and Self-learning Inter-individual Sleep Apnea Screening
with a Level IV Monitoring System | Purpose: We propose a phenotype-based artificial intelligence system that can
self-learn and is accurate for screening purposes, and test it on a Level IV
monitoring system. Methods: Based on the physiological knowledge, we
hypothesize that the phenotype information will allow us to find subjects from
a well-annotated database that share similar sleep apnea patterns. Therefore,
for a new-arriving subject, we can establish a prediction model from the
existing database that is adaptive to the subject. We test the proposed
algorithm on a database consisting of 62 subjects with the signals recorded
from a Level IV wearable device measuring the thoracic and abdominal movements
and the SpO2. Results: With the leave-one cross validation, the accuracy of the
proposed algorithm to screen subjects with an apnea-hypopnea index greater or
equal to 15 is 93.6%, the positive likelihood ratio is 6.8, and the negative
likelihood ratio is 0.03. Conclusion: The results confirm the hypothesis and
show that the proposed algorithm has great potential to screen patients with
SAS.
| stat.AP | purpose we propose a phenotypebased artificial intelligence system that can selflearn and is accurate for screening purposes and test it on a level iv monitoring system methods based on the physiological knowledge we hypothesize that the phenotype information will allow us to find subjects from a wellannotated database that share similar sleep apnea patterns therefore for a newarriving subject we can establish a prediction model from the existing database that is adaptive to the subject we test the proposed algorithm on a database consisting of 62 subjects with the signals recorded from a level iv wearable device measuring the thoracic and abdominal movements and the spo2 results with the leaveone cross validation the accuracy of the proposed algorithm to screen subjects with an apneahypopnea index greater or equal to 15 is 936 the positive likelihood ratio is 68 and the negative likelihood ratio is 003 conclusion the results confirm the hypothesis and show that the proposed algorithm has great potential to screen patients with sas | [['purpose', 'we', 'propose', 'a', 'phenotypebased', 'artificial', 'intelligence', 'system', 'that', 'can', 'selflearn', 'and', 'is', 'accurate', 'for', 'screening', 'purposes', 'and', 'test', 'it', 'on', 'a', 'level', 'iv', 'monitoring', 'system', 'methods', 'based', 'on', 'the', 'physiological', 'knowledge', 'we', 'hypothesize', 'that', 'the', 'phenotype', 'information', 'will', 'allow', 'us', 'to', 'find', 'subjects', 'from', 'a', 'wellannotated', 'database', 'that', 'share', 'similar', 'sleep', 'apnea', 'patterns', 'therefore', 'for', 'a', 'newarriving', 'subject', 'we', 'can', 'establish', 'a', 'prediction', 'model', 'from', 'the', 'existing', 'database', 'that', 'is', 'adaptive', 'to', 'the', 'subject', 'we', 'test', 'the', 'proposed', 'algorithm', 'on', 'a', 'database', 'consisting', 'of', '62', 'subjects', 'with', 'the', 'signals', 'recorded', 'from', 'a', 'level', 'iv', 'wearable', 'device', 'measuring', 'the', 'thoracic', 'and', 'abdominal', 'movements', 'and', 'the', 'spo2', 'results', 'with', 'the', 'leaveone', 'cross', 'validation', 'the', 'accuracy', 'of', 'the', 'proposed', 'algorithm', 'to', 'screen', 'subjects', 'with', 'an', 'apneahypopnea', 'index', 'greater', 'or', 'equal', 'to', '15', 'is', '936', 'the', 'positive', 'likelihood', 'ratio', 'is', '68', 'and', 'the', 'negative', 'likelihood', 'ratio', 'is', '003', 'conclusion', 'the', 'results', 'confirm', 'the', 'hypothesis', 'and', 'show', 'that', 'the', 'proposed', 'algorithm', 'has', 'great', 'potential', 'to', 'screen', 'patients', 'with', 'sas']] | [-0.060537465727636415, 0.014189608554989939, -0.10649648771233718, 0.04312866116709058, -0.05755500185667821, -0.17922531996466082, 0.08125077669873186, 0.38153833373498913, -0.17142314869355155, -0.3571833956130543, 0.09980669796180489, -0.3258989929273632, -0.1808020166535023, 0.21941070522684952, -0.12215105925472627, 0.0453176153187426, 0.10889553917450426, 0.07957474098422258, 0.00047722501790162567, -0.2430891485086509, 0.2468041838175669, 0.06850246705913118, 0.3562789615706442, 0.04076716996532697, 0.11681129157930752, -0.006988086315415661, -0.03149246208815147, 0.0157472177969743, -0.08298090249590137, 0.12839022926626126, 0.24970784040619126, 0.19715888785799932, 0.30141580786255207, -0.3767262157515524, -0.1683298482860421, 0.09810031220744948, 0.08839373330127229, 0.08844552894834407, -0.03538458497821706, -0.31938987570057004, 0.13278152348809175, -0.14575937023872268, -0.06186650848010358, -0.05510170614312154, 0.018371072189986522, -0.014007122032792649, -0.3320319528882363, 0.07252207860894362, -0.005832098832249826, 0.09653911428375644, -0.10661377614618552, -0.11763500067497956, 0.011139083987297866, 0.14824721913188926, 0.05575058387190404, 0.03774318201156472, 0.1642693326004451, -0.096983362596644, -0.12168760829488023, 0.3483020342432356, -0.051018384429886474, -0.1852413977854972, 0.2076161623258514, -0.11591074659824603, -0.09268378551401522, 0.1236130252642476, 0.20628099981695414, 0.07660232912401975, -0.1578100248679565, -0.030711198262494313, -0.005532096837855506, 0.24657029946918907, 0.025521833543240537, -0.05583845542581833, 0.19249990731130662, 0.19220663981384928, 0.010772364890862326, 0.10760568594993873, -0.18882888908532697, -0.010247973800399659, -0.23897205019096399, -0.15440963586763065, -0.14603216334257668, 0.012252546334205345, -0.08955385169446012, -0.12635528024066217, 0.3932167058738284, 0.19836126725038988, 0.15160169267031995, 0.07927810356327512, 0.30556113840954274, 0.05244478628745083, 0.093257424965362, 0.056632187281466254, 0.21311839849265837, 0.035435076432753794, 0.10231718905443637, -0.20321649334231473, 0.12411941454300414, -0.013068967877731005] |
1,802.09707 | Understanding and Enhancing the Transferability of Adversarial Examples | State-of-the-art deep neural networks are known to be vulnerable to
adversarial examples, formed by applying small but malicious perturbations to
the original inputs. Moreover, the perturbations can \textit{transfer across
models}: adversarial examples generated for a specific model will often mislead
other unseen models. Consequently the adversary can leverage it to attack
deployed systems without any query, which severely hinder the application of
deep learning, especially in the areas where security is crucial. In this work,
we systematically study how two classes of factors that might influence the
transferability of adversarial examples. One is about model-specific factors,
including network architecture, model capacity and test accuracy. The other is
the local smoothness of loss function for constructing adversarial examples.
Based on these understanding, a simple but effective strategy is proposed to
enhance transferability. We call it variance-reduced attack, since it utilizes
the variance-reduced gradient to generate adversarial example. The
effectiveness is confirmed by a variety of experiments on both CIFAR-10 and
ImageNet datasets.
| stat.ML cs.CR cs.LG | stateoftheart deep neural networks are known to be vulnerable to adversarial examples formed by applying small but malicious perturbations to the original inputs moreover the perturbations can textittransfer across models adversarial examples generated for a specific model will often mislead other unseen models consequently the adversary can leverage it to attack deployed systems without any query which severely hinder the application of deep learning especially in the areas where security is crucial in this work we systematically study how two classes of factors that might influence the transferability of adversarial examples one is about modelspecific factors including network architecture model capacity and test accuracy the other is the local smoothness of loss function for constructing adversarial examples based on these understanding a simple but effective strategy is proposed to enhance transferability we call it variancereduced attack since it utilizes the variancereduced gradient to generate adversarial example the effectiveness is confirmed by a variety of experiments on both cifar10 and imagenet datasets | [['stateoftheart', 'deep', 'neural', 'networks', 'are', 'known', 'to', 'be', 'vulnerable', 'to', 'adversarial', 'examples', 'formed', 'by', 'applying', 'small', 'but', 'malicious', 'perturbations', 'to', 'the', 'original', 'inputs', 'moreover', 'the', 'perturbations', 'can', 'textittransfer', 'across', 'models', 'adversarial', 'examples', 'generated', 'for', 'a', 'specific', 'model', 'will', 'often', 'mislead', 'other', 'unseen', 'models', 'consequently', 'the', 'adversary', 'can', 'leverage', 'it', 'to', 'attack', 'deployed', 'systems', 'without', 'any', 'query', 'which', 'severely', 'hinder', 'the', 'application', 'of', 'deep', 'learning', 'especially', 'in', 'the', 'areas', 'where', 'security', 'is', 'crucial', 'in', 'this', 'work', 'we', 'systematically', 'study', 'how', 'two', 'classes', 'of', 'factors', 'that', 'might', 'influence', 'the', 'transferability', 'of', 'adversarial', 'examples', 'one', 'is', 'about', 'modelspecific', 'factors', 'including', 'network', 'architecture', 'model', 'capacity', 'and', 'test', 'accuracy', 'the', 'other', 'is', 'the', 'local', 'smoothness', 'of', 'loss', 'function', 'for', 'constructing', 'adversarial', 'examples', 'based', 'on', 'these', 'understanding', 'a', 'simple', 'but', 'effective', 'strategy', 'is', 'proposed', 'to', 'enhance', 'transferability', 'we', 'call', 'it', 'variancereduced', 'attack', 'since', 'it', 'utilizes', 'the', 'variancereduced', 'gradient', 'to', 'generate', 'adversarial', 'example', 'the', 'effectiveness', 'is', 'confirmed', 'by', 'a', 'variety', 'of', 'experiments', 'on', 'both', 'cifar10', 'and', 'imagenet', 'datasets']] | [-0.07696650964498986, 0.014531692877426394, -0.03361208270653151, 0.12275782115466427, -0.1110008482253761, -0.2165457741037244, 0.04914859012933448, 0.4084339913679287, -0.26355361568566876, -0.3485395296942443, 0.1032510503049707, -0.26921145485248416, -0.2562215995581937, 0.22623964468657504, -0.1597273670020513, 0.08561117909412133, 0.08139806976469117, 0.03256219320028322, -0.036896371575130614, -0.3602070097833348, 0.3523219989336212, 0.06578827941812052, 0.31631263091385337, 0.051604909167508595, 0.08552212275017154, -0.08362650057824794, 0.022796419342921582, 0.00578972923613037, -0.04134281494793868, 0.13068145500728862, 0.28855480520255694, 0.20111666545271872, 0.3261580240279727, -0.4144061565049924, -0.2655798346037045, 0.12665695845571462, 0.1146980131874443, 0.15633447948794127, -0.056533108683652245, -0.3525104468339123, 0.13152847471938003, -0.20008887307194528, -0.03042187395349174, -0.1977903825842077, -0.05034881455940195, 0.01589375812727667, -0.303465007242994, -0.01097508653829209, 0.10807296690472867, 0.026364286305033603, -0.023124996141996236, -0.0875522974471096, -0.010722830222221091, 0.14876048937439917, 0.052434167667524886, 0.02663977990159765, 0.1991875678038923, -0.19888492760619556, -0.13242758655833314, 0.32713704586494713, -0.04831939679570496, -0.23091070368100192, 0.22158867135149193, 0.009009328641695902, -0.12636341014003846, 0.07719533490017057, 0.27092385217547416, 0.12527252965664956, -0.14448837855888996, 0.03154572198181995, -0.01747478217439493, 0.16479487258184236, 0.05138008843860007, -0.0011210410084459, 0.13019237467233324, 0.21502135452938093, 0.04689506976283155, 0.174081633600872, -0.11081893038062844, -0.10387933392776176, -0.22616466173203661, -0.053794325607304926, -0.19169179638265632, 0.024929635152511766, -0.09937563762050558, -0.13269727664010134, 0.4076690844085533, 0.2561851283317992, 0.2049266687448835, 0.07788178440150659, 0.3587407098035328, 0.00586370968958363, 0.12461247014689433, 0.10866702545899898, 0.22684096688171848, 0.016698061033093837, 0.05065142830353579, -0.1431809680565493, 0.1692846410878701, 0.017083601815102156] |
1,802.09708 | Series solutions of Laguerre- and Jacobi-type differential equations in
terms of orthogonal polynomials and physical applications | We introduce two ordinary second-order linear differential equations of the
Laguerre- and Jacobi-type. Solutions are written as infinite series of square
integrable functions in terms of the Laguerre and Jacobi polynomials,
respectively. The expansion coefficients of the series satisfy three-term
recursion relations, which are solved in terms of orthogonal polynomials with
continuous and/or discrete spectra. Most of these are well-known polynomials
whereas few are not. We present physical applications of these differential
equations in quantum mechanics.
| math-ph math.MP | we introduce two ordinary secondorder linear differential equations of the laguerre and jacobitype solutions are written as infinite series of square integrable functions in terms of the laguerre and jacobi polynomials respectively the expansion coefficients of the series satisfy threeterm recursion relations which are solved in terms of orthogonal polynomials with continuous andor discrete spectra most of these are wellknown polynomials whereas few are not we present physical applications of these differential equations in quantum mechanics | [['we', 'introduce', 'two', 'ordinary', 'secondorder', 'linear', 'differential', 'equations', 'of', 'the', 'laguerre', 'and', 'jacobitype', 'solutions', 'are', 'written', 'as', 'infinite', 'series', 'of', 'square', 'integrable', 'functions', 'in', 'terms', 'of', 'the', 'laguerre', 'and', 'jacobi', 'polynomials', 'respectively', 'the', 'expansion', 'coefficients', 'of', 'the', 'series', 'satisfy', 'threeterm', 'recursion', 'relations', 'which', 'are', 'solved', 'in', 'terms', 'of', 'orthogonal', 'polynomials', 'with', 'continuous', 'andor', 'discrete', 'spectra', 'most', 'of', 'these', 'are', 'wellknown', 'polynomials', 'whereas', 'few', 'are', 'not', 'we', 'present', 'physical', 'applications', 'of', 'these', 'differential', 'equations', 'in', 'quantum', 'mechanics']] | [-0.18902270370898278, 0.10237144217458799, -0.048962787277751454, 0.0518705373397097, -0.1039567535473524, -0.12848219155382953, -0.10627369669045468, 0.304715684235194, -0.3372057896845753, -0.21204986180619975, 0.13233447235573917, -0.31545890171669033, -0.18847548094038902, 0.2035371505189687, -0.028770335588457163, 0.14918350403374797, 0.010548774869867453, 0.020566676455353827, -0.17091549741790482, -0.3068825748571391, 0.3220664230052774, -0.0733914076255659, 0.17231196747161448, -0.0628145654214007, 0.14905272936448455, -0.032430011270518755, -0.07843313566225238, -0.06704773881325596, -0.10625276810146476, 0.1281296751756025, 0.33056060300747814, 0.08555611096150977, 0.2238826932091462, -0.4434601436614206, -0.10840737509639248, 0.10870639325462673, 0.20306585944796862, 0.025505977782335033, 0.021677330344621288, -0.22141526255903668, 0.014106644550338387, -0.1459303043421211, -0.17749349392129501, -0.1383371778739322, -0.04622014028044712, 0.18538975544077785, -0.25162821376426636, 0.14055682696696176, 0.05931904826215223, 0.12995393733543, -0.017362584773524616, -0.1727588758191192, 0.021631962270475924, 0.03247051523067057, -0.017828596002226204, -0.10637043050098184, -0.002919337491651899, -0.0939419777500198, -0.123205019504224, 0.40681725697542886, -0.0618929277835904, -0.31920223726008673, 0.10327697264667797, -0.19016677991634137, -0.19451831408322937, 0.0973822311559496, 0.14248039907359175, 0.13497467758134007, -0.1530184056609869, 0.11801327124550498, -0.0631823628944786, 0.06572856781023897, 0.17957086749619952, 0.08652938474092241, 0.13652045365520998, -0.06983343259382405, -0.021876753871574214, 0.14347263692731135, 0.06582366164596017, -0.1992103115067278, -0.3539978882196776, -0.15832771656201466, -0.13954143798726268, 0.045862539821667415, -0.16935783214093567, -0.25028679185350866, 0.38003766556319435, 0.039067862310299746, 0.14081963534025768, 0.10443529654692515, 0.17771509422087356, 0.3015671551677913, 0.030490083969198167, 0.027440541656687856, 0.15182403876985373, 0.23900897796939766, 0.09642450255341828, -0.17269986877708057, 0.005635631744026844, 0.2221009593432475] |
1,802.09709 | Fully Dynamic Maximal Independent Set with Sublinear Update Time | A maximal independent set (MIS) can be maintained in an evolving $m$-edge
graph by simply recomputing it from scratch in $O(m)$ time after each update.
But can it be maintained in time sublinear in $m$ in fully dynamic graphs?
We answer this fundamental open question in the affirmative. We present a
deterministic algorithm with amortized update time $O(\min\{\Delta,m^{3/4}\})$,
where $\Delta$ is a fixed bound on the maximum degree in the graph and $m$ is
the (dynamically changing) number of edges.
We further present a distributed implementation of our algorithm with
$O(\min\{\Delta,m^{3/4}\})$ amortized message complexity, and $O(1)$ amortized
round complexity and adjustment complexity (the number of vertices that change
their output after each update). This strengthens a similar result by
Censor-Hillel, Haramaty, and Karnin (PODC'16) that required an assumption of a
non-adaptive oblivious adversary.
| cs.DS | a maximal independent set mis can be maintained in an evolving medge graph by simply recomputing it from scratch in om time after each update but can it be maintained in time sublinear in m in fully dynamic graphs we answer this fundamental open question in the affirmative we present a deterministic algorithm with amortized update time omindeltam34 where delta is a fixed bound on the maximum degree in the graph and m is the dynamically changing number of edges we further present a distributed implementation of our algorithm with omindeltam34 amortized message complexity and o1 amortized round complexity and adjustment complexity the number of vertices that change their output after each update this strengthens a similar result by censorhillel haramaty and karnin podc16 that required an assumption of a nonadaptive oblivious adversary | [['a', 'maximal', 'independent', 'set', 'mis', 'can', 'be', 'maintained', 'in', 'an', 'evolving', 'medge', 'graph', 'by', 'simply', 'recomputing', 'it', 'from', 'scratch', 'in', 'om', 'time', 'after', 'each', 'update', 'but', 'can', 'it', 'be', 'maintained', 'in', 'time', 'sublinear', 'in', 'm', 'in', 'fully', 'dynamic', 'graphs', 'we', 'answer', 'this', 'fundamental', 'open', 'question', 'in', 'the', 'affirmative', 'we', 'present', 'a', 'deterministic', 'algorithm', 'with', 'amortized', 'update', 'time', 'omindeltam34', 'where', 'delta', 'is', 'a', 'fixed', 'bound', 'on', 'the', 'maximum', 'degree', 'in', 'the', 'graph', 'and', 'm', 'is', 'the', 'dynamically', 'changing', 'number', 'of', 'edges', 'we', 'further', 'present', 'a', 'distributed', 'implementation', 'of', 'our', 'algorithm', 'with', 'omindeltam34', 'amortized', 'message', 'complexity', 'and', 'o1', 'amortized', 'round', 'complexity', 'and', 'adjustment', 'complexity', 'the', 'number', 'of', 'vertices', 'that', 'change', 'their', 'output', 'after', 'each', 'update', 'this', 'strengthens', 'a', 'similar', 'result', 'by', 'censorhillel', 'haramaty', 'and', 'karnin', 'podc16', 'that', 'required', 'an', 'assumption', 'of', 'a', 'nonadaptive', 'oblivious', 'adversary']] | [-0.1620096071514728, 0.11763877388202809, -0.05237472861571083, -0.007540885887731959, -0.07602357519685495, -0.19985752264948042, 0.17265942756128602, 0.3965285936916681, -0.29878381865197107, -0.37989368882114277, 0.09909915088682919, -0.21088468781987527, -0.12768404398820735, 0.11126329627630294, -0.13804478124764405, 0.07248222828261498, 0.08345290207780226, 0.047958413272031715, 0.017668055123614527, -0.35611034794649304, 0.22235876491338827, 0.05632725673993783, 0.17063152446250493, 0.004138265764410782, 0.07477981378359341, 0.04138184631159319, -0.03082373820917499, 0.048996255615782136, -0.10798723509421841, 0.05138627356408458, 0.25416380900861624, 0.21055930853628552, 0.29912779859750344, -0.4327523096051431, -0.12338911067769702, 0.13047575441896356, 0.1574086411042083, 0.10786663180329185, -0.027265499766103755, -0.23177885458125433, 0.09437512172231997, -0.1120158917809131, -0.05581423826078023, 0.010615700204625614, 0.052931818437125334, -0.03519069872572458, -0.2838737137521148, -0.006489729263672703, 0.1005073653506045, 0.0075714063543574255, 0.017025128201252425, -0.07855808844481756, 0.018587818326379516, 0.11320037170159246, -0.035164289804665065, 0.12750778634003118, 0.07327918567400622, -0.06351755157680272, -0.1638648967237625, 0.3092881781259145, -0.08031442194924991, -0.17451613140117406, 0.08248927387499944, -0.07532409839030124, -0.18405037063096924, 0.12720230790695414, 0.15669487865074516, 0.14428039037279392, -0.08831654767386783, 0.14802264035469329, -0.09920455189771894, 0.218262562110733, 0.09601925240647524, 0.021919807608246356, 0.06709566310265179, 0.1835938937562917, 0.15264929904903574, 0.135739643363058, 0.04145533124468975, -0.04757011799698457, -0.2794739909231999, -0.15451042592583253, -0.23658638828936474, 0.06343080121953797, -0.18791975765760385, -0.12809976110500948, 0.38067553243494795, 0.13198405208374211, 0.24618871431251554, 0.14899686609249985, 0.3164073721316636, 0.07473179457818169, 0.02525036264371995, 0.2523798487513305, 0.1360995076120572, 0.04532628172756474, 0.0681461682928292, -0.2121934537142095, 0.16029223515210092, 0.07669783870276428] |
1,802.0971 | Hot and Dense Homogeneous Nucleonic Matter Constrained by Observations,
Experiment, and Theory | We construct a new class of phenomenological equations of state for
homogeneous matter for use in simulations of hot and dense matter in local
thermodynamic equilibrium. We construct a functional form which respects
experimental, observational and theoretical constraints on the nature of matter
in various density and temperature regimes. Our equation of state matches (i)
the virial coefficients expected from nucleon-nucleon scattering phase shifts,
(ii) experimental measurements of nuclear masses and charge radii, (iii)
observations of neutron star radii, (iv) theory results on the equation of
state of neutron matter near the saturation density, and (v) theory results on
the evolution of the EOS at finite temperatures near the saturation density.
Our analytical model allows one to compute the variation in the thermodynamic
quantities based on the uncertainties in the nature of the nucleon-nucleon
interaction. Finally, we perform a correction to ensure the equation of state
is causal at all densities, temperatures, and electron fractions.
| nucl-th astro-ph.HE astro-ph.SR | we construct a new class of phenomenological equations of state for homogeneous matter for use in simulations of hot and dense matter in local thermodynamic equilibrium we construct a functional form which respects experimental observational and theoretical constraints on the nature of matter in various density and temperature regimes our equation of state matches i the virial coefficients expected from nucleonnucleon scattering phase shifts ii experimental measurements of nuclear masses and charge radii iii observations of neutron star radii iv theory results on the equation of state of neutron matter near the saturation density and v theory results on the evolution of the eos at finite temperatures near the saturation density our analytical model allows one to compute the variation in the thermodynamic quantities based on the uncertainties in the nature of the nucleonnucleon interaction finally we perform a correction to ensure the equation of state is causal at all densities temperatures and electron fractions | [['we', 'construct', 'a', 'new', 'class', 'of', 'phenomenological', 'equations', 'of', 'state', 'for', 'homogeneous', 'matter', 'for', 'use', 'in', 'simulations', 'of', 'hot', 'and', 'dense', 'matter', 'in', 'local', 'thermodynamic', 'equilibrium', 'we', 'construct', 'a', 'functional', 'form', 'which', 'respects', 'experimental', 'observational', 'and', 'theoretical', 'constraints', 'on', 'the', 'nature', 'of', 'matter', 'in', 'various', 'density', 'and', 'temperature', 'regimes', 'our', 'equation', 'of', 'state', 'matches', 'i', 'the', 'virial', 'coefficients', 'expected', 'from', 'nucleonnucleon', 'scattering', 'phase', 'shifts', 'ii', 'experimental', 'measurements', 'of', 'nuclear', 'masses', 'and', 'charge', 'radii', 'iii', 'observations', 'of', 'neutron', 'star', 'radii', 'iv', 'theory', 'results', 'on', 'the', 'equation', 'of', 'state', 'of', 'neutron', 'matter', 'near', 'the', 'saturation', 'density', 'and', 'v', 'theory', 'results', 'on', 'the', 'evolution', 'of', 'the', 'eos', 'at', 'finite', 'temperatures', 'near', 'the', 'saturation', 'density', 'our', 'analytical', 'model', 'allows', 'one', 'to', 'compute', 'the', 'variation', 'in', 'the', 'thermodynamic', 'quantities', 'based', 'on', 'the', 'uncertainties', 'in', 'the', 'nature', 'of', 'the', 'nucleonnucleon', 'interaction', 'finally', 'we', 'perform', 'a', 'correction', 'to', 'ensure', 'the', 'equation', 'of', 'state', 'is', 'causal', 'at', 'all', 'densities', 'temperatures', 'and', 'electron', 'fractions']] | [-0.08302479918685651, 0.14713719740750328, -0.1404034691412122, 0.05710256893202783, -0.028709485426905657, -0.04640588431108383, 0.0654315767644514, 0.29954100282442186, -0.1988674582913518, -0.3030727911349987, 0.03597051671090266, -0.3320892857343537, -0.029780449175966842, 0.15126585806419532, 0.05950224794177038, 0.054547608619736086, 0.012971100741396508, 0.058719530385438236, -0.1430006088929311, -0.19268632975346858, 0.35478292058011696, 0.02555166626228921, 0.2396967795260641, 0.09437070929956051, 0.08022203463159742, -0.024307128982318023, -0.0039472843280002, 0.020196065240569654, -0.21299254315034036, 0.05306956390700033, 0.2357948374667866, 0.07205993698969965, 0.16660069449834766, -0.4538070425751709, -0.23817917195058638, 0.058383882081797046, 0.0687496961995719, 0.135001812730315, -0.058885563659151235, -0.25525868514011946, 0.02947187927521525, -0.20441481261363914, -0.17375377495322497, -0.09522461117575726, 0.031414887612505306, 0.0527001524223916, -0.2751876351093092, 0.15663210866792548, -0.023265587451357032, -0.01291022403616338, -0.16056763435481117, -0.1465839600355755, -0.02729928589223193, 0.04359139488604401, 0.007056129658444515, -0.002050337498827327, 0.16947006472656803, -0.19553377487125898, -0.03729706952168096, 0.37473651349784864, -0.07737112015433188, -0.11081419942389813, 0.18431462892030756, -0.16934796574435407, -0.14585609184277634, 0.13354754828427348, 0.16834617305787342, 0.12626292789054494, -0.13333232971058498, 0.08430409465480836, -0.006279521164364151, 0.17717803042502173, 0.017181331087504664, 0.04761655937219339, 0.24980711346912768, 0.15672411660573657, 0.016420899253458746, 0.055994547443885, -0.12089494509141772, -0.13892967889926608, -0.35047997696129907, -0.0841934776774818, -0.16348864622489218, 0.03384752570230874, -0.12003872386694345, -0.13937274799832414, 0.36517183835197603, 0.15987253378956548, 0.1852340197671325, 0.035642846836708486, 0.2904945213768271, 0.12388115628066683, 0.001989582664663753, 0.08032977939733575, 0.26635877233629507, 0.23356650606578877, 0.08681493135950258, -0.3044914730629253, 0.04618424568926134, 0.05889968110338575] |
1,802.09711 | Impact of damping on superconducting gap oscillations induced by intense
Terahertz pulses | We investigate the interplay between gap oscillations and damping in the
dynamics of superconductors taken out of equilibrium by strong optical pulses
with sub-gap Terahertz frequencies. A semi-phenomenological formalism is
developed to include the damping within the electronic subsystem that arises
from effects beyond BCS, such as interactions between Bogoliubov quasiparticles
and decay of the Higgs mode. Such processes are conveniently expressed as
$T_{1}$ and $T_{2}$ times in the standard pseudospin language for
superconductors. Comparing with data on NbN that we report here, we argue that
the superconducting dynamics in the picosecond time scale, after the pump is
turned off, is governed by the $T_{2}$ process.
| cond-mat.supr-con | we investigate the interplay between gap oscillations and damping in the dynamics of superconductors taken out of equilibrium by strong optical pulses with subgap terahertz frequencies a semiphenomenological formalism is developed to include the damping within the electronic subsystem that arises from effects beyond bcs such as interactions between bogoliubov quasiparticles and decay of the higgs mode such processes are conveniently expressed as t_1 and t_2 times in the standard pseudospin language for superconductors comparing with data on nbn that we report here we argue that the superconducting dynamics in the picosecond time scale after the pump is turned off is governed by the t_2 process | [['we', 'investigate', 'the', 'interplay', 'between', 'gap', 'oscillations', 'and', 'damping', 'in', 'the', 'dynamics', 'of', 'superconductors', 'taken', 'out', 'of', 'equilibrium', 'by', 'strong', 'optical', 'pulses', 'with', 'subgap', 'terahertz', 'frequencies', 'a', 'semiphenomenological', 'formalism', 'is', 'developed', 'to', 'include', 'the', 'damping', 'within', 'the', 'electronic', 'subsystem', 'that', 'arises', 'from', 'effects', 'beyond', 'bcs', 'such', 'as', 'interactions', 'between', 'bogoliubov', 'quasiparticles', 'and', 'decay', 'of', 'the', 'higgs', 'mode', 'such', 'processes', 'are', 'conveniently', 'expressed', 'as', 't_1', 'and', 't_2', 'times', 'in', 'the', 'standard', 'pseudospin', 'language', 'for', 'superconductors', 'comparing', 'with', 'data', 'on', 'nbn', 'that', 'we', 'report', 'here', 'we', 'argue', 'that', 'the', 'superconducting', 'dynamics', 'in', 'the', 'picosecond', 'time', 'scale', 'after', 'the', 'pump', 'is', 'turned', 'off', 'is', 'governed', 'by', 'the', 't_2', 'process']] | [-0.1654405367718834, 0.2572114812396906, -0.07499039400959792, 0.08516962549664349, -0.017330818862285255, -0.13724289915990084, 0.08659098063428658, 0.3888075494576456, -0.27863347240864245, -0.2504137233075387, 0.016780374721044076, -0.29991900576893593, -0.08572632137615725, 0.22604929326313003, 0.063871969381031, 0.011408159111731878, -0.008173553718974427, -0.04678527717830016, -0.05726563571820492, -0.16395175687854513, 0.3181797452051333, 0.019047023983285675, 0.29399309285810954, 0.07029792010445886, 0.07171293899069874, 0.026051807472095737, 0.07229130476590176, -0.030303461090573726, -0.12056197467890738, 0.008026993271174296, 0.2624572705618053, -0.020433685412841303, 0.20947466283281035, -0.49558407396851284, -0.20267414739399375, 0.028464342941934208, 0.1490893410474835, 0.14517641374138449, 0.008461069947170129, -0.30820362976277776, -0.004131410691562056, -0.13259125148486522, -0.0742628894096135, -0.09054050550637942, 0.021853998725144368, -0.0022759234383350835, -0.22372117523051235, 0.12143013972178418, 0.05397235087496843, 0.06461597932502627, -0.022790284576948802, -0.06949465739527577, -0.03517674343695618, 0.04835182064397366, 0.08920448161535326, 0.00521863912636379, 0.16383298583557163, -0.1098418865344083, -0.1137591410902733, 0.37300004469195625, -0.12750267555919598, -0.09548982243626905, 0.14803597152031045, -0.1674352344103544, -0.03600725492919391, 0.11264677628663913, 0.10730808451420294, 0.07875507184357014, -0.15862253547716393, 0.1036593940000287, 0.01760329935207682, 0.1848353772371445, 0.060859477905257836, 0.13436808767025624, 0.2319917487340786, 0.23868919094807012, 0.006666302373457067, 0.14413293504940328, -0.08943017410830471, -0.08574525927158319, -0.29755957454513265, -0.090765985558975, -0.19277040320443087, 0.08024433917225392, -0.014892326302871434, -0.11087553042320991, 0.4078135169814077, 0.1632529655295723, 0.1936877011057903, -0.007916372084884712, 0.2422756556913538, 0.16920138389544281, 0.08669857547249434, 0.03699172445230256, 0.2669528079799043, 0.1513046341781276, 0.10117993332041463, -0.3393326593048976, 0.009661024159593683, 0.012103504387064363] |
1,802.09712 | Mapping a quantum walk by tuning the coupling coefficient | We present a method to map the evolution of photonic random walks that is
compatible with nonclassical input light. Our approach leverages a newly
developed flexible waveguide platform to tune the jumping rate between spatial
modes, allowing the observation of a range of evolution times in a chip of
fixed length. In a proof-of-principle demonstration we reconstruct the
evolution of photons through a uniform array of coupled waveguides by
monitoring the end-face alone. This approach enables direct observation of mode
occupancy at arbitrary resolution, extending the utility of photonic random
walks for quantum simulations and related applications.
| quant-ph physics.optics | we present a method to map the evolution of photonic random walks that is compatible with nonclassical input light our approach leverages a newly developed flexible waveguide platform to tune the jumping rate between spatial modes allowing the observation of a range of evolution times in a chip of fixed length in a proofofprinciple demonstration we reconstruct the evolution of photons through a uniform array of coupled waveguides by monitoring the endface alone this approach enables direct observation of mode occupancy at arbitrary resolution extending the utility of photonic random walks for quantum simulations and related applications | [['we', 'present', 'a', 'method', 'to', 'map', 'the', 'evolution', 'of', 'photonic', 'random', 'walks', 'that', 'is', 'compatible', 'with', 'nonclassical', 'input', 'light', 'our', 'approach', 'leverages', 'a', 'newly', 'developed', 'flexible', 'waveguide', 'platform', 'to', 'tune', 'the', 'jumping', 'rate', 'between', 'spatial', 'modes', 'allowing', 'the', 'observation', 'of', 'a', 'range', 'of', 'evolution', 'times', 'in', 'a', 'chip', 'of', 'fixed', 'length', 'in', 'a', 'proofofprinciple', 'demonstration', 'we', 'reconstruct', 'the', 'evolution', 'of', 'photons', 'through', 'a', 'uniform', 'array', 'of', 'coupled', 'waveguides', 'by', 'monitoring', 'the', 'endface', 'alone', 'this', 'approach', 'enables', 'direct', 'observation', 'of', 'mode', 'occupancy', 'at', 'arbitrary', 'resolution', 'extending', 'the', 'utility', 'of', 'photonic', 'random', 'walks', 'for', 'quantum', 'simulations', 'and', 'related', 'applications']] | [-0.13471045839052992, 0.15211469205768452, -0.09025124441736292, -0.04603714818499752, -0.0591605104933272, -0.16529134322034636, 0.07072971441984638, 0.4367978293352674, -0.24434933993850172, -0.28547715019559505, 0.053658068955386266, -0.24695022453160323, -0.1288504152673959, 0.23681585920360132, 0.00475669909537453, 0.11040816759779454, 0.07917834576411345, -0.044389375130233076, -0.03315200532556118, -0.15843845953800015, 0.24865577043245365, 0.07593667041150297, 0.32034294684561565, 0.022972556138315153, 0.16672679011892413, 0.06338365377915889, -0.04169238361136354, -0.034152776569358466, -0.11732017113768661, 0.14693109908611657, 0.20811642556614482, 0.06002251525078276, 0.277671880760835, -0.41840871402360114, -0.2245547189329242, 0.061291110721061526, 0.14186911832135574, 0.15188765170571117, -0.05638567204395136, -0.2960528095550451, 0.04853992309594124, -0.15180690296608762, -0.16704432417148934, -0.033137790325875445, -0.012944834162817173, 0.019370297334857824, -0.2740649258353047, 0.01775517121447039, 0.022435921232321673, 0.03237664989512606, 0.004092326690202828, 0.026323089025045755, 0.022565703827062064, 0.1011515757292221, -0.08582373613674078, -0.0010980925685966138, 0.14950437819796433, -0.07188803359107643, -0.1835977749361359, 0.3547502040032528, -0.09305721436886444, -0.16490975909952804, 0.16453760745215049, -0.1290087063491378, -0.07969907889161836, 0.14216929876735224, 0.21312983486724577, 0.10716199701095057, -0.10255897650015108, 0.052023519029764015, -0.023527684813538164, 0.2137316680086066, 0.059395750389271175, 0.08947896525340597, 0.2378809893570994, 0.23104153901876248, 0.0562600671738559, 0.17677570664391076, -0.10009569478864522, -0.09030249227587249, -0.2908578330276476, -0.17741676421533578, -0.23219562452568518, 0.06172098606325609, -0.10810479338682309, -0.15301078817202257, 0.4385334308806461, 0.16865000013050804, 0.18238914527536668, 0.07430852312095386, 0.30232612455033303, 0.08939371375755896, 0.08826985004233177, 0.019919578403656938, 0.17942974660737612, 0.1751513957446825, 0.10648580187074744, -0.23518041435619527, 0.008220299377499782, -0.0009126138162904794] |
1,802.09713 | Robust High-Dynamic-Range Vector Magnetometry via Nitrogen-Vacancy
Centers in Diamond | We demonstrate a robust, scale-factor-free vector magnetometer, which uses a
closed-loop frequency-locking scheme to simultaneously track Zeeman-split
resonance pairs of nitrogen-vacancy (NV) centers in diamond. Compared with
open-loop methodologies, this technique is robust against fluctuations in
temperature, resonance linewidth, and contrast; offers a
three-order-of-magnitude increase in dynamic range; and allows for simultaneous
interrogation of multiple transition frequencies. By directly detecting the
resonance frequencies of NV centers aligned along each of the diamond's four
tetrahedral crystallographic axes, we perform full vector reconstruction of an
applied magnetic field.
| quant-ph cond-mat.mes-hall physics.app-ph physics.ins-det | we demonstrate a robust scalefactorfree vector magnetometer which uses a closedloop frequencylocking scheme to simultaneously track zeemansplit resonance pairs of nitrogenvacancy nv centers in diamond compared with openloop methodologies this technique is robust against fluctuations in temperature resonance linewidth and contrast offers a threeorderofmagnitude increase in dynamic range and allows for simultaneous interrogation of multiple transition frequencies by directly detecting the resonance frequencies of nv centers aligned along each of the diamonds four tetrahedral crystallographic axes we perform full vector reconstruction of an applied magnetic field | [['we', 'demonstrate', 'a', 'robust', 'scalefactorfree', 'vector', 'magnetometer', 'which', 'uses', 'a', 'closedloop', 'frequencylocking', 'scheme', 'to', 'simultaneously', 'track', 'zeemansplit', 'resonance', 'pairs', 'of', 'nitrogenvacancy', 'nv', 'centers', 'in', 'diamond', 'compared', 'with', 'openloop', 'methodologies', 'this', 'technique', 'is', 'robust', 'against', 'fluctuations', 'in', 'temperature', 'resonance', 'linewidth', 'and', 'contrast', 'offers', 'a', 'threeorderofmagnitude', 'increase', 'in', 'dynamic', 'range', 'and', 'allows', 'for', 'simultaneous', 'interrogation', 'of', 'multiple', 'transition', 'frequencies', 'by', 'directly', 'detecting', 'the', 'resonance', 'frequencies', 'of', 'nv', 'centers', 'aligned', 'along', 'each', 'of', 'the', 'diamonds', 'four', 'tetrahedral', 'crystallographic', 'axes', 'we', 'perform', 'full', 'vector', 'reconstruction', 'of', 'an', 'applied', 'magnetic', 'field']] | [-0.14691616037641378, 0.13095848968625753, 0.013879412938566768, -0.02757066306384171, -0.025246497846263295, -0.17242366238223278, 0.04832867852905217, 0.501395891343846, -0.22673685894457293, -0.2881366004290826, 0.028873464280246373, -0.26384574336236044, -0.04647834923337488, 0.18030278788989082, -0.021540621306528063, 0.05377306402386988, 0.05248947548953926, 0.03990973157479483, -0.033565071410061244, -0.12314820144982899, 0.24257988418068957, 0.025700788156074635, 0.4098885662196314, -0.02551013740217861, 0.1298199253540267, 0.09065763064495781, 0.08510653409449494, 0.011789361464188379, -0.05931071048492895, 0.12957993062925252, 0.2828452928539585, 0.050547666058820835, 0.2290608213885742, -0.37291411373983413, -0.16843162683550925, 0.08399815641836647, 0.16455261652522227, 0.2134836972636335, -0.08130203316344277, -0.30114271519157815, 0.07620802747414393, -0.09492629516102812, -0.15532451607834766, -0.12307030459975495, -0.05841436995713807, -0.005551556745708427, -0.3207030782585635, 0.08648149677387931, 0.036391929501106084, 0.12947676568566, -0.11131168983068646, -0.06424292248180684, 0.01741259505164207, 0.08053459159701186, -0.05283241857336286, 0.058478992448790984, 0.25363153175943914, -0.020608049631118775, -0.2016505257692188, 0.3227615134023568, -0.08963165976764524, -0.10832970170030261, 0.16082181025789502, -0.16134808171225493, -0.07095727507463273, 0.18014352415852686, 0.1602108527358402, 0.1613218993989422, -0.15192448816207402, 0.0183769570211606, 0.06114191132296315, 0.21062812467708308, 0.08754396481329904, 0.054399413933210516, 0.23015529615256716, 0.1598805072991287, 0.12242345081313569, 0.16705963997416856, -0.19990626240477843, -0.05024422036812586, -0.17619913145420416, -0.11776337546351201, -0.1453510051154915, -0.020555334543699726, -0.0854812445499085, -0.14163835933158064, 0.4179910406567454, 0.17199286684832152, 0.23241259960786384, -0.06422220805851633, 0.3455904885304763, 0.04453350111075184, 0.1308687605730751, -0.010918123957098408, 0.24064632734174238, 0.22173447522663456, 0.08774430551840103, -0.3282416196046945, -0.03312672331162235, -0.051422040112426175] |
1,802.09714 | Robust Actor-Critic Contextual Bandit for Mobile Health (mHealth)
Interventions | We consider the actor-critic contextual bandit for the mobile health
(mHealth) intervention. State-of-the-art decision-making algorithms generally
ignore the outliers in the dataset. In this paper, we propose a novel robust
contextual bandit method for the mHealth. It can achieve the conflicting goal
of reducing the influence of outliers while seeking for a similar solution
compared with the state-of-the-art contextual bandit methods on the datasets
without outliers. Such performance relies on two technologies: (1) the
capped-$\ell_{2}$ norm; (2) a reliable method to set the thresholding
hyper-parameter, which is inspired by one of the most fundamental techniques in
the statistics. Although the model is non-convex and non-differentiable, we
propose an effective reweighted algorithm and provide solid theoretical
analyses. We prove that the proposed algorithm can find sufficiently decreasing
points after each iteration and finally converges after a finite number of
iterations. Extensive experiment results on two datasets demonstrate that our
method can achieve almost identical results compared with state-of-the-art
contextual bandit methods on the dataset without outliers, and significantly
outperform those state-of-the-art methods on the badly noised dataset with
outliers in a variety of parameter settings.
| cs.LG | we consider the actorcritic contextual bandit for the mobile health mhealth intervention stateoftheart decisionmaking algorithms generally ignore the outliers in the dataset in this paper we propose a novel robust contextual bandit method for the mhealth it can achieve the conflicting goal of reducing the influence of outliers while seeking for a similar solution compared with the stateoftheart contextual bandit methods on the datasets without outliers such performance relies on two technologies 1 the cappedell_2 norm 2 a reliable method to set the thresholding hyperparameter which is inspired by one of the most fundamental techniques in the statistics although the model is nonconvex and nondifferentiable we propose an effective reweighted algorithm and provide solid theoretical analyses we prove that the proposed algorithm can find sufficiently decreasing points after each iteration and finally converges after a finite number of iterations extensive experiment results on two datasets demonstrate that our method can achieve almost identical results compared with stateoftheart contextual bandit methods on the dataset without outliers and significantly outperform those stateoftheart methods on the badly noised dataset with outliers in a variety of parameter settings | [['we', 'consider', 'the', 'actorcritic', 'contextual', 'bandit', 'for', 'the', 'mobile', 'health', 'mhealth', 'intervention', 'stateoftheart', 'decisionmaking', 'algorithms', 'generally', 'ignore', 'the', 'outliers', 'in', 'the', 'dataset', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'robust', 'contextual', 'bandit', 'method', 'for', 'the', 'mhealth', 'it', 'can', 'achieve', 'the', 'conflicting', 'goal', 'of', 'reducing', 'the', 'influence', 'of', 'outliers', 'while', 'seeking', 'for', 'a', 'similar', 'solution', 'compared', 'with', 'the', 'stateoftheart', 'contextual', 'bandit', 'methods', 'on', 'the', 'datasets', 'without', 'outliers', 'such', 'performance', 'relies', 'on', 'two', 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1,802.09715 | Chromium-Induced Ferromagnetism with Perpendicular Anisotropy in
Topological Crystalline Insulator SnTe (111) Thin Films | Topological crystalline insulator (TCI) is a recently-discovered topological
phase of matter. It possesses multiple Dirac surface states, which are
protected by the crystal symmetry. This is in contrast to the time reversal
symmetry that is operative in the well-known topological insulators. In the
presence of a Zeeman field and/or strain, the multiple Dirac surface states are
gapped. The high-Chern-number quantum anomalous Hall (QAH) state is predicted
to emerge if the chemical potential resides in all the Zeeman gaps. Here, we
use molecular beam epitaxy to grow 12 double layer (DL) pure and Cr-doped SnTe
(111) thin film on heat-treated SrTiO3 (111) substrate using a quintuple layer
of insulating (Bi0.2Sb0.8)2Te3 topological insulator as a buffer film. The Hall
traces of Cr-doped SnTe film at low temperatures display square hysteresis
loops indicating long-range ferromagnetic order with perpendicular anisotropy.
The Curie temperature of the 12DL Sn0.9Cr0.1Te film is ~ 110 K. Due to the
chemical potential crossing the bulk valence bands, the anomalous Hall
resistance of 12DL Sn0.9Cr0.1Te film is substantially lower than the predicted
quantized value (~1/4 h/e2). It is possible that with systematic tuning the
chemical potential via chemical doping and electrical gating, the
high-Chern-number QAH state can be realized in the Cr-doped SnTe (111) thin
film.
| cond-mat.mes-hall | topological crystalline insulator tci is a recentlydiscovered topological phase of matter it possesses multiple dirac surface states which are protected by the crystal symmetry this is in contrast to the time reversal symmetry that is operative in the wellknown topological insulators in the presence of a zeeman field andor strain the multiple dirac surface states are gapped the highchernnumber quantum anomalous hall qah state is predicted to emerge if the chemical potential resides in all the zeeman gaps here we use molecular beam epitaxy to grow 12 double layer dl pure and crdoped snte 111 thin film on heattreated srtio3 111 substrate using a quintuple layer of insulating bi02sb082te3 topological insulator as a buffer film the hall traces of crdoped snte film at low temperatures display square hysteresis loops indicating longrange ferromagnetic order with perpendicular anisotropy the curie temperature of the 12dl sn09cr01te film is 110 k due to the chemical potential crossing the bulk valence bands the anomalous hall resistance of 12dl sn09cr01te film is substantially lower than the predicted quantized value 14 he2 it is possible that with systematic tuning the chemical potential via chemical doping and electrical gating the highchernnumber qah state can be realized in the crdoped snte 111 thin film | [['topological', 'crystalline', 'insulator', 'tci', 'is', 'a', 'recentlydiscovered', 'topological', 'phase', 'of', 'matter', 'it', 'possesses', 'multiple', 'dirac', 'surface', 'states', 'which', 'are', 'protected', 'by', 'the', 'crystal', 'symmetry', 'this', 'is', 'in', 'contrast', 'to', 'the', 'time', 'reversal', 'symmetry', 'that', 'is', 'operative', 'in', 'the', 'wellknown', 'topological', 'insulators', 'in', 'the', 'presence', 'of', 'a', 'zeeman', 'field', 'andor', 'strain', 'the', 'multiple', 'dirac', 'surface', 'states', 'are', 'gapped', 'the', 'highchernnumber', 'quantum', 'anomalous', 'hall', 'qah', 'state', 'is', 'predicted', 'to', 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1,802.09716 | Boltzmann scaling of spontaneous Hall current and nonequilibrium
spin-polarization | We extend the semiclassical Boltzmann formalism for the anomalous Hall effect
(AHE) in nondegenerate multiband electron systems to the spin Hall effect (SHE)
and unconventional Edelstein effect (UEE, cannot be accounted for by the
conventional Boltzmann equation, unlike the conventional Edelstein effect).
This extension is confirmed by extending the Kohn-Luttinger density-matrix
transport theory in the weak disorder-potential regime. By performing Kubo
linear response calculations in a prototypical multiband model, the Boltzmann
scaling for the AHE/SHE and UEE is found to be valid only if the
disorder-broadening of bands is quite smaller than the minimal intrinsic
energy-scale around the Fermi level. Discussions on this criterion in various
multiband systems are also presented. A qualitative phase diagram is proposed
to show the influences of changing independently the impurity density and
strength of disorder potential on the AHE/SHE and UEE.
| cond-mat.mes-hall | we extend the semiclassical boltzmann formalism for the anomalous hall effect ahe in nondegenerate multiband electron systems to the spin hall effect she and unconventional edelstein effect uee cannot be accounted for by the conventional boltzmann equation unlike the conventional edelstein effect this extension is confirmed by extending the kohnluttinger densitymatrix transport theory in the weak disorderpotential regime by performing kubo linear response calculations in a prototypical multiband model the boltzmann scaling for the aheshe and uee is found to be valid only if the disorderbroadening of bands is quite smaller than the minimal intrinsic energyscale around the fermi level discussions on this criterion in various multiband systems are also presented a qualitative phase diagram is proposed to show the influences of changing independently the impurity density and strength of disorder potential on the aheshe and uee | [['we', 'extend', 'the', 'semiclassical', 'boltzmann', 'formalism', 'for', 'the', 'anomalous', 'hall', 'effect', 'ahe', 'in', 'nondegenerate', 'multiband', 'electron', 'systems', 'to', 'the', 'spin', 'hall', 'effect', 'she', 'and', 'unconventional', 'edelstein', 'effect', 'uee', 'can', 'not', 'be', 'accounted', 'for', 'by', 'the', 'conventional', 'boltzmann', 'equation', 'unlike', 'the', 'conventional', 'edelstein', 'effect', 'this', 'extension', 'is', 'confirmed', 'by', 'extending', 'the', 'kohnluttinger', 'densitymatrix', 'transport', 'theory', 'in', 'the', 'weak', 'disorderpotential', 'regime', 'by', 'performing', 'kubo', 'linear', 'response', 'calculations', 'in', 'a', 'prototypical', 'multiband', 'model', 'the', 'boltzmann', 'scaling', 'for', 'the', 'aheshe', 'and', 'uee', 'is', 'found', 'to', 'be', 'valid', 'only', 'if', 'the', 'disorderbroadening', 'of', 'bands', 'is', 'quite', 'smaller', 'than', 'the', 'minimal', 'intrinsic', 'energyscale', 'around', 'the', 'fermi', 'level', 'discussions', 'on', 'this', 'criterion', 'in', 'various', 'multiband', 'systems', 'are', 'also', 'presented', 'a', 'qualitative', 'phase', 'diagram', 'is', 'proposed', 'to', 'show', 'the', 'influences', 'of', 'changing', 'independently', 'the', 'impurity', 'density', 'and', 'strength', 'of', 'disorder', 'potential', 'on', 'the', 'aheshe', 'and', 'uee']] | [-0.13293128187112785, 0.1628315618097851, -0.09553829866151015, 0.10579176747102152, -0.08980479693488666, -0.15830547977238893, 0.07236234043052213, 0.31465268582450573, -0.265620924718678, -0.25426971890998107, 0.014360539554790766, -0.30438163375688926, -0.15430829597430096, 0.21234703458914603, 0.012398857521583085, 0.02049939117428881, -0.02357059151486114, -0.04219625739173757, -0.10362975122062144, -0.22275670602469258, 0.3027315636855309, 0.05538082582427672, 0.32689173284366174, 0.0841049078558744, 0.031002366756621522, 0.0689070622505689, 0.046864557476645266, 0.0821305950689647, -0.10763322587504431, 0.022779385593754274, 0.2118278299415208, -0.09986245085795721, 0.20015072699774195, -0.4102463253325334, -0.2611941711261386, 0.01627884663089558, 0.1309562450464539, 0.16733789370498722, -0.015089015625589699, -0.2866205193378307, 0.05385255250665877, -0.190312377349646, -0.13346501750250658, -0.08021449486086904, 0.020236352375812002, -0.050818403596403425, -0.23814386615391683, 0.1417873866457268, 0.06482057175426571, 0.07629650776846877, -0.08180770104647511, -0.1400291593262443, -0.028535685123427322, 0.037275287398585565, 0.024132835277770128, 0.023324226991799486, 0.11770465449878463, -0.12298147960876425, -0.11858752478534977, 0.3754944191486747, -0.08726048466320477, -0.17574057814285712, 0.13803615338272518, -0.1948276304018994, -0.07445508067547861, 0.10969416639526133, 0.1015630013136952, 0.08257347887588871, -0.17817941498425272, 0.1277703937884696, -0.04138763048082452, 0.13623790607132294, -0.04027021509698696, 0.050581643492397334, 0.20853685355848736, 0.1778703362715465, -0.01098763149369646, 0.1047962172732999, -0.11725978252426204, -0.07818054766911599, -0.23077466414758452, -0.11867944494483204, -0.24654168727014353, 0.07645072844062707, -0.045573547030195456, -0.14131777049559685, 0.3698449785027791, 0.2083924914399783, 0.14191709730765542, -0.007381128537020197, 0.26424941643382666, 0.20068795934871392, 0.07228219474631327, 0.05433746142899273, 0.2797766523983295, 0.1591724370451023, 0.08575310627412465, -0.3393234510630093, 0.07924776949609319, 0.07013226896696896] |
1,802.09717 | A multi-step approximant for fixed point problem and convex optimization
problem in Hadamard spaces | The purpose of this paper is to propose and analyze a multi-step iterative
algorithm to solve a convex optimization problem and a fixed point problem
posed on a Hadamard space. The convergence properties of the proposed algorithm
are analyzed by employing suitable conditions on the control sequences of
parameters and the structural properties of the under lying space. We aim to
establish strong and del-convergence results of the proposed iterative
algorithm and compute an optimal solution for a minimizer of proper convex
lower semicontinuous function and a common fixed point of a finite family of
total asymptotically nonexpansive mappings in Hadamard spaces. Our results can
be viewed as an extension and generalization of various corresponding results
established in the current literature.
| math.FA | the purpose of this paper is to propose and analyze a multistep iterative algorithm to solve a convex optimization problem and a fixed point problem posed on a hadamard space the convergence properties of the proposed algorithm are analyzed by employing suitable conditions on the control sequences of parameters and the structural properties of the under lying space we aim to establish strong and delconvergence results of the proposed iterative algorithm and compute an optimal solution for a minimizer of proper convex lower semicontinuous function and a common fixed point of a finite family of total asymptotically nonexpansive mappings in hadamard spaces our results can be viewed as an extension and generalization of various corresponding results established in the current literature | [['the', 'purpose', 'of', 'this', 'paper', 'is', 'to', 'propose', 'and', 'analyze', 'a', 'multistep', 'iterative', 'algorithm', 'to', 'solve', 'a', 'convex', 'optimization', 'problem', 'and', 'a', 'fixed', 'point', 'problem', 'posed', 'on', 'a', 'hadamard', 'space', 'the', 'convergence', 'properties', 'of', 'the', 'proposed', 'algorithm', 'are', 'analyzed', 'by', 'employing', 'suitable', 'conditions', 'on', 'the', 'control', 'sequences', 'of', 'parameters', 'and', 'the', 'structural', 'properties', 'of', 'the', 'under', 'lying', 'space', 'we', 'aim', 'to', 'establish', 'strong', 'and', 'delconvergence', 'results', 'of', 'the', 'proposed', 'iterative', 'algorithm', 'and', 'compute', 'an', 'optimal', 'solution', 'for', 'a', 'minimizer', 'of', 'proper', 'convex', 'lower', 'semicontinuous', 'function', 'and', 'a', 'common', 'fixed', 'point', 'of', 'a', 'finite', 'family', 'of', 'total', 'asymptotically', 'nonexpansive', 'mappings', 'in', 'hadamard', 'spaces', 'our', 'results', 'can', 'be', 'viewed', 'as', 'an', 'extension', 'and', 'generalization', 'of', 'various', 'corresponding', 'results', 'established', 'in', 'the', 'current', 'literature']] | [-0.11460299547761679, -0.0021875116418717273, -0.09590868360052505, 0.08397599147089446, -0.05512839838047512, -0.09768184751737863, 0.0926203387605104, 0.3839966855943203, -0.30476923945825546, -0.25340837659314275, 0.16217601828781578, -0.21704049832575645, -0.1830972439299027, 0.2139946343920504, -0.11309601866135684, 0.13017074257756273, 0.04220303091957855, 0.010700689279474318, -0.14386150849750265, -0.2622459745480834, 0.3375308936345391, 0.010471862876632562, 0.2648779923523155, 0.03994133387604961, 0.159421752137132, 0.01522902143963923, -0.004100368870422244, 0.047904320600112744, -0.1590467391021472, 0.13658158161949055, 0.2545647880062461, 0.1561738481512293, 0.3403536530211568, -0.36380286391358824, -0.16169309567194431, 0.1342005465955784, 0.11324103838414885, 0.04959257283868889, -0.07137970304465853, -0.26243623183108866, 0.12163684504339471, -0.084289665450342, -0.13958073229296133, -0.0833049404124419, -0.043953877345969276, 0.04193433061397324, -0.33204354741610587, -0.004554377558330695, 0.07840154242391388, 0.03261028785940046, -0.12285054055197785, -0.11095677587824564, 0.02745300676227392, 0.09277097544400022, 0.030840611626626924, 0.06847885787913886, 0.0824230791729254, -0.05424086060957052, -0.14026883519254624, 0.3527279896055309, -0.06716369940744092, -0.24926374127389864, 0.16843813022132964, -0.05342318120916995, -0.12524176943503942, 0.1203689259942621, 0.20275175729766487, 0.20778443266171961, -0.17341848705740023, 0.1221619587900932, -0.08499023163846384, 0.0994753085760749, 0.048305034501633294, 0.028390747712304196, 0.1061085154748677, 0.15159365949220954, 0.18434327094970893, 0.20360655755212065, -0.024695041562275342, -0.10239193801292762, -0.30401930402343474, -0.1505509044509381, -0.19656775931362064, 0.011592266836669297, -0.1115130873912373, -0.18704704631430408, 0.39050843789009376, 0.12198628719197586, 0.2127526591066271, 0.09484441271827866, 0.2608507201065853, 0.13144868161762133, -0.01553503130999161, 0.10544576514900351, 0.18408720949664711, 0.14393198745674454, 0.03802558524378886, -0.2162263882472568, 0.045497753172336765, 0.15448505690631767] |
1,802.09718 | Perturbative QCD Analysis of Exclusive Processes $e^+e^-\rightarrow VP$
and $e^+e^-\rightarrow TP$ | We study the $e^+e^-\to VP$ and $e^+e^-\to TP$ processes in the perturbative
QCD approach based on $k_T$ factorization, where the $P,V$ and $T$ denotes a
light pseudo-scalar, vector and tensor meson, respectively. We point out in the
case of $e^+e^-\to TP$ transition due to charge conjugation invariance, only
three channels are allowed: $e^+e^-\to a_2^{\pm} \pi^\mp$, $e^+e^-\to
K_2^{*\pm} K^\mp$ and the V-spin suppressed $e^+e^-\to K_2^{*0} \bar
K^0+\overline K_2^{*0} K^0 $. Cross sections of $e^+e^-\to VP$ and $e^+e^-\to
TP$ at $\sqrt{s}=3.67$ GeV and $\sqrt{s}=10.58$ GeV are calculated and the
invariant mass dependence is found to favor the $1/s^4$ power law. Most of our
theoretical results are consistent with the available experimental data and
other predictions can be tested at the ongoing BESIII and forthcoming Belle-II
experiments.
| hep-ph hep-ex | we study the eeto vp and eeto tp processes in the perturbative qcd approach based on k_t factorization where the pv and t denotes a light pseudoscalar vector and tensor meson respectively we point out in the case of eeto tp transition due to charge conjugation invariance only three channels are allowed eeto a_2pm pimp eeto k_2pm kmp and the vspin suppressed eeto k_20 bar k0overline k_20 k0 cross sections of eeto vp and eeto tp at sqrts367 gev and sqrts1058 gev are calculated and the invariant mass dependence is found to favor the 1s4 power law most of our theoretical results are consistent with the available experimental data and other predictions can be tested at the ongoing besiii and forthcoming belleii experiments | [['we', 'study', 'the', 'eeto', 'vp', 'and', 'eeto', 'tp', 'processes', 'in', 'the', 'perturbative', 'qcd', 'approach', 'based', 'on', 'k_t', 'factorization', 'where', 'the', 'pv', 'and', 't', 'denotes', 'a', 'light', 'pseudoscalar', 'vector', 'and', 'tensor', 'meson', 'respectively', 'we', 'point', 'out', 'in', 'the', 'case', 'of', 'eeto', 'tp', 'transition', 'due', 'to', 'charge', 'conjugation', 'invariance', 'only', 'three', 'channels', 'are', 'allowed', 'eeto', 'a_2pm', 'pimp', 'eeto', 'k_2pm', 'kmp', 'and', 'the', 'vspin', 'suppressed', 'eeto', 'k_20', 'bar', 'k0overline', 'k_20', 'k0', 'cross', 'sections', 'of', 'eeto', 'vp', 'and', 'eeto', 'tp', 'at', 'sqrts367', 'gev', 'and', 'sqrts1058', 'gev', 'are', 'calculated', 'and', 'the', 'invariant', 'mass', 'dependence', 'is', 'found', 'to', 'favor', 'the', '1s4', 'power', 'law', 'most', 'of', 'our', 'theoretical', 'results', 'are', 'consistent', 'with', 'the', 'available', 'experimental', 'data', 'and', 'other', 'predictions', 'can', 'be', 'tested', 'at', 'the', 'ongoing', 'besiii', 'and', 'forthcoming', 'belleii', 'experiments']] | [-0.08685578984635262, 0.2045969795008811, -0.0859794408393403, 0.10984266807887859, -0.06857473629837235, -0.14962309413822367, 0.06369725032321488, 0.3233942942655024, -0.1783443589976135, -0.1306580010956774, -0.042854308393240594, -0.4081569370503227, 0.0027144702290267256, 0.14881413131176183, 0.1044962970384707, 0.15616832792584318, 0.11328737426083535, 0.020936089152625452, -0.029537464080688854, -0.20189942072223252, 0.255421269312501, 0.0228477088889728, 0.21524757677689194, 0.18085714074162146, -0.0010624805882495517, 0.025364834499002124, -0.05766526393126696, -0.12952892072498798, -0.1770500398396204, 0.004515953839290887, 0.2753645013474549, 0.07971668778821671, 0.03341325556587738, -0.2899995613920813, -0.057429066410986704, 0.17579105703431802, 0.13324726533998424, 0.014515214840260644, 0.0057760390326924, -0.36765711634846715, 0.18270647778408602, -0.1749657781406616, -0.04849596073909197, -0.1216445638720567, 0.017206406496309987, -0.10926471676793881, -0.386877145699691, 0.08759236748834762, -0.03856708147019769, 0.038887535648730896, -0.00326113729000402, -0.26319930469229197, -0.06683406529676479, -0.023923150023135047, 0.09284032210998702, 0.14516278449639988, 0.22078584632836282, -0.09793254802158723, -0.2091788376720312, 0.4198059558092306, -0.07495175009826198, -0.13229122710763477, 0.09494304869343372, -0.26991599899871893, -0.15640883787030666, 0.11849995437466229, 0.20938326760466833, 0.08203216226277922, -0.1565120952591921, 0.17578288507987358, 0.038590268949822835, 0.10632615769985326, 0.11579682463974071, 0.04438353398970018, 0.11459319199129822, 0.15514340842346427, -0.06021799395481745, 0.00968799498853817, -0.1238425441183305, -0.09470311995149434, -0.411717316134794, -0.10431706345795343, -0.038518407494605826, 0.0789959530501316, -0.04011544142740604, 0.010670471773482858, 0.31898323408483215, 0.06607285164063796, 0.3175781832624731, 0.006326184732218584, 0.32186218314260867, 0.12391648766642901, 0.04151774955292543, 0.09446959416770066, 0.2673676378733944, 0.17215426817225912, 0.16852951489854603, -0.28922685080906374, 0.0301866763853468, -0.015488297709574302] |
1,802.09719 | Electronic structure and optical properties of Sr$_2$IrO$_4$ under
epitaxial strain | We study the modification of the electronic structure in the strong
spin-orbit coupled Sr$_2$IrO$_4$ by epitaxial strain using density functional
methods. Structural optimization shows that strain changes the internal
structural parameters such as the Ir-O-Ir bond angle, which has an important
effect on the band structure. An interesting prediction is the $\Gamma - $X
crossover of the valence band maximum with strain, while the conduction minimum
at M remains unchanged. This in turn suggests strong strain dependence of the
transport properties for the hole doped system, but not when the system is
electron-doped. Taking the measured value of the $\Gamma-X$ separation for the
unstrained case, we predict the $\Gamma - $X crossover of the valence band
maximum to occur for the tensile epitaxial strain $e_{xx} \approx 3\%$. A
minimal tight-binding model within the $J_{\rm eff} = 1/2$ subspace is
developed to describe the main features of the band structure. The optical
absorption spectra under epitaxial strain are computed using density-functional
theory, which explains the observed anisotropy in the optical spectra with the
polarization of the incident light. We show that the optical transitions
between the Ir (d) states, which are dipole forbidden, can be explained in
terms of the admixture of Ir (p) orbitals with the Ir (d) bands.
| cond-mat.mtrl-sci | we study the modification of the electronic structure in the strong spinorbit coupled sr_2iro_4 by epitaxial strain using density functional methods structural optimization shows that strain changes the internal structural parameters such as the iroir bond angle which has an important effect on the band structure an interesting prediction is the gamma x crossover of the valence band maximum with strain while the conduction minimum at m remains unchanged this in turn suggests strong strain dependence of the transport properties for the hole doped system but not when the system is electrondoped taking the measured value of the gammax separation for the unstrained case we predict the gamma x crossover of the valence band maximum to occur for the tensile epitaxial strain e_xx approx 3 a minimal tightbinding model within the j_rm eff 12 subspace is developed to describe the main features of the band structure the optical absorption spectra under epitaxial strain are computed using densityfunctional theory which explains the observed anisotropy in the optical spectra with the polarization of the incident light we show that the optical transitions between the ir d states which are dipole forbidden can be explained in terms of the admixture of ir p orbitals with the ir d bands | [['we', 'study', 'the', 'modification', 'of', 'the', 'electronic', 'structure', 'in', 'the', 'strong', 'spinorbit', 'coupled', 'sr_2iro_4', 'by', 'epitaxial', 'strain', 'using', 'density', 'functional', 'methods', 'structural', 'optimization', 'shows', 'that', 'strain', 'changes', 'the', 'internal', 'structural', 'parameters', 'such', 'as', 'the', 'iroir', 'bond', 'angle', 'which', 'has', 'an', 'important', 'effect', 'on', 'the', 'band', 'structure', 'an', 'interesting', 'prediction', 'is', 'the', 'gamma', 'x', 'crossover', 'of', 'the', 'valence', 'band', 'maximum', 'with', 'strain', 'while', 'the', 'conduction', 'minimum', 'at', 'm', 'remains', 'unchanged', 'this', 'in', 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1,802.0972 | Overview of Approximate Bayesian Computation | This Chapter, "Overview of Approximate Bayesian Computation", is to appear as
the first chapter in the forthcoming Handbook of Approximate Bayesian
Computation (2018). It details the main ideas and concepts behind ABC methods
with many examples and illustrations.
| stat.CO stat.ME stat.ML | this chapter overview of approximate bayesian computation is to appear as the first chapter in the forthcoming handbook of approximate bayesian computation 2018 it details the main ideas and concepts behind abc methods with many examples and illustrations | [['this', 'chapter', 'overview', 'of', 'approximate', 'bayesian', 'computation', 'is', 'to', 'appear', 'as', 'the', 'first', 'chapter', 'in', 'the', 'forthcoming', 'handbook', 'of', 'approximate', 'bayesian', 'computation', '2018', 'it', 'details', 'the', 'main', 'ideas', 'and', 'concepts', 'behind', 'abc', 'methods', 'with', 'many', 'examples', 'and', 'illustrations']] | [-0.00674871585674976, -0.032744017454158315, -0.05733611393033674, 0.11023210430223691, -0.12362909679742236, -0.09035421364272847, -0.0091024878140735, 0.3253471054332821, -0.28626350516232807, -0.3995374237236224, 0.21236837739553793, -0.2402326966586866, -0.2747304114071946, 0.1869739688393709, -0.10641709070401512, 0.05039867302893024, 0.10445276090238047, -0.055408173534823094, -0.09627897395311218, -0.3090905332447667, 0.26054847407105725, 0.10692538492577641, 0.22342464283696914, 0.026369152026937195, 0.048876181171324695, 0.0008268942811379308, -0.1677463944315126, -0.05066877730975026, -0.21887894697781457, 0.2135191811493745, 0.365673248803145, 0.20002550202862998, 0.33885106552196176, -0.4187403728597258, -0.10413090830766841, 0.03312042777389778, 0.18009598793363885, 0.16759567746990606, 0.0055443235476942436, -0.27333057360527546, 0.03735916027309079, -0.17531551983464802, -0.14777313265949488, -0.11235458455293586, 0.03698423338171683, 0.041246468378080624, -0.17357825951062536, 0.016677300286430278, 0.11342904726533513, 0.08091042024132453, 0.06512071586851227, -0.22089645200359978, 0.07581082010935795, 0.048938903859571406, 0.06557228030808467, 0.01907122994184886, 0.09437136621655602, -0.10760056656956869, -0.20898248838554873, 0.3308901888759513, 0.04121372505630318, -0.11446586405662329, 0.17239264398813248, -0.010399932311357636, -0.24775615807524637, 0.04081588005647063, 0.20071294050859778, 0.09025946581785224, -0.15421291543660978, 0.1185783268363019, 0.049214796371463886, 0.11230073736882523, 0.014611981760122274, -0.016910726020700838, 0.1927017898690936, 0.20307900952665428, -0.006978784738365855, 0.07547000239260103, -0.028147776169996513, -0.2066579135624986, -0.4368232970959262, -0.20014736884714743, -0.19475258328020573, -0.015701048345746177, 0.013334312329932704, -0.15700754218299776, 0.4066746498605138, 0.23465635801518434, 0.16581516470269939, 0.022561372894989818, 0.38579794303759146, 0.06318171905341412, -0.07789873792544792, 0.08053708960008073, 0.19001376706690185, 0.19021171385324315, 0.15711878491626857, -0.016463465388178042, 0.016100295290877847, 0.08012035913079192] |
1,802.09721 | Medium-resolution integral-field spectroscopy for high-contrast
exoplanet imaging: Molecule maps of the $\beta$ Pictoris system with SINFONI | ADI and SDI are well-established high-contrast imaging techniques, but their
application is challenging for companions at small angular separations. The aim
of this paper is to investigate to what extent adaptive-optics assisted,
medium-resolution (R$\sim$5000) integral field spectrographs (IFS) can be used
to directly detect the absorption of molecular species in the spectra of
planets and substellar companions when these are not present in the spectrum of
the star. We analyzed archival data of $\beta$ Pictoris taken with the SINFONI
integral field spectrograph (VLT), originally taken to image $\beta$ Pic b
using ADI techniques. At each spatial position in the field, a scaled instance
of the stellar spectrum is subtracted from the data after which the residuals
are cross-correlated with model spectra. The cross-correlation co-adds the
individual absorption lines of the planet emission spectrum constructively, but
not residual telluric and stellar features. Cross-correlation with CO and
H$_2$O models results in significant detections of $\beta$ Pic b at SNRs of
14.5 and 17.0 respectively. Correlation with a 1700K BT-Settl model provides a
signal with an SNR of 25.0. This contrasts with ADI, which barely reveals the
planet. While the AO system only achieved modest Strehl ratios of 19-27%
leading to a raw contrast of 1:240 at the planet position, cross-correlation
achieves a 3$\sigma$ contrast limit of $2.5\times10^{-5}$ in this 2.5h data set
$0.36"$ away from the star. AO-assisted, medium-resolution IFS such as SINFONI
(VLT) and OSIRIS (Keck), can be used for high-contrast imaging utilizing
cross-correlation techniques for planets that are close to their star and
embedded in speckle noise. We refer to this method as molecule mapping, and
advocate its application to observations with future medium resolution
instruments, in particular ERIS (VLT), HARMONI (ELT) and NIRSpec and MIRI
(JWST).
| astro-ph.EP | adi and sdi are wellestablished highcontrast imaging techniques but their application is challenging for companions at small angular separations the aim of this paper is to investigate to what extent adaptiveoptics assisted mediumresolution rsim5000 integral field spectrographs ifs can be used to directly detect the absorption of molecular species in the spectra of planets and substellar companions when these are not present in the spectrum of the star we analyzed archival data of beta pictoris taken with the sinfoni integral field spectrograph vlt originally taken to image beta pic b using adi techniques at each spatial position in the field a scaled instance of the stellar spectrum is subtracted from the data after which the residuals are crosscorrelated with model spectra the crosscorrelation coadds the individual absorption lines of the planet emission spectrum constructively but not residual telluric and stellar features crosscorrelation with co and h_2o models results in significant detections of beta pic b at snrs of 145 and 170 respectively correlation with a 1700k btsettl model provides a signal with an snr of 250 this contrasts with adi which barely reveals the planet while the ao system only achieved modest strehl ratios of 1927 leading to a raw contrast of 1240 at the planet position crosscorrelation achieves a 3sigma contrast limit of 25times105 in this 25h data set 036 away from the star aoassisted mediumresolution ifs such as sinfoni vlt and osiris keck can be used for highcontrast imaging utilizing crosscorrelation techniques for planets that are close to their star and embedded in speckle noise we refer to this method as molecule mapping and advocate its application to observations with future medium resolution instruments in particular eris vlt harmoni elt and nirspec and miri jwst | [['adi', 'and', 'sdi', 'are', 'wellestablished', 'highcontrast', 'imaging', 'techniques', 'but', 'their', 'application', 'is', 'challenging', 'for', 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1,802.09722 | Some knots with surgeries yielding lens spaces | This is a facsimile of the circa 1990 unpublished manuscript with the same
title. All the original text, figures and tables are included; although text
has been reset in \TeX, the original hand-drawn figures have been redrawn
digitally, and the parameter $k$ in the original table of lens spaces has been
replaced with the originally intended $\lambda$. And, of course, this abstract
has been added.
| math.GT | this is a facsimile of the circa 1990 unpublished manuscript with the same title all the original text figures and tables are included although text has been reset in tex the original handdrawn figures have been redrawn digitally and the parameter k in the original table of lens spaces has been replaced with the originally intended lambda and of course this abstract has been added | [['this', 'is', 'a', 'facsimile', 'of', 'the', 'circa', '1990', 'unpublished', 'manuscript', 'with', 'the', 'same', 'title', 'all', 'the', 'original', 'text', 'figures', 'and', 'tables', 'are', 'included', 'although', 'text', 'has', 'been', 'reset', 'in', 'tex', 'the', 'original', 'handdrawn', 'figures', 'have', 'been', 'redrawn', 'digitally', 'and', 'the', 'parameter', 'k', 'in', 'the', 'original', 'table', 'of', 'lens', 'spaces', 'has', 'been', 'replaced', 'with', 'the', 'originally', 'intended', 'lambda', 'and', 'of', 'course', 'this', 'abstract', 'has', 'been', 'added']] | [-0.0691559181723278, 0.06803357157332357, -0.09651765059243189, 0.027118976691781427, -0.11858118874806678, -0.11773545794858364, -0.01632359603900113, 0.3777187230880372, -0.20562862252700143, -0.31931041966890916, 0.14437129157522577, -0.32196717389160767, -0.09879281766143322, 0.16273874938633526, -0.13803819882741664, 0.08958918439748231, 0.0416107279525022, 0.09641648444812745, -0.043440308450954035, -0.36647933248605113, 0.2573980425368063, 0.07508941325795604, 0.19811016056337394, -0.005595828566583805, 0.09738641245348845, -0.03730807703686878, -0.09445125015918165, 0.0013881471095373854, -0.11563048580137547, 0.1137595999016412, 0.2873767363271327, 0.1419348528579576, 0.27883450521039777, -0.349552523373859, -0.19435119057743577, 0.07911632567993365, 0.13440762354457547, 0.14045092431479134, -0.006459329577864992, -0.33369326387764886, 0.12589301334810443, -0.1764855489891488, -0.03580619467902579, -0.021569232316323905, 0.11769356520380825, 0.03866176230076235, -0.13155667726096, -0.012707034504273906, 0.13094076566630974, 0.12525834800908342, -0.021693853566830512, -0.2313277144858148, -0.0020666325435740873, 0.15234319969749777, 0.027409938684286317, 0.09389985269808676, 0.04358081899408717, -0.034623489576915745, -0.09136433183812187, 0.4040330346324481, -0.0038458658673334867, -0.17499270095140673, 0.11033541886718012, -0.06539837004675064, -0.1168575510610026, 0.1503614345965616, 0.0708960499468958, 0.029427054338157177, -0.17928202117036562, 0.18239367107980797, -0.10478139480437676, 0.1981332635587023, 0.16311098880396457, -0.02620143835520139, 0.1394011838710867, 0.12478126232872455, -0.08203524110649596, 0.15780321988859214, -0.05187013471731916, -0.03678656431566196, -0.24037211530958302, -0.1898479382662117, -0.17642456860812672, 0.007489225856261328, 0.03300678917798905, -0.12090077191533055, 0.397313597088214, 0.12494463662733324, 0.1631061237421818, -0.03312811578507535, 0.268064811185468, 0.09148339099192526, 0.1069417841727045, 0.042560300025797915, 0.21270001376979053, 0.06051233746984508, 0.21649371585226618, -0.057585961309087, 0.13263423069292912, 0.08023699684054009] |
1,802.09723 | Recurrent Residual Module for Fast Inference in Videos | Deep convolutional neural networks (CNNs) have made impressive progress in
many video recognition tasks such as video pose estimation and video object
detection. However, CNN inference on video is computationally expensive due to
processing dense frames individually. In this work, we propose a framework
called Recurrent Residual Module (RRM) to accelerate the CNN inference for
video recognition tasks. This framework has a novel design of using the
similarity of the intermediate feature maps of two consecutive frames, to
largely reduce the redundant computation. One unique property of the proposed
method compared to previous work is that feature maps of each frame are
precisely computed. The experiments show that, while maintaining the similar
recognition performance, our RRM yields averagely 2x acceleration on the
commonly used CNNs such as AlexNet, ResNet, deep compression model (thus 8-12x
faster than the original dense models using the efficient inference engine),
and impressively 9x acceleration on some binary networks such as XNOR-Nets
(thus 500x faster than the original model). We further verify the effectiveness
of the RRM on speeding up CNNs for video pose estimation and video object
detection.
| cs.CV | deep convolutional neural networks cnns have made impressive progress in many video recognition tasks such as video pose estimation and video object detection however cnn inference on video is computationally expensive due to processing dense frames individually in this work we propose a framework called recurrent residual module rrm to accelerate the cnn inference for video recognition tasks this framework has a novel design of using the similarity of the intermediate feature maps of two consecutive frames to largely reduce the redundant computation one unique property of the proposed method compared to previous work is that feature maps of each frame are precisely computed the experiments show that while maintaining the similar recognition performance our rrm yields averagely 2x acceleration on the commonly used cnns such as alexnet resnet deep compression model thus 812x faster than the original dense models using the efficient inference engine and impressively 9x acceleration on some binary networks such as xnornets thus 500x faster than the original model we further verify the effectiveness of the rrm on speeding up cnns for video pose estimation and video object detection | [['deep', 'convolutional', 'neural', 'networks', 'cnns', 'have', 'made', 'impressive', 'progress', 'in', 'many', 'video', 'recognition', 'tasks', 'such', 'as', 'video', 'pose', 'estimation', 'and', 'video', 'object', 'detection', 'however', 'cnn', 'inference', 'on', 'video', 'is', 'computationally', 'expensive', 'due', 'to', 'processing', 'dense', 'frames', 'individually', 'in', 'this', 'work', 'we', 'propose', 'a', 'framework', 'called', 'recurrent', 'residual', 'module', 'rrm', 'to', 'accelerate', 'the', 'cnn', 'inference', 'for', 'video', 'recognition', 'tasks', 'this', 'framework', 'has', 'a', 'novel', 'design', 'of', 'using', 'the', 'similarity', 'of', 'the', 'intermediate', 'feature', 'maps', 'of', 'two', 'consecutive', 'frames', 'to', 'largely', 'reduce', 'the', 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1,802.09724 | Coronal properties of the Seyfert 1 galaxy 3C 120 with NuSTAR | We present measurement of the cut-off energy, a proxy for the temperature of
the corona in the nuclear continuum of the Seyfert 1 galaxy 3C 120 using
$\sim$120 ks of observation from ${\it NuSTAR}$. The quality broad band
spectrum from 3$-$79 keV has enabled us to measure the Compton reflection
component (R) and to constrain the temperature of the coronal plasma. Fitting
one of the advanced Comptonization models, ${\it compPS}$ to the observed broad
band spectrum we derived the kinetic temperature of the electrons in the corona
to be $kT_e = 25 \pm 2$ keV with Compton ${\it y}$ parameter of $y = 2.2 \pm
0.1$ for a slab geometry and $kT_e = 26_{-0}^{+2}$ keV with a $y$ of
$2.99_{-0.18}^{+2.99}$ assuming a spherical geometry. We noticed excess
emission from $\sim$10$-$35 keV arising due to Compton reflection and a broad
Fe $K\alpha$ line at 6.43 keV with an equivalent width of 60 $\pm$ 5 eV. The
variations in count rates in the soft (3$-$10 keV) band is found to be more
compared to the hard (10$-$79 keV) band with mean fractional variability
amplitudes of 0.065$\pm$0.002 and 0.052$\pm$0.003 for the soft and hard bands
respectively. 3C 120 is known to have a strong jet, however, our results
indicate that it is either dormant or its contribution if any to the X-ray
emission is negligible during the epoch of ${\it NuSTAR}$ observation.
| astro-ph.HE | we present measurement of the cutoff energy a proxy for the temperature of the corona in the nuclear continuum of the seyfert 1 galaxy 3c 120 using sim120 ks of observation from it nustar the quality broad band spectrum from 379 kev has enabled us to measure the compton reflection component r and to constrain the temperature of the coronal plasma fitting one of the advanced comptonization models it compps to the observed broad band spectrum we derived the kinetic temperature of the electrons in the corona to be kt_e 25 pm 2 kev with compton it y parameter of y 22 pm 01 for a slab geometry and kt_e 26_02 kev with a y of 299_018299 assuming a spherical geometry we noticed excess emission from sim1035 kev arising due to compton reflection and a broad fe kalpha line at 643 kev with an equivalent width of 60 pm 5 ev the variations in count rates in the soft 310 kev band is found to be more compared to the hard 1079 kev band with mean fractional variability amplitudes of 0065pm0002 and 0052pm0003 for the soft and hard bands respectively 3c 120 is known to have a strong jet however our results indicate that it is either dormant or its contribution if any to the xray emission is negligible during the epoch of it nustar observation | [['we', 'present', 'measurement', 'of', 'the', 'cutoff', 'energy', 'a', 'proxy', 'for', 'the', 'temperature', 'of', 'the', 'corona', 'in', 'the', 'nuclear', 'continuum', 'of', 'the', 'seyfert', '1', 'galaxy', '3c', '120', 'using', 'sim120', 'ks', 'of', 'observation', 'from', 'it', 'nustar', 'the', 'quality', 'broad', 'band', 'spectrum', 'from', '379', 'kev', 'has', 'enabled', 'us', 'to', 'measure', 'the', 'compton', 'reflection', 'component', 'r', 'and', 'to', 'constrain', 'the', 'temperature', 'of', 'the', 'coronal', 'plasma', 'fitting', 'one', 'of', 'the', 'advanced', 'comptonization', 'models', 'it', 'compps', 'to', 'the', 'observed', 'broad', 'band', 'spectrum', 'we', 'derived', 'the', 'kinetic', 'temperature', 'of', 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1,802.09725 | High-dimensional ABC | This Chapter, "High-dimensional ABC", is to appear in the forthcoming
Handbook of Approximate Bayesian Computation (2018). It details the main ideas
and concepts behind extending ABC methods to higher dimensions, with supporting
examples and illustrations.
| stat.CO stat.ME stat.ML | this chapter highdimensional abc is to appear in the forthcoming handbook of approximate bayesian computation 2018 it details the main ideas and concepts behind extending abc methods to higher dimensions with supporting examples and illustrations | [['this', 'chapter', 'highdimensional', 'abc', 'is', 'to', 'appear', 'in', 'the', 'forthcoming', 'handbook', 'of', 'approximate', 'bayesian', 'computation', '2018', 'it', 'details', 'the', 'main', 'ideas', 'and', 'concepts', 'behind', 'extending', 'abc', 'methods', 'to', 'higher', 'dimensions', 'with', 'supporting', 'examples', 'and', 'illustrations']] | [-0.024093492382339068, 0.003096228704920837, -0.04100902916065284, 0.11871223912707397, -0.1321974110390459, -0.12823272965283, 0.008199688073779856, 0.326511367729732, -0.25015949571638235, -0.3509212012402713, 0.17438433003678386, -0.2519427687328841, -0.24975779801607131, 0.18959693592041732, -0.14018693290833784, 0.0591586705829416, 0.07490076588998948, -0.10812054920409407, -0.07610962013048785, -0.34544432679457326, 0.2622848785349301, 0.09577950579779489, 0.23661939661417689, 0.005624646001628467, 0.028417140059173108, -0.003644366016877549, -0.1352088185293334, -0.020108052702354533, -0.20293563521866287, 0.25511615944228, 0.35016902408429557, 0.15966893993318082, 0.3049628018268517, -0.3958952149642365, -0.1466995600078787, 0.008445370253840727, 0.17002976829452174, 0.15787012400105596, 0.025937696546316148, -0.29923417711896555, 0.08903107302529471, -0.12482908877011921, -0.18847733461963279, -0.12932466718235186, 0.03139131934814421, -0.003113680300599039, -0.20688843548830066, 0.039494210907391136, 0.11086565197578498, 0.09211632017312306, 0.06558900648461921, -0.2099668680823275, 0.030036853280450616, 0.0406169094145298, 0.06467492789961397, 0.015030343910413128, 0.07011992050600903, -0.09999000116783593, -0.21945817827114036, 0.32618822093520844, 0.06784997747412749, -0.1679400585325701, 0.23702997746212143, -0.05998477353049176, -0.22893867367612464, 0.04740727078169584, 0.18008048459887505, 0.07160788594878145, -0.08025893196463585, 0.13318744913475322, 0.05995233648323587, 0.1379117679915258, 0.04506966064551047, -0.06038403789113675, 0.1690905587614647, 0.182630140733506, 0.008672589462782656, 0.07805700208991766, -0.030611114203929903, -0.20381361969879697, -0.3758203247828143, -0.20001626911440065, -0.18940652443894318, -0.011108574883214066, -0.034903234029687674, -0.14452446006138675, 0.37560225246208057, 0.23124762503430246, 0.18306174908897707, 0.009132481632488115, 0.35057843806488176, 0.08769980597176723, -0.011677865471158708, 0.08761232664276447, 0.1742127584360008, 0.17755991002278668, 0.15774266302386034, -0.008390621987304517, -0.024154149010843996, 0.0674400843679905] |
1,802.09726 | Increasing the efficiency of photon collection in LArTPCs: the ARAPUCA
light trap | The Liquid Argon Time Projection Chambers (LArTPCs) are a choice for the next
generation of large neutrino detectors due to their optimal performance in
particle tracking and calorimetry. The detection of Argon scintillation light
plays a crucial role in the event reconstruction as well as the time reference
for non-beam physics such as supernovae neutrino detection and baryon number
violation studies. In this contribution, we present the current R&D work on the
ARAPUCA (Argon R&D Advanced Program at UNICAMP), a light trap device to enhance
Ar scintillation light collection and thus the overall performance of LArTPCs.
The ARAPUCA working principle is based on a suitable combination of dichroic
filters and wavelength shifters to achieve a high efficiency in light
collection. We discuss the operational principles, the last results of
laboratory tests and the application of the ARAPUCA as the alternative photon
detection system in the protoDUNE detector.
| physics.ins-det hep-ex | the liquid argon time projection chambers lartpcs are a choice for the next generation of large neutrino detectors due to their optimal performance in particle tracking and calorimetry the detection of argon scintillation light plays a crucial role in the event reconstruction as well as the time reference for nonbeam physics such as supernovae neutrino detection and baryon number violation studies in this contribution we present the current rd work on the arapuca argon rd advanced program at unicamp a light trap device to enhance ar scintillation light collection and thus the overall performance of lartpcs the arapuca working principle is based on a suitable combination of dichroic filters and wavelength shifters to achieve a high efficiency in light collection we discuss the operational principles the last results of laboratory tests and the application of the arapuca as the alternative photon detection system in the protodune detector | [['the', 'liquid', 'argon', 'time', 'projection', 'chambers', 'lartpcs', 'are', 'a', 'choice', 'for', 'the', 'next', 'generation', 'of', 'large', 'neutrino', 'detectors', 'due', 'to', 'their', 'optimal', 'performance', 'in', 'particle', 'tracking', 'and', 'calorimetry', 'the', 'detection', 'of', 'argon', 'scintillation', 'light', 'plays', 'a', 'crucial', 'role', 'in', 'the', 'event', 'reconstruction', 'as', 'well', 'as', 'the', 'time', 'reference', 'for', 'nonbeam', 'physics', 'such', 'as', 'supernovae', 'neutrino', 'detection', 'and', 'baryon', 'number', 'violation', 'studies', 'in', 'this', 'contribution', 'we', 'present', 'the', 'current', 'rd', 'work', 'on', 'the', 'arapuca', 'argon', 'rd', 'advanced', 'program', 'at', 'unicamp', 'a', 'light', 'trap', 'device', 'to', 'enhance', 'ar', 'scintillation', 'light', 'collection', 'and', 'thus', 'the', 'overall', 'performance', 'of', 'lartpcs', 'the', 'arapuca', 'working', 'principle', 'is', 'based', 'on', 'a', 'suitable', 'combination', 'of', 'dichroic', 'filters', 'and', 'wavelength', 'shifters', 'to', 'achieve', 'a', 'high', 'efficiency', 'in', 'light', 'collection', 'we', 'discuss', 'the', 'operational', 'principles', 'the', 'last', 'results', 'of', 'laboratory', 'tests', 'and', 'the', 'application', 'of', 'the', 'arapuca', 'as', 'the', 'alternative', 'photon', 'detection', 'system', 'in', 'the', 'protodune', 'detector']] | [-0.05284117411570243, 0.1366570476651648, -0.05856862219468671, 0.028394480074318697, -0.008339671766524817, -0.11922884203468254, 0.040470918230268924, 0.36074897188211785, -0.18537160725535534, -0.34417997355110386, 0.12138461204305874, -0.30295449379217004, -0.05240389683480267, 0.2311921350010132, -0.051345287412011026, 0.119232033566274, 0.06963888829935114, -0.03134076327535317, -0.07426290464631859, -0.21576263251885466, 0.19749907703973593, 0.157998942915781, 0.32429220114967655, 0.06808130692082401, 0.16004712806799176, 0.016837800940067895, -0.08887075774568025, -0.041621937155153374, -0.051577938891643166, 0.05309766738637522, 0.2976861368281906, 0.14767365749342506, 0.19543798815230934, -0.4358742078576161, -0.17663007784875578, 0.10263442966554846, 0.08911742985590684, 0.057850885546099406, -0.13017644676962728, -0.28444193539900237, 0.009231327731181316, -0.17088957425352616, -0.1426306698870446, -0.006882603116809441, -0.02439579803838718, 0.04539932060941616, -0.23936943002528238, -0.0108273269190472, 0.012393215435430753, 0.030502167397311757, -0.014341870271347363, -0.1050638528627844, 0.07638133213487866, 0.0788427945131398, 0.016659995764303877, 0.024241966847963883, 0.20449271166125363, -0.15124690481841715, -0.11130393799837857, 0.38216214115750424, -0.09705992919103033, -0.14759147108918955, 0.17951188567031148, -0.15371207035697845, -0.08638270019211483, 0.1504034977786395, 0.23294505885593136, 0.09628141430985866, -0.1410319507201234, 0.02657762752825293, 0.0005449505311398938, 0.16285865344613992, 0.08127161700177152, 0.10686422005093017, 0.22510636709852233, 0.30019845435598574, 0.08695067953457739, 0.07050652971465876, -0.19734681723480982, 0.004947612561019403, -0.3620052555335217, -0.23127701600101225, -0.15005127831875364, 0.003310138533892883, -0.044493348960076506, -0.11541834306351993, 0.4145003039054066, 0.133766224370243, 0.10184429693796045, -0.027192641955405966, 0.34318290086349057, 0.04346846122267738, 0.05981461864224553, -0.033523900374187295, 0.3069084516796125, 0.09898226486430281, 0.18539877215615747, -0.2739105242475563, 0.06405975815656335, 0.05385815711901048] |
1,802.09727 | Novel vortex structures in the three-dimensional superconductor under
the helical magnetic field from the chiral helimagnet | We have investigated vortex structures in three-dimensional superconductors
under a helical magnetic field from a chiral helimagnet numerically. In order
to obtain vortex structures, we solve three-dimensional Ginzburg-Landau
equations with the finite element method. The distribution of the helical
magnetic field is assumed to be proportional to the distribution of the
magnetic moments in the chiral helimagnet. Then, the magnetic field is the same
direction in the yz-plane and helical rotation along the helical axis. Under
this helical magnetic field, vortices appear to be perpendicular to the surface
of the superconductor. But we have found that there are tilted vortices toward
the helical axis, although there is no component of the magnetic field along
the helical axis. This vortex structure depends on the chirality of the
distribution of the helical magnetic field.
| cond-mat.supr-con | we have investigated vortex structures in threedimensional superconductors under a helical magnetic field from a chiral helimagnet numerically in order to obtain vortex structures we solve threedimensional ginzburglandau equations with the finite element method the distribution of the helical magnetic field is assumed to be proportional to the distribution of the magnetic moments in the chiral helimagnet then the magnetic field is the same direction in the yzplane and helical rotation along the helical axis under this helical magnetic field vortices appear to be perpendicular to the surface of the superconductor but we have found that there are tilted vortices toward the helical axis although there is no component of the magnetic field along the helical axis this vortex structure depends on the chirality of the distribution of the helical magnetic field | [['we', 'have', 'investigated', 'vortex', 'structures', 'in', 'threedimensional', 'superconductors', 'under', 'a', 'helical', 'magnetic', 'field', 'from', 'a', 'chiral', 'helimagnet', 'numerically', 'in', 'order', 'to', 'obtain', 'vortex', 'structures', 'we', 'solve', 'threedimensional', 'ginzburglandau', 'equations', 'with', 'the', 'finite', 'element', 'method', 'the', 'distribution', 'of', 'the', 'helical', 'magnetic', 'field', 'is', 'assumed', 'to', 'be', 'proportional', 'to', 'the', 'distribution', 'of', 'the', 'magnetic', 'moments', 'in', 'the', 'chiral', 'helimagnet', 'then', 'the', 'magnetic', 'field', 'is', 'the', 'same', 'direction', 'in', 'the', 'yzplane', 'and', 'helical', 'rotation', 'along', 'the', 'helical', 'axis', 'under', 'this', 'helical', 'magnetic', 'field', 'vortices', 'appear', 'to', 'be', 'perpendicular', 'to', 'the', 'surface', 'of', 'the', 'superconductor', 'but', 'we', 'have', 'found', 'that', 'there', 'are', 'tilted', 'vortices', 'toward', 'the', 'helical', 'axis', 'although', 'there', 'is', 'no', 'component', 'of', 'the', 'magnetic', 'field', 'along', 'the', 'helical', 'axis', 'this', 'vortex', 'structure', 'depends', 'on', 'the', 'chirality', 'of', 'the', 'distribution', 'of', 'the', 'helical', 'magnetic', 'field']] | [-0.27165442611493, 0.23244751948037778, -0.07001388228540732, 0.007325079797407274, -0.11329892102741834, -0.05751097473054842, -0.07019300071282708, 0.41849333784458315, -0.2691624685980831, -0.2643206845766117, 0.026096508559545106, -0.2101394861485019, -0.09065753687878675, 0.14757513771341604, 0.07558283329038232, -0.007342053594942571, -0.07434896062742072, 0.05698884575924074, -0.07485871988694381, -0.177515078221349, 0.31778304022384074, -0.03520149946262157, 0.3399933758368151, 0.008868201518480695, 0.045592302371832455, -0.04800777737700352, 0.12342399638146162, 0.08755905879661441, -0.14611815912570764, 0.011656695433581868, 0.1324733255685053, -0.10929942359992613, 0.15617263614319998, -0.5106235001320866, -0.1683870048516176, 0.037438246005242974, 0.19105442022467314, 0.16300866544726444, -0.055763086513086986, -0.2721816728907553, 0.1246813393099177, -0.0703011565404295, -0.2290867075331114, -0.057085671426841254, 0.005206589664643009, 0.03783687113106928, -0.2566728327889877, 0.07605847854618773, 0.06684965950041784, 0.13418025241910733, -0.11876496153171033, -0.05572907966702725, -0.10571944537911225, 0.02740403045688502, 0.17329615665331596, 0.1598626345142045, 0.15169156567108902, -0.16804913154699147, -0.12464901906170064, 0.3648284691470591, -0.02819812792409776, -0.20556124846563872, 0.07184039827905397, -0.21776559861080552, -0.08904385302307535, 0.21013701983522906, 0.13105127345911707, 0.10187449937714546, -0.056514609880678385, 0.062241256208367166, -0.09985001143914732, 0.12196673483721855, 0.031373726835502595, -0.026425907184602693, 0.33444407779836294, 0.13693615001852089, 0.06013942216470076, 0.15397132185788712, -0.20527554804875486, -0.08780095541398182, -0.245225370297152, -0.17725061371245168, -0.21324724339259168, 0.01600791751689306, -0.03570113808724052, -0.25022059620118164, 0.4362744382004056, 0.17449437170007237, 0.15642686705850242, -0.09589856413676347, 0.2847914316437461, 0.08838013066402213, 0.106962266521419, 0.11095603277278838, 0.2814150044666321, 0.285852188244462, 0.12849399797569, -0.29233558712858765, 0.01922882051219472, 0.019144164530602706] |
1,802.09728 | Modelling and Analysis of Temporal Preference Drifts Using A
Component-Based Factorised Latent Approach | The changes in user preferences can originate from substantial reasons, like
personality shift, or transient and circumstantial ones, like seasonal changes
in item popularities. Disregarding these temporal drifts in modelling user
preferences can result in unhelpful recommendations. Moreover, different
temporal patterns can be associated with various preference domains, and
preference components and their combinations. These components comprise
preferences over features, preferences over feature values, conditional
dependencies between features, socially-influenced preferences, and bias. For
example, in the movies domain, the user can change his rating behaviour (bias
shift), her preference for genre over language (feature preference shift), or
start favouring drama over comedy (feature value preference shift). In this
paper, we first propose a novel latent factor model to capture the
domain-dependent component-specific temporal patterns in preferences. The
component-based approach followed in modelling the aspects of preferences and
their temporal effects enables us to arbitrarily switch components on and off.
We evaluate the proposed method on three popular recommendation datasets and
show that it significantly outperforms the most accurate state-of-the-art
static models. The experiments also demonstrate the greater robustness and
stability of the proposed dynamic model in comparison with the most successful
models to date. We also analyse the temporal behaviour of different preference
components and their combinations and show that the dynamic behaviour of
preference components is highly dependent on the preference dataset and domain.
Therefore, the results also highlight the importance of modelling temporal
effects but also underline the advantages of a component-based architecture
that is better suited to capture domain-specific balances in the contributions
of the aspects.
| cs.IR cs.AI | the changes in user preferences can originate from substantial reasons like personality shift or transient and circumstantial ones like seasonal changes in item popularities disregarding these temporal drifts in modelling user preferences can result in unhelpful recommendations moreover different temporal patterns can be associated with various preference domains and preference components and their combinations these components comprise preferences over features preferences over feature values conditional dependencies between features sociallyinfluenced preferences and bias for example in the movies domain the user can change his rating behaviour bias shift her preference for genre over language feature preference shift or start favouring drama over comedy feature value preference shift in this paper we first propose a novel latent factor model to capture the domaindependent componentspecific temporal patterns in preferences the componentbased approach followed in modelling the aspects of preferences and their temporal effects enables us to arbitrarily switch components on and off we evaluate the proposed method on three popular recommendation datasets and show that it significantly outperforms the most accurate stateoftheart static models the experiments also demonstrate the greater robustness and stability of the proposed dynamic model in comparison with the most successful models to date we also analyse the temporal behaviour of different preference components and their combinations and show that the dynamic behaviour of preference components is highly dependent on the preference dataset and domain therefore the results also highlight the importance of modelling temporal effects but also underline the advantages of a componentbased architecture that is better suited to capture domainspecific balances in the contributions of the aspects | [['the', 'changes', 'in', 'user', 'preferences', 'can', 'originate', 'from', 'substantial', 'reasons', 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1,802.09729 | Network-Clustered Multi-Modal Bug Localization | Developers often spend much effort and resources to debug a program. To help
the developers debug, numerous information retrieval (IR)-based and
spectrum-based bug localization techniques have been devised. IR-based
techniques process textual information in bug reports, while spectrum-based
techniques process program spectra (i.e., a record of which program elements
are executed for each test case). While both techniques ultimately generate a
ranked list of program elements that likely contain a bug, they only consider
one source of information--either bug reports or program spectra--which is not
optimal. In light of this deficiency, this paper presents a new approach dubbed
Network-clustered Multi-modal Bug Localization (NetML), which utilizes
multi-modal information from both bug reports and program spectra to localize
bugs. NetML facilitates an effective bug localization by carrying out a joint
optimization of bug localization error and clustering of both bug reports and
program elements (i.e., methods). The clustering is achieved through the
incorporation of network Lasso regularization, which incentivizes the model
parameters of similar bug reports and similar program elements to be close
together. To estimate the model parameters of both bug reports and methods,
NetML employs an adaptive learning procedure based on Newton method that
updates the parameters on a per-feature basis. Extensive experiments on 355
real bugs from seven software systems have been conducted to benchmark NetML
against various state-of-the-art localization methods. The results show that
NetML surpasses the best-performing baseline by 31.82%, 22.35%, 19.72%, and
19.24%, in terms of the number of bugs successfully localized when a developer
inspects the top 1, 5, and 10 methods and Mean Average Precision (MAP),
respectively.
| cs.IR cs.LG cs.SE | developers often spend much effort and resources to debug a program to help the developers debug numerous information retrieval irbased and spectrumbased bug localization techniques have been devised irbased techniques process textual information in bug reports while spectrumbased techniques process program spectra ie a record of which program elements are executed for each test case while both techniques ultimately generate a ranked list of program elements that likely contain a bug they only consider one source of informationeither bug reports or program spectrawhich is not optimal in light of this deficiency this paper presents a new approach dubbed networkclustered multimodal bug localization netml which utilizes multimodal information from both bug reports and program spectra to localize bugs netml facilitates an effective bug localization by carrying out a joint optimization of bug localization error and clustering of both bug reports and program elements ie methods the clustering is achieved through the incorporation of network lasso regularization which incentivizes the model parameters of similar bug reports and similar program elements to be close together to estimate the model parameters of both bug reports and methods netml employs an adaptive learning procedure based on newton method that updates the parameters on a perfeature basis extensive experiments on 355 real bugs from seven software systems have been conducted to benchmark netml against various stateoftheart localization methods the results show that netml surpasses the bestperforming baseline by 3182 2235 1972 and 1924 in terms of the number of bugs successfully localized when a developer inspects the top 1 5 and 10 methods and mean average precision map respectively | [['developers', 'often', 'spend', 'much', 'effort', 'and', 'resources', 'to', 'debug', 'a', 'program', 'to', 'help', 'the', 'developers', 'debug', 'numerous', 'information', 'retrieval', 'irbased', 'and', 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1,802.0973 | Causal holographic information does not satisfy the linearized quantum
focusing condition | The Hubeny-Rangamani causal holographic information (CHI) defined by a region
$R$ of a holographic quantum field theory (QFT) is a modern version of the idea
that the area of event horizons might be related to an entropy. Here the event
horizon lives in a dual gravitational bulk theory with Newton's constant
$G_{\rm bulk}$, and the relation involves a factor of $4G_{\rm bulk}$. The fact
that CHI is bounded below by the von Neumann entropy $S$ suggests that CHI is
coarse-grained. Its properties could thus differ markedly from those of $S$. In
particular, recent results imply that when $d\le 4$ holographic QFTs are
perturbatively coupled to $d$-dimensional gravity, the combined system
satisfies the so-called quantum focusing condition (QFC) at leading order in
the new gravitational coupling $G_d$ when the QFT entropy is taken to be that
of von Neumann. However, by studying states dual to spherical bulk (anti--de
Sitter) Schwarschild black holes in the conformal frame for which the boundary
is a $(2+1)$-dimensional de Sitter space, we find the QFC defined by CHI is
violated even when perturbing about a Killing horizon and using a single null
congruence. Since it is known that a generalized second law (GSL) holds in this
context, our work demonstrates that the QFC is not required in order for an
entropy, or an entropy-like quantity, to satisfy such a GSL.
| hep-th gr-qc | the hubenyrangamani causal holographic information chi defined by a region r of a holographic quantum field theory qft is a modern version of the idea that the area of event horizons might be related to an entropy here the event horizon lives in a dual gravitational bulk theory with newtons constant g_rm bulk and the relation involves a factor of 4g_rm bulk the fact that chi is bounded below by the von neumann entropy s suggests that chi is coarsegrained its properties could thus differ markedly from those of s in particular recent results imply that when dle 4 holographic qfts are perturbatively coupled to ddimensional gravity the combined system satisfies the socalled quantum focusing condition qfc at leading order in the new gravitational coupling g_d when the qft entropy is taken to be that of von neumann however by studying states dual to spherical bulk antide sitter schwarschild black holes in the conformal frame for which the boundary is a 21dimensional de sitter space we find the qfc defined by chi is violated even when perturbing about a killing horizon and using a single null congruence since it is known that a generalized second law gsl holds in this context our work demonstrates that the qfc is not required in order for an entropy or an entropylike quantity to satisfy such a gsl | [['the', 'hubenyrangamani', 'causal', 'holographic', 'information', 'chi', 'defined', 'by', 'a', 'region', 'r', 'of', 'a', 'holographic', 'quantum', 'field', 'theory', 'qft', 'is', 'a', 'modern', 'version', 'of', 'the', 'idea', 'that', 'the', 'area', 'of', 'event', 'horizons', 'might', 'be', 'related', 'to', 'an', 'entropy', 'here', 'the', 'event', 'horizon', 'lives', 'in', 'a', 'dual', 'gravitational', 'bulk', 'theory', 'with', 'newtons', 'constant', 'g_rm', 'bulk', 'and', 'the', 'relation', 'involves', 'a', 'factor', 'of', '4g_rm', 'bulk', 'the', 'fact', 'that', 'chi', 'is', 'bounded', 'below', 'by', 'the', 'von', 'neumann', 'entropy', 's', 'suggests', 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1,802.09731 | Pulsar current sheet Cerenkov radiation | Plasma-filled pulsar magnetospheres contain thin current sheets wherein the
charged particles are accelerated by magnetic reconnections to travel at
ultra-relativistic speeds. On the other hand, the plasma frequency of the more
regular force-free regions of the magnetosphere rests almost precisely on the
upper limit of radio frequencies, with the cyclotron frequency being far higher
due to the strong magnetic field. This combination produces a peculiar
situation, whereby radio-frequency waves can travel at subluminal speeds
without becoming evanescent. The conditions are thus conducive to Cerenkov
radiation originating from current sheets, which could plausibly serve as a
coherent radio emission mechanism. In this paper we aim to provide a portrait
of the relevant processes involved, and show that this mechanism can possibly
account for some of the most salient features of the observed radio signals.
| astro-ph.HE | plasmafilled pulsar magnetospheres contain thin current sheets wherein the charged particles are accelerated by magnetic reconnections to travel at ultrarelativistic speeds on the other hand the plasma frequency of the more regular forcefree regions of the magnetosphere rests almost precisely on the upper limit of radio frequencies with the cyclotron frequency being far higher due to the strong magnetic field this combination produces a peculiar situation whereby radiofrequency waves can travel at subluminal speeds without becoming evanescent the conditions are thus conducive to cerenkov radiation originating from current sheets which could plausibly serve as a coherent radio emission mechanism in this paper we aim to provide a portrait of the relevant processes involved and show that this mechanism can possibly account for some of the most salient features of the observed radio signals | [['plasmafilled', 'pulsar', 'magnetospheres', 'contain', 'thin', 'current', 'sheets', 'wherein', 'the', 'charged', 'particles', 'are', 'accelerated', 'by', 'magnetic', 'reconnections', 'to', 'travel', 'at', 'ultrarelativistic', 'speeds', 'on', 'the', 'other', 'hand', 'the', 'plasma', 'frequency', 'of', 'the', 'more', 'regular', 'forcefree', 'regions', 'of', 'the', 'magnetosphere', 'rests', 'almost', 'precisely', 'on', 'the', 'upper', 'limit', 'of', 'radio', 'frequencies', 'with', 'the', 'cyclotron', 'frequency', 'being', 'far', 'higher', 'due', 'to', 'the', 'strong', 'magnetic', 'field', 'this', 'combination', 'produces', 'a', 'peculiar', 'situation', 'whereby', 'radiofrequency', 'waves', 'can', 'travel', 'at', 'subluminal', 'speeds', 'without', 'becoming', 'evanescent', 'the', 'conditions', 'are', 'thus', 'conducive', 'to', 'cerenkov', 'radiation', 'originating', 'from', 'current', 'sheets', 'which', 'could', 'plausibly', 'serve', 'as', 'a', 'coherent', 'radio', 'emission', 'mechanism', 'in', 'this', 'paper', 'we', 'aim', 'to', 'provide', 'a', 'portrait', 'of', 'the', 'relevant', 'processes', 'involved', 'and', 'show', 'that', 'this', 'mechanism', 'can', 'possibly', 'account', 'for', 'some', 'of', 'the', 'most', 'salient', 'features', 'of', 'the', 'observed', 'radio', 'signals']] | [-0.16092163360724926, 0.23085229689101303, -0.0361982163749075, 0.0887580290270437, -0.13192866332093744, -0.10194347345417268, 0.010127381317464537, 0.38602390423893257, -0.23445234815082408, -0.2906808214108075, 0.05523575337418124, -0.2421838687032573, -0.06450996344516936, 0.266774981211916, 0.006815755235633456, -0.04062468482135914, 0.04721159476671312, 0.0022745572953551474, 0.018002530596660155, -0.10411351971944034, 0.2923561956600419, 0.1161569316899474, 0.26708388929360344, 0.031087196123947326, 0.061338339576014506, -0.0864796448723042, 0.008833037531335972, 0.009465702427761223, -0.05395614378795656, 0.08866024922047343, 0.23099808544760808, 0.08387307994088676, 0.21503920058012568, -0.5141504373501188, -0.24812955853942417, 0.06199882765601676, 0.1782373927703873, 0.11060104178985987, -0.04891504765555168, -0.2956641616047661, 0.060112178444694304, -0.12781331377082916, -0.1669869301035384, 0.016451939332992174, 0.003041890463389148, 0.03340185704620037, -0.24583213099521845, 0.0788432171610289, 0.06849625352437475, 0.004985152985559272, -0.0833895669819409, -0.05930436142419178, -0.018855115715624357, 0.07580353543372419, 0.10839379396765753, 0.035042971700843056, 0.19467905116673642, -0.14831284439205228, -0.099064460003668, 0.396169291178983, -0.03855884837028675, -0.12011471476241302, 0.25483669699484807, -0.24464351459077202, -0.09359666143887137, 0.2093377478168647, 0.1803709574295838, 0.09650431164099198, -0.142895682517061, -0.007605742488522083, -0.009537524302118927, 0.11286895988155436, 0.114339355922031, 0.08304247891712457, 0.343840516872592, 0.11959875516525183, 0.049536407890176416, 0.12406639378348057, -0.14607257086825662, -0.009812180297729328, -0.27157547838304935, -0.07426026956129231, -0.11233431271004274, 0.06468118750490248, -0.04959225821949076, -0.17069533367158102, 0.41041130692999167, 0.17644477597808927, 0.16069561774541335, -0.0185641680364462, 0.35596862831678155, 0.12319157611232083, 0.05872940319009069, 0.12849611129009522, 0.31771883000624085, 0.1112780014938794, 0.14427988113377233, -0.2012324321899507, 0.06776143016671776, 0.027050051671851958] |
1,802.09732 | Online learning with kernel losses | We present a generalization of the adversarial linear bandits framework,
where the underlying losses are kernel functions (with an associated
reproducing kernel Hilbert space) rather than linear functions. We study a
version of the exponential weights algorithm and bound its regret in this
setting. Under conditions on the eigendecay of the kernel we provide a sharp
characterization of the regret for this algorithm. When we have polynomial
eigendecay $\mu_j \le \mathcal{O}(j^{-\beta})$, we find that the regret is
bounded by $\mathcal{R}_n \le \mathcal{O}(n^{\beta/(2(\beta-1))})$; while under
the assumption of exponential eigendecay $\mu_j \le \mathcal{O}(e^{-\beta j
})$, we get an even tighter bound on the regret $\mathcal{R}_n \le
\mathcal{O}(n^{1/2}\log(n)^{1/2})$. We also study the full information setting
when the underlying losses are kernel functions and present an adapted
exponential weights algorithm and a conditional gradient descent algorithm.
| stat.ML cs.LG | we present a generalization of the adversarial linear bandits framework where the underlying losses are kernel functions with an associated reproducing kernel hilbert space rather than linear functions we study a version of the exponential weights algorithm and bound its regret in this setting under conditions on the eigendecay of the kernel we provide a sharp characterization of the regret for this algorithm when we have polynomial eigendecay mu_j le mathcalojbeta we find that the regret is bounded by mathcalr_n le mathcalonbeta2beta1 while under the assumption of exponential eigendecay mu_j le mathcaloebeta j we get an even tighter bound on the regret mathcalr_n le mathcalon12logn12 we also study the full information setting when the underlying losses are kernel functions and present an adapted exponential weights algorithm and a conditional gradient descent algorithm | [['we', 'present', 'a', 'generalization', 'of', 'the', 'adversarial', 'linear', 'bandits', 'framework', 'where', 'the', 'underlying', 'losses', 'are', 'kernel', 'functions', 'with', 'an', 'associated', 'reproducing', 'kernel', 'hilbert', 'space', 'rather', 'than', 'linear', 'functions', 'we', 'study', 'a', 'version', 'of', 'the', 'exponential', 'weights', 'algorithm', 'and', 'bound', 'its', 'regret', 'in', 'this', 'setting', 'under', 'conditions', 'on', 'the', 'eigendecay', 'of', 'the', 'kernel', 'we', 'provide', 'a', 'sharp', 'characterization', 'of', 'the', 'regret', 'for', 'this', 'algorithm', 'when', 'we', 'have', 'polynomial', 'eigendecay', 'mu_j', 'le', 'mathcalojbeta', 'we', 'find', 'that', 'the', 'regret', 'is', 'bounded', 'by', 'mathcalr_n', 'le', 'mathcalonbeta2beta1', 'while', 'under', 'the', 'assumption', 'of', 'exponential', 'eigendecay', 'mu_j', 'le', 'mathcaloebeta', 'j', 'we', 'get', 'an', 'even', 'tighter', 'bound', 'on', 'the', 'regret', 'mathcalr_n', 'le', 'mathcalon12logn12', 'we', 'also', 'study', 'the', 'full', 'information', 'setting', 'when', 'the', 'underlying', 'losses', 'are', 'kernel', 'functions', 'and', 'present', 'an', 'adapted', 'exponential', 'weights', 'algorithm', 'and', 'a', 'conditional', 'gradient', 'descent', 'algorithm']] | [-0.09572491101607739, 0.051604375242618516, -0.12354171503830003, 0.14084501660818205, -0.07792551056809316, -0.14936068765746313, 0.058280378698327695, 0.41955758005497046, -0.2713767720852047, -0.2363589492852043, 0.10217487683894433, -0.24518364501273027, -0.19042956092016539, 0.19470030536285776, -0.10470821539638564, 0.08322832935618862, 0.03691680011252174, 0.05109780543921261, -0.0707843453346868, -0.3185582791120396, 0.32500684585102135, 0.07132272289891262, 0.21180537423902024, 0.01632140136189264, 0.1171574290033277, 0.027141119287989568, 0.03453040646854788, -0.027486632923910292, -0.21446345389477983, 0.1040048991835647, 0.19443168758880347, 0.15602898971701507, 0.3595258124987595, -0.3715873250475852, -0.13469975487532793, 0.20435656041263428, 0.10125384998536902, 0.03504074254487932, -0.008729622337341425, -0.2630085297569167, 0.06904576986198663, -0.12636429553822381, -0.05894416275987169, -0.09134189659380354, -0.03829194245736289, 0.01940491195591676, -0.3656746129418025, 0.07466692547109233, 0.15572657703523873, 0.05008892546231891, -0.06672389056348038, -0.16256276469539443, 0.06354405693491572, 0.005466553333917545, -0.005421844483862515, 0.026569181343802484, 0.06253477191125967, -0.12715850666063488, -0.10266118139225, 0.2564951753374771, -0.09987355068381021, -0.22364791827567387, 0.12005260208024993, -0.132459581396688, -0.12934165937986108, 0.07478768658620538, 0.2145479977116338, 0.18960397748742253, -0.08583678590116506, 0.18885253294365612, -0.10505771145835752, 0.1321809785295045, 0.06921866137417965, 0.057452541888778796, -0.008575601306802128, 0.10270249255336239, 0.17875975363858743, 0.16905703262091265, -0.03417137691258176, -0.10012192100475659, -0.3352643597390852, -0.14502859357617126, -0.2059459280117153, 0.027245766549640393, -0.18357202701702136, -0.1580427167355083, 0.34124612506639096, 0.08848996455344604, 0.2563902830479492, 0.21293358007096685, 0.26781410703551956, 0.15351446588465478, 0.016549160518479766, 0.19336851286203682, 0.16363023175563285, 0.1104971806944377, 0.030129671278700698, -0.19494202722580667, 0.12436153777161962, 0.1138477767930226] |
1,802.09733 | Sharp oracle inequalities for stationary points of nonconvex penalized
M-estimators | Many statistical estimation procedures lead to nonconvex optimization
problems. Algorithms to solve these are often guaranteed to output a stationary
point of the optimization problem. Oracle inequalities are an important
theoretical instrument to asses the statistical performance of an estimator.
Oracle results have focused on the theoretical properties of the uncomputable
(global) minimum or maximum. In the present work a general framework used for
convex optimization problems to derive oracle inequalities for stationary
points is extended. A main new ingredient of these oracle inequalities is that
they are sharp: they show closeness to the best approximation within the model
plus a remainder term. We apply this framework to different estimation
problems.
| math.ST stat.TH | many statistical estimation procedures lead to nonconvex optimization problems algorithms to solve these are often guaranteed to output a stationary point of the optimization problem oracle inequalities are an important theoretical instrument to asses the statistical performance of an estimator oracle results have focused on the theoretical properties of the uncomputable global minimum or maximum in the present work a general framework used for convex optimization problems to derive oracle inequalities for stationary points is extended a main new ingredient of these oracle inequalities is that they are sharp they show closeness to the best approximation within the model plus a remainder term we apply this framework to different estimation problems | [['many', 'statistical', 'estimation', 'procedures', 'lead', 'to', 'nonconvex', 'optimization', 'problems', 'algorithms', 'to', 'solve', 'these', 'are', 'often', 'guaranteed', 'to', 'output', 'a', 'stationary', 'point', 'of', 'the', 'optimization', 'problem', 'oracle', 'inequalities', 'are', 'an', 'important', 'theoretical', 'instrument', 'to', 'asses', 'the', 'statistical', 'performance', 'of', 'an', 'estimator', 'oracle', 'results', 'have', 'focused', 'on', 'the', 'theoretical', 'properties', 'of', 'the', 'uncomputable', 'global', 'minimum', 'or', 'maximum', 'in', 'the', 'present', 'work', 'a', 'general', 'framework', 'used', 'for', 'convex', 'optimization', 'problems', 'to', 'derive', 'oracle', 'inequalities', 'for', 'stationary', 'points', 'is', 'extended', 'a', 'main', 'new', 'ingredient', 'of', 'these', 'oracle', 'inequalities', 'is', 'that', 'they', 'are', 'sharp', 'they', 'show', 'closeness', 'to', 'the', 'best', 'approximation', 'within', 'the', 'model', 'plus', 'a', 'remainder', 'term', 'we', 'apply', 'this', 'framework', 'to', 'different', 'estimation', 'problems']] | [-0.05409669768912634, -0.05190576577054647, -0.11974471699664588, 0.17837817022086097, -0.09227647966294138, -0.19747249299643543, 0.061587237503362806, 0.3772327999336863, -0.29842302044811614, -0.3389685480049937, 0.15195964621946317, -0.2633057944224896, -0.1444344255288744, 0.20816851909658327, -0.15568166482262313, 0.18699092488433863, 0.07304326965062467, -0.00759282958198775, -0.10613168710171506, -0.3000733597824971, 0.24985283966855826, 0.03436149276272805, 0.2576466519175819, 0.03801815092630752, 0.08112737298146025, -0.014762102009577525, 0.02858826062675599, 0.03329791120245113, -0.15367015088764951, 0.17059654958424503, 0.3007470742329485, 0.19741310370112727, 0.3861480631303411, -0.4119490576354233, -0.18590110678829858, 0.13522683667555987, 0.1297525407584921, 0.08584383385977498, -0.01137545401217869, -0.24357871388647337, 0.0654409340297518, -0.07362353169938197, -0.10404621083960608, -0.09596943062402911, -0.07544916273757547, 0.03383381958413231, -0.36351574888570354, 0.06941976368024542, 0.06865739226676859, 0.006300739229757439, -0.06736507488683134, -0.1461627037056747, 0.11079168563859688, 0.09217024402827159, 0.07190920038228468, 0.029764145685082954, 0.10681411471670947, -0.08839159986415358, -0.16641239454416004, 0.33212597329203075, 0.0038634457600277825, -0.2348883164572521, 0.1657105915852495, -0.05567150676270594, -0.18262265567659391, 0.11983249882269684, 0.2526743788511266, 0.1445805283036788, -0.21097988720463068, 0.0826338417198811, -0.06804865351164932, 0.13925233375630341, -0.015497602499299892, 0.04172430587103926, 0.12739334687557038, 0.12055224489403872, 0.16391893160091042, 0.17166677180484677, -0.027718066376568918, -0.1277930466489665, -0.32993448954411186, -0.10440848385055156, -0.1979711223958221, -0.024093137156251852, -0.14592042703366093, -0.21252782673885426, 0.3679913715543309, 0.18389372324554232, 0.15211585951918685, 0.08820766516696862, 0.29993999639089713, 0.14624828930424005, 0.0013592753854060025, 0.1213039682028597, 0.26835693008484535, 0.14637145529257822, 0.04483913865175333, -0.16467768888551373, 0.11630127555900463, 0.10444307290353216] |
1,802.09734 | To Stay or to Leave: Churn Prediction for Urban Migrants in the Initial
Period | In China, 260 million people migrate to cities to realize their urban dreams.
Despite that these migrants play an important role in the rapid urbanization
process, many of them fail to settle down and eventually leave the city. The
integration process of migrants thus raises an important issue for scholars and
policymakers.
In this paper, we use Shanghai as an example to investigate migrants'
behavior in their first weeks and in particular, how their behavior relates to
early departure. Our dataset consists of a one-month complete dataset of 698
telecommunication logs between 54 million users, plus a novel and publicly
available housing price data for 18K real estates in Shanghai. We find that
migrants who end up leaving early tend to neither develop diverse connections
in their first weeks nor move around the city. Their active areas also have
higher housing prices than that of staying migrants. We formulate a churn
prediction problem to determine whether a migrant is going to leave based on
her behavior in the first few days. The prediction performance improves as we
include data from more days. Interestingly, when using the same features, the
classifier trained from only the first few days is already as good as the
classifier trained using full data, suggesting that the performance difference
mainly lies in the difference between features.
| cs.SI | in china 260 million people migrate to cities to realize their urban dreams despite that these migrants play an important role in the rapid urbanization process many of them fail to settle down and eventually leave the city the integration process of migrants thus raises an important issue for scholars and policymakers in this paper we use shanghai as an example to investigate migrants behavior in their first weeks and in particular how their behavior relates to early departure our dataset consists of a onemonth complete dataset of 698 telecommunication logs between 54 million users plus a novel and publicly available housing price data for 18k real estates in shanghai we find that migrants who end up leaving early tend to neither develop diverse connections in their first weeks nor move around the city their active areas also have higher housing prices than that of staying migrants we formulate a churn prediction problem to determine whether a migrant is going to leave based on her behavior in the first few days the prediction performance improves as we include data from more days interestingly when using the same features the classifier trained from only the first few days is already as good as the classifier trained using full data suggesting that the performance difference mainly lies in the difference between features | [['in', 'china', '260', 'million', 'people', 'migrate', 'to', 'cities', 'to', 'realize', 'their', 'urban', 'dreams', 'despite', 'that', 'these', 'migrants', 'play', 'an', 'important', 'role', 'in', 'the', 'rapid', 'urbanization', 'process', 'many', 'of', 'them', 'fail', 'to', 'settle', 'down', 'and', 'eventually', 'leave', 'the', 'city', 'the', 'integration', 'process', 'of', 'migrants', 'thus', 'raises', 'an', 'important', 'issue', 'for', 'scholars', 'and', 'policymakers', 'in', 'this', 'paper', 'we', 'use', 'shanghai', 'as', 'an', 'example', 'to', 'investigate', 'migrants', 'behavior', 'in', 'their', 'first', 'weeks', 'and', 'in', 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1,802.09735 | Free-standing bialkali photocathodes using atomically thin substrates | We report successful deposition of high quantum efficiency (QE) bialkali
antimonide K2CsSb photocathodes on graphene films. The results pave a pathway
towards an ultimate goal of encapsulating technologically-relevant
photocathodes for accelerator technology with an atomically-thin protecting
layer to enhance lifetime while minimizing QE losses. A QE of 17 % at ~3.1 eV
(405 nm) is the highest value reported so far on graphene substrates and is
comparable to that obtained on stainless steel and nickel reference substrates.
The spectral responses of the photocathodes on graphene exhibit signature
features of K2CsSb including the characteristic absorption at ~2.5 eV.
Materials characterization based on X-ray fluorescence (XRF) and X-ray
diffraction (XRD) reveals that the composition and crystal quality of these
photocathodes deposited on graphene is comparable to those deposited on a
reference substrate. Quantitative agreement between optical calculations and QE
measurements for the K2CsSb on free suspended graphene and a graphene coated
metal substrate further confirms the high quality interface between the
photocathodes and graphene. Finally, a correlation between the QE and graphene
quality as characterized by Raman spectroscopy suggests that a lower density of
atomistic defects in the graphene films leads to higher QE of the deposited
K2CsSb photocathodes.
| cond-mat.mtrl-sci | we report successful deposition of high quantum efficiency qe bialkali antimonide k2cssb photocathodes on graphene films the results pave a pathway towards an ultimate goal of encapsulating technologicallyrelevant photocathodes for accelerator technology with an atomicallythin protecting layer to enhance lifetime while minimizing qe losses a qe of 17 at 31 ev 405 nm is the highest value reported so far on graphene substrates and is comparable to that obtained on stainless steel and nickel reference substrates the spectral responses of the photocathodes on graphene exhibit signature features of k2cssb including the characteristic absorption at 25 ev materials characterization based on xray fluorescence xrf and xray diffraction xrd reveals that the composition and crystal quality of these photocathodes deposited on graphene is comparable to those deposited on a reference substrate quantitative agreement between optical calculations and qe measurements for the k2cssb on free suspended graphene and a graphene coated metal substrate further confirms the high quality interface between the photocathodes and graphene finally a correlation between the qe and graphene quality as characterized by raman spectroscopy suggests that a lower density of atomistic defects in the graphene films leads to higher qe of the deposited k2cssb photocathodes | [['we', 'report', 'successful', 'deposition', 'of', 'high', 'quantum', 'efficiency', 'qe', 'bialkali', 'antimonide', 'k2cssb', 'photocathodes', 'on', 'graphene', 'films', 'the', 'results', 'pave', 'a', 'pathway', 'towards', 'an', 'ultimate', 'goal', 'of', 'encapsulating', 'technologicallyrelevant', 'photocathodes', 'for', 'accelerator', 'technology', 'with', 'an', 'atomicallythin', 'protecting', 'layer', 'to', 'enhance', 'lifetime', 'while', 'minimizing', 'qe', 'losses', 'a', 'qe', 'of', '17', 'at', '31', 'ev', '405', 'nm', 'is', 'the', 'highest', 'value', 'reported', 'so', 'far', 'on', 'graphene', 'substrates', 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1,802.09736 | Cognitive Radar Antenna Selection via Deep Learning | Direction of arrival (DoA) estimation of targets improves with the number of
elements employed by a phased array radar antenna. Since larger arrays have
high associated cost, area and computational load, there is recent interest in
thinning the antenna arrays without loss of far-field DoA accuracy. In this
context, a cognitive radar may deploy a full array and then select an optimal
subarray to transmit and receive the signals in response to changes in the
target environment. Prior works have used optimization and greedy search
methods to pick the best subarrays cognitively. In this paper, we leverage deep
learning to address the antenna selection problem. Specifically, we construct a
convolutional neural network (CNN) as a multi-class classification framework
where each class designates a different subarray. The proposed network
determines a new array every time data is received by the radar, thereby making
antenna selection a cognitive operation. Our numerical experiments show that
{the proposed CNN structure provides 22% better classification performance than
a Support Vector Machine and the resulting subarrays yield 72% more accurate
DoA estimates than random array selections.
| eess.SP stat.ML | direction of arrival doa estimation of targets improves with the number of elements employed by a phased array radar antenna since larger arrays have high associated cost area and computational load there is recent interest in thinning the antenna arrays without loss of farfield doa accuracy in this context a cognitive radar may deploy a full array and then select an optimal subarray to transmit and receive the signals in response to changes in the target environment prior works have used optimization and greedy search methods to pick the best subarrays cognitively in this paper we leverage deep learning to address the antenna selection problem specifically we construct a convolutional neural network cnn as a multiclass classification framework where each class designates a different subarray the proposed network determines a new array every time data is received by the radar thereby making antenna selection a cognitive operation our numerical experiments show that the proposed cnn structure provides 22 better classification performance than a support vector machine and the resulting subarrays yield 72 more accurate doa estimates than random array selections | [['direction', 'of', 'arrival', 'doa', 'estimation', 'of', 'targets', 'improves', 'with', 'the', 'number', 'of', 'elements', 'employed', 'by', 'a', 'phased', 'array', 'radar', 'antenna', 'since', 'larger', 'arrays', 'have', 'high', 'associated', 'cost', 'area', 'and', 'computational', 'load', 'there', 'is', 'recent', 'interest', 'in', 'thinning', 'the', 'antenna', 'arrays', 'without', 'loss', 'of', 'farfield', 'doa', 'accuracy', 'in', 'this', 'context', 'a', 'cognitive', 'radar', 'may', 'deploy', 'a', 'full', 'array', 'and', 'then', 'select', 'an', 'optimal', 'subarray', 'to', 'transmit', 'and', 'receive', 'the', 'signals', 'in', 'response', 'to', 'changes', 'in', 'the', 'target', 'environment', 'prior', 'works', 'have', 'used', 'optimization', 'and', 'greedy', 'search', 'methods', 'to', 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1,802.09737 | Proceedings 14th International Conference on Quantum Physics and Logic | This volume contains the proceedings of the 14th International Conference on
Quantum Physics and Logic (QPL 2017), which was held July 3-7, 2017 at the LUX
Cinema Nijmegen, the Netherlands, and was hosted by Radboud University. QPL is
a conference that brings together researchers working on mathematical
foundations of quantum physics, quantum computing, and related areas, with a
focus on structural perspectives and the use of logical tools, ordered
algebraic and category-theoretic structures, formal languages, semantical
methods, and other computer science techniques applied to the study of physical
behaviour in general. This conference also welcomes work that applies
structures and methods inspired by quantum theory to other fields (including
computer science).
| cs.LO cs.PL | this volume contains the proceedings of the 14th international conference on quantum physics and logic qpl 2017 which was held july 37 2017 at the lux cinema nijmegen the netherlands and was hosted by radboud university qpl is a conference that brings together researchers working on mathematical foundations of quantum physics quantum computing and related areas with a focus on structural perspectives and the use of logical tools ordered algebraic and categorytheoretic structures formal languages semantical methods and other computer science techniques applied to the study of physical behaviour in general this conference also welcomes work that applies structures and methods inspired by quantum theory to other fields including computer science | [['this', 'volume', 'contains', 'the', 'proceedings', 'of', 'the', '14th', 'international', 'conference', 'on', 'quantum', 'physics', 'and', 'logic', 'qpl', '2017', 'which', 'was', 'held', 'july', '37', '2017', 'at', 'the', 'lux', 'cinema', 'nijmegen', 'the', 'netherlands', 'and', 'was', 'hosted', 'by', 'radboud', 'university', 'qpl', 'is', 'a', 'conference', 'that', 'brings', 'together', 'researchers', 'working', 'on', 'mathematical', 'foundations', 'of', 'quantum', 'physics', 'quantum', 'computing', 'and', 'related', 'areas', 'with', 'a', 'focus', 'on', 'structural', 'perspectives', 'and', 'the', 'use', 'of', 'logical', 'tools', 'ordered', 'algebraic', 'and', 'categorytheoretic', 'structures', 'formal', 'languages', 'semantical', 'methods', 'and', 'other', 'computer', 'science', 'techniques', 'applied', 'to', 'the', 'study', 'of', 'physical', 'behaviour', 'in', 'general', 'this', 'conference', 'also', 'welcomes', 'work', 'that', 'applies', 'structures', 'and', 'methods', 'inspired', 'by', 'quantum', 'theory', 'to', 'other', 'fields', 'including', 'computer', 'science']] | [-0.055807318165059294, 0.1032780092728727, -0.12888018076668853, 0.04228275157993676, -0.14748732600495354, -0.13402146292296616, 0.02617454636938501, 0.24128708348248726, -0.21252537046733253, -0.3766900782666362, 0.11673261743638799, -0.30260229695730984, -0.19198555277811513, 0.2583816909810176, -0.12524380690946774, 0.03417525641611769, 0.049976855289895795, 0.014449614448355394, -0.05035684376468395, -0.3359098908426408, 0.2607938999574692, 0.09560341306181776, 0.3468518127930594, 0.08321130558479208, 0.07519765758702347, 0.035355000488191575, -0.09918606527955146, 0.001940361568116927, -0.12888323052155445, 0.21032724787086785, 0.39214892703872006, 0.18027541831320337, 0.2838030146804076, -0.47109180244172477, -0.14431111893809592, -0.048973595448727675, -0.029752879093090694, 0.07552101356837361, -0.04001237884235174, -0.3551689060320994, -0.00917799250633867, -0.1982805570168001, -0.06852657185984892, -0.007807159156203983, 0.05735112179641251, 0.0004452135778862882, -0.10316041059926287, 0.0007421568197068163, 0.0790740308493532, 0.19962897195941182, 0.019936021769771706, -0.1465537759647411, 0.07288778617218775, 0.11674884916492947, -0.05561985045058972, 0.05978992876600944, 0.13164656747212247, -0.1159535232304201, -0.26738910053999304, 0.41395748290023554, 0.02945236842408105, -0.02690758226074379, 0.24792910885351063, -0.09443844830499845, -0.25228191923081605, -0.0027069289128187003, 0.241448818361974, 0.03694487668926249, -0.13758688591638799, 0.23262728026675833, 0.03075483590700068, 0.2032474875156474, 0.10914301434699614, -0.01940543665330404, 0.24558644079779451, 0.155510845334009, -0.023002354528855632, 0.07297030565389725, -0.020118592195800162, -0.17994690790084433, -0.29849050187312803, -0.143520491361316, -0.12661791456284355, -0.0016503440602137162, 0.07397237718029279, -0.13958904464301225, 0.3581181059576789, 0.1377952203095832, 0.04122761169318445, -0.03982850390057466, 0.24287185772334705, 0.023479943824428563, 0.035348269517894264, 0.07252038403221213, 0.19388472289371364, 0.17611576611310378, 0.2250482154724834, -0.10744148008588299, 0.00866677164024598, 0.10678651096794319] |
1,802.09738 | Quantum enhanced optomechanical magnetometry | The resonant enhancement of both mechanical and optical response in
microcavity optomechanical devices allows exquisitely sensitive measurements of
stimuli such as acceleration, mass and magnetic fields. In this work, we show
that quantum correlated light can improve the performance of such sensors,
increasing both their sensitivity and their bandwidth. Specifically, we develop
a silicon-chip based cavity optomechanical magnetometer that incorporates phase
squeezed light to suppress optical shot noise. At frequencies where shot noise
is the dominant noise source this allows a 20% improvement in magnetic field
sensitivity. Furthermore, squeezed light broadens the range of frequencies at
which thermal noise dominates, which has the effect of increasing the overall
sensor bandwidth by 50%. These proof-of-principle results open the door to
apply quantum correlated light more broadly in chip-scale sensors and devices.
| physics.optics quant-ph | the resonant enhancement of both mechanical and optical response in microcavity optomechanical devices allows exquisitely sensitive measurements of stimuli such as acceleration mass and magnetic fields in this work we show that quantum correlated light can improve the performance of such sensors increasing both their sensitivity and their bandwidth specifically we develop a siliconchip based cavity optomechanical magnetometer that incorporates phase squeezed light to suppress optical shot noise at frequencies where shot noise is the dominant noise source this allows a 20 improvement in magnetic field sensitivity furthermore squeezed light broadens the range of frequencies at which thermal noise dominates which has the effect of increasing the overall sensor bandwidth by 50 these proofofprinciple results open the door to apply quantum correlated light more broadly in chipscale sensors and devices | [['the', 'resonant', 'enhancement', 'of', 'both', 'mechanical', 'and', 'optical', 'response', 'in', 'microcavity', 'optomechanical', 'devices', 'allows', 'exquisitely', 'sensitive', 'measurements', 'of', 'stimuli', 'such', 'as', 'acceleration', 'mass', 'and', 'magnetic', 'fields', 'in', 'this', 'work', 'we', 'show', 'that', 'quantum', 'correlated', 'light', 'can', 'improve', 'the', 'performance', 'of', 'such', 'sensors', 'increasing', 'both', 'their', 'sensitivity', 'and', 'their', 'bandwidth', 'specifically', 'we', 'develop', 'a', 'siliconchip', 'based', 'cavity', 'optomechanical', 'magnetometer', 'that', 'incorporates', 'phase', 'squeezed', 'light', 'to', 'suppress', 'optical', 'shot', 'noise', 'at', 'frequencies', 'where', 'shot', 'noise', 'is', 'the', 'dominant', 'noise', 'source', 'this', 'allows', 'a', '20', 'improvement', 'in', 'magnetic', 'field', 'sensitivity', 'furthermore', 'squeezed', 'light', 'broadens', 'the', 'range', 'of', 'frequencies', 'at', 'which', 'thermal', 'noise', 'dominates', 'which', 'has', 'the', 'effect', 'of', 'increasing', 'the', 'overall', 'sensor', 'bandwidth', 'by', '50', 'these', 'proofofprinciple', 'results', 'open', 'the', 'door', 'to', 'apply', 'quantum', 'correlated', 'light', 'more', 'broadly', 'in', 'chipscale', 'sensors', 'and', 'devices']] | [-0.13596800908125042, 0.2392192179528462, -0.02968811563598786, -0.01568297727860135, -0.0478060147508459, -0.1748785359943791, 0.07572820268538889, 0.4322428537971275, -0.24385902493138067, -0.3285564453225554, 0.036599151216187446, -0.2926804259080573, -0.14210045375218688, 0.28312915539036887, -0.08610473007194755, 0.07579987276189369, 0.034059127453396947, -0.020377315770358194, 0.00276728313733903, -0.17628920042360302, 0.24855297066762236, 0.08707072415259169, 0.3486860665788715, 0.0798133669579907, 0.10864282494353115, 0.009421127310470324, 0.015022656750367132, -0.021207443229103274, -0.04638134817425396, 0.07229114442074656, 0.2571315888835247, 0.004657974163460177, 0.25458633246319007, -0.4149465976362369, -0.23040550181916516, 0.09785603087164405, 0.14699785560802664, 0.14534015809691173, -0.06186599714932837, -0.28016195935016686, 0.014974979848904146, -0.1398839612036597, -0.10797434171292634, -0.09262992020032203, -0.020947114751284378, 0.028271775436407142, -0.2705557095969832, 0.06812041980582614, 0.035885792547771925, 0.04895237708363191, -0.029895539678201844, -0.06102026687833921, 0.039317787857726216, 0.09513919234867821, -0.05243696909679403, 0.03399256126262074, 0.2726898539753616, -0.1695088344525055, -0.09437947880924326, 0.3337119391391978, -0.12044386235571126, -0.11317728163833304, 0.15445581712225784, -0.16537891961850745, -0.046167146428957466, 0.14657414054259832, 0.20809169382925413, 0.05018333941321304, -0.15063789135653727, 0.01716622353401468, 0.08398415962623995, 0.24121566691937632, 0.08844923337401692, 0.21534490520712132, 0.21854510607898178, 0.20499334387596727, 0.06337314694054974, 0.18114422541653175, -0.17820594670222134, -0.008169313943259014, -0.22250359524907762, -0.09618014735241905, -0.16855534993458626, 0.06070473611845758, -0.09714597671846822, -0.11978651975938516, 0.4231857296599205, 0.25477438281441844, 0.1282389420951002, -0.010447030437590425, 0.37586789931957576, 0.11356680017044089, 0.07824102075149615, 0.0060279965797771316, 0.33490853357966266, 0.16555746328157855, 0.13985491902098174, -0.2750453601172555, -0.015627989000388125, -0.14943034570057726] |
1,802.09739 | Size effects on supercooling phenomena in strongly correlated electron
systems: IrTe$_2$ and $\theta$-(BEDT-TTF)$_2$RbZn(SCN)$_4$ | We report that the sample miniaturization of first-order-phase-transition
bulk systems causes a greater degree of supercooling. From a theoretical
perspective, the size effects can be rationalized by considering two
mechanisms: (i) the nucleation is a rare and stochastic event, and thus, its
rate is correlated with the volume and/or surface area of a given sample; (ii)
when the sample size decreases, the dominant heterogeneous nucleation sites
that play a primary role for relatively large samples are annealed out. We
experimentally verified the size effects on the supercooling phenomena for two
different types of strongly correlated electron systems: the transition-metal
dichalcogenide IrTe$_2$ and the organic conductor
$\theta$-(BEDT-TTF)$_2$RbZn(SCN)$_4$. The origin of the size effects considered
in this study does not depend on microscopic details of the material;
therefore, they may often be involved in the first-order-transition behavior of
small-volume specimens.
| cond-mat.str-el | we report that the sample miniaturization of firstorderphasetransition bulk systems causes a greater degree of supercooling from a theoretical perspective the size effects can be rationalized by considering two mechanisms i the nucleation is a rare and stochastic event and thus its rate is correlated with the volume andor surface area of a given sample ii when the sample size decreases the dominant heterogeneous nucleation sites that play a primary role for relatively large samples are annealed out we experimentally verified the size effects on the supercooling phenomena for two different types of strongly correlated electron systems the transitionmetal dichalcogenide irte_2 and the organic conductor thetabedtttf_2rbznscn_4 the origin of the size effects considered in this study does not depend on microscopic details of the material therefore they may often be involved in the firstordertransition behavior of smallvolume specimens | [['we', 'report', 'that', 'the', 'sample', 'miniaturization', 'of', 'firstorderphasetransition', 'bulk', 'systems', 'causes', 'a', 'greater', 'degree', 'of', 'supercooling', 'from', 'a', 'theoretical', 'perspective', 'the', 'size', 'effects', 'can', 'be', 'rationalized', 'by', 'considering', 'two', 'mechanisms', 'i', 'the', 'nucleation', 'is', 'a', 'rare', 'and', 'stochastic', 'event', 'and', 'thus', 'its', 'rate', 'is', 'correlated', 'with', 'the', 'volume', 'andor', 'surface', 'area', 'of', 'a', 'given', 'sample', 'ii', 'when', 'the', 'sample', 'size', 'decreases', 'the', 'dominant', 'heterogeneous', 'nucleation', 'sites', 'that', 'play', 'a', 'primary', 'role', 'for', 'relatively', 'large', 'samples', 'are', 'annealed', 'out', 'we', 'experimentally', 'verified', 'the', 'size', 'effects', 'on', 'the', 'supercooling', 'phenomena', 'for', 'two', 'different', 'types', 'of', 'strongly', 'correlated', 'electron', 'systems', 'the', 'transitionmetal', 'dichalcogenide', 'irte_2', 'and', 'the', 'organic', 'conductor', 'thetabedtttf_2rbznscn_4', 'the', 'origin', 'of', 'the', 'size', 'effects', 'considered', 'in', 'this', 'study', 'does', 'not', 'depend', 'on', 'microscopic', 'details', 'of', 'the', 'material', 'therefore', 'they', 'may', 'often', 'be', 'involved', 'in', 'the', 'firstordertransition', 'behavior', 'of', 'smallvolume', 'specimens']] | [-0.13743650725421805, 0.19884984924595941, -0.05068592413294094, 0.05134430805617875, -0.02209848217252228, -0.10835026082608643, 0.0882937901981037, 0.35469665219662366, -0.24754152377998387, -0.2860749029726894, 0.08566989271246173, -0.2989435569003776, -0.13508149028272817, 0.2015679410831244, -0.017161983855206658, -0.032750223377391835, 0.008134197367838136, -0.03425334996923252, -0.053436362696811554, -0.24553169564654428, 0.29860642338516535, 0.08092227220983693, 0.31344522262785446, 0.08695261490496772, 0.035620986180448976, -0.021770812098488763, 0.007799421713032105, 0.08509024861096232, -0.14297278520394616, 0.06244956815207843, 0.23596132052717386, 0.020703458268609313, 0.2618940529723962, -0.4573181483955489, -0.22735388572155327, 0.08052938096397728, 0.12669020756902347, 0.1286760061934021, -0.07852670630284896, -0.2172465715419363, 0.05534639328511225, -0.10140043841771937, -0.1471842294244669, -0.010430319610707187, 0.03094184832104171, 0.03902014228835334, -0.2341333302255306, 0.09017055007732577, 0.06447567934584286, 0.08594910610829376, -0.0550401180965343, -0.13639705799933938, -0.04439893974060262, 0.11370219873820639, 0.047312205305529965, -0.031489014432386116, 0.21144010100375724, -0.1461278365942201, -0.062471937622737, 0.3883145989160295, 0.0015035219671618606, -0.15462378428524567, 0.22826687751027444, -0.19733689253183978, -0.10021985562656213, 0.18847310953532104, 0.19602004421391972, 0.12460828507319092, -0.14531193127633607, 0.04695195678181739, 0.004332039808785474, 0.19583649882805293, -0.0010206657341095032, 0.08909691422142917, 0.23866978403594757, 0.23047814877117398, -0.026024614442657266, 0.13368578884207333, -0.11094842427927587, -0.06687456698639802, -0.25957833562322236, -0.17016558458476708, -0.20585314619044462, 0.06427182251516367, -0.11845662266466576, -0.17315629815587913, 0.35882830011347927, 0.11822767038398457, 0.19760604066843235, -0.026142353643835693, 0.22033928427155372, 0.06570518761873245, 0.09036653293641629, 0.0024138992341856164, 0.23132680869074884, 0.08216196031102704, 0.07737317257733256, -0.2673253601313465, 0.18447022148132047, -0.005053125273574282] |
1,802.0974 | Numerical computation of Petersson inner products and $q$-expansions | In this paper we discuss the problem of numerically computing Petersson inner
products of modular forms, given their $q$-expansion at $\infty$. A formula of
Nelson reduces this to obtaining $q$-expansions at all cusps, and we describe
two algorithms based on linear interpolation for numerically obtaining such
expansions. We apply our methods to numerically verify constants arising in an
explicit version of Ichino's triple-product formula relating $\langle
fg,h\rangle$ to the central value of $L(f\times g\times \bar{h},s)$, for three
modular forms $f,g,h$ of compatible weights and characters.
| math.NT | in this paper we discuss the problem of numerically computing petersson inner products of modular forms given their qexpansion at infty a formula of nelson reduces this to obtaining qexpansions at all cusps and we describe two algorithms based on linear interpolation for numerically obtaining such expansions we apply our methods to numerically verify constants arising in an explicit version of ichinos tripleproduct formula relating langle fghrangle to the central value of lftimes gtimes barhs for three modular forms fgh of compatible weights and characters | [['in', 'this', 'paper', 'we', 'discuss', 'the', 'problem', 'of', 'numerically', 'computing', 'petersson', 'inner', 'products', 'of', 'modular', 'forms', 'given', 'their', 'qexpansion', 'at', 'infty', 'a', 'formula', 'of', 'nelson', 'reduces', 'this', 'to', 'obtaining', 'qexpansions', 'at', 'all', 'cusps', 'and', 'we', 'describe', 'two', 'algorithms', 'based', 'on', 'linear', 'interpolation', 'for', 'numerically', 'obtaining', 'such', 'expansions', 'we', 'apply', 'our', 'methods', 'to', 'numerically', 'verify', 'constants', 'arising', 'in', 'an', 'explicit', 'version', 'of', 'ichinos', 'tripleproduct', 'formula', 'relating', 'langle', 'fghrangle', 'to', 'the', 'central', 'value', 'of', 'lftimes', 'gtimes', 'barhs', 'for', 'three', 'modular', 'forms', 'fgh', 'of', 'compatible', 'weights', 'and', 'characters']] | [-0.15652752894324712, 0.033841785699190816, -0.09372385053794427, 0.09268064385964479, -0.06603763548163585, -0.09178522316155484, 0.015891719554096507, 0.33182360014193746, -0.2834499684802021, -0.22225705964535655, 0.09635865079317556, -0.2571794444818543, -0.16149343009645412, 0.2690073887267745, -0.06207024510837642, 0.06336184676332646, 0.013390761936600291, 0.044408164583202674, -0.14770614375999894, -0.27243343848420914, 0.37424329811909113, 0.0012146614559264068, 0.19124557004949774, 0.06259675151163555, 0.10356965354546983, 0.026432158778904074, -0.03452762007062514, -0.07559901029320366, -0.20097021343107951, 0.17424079068481968, 0.2736089422131877, 0.08937733160915325, 0.19265597765602197, -0.4054428595735366, -0.03961496777742742, 0.15757540962378302, 0.1490314431623163, 0.057621594563306094, 0.0032554543556095696, -0.21286639083648123, 0.10069344062582557, -0.20909257822512953, -0.17830335691077523, -0.13193966219403658, 0.046601224118417287, -0.011309612250651222, -0.29168563998158437, 0.059747404918209256, 0.03387188704765727, 0.0820282643705786, -0.08861823875950761, -0.16833216607211585, 0.04153640787902636, 0.10534314258046538, 0.02752510149099202, -0.02255294632435922, 0.047536951568291845, -0.12800196770870362, -0.10897631096619978, 0.33447323537555085, -0.06605360626680665, -0.2034555891281869, 0.12020129873417318, -0.11565456414842103, -0.20046038863092033, 0.05774774009653603, 0.12802013814875698, 0.13890819756944625, -0.07435748157798346, 0.1513202432865636, -0.06366212240768125, 0.07269758952526285, 0.15566037079958941, -0.022494682497962052, 0.11528749867196543, 0.039311894350292455, 0.03022282734423517, 0.17937903557286924, 0.0065159754749073324, -0.06979412611865674, -0.33325218822223596, -0.19846185875764813, -0.16374034692213524, 0.05386971412450973, -0.12807585191260742, -0.18283531018140087, 0.376571602087064, 0.10857924526691975, 0.22048966148980412, 0.16748515930284846, 0.2325185187699565, 0.1723957061052255, 0.05271832196950823, 0.09621854353112629, 0.1431013113140207, 0.18387199193239212, 0.018397956998199672, -0.19599644543535738, 0.007175562207598284, 0.1802736759544855] |
1,802.09741 | Non-invasive force measurement reveals the number of active kinesins on
a synaptic vesicle precursor in axonal transport regulated by ARL-8 | Kinesin superfamily protein UNC-104, a member of the kinesin-3 family,
transports synaptic vesicle precursors (SVPs). In this study, the number of
active UNC-104 molecules hauling a single SVP in axons in the worm
Caenorhabditis elegans was counted by applying a newly developed non-invasive
force measurement technique. The distribution of the force acting on a SVP
transported by UNC-104 was spread out over several clusters, implying the
presence of several force-producing units (FPUs). We then compared the number
of FPUs in the wild-type worms with that in arl-8 gene-deletion mutant worms.
ARL-8 is a SVP-bound arf-like small guanosine triphosphatase, and is known to
promote unlocking of the autoinhibition of the motor, which is critical for
avoiding unnecessary consumption of adenosine triphosphate when the motor does
not bind to a SVP. There were fewer FPUs in the arl-8 mutant worms. This
finding indicates that a lack of ARL-8 decreased the number of active UNC-104
motors, which then led to a decrease in the number of motors responsible for
SVP transport.
| physics.bio-ph | kinesin superfamily protein unc104 a member of the kinesin3 family transports synaptic vesicle precursors svps in this study the number of active unc104 molecules hauling a single svp in axons in the worm caenorhabditis elegans was counted by applying a newly developed noninvasive force measurement technique the distribution of the force acting on a svp transported by unc104 was spread out over several clusters implying the presence of several forceproducing units fpus we then compared the number of fpus in the wildtype worms with that in arl8 genedeletion mutant worms arl8 is a svpbound arflike small guanosine triphosphatase and is known to promote unlocking of the autoinhibition of the motor which is critical for avoiding unnecessary consumption of adenosine triphosphate when the motor does not bind to a svp there were fewer fpus in the arl8 mutant worms this finding indicates that a lack of arl8 decreased the number of active unc104 motors which then led to a decrease in the number of motors responsible for svp transport | [['kinesin', 'superfamily', 'protein', 'unc104', 'a', 'member', 'of', 'the', 'kinesin3', 'family', 'transports', 'synaptic', 'vesicle', 'precursors', 'svps', 'in', 'this', 'study', 'the', 'number', 'of', 'active', 'unc104', 'molecules', 'hauling', 'a', 'single', 'svp', 'in', 'axons', 'in', 'the', 'worm', 'caenorhabditis', 'elegans', 'was', 'counted', 'by', 'applying', 'a', 'newly', 'developed', 'noninvasive', 'force', 'measurement', 'technique', 'the', 'distribution', 'of', 'the', 'force', 'acting', 'on', 'a', 'svp', 'transported', 'by', 'unc104', 'was', 'spread', 'out', 'over', 'several', 'clusters', 'implying', 'the', 'presence', 'of', 'several', 'forceproducing', 'units', 'fpus', 'we', 'then', 'compared', 'the', 'number', 'of', 'fpus', 'in', 'the', 'wildtype', 'worms', 'with', 'that', 'in', 'arl8', 'genedeletion', 'mutant', 'worms', 'arl8', 'is', 'a', 'svpbound', 'arflike', 'small', 'guanosine', 'triphosphatase', 'and', 'is', 'known', 'to', 'promote', 'unlocking', 'of', 'the', 'autoinhibition', 'of', 'the', 'motor', 'which', 'is', 'critical', 'for', 'avoiding', 'unnecessary', 'consumption', 'of', 'adenosine', 'triphosphate', 'when', 'the', 'motor', 'does', 'not', 'bind', 'to', 'a', 'svp', 'there', 'were', 'fewer', 'fpus', 'in', 'the', 'arl8', 'mutant', 'worms', 'this', 'finding', 'indicates', 'that', 'a', 'lack', 'of', 'arl8', 'decreased', 'the', 'number', 'of', 'active', 'unc104', 'motors', 'which', 'then', 'led', 'to', 'a', 'decrease', 'in', 'the', 'number', 'of', 'motors', 'responsible', 'for', 'svp', 'transport']] | [-0.1581343768104888, 0.18372716286174226, -0.026522629505318657, -0.003311571962535154, -0.034341630328548846, -0.15299175917909186, 0.09856641733956455, 0.3257972464851308, -0.2549138242469692, -0.28611328144466913, 0.023442573178837803, -0.2586470680533505, -0.21064219724318786, 0.19917784052157048, -0.09882253212797479, -0.007781629320006908, 0.04248342700245813, 0.04165995673407096, 0.11059142909262602, -0.21619173773584274, 0.17053022340121793, 0.04497033891427081, 0.25459305296947315, 0.01007290609271788, 0.11347871357695734, -0.021677119615516147, 0.029115445603809614, -0.0010290610939037146, -0.08846681137903233, 0.11391132420231304, 0.19682495147536405, 0.103642657316835, 0.3042817968057423, -0.445620288106999, -0.20863251656112147, 0.1323156303054619, 0.18117382479888364, 0.11691746705285523, -0.05094147453910853, -0.22487960094671197, 0.1013361718590803, -0.15542618793480825, -0.09444835705245368, -0.030219960029282403, 0.05644082823745543, 0.10589975963499988, -0.21683487962369194, 0.08099860340220535, 0.005954491501253825, 0.10569372518192523, -0.08051022924284064, -0.10477822019559581, -0.06570893864533524, 0.15313833326377435, 0.05977979112308609, 0.07395606411183707, 0.255451928037673, -0.13880946946319012, -0.09282077948432188, 0.32444486286166047, 0.012486559601511987, -0.16383843571118012, 0.16048601913839441, -0.08553238518581521, -0.14509353607824846, 0.18245283767677525, 0.11804019222206368, 0.11063053189186244, -0.15856326458787207, -0.024461087595072303, -0.04111060315584082, 0.16448671830869166, 0.1002981040283197, -0.07322680414370375, 0.14291814653907062, 0.19720982607289375, 0.04837021833603702, 0.15681843772720797, -0.11705671995807235, -0.09351573569171993, -0.19510665575536423, -0.20562611702721703, -0.162801593622312, 0.05645193143972414, -0.02316051057286819, -0.15234622522683178, 0.37092384786867516, 0.08684265511337577, 0.17309635139649687, 0.06990631181525248, 0.2163849913447005, -0.02163364446406798, 0.17972721929644894, 0.04810185555408413, 0.18204636265603236, 0.08742894227588095, 0.09788555769383249, -0.2901186367139084, 0.14192710126602523, 0.040588023816803244] |
1,802.09742 | Magnetic field dependence of the nonlinear magnetic response and
tricritical point in the monoaxial chiral helimagnet Cr$_{1/3}$NbS$_{2}$ | We present a comprehensive study of the magnetization dynamics and phase
evolution in Cr$_{1/3}$NbS$_{2}$, which realizes a chiral soliton lattice
(CSL). The magnetic field dependence of the ac magnetic response is analyzed
for five harmonic components, $M_{n\omega}(H)$ $(n =1-5)$, using a phase
sensitive measurement over a frequency range, $f = 11 - 10,000$ Hz. At a
critical field, the modulated CSL continuously evolves from a helicity-rich to
a ferromagnetic domain-rich structure, where the crossover is revealed by the
onset of an anomalous nonlinear magnetic response that coincides with extremely
slow dynamics. The behavior is indicative of the formation of a spatially
coherent array of large ferromagnetic domains which relax on macroscopic
time-scales. The frequency dependence of the ac magnetic loss displays an
asymmetric distribution of relaxation times across the highly nonlinear CSL
regime, which shift to shorter time-scales with increasing temperature. We
experimentally resolve the tricritical point at $T_{TCP}$ in a temperature
regime above the ferromagnetic Curie temperature which separates the linear and
nonlinear regimes of the CSL at the phase transition. A comprehensive phase
diagram is constructed which summarized the features of the field and
temperature dependence of the magnetic crossovers and phase transitions in
Cr$_{1/3}$NbS$_{2}$.
| cond-mat.str-el | we present a comprehensive study of the magnetization dynamics and phase evolution in cr_13nbs_2 which realizes a chiral soliton lattice csl the magnetic field dependence of the ac magnetic response is analyzed for five harmonic components m_nomegah n 15 using a phase sensitive measurement over a frequency range f 11 10000 hz at a critical field the modulated csl continuously evolves from a helicityrich to a ferromagnetic domainrich structure where the crossover is revealed by the onset of an anomalous nonlinear magnetic response that coincides with extremely slow dynamics the behavior is indicative of the formation of a spatially coherent array of large ferromagnetic domains which relax on macroscopic timescales the frequency dependence of the ac magnetic loss displays an asymmetric distribution of relaxation times across the highly nonlinear csl regime which shift to shorter timescales with increasing temperature we experimentally resolve the tricritical point at t_tcp in a temperature regime above the ferromagnetic curie temperature which separates the linear and nonlinear regimes of the csl at the phase transition a comprehensive phase diagram is constructed which summarized the features of the field and temperature dependence of the magnetic crossovers and phase transitions in cr_13nbs_2 | [['we', 'present', 'a', 'comprehensive', 'study', 'of', 'the', 'magnetization', 'dynamics', 'and', 'phase', 'evolution', 'in', 'cr_13nbs_2', 'which', 'realizes', 'a', 'chiral', 'soliton', 'lattice', 'csl', 'the', 'magnetic', 'field', 'dependence', 'of', 'the', 'ac', 'magnetic', 'response', 'is', 'analyzed', 'for', 'five', 'harmonic', 'components', 'm_nomegah', 'n', '15', 'using', 'a', 'phase', 'sensitive', 'measurement', 'over', 'a', 'frequency', 'range', 'f', '11', '10000', 'hz', 'at', 'a', 'critical', 'field', 'the', 'modulated', 'csl', 'continuously', 'evolves', 'from', 'a', 'helicityrich', 'to', 'a', 'ferromagnetic', 'domainrich', 'structure', 'where', 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1,802.09743 | Depth-resolved resonant inelastic x-ray scattering at a
superconductor/half-metallic ferromagnet interface through standing-wave
excitation | We demonstrate that combining standing-wave (SW) excitation with resonant
inelastic x-ray scattering (RIXS) can lead to depth resolution and interface
sensitivity for studying orbital and magnetic excitations in correlated oxide
heterostructures. SW-RIXS has been applied to multilayer heterostructures
consisting of a superconductor La$_{1.85}$Sr$_{0.15}$CuO$_{4}$(LSCO) and a
half-metallic ferromagnet La$_{0.67}$Sr$_{0.33}$MnO$_{3}$ (LSMO). Easily
observable SW effects on the RIXS excitations were found in these LSCO/LSMO
multilayers. In addition, we observe different depth distribution of the RIXS
excitations. The magnetic excitations are found to arise from the LSCO/LSMO
interfaces, and there is also a suggestion that one of the dd excitations comes
from the interfaces. SW-RIXS measurements of correlated-oxide and other
multilayer heterostructures should provide unique layer-resolved insights
concerning their orbital and magnetic excitations, as well as a challenge for
RIXS theory to specifically deal with interface effects.
| cond-mat.mtrl-sci cond-mat.str-el cond-mat.supr-con | we demonstrate that combining standingwave sw excitation with resonant inelastic xray scattering rixs can lead to depth resolution and interface sensitivity for studying orbital and magnetic excitations in correlated oxide heterostructures swrixs has been applied to multilayer heterostructures consisting of a superconductor la_185sr_015cuo_4lsco and a halfmetallic ferromagnet la_067sr_033mno_3 lsmo easily observable sw effects on the rixs excitations were found in these lscolsmo multilayers in addition we observe different depth distribution of the rixs excitations the magnetic excitations are found to arise from the lscolsmo interfaces and there is also a suggestion that one of the dd excitations comes from the interfaces swrixs measurements of correlatedoxide and other multilayer heterostructures should provide unique layerresolved insights concerning their orbital and magnetic excitations as well as a challenge for rixs theory to specifically deal with interface effects | [['we', 'demonstrate', 'that', 'combining', 'standingwave', 'sw', 'excitation', 'with', 'resonant', 'inelastic', 'xray', 'scattering', 'rixs', 'can', 'lead', 'to', 'depth', 'resolution', 'and', 'interface', 'sensitivity', 'for', 'studying', 'orbital', 'and', 'magnetic', 'excitations', 'in', 'correlated', 'oxide', 'heterostructures', 'swrixs', 'has', 'been', 'applied', 'to', 'multilayer', 'heterostructures', 'consisting', 'of', 'a', 'superconductor', 'la_185sr_015cuo_4lsco', 'and', 'a', 'halfmetallic', 'ferromagnet', 'la_067sr_033mno_3', 'lsmo', 'easily', 'observable', 'sw', 'effects', 'on', 'the', 'rixs', 'excitations', 'were', 'found', 'in', 'these', 'lscolsmo', 'multilayers', 'in', 'addition', 'we', 'observe', 'different', 'depth', 'distribution', 'of', 'the', 'rixs', 'excitations', 'the', 'magnetic', 'excitations', 'are', 'found', 'to', 'arise', 'from', 'the', 'lscolsmo', 'interfaces', 'and', 'there', 'is', 'also', 'a', 'suggestion', 'that', 'one', 'of', 'the', 'dd', 'excitations', 'comes', 'from', 'the', 'interfaces', 'swrixs', 'measurements', 'of', 'correlatedoxide', 'and', 'other', 'multilayer', 'heterostructures', 'should', 'provide', 'unique', 'layerresolved', 'insights', 'concerning', 'their', 'orbital', 'and', 'magnetic', 'excitations', 'as', 'well', 'as', 'a', 'challenge', 'for', 'rixs', 'theory', 'to', 'specifically', 'deal', 'with', 'interface', 'effects']] | [-0.16040726940627792, 0.17243814926041523, -0.07978888232901227, 0.08343897125905642, -0.07359028950122593, -0.15456411937338999, 0.04131067219623219, 0.45937582502665464, -0.28782492033496965, -0.2942761766244075, -0.015489556258671655, -0.3795361684606178, -0.12155588686437113, 0.20792118736426346, 0.08148968221212272, 0.03568303101201309, 0.014159645894324058, -0.0867517462354499, -0.051855330380931264, -0.16142729836064973, 0.29708278854741366, 0.01007688771278481, 0.28743091505020857, 0.1337903250969248, 0.010295467507603462, 0.05068411253159866, 0.13344916019559605, 0.01063793547655223, -0.11911022627884904, 0.09968200089588208, 0.3236334334451385, -0.1051322320545296, 0.12858089158544317, -0.5006875429680804, -0.22201219895941904, -0.07571572433516849, 0.18591054072749102, 0.13352693114575231, -0.0797794257350688, -0.27388806601811666, 0.04893840388103854, -0.14104603954183403, -0.09643492511713703, -0.12430140123797173, -0.05650227752266801, 0.022151038465381134, -0.2522389830683096, 0.041412564378106254, 0.04757202051496279, 0.09512363766407361, -0.13485964884148416, -0.13860272450256161, -0.0911236217343685, 0.04777706390450476, 0.05914283072888793, 0.05028411333478289, 0.13441360631986754, -0.1292075267419932, -0.16265865186232986, 0.33499808782744367, -0.03909132800799853, -0.07346423500712262, 0.2156339089924586, -0.1911976556875743, -0.09227762992759381, 0.13168654422770487, 0.13741319934251806, 0.08059362731910369, -0.1373462974661379, 0.07521839218770765, -0.0063040364111657254, 0.21704869937093463, 0.07335874226919259, 0.14355762348441203, 0.2774559581557696, 0.18613710758563684, -0.006219340306415688, 0.14189562768342512, -0.16416232966548705, 0.013387417980993632, -0.15444455956821912, -0.1430413073321688, -0.1748388014639204, 0.052517101143166656, -0.009066857669722594, -0.20371825810980226, 0.39192661822380614, 0.17121136018249672, 0.16803225465355354, -0.0832016595377354, 0.2245618949746131, 0.12820370208373788, 0.0811309709570196, -0.004742179633467458, 0.24822076556483808, 0.17463555178073875, 0.1284519393411756, -0.26311760520729877, 0.08412511026199354, -0.036166894242342096] |
1,802.09744 | A coarse grid projection method for accelerating heat transfer
computations | Coarse Grid Projection (CGP) methodology is used to accelerate the
computations of sets of decoupled nonlinear evolutionary and linear static
equations. In CGP, the linear equations are solved on a coarsened mesh compared
to the nonlinear equations, leading to a reduction in central processing unit
(CPU) time. The accuracy of the CGP scheme has been assessed for the
advection-diffusion equation along with the pressure Poisson equation. Here we
add another decoupled equation to this set: the energy equation. In this
article, we examine the influence of CGP methodology for the first time on
thermal fields. To this purpose, a semi-implicit-time-integration
unstructured-triangular-finite-element CGP version is selected. The CGP
platform is validated with two different test cases: first, natural convection
induced by a hot circular cylinder located in the center of a cold square
cylinder, and second, the flow over a circular cylinder with the condition of
constant cylinder temperature. Regarding the first test case, the CGP and
non-CGP simulations are carried out for different Rayleigh numbers. The
velocity and temperature fields as well as the local Nusselt number on the
surface of the inner hot cylinder calculated by CGP reveal good agreement with
the non-CGP data. Concerning the second test case, the temperature variable is
used as the passive scalar. For different Prandtl numbers, we compare the CGP
and non-CGP configurations according to the Nusselt number and the spatial
structure of the scalar field obtained. The phase lag between the standard and
CGP approaches is transmitted from the velocity field into the temperature
filed, and thus into the local transient Nusselt number. For one and two levels
of coarsening, the numerical predictions by CGP for the unsteady local heat
transfer coefficients agree well with available data in the literature.
| physics.comp-ph | coarse grid projection cgp methodology is used to accelerate the computations of sets of decoupled nonlinear evolutionary and linear static equations in cgp the linear equations are solved on a coarsened mesh compared to the nonlinear equations leading to a reduction in central processing unit cpu time the accuracy of the cgp scheme has been assessed for the advectiondiffusion equation along with the pressure poisson equation here we add another decoupled equation to this set the energy equation in this article we examine the influence of cgp methodology for the first time on thermal fields to this purpose a semiimplicittimeintegration unstructuredtriangularfiniteelement cgp version is selected the cgp platform is validated with two different test cases first natural convection induced by a hot circular cylinder located in the center of a cold square cylinder and second the flow over a circular cylinder with the condition of constant cylinder temperature regarding the first test case the cgp and noncgp simulations are carried out for different rayleigh numbers the velocity and temperature fields as well as the local nusselt number on the surface of the inner hot cylinder calculated by cgp reveal good agreement with the noncgp data concerning the second test case the temperature variable is used as the passive scalar for different prandtl numbers we compare the cgp and noncgp configurations according to the nusselt number and the spatial structure of the scalar field obtained the phase lag between the standard and cgp approaches is transmitted from the velocity field into the temperature filed and thus into the local transient nusselt number for one and two levels of coarsening the numerical predictions by cgp for the unsteady local heat transfer coefficients agree well with available data in the literature | [['coarse', 'grid', 'projection', 'cgp', 'methodology', 'is', 'used', 'to', 'accelerate', 'the', 'computations', 'of', 'sets', 'of', 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1,802.09745 | ReHAR: Robust and Efficient Human Activity Recognition | Designing a scheme that can achieve a good performance in predicting single
person activities and group activities is a challenging task. In this paper, we
propose a novel robust and efficient human activity recognition scheme called
ReHAR, which can be used to handle single person activities and group
activities prediction. First, we generate an optical flow image for each video
frame. Then, both video frames and their corresponding optical flow images are
fed into a Single Frame Representation Model to generate representations.
Finally, an LSTM is used to pre- dict the final activities based on the
generated representations. The whole model is trained end-to-end to allow
meaningful representations to be generated for the final activity recognition.
We evaluate ReHAR using two well-known datasets: the NCAA Basketball Dataset
and the UCFSports Action Dataset. The experimental results show that the pro-
posed ReHAR achieves a higher activity recognition accuracy with an order of
magnitude shorter computation time compared to the state-of-the-art methods.
| cs.CV | designing a scheme that can achieve a good performance in predicting single person activities and group activities is a challenging task in this paper we propose a novel robust and efficient human activity recognition scheme called rehar which can be used to handle single person activities and group activities prediction first we generate an optical flow image for each video frame then both video frames and their corresponding optical flow images are fed into a single frame representation model to generate representations finally an lstm is used to pre dict the final activities based on the generated representations the whole model is trained endtoend to allow meaningful representations to be generated for the final activity recognition we evaluate rehar using two wellknown datasets the ncaa basketball dataset and the ucfsports action dataset the experimental results show that the pro posed rehar achieves a higher activity recognition accuracy with an order of magnitude shorter computation time compared to the stateoftheart methods | [['designing', 'a', 'scheme', 'that', 'can', 'achieve', 'a', 'good', 'performance', 'in', 'predicting', 'single', 'person', 'activities', 'and', 'group', 'activities', 'is', 'a', 'challenging', 'task', 'in', 'this', 'paper', 'we', 'propose', 'a', 'novel', 'robust', 'and', 'efficient', 'human', 'activity', 'recognition', 'scheme', 'called', 'rehar', 'which', 'can', 'be', 'used', 'to', 'handle', 'single', 'person', 'activities', 'and', 'group', 'activities', 'prediction', 'first', 'we', 'generate', 'an', 'optical', 'flow', 'image', 'for', 'each', 'video', 'frame', 'then', 'both', 'video', 'frames', 'and', 'their', 'corresponding', 'optical', 'flow', 'images', 'are', 'fed', 'into', 'a', 'single', 'frame', 'representation', 'model', 'to', 'generate', 'representations', 'finally', 'an', 'lstm', 'is', 'used', 'to', 'pre', 'dict', 'the', 'final', 'activities', 'based', 'on', 'the', 'generated', 'representations', 'the', 'whole', 'model', 'is', 'trained', 'endtoend', 'to', 'allow', 'meaningful', 'representations', 'to', 'be', 'generated', 'for', 'the', 'final', 'activity', 'recognition', 'we', 'evaluate', 'rehar', 'using', 'two', 'wellknown', 'datasets', 'the', 'ncaa', 'basketball', 'dataset', 'and', 'the', 'ucfsports', 'action', 'dataset', 'the', 'experimental', 'results', 'show', 'that', 'the', 'pro', 'posed', 'rehar', 'achieves', 'a', 'higher', 'activity', 'recognition', 'accuracy', 'with', 'an', 'order', 'of', 'magnitude', 'shorter', 'computation', 'time', 'compared', 'to', 'the', 'stateoftheart', 'methods']] | [-0.06543986892502289, 0.015790701662172068, -0.09075078551177285, 0.053060338126670104, -0.09514805088256253, -0.16244910208042712, -0.005780483868147712, 0.4916156433755532, -0.24434833918930962, -0.32262407232192347, 0.08161456140660447, -0.2622516777832061, -0.1637283166870475, 0.22091093814233317, -0.16676787023734505, 0.04888593171199318, 0.16910609768965515, 0.1096067368722288, -0.04326590770797338, -0.29546446681488303, 0.23147955752647248, 0.04944986321788747, 0.35631432908121496, 0.0034557890554424374, 0.15408496336021926, -0.04554099118540762, -0.031611326574056874, -0.022275807757978328, -0.026617763365993596, 0.183550795505289, 0.2995865001910715, 0.1627044814347755, 0.28937908768857595, -0.4017309011076577, -0.1814303096020012, 0.08642451293417253, 0.12182264142466011, 0.10842042449521613, -0.05386566885645152, -0.37926242739195004, 0.10830178028554656, -0.19386339250631862, 0.03686136600881582, -0.14382766176131553, -0.00463498954923125, -0.060324068059708226, -0.3318800920271315, 0.03649405667092651, 0.021444508389686236, 0.06578686434659176, -0.10099411823757691, -0.03650554750493029, 0.021685253860778176, 0.25778402873838785, 0.009020637138746679, 0.09714216550346463, 0.16231130474770908, -0.18059850399617972, -0.17882247262750753, 0.415550625952892, -0.0944482835544477, -0.20779019853798672, 0.1934725611572503, -0.04409166831173934, -0.11465704923321027, 0.1064533005876001, 0.2583985730947461, 0.14643218057462945, -0.14811862721981015, -0.08686237625843204, -0.07403564069536514, 0.22283223638733035, 0.03427063597773668, -0.029017293204469753, 0.1761054712238547, 0.24748531349468977, -0.005644923911313526, 0.1266605152923148, -0.1307926837776904, -0.020410556596470997, -0.20389913408071153, -0.10475373194058193, -0.13294728682230925, -0.03184181409887969, -0.06969387925882983, -0.09563101102394285, 0.4419939951550532, 0.22072746736812404, 0.20188109158771111, 0.1064231330419716, 0.3361183529952541, 0.046511381177697333, 0.09984473888034699, 0.08735698032505752, 0.13937459058142848, -0.024395966943120583, 0.10021174207831791, -0.18620918533415534, 0.05036171932588331, 0.11109877748676808] |
1,802.09746 | Surrogate Model Assisted Cooperative Coevolution for Large Scale
Optimization | It has been shown that cooperative coevolution (CC) can effectively deal with
large scale optimization problems (LSOPs) through a divide-and-conquer
strategy. However, its performance is severely restricted by the current
context-vector-based sub-solution evaluation method since this method needs to
access the original high dimensional simulation model when evaluating each
sub-solution and thus requires many computation resources. To alleviate this
issue, this study proposes a novel surrogate model assisted cooperative
coevolution (SACC) framework. SACC constructs a surrogate model for each
sub-problem obtained via decomposition and employs it to evaluate corresponding
sub-solutions. The original simulation model is only adopted to reevaluate some
good sub-solutions selected by surrogate models, and these real evaluated
sub-solutions will be in turn employed to update surrogate models. By this
means, the computation cost could be greatly reduced without significantly
sacrificing evaluation quality. To show the efficiency of SACC, this study uses
radial basis function (RBF) and success-history based adaptive differential
evolution (SHADE) as surrogate model and optimizer, respectively. RBF and SHADE
have been proved to be effective on small and medium scale problems. This study
first scales them up to LSOPs of 1000 dimensions under the SACC framework,
where they are tailored to a certain extent for adapting to the characteristics
of LSOP and SACC. Empirical studies on IEEE CEC 2010 benchmark functions
demonstrate that SACC significantly enhances the evaluation efficiency on
sub-solutions, and even with much fewer computation resource, the resultant
RBF-SHADE-SACC algorithm is able to find much better solutions than traditional
CC algorithms.
| cs.NE | it has been shown that cooperative coevolution cc can effectively deal with large scale optimization problems lsops through a divideandconquer strategy however its performance is severely restricted by the current contextvectorbased subsolution evaluation method since this method needs to access the original high dimensional simulation model when evaluating each subsolution and thus requires many computation resources to alleviate this issue this study proposes a novel surrogate model assisted cooperative coevolution sacc framework sacc constructs a surrogate model for each subproblem obtained via decomposition and employs it to evaluate corresponding subsolutions the original simulation model is only adopted to reevaluate some good subsolutions selected by surrogate models and these real evaluated subsolutions will be in turn employed to update surrogate models by this means the computation cost could be greatly reduced without significantly sacrificing evaluation quality to show the efficiency of sacc this study uses radial basis function rbf and successhistory based adaptive differential evolution shade as surrogate model and optimizer respectively rbf and shade have been proved to be effective on small and medium scale problems this study first scales them up to lsops of 1000 dimensions under the sacc framework where they are tailored to a certain extent for adapting to the characteristics of lsop and sacc empirical studies on ieee cec 2010 benchmark functions demonstrate that sacc significantly enhances the evaluation efficiency on subsolutions and even with much fewer computation resource the resultant rbfshadesacc algorithm is able to find much better solutions than traditional cc algorithms | [['it', 'has', 'been', 'shown', 'that', 'cooperative', 'coevolution', 'cc', 'can', 'effectively', 'deal', 'with', 'large', 'scale', 'optimization', 'problems', 'lsops', 'through', 'a', 'divideandconquer', 'strategy', 'however', 'its', 'performance', 'is', 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1,802.09747 | Accelerating Asynchronous Algorithms for Convex Optimization by Momentum
Compensation | Asynchronous algorithms have attracted much attention recently due to the
crucial demands on solving large-scale optimization problems. However, the
accelerated versions of asynchronous algorithms are rarely studied. In this
paper, we propose the "momentum compensation" technique to accelerate
asynchronous algorithms for convex problems. Specifically, we first accelerate
the plain Asynchronous Gradient Descent, which achieves a faster
$O(1/\sqrt{\epsilon})$ (v.s. $O(1/\epsilon)$) convergence rate for non-strongly
convex functions, and $O(\sqrt{\kappa}\log(1/\epsilon))$ (v.s. $O(\kappa
\log(1/\epsilon))$) for strongly convex functions to reach an $\epsilon$-
approximate minimizer with the condition number $\kappa$. We further apply the
technique to accelerate modern stochastic asynchronous algorithms such as
Asynchronous Stochastic Coordinate Descent and Asynchronous Stochastic Gradient
Descent. Both of the resultant practical algorithms are faster than existing
ones by order. To the best of our knowledge, we are the first to consider
accelerated algorithms that allow updating by delayed gradients and are the
first to propose truly accelerated asynchronous algorithms. Finally, the
experimental results on a shared memory system show that acceleration can lead
to significant performance gains on ill-conditioned problems.
| math.OC cs.LG | asynchronous algorithms have attracted much attention recently due to the crucial demands on solving largescale optimization problems however the accelerated versions of asynchronous algorithms are rarely studied in this paper we propose the momentum compensation technique to accelerate asynchronous algorithms for convex problems specifically we first accelerate the plain asynchronous gradient descent which achieves a faster o1sqrtepsilon vs o1epsilon convergence rate for nonstrongly convex functions and osqrtkappalog1epsilon vs okappa log1epsilon for strongly convex functions to reach an epsilon approximate minimizer with the condition number kappa we further apply the technique to accelerate modern stochastic asynchronous algorithms such as asynchronous stochastic coordinate descent and asynchronous stochastic gradient descent both of the resultant practical algorithms are faster than existing ones by order to the best of our knowledge we are the first to consider accelerated algorithms that allow updating by delayed gradients and are the first to propose truly accelerated asynchronous algorithms finally the experimental results on a shared memory system show that acceleration can lead to significant performance gains on illconditioned problems | [['asynchronous', 'algorithms', 'have', 'attracted', 'much', 'attention', 'recently', 'due', 'to', 'the', 'crucial', 'demands', 'on', 'solving', 'largescale', 'optimization', 'problems', 'however', 'the', 'accelerated', 'versions', 'of', 'asynchronous', 'algorithms', 'are', 'rarely', 'studied', 'in', 'this', 'paper', 'we', 'propose', 'the', 'momentum', 'compensation', 'technique', 'to', 'accelerate', 'asynchronous', 'algorithms', 'for', 'convex', 'problems', 'specifically', 'we', 'first', 'accelerate', 'the', 'plain', 'asynchronous', 'gradient', 'descent', 'which', 'achieves', 'a', 'faster', 'o1sqrtepsilon', 'vs', 'o1epsilon', 'convergence', 'rate', 'for', 'nonstrongly', 'convex', 'functions', 'and', 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1,802.09748 | Skew hook formula for $d$-complete posets | Peterson and Proctor obtained a formula which expresses the multivariate
generating function for $P$-partitions on a $d$-complete poset $P$ as a product
in terms of hooks in $P$. In this paper, we give a skew generalization of
Peterson--Proctor's hook formula, i.e., a formula for the generating function
for $(P \setminus F)$-partitions for a $d$-complete poset $P$ and its order
filter $F$, by using the notion of excited diagrams. Our proof uses the
Billey-type formula and the Chevalley-type formula in the equivariant
$K$-theory of Kac--Moody partial flag varieties. This generalization provides
an alternate proof of Peterson--Proctor's hook formula.
| math.CO | peterson and proctor obtained a formula which expresses the multivariate generating function for ppartitions on a dcomplete poset p as a product in terms of hooks in p in this paper we give a skew generalization of petersonproctors hook formula ie a formula for the generating function for p setminus fpartitions for a dcomplete poset p and its order filter f by using the notion of excited diagrams our proof uses the billeytype formula and the chevalleytype formula in the equivariant ktheory of kacmoody partial flag varieties this generalization provides an alternate proof of petersonproctors hook formula | [['peterson', 'and', 'proctor', 'obtained', 'a', 'formula', 'which', 'expresses', 'the', 'multivariate', 'generating', 'function', 'for', 'ppartitions', 'on', 'a', 'dcomplete', 'poset', 'p', 'as', 'a', 'product', 'in', 'terms', 'of', 'hooks', 'in', 'p', 'in', 'this', 'paper', 'we', 'give', 'a', 'skew', 'generalization', 'of', 'petersonproctors', 'hook', 'formula', 'ie', 'a', 'formula', 'for', 'the', 'generating', 'function', 'for', 'p', 'setminus', 'fpartitions', 'for', 'a', 'dcomplete', 'poset', 'p', 'and', 'its', 'order', 'filter', 'f', 'by', 'using', 'the', 'notion', 'of', 'excited', 'diagrams', 'our', 'proof', 'uses', 'the', 'billeytype', 'formula', 'and', 'the', 'chevalleytype', 'formula', 'in', 'the', 'equivariant', 'ktheory', 'of', 'kacmoody', 'partial', 'flag', 'varieties', 'this', 'generalization', 'provides', 'an', 'alternate', 'proof', 'of', 'petersonproctors', 'hook', 'formula']] | [-0.16351696021462742, 0.017337897024270587, -0.14207995206509766, 0.09455287967024273, -0.10955097183193031, -0.1231743131911284, 0.06754208069025097, 0.24024393954559375, -0.28753942408059774, -0.23410222609772494, 0.026679092768187584, -0.21770947821695652, -0.18633671833300278, 0.21070973354538805, -0.16121532554174528, -0.019005172641482205, 0.015808146294990652, 0.050265668955092366, -0.08116601395028594, -0.22456800466446256, 0.33169932790394674, -0.03782904326523605, 0.21235063828920064, 0.07828582587995027, 0.11828232730591767, 0.10511952717053263, -0.055202258446891056, -0.05942462224415258, -0.20855864823648804, 0.16090985603238406, 0.2736895816572207, 0.1228288452042953, 0.1927544309953718, -0.3177139718673731, -0.02913607155512038, 0.1596508128274428, 0.16819491152602592, 0.04212780542255036, -0.008040773972721868, -0.24343149445607867, 0.07858473077220351, -0.27064355764734116, -0.17663430175008743, -0.04667247164700376, 0.13400032138942103, 0.017998677492141724, -0.3308517483308127, 0.00201806824066137, 0.1732319995172714, 0.14058120192279794, -0.0356279658999196, -0.19265596147038436, -0.00645562903465409, 0.029697564126629578, -0.039869503157311366, 0.07584333907028562, 0.025963170257838147, -0.07882828057596558, -0.1573352982633208, 0.32616682158488974, -0.05668763014806533, -0.23425249700483522, -0.0012725850567221642, -0.15665029842700612, -0.1471996585005208, 0.10693671073470461, 0.04762277214934951, 0.18317813506644023, -0.03806718530035333, 0.13150218324061777, -0.16108776669655192, -0.002934239669948032, 0.17159752647245402, -0.012287720074681076, 0.1233318689009665, 0.04761096037140018, 0.012456185007958035, 0.24932143788135266, 0.016200292308961875, -0.007252434688914371, -0.35405808612704276, -0.24185733477536, -0.15269095201633479, 0.10364741846722991, -0.13861496433183723, -0.24448901275663, 0.3764052625328891, 0.038265597077674775, 0.19104534902358672, 0.18430625971431205, 0.22682426904181116, 0.12658479768096617, 0.059372948840456574, -0.04276094013628991, 0.009210975438748535, 0.25410303842815524, 0.030063449184557323, -0.12818836678848847, 0.08762473851981524, 0.29478115884489137] |
1,802.09749 | A new class of refined Eulerian polynomials | In this note we introduce a new class of refined Eulerian polynomials defined
by $$A_n(p,q)=\sum_{\pi\in\mathfrak{S}_n}p^{{\rm odes}(\pi)}q^{{\rm
edes}(\pi)},$$ where ${\rm odes}(\pi)$ and ${\rm edes}(\pi)$ enumerate the
number of descents of permutation $\pi$ in odd and even positions,
respectively. We show that the refined Eulerian polynomials
$A_{2k+1}(p,q),k=0,1,2,\ldots,$ and $(1+q)A_{2k}(p,q),k=1,2,\ldots,$ have a
nice symmetry property.
| math.CO | in this note we introduce a new class of refined eulerian polynomials defined by a_npqsum_piinmathfraks_nprm odespiqrm edespi where rm odespi and rm edespi enumerate the number of descents of permutation pi in odd and even positions respectively we show that the refined eulerian polynomials a_2k1pqk012ldots and 1qa_2kpqk12ldots have a nice symmetry property | [['in', 'this', 'note', 'we', 'introduce', 'a', 'new', 'class', 'of', 'refined', 'eulerian', 'polynomials', 'defined', 'by', 'a_npqsum_piinmathfraks_nprm', 'odespiqrm', 'edespi', 'where', 'rm', 'odespi', 'and', 'rm', 'edespi', 'enumerate', 'the', 'number', 'of', 'descents', 'of', 'permutation', 'pi', 'in', 'odd', 'and', 'even', 'positions', 'respectively', 'we', 'show', 'that', 'the', 'refined', 'eulerian', 'polynomials', 'a_2k1pqk012ldots', 'and', '1qa_2kpqk12ldots', 'have', 'a', 'nice', 'symmetry', 'property']] | [-0.1991222958597872, 0.16813732232484552, -0.08446611660636133, 0.07493591835049705, -0.07576170281196634, -0.10449168112956815, 0.0056766501627862455, 0.3205872916099098, -0.3034360121521685, -0.28234575076235663, 0.03520672676256961, -0.20340582836005422, -0.16616279780864715, 0.11904341234929032, -0.10090257268812922, 0.016897599440481928, 0.023687816949354276, 0.051772688422352074, -0.1318101037500633, -0.2663500507000006, 0.2891770088010364, -0.05662734518862433, 0.1678799566295412, 0.0019423980576296648, 0.09724668307850758, 0.01633299778526028, -0.06007072606848346, 0.060890512333975896, -0.1977247952232978, 0.11122404313128856, 0.2317555871585177, 0.1178881364564101, 0.17316181204385228, -0.38737130032645334, -0.06577047612776774, 0.18907763076325257, 0.17521886941459444, 0.041798418548165094, -0.05862784425003661, -0.22857831679284574, 0.16520867285629112, -0.16930407256715826, -0.14721178122175235, -0.07948820001135269, 0.07043302034338315, 0.06793591611915165, -0.28932833520488604, 0.04168294071116381, 0.10634674690663815, 0.1801374077383015, 0.08567625876102182, -0.17457789104017946, -0.021553360174099603, 0.02488075509690033, -0.02034488647348351, 0.04816122442069981, -0.04722612973871744, -0.09086968753383391, -0.10933348390842891, 0.39048863136106066, -0.005341301092671023, -0.2567849541289939, 0.057699988016651736, -0.15941943939154346, -0.2802755604394608, 0.09038789656996313, 0.1263494542385969, 0.19108791208515566, 0.0049522900746928325, 0.10764951691057326, -0.19631684114121728, 0.08264764274160068, 0.1552179274873601, 0.031933954016615945, 0.1319532527588308, -0.007112498115748167, 0.06627483997597462, 0.1807196643203497, -0.05890992101695802, -0.014293782744142744, -0.3245787842406167, -0.2017469243870841, -0.1619504841665427, 0.052419660902685586, -0.12322515513030036, -0.1435926532993714, 0.4104102152089278, 0.13166484449886615, 0.2008271930946244, 0.16524241833637157, 0.17084541221459706, 0.0779895412011279, 0.04082779222064548, 0.08184998706112512, 0.0890627645370033, 0.17980087569707798, -0.007244251854717732, -0.18889098858667744, -0.004408527486440208, 0.2052745242189202] |
1,802.0975 | Train Feedfoward Neural Network with Layer-wise Adaptive Rate via
Approximating Back-matching Propagation | Stochastic gradient descent (SGD) has achieved great success in training deep
neural network, where the gradient is computed through back-propagation.
However, the back-propagated values of different layers vary dramatically. This
inconsistence of gradient magnitude across different layers renders
optimization of deep neural network with a single learning rate problematic. We
introduce the back-matching propagation which computes the backward values on
the layer's parameter and the input by matching backward values on the layer's
output. This leads to solving a bunch of least-squares problems, which requires
high computational cost. We then reduce the back-matching propagation with
approximations and propose an algorithm that turns to be the regular SGD with a
layer-wise adaptive learning rate strategy. This allows an easy implementation
of our algorithm in current machine learning frameworks equipped with
auto-differentiation. We apply our algorithm in training modern deep neural
networks and achieve favorable results over SGD.
| stat.ML cs.LG | stochastic gradient descent sgd has achieved great success in training deep neural network where the gradient is computed through backpropagation however the backpropagated values of different layers vary dramatically this inconsistence of gradient magnitude across different layers renders optimization of deep neural network with a single learning rate problematic we introduce the backmatching propagation which computes the backward values on the layers parameter and the input by matching backward values on the layers output this leads to solving a bunch of leastsquares problems which requires high computational cost we then reduce the backmatching propagation with approximations and propose an algorithm that turns to be the regular sgd with a layerwise adaptive learning rate strategy this allows an easy implementation of our algorithm in current machine learning frameworks equipped with autodifferentiation we apply our algorithm in training modern deep neural networks and achieve favorable results over sgd | [['stochastic', 'gradient', 'descent', 'sgd', 'has', 'achieved', 'great', 'success', 'in', 'training', 'deep', 'neural', 'network', 'where', 'the', 'gradient', 'is', 'computed', 'through', 'backpropagation', 'however', 'the', 'backpropagated', 'values', 'of', 'different', 'layers', 'vary', 'dramatically', 'this', 'inconsistence', 'of', 'gradient', 'magnitude', 'across', 'different', 'layers', 'renders', 'optimization', 'of', 'deep', 'neural', 'network', 'with', 'a', 'single', 'learning', 'rate', 'problematic', 'we', 'introduce', 'the', 'backmatching', 'propagation', 'which', 'computes', 'the', 'backward', 'values', 'on', 'the', 'layers', 'parameter', 'and', 'the', 'input', 'by', 'matching', 'backward', 'values', 'on', 'the', 'layers', 'output', 'this', 'leads', 'to', 'solving', 'a', 'bunch', 'of', 'leastsquares', 'problems', 'which', 'requires', 'high', 'computational', 'cost', 'we', 'then', 'reduce', 'the', 'backmatching', 'propagation', 'with', 'approximations', 'and', 'propose', 'an', 'algorithm', 'that', 'turns', 'to', 'be', 'the', 'regular', 'sgd', 'with', 'a', 'layerwise', 'adaptive', 'learning', 'rate', 'strategy', 'this', 'allows', 'an', 'easy', 'implementation', 'of', 'our', 'algorithm', 'in', 'current', 'machine', 'learning', 'frameworks', 'equipped', 'with', 'autodifferentiation', 'we', 'apply', 'our', 'algorithm', 'in', 'training', 'modern', 'deep', 'neural', 'networks', 'and', 'achieve', 'favorable', 'results', 'over', 'sgd']] | [-0.07286746428054694, 0.01742984957324041, -0.06208845433358052, 0.036704873211669084, -0.09651722525858818, -0.1913191297502984, 0.055413315406751706, 0.47329124435144543, -0.360089252556974, -0.32173987977168433, 0.045601686829547974, -0.19671521329551006, -0.1894309861738592, 0.18107511540428314, -0.11937911934793403, 0.09932749649963887, 0.15223617457995217, -0.004326672950274732, -0.10144682423162198, -0.3225887952075812, 0.26059457991823987, 0.08272934370863168, 0.3489533211933832, -0.0402275329481249, 0.20502431999333043, -0.008167502655303234, 0.03025525981841022, -0.016152983711560397, -0.05653433179769271, 0.1786398648777546, 0.2769458489364957, 0.17625453414982312, 0.38116365316489786, -0.4624065859243274, -0.21680776459126644, 0.11385751496370537, 0.17343814962855317, 0.12470362665552696, -0.026854104676590083, -0.24414414626048647, 0.09161948191786619, -0.12279727626974656, 0.010502227108402509, -0.1321065280385545, -0.09196353768483315, 0.029851213766561746, -0.3128188142922949, 0.011210647872521554, 0.0343825820542805, 0.029077998470923263, -0.01023200125958171, -0.13979543230100855, 0.0331925246800768, 0.07410621410873655, 0.057919804139177584, 0.11260882068157502, 0.13744019414298236, -0.16890365472350474, -0.12605608609658092, 0.2761639524952904, -0.08633680301654624, -0.20746891465586648, 0.15218506337220028, 0.014161191141146733, -0.10217281442441761, 0.13269380274330814, 0.2558569152112285, 0.15333322274709146, -0.11678506573981108, 0.037170854794604656, 0.002811356351953255, 0.15661825890228637, 0.03892236304380102, -0.04507883580573771, 0.10683994717124135, 0.2682774498586683, 0.11160151640029803, 0.1451859269873239, -0.1449086268347519, -0.13094720924958866, -0.20686230960314814, -0.09895321772248829, -0.1559836129085416, -0.0230022097669848, -0.17904235390208306, -0.17170240937362183, 0.39970494995582595, 0.21235252272541802, 0.23660504259169102, 0.15705644317933723, 0.3612295250370078, 0.1204948510084786, 0.1498127763497656, 0.16508942921901096, 0.2443182850607403, 0.09404678367977733, 0.16820981623907894, -0.2023080061955301, 0.13194113262380436, 0.08095625288822778] |
1,802.09751 | Generalized Binary Search For Split-Neighborly Problems | In sequential hypothesis testing, Generalized Binary Search (GBS) greedily
chooses the test with the highest information gain at each step. It is known
that GBS obtains the gold standard query cost of $O(\log n)$ for problems
satisfying the $k$-neighborly condition, which requires any two tests to be
connected by a sequence of tests where neighboring tests disagree on at most
$k$ hypotheses. In this paper, we introduce a weaker condition,
split-neighborly, which requires that for the set of hypotheses two neighbors
disagree on, any subset is splittable by some test. For four problems that are
not $k$-neighborly for any constant $k$, we prove that they are
split-neighborly, which allows us to obtain the optimal $O(\log n)$ worst-case
query cost.
| cs.AI cs.DS | in sequential hypothesis testing generalized binary search gbs greedily chooses the test with the highest information gain at each step it is known that gbs obtains the gold standard query cost of olog n for problems satisfying the kneighborly condition which requires any two tests to be connected by a sequence of tests where neighboring tests disagree on at most k hypotheses in this paper we introduce a weaker condition splitneighborly which requires that for the set of hypotheses two neighbors disagree on any subset is splittable by some test for four problems that are not kneighborly for any constant k we prove that they are splitneighborly which allows us to obtain the optimal olog n worstcase query cost | [['in', 'sequential', 'hypothesis', 'testing', 'generalized', 'binary', 'search', 'gbs', 'greedily', 'chooses', 'the', 'test', 'with', 'the', 'highest', 'information', 'gain', 'at', 'each', 'step', 'it', 'is', 'known', 'that', 'gbs', 'obtains', 'the', 'gold', 'standard', 'query', 'cost', 'of', 'olog', 'n', 'for', 'problems', 'satisfying', 'the', 'kneighborly', 'condition', 'which', 'requires', 'any', 'two', 'tests', 'to', 'be', 'connected', 'by', 'a', 'sequence', 'of', 'tests', 'where', 'neighboring', 'tests', 'disagree', 'on', 'at', 'most', 'k', 'hypotheses', 'in', 'this', 'paper', 'we', 'introduce', 'a', 'weaker', 'condition', 'splitneighborly', 'which', 'requires', 'that', 'for', 'the', 'set', 'of', 'hypotheses', 'two', 'neighbors', 'disagree', 'on', 'any', 'subset', 'is', 'splittable', 'by', 'some', 'test', 'for', 'four', 'problems', 'that', 'are', 'not', 'kneighborly', 'for', 'any', 'constant', 'k', 'we', 'prove', 'that', 'they', 'are', 'splitneighborly', 'which', 'allows', 'us', 'to', 'obtain', 'the', 'optimal', 'olog', 'n', 'worstcase', 'query', 'cost']] | [-0.1296179368136785, 0.07977878662128733, -0.04655392779212477, 0.0479895964744461, -0.0918252984356358, -0.24300644770423827, 0.12510061100260633, 0.3799144921776576, -0.23859314290651432, -0.32130387923720044, 0.08931057096825132, -0.2811473788969412, -0.08249678787711658, 0.19108055281834915, -0.046844306202907846, 0.04119834073214258, 0.09494767092868812, 0.09383839234295818, -0.03406853336068746, -0.3656099002836192, 0.301379886139423, 0.020840524241097398, 0.23861029063566372, -0.004666774230213183, 0.09505252753440131, 0.01894508196343469, 0.00988244991669925, 0.020176026014945447, -0.12801726169324018, 0.08405971234170799, 0.26557062252257496, 0.19360270314356393, 0.3271627034832779, -0.41217806115428096, -0.13031350950606996, 0.15893505489091492, 0.09781273469551761, 0.0685935217845373, 0.008391724624790443, -0.19733421237255336, 0.1776943038034643, -0.059749394377621896, -0.05915014337326408, -0.027017837270903282, 0.0011167415481410984, -0.0061310272281750655, -0.36616492638032105, -0.0024780450969870784, 0.07589005000698261, 0.013542852854021849, -0.01649306798363741, -0.12089839877767695, 0.03829537618021744, 0.112889233777602, 0.007098163252210833, 0.06962364094837321, 0.09423506366582508, -0.0711080784149245, -0.16892090876801655, 0.3828731657913289, -0.029704001701822996, -0.22450312085720336, 0.17780345188390112, -0.1272966309577927, -0.19193145455633345, 0.11984995137263313, 0.12272214492321269, 0.13013868528999326, -0.13812607216338316, 0.09147334102795929, -0.10022722699659037, 0.18972008887073424, 0.1367191979343183, 0.023380878664011884, 0.13175783638691163, 0.12732925556568253, 0.13088728481919593, 0.11673467164425355, -0.038451308129816994, -0.056263228265457176, -0.3386232238262892, -0.1681540150466001, -0.1977879740934596, 0.01780837680559912, -0.1564455714363318, -0.1398039842183646, 0.3054072973596999, 0.15133724980947807, 0.19550330120608464, 0.13939227416422856, 0.26361160077409357, 0.05832369175740084, 0.05710082361275633, 0.13802256421623832, 0.1744080202757982, 0.03433507891435526, -0.022698584203727733, -0.15484119762276483, 0.14373698859658635, 0.0767440595664084] |
1,802.09752 | Search for the rare decays $D\to h(h')e^+e^-$ | We search for rare decays of $D$ mesons to hadrons accompany with an
electron-positron pair (h(h')$e^+e^-$), using an $e^+e^-$ collision sample
corresponding to an integrated luminosity of 2.93 fb$^{-1}$ collected with the
BESIII detector at $\sqrt{s}$ = 3.773 GeV. No significant signals are observed,
and the corresponding upper limits on the branching fractions at the $90\%$
confidence level are determined. The sensitivities of the results are at the
level of $10^{-5} \sim 10^{-6}$, providing a large improvement over previous
searches.
| hep-ex | we search for rare decays of d mesons to hadrons accompany with an electronpositron pair hhee using an ee collision sample corresponding to an integrated luminosity of 293 fb1 collected with the besiii detector at sqrts 3773 gev no significant signals are observed and the corresponding upper limits on the branching fractions at the 90 confidence level are determined the sensitivities of the results are at the level of 105 sim 106 providing a large improvement over previous searches | [['we', 'search', 'for', 'rare', 'decays', 'of', 'd', 'mesons', 'to', 'hadrons', 'accompany', 'with', 'an', 'electronpositron', 'pair', 'hhee', 'using', 'an', 'ee', 'collision', 'sample', 'corresponding', 'to', 'an', 'integrated', 'luminosity', 'of', '293', 'fb1', 'collected', 'with', 'the', 'besiii', 'detector', 'at', 'sqrts', '3773', 'gev', 'no', 'significant', 'signals', 'are', 'observed', 'and', 'the', 'corresponding', 'upper', 'limits', 'on', 'the', 'branching', 'fractions', 'at', 'the', '90', 'confidence', 'level', 'are', 'determined', 'the', 'sensitivities', 'of', 'the', 'results', 'are', 'at', 'the', 'level', 'of', '105', 'sim', '106', 'providing', 'a', 'large', 'improvement', 'over', 'previous', 'searches']] | [-0.0826262551432965, 0.18993792253250155, -0.03316225639830988, 0.10197731119114906, -0.003932354962811447, -0.043988836899352, 0.06804018991384417, 0.34668446600867003, -0.11790004022753774, -0.3707614582843887, 0.014515355677128984, -0.45284458011006695, 0.1560462585483224, 0.24176778349404535, 0.11149949285512169, 0.08449352318898608, 0.137998942238016, 0.03329567923449362, -0.06239343330246182, -0.2530204209839352, 0.16687435990509888, 0.14955264490205222, 0.23269851414415127, 0.08711041872485135, 0.08677918256188814, -0.04337848011905757, -0.05173340985455956, -0.10509947489779921, -0.13032748022427162, 0.07039462810364337, 0.2688810212077955, 0.13385102386252049, 0.1507919935318522, -0.3273382812303913, 0.015277241398460971, 0.18586989804111326, 0.13358128059488267, -0.0022435679655665387, -0.03158593024515236, -0.40299206890929967, 0.1752710019533809, -0.1931705991558444, -0.07875913063374658, 0.031981874227476045, 0.05160499899051128, -0.08290283820138146, -0.3244878737948453, 0.09123611504522462, -0.08155063341538875, 0.12287582931943082, -0.0539161581486368, -0.2418248535399564, -0.03625486905011945, -0.05768774202069602, 0.02935178597153236, 0.08544765935407785, 0.18889809273875868, -0.1208800605008713, -0.20541262012930253, 0.3140789285923044, -0.061861492005379826, -0.09447278821570738, 0.2407161497976631, -0.2348948217367228, -0.09537924790922074, 0.2807876600955541, 0.3033135978815456, 0.024487334267737772, -0.22931226110085845, 0.06936453109627995, 0.0029845112122786352, 0.19774598898127294, 0.09442655062183547, 0.10154407070681024, 0.22180614873575857, 0.24406510521060762, 0.002117013487105186, 0.05878839108388489, -0.16997941058929053, 0.010064384882123424, -0.4273195932507336, -0.0723175114999788, -0.07479341707687873, 0.07495940988137124, -0.07804544554192734, -0.017001926875076234, 0.3259504772961522, 0.09825945792731662, 0.3705253589134186, 0.0639261075695499, 0.23003338606287846, 0.1902750510877619, 0.028758203360037163, 0.10272791129775727, 0.3260590521356043, 0.08413719570932862, 0.11271958795632833, -0.20166727145447227, 0.0007813457124985945, -0.0405673734151209] |
1,802.09753 | Orbital parameters and evolutionary status of the highly peculiar binary
system HD 66051 | The spectroscopic binary system HD 66051 (V414 Pup) consists of a highly
peculiar CP3 (HgMn) star and an A-type component. It also shows out-of-eclipse
variability that is due to chemical spots. This combination allows the
derivation of tight constraints for the testing of time-dependent diffusion
models. We analysed radial velocity and photometric data using two different
methods to determine astrophysical parameters and the orbit of the system.
Appropriate isochrones were used to derive the age of the system. The orbital
solution and the estimates from the isochrones are in excellent agreement with
the estimates from a prior spectroscopic study. The system is very close to the
zero-age main sequence and younger than 120 Myr. HD 66051 is a most important
spectroscopic binary system that can be used to test the predictions of the
diffusion theory explaining the peculiar surface abundances of CP3 stars.
| astro-ph.SR | the spectroscopic binary system hd 66051 v414 pup consists of a highly peculiar cp3 hgmn star and an atype component it also shows outofeclipse variability that is due to chemical spots this combination allows the derivation of tight constraints for the testing of timedependent diffusion models we analysed radial velocity and photometric data using two different methods to determine astrophysical parameters and the orbit of the system appropriate isochrones were used to derive the age of the system the orbital solution and the estimates from the isochrones are in excellent agreement with the estimates from a prior spectroscopic study the system is very close to the zeroage main sequence and younger than 120 myr hd 66051 is a most important spectroscopic binary system that can be used to test the predictions of the diffusion theory explaining the peculiar surface abundances of cp3 stars | [['the', 'spectroscopic', 'binary', 'system', 'hd', '66051', 'v414', 'pup', 'consists', 'of', 'a', 'highly', 'peculiar', 'cp3', 'hgmn', 'star', 'and', 'an', 'atype', 'component', 'it', 'also', 'shows', 'outofeclipse', 'variability', 'that', 'is', 'due', 'to', 'chemical', 'spots', 'this', 'combination', 'allows', 'the', 'derivation', 'of', 'tight', 'constraints', 'for', 'the', 'testing', 'of', 'timedependent', 'diffusion', 'models', 'we', 'analysed', 'radial', 'velocity', 'and', 'photometric', 'data', 'using', 'two', 'different', 'methods', 'to', 'determine', 'astrophysical', 'parameters', 'and', 'the', 'orbit', 'of', 'the', 'system', 'appropriate', 'isochrones', 'were', 'used', 'to', 'derive', 'the', 'age', 'of', 'the', 'system', 'the', 'orbital', 'solution', 'and', 'the', 'estimates', 'from', 'the', 'isochrones', 'are', 'in', 'excellent', 'agreement', 'with', 'the', 'estimates', 'from', 'a', 'prior', 'spectroscopic', 'study', 'the', 'system', 'is', 'very', 'close', 'to', 'the', 'zeroage', 'main', 'sequence', 'and', 'younger', 'than', '120', 'myr', 'hd', '66051', 'is', 'a', 'most', 'important', 'spectroscopic', 'binary', 'system', 'that', 'can', 'be', 'used', 'to', 'test', 'the', 'predictions', 'of', 'the', 'diffusion', 'theory', 'explaining', 'the', 'peculiar', 'surface', 'abundances', 'of', 'cp3', 'stars']] | [-0.09940004114325578, 0.06765901399901363, -0.11399236455900778, 0.08128071606690458, -0.10196138881671597, -0.1154129557527969, 0.05872733865021794, 0.3731385014531478, -0.19405475400411196, -0.3322422703085336, 0.07868827216271443, -0.2807358117975191, -0.060135904053540926, 0.22697105367740117, -0.07946848307906741, 0.031590140465660096, 0.17287170063887894, -0.002682181503164621, -0.05775117266408338, -0.24579141785236547, 0.29989663685153856, 0.0516214150489426, 0.15569796068200342, -0.08103385999221617, 0.052238011681048434, -0.0902387208000324, -0.05825190362192585, -0.04691475362215244, -0.17226803217226275, 0.09381393242535561, 0.19849020384308333, 0.12038642486793474, 0.17038704549342815, -0.32979880843285314, -0.2138382889868193, 0.030913669399549842, 0.1880251146249578, 0.08884144677865831, -0.019899847481111194, -0.2579102682877778, 0.08726732596971462, -0.16244934592641969, -0.1615843909340058, -0.014235126451444877, 0.05784895340584113, 0.037959459800155124, -0.27034322959436496, 0.0945232756455137, 0.026627609240625735, 0.1246860229580755, -0.18363520866596061, -0.15369578850255544, -0.0694685498724731, 0.13613578621101316, 0.05226836933485481, 0.08313569303398663, 0.08210934847790066, -0.08284256071947567, -0.00698470531038048, 0.407021602550128, -0.11858726124835453, -0.07612691104287465, 0.24160909834957328, -0.15632852677150932, -0.15065101078960677, 0.1119498771116872, 0.1341178170044605, 0.1575812314289399, -0.22474768458091668, 0.009185607123277215, 0.004913540891515957, 0.22065842909161265, 0.01548176781195675, 0.024109268311317274, 0.2928240363105712, 0.15298327770162845, 0.0047978222375066664, 0.07453483199818768, -0.21438657410416595, -0.07643078331192824, -0.22087259929377953, -0.12036432110061737, -0.12397625265990607, 0.044254281205571136, -0.1575953036043129, -0.14473720408753085, 0.3621385611501903, 0.14947858940265601, 0.19813013852501787, -0.0038540094605528973, 0.28422939042482054, 0.10270062181114836, 0.07043414336012703, 0.07833977779176768, 0.27039379664552465, 0.22909001464312764, 0.09025830632849584, -0.28364067909129054, 0.10563125893224398, 0.03960336104992934] |
1,802.09754 | A Lyapunov function for fully nonlinear parabolic equations in one
spatial variable | Lyapunov functions are used to prove stability of equilibria, or to indicate
a gradient-like structure of a dynamical system. Zelenyak (1968) and Matano
(1988) constructed a Lyapunov function for quasilinear parabolic equations. We
modify Matano's method to construct a Lyapunov function for fully nonlinear
parabolic equations under Dirichlet and mixed nonlinear boundary conditions of
Robin type.
| math.DS math.AP | lyapunov functions are used to prove stability of equilibria or to indicate a gradientlike structure of a dynamical system zelenyak 1968 and matano 1988 constructed a lyapunov function for quasilinear parabolic equations we modify matanos method to construct a lyapunov function for fully nonlinear parabolic equations under dirichlet and mixed nonlinear boundary conditions of robin type | [['lyapunov', 'functions', 'are', 'used', 'to', 'prove', 'stability', 'of', 'equilibria', 'or', 'to', 'indicate', 'a', 'gradientlike', 'structure', 'of', 'a', 'dynamical', 'system', 'zelenyak', '1968', 'and', 'matano', '1988', 'constructed', 'a', 'lyapunov', 'function', 'for', 'quasilinear', 'parabolic', 'equations', 'we', 'modify', 'matanos', 'method', 'to', 'construct', 'a', 'lyapunov', 'function', 'for', 'fully', 'nonlinear', 'parabolic', 'equations', 'under', 'dirichlet', 'and', 'mixed', 'nonlinear', 'boundary', 'conditions', 'of', 'robin', 'type']] | [-0.17872916808859868, 0.014147067374803804, -0.16050738538615406, 0.08449643512510441, -0.11724819984202357, -0.20156980919948017, -0.039520428247157145, 0.23224227611314166, -0.34914392991499466, -0.17607072395357218, 0.15143137304535645, -0.21589237153530122, -0.20209876152009448, 0.19208225038495252, -0.06839830245484005, 0.1970470063854009, 0.061756516434252264, -0.03916226093318652, -0.08648632126436992, -0.20822337242266672, 0.3840763051697815, -0.08898828837766566, 0.20748378553173757, -0.02255682972026989, 0.13560413217002695, -0.006807609609412876, 0.02574063536118377, 0.04558979481120001, -0.19375507772307504, 0.05610633182170039, 0.23583829843185164, 0.022210721142420713, 0.3462424845985052, -0.39584827443415466, -0.22298560628498143, 0.08710062102076005, 0.07627759541130878, 0.06555456708778035, 0.00467753417535939, -0.29493649954145607, 0.13143221104771577, -0.13022644145583565, -0.25783717358823527, -0.08018738503821872, -0.0002451531504365531, 0.07705773770682176, -0.4103551777809943, 0.13081027005206455, 0.04159789726042866, 0.07229600485668264, -0.19298414607447656, -0.07596666672986678, -0.09336194329133088, 0.015458894068036567, -0.03784767679700797, -0.052169967883012515, 0.05698663640598005, -0.05074808305468072, -0.10010706502097574, 0.2807459459894083, -0.09050393247003244, -0.31503183056007733, 0.16905222074552015, -0.08968791829591448, -0.1124084064821628, 0.09920819029211998, 0.23150449110703034, 0.17324113226072355, -0.1631538091407327, 0.10994887542275882, -0.04125898732507432, 0.14541268921033904, 0.1036538538353687, -0.052194102260876785, 0.05941177624362436, 0.08338041359728032, 0.1628499786538834, 0.1598573759706183, 0.06288660380311988, -0.1491850469261408, -0.2943032633851875, -0.13596087725494396, -0.10296811249784447, 0.10756164792586456, -0.04957230836946771, -0.29114216946234756, 0.4102367202666673, 0.03183164526708424, 0.11375598165799271, 0.1107548927126283, 0.15803967863321305, 0.21505738942121919, -0.023911170652982865, 0.10511291676772419, 0.22672678103501145, 0.2016863496889445, 0.12728094613518226, -0.24430633190786466, 0.02795158671638505, 0.2287812845612114] |
1,802.09755 | Lower semi-continuity of the Waldschmidt constants | In this paper, we study the Waldschmidt constant of a generalized fat point
subscheme $Z=m_1p_1+\cdots+m_rp_r$ of $\mathbb{P}^2$, where $p_1,\cdots,p_r$
are essentially distinct points on $\mathbb{P}^2$, satisfying the proximity
inequalities. Furthermore, we prove its lower semi-continuity for $r\le 8$.
Using this property, we also calculate the Waldschmidt constants of the fat
point subschemes $Z=p_1+\cdots+p_5$ giving weak del Pezzo surfaces of degree 4.
| math.AG | in this paper we study the waldschmidt constant of a generalized fat point subscheme zm_1p_1cdotsm_rp_r of mathbbp2 where p_1cdotsp_r are essentially distinct points on mathbbp2 satisfying the proximity inequalities furthermore we prove its lower semicontinuity for rle 8 using this property we also calculate the waldschmidt constants of the fat point subschemes zp_1cdotsp_5 giving weak del pezzo surfaces of degree 4 | [['in', 'this', 'paper', 'we', 'study', 'the', 'waldschmidt', 'constant', 'of', 'a', 'generalized', 'fat', 'point', 'subscheme', 'zm_1p_1cdotsm_rp_r', 'of', 'mathbbp2', 'where', 'p_1cdotsp_r', 'are', 'essentially', 'distinct', 'points', 'on', 'mathbbp2', 'satisfying', 'the', 'proximity', 'inequalities', 'furthermore', 'we', 'prove', 'its', 'lower', 'semicontinuity', 'for', 'rle', '8', 'using', 'this', 'property', 'we', 'also', 'calculate', 'the', 'waldschmidt', 'constants', 'of', 'the', 'fat', 'point', 'subschemes', 'zp_1cdotsp_5', 'giving', 'weak', 'del', 'pezzo', 'surfaces', 'of', 'degree', '4']] | [-0.26129991662335295, 0.019307413507766765, -0.08534521338176625, 0.10328552333622015, 0.014209819419694871, -0.19891123928065443, 0.07445364164646137, 0.2920287334328068, -0.3087107758037746, -0.18046533632702355, 0.07319566345540807, -0.29166737701422696, -0.13871787530209484, 0.18823623387865593, -0.14786011953677597, 0.026048298322009566, -0.013853286457215917, 0.028359827649747503, -0.12425856500992487, -0.3547544529147703, 0.4539227743215602, -0.03867945393972934, 0.20292861982256752, 0.14891466488740568, 0.10509014373709416, -0.011363045601495382, 0.039029869973531056, -0.026225277431437682, -0.2695787296357468, 0.15728920569707608, 0.25852641123266695, 0.06312301035986506, 0.14590894003751978, -0.3654970582574606, -0.09893656574221778, 0.23503696243680114, 0.1446441885099971, -0.005542474204738592, -0.01436692403814081, -0.20363747236190427, 0.1418701552721704, -0.07822440573990802, -0.2628504220508681, -0.05875284918423357, 0.020167647098223197, 0.06105394903490127, -0.22955737704539608, -0.004777053038384926, 0.10488435712137163, 0.18565080928463681, -0.0003230207186224389, -0.12340039681193643, -0.06239726332995783, 0.007823075352493545, -0.0019484836897202607, 0.062343725521149564, 0.06182298076274837, -0.0834055557959424, -0.09600286737911339, 0.29582794087714165, -0.05383057314260253, -0.1982377701085703, 0.10574808106597128, -0.18941982507962604, -0.17849514872670688, 0.12705811089033198, 0.13285231657711596, 0.20731693795271988, -0.060179585767588736, 0.2148187836985393, -0.09895500906839452, 0.047965908765287044, 0.20827378238679778, 0.02791496847981009, 0.08080704317524515, 0.07914966500589046, 0.10166658029152915, 0.14221569619559007, -0.09067089188892137, -0.01800525589878189, -0.42749569916712316, -0.21106259152293205, -0.11729889957170034, 0.16862784192801036, -0.20026006072394326, -0.1641830772739546, 0.4082223114653908, 0.04237998728158659, 0.23794643105617885, 0.13026137195591783, 0.19992429737387032, 0.055920841043879246, -0.04295125233153973, 0.10130046754433163, 0.19159895835187415, 0.12496560426621602, -0.04247428873023982, -0.09133904603920107, 0.02076404414878323, 0.22347307126519494] |
1,802.09756 | Real-Time Bidding with Multi-Agent Reinforcement Learning in Display
Advertising | Real-time advertising allows advertisers to bid for each impression for a
visiting user. To optimize specific goals such as maximizing revenue and return
on investment (ROI) led by ad placements, advertisers not only need to estimate
the relevance between the ads and user's interests, but most importantly
require a strategic response with respect to other advertisers bidding in the
market. In this paper, we formulate bidding optimization with multi-agent
reinforcement learning. To deal with a large number of advertisers, we propose
a clustering method and assign each cluster with a strategic bidding agent. A
practical Distributed Coordinated Multi-Agent Bidding (DCMAB) has been proposed
and implemented to balance the tradeoff between the competition and cooperation
among advertisers. The empirical study on our industry-scaled real-world data
has demonstrated the effectiveness of our methods. Our results show
cluster-based bidding would largely outperform single-agent and bandit
approaches, and the coordinated bidding achieves better overall objectives than
purely self-interested bidding agents.
| stat.ML cs.AI cs.LG | realtime advertising allows advertisers to bid for each impression for a visiting user to optimize specific goals such as maximizing revenue and return on investment roi led by ad placements advertisers not only need to estimate the relevance between the ads and users interests but most importantly require a strategic response with respect to other advertisers bidding in the market in this paper we formulate bidding optimization with multiagent reinforcement learning to deal with a large number of advertisers we propose a clustering method and assign each cluster with a strategic bidding agent a practical distributed coordinated multiagent bidding dcmab has been proposed and implemented to balance the tradeoff between the competition and cooperation among advertisers the empirical study on our industryscaled realworld data has demonstrated the effectiveness of our methods our results show clusterbased bidding would largely outperform singleagent and bandit approaches and the coordinated bidding achieves better overall objectives than purely selfinterested bidding agents | [['realtime', 'advertising', 'allows', 'advertisers', 'to', 'bid', 'for', 'each', 'impression', 'for', 'a', 'visiting', 'user', 'to', 'optimize', 'specific', 'goals', 'such', 'as', 'maximizing', 'revenue', 'and', 'return', 'on', 'investment', 'roi', 'led', 'by', 'ad', 'placements', 'advertisers', 'not', 'only', 'need', 'to', 'estimate', 'the', 'relevance', 'between', 'the', 'ads', 'and', 'users', 'interests', 'but', 'most', 'importantly', 'require', 'a', 'strategic', 'response', 'with', 'respect', 'to', 'other', 'advertisers', 'bidding', 'in', 'the', 'market', 'in', 'this', 'paper', 'we', 'formulate', 'bidding', 'optimization', 'with', 'multiagent', 'reinforcement', 'learning', 'to', 'deal', 'with', 'a', 'large', 'number', 'of', 'advertisers', 'we', 'propose', 'a', 'clustering', 'method', 'and', 'assign', 'each', 'cluster', 'with', 'a', 'strategic', 'bidding', 'agent', 'a', 'practical', 'distributed', 'coordinated', 'multiagent', 'bidding', 'dcmab', 'has', 'been', 'proposed', 'and', 'implemented', 'to', 'balance', 'the', 'tradeoff', 'between', 'the', 'competition', 'and', 'cooperation', 'among', 'advertisers', 'the', 'empirical', 'study', 'on', 'our', 'industryscaled', 'realworld', 'data', 'has', 'demonstrated', 'the', 'effectiveness', 'of', 'our', 'methods', 'our', 'results', 'show', 'clusterbased', 'bidding', 'would', 'largely', 'outperform', 'singleagent', 'and', 'bandit', 'approaches', 'and', 'the', 'coordinated', 'bidding', 'achieves', 'better', 'overall', 'objectives', 'than', 'purely', 'selfinterested', 'bidding', 'agents']] | [-0.08892621368006501, -0.07197798381018296, -0.050891595517660114, 0.06802386317217674, -0.21810973874994782, -0.24034779212231955, 0.1907117730860792, 0.49239395856373497, -0.23572654598286713, -0.3499019211146817, 0.05652044032391935, -0.3257097122366215, -0.17430316307770946, 0.10630135204077565, -0.19745324493397948, 0.043265998354423546, 0.051279644557054145, 0.044695952713683054, 0.043621382721988546, -0.34458373268074416, 0.26919074570714774, 0.07609352473072804, 0.3394154372758099, 0.02142125081540049, 0.09574912897652837, 0.04138227180251247, -0.0096370054608477, -0.0025231721629570057, -0.12655509100661763, 0.16651850317411318, 0.41288208010812083, 0.21450837451644097, 0.45078047389140374, -0.3993184819345834, -0.1357676937749803, 0.15043723495229594, 0.11374254895422559, -0.014894054488992536, -0.0743153950867739, -0.2909971974009962, 0.046052735831056325, -0.24967853282275912, 0.03681382179175588, -0.1236036779788359, -0.058655787171650826, 0.03946085443928862, -0.3806809477489925, -0.08127925045752003, -0.02392287884971925, 0.010235609864670928, -0.11906106523034017, -0.10524243573573502, 0.007352774519799882, 0.19995457513935186, 0.12081995998605989, -0.0354329748880481, 0.1819302404387068, -0.16305821299645143, -0.258564680560746, 0.4254653143708582, 0.037200597025187195, -0.15896135683673399, 0.17664128469602605, -0.045314940106873584, -0.135363643196738, 0.09485024752325148, 0.24830695303072306, 0.14202290180127147, -0.17804758883664965, -0.006594483607203712, -0.05571350111934514, 0.2048306171298511, 0.03196570406329225, 0.011490275358400222, 0.1844991602974206, 0.2391087745781988, 0.2104096363325809, 0.09655125139473163, 0.03718724109038904, -0.19736126049530583, -0.14573423648646175, -0.11247750058885084, -0.15660344313621496, -0.0028412870369366274, -0.12868091011015084, -0.10519335001658697, 0.37460466308591817, 0.20969560162578907, 0.1110314013430389, 0.14896773899808624, 0.3479942916650567, 0.05346860109326466, 0.04123452740914926, 0.12531687804292163, 0.21897423837194824, -0.12309081503341289, 0.20573096705771463, -0.22344928658446417, 0.1744763933578748, -0.017464499997712865] |
1,802.09757 | Ultrafast Laser Nanostructured ITO Acts as Liquid Crystal Alignment
Layer and Higher Transparency Electrode | Electrodes with higher transparency that can also align liquid crystals (LCs)
are of high importance for improved costs and energy consumption of LC
displays. Here we demonstrate for the first time alignment of liquid crystals
on femtosecond laser nanostructured indium tin oxide (ITO) coated glass
exhibiting also higher transparency due to the less interface reflections. The
nano paterns were created by fs laser directlly on ITO films without any
additional spin coating materials or lithography procces. Nine regions of
laser-induced nanostructures were fabricated with different alignment
orientations and various pulse energy levels on top of the ITO. The device
interfacial anchoring energy was found to be comparable to the anchoring energy
of nematic LC on photosensitive polymers. The device exhibits contrast of 30:1
and relaxation time of 330ms expected for thick LC devices. The measured
transparency of the LC device with two ITO nanograting substrates is 10% higher
than the uniform ITO film based LC devices. The alignment methodology presented
here paves the way for improved LC displays and new structured LC photonic
devices.
| physics.optics physics.app-ph | electrodes with higher transparency that can also align liquid crystals lcs are of high importance for improved costs and energy consumption of lc displays here we demonstrate for the first time alignment of liquid crystals on femtosecond laser nanostructured indium tin oxide ito coated glass exhibiting also higher transparency due to the less interface reflections the nano paterns were created by fs laser directlly on ito films without any additional spin coating materials or lithography procces nine regions of laserinduced nanostructures were fabricated with different alignment orientations and various pulse energy levels on top of the ito the device interfacial anchoring energy was found to be comparable to the anchoring energy of nematic lc on photosensitive polymers the device exhibits contrast of 301 and relaxation time of 330ms expected for thick lc devices the measured transparency of the lc device with two ito nanograting substrates is 10 higher than the uniform ito film based lc devices the alignment methodology presented here paves the way for improved lc displays and new structured lc photonic devices | [['electrodes', 'with', 'higher', 'transparency', 'that', 'can', 'also', 'align', 'liquid', 'crystals', 'lcs', 'are', 'of', 'high', 'importance', 'for', 'improved', 'costs', 'and', 'energy', 'consumption', 'of', 'lc', 'displays', 'here', 'we', 'demonstrate', 'for', 'the', 'first', 'time', 'alignment', 'of', 'liquid', 'crystals', 'on', 'femtosecond', 'laser', 'nanostructured', 'indium', 'tin', 'oxide', 'ito', 'coated', 'glass', 'exhibiting', 'also', 'higher', 'transparency', 'due', 'to', 'the', 'less', 'interface', 'reflections', 'the', 'nano', 'paterns', 'were', 'created', 'by', 'fs', 'laser', 'directlly', 'on', 'ito', 'films', 'without', 'any', 'additional', 'spin', 'coating', 'materials', 'or', 'lithography', 'procces', 'nine', 'regions', 'of', 'laserinduced', 'nanostructures', 'were', 'fabricated', 'with', 'different', 'alignment', 'orientations', 'and', 'various', 'pulse', 'energy', 'levels', 'on', 'top', 'of', 'the', 'ito', 'the', 'device', 'interfacial', 'anchoring', 'energy', 'was', 'found', 'to', 'be', 'comparable', 'to', 'the', 'anchoring', 'energy', 'of', 'nematic', 'lc', 'on', 'photosensitive', 'polymers', 'the', 'device', 'exhibits', 'contrast', 'of', '301', 'and', 'relaxation', 'time', 'of', '330ms', 'expected', 'for', 'thick', 'lc', 'devices', 'the', 'measured', 'transparency', 'of', 'the', 'lc', 'device', 'with', 'two', 'ito', 'nanograting', 'substrates', 'is', '10', 'higher', 'than', 'the', 'uniform', 'ito', 'film', 'based', 'lc', 'devices', 'the', 'alignment', 'methodology', 'presented', 'here', 'paves', 'the', 'way', 'for', 'improved', 'lc', 'displays', 'and', 'new', 'structured', 'lc', 'photonic', 'devices']] | [-0.12211338733870755, 0.1960321178440662, -0.0521908452076947, -0.035233172507929233, -0.016635463753824725, -0.21097640111624702, 0.03106884678469642, 0.5263507506864913, -0.21469621852259427, -0.350581927653676, 0.011639212551252807, -0.2864831634126056, -0.08513202168293954, 0.22302282880717778, -0.04925736990921638, 0.06768621840678593, -0.03301036028492758, -0.12545762314077685, -0.07395851994892035, -0.1855186133946785, 0.19439948318142664, 0.04427193941356724, 0.37618314141188475, 0.060564075136447654, 0.10555783828090438, -0.015461266605073914, 0.11282194157076232, -0.012118585643303745, -0.1502925041366646, 0.12481175537001998, 0.23487560348037412, -0.13376748520223533, 0.17481907682274195, -0.5573104159851723, -0.22022502623388873, -0.022312270817072953, 0.0904377923679182, 0.08782786044346935, -0.10086434232071043, -0.23531927946297562, 0.074489481443101, -0.11294436658191605, -0.10388645426043214, -0.014480298039886881, -0.020050618974218035, 0.08798903083558851, -0.1917070110081969, 0.013958435071125517, 0.0613702866851407, 0.08814724008278811, -0.07170999361748245, -0.13061882854877588, -0.07940330565975541, -0.019815641244435134, -0.023981144736685295, -0.002487360547050176, 0.26208360501674605, -0.109182758397861, -0.11823924451874679, 0.3422276180621017, -0.06233274385458037, -0.10744523747878916, 0.18386494144249488, -0.1659016167608035, 0.01839071808328085, 0.21575449386625276, 0.14650342405417605, 0.11701194898444502, -0.1704607903080828, 0.007204205568825059, 0.07363771512447034, 0.23152908895109944, 0.1785865086473196, 0.07367372658815892, 0.17829580615712878, 0.2907563022331006, 0.034819256317089584, 0.16610012935775825, -0.1471881657054944, 0.002545298738679027, -0.21540008643642067, -0.23892236887888216, -0.1714294398751329, 0.052150378862450664, -0.12542619862942955, -0.17804582722704201, 0.3637816670241163, 0.09976321800392779, 0.10246082893059151, -0.04178765913718106, 0.24507492229630076, 0.062164181427044024, 0.09569678815519984, -0.06880529446472579, 0.2708945172085591, 0.12328920846887152, 0.1376082680955091, -0.2405794390148538, 0.12546764721217402, -0.034490742318003496] |
1,802.09758 | Exotic phases of frustrated antiferromagnet LiCu2O2 | 7Li NMR spectra were measured in a magnetic field up to 17 T at temperatures
5-30 K on single crystalline LiCu2O2. Earlier reported anomalies on
magnetization curves correspond to magnetic field values where we observe
changes of the NMR spectral shape. For the interpretation of the field and
temperature evolutions of our NMR spectra, the magnetic structures were
analyzed in the frame of the phenomenological theoretical approach of the
Dzyaloshinskii-Landau theory. A set of possible planar and collinear structures
was obtained. Most of these structures have an unusual configuration; they are
characterized by a two-component order parameter and their magnetic moments
vary harmonically not only in direction, but also in size. From the modeling of
the observed spectra, a possible scenario of magnetic structure transformations
is obtained.
| cond-mat.str-el | 7li nmr spectra were measured in a magnetic field up to 17 t at temperatures 530 k on single crystalline licu2o2 earlier reported anomalies on magnetization curves correspond to magnetic field values where we observe changes of the nmr spectral shape for the interpretation of the field and temperature evolutions of our nmr spectra the magnetic structures were analyzed in the frame of the phenomenological theoretical approach of the dzyaloshinskiilandau theory a set of possible planar and collinear structures was obtained most of these structures have an unusual configuration they are characterized by a twocomponent order parameter and their magnetic moments vary harmonically not only in direction but also in size from the modeling of the observed spectra a possible scenario of magnetic structure transformations is obtained | [['7li', 'nmr', 'spectra', 'were', 'measured', 'in', 'a', 'magnetic', 'field', 'up', 'to', '17', 't', 'at', 'temperatures', '530', 'k', 'on', 'single', 'crystalline', 'licu2o2', 'earlier', 'reported', 'anomalies', 'on', 'magnetization', 'curves', 'correspond', 'to', 'magnetic', 'field', 'values', 'where', 'we', 'observe', 'changes', 'of', 'the', 'nmr', 'spectral', 'shape', 'for', 'the', 'interpretation', 'of', 'the', 'field', 'and', 'temperature', 'evolutions', 'of', 'our', 'nmr', 'spectra', 'the', 'magnetic', 'structures', 'were', 'analyzed', 'in', 'the', 'frame', 'of', 'the', 'phenomenological', 'theoretical', 'approach', 'of', 'the', 'dzyaloshinskiilandau', 'theory', 'a', 'set', 'of', 'possible', 'planar', 'and', 'collinear', 'structures', 'was', 'obtained', 'most', 'of', 'these', 'structures', 'have', 'an', 'unusual', 'configuration', 'they', 'are', 'characterized', 'by', 'a', 'twocomponent', 'order', 'parameter', 'and', 'their', 'magnetic', 'moments', 'vary', 'harmonically', 'not', 'only', 'in', 'direction', 'but', 'also', 'in', 'size', 'from', 'the', 'modeling', 'of', 'the', 'observed', 'spectra', 'a', 'possible', 'scenario', 'of', 'magnetic', 'structure', 'transformations', 'is', 'obtained']] | [-0.15252372369148015, 0.1797281067296613, -0.07293161952134503, 0.023913596927683564, -0.03844113399954661, -0.08271075638809375, 0.022561279863732617, 0.4287046181363246, -0.24065116843271497, -0.36191159016674473, 0.028305228352398862, -0.26755625484806916, -0.06393101992499498, 0.21197131679703793, 0.04760413198539662, 0.02474337418589996, -0.03029786479762859, 0.07936093064592338, -0.09049935593262375, -0.20781195162525695, 0.27300128419255276, 0.03672584495876753, 0.2623992019576863, 0.014608290748641131, 0.01953820603722263, -0.04117956347689624, 0.024302635881458482, 0.07018150235452349, -0.152451763690878, 0.06742528817457719, 0.21102668738938749, 0.015381299473884856, 0.11909686148883628, -0.4073961799786914, -0.22180045747183383, 0.049791119076193324, 0.11585639151079315, 0.11394654904004364, -0.034959537296792464, -0.2567117245191531, 0.05818788367988808, -0.08054728141897136, -0.14771915971493674, -0.1182058353479656, 0.011296022207557505, 0.024531322189547594, -0.2406324760139262, 0.09053799064089876, 0.05786341997528715, 0.14981362533326897, -0.15750826203766916, -0.1410469359880875, -0.030034146829700424, 0.05811203054950705, 0.046916159951785906, 0.04550012165961403, 0.1515183719540281, -0.10980252462895661, -0.1291609757712909, 0.3379083470633579, -0.049538679805303375, -0.07891317985818855, 0.14929327526543704, -0.22987244786354638, -0.14117673313289525, 0.1886624247463982, 0.13057435774022624, 0.1434692702041791, -0.13078418056275473, 0.08097319522482668, -0.01973682844508735, 0.17917601015171156, 0.07885563397587883, 0.02640698839806848, 0.2313397292801667, 0.12041401848961998, -0.04986721107418397, 0.11528962754481842, -0.15431629870796487, -0.05241818814482983, -0.2558587538059949, -0.10198032768214092, -0.16922566287278656, 0.04406602715804068, -0.07260332643463266, -0.16500670565587897, 0.4185864512941667, 0.11884860726930792, 0.25627550392666654, -0.05663357171533068, 0.2374131866390743, 0.0918538796398761, 0.08358499687349809, 0.03796471795344371, 0.2730482651275538, 0.20952981131683504, 0.1461607539409121, -0.2574652941834684, 0.047861716538179847, -0.011333254476388296] |
1,802.09759 | Rayleigh-Benard convection in a hard disk system | We do a generic study of the behavior of a hard disk system under the action
of a thermal gradient in presence of an uniform gravity field. We observe the
conduction-convection transition and measure the main system observables and
fields as the thermal current, global pressure, velocity field, temperature
field,... We can highlight two of the main results of this overall work: (1)
for large enough thermal gradients and a given gravity, we show that the
hydrodynamic fields (density, temperature and velocity) have a natural scaling
form with the gradient. And (2) we show that local equilibrium holds if the
mechanical pressure and the thermodynamic one are not equal, that is, the
Stoke's assumption does not hold in this case. Moreover we observe that the
best fit to the data is obtained when the bulk viscosity depends on the
mechanical pressure.
| cond-mat.stat-mech | we do a generic study of the behavior of a hard disk system under the action of a thermal gradient in presence of an uniform gravity field we observe the conductionconvection transition and measure the main system observables and fields as the thermal current global pressure velocity field temperature field we can highlight two of the main results of this overall work 1 for large enough thermal gradients and a given gravity we show that the hydrodynamic fields density temperature and velocity have a natural scaling form with the gradient and 2 we show that local equilibrium holds if the mechanical pressure and the thermodynamic one are not equal that is the stokes assumption does not hold in this case moreover we observe that the best fit to the data is obtained when the bulk viscosity depends on the mechanical pressure | [['we', 'do', 'a', 'generic', 'study', 'of', 'the', 'behavior', 'of', 'a', 'hard', 'disk', 'system', 'under', 'the', 'action', 'of', 'a', 'thermal', 'gradient', 'in', 'presence', 'of', 'an', 'uniform', 'gravity', 'field', 'we', 'observe', 'the', 'conductionconvection', 'transition', 'and', 'measure', 'the', 'main', 'system', 'observables', 'and', 'fields', 'as', 'the', 'thermal', 'current', 'global', 'pressure', 'velocity', 'field', 'temperature', 'field', 'we', 'can', 'highlight', 'two', 'of', 'the', 'main', 'results', 'of', 'this', 'overall', 'work', '1', 'for', 'large', 'enough', 'thermal', 'gradients', 'and', 'a', 'given', 'gravity', 'we', 'show', 'that', 'the', 'hydrodynamic', 'fields', 'density', 'temperature', 'and', 'velocity', 'have', 'a', 'natural', 'scaling', 'form', 'with', 'the', 'gradient', 'and', '2', 'we', 'show', 'that', 'local', 'equilibrium', 'holds', 'if', 'the', 'mechanical', 'pressure', 'and', 'the', 'thermodynamic', 'one', 'are', 'not', 'equal', 'that', 'is', 'the', 'stokes', 'assumption', 'does', 'not', 'hold', 'in', 'this', 'case', 'moreover', 'we', 'observe', 'that', 'the', 'best', 'fit', 'to', 'the', 'data', 'is', 'obtained', 'when', 'the', 'bulk', 'viscosity', 'depends', 'on', 'the', 'mechanical', 'pressure']] | [-0.1498206948229511, 0.14126254451953824, -0.12042762075683901, 0.017661261219265204, -0.03830351308653397, -0.07984080552456102, 0.0010743088321760296, 0.3576408738270402, -0.2633332696377433, -0.27397412427069084, 0.09283552802267618, -0.23799106277126286, -0.12089246574157317, 0.17797984717097798, -0.0463329007383436, 0.00629068183729292, 0.011845275126064994, 0.06658061593438365, -0.06616349931074572, -0.21692485879840595, 0.3598911509142324, 0.02862648433074355, 0.2767589099239558, 0.08271220133298941, 0.08915149580903485, -0.043890393272574456, 0.036202673903400345, 0.11182211596917893, -0.15496274318117814, 0.03736719509262392, 0.14244075104943477, 0.07071262339595705, 0.24539310823061636, -0.4183126958619271, -0.22901310613378884, 0.12055163479775989, 0.08843074112664909, 0.1308837400117357, -0.05097644639650493, -0.1813980403638977, 0.07928033083610769, -0.12131625727883406, -0.14415857127335455, -0.0992173072649166, 0.0012342217170433806, 0.043130070932342536, -0.27977122338821314, 0.10902463656717114, 0.10086753885428022, 0.05536678023636341, -0.12593005109644895, -0.09929954636276567, -0.03744933257278587, 0.12566152440454711, 0.0693577680819934, 0.04948360669160528, 0.1914846000727266, -0.1741643291049903, -0.033258707748193825, 0.38592678398958274, -0.14440827571919987, -0.1623197065799364, 0.22625999265624808, -0.21353195465302893, -0.11330767267583204, 0.09154768141784839, 0.13752244699613325, 0.09908581196130918, -0.13319550822374626, 0.07843056272332823, -0.05467969161940606, 0.18967379392623634, 0.02500683918395745, -0.003761372116527387, 0.2029694216059787, 0.10565634847319286, 0.08071091296816511, 0.13022114147066272, -0.10658083105268555, -0.05678884906893862, -0.3287077727727592, -0.18969817877015366, -0.1801655373003866, 0.0630627177358422, -0.11308670098764456, -0.1697689995901393, 0.3583711427952429, 0.19702897406449274, 0.19180912861400948, 0.06693786384670862, 0.29640390645779136, 0.15082431557239034, 0.05090000721309999, 0.12705446777067014, 0.30329275925510696, 0.1357349695238684, 0.11495391098183713, -0.2714933044742793, 0.03161583090966035, 0.004758402622038764] |
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