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1,802.0136
ORLA/OLAA: Orthogonal Coexistence of LAA and WiFi in Unlicensed Spectrum
Future mobile networks will exploit unlicensed spectrum to boost capacity and meet growing user demands cost-effectively. The 3GPP has recently defined a Licensed-Assisted Access (LAA) scheme to enable global Unlicensed LTE (U-LTE) deployment, aiming at ($i$) ensuring fair coexistence with incumbent WiFi networks, i.e., impacting on their performance no more than another WiFi device, and ($ii$) achieving superior airtime efficiency as compared to WiFi. In this paper we show the standardized LAA fails to simultaneously fulfill these objectives, and design an alternative orthogonal (collision-free) listen-before-talk coexistence paradigm that provides a substantial improvement in performance, yet imposes no penalty on existing WiFi networks. We derive two LAA optimal transmission policies, ORLA and OLAA, that maximize LAA throughput in both asynchronous and synchronous (i.e., with alignment to licensed anchor frame boundaries) modes of operation, respectively. We present a comprehensive performance evaluation through which we demonstrate that, when aggregating packets, IEEE 802.11ac WiFi can be more efficient than 3GPP LAA, whereas our proposals can attain 100% higher throughput, without harming WiFi. We further show that long U-LTE frames incur up to 92% throughput losses on WiFi when using 3GPP LAA, whilst ORLA/OLAA sustain $>$200% gains at no cost, even in the presence of non-saturated WiFi and/or in multi-rate scenarios.
cs.NI
future mobile networks will exploit unlicensed spectrum to boost capacity and meet growing user demands costeffectively the 3gpp has recently defined a licensedassisted access laa scheme to enable global unlicensed lte ulte deployment aiming at i ensuring fair coexistence with incumbent wifi networks ie impacting on their performance no more than another wifi device and ii achieving superior airtime efficiency as compared to wifi in this paper we show the standardized laa fails to simultaneously fulfill these objectives and design an alternative orthogonal collisionfree listenbeforetalk coexistence paradigm that provides a substantial improvement in performance yet imposes no penalty on existing wifi networks we derive two laa optimal transmission policies orla and olaa that maximize laa throughput in both asynchronous and synchronous ie with alignment to licensed anchor frame boundaries modes of operation respectively we present a comprehensive performance evaluation through which we demonstrate that when aggregating packets ieee 80211ac wifi can be more efficient than 3gpp laa whereas our proposals can attain 100 higher throughput without harming wifi we further show that long ulte frames incur up to 92 throughput losses on wifi when using 3gpp laa whilst orlaolaa sustain 200 gains at no cost even in the presence of nonsaturated wifi andor in multirate scenarios
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1,802.01361
Measure-preserving symmetries and reversibilities of ordinary differential systems
We prove that measure-preserving symmetries of an $n$-dimensional differential system preserve its divergence and the divergence derivatives along the solutions. Also, we prove that measure-preserving reversibilities preserve odd-order divergence derivatives along the solutions, and that even-order derivatives are multiplied by $-1$. We apply such results to find all the area-preserving symmetries and reversibilities of planar Lotka-Volterra and Li\'enard systems.
math.DS
we prove that measurepreserving symmetries of an ndimensional differential system preserve its divergence and the divergence derivatives along the solutions also we prove that measurepreserving reversibilities preserve oddorder divergence derivatives along the solutions and that evenorder derivatives are multiplied by 1 we apply such results to find all the areapreserving symmetries and reversibilities of planar lotkavolterra and lienard systems
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1,802.01362
Cuspidal cohomology of stacks of shtukas
Let $G$ be a connected split reductive group over a finite field ${\mathbb F}_q$ and $X$ a smooth projective geometrically connected curve over ${\mathbb F}_q$. The $\ell$-adic cohomology of stacks of $G$-shtukas is a generalization of the space of automorphic forms with compact support over the function field of $X$. In this paper, we construct a constant term morphism on the cohomology of stacks of shtukas which is a generalization of the constant term morphism for automorphic forms. We also define the cuspidal cohomology which generalizes the space of cuspidal automorphic forms. Then we show that the cuspidal cohomology has finite dimension and that it is equal to the (rationally) Hecke-finite cohomology defined by V. Lafforgue.
math.AG math.NT math.RT
let g be a connected split reductive group over a finite field mathbb f_q and x a smooth projective geometrically connected curve over mathbb f_q the elladic cohomology of stacks of gshtukas is a generalization of the space of automorphic forms with compact support over the function field of x in this paper we construct a constant term morphism on the cohomology of stacks of shtukas which is a generalization of the constant term morphism for automorphic forms we also define the cuspidal cohomology which generalizes the space of cuspidal automorphic forms then we show that the cuspidal cohomology has finite dimension and that it is equal to the rationally heckefinite cohomology defined by v lafforgue
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1,802.01363
First global next-to-leading order determination of diffractive parton distribution functions and their uncertainties within the {\tt xFitter} framework
We present {\tt GKG18-DPDFs}, a next-to-leading order (NLO) QCD analysis of diffractive parton distribution functions (diffractive PDFs) and their uncertainties. This is the first global set of diffractive PDFs determined within the {\tt xFitter} framework. This analysis is motivated by all available and most up-to-date data on inclusive diffractive deep inelastic scattering (diffractive DIS). Heavy quark contributions are considered within the framework of the Thorne-Roberts (TR) general mass variable flavor number scheme (GM-VFNS). We form a mutually consistent set of diffractive PDFs due to the inclusion of high-precision data from H1/ZEUS combined inclusive diffractive cross sections measurements. We study the impact of the H1/ZEUS combined data by producing a variety of determinations based on reduced data sets. We find that these data sets have a significant impact on the diffractive PDFs with some substantial reductions in uncertainties. The predictions based on the extracted diffractive PDFs are compared to the analyzed diffractive DIS data and with other determinations of the diffractive PDFs.
hep-ph hep-ex
we present tt gkg18dpdfs a nexttoleading order nlo qcd analysis of diffractive parton distribution functions diffractive pdfs and their uncertainties this is the first global set of diffractive pdfs determined within the tt xfitter framework this analysis is motivated by all available and most uptodate data on inclusive diffractive deep inelastic scattering diffractive dis heavy quark contributions are considered within the framework of the thorneroberts tr general mass variable flavor number scheme gmvfns we form a mutually consistent set of diffractive pdfs due to the inclusion of highprecision data from h1zeus combined inclusive diffractive cross sections measurements we study the impact of the h1zeus combined data by producing a variety of determinations based on reduced data sets we find that these data sets have a significant impact on the diffractive pdfs with some substantial reductions in uncertainties the predictions based on the extracted diffractive pdfs are compared to the analyzed diffractive dis data and with other determinations of the diffractive pdfs
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1,802.01364
Classifying and modelling spiral structures in hydrodynamic simulations of astrophysical discs
We demonstrate numerical techniques for automatic identification of individual spiral arms in hydrodynamic simulations of astrophysical discs. Building on our earlier work, which used tensor classification to identify regions that were "spiral-like", we can now obtain fits to spirals for individual arm elements. We show this process can even detect spirals in relatively flocculent spiral patterns, but the resulting fits to logarithmic "grand-design" spirals are less robust. Our methods not only permit the estimation of pitch angles, but also direct measurements of the spiral arm width and pattern speed. In principle, our techniques will allow the tracking of material as it passes through an arm. Our demonstration uses smoothed particle hydrodynamics simulations, but we stress that the method is suitable for any finite-element hydrodynamics system. We anticipate our techniques will be essential to studies of star formation in disc galaxies, and attempts to find the origin of recently observed spiral structure in protostellar discs.
astro-ph.GA astro-ph.EP
we demonstrate numerical techniques for automatic identification of individual spiral arms in hydrodynamic simulations of astrophysical discs building on our earlier work which used tensor classification to identify regions that were spirallike we can now obtain fits to spirals for individual arm elements we show this process can even detect spirals in relatively flocculent spiral patterns but the resulting fits to logarithmic granddesign spirals are less robust our methods not only permit the estimation of pitch angles but also direct measurements of the spiral arm width and pattern speed in principle our techniques will allow the tracking of material as it passes through an arm our demonstration uses smoothed particle hydrodynamics simulations but we stress that the method is suitable for any finiteelement hydrodynamics system we anticipate our techniques will be essential to studies of star formation in disc galaxies and attempts to find the origin of recently observed spiral structure in protostellar discs
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1,802.01365
A Bilevel Approach for Parameter Learning in Inverse Problems
A learning approach to selecting regularization parameters in multi-penalty Tikhonov regularization is investigated. It leads to a bilevel optimization problem, where the lower level problem is a Tikhonov regularized problem parameterized in the regularization parameters. Conditions which ensure the existence of solutions to the bilevel optimization problem of interest are derived, and these conditions are verified for two relevant examples. Difficulties arising from the possible lack of convexity of the lower level problems are discussed. Optimality conditions are given provided that a reasonable constraint qualification holds. Finally, results from numerical experiments used to test the developed theory are presented.
math.OC
a learning approach to selecting regularization parameters in multipenalty tikhonov regularization is investigated it leads to a bilevel optimization problem where the lower level problem is a tikhonov regularized problem parameterized in the regularization parameters conditions which ensure the existence of solutions to the bilevel optimization problem of interest are derived and these conditions are verified for two relevant examples difficulties arising from the possible lack of convexity of the lower level problems are discussed optimality conditions are given provided that a reasonable constraint qualification holds finally results from numerical experiments used to test the developed theory are presented
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1,802.01366
First Measurements of Beam Backgrounds at SuperKEKB
The high design luminosity of the SuperKEKB electron-positron collider is expected to result in challenging levels of beam-induced backgrounds in the interaction region. Properly simulating and mitigating these backgrounds is critical to the success of the Belle~II experiment. We report on measurements performed with a suite of dedicated beam background detectors, collectively known as BEAST II, during the so-called Phase 1 commissioning run of SuperKEKB in 2016, which involved operation of both the high energy ring (HER) of 7 GeV electrons as well as the low energy ring (LER) of 4 GeV positrons. We describe the BEAST II detector systems, the simulation of beam backgrounds, and the measurements performed. The measurements include standard ones of dose rates versus accelerator conditions, and more novel investigations, such as bunch-by-bunch measurements of injection backgrounds and measurements sensitive to the energy spectrum and angular distribution of fast neutrons. We observe beam-gas, Touschek, beam-dust, and injection backgrounds. We do not observe significant synchrotron radiation, as expected. Measured LER beam-gas backgrounds and Touschek backgrounds in both rings are slightly elevated, on average three times larger than the levels predicted by simulation. HER beam-gas backgrounds are on on average two orders of magnitude larger than predicted. Systematic uncertainties and channel-to-channel variations are large, so that these excesses constitute only 1-2 sigma level effects. Neutron background rates are higher than predicted and should be studied further. We will measure the remaining beam background processes, due to colliding beams, in the imminent commissioning Phase 2. These backgrounds are expected to be the most critical for Belle II, to the point of necessitating replacement of detector components during the Phase 3 (full-luminosity) operation of SuperKEB.
physics.ins-det hep-ex physics.acc-ph
the high design luminosity of the superkekb electronpositron collider is expected to result in challenging levels of beaminduced backgrounds in the interaction region properly simulating and mitigating these backgrounds is critical to the success of the belleii experiment we report on measurements performed with a suite of dedicated beam background detectors collectively known as beast ii during the socalled phase 1 commissioning run of superkekb in 2016 which involved operation of both the high energy ring her of 7 gev electrons as well as the low energy ring ler of 4 gev positrons we describe the beast ii detector systems the simulation of beam backgrounds and the measurements performed the measurements include standard ones of dose rates versus accelerator conditions and more novel investigations such as bunchbybunch measurements of injection backgrounds and measurements sensitive to the energy spectrum and angular distribution of fast neutrons we observe beamgas touschek beamdust and injection backgrounds we do not observe significant synchrotron radiation as expected measured ler beamgas backgrounds and touschek backgrounds in both rings are slightly elevated on average three times larger than the levels predicted by simulation her beamgas backgrounds are on on average two orders of magnitude larger than predicted systematic uncertainties and channeltochannel variations are large so that these excesses constitute only 12 sigma level effects neutron background rates are higher than predicted and should be studied further we will measure the remaining beam background processes due to colliding beams in the imminent commissioning phase 2 these backgrounds are expected to be the most critical for belle ii to the point of necessitating replacement of detector components during the phase 3 fullluminosity operation of superkeb
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1,802.01367
Integrable Subsectors from Holography
We consider operators in ${\cal N}=4$ super Yang-Mills theory dual to closed string states propagating on a class of LLM geometries. The LLM geometries we consider are specified by a boundary condition that is a set of black rings on the LLM plane. When projected to the LLM plane, the closed strings are polygons with all corners lying on the outer edge of a single ring. The large $N$ limit of correlators of these operators receives contributions from non-planar diagrams even for the leading large $N$ dynamics. Our interest in these fluctuations is because a previous weak coupling analysis argues that the net effect of summing the huge set of non-planar diagrams, is a simple rescaling of the 't Hooft coupling. We carry out some nontrivial checks of this proposal. Using the $su(2|2)^2$ symmetry we determine the two magnon $S$-matrix and demonstrate that it agrees, up to two loops, with a weak coupling computation performed in the CFT. We also compute the first finite size corrections to both the magnon and the dyonic magnon by constructing solutions to the Nambu-Goto action that carry finite angular momentum. These finite size computations constitute a strong coupling confirmation of the proposal.
hep-th
we consider operators in cal n4 super yangmills theory dual to closed string states propagating on a class of llm geometries the llm geometries we consider are specified by a boundary condition that is a set of black rings on the llm plane when projected to the llm plane the closed strings are polygons with all corners lying on the outer edge of a single ring the large n limit of correlators of these operators receives contributions from nonplanar diagrams even for the leading large n dynamics our interest in these fluctuations is because a previous weak coupling analysis argues that the net effect of summing the huge set of nonplanar diagrams is a simple rescaling of the t hooft coupling we carry out some nontrivial checks of this proposal using the su222 symmetry we determine the two magnon smatrix and demonstrate that it agrees up to two loops with a weak coupling computation performed in the cft we also compute the first finite size corrections to both the magnon and the dyonic magnon by constructing solutions to the nambugoto action that carry finite angular momentum these finite size computations constitute a strong coupling confirmation of the proposal
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1,802.01368
Dynamical gauge symmetry breaking in lower-dimensional Lorentz-violating supersymmetric theory
In this work we study the dynamical generation of mass in the Lorentz-violating low-dimensional Super-Yang-Mills theory in the aether superspace coupled to a scalar matter. We also suggest that our studies can be applied for condensed matter systems, especially lower-dimensional superconductors and topological insulators. In low dimensional materials, the parameter $\Delta$ generated by presence of the aether term can be interpreted as a quantity that renormalizes the propagation velocity of the bosonic mode with respect to the Fermi velocity.
hep-th
in this work we study the dynamical generation of mass in the lorentzviolating lowdimensional superyangmills theory in the aether superspace coupled to a scalar matter we also suggest that our studies can be applied for condensed matter systems especially lowerdimensional superconductors and topological insulators in low dimensional materials the parameter delta generated by presence of the aether term can be interpreted as a quantity that renormalizes the propagation velocity of the bosonic mode with respect to the fermi velocity
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1,802.01369
Driven Hofstadter Butterflies and Related Topological Invariants
The properties of the Hofstadter butterfly, a fractal, self similar spectrum of a two dimensional electron gas, are studied in the case where the system is additionally illuminated with monochromatic light. This is accomplished by applying Floquet theory to a tight binding model on the honeycomb lattice subjected to a perpendicular magnetic field and either linearly or circularly polarized light. It is shown how the deformation of the fractal structure of the spectrum depends on intensity and polarization. Thereby, the topological properties of the Hofstadter butterfly in presence of the oscillating electric field are investigated. A thorough numerical analysis of not only the Chern numbers but also the $W_{3}$-invariants gives the appropriate insight into the topology of this driven system. This includes a comparison of a direct $W_3$-calculation to the method based on summing up Chern numbers of the truncated Floquet Hamiltonian.
cond-mat.mes-hall
the properties of the hofstadter butterfly a fractal self similar spectrum of a two dimensional electron gas are studied in the case where the system is additionally illuminated with monochromatic light this is accomplished by applying floquet theory to a tight binding model on the honeycomb lattice subjected to a perpendicular magnetic field and either linearly or circularly polarized light it is shown how the deformation of the fractal structure of the spectrum depends on intensity and polarization thereby the topological properties of the hofstadter butterfly in presence of the oscillating electric field are investigated a thorough numerical analysis of not only the chern numbers but also the w_3invariants gives the appropriate insight into the topology of this driven system this includes a comparison of a direct w_3calculation to the method based on summing up chern numbers of the truncated floquet hamiltonian
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1,802.0137
A quantitative shrinking target result on Sturmian sequences for rotations
Let $R_\alpha$ be an irrational rotation of the circle, and code the orbit of any point $x$ by whether $R_\alpha^i(x)$ belongs to $[0,\alpha)$ or $[\alpha,1)$ -- this produces a Sturmian sequence. A point is undetermined at step $j$ if its coding up to time $j$ does not determine its coding at time $j+1$. We prove a pair of results on the asymptotic frequency of a point being undetermined, for full measure sets of $\alpha$ and $x$.
math.DS
let r_alpha be an irrational rotation of the circle and code the orbit of any point x by whether r_alphaix belongs to 0alpha or alpha1 this produces a sturmian sequence a point is undetermined at step j if its coding up to time j does not determine its coding at time j1 we prove a pair of results on the asymptotic frequency of a point being undetermined for full measure sets of alpha and x
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1,802.01371
General relativity with nonzero cosmological constant as a gauge theory
We show in a new way that the general relativity action (and Lagrangian)in recent Einstein-Palatini formulation is equivalent in four dimensions to the action (and Lagrangian) of a gauge field. This paper is a continuation of the previous paper [17] and it also gives an amended version of the lecture delivered by one of the authors [M.D.] at Hypercomplex Seminar in Bedlewo.
gr-qc
we show in a new way that the general relativity action and lagrangianin recent einsteinpalatini formulation is equivalent in four dimensions to the action and lagrangian of a gauge field this paper is a continuation of the previous paper 17 and it also gives an amended version of the lecture delivered by one of the authors md at hypercomplex seminar in bedlewo
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1,802.01372
Multi-parameter extensions of a theorem of Pichorides
Extending work of Pichorides and Zygmund to the $d$-dimensional setting, we show that the supremum of $L^p$-norms of the Littlewood-Paley square function over the unit ball of the analytic Hardy spaces $H^p_A(\mathbb{T}^d)$ blows up like $(p-1)^{-d}$ as $p\to 1^+$. Furthermore, we obtain an $L\log^d L$-estimate for square functions on $H^1_A(\mathbb{T}^d)$. Euclidean variants of Pichorides's theorem are also obtained.
math.CA math.CV
extending work of pichorides and zygmund to the ddimensional setting we show that the supremum of lpnorms of the littlewoodpaley square function over the unit ball of the analytic hardy spaces hp_amathbbtd blows up like p1d as pto 1 furthermore we obtain an llogd lestimate for square functions on h1_amathbbtd euclidean variants of pichoridess theorem are also obtained
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1,802.01373
Optimal Besov differentiability for entropy solutions of the Eikonal equation
In this paper we study the Eikonal equation in a bounded planar domain. We prove the equivalence among optimal Besov regularity, the finiteness of every entropy production and the validity of a kinetic formulation.
math.AP
in this paper we study the eikonal equation in a bounded planar domain we prove the equivalence among optimal besov regularity the finiteness of every entropy production and the validity of a kinetic formulation
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1,802.01374
Congruences for the Coefficients of the Powers of the Euler Product
Let $p_k(n)$ be given by the $k$-th power of the Euler Product $\prod _{n=1}^{\infty}(1-q^n)^k=\sum_{n=0}^{\infty}p_k(n)q^{n}$. By investigating the properties of the modular equations of the second and the third order under the Atkin $U$-operator, we determine the generating functions of $p_{8k}(2^{2\alpha} n +\frac{k(2^{2\alpha}-1)}{3})$ $(1\leq k\leq 3)$ and $p_{3k} (3^{2\beta}n+\frac{k(3^{2\beta}-1)}{8})$ $(1\leq k\leq 8)$ in terms of some linear recurring sequences. Combining with a result of Engstrom about the periodicity of linear recurring sequences modulo $m$, we obtain infinite families of congruences for $p_k(n)$ modulo any $m\geq2$, where $1\leq k\leq 24$ and $3|k$ or $8|k$. Based on these congruences for $p_k(n)$, infinite families of congruences for many partition functions such as the overpartition function, $t$-core partition functions and $\ell$-regular partition functions are easily obtained.
math.CO math.NT
let p_kn be given by the kth power of the euler product prod _n1infty1qnksum_n0inftyp_knqn by investigating the properties of the modular equations of the second and the third order under the atkin uoperator we determine the generating functions of p_8k22alpha n frack22alpha13 1leq kleq 3 and p_3k 32betanfrack32beta18 1leq kleq 8 in terms of some linear recurring sequences combining with a result of engstrom about the periodicity of linear recurring sequences modulo m we obtain infinite families of congruences for p_kn modulo any mgeq2 where 1leq kleq 24 and 3k or 8k based on these congruences for p_kn infinite families of congruences for many partition functions such as the overpartition function tcore partition functions and ellregular partition functions are easily obtained
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1,802.01375
Adipochondrocytes in rabbit auricular cartilage
Chondrocytes are described as one cell population in different cartilage types. The auricular cartilage in mouse and rat contains unique chondrocytes similar in morphology to white adipocytes and known as lipochondrocytes. Lipochondrocytes were not mentioned in other species. The current study aimed to explore the existence of this cell type in rabbits. The auricles of adult male white rabbits were harvested and processed for histological examination with light and electron microscopy. With the light microscopy, the auricular cartilage of adult rabbits contained central large rounded adipocyte-like chondrocytes, termed in the current study adipochondrocytes The adipochondrocytes were embedded in relatively wide lacunae and had large lipid droplets with a rim of cytoplasm. The scanning electron microscopy confirmed this result. With the transmission electron microscopy, the adipochondrocytes showed dark nucleus and electron-dense cytoplasm with few organelles and cytoplasmic processes. The adipochondrocytes of the auricular cartilage in adult rabbits were unique cell type and different from chondrocytes in other cartilage subtypes. This result should be considered during cartilage transplant. Further studies are suggested to investigate the development and physiological roles of adipochondrocytes in the auricular cartilage in rabbits.
q-bio.TO
chondrocytes are described as one cell population in different cartilage types the auricular cartilage in mouse and rat contains unique chondrocytes similar in morphology to white adipocytes and known as lipochondrocytes lipochondrocytes were not mentioned in other species the current study aimed to explore the existence of this cell type in rabbits the auricles of adult male white rabbits were harvested and processed for histological examination with light and electron microscopy with the light microscopy the auricular cartilage of adult rabbits contained central large rounded adipocytelike chondrocytes termed in the current study adipochondrocytes the adipochondrocytes were embedded in relatively wide lacunae and had large lipid droplets with a rim of cytoplasm the scanning electron microscopy confirmed this result with the transmission electron microscopy the adipochondrocytes showed dark nucleus and electrondense cytoplasm with few organelles and cytoplasmic processes the adipochondrocytes of the auricular cartilage in adult rabbits were unique cell type and different from chondrocytes in other cartilage subtypes this result should be considered during cartilage transplant further studies are suggested to investigate the development and physiological roles of adipochondrocytes in the auricular cartilage in rabbits
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1,802.01376
Two-dimensional type-II Dirac fermions in layered oxides
Relativistic massless Dirac fermions can be probed with high-energy physics experiments, but appear also as low-energy quasi-particle excitations in electronic band structures. In condensed matter systems, their massless nature can be protected by crystal symmetries. Classification of such symmetry-protected relativistic band degeneracies has been fruitful, although many of the predicted quasi-particles still await their experimental discovery. Here we reveal, using angle-resolved photoemission spectroscopy, the existence of two-dimensional type-II Dirac fermions in the high-temperature superconductor La$_{1.77}$Sr$_{0.23}$CuO$_4$. The Dirac point, constituting the crossing of $d_{x^2-y^2}$ and $d_{z^2}$ bands, is found approximately one electronvolt below the Fermi level ($E_\mathrm{F}$) and is protected by mirror symmetry. If spin-orbit coupling is considered, the Dirac point degeneracy is lifted and the bands acquire a topologically non-trivial character. In certain nickelate systems, band structure calculations suggest that the same type-II Dirac fermions can be realised near $E_\mathrm{F}$.
cond-mat.str-el cond-mat.mtrl-sci cond-mat.supr-con
relativistic massless dirac fermions can be probed with highenergy physics experiments but appear also as lowenergy quasiparticle excitations in electronic band structures in condensed matter systems their massless nature can be protected by crystal symmetries classification of such symmetryprotected relativistic band degeneracies has been fruitful although many of the predicted quasiparticles still await their experimental discovery here we reveal using angleresolved photoemission spectroscopy the existence of twodimensional typeii dirac fermions in the hightemperature superconductor la_177sr_023cuo_4 the dirac point constituting the crossing of d_x2y2 and d_z2 bands is found approximately one electronvolt below the fermi level e_mathrmf and is protected by mirror symmetry if spinorbit coupling is considered the dirac point degeneracy is lifted and the bands acquire a topologically nontrivial character in certain nickelate systems band structure calculations suggest that the same typeii dirac fermions can be realised near e_mathrmf
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1,802.01377
The nature of the TRAPPIST-1 exoplanets
Context. The TRAPPIST-1 system hosts seven Earth-sized, temperate exoplanets orbiting an ultra-cool dwarf star. As such, it represents a remarkable setting to study the formation and evolution of terrestrial planets that formed in the same protoplanetary disk. While the sizes of the TRAPPIST-1 planets are all known to better than 5% precision, their densities have significant uncertainties (between 28% and 95%) because of poor constraints on the planet's masses. Aims.The goal of this paper is to improve our knowledge of the TRAPPIST-1 planetary masses and densities using transit-timing variations (TTV). The complexity of the TTV inversion problem is known to be particularly acute in multi-planetary systems (convergence issues, degeneracies and size of the parameter space), especially for resonant chain systems such as TRAPPIST-1. Methods. To overcome these challenges, we have used a novel method that employs a genetic algorithm coupled to a full N-body integrator that we applied to a set of 284 individual transit timings. This approach enables us to efficiently explore the parameter space and to derive reliable masses and densities from TTVs for all seven planets. Results. Our new masses result in a five- to eight-fold improvement on the planetary density uncertainties, with precisions ranging from 5% to 12%. These updated values provide new insights into the bulk structure of the TRAPPIST-1 planets. We find that TRAPPIST-1\,c and e likely have largely rocky interiors, while planets b, d, f, g, and h require envelopes of volatiles in the form of thick atmospheres, oceans, or ice, in most cases with water mass fractions less than 5%.
astro-ph.EP
context the trappist1 system hosts seven earthsized temperate exoplanets orbiting an ultracool dwarf star as such it represents a remarkable setting to study the formation and evolution of terrestrial planets that formed in the same protoplanetary disk while the sizes of the trappist1 planets are all known to better than 5 precision their densities have significant uncertainties between 28 and 95 because of poor constraints on the planets masses aimsthe goal of this paper is to improve our knowledge of the trappist1 planetary masses and densities using transittiming variations ttv the complexity of the ttv inversion problem is known to be particularly acute in multiplanetary systems convergence issues degeneracies and size of the parameter space especially for resonant chain systems such as trappist1 methods to overcome these challenges we have used a novel method that employs a genetic algorithm coupled to a full nbody integrator that we applied to a set of 284 individual transit timings this approach enables us to efficiently explore the parameter space and to derive reliable masses and densities from ttvs for all seven planets results our new masses result in a five to eightfold improvement on the planetary density uncertainties with precisions ranging from 5 to 12 these updated values provide new insights into the bulk structure of the trappist1 planets we find that trappist1c and e likely have largely rocky interiors while planets b d f g and h require envelopes of volatiles in the form of thick atmospheres oceans or ice in most cases with water mass fractions less than 5
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1,802.01378
Psychological Safety and Norm Clarity in Software Engineering Teams
In the software engineering industry today, companies primarily conduct their work in teams. To increase organizational productivity, it is thus crucial to know the factors that affect team effectiveness. Two team-related concepts that have gained prominence lately are psychological safety and team norms. Still, few studies exist that explore these in a software engineering context. Therefore, with the aim of extending the knowledge of these concepts, we examined if psychological safety and team norm clarity associate positively with software developers' self-assessed team performance and job satisfaction, two important elements of effectiveness. We collected industry survey data from practitioners (N = 217) in 38 development teams working for five different organizations. The result of multiple linear regression analyses indicates that both psychological safety and team norm clarity predict team members' self-assessed performance and job satisfaction. The findings also suggest that clarity of norms is a stronger (30\% and 71\% stronger, respectively) predictor than psychological safety. This research highlights the need to examine, in more detail, the relationship between social norms and software development. The findings of this study could serve as an empirical baseline for such, future work.
cs.SE
in the software engineering industry today companies primarily conduct their work in teams to increase organizational productivity it is thus crucial to know the factors that affect team effectiveness two teamrelated concepts that have gained prominence lately are psychological safety and team norms still few studies exist that explore these in a software engineering context therefore with the aim of extending the knowledge of these concepts we examined if psychological safety and team norm clarity associate positively with software developers selfassessed team performance and job satisfaction two important elements of effectiveness we collected industry survey data from practitioners n 217 in 38 development teams working for five different organizations the result of multiple linear regression analyses indicates that both psychological safety and team norm clarity predict team members selfassessed performance and job satisfaction the findings also suggest that clarity of norms is a stronger 30 and 71 stronger respectively predictor than psychological safety this research highlights the need to examine in more detail the relationship between social norms and software development the findings of this study could serve as an empirical baseline for such future work
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1,802.01379
Online Compact Convexified Factorization Machine
Factorization Machine (FM) is a supervised learning approach with a powerful capability of feature engineering. It yields state-of-the-art performance in various batch learning tasks where all the training data is made available prior to the training. However, in real-world applications where the data arrives sequentially in a streaming manner, the high cost of re-training with batch learning algorithms has posed formidable challenges in the online learning scenario. The initial challenge is that no prior formulations of FM could fulfill the requirements in Online Convex Optimization (OCO) -- the paramount framework for online learning algorithm design. To address the aforementioned challenge, we invent a new convexification scheme leading to a Compact Convexified FM (CCFM) that seamlessly meets the requirements in OCO. However for learning Compact Convexified FM (CCFM) in the online learning setting, most existing algorithms suffer from expensive projection operations. To address this subsequent challenge, we follow the general projection-free algorithmic framework of Online Conditional Gradient and propose an Online Compact Convex Factorization Machine (OCCFM) algorithm that eschews the projection operation with efficient linear optimization steps. In support of the proposed OCCFM in terms of its theoretical foundation, we prove that the developed algorithm achieves a sub-linear regret bound. To evaluate the empirical performance of OCCFM, we conduct extensive experiments on 6 real-world datasets for online recommendation and binary classification tasks. The experimental results show that OCCFM outperforms the state-of-art online learning algorithms.
cs.LG
factorization machine fm is a supervised learning approach with a powerful capability of feature engineering it yields stateoftheart performance in various batch learning tasks where all the training data is made available prior to the training however in realworld applications where the data arrives sequentially in a streaming manner the high cost of retraining with batch learning algorithms has posed formidable challenges in the online learning scenario the initial challenge is that no prior formulations of fm could fulfill the requirements in online convex optimization oco the paramount framework for online learning algorithm design to address the aforementioned challenge we invent a new convexification scheme leading to a compact convexified fm ccfm that seamlessly meets the requirements in oco however for learning compact convexified fm ccfm in the online learning setting most existing algorithms suffer from expensive projection operations to address this subsequent challenge we follow the general projectionfree algorithmic framework of online conditional gradient and propose an online compact convex factorization machine occfm algorithm that eschews the projection operation with efficient linear optimization steps in support of the proposed occfm in terms of its theoretical foundation we prove that the developed algorithm achieves a sublinear regret bound to evaluate the empirical performance of occfm we conduct extensive experiments on 6 realworld datasets for online recommendation and binary classification tasks the experimental results show that occfm outperforms the stateofart online learning algorithms
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1,802.0138
Moir\'e structure of MoS$_2$ on Au(111): Local structural and electronic properties
Monolayer islands of molybdenum disulfide (MoS$_2$) on Au(111) form a characteristic moir\'e structure, leading to locally different stacking sequences at the S-Mo-S-Au interface. Using low-temperature scanning tunneling microscopy (STM) and atomic force microscopy (AFM), we find that the moir\'e islands exhibit a unique orientation with respect to the Au crystal structure. This indicates a clear preference of MoS$_2$ growth in a regular stacking fashion. We further probe the influence of the local atomic structure on the electronic properties. Differential conductance spectra show pronounced features of the valence band and conduction band, some of which undergo significant shifts depending on the local atomic structure. We also determine the tunneling decay constant as a function of the bias voltage by a height-modulated spectroscopy method. This allows for an increased sensitivity of states with non-negligible parallel momentum $k_\parallel$ and the identification of the origin of the states from different areas in the Brillouin zone.
cond-mat.mes-hall
monolayer islands of molybdenum disulfide mos_2 on au111 form a characteristic moire structure leading to locally different stacking sequences at the smosau interface using lowtemperature scanning tunneling microscopy stm and atomic force microscopy afm we find that the moire islands exhibit a unique orientation with respect to the au crystal structure this indicates a clear preference of mos_2 growth in a regular stacking fashion we further probe the influence of the local atomic structure on the electronic properties differential conductance spectra show pronounced features of the valence band and conduction band some of which undergo significant shifts depending on the local atomic structure we also determine the tunneling decay constant as a function of the bias voltage by a heightmodulated spectroscopy method this allows for an increased sensitivity of states with nonnegligible parallel momentum k_parallel and the identification of the origin of the states from different areas in the brillouin zone
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1,802.01381
Randomness and isometries in echo state networks and compressed sensing
Although largely different concepts, echo state networks and compressed sensing models both rely on collections of random weights; as the reservoir dynamics for echo state networks, and the sensing coefficients in compressed sensing. Several methods for generating the random matrices and metrics to indicate desirable performance are well-studied in compressed sensing, but less so for echo state networks. This work explores any overlap in these compressed sensing methods and metrics for application to echo state networks. Several methods for generating the random reservoir weights are considered, and a new metric, inspired by the restricted isometry property for compressed sensing, is proposed for echo state networks. The methods and metrics are investigated theoretically and experimentally, with results suggesting that the same types of random matrices work well for both echo state network and compressed sensing scenarios, and that echo state network classification accuracy is improved when the proposed restricted isometry-like constants are close to 1.
cs.IT eess.SP math.IT
although largely different concepts echo state networks and compressed sensing models both rely on collections of random weights as the reservoir dynamics for echo state networks and the sensing coefficients in compressed sensing several methods for generating the random matrices and metrics to indicate desirable performance are wellstudied in compressed sensing but less so for echo state networks this work explores any overlap in these compressed sensing methods and metrics for application to echo state networks several methods for generating the random reservoir weights are considered and a new metric inspired by the restricted isometry property for compressed sensing is proposed for echo state networks the methods and metrics are investigated theoretically and experimentally with results suggesting that the same types of random matrices work well for both echo state network and compressed sensing scenarios and that echo state network classification accuracy is improved when the proposed restricted isometrylike constants are close to 1
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1,802.01382
Comment on "Experimental Verification of a Jarzynski-Related Information-Theoretic Equality by a Single Trapped Ion" PRL 120 010601 (2018)
The target paper presents an experimental verification of a "Jarzynski-related" equality. We show that the latter equality is in fact not related to the Jarzynski equality.
cond-mat.stat-mech
the target paper presents an experimental verification of a jarzynskirelated equality we show that the latter equality is in fact not related to the jarzynski equality
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1,802.01383
Commutator Subgroups of Virtual and Welded Braid Groups
Let $VB_n$, resp. $WB_n$ denote the virtual, resp. welded, braid group on $n$ strands. We study their commutator subgroups $VB_n' = [VB_n, VB_n]$ and, $WB_n' = [WB_n, WB_n]$ respectively. We obtain a set of generators and defining relations for these commutator subgroups. In particular, we prove that $VB_n'$ is finitely generated if and only if $n \geq 4$, and $WB_n'$ is finitely generated for $n \geq 3$. Also we prove that $VB_3'/VB_3'' =\mathbb{Z}_3 \oplus \mathbb{Z}_3 \oplus\mathbb{Z}_3 \oplus \mathbb{Z}^{\infty}$, $VB_4' / VB_4'' = \mathbb{Z}_3 \oplus \mathbb{Z}_3 \oplus \mathbb{Z}_3$, $WB_3'/WB_3'' = \mathbb{Z}_3 \oplus \mathbb{Z}_3 \oplus\mathbb{Z}_3 \oplus \mathbb{Z},$ $WB_4'/WB_4'' = \mathbb{Z}_3,$ and for $n \geq 5$ the commutator subgroups $VB_n'$ and $WB_n'$ are perfect, i.e. the commutator subgroup is equal to the second commutator subgroup.
math.GT math.GR
let vb_n resp wb_n denote the virtual resp welded braid group on n strands we study their commutator subgroups vb_n vb_n vb_n and wb_n wb_n wb_n respectively we obtain a set of generators and defining relations for these commutator subgroups in particular we prove that vb_n is finitely generated if and only if n geq 4 and wb_n is finitely generated for n geq 3 also we prove that vb_3vb_3 mathbbz_3 oplus mathbbz_3 oplusmathbbz_3 oplus mathbbzinfty vb_4 vb_4 mathbbz_3 oplus mathbbz_3 oplus mathbbz_3 wb_3wb_3 mathbbz_3 oplus mathbbz_3 oplusmathbbz_3 oplus mathbbz wb_4wb_4 mathbbz_3 and for n geq 5 the commutator subgroups vb_n and wb_n are perfect ie the commutator subgroup is equal to the second commutator subgroup
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1,802.01384
Strong Decay of $P_c(4380)$ Pentaquark in a Molecular Picture
There are different assumptions on the substructure of the pentaquarks $P_c(4380)$ and $P_c(4450)$, newly founded in $J/\psi N $ invariant mass by the LHCb collaboration, giving consistent mass results with the experimental observations. The experimental data and recent theoretical studies on their mass suggest interpretation of these states as spin-3/2 negative-parity and spin-5/2 positive-parity pentaquarks, respectively. There may exist opposite-parity states corresponding to these particles, as well. Despite a lot of studies, however, the nature and internal organization of these pentaquarks in terms of quarks and gluons are not clear. To this end we need more theoretical investigations on other physical properties of these states. In this accordance, we study a strong and dominant decay of the $P_c(4380)$ to $J/\psi$ and $N$ in the framework of three point QCD sum rule method. An interpolating current in a molecular form is applied to calculate six strong coupling form factors defining the transitions of the positive and negative parity spin-3/2 pentaquark states. The values of the coupling constants are used in the calculation of the decay widths of these transitions. The obtained results are compared with the existing experimental data.
hep-ph hep-ex hep-lat
there are different assumptions on the substructure of the pentaquarks p_c4380 and p_c4450 newly founded in jpsi n invariant mass by the lhcb collaboration giving consistent mass results with the experimental observations the experimental data and recent theoretical studies on their mass suggest interpretation of these states as spin32 negativeparity and spin52 positiveparity pentaquarks respectively there may exist oppositeparity states corresponding to these particles as well despite a lot of studies however the nature and internal organization of these pentaquarks in terms of quarks and gluons are not clear to this end we need more theoretical investigations on other physical properties of these states in this accordance we study a strong and dominant decay of the p_c4380 to jpsi and n in the framework of three point qcd sum rule method an interpolating current in a molecular form is applied to calculate six strong coupling form factors defining the transitions of the positive and negative parity spin32 pentaquark states the values of the coupling constants are used in the calculation of the decay widths of these transitions the obtained results are compared with the existing experimental data
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1,802.01385
Chiral Anomaly, Topological Field Theory, and Novel States of Matter
Starting with a description of the motivation underlying the analysis presented in this paper and a brief survey of the chiral anomaly, I proceed to review some basic elements of the theory of the quantum Hall effect in 2D incompressible electron gases in an external magnetic field, ("Hall insulators"). I discuss the origin and role of anomalous chiral edge currents and of anomaly inflow in 2D insulators with explicitly or spontaneously broken time reversal, i.e., in Hall insulators and "Chern insulators". The topological Chern-Simons action yielding the large-scale response equations for the 2D bulk of such states of matter is displayed. A classification of Hall insulators featuring quasi-particles with abelian braid statistics is sketched. Subsequently, the chiral edge spin currents encountered in some time-reversal invariant 2D topological insulators with spin-orbit interactions and the bulk response equations of such materials are described. A short digression into the theory of 3D topological insulators, including "axionic insulators", follows next. To conclude, some open problems are described and a problem in cosmology related to axionic insulators is mentioned. As far as the quantum Hall effect and the spin currents in time-reversal invariant 2D topological insulators are concerned this review is based on extensive work my collaborators and I carried out in the early 1990's.
cond-mat.mes-hall
starting with a description of the motivation underlying the analysis presented in this paper and a brief survey of the chiral anomaly i proceed to review some basic elements of the theory of the quantum hall effect in 2d incompressible electron gases in an external magnetic field hall insulators i discuss the origin and role of anomalous chiral edge currents and of anomaly inflow in 2d insulators with explicitly or spontaneously broken time reversal ie in hall insulators and chern insulators the topological chernsimons action yielding the largescale response equations for the 2d bulk of such states of matter is displayed a classification of hall insulators featuring quasiparticles with abelian braid statistics is sketched subsequently the chiral edge spin currents encountered in some timereversal invariant 2d topological insulators with spinorbit interactions and the bulk response equations of such materials are described a short digression into the theory of 3d topological insulators including axionic insulators follows next to conclude some open problems are described and a problem in cosmology related to axionic insulators is mentioned as far as the quantum hall effect and the spin currents in timereversal invariant 2d topological insulators are concerned this review is based on extensive work my collaborators and i carried out in the early 1990s
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1,802.01386
Curvature Inequalities and Extremal Operators
A curvature inequality is established for contractive commuting tuples of operators in the Cowen-Douglas class of rank n. Properties of the extremal operators, that is, the operators which achieve equality, are investigated. Specifically, a substantial part of a well known question due to R. G. Douglas involving these extremal operators, in the case of the unit disc, is answered.
math.FA
a curvature inequality is established for contractive commuting tuples of operators in the cowendouglas class of rank n properties of the extremal operators that is the operators which achieve equality are investigated specifically a substantial part of a well known question due to r g douglas involving these extremal operators in the case of the unit disc is answered
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1,802.01387
Classification of Informative Frames in Colonoscopy Videos Using Convolutional Neural Networks with Binarized Weights
Colorectal cancer is one of the common cancers in the United States. Polyp is one of the main causes of the colonic cancer and early detection of polyps will increase chance of cancer treatments. In this paper, we propose a novel classification of informative frames based on a convolutional neural network with binarized weights. The proposed CNN is trained with colonoscopy frames along with the labels of the frames as input data. We also used binarized weights and kernels to reduce the size of CNN and make it suitable for implementation in medical hardware. We evaluate our proposed method using Asu Mayo Test clinic database, which contains colonoscopy videos of different patients. Our proposed method reaches a dice score of 71.20% and accuracy of more than 90% using the mentioned dataset.
eess.IV
colorectal cancer is one of the common cancers in the united states polyp is one of the main causes of the colonic cancer and early detection of polyps will increase chance of cancer treatments in this paper we propose a novel classification of informative frames based on a convolutional neural network with binarized weights the proposed cnn is trained with colonoscopy frames along with the labels of the frames as input data we also used binarized weights and kernels to reduce the size of cnn and make it suitable for implementation in medical hardware we evaluate our proposed method using asu mayo test clinic database which contains colonoscopy videos of different patients our proposed method reaches a dice score of 7120 and accuracy of more than 90 using the mentioned dataset
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1,802.01388
A Signature-based Algorithm for computing Computing Gr\"obner Bases over Principal Ideal Domains
Signature-based algorithms have become a standard approach for Gr\"obner basis computations for polynomial systems over fields, but how to extend these techniques to coefficients in general rings is not yet as well understood. In this paper, we present a proof-of-concept signature-based algorithm for computing Gr\"obner bases over commutative integral domains. It is adapted from a general version of M\"oller's algorithm (1988) which considers reductions by multiple polynomials at each step. This algorithm performs reductions with non-decreasing signatures, and in particular, signature drops do not occur. When the coefficients are from a principal ideal domain (e.g. the ring of integers or the ring of univariate polynomials over a field), we prove correctness and termination of the algorithm, and we show how to use signature properties to implement classic signature-based criteria to eliminate some redundant reductions. In particular, if the input is a regular sequence, the algorithm operates without any reduction to 0. We have written a toy implementation of the algorithm in Magma. Early experimental results suggest that the algorithm might even be correct and terminate in a more general setting, for polynomials over a unique factorization domain (e.g. the ring of multivariate polynomials over a field or a PID).
cs.SC
signaturebased algorithms have become a standard approach for grobner basis computations for polynomial systems over fields but how to extend these techniques to coefficients in general rings is not yet as well understood in this paper we present a proofofconcept signaturebased algorithm for computing grobner bases over commutative integral domains it is adapted from a general version of mollers algorithm 1988 which considers reductions by multiple polynomials at each step this algorithm performs reductions with nondecreasing signatures and in particular signature drops do not occur when the coefficients are from a principal ideal domain eg the ring of integers or the ring of univariate polynomials over a field we prove correctness and termination of the algorithm and we show how to use signature properties to implement classic signaturebased criteria to eliminate some redundant reductions in particular if the input is a regular sequence the algorithm operates without any reduction to 0 we have written a toy implementation of the algorithm in magma early experimental results suggest that the algorithm might even be correct and terminate in a more general setting for polynomials over a unique factorization domain eg the ring of multivariate polynomials over a field or a pid
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1,802.01389
Counting inversions and descents of random elements in finite Coxeter groups
We investigate Mahonian and Eulerian probability distributions given by inversions and descents in general finite Coxeter groups. We provide uniform formulas for the means and variances in terms of Coxeter group data in both cases. We also provide uniform formulas for the double-Eulerian probability distribution of the sum of descents and inverse descents. We finally establish necessary and sufficient conditions for general sequences of Coxeter groups of increasing rank under which Mahonian and Eulerian probability distributions satisfy central and local limit theorems.
math.CO
we investigate mahonian and eulerian probability distributions given by inversions and descents in general finite coxeter groups we provide uniform formulas for the means and variances in terms of coxeter group data in both cases we also provide uniform formulas for the doubleeulerian probability distribution of the sum of descents and inverse descents we finally establish necessary and sufficient conditions for general sequences of coxeter groups of increasing rank under which mahonian and eulerian probability distributions satisfy central and local limit theorems
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1,802.0139
Isoperimetric inequality and Weitzenb\"ock type formula for critical metrics of the volume
We provide an isoperimetric inequality for critical metrics of the volume functional with nonnegative scalar curvature on compact manifolds with boundary. In addition, we establish a Weitzenb\"ock type formula for critical metrics of the volume functional on four-dimensional manifolds. As an application, we obtain a classification result for such metrics.
math.DG
we provide an isoperimetric inequality for critical metrics of the volume functional with nonnegative scalar curvature on compact manifolds with boundary in addition we establish a weitzenbock type formula for critical metrics of the volume functional on fourdimensional manifolds as an application we obtain a classification result for such metrics
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1,802.01391
Plasma evolution within an erupting coronal cavity
Coronal cavities have previously been observed associated with long-lived quiescent filaments and are thought to correspond to the associated magnetic flux rope. Although the standard flare model predicts a coronal cavity corresponding to the erupting flux rope, these have only been observed using broadband imaging data, restricting analysis to the plane-of-sky. We present a unique set of spectroscopic observations of an active region filament seen erupting at the solar limb in the extreme ultraviolet (EUV). The cavity erupted and expanded rapidly, with the change in rise phase contemporaneous with an increase in non-thermal electron energy flux of the associated flare. Hot and cool filamentary material was observed to rise with the erupting flux rope, disappearing suddenly as the cavity appeared. Although strongly blue-shifted plasma continued to be observed flowing from the apex of the erupting flux rope, this outflow soon ceased. These results indicate that the sudden injection of energy from the flare beneath forced the rapid eruption and expansion of the flux rope, driving strong plasma flows which resulted in the eruption of an under-dense filamentary flux rope.
astro-ph.SR
coronal cavities have previously been observed associated with longlived quiescent filaments and are thought to correspond to the associated magnetic flux rope although the standard flare model predicts a coronal cavity corresponding to the erupting flux rope these have only been observed using broadband imaging data restricting analysis to the planeofsky we present a unique set of spectroscopic observations of an active region filament seen erupting at the solar limb in the extreme ultraviolet euv the cavity erupted and expanded rapidly with the change in rise phase contemporaneous with an increase in nonthermal electron energy flux of the associated flare hot and cool filamentary material was observed to rise with the erupting flux rope disappearing suddenly as the cavity appeared although strongly blueshifted plasma continued to be observed flowing from the apex of the erupting flux rope this outflow soon ceased these results indicate that the sudden injection of energy from the flare beneath forced the rapid eruption and expansion of the flux rope driving strong plasma flows which resulted in the eruption of an underdense filamentary flux rope
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1,802.01392
Grassmann representation in qubit informatics and superlogic
The Grassmann representation for the system of qubits, is considered. The treatment is based on natural description of the qubits system as fermions and uses coherent states of fermions. The quantum logic gates are represented in two forms - by symbols of operations and by partial differential operators on the symbols of the states. The considered representation of quantum logic is called as superlogic. The examples are given for classical logic operations of negation, conjunction, disjunction and for reversible three-bit Toffoli gate and its quantum generalization - three-qbit Deutsch gate. The representation for composite gates is also considered. Path integral represenatation in Grassmann algebra for quantum automaton with qubits memory is described. In particular for the autonomous automaton corresponding to the special case of general dynamic system this description differ from path integral representation in commutative memory phase space by the specific nonliner term in superaction.
quant-ph
the grassmann representation for the system of qubits is considered the treatment is based on natural description of the qubits system as fermions and uses coherent states of fermions the quantum logic gates are represented in two forms by symbols of operations and by partial differential operators on the symbols of the states the considered representation of quantum logic is called as superlogic the examples are given for classical logic operations of negation conjunction disjunction and for reversible threebit toffoli gate and its quantum generalization threeqbit deutsch gate the representation for composite gates is also considered path integral represenatation in grassmann algebra for quantum automaton with qubits memory is described in particular for the autonomous automaton corresponding to the special case of general dynamic system this description differ from path integral representation in commutative memory phase space by the specific nonliner term in superaction
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1,802.01393
Seasonal Stochastic Volatility and the Samuelson Effect in Agricultural Futures Markets
We introduce a multi-factor stochastic volatility model for commodities that incorporates seasonality and the Samuelson effect. Conditions on the seasonal term under which the corresponding volatility factor is well-defined are given, and five different specifications of the seasonality pattern are proposed. We calculate the joint characteristic function of two futures prices for different maturities in the risk-neutral measure. The model is then presented under the physical measure, and its state-space representation is derived, in order to estimate the parameters with the Kalman filter for time series of corn, cotton, soybean, sugar and wheat futures from 2007 to 2017. The seasonal model significantly outperforms the nested non-seasonal model in all five markets, and we show which seasonality patterns are particularly well-suited in each case. We also confirm the importance of correctly modelling the Samuelson effect in order to account for futures with different maturities. Our results are clearly confirmed in a robustness check carried out with an alternative dataset of constant maturity futures for the same agricultural markets.
q-fin.PR
we introduce a multifactor stochastic volatility model for commodities that incorporates seasonality and the samuelson effect conditions on the seasonal term under which the corresponding volatility factor is welldefined are given and five different specifications of the seasonality pattern are proposed we calculate the joint characteristic function of two futures prices for different maturities in the riskneutral measure the model is then presented under the physical measure and its statespace representation is derived in order to estimate the parameters with the kalman filter for time series of corn cotton soybean sugar and wheat futures from 2007 to 2017 the seasonal model significantly outperforms the nested nonseasonal model in all five markets and we show which seasonality patterns are particularly wellsuited in each case we also confirm the importance of correctly modelling the samuelson effect in order to account for futures with different maturities our results are clearly confirmed in a robustness check carried out with an alternative dataset of constant maturity futures for the same agricultural markets
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1,802.01394
General features of experiments on the dynamics of laser-driven electron-positron beams
The experimental study of the dynamics of neutral electron-positron beams is an emerging area of research, enabled by the recent results on the generation of this exotic state of matter in the laboratory. Electron-positron beams and plasmas are believed to play a major role in the dynamics of extreme astrophysical objects such as supermassive black holes and pulsars. For instance, they are believed to be the main constituents of a large number of astrophysical jets, and they have been proposed to significantly contribute to the emission of gamma-ray bursts and their afterglow. However, despite extensive numerical modelling and indirect astrophysical observations, a detailed experimental characterisation of the dynamics of these objects is still at its infancy. Here, we will report on some of the general features of experiments studying the dynamics of electron-positron beams in a fully laser-driven setup.
physics.plasm-ph
the experimental study of the dynamics of neutral electronpositron beams is an emerging area of research enabled by the recent results on the generation of this exotic state of matter in the laboratory electronpositron beams and plasmas are believed to play a major role in the dynamics of extreme astrophysical objects such as supermassive black holes and pulsars for instance they are believed to be the main constituents of a large number of astrophysical jets and they have been proposed to significantly contribute to the emission of gammaray bursts and their afterglow however despite extensive numerical modelling and indirect astrophysical observations a detailed experimental characterisation of the dynamics of these objects is still at its infancy here we will report on some of the general features of experiments studying the dynamics of electronpositron beams in a fully laserdriven setup
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1,802.01395
Intent-Based In-flight Service Encryption in Multi-Layer Transport Networks
We demonstrate multi-layer encrypted service provisioning via the ACINO orchestrator. ACINO combines a novel intent interface with an ONOS-based SDN orchestrator to facilitate encrypted services at IP, Ethernet and optical network layers.
cs.NI cs.CR
we demonstrate multilayer encrypted service provisioning via the acino orchestrator acino combines a novel intent interface with an onosbased sdn orchestrator to facilitate encrypted services at ip ethernet and optical network layers
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1,802.01396
To understand deep learning we need to understand kernel learning
Generalization performance of classifiers in deep learning has recently become a subject of intense study. Deep models, typically over-parametrized, tend to fit the training data exactly. Despite this "overfitting", they perform well on test data, a phenomenon not yet fully understood. The first point of our paper is that strong performance of overfitted classifiers is not a unique feature of deep learning. Using six real-world and two synthetic datasets, we establish experimentally that kernel machines trained to have zero classification or near zero regression error perform very well on test data, even when the labels are corrupted with a high level of noise. We proceed to give a lower bound on the norm of zero loss solutions for smooth kernels, showing that they increase nearly exponentially with data size. We point out that this is difficult to reconcile with the existing generalization bounds. Moreover, none of the bounds produce non-trivial results for interpolating solutions. Second, we show experimentally that (non-smooth) Laplacian kernels easily fit random labels, a finding that parallels results for ReLU neural networks. In contrast, fitting noisy data requires many more epochs for smooth Gaussian kernels. Similar performance of overfitted Laplacian and Gaussian classifiers on test, suggests that generalization is tied to the properties of the kernel function rather than the optimization process. Certain key phenomena of deep learning are manifested similarly in kernel methods in the modern "overfitted" regime. The combination of the experimental and theoretical results presented in this paper indicates a need for new theoretical ideas for understanding properties of classical kernel methods. We argue that progress on understanding deep learning will be difficult until more tractable "shallow" kernel methods are better understood.
stat.ML cs.LG
generalization performance of classifiers in deep learning has recently become a subject of intense study deep models typically overparametrized tend to fit the training data exactly despite this overfitting they perform well on test data a phenomenon not yet fully understood the first point of our paper is that strong performance of overfitted classifiers is not a unique feature of deep learning using six realworld and two synthetic datasets we establish experimentally that kernel machines trained to have zero classification or near zero regression error perform very well on test data even when the labels are corrupted with a high level of noise we proceed to give a lower bound on the norm of zero loss solutions for smooth kernels showing that they increase nearly exponentially with data size we point out that this is difficult to reconcile with the existing generalization bounds moreover none of the bounds produce nontrivial results for interpolating solutions second we show experimentally that nonsmooth laplacian kernels easily fit random labels a finding that parallels results for relu neural networks in contrast fitting noisy data requires many more epochs for smooth gaussian kernels similar performance of overfitted laplacian and gaussian classifiers on test suggests that generalization is tied to the properties of the kernel function rather than the optimization process certain key phenomena of deep learning are manifested similarly in kernel methods in the modern overfitted regime the combination of the experimental and theoretical results presented in this paper indicates a need for new theoretical ideas for understanding properties of classical kernel methods we argue that progress on understanding deep learning will be difficult until more tractable shallow kernel methods are better understood
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1,802.01397
Generic representations for symmetric spaces
For a connected quasi-split reductive algebraic group $G$ over a field $k$, which is either a finite field or a non-archimedean local field, $\theta$ an involutive automorphism of $G$ over $k$, let $K =G^\theta$. Let $K^1=[K^0,K^0]$, the commutator subgroup of $K^0$, the connected component of identity of $K$. In this paper, we provide a simple condition on $(G,\theta)$ for there to be an irreducible admissible generic representations $\pi$ of $G$ with ${\rm Hom}_{K^1}[\pi,{\mathbb C}] \not = 0$. The condition is most easily stated in terms of a real reductive group $G_\theta({\mathbb R})$ associated to the pair $(G,\theta)$ being quasi-split.
math.RT math.NT
for a connected quasisplit reductive algebraic group g over a field k which is either a finite field or a nonarchimedean local field theta an involutive automorphism of g over k let k gtheta let k1k0k0 the commutator subgroup of k0 the connected component of identity of k in this paper we provide a simple condition on gtheta for there to be an irreducible admissible generic representations pi of g with rm hom_k1pimathbb c not 0 the condition is most easily stated in terms of a real reductive group g_thetamathbb r associated to the pair gtheta being quasisplit
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1,802.01398
Soft photon and two hard jets forward production in proton-nucleus collisions
We calculate the cross section for production of a soft photon and two hard jets in the forward rapidity region in proton-nucleus collisions at high energies. The calculation is performed within the hybrid formalism. The hardness of the final particles is defined with respect to the saturation scale of the nucleus. We consider both the correlation limit of small momentum imbalance and the dilute target limit where the momentum imbalance is of the order of the hardness of the jets. The results depend on the first two transverse-momentum-dependent (TMD) gluon distributions of the nucleus.
hep-ph nucl-th
we calculate the cross section for production of a soft photon and two hard jets in the forward rapidity region in protonnucleus collisions at high energies the calculation is performed within the hybrid formalism the hardness of the final particles is defined with respect to the saturation scale of the nucleus we consider both the correlation limit of small momentum imbalance and the dilute target limit where the momentum imbalance is of the order of the hardness of the jets the results depend on the first two transversemomentumdependent tmd gluon distributions of the nucleus
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1,802.01399
Molecular diffusion of stable water isotopes in polar firn as a proxy for past temperatures
Polar precipitation archived in ice caps contains information on past temperature conditions. Such information can be retrieved by measuring the water isotopic signals of $\delta{}^{18}\mathrm{O}$ and $\delta\mathrm{D}$ in ice cores. These signals have been attenuated during densification due to molecular diffusion in the firn column, where the magnitude of the diffusion is isotopologoue specific and temperature dependent. By utilizing the differential diffusion signal, dual isotope measurements of $\delta{}^{18}\mathrm{O}$ and $\delta\mathrm{D}$ enable multiple temperature reconstruction techniques. This study assesses how well six different methods can be used to reconstruct past surface temperatures from the diffusion-based temperature proxies. Two of the methods are based on the single diffusion lengths of $\delta{}^{18}\mathrm{O}$ and $\delta\mathrm{D}$, three of the methods employ the differential diffusion signal, while the last uses the ratio between the single diffusion lengths. All techniques are tested on synthetic data in order to evaluate their accuracy and precision. We perform a benchmark test to thirteen high resolution Holocene data sets from Greenland and Antarctica, which represent a broad range of mean annual surface temperatures and accumulation rates. Based on the benchmark test, we comment on the accuracy and precision of the methods. Both the benchmark test and the synthetic data test demonstrate that the most precise reconstructions are obtained when using the single isotope diffusion lengths, with precisions of approximately $1.0\,^\mathrm{o}\mathrm{C}$. In the benchmark test, the single isotope diffusion lengths are also found to reconstruct consistent temperatures with a root-mean-square-deviation of $0.7\,^\mathrm{o}\mathrm{C}$.
physics.geo-ph
polar precipitation archived in ice caps contains information on past temperature conditions such information can be retrieved by measuring the water isotopic signals of delta18mathrmo and deltamathrmd in ice cores these signals have been attenuated during densification due to molecular diffusion in the firn column where the magnitude of the diffusion is isotopologoue specific and temperature dependent by utilizing the differential diffusion signal dual isotope measurements of delta18mathrmo and deltamathrmd enable multiple temperature reconstruction techniques this study assesses how well six different methods can be used to reconstruct past surface temperatures from the diffusionbased temperature proxies two of the methods are based on the single diffusion lengths of delta18mathrmo and deltamathrmd three of the methods employ the differential diffusion signal while the last uses the ratio between the single diffusion lengths all techniques are tested on synthetic data in order to evaluate their accuracy and precision we perform a benchmark test to thirteen high resolution holocene data sets from greenland and antarctica which represent a broad range of mean annual surface temperatures and accumulation rates based on the benchmark test we comment on the accuracy and precision of the methods both the benchmark test and the synthetic data test demonstrate that the most precise reconstructions are obtained when using the single isotope diffusion lengths with precisions of approximately 10mathrmomathrmc in the benchmark test the single isotope diffusion lengths are also found to reconstruct consistent temperatures with a rootmeansquaredeviation of 07mathrmomathrmc
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1,802.014
Polarization and Fake News: Early Warning of Potential Misinformation Targets
Users polarization and confirmation bias play a key role in misinformation spreading on online social media. Our aim is to use this information to determine in advance potential targets for hoaxes and fake news. In this paper, we introduce a general framework for promptly identifying polarizing content on social media and, thus, "predicting" future fake news topics. We validate the performances of the proposed methodology on a massive Italian Facebook dataset, showing that we are able to identify topics that are susceptible to misinformation with 77% accuracy. Moreover, such information may be embedded as a new feature in an additional classifier able to recognize fake news with 91% accuracy. The novelty of our approach consists in taking into account a series of characteristics related to users behavior on online social media, making a first, important step towards the smoothing of polarization and the mitigation of misinformation phenomena.
cs.SI
users polarization and confirmation bias play a key role in misinformation spreading on online social media our aim is to use this information to determine in advance potential targets for hoaxes and fake news in this paper we introduce a general framework for promptly identifying polarizing content on social media and thus predicting future fake news topics we validate the performances of the proposed methodology on a massive italian facebook dataset showing that we are able to identify topics that are susceptible to misinformation with 77 accuracy moreover such information may be embedded as a new feature in an additional classifier able to recognize fake news with 91 accuracy the novelty of our approach consists in taking into account a series of characteristics related to users behavior on online social media making a first important step towards the smoothing of polarization and the mitigation of misinformation phenomena
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1,802.01401
Transition Metal Chalcogenide Tin Sulfide Nanodimensional Films Align Liquid Crystals
Transition metal chalcogenide tin sulfide (SnS) films as alternative noncontact alignment layer for liquid crystals, have been demonstrated and investigated. The SnS has an anisotropic atomic chain structure similar to black Phosphorous which causes the liquid crystal molecules to align without the need for any additional surface treatments. The high anisotropic nature of SnS promotes the alignment of the easy axis of liquid crystal molecules along the periodic atomic grooves of the SnS layer. The atomically thin SnS layers were deposited on indium tin oxide films on glass substrates, at room temperature by chemical vapor deposition. The device characteristics are comparable to those commercially available, which use photo-aligning polymer materials. We measured threshold voltage of 0.92V, anchoring energy of 1.573x10^(-6) J/m^2, contrast ratio better than 71:1 and electro-optical rise/fall times of 80/390ms, respectively for ~11 micron thick liquid crystal device as expected.
physics.app-ph
transition metal chalcogenide tin sulfide sns films as alternative noncontact alignment layer for liquid crystals have been demonstrated and investigated the sns has an anisotropic atomic chain structure similar to black phosphorous which causes the liquid crystal molecules to align without the need for any additional surface treatments the high anisotropic nature of sns promotes the alignment of the easy axis of liquid crystal molecules along the periodic atomic grooves of the sns layer the atomically thin sns layers were deposited on indium tin oxide films on glass substrates at room temperature by chemical vapor deposition the device characteristics are comparable to those commercially available which use photoaligning polymer materials we measured threshold voltage of 092v anchoring energy of 1573x106 jm2 contrast ratio better than 711 and electrooptical risefall times of 80390ms respectively for 11 micron thick liquid crystal device as expected
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1,802.01402
Holder continuity of the steepest descent direction for multiobjective optimization
The aim of this manuscript is to characterize the continuity properties of the multiobjective steepest descent direction for smooth objective functions. We will show that this direction is Holder continuous with optimal exponent 1/2. In particular, this direction fails to be Lipschitz continuous even for polynomial objectives.
math.OC
the aim of this manuscript is to characterize the continuity properties of the multiobjective steepest descent direction for smooth objective functions we will show that this direction is holder continuous with optimal exponent 12 in particular this direction fails to be lipschitz continuous even for polynomial objectives
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1,802.01403
An AI aid to the editors. Exploring the possibility of an AI assisted article classification system
This work is a preliminary exploratory study of how we could progress a step towards an AI assisted article classification sys- tem in academia. The proposed system aims to aid the journal editors in their decisions by pinpointing the potential weaknesses or strengths of a submitted manuscript. From a large collection of articles and corresponding author-editor interactions we explore the possible reasons that lead to a paper being not forwarded for review. Our investigation reveals that in most cases either it is be- cause the prospective manuscript is out of scope of the journal or the manuscript does not satisfy the minimum quality requirements to maintain the standard of the journal. We extract several features to quantify the quality of a paper and the degree of in-scope explor- ing keyword search, citation analysis, reputations of authors and affiliations, similarity with respect to accepted papers. With these features we train standard machine learning classifiers to develop a classification system. On a decent set of test data our approach yields promising results across 3 different journals. We believe that our approach is generic and could be adapted to other journals with appropriate adjustments.
cs.DL
this work is a preliminary exploratory study of how we could progress a step towards an ai assisted article classification sys tem in academia the proposed system aims to aid the journal editors in their decisions by pinpointing the potential weaknesses or strengths of a submitted manuscript from a large collection of articles and corresponding authoreditor interactions we explore the possible reasons that lead to a paper being not forwarded for review our investigation reveals that in most cases either it is be cause the prospective manuscript is out of scope of the journal or the manuscript does not satisfy the minimum quality requirements to maintain the standard of the journal we extract several features to quantify the quality of a paper and the degree of inscope explor ing keyword search citation analysis reputations of authors and affiliations similarity with respect to accepted papers with these features we train standard machine learning classifiers to develop a classification system on a decent set of test data our approach yields promising results across 3 different journals we believe that our approach is generic and could be adapted to other journals with appropriate adjustments
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1,802.01404
Blowup Analysis for the Perfect Conductivity Problem with convex but not strictly convex inclusions
In the perfect conductivity problem, it is interesting to study whether the electric field can become arbitrarily large or not, in a narrow region between two adjacent perfectly conducting inclusions. In this paper, we show that the relative convexity of two adjacent inclusions plays a key role in the blowup analysis of the electric field and find some new phenomena. By energy method, we prove the boundedness of the gradient of the solution if two adjacent inclusions fail to be locally relatively strictly convex, namely, if the top and bottom boundaries of the narrow region are partially "flat". The boundary estimates when an inclusion with partially "flat" boundary is close to the "flat" matrix boundary and estimates for the general elliptic equation of divergence form are also established in all dimensions.
math.AP
in the perfect conductivity problem it is interesting to study whether the electric field can become arbitrarily large or not in a narrow region between two adjacent perfectly conducting inclusions in this paper we show that the relative convexity of two adjacent inclusions plays a key role in the blowup analysis of the electric field and find some new phenomena by energy method we prove the boundedness of the gradient of the solution if two adjacent inclusions fail to be locally relatively strictly convex namely if the top and bottom boundaries of the narrow region are partially flat the boundary estimates when an inclusion with partially flat boundary is close to the flat matrix boundary and estimates for the general elliptic equation of divergence form are also established in all dimensions
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1,802.01405
Comparing approaches for mitigating intergroup variability in personality recognition
Personality have been found to predict many life outcomes, and there have been huge interests on automatic personality recognition from a speaker's utterance. Previously, we achieved accuracies between 37%-44% for three-way classification of high, medium or low for each of the Big Five personality traits (Openness to Experience, Conscientiousness, Extraversion, Agreeableness, Neuroticism). We show here that we can improve performance on this task by accounting for heterogeneity of gender and L1 in our data, which has English speech from female and male native speakers of Chinese and Standard American English (SAE). We experiment with personalizing models by L1 and gender and normalizing features by speaker, L1 group, and/or gender.
cs.SD cs.CL eess.AS
personality have been found to predict many life outcomes and there have been huge interests on automatic personality recognition from a speakers utterance previously we achieved accuracies between 3744 for threeway classification of high medium or low for each of the big five personality traits openness to experience conscientiousness extraversion agreeableness neuroticism we show here that we can improve performance on this task by accounting for heterogeneity of gender and l1 in our data which has english speech from female and male native speakers of chinese and standard american english sae we experiment with personalizing models by l1 and gender and normalizing features by speaker l1 group andor gender
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1,802.01406
Vertices for Iwahori-Hecke algebras and the Dipper-Du conjecture
Let $\mathscr{H}_n$ denote the Iwahori-Hecke algebra corresponding to the symmetric group $\mathfrak{S}_n$. We set up a Green correspondence for bimodules of these Hecke algebras, and a Brauer correspondence between their blocks. We examine Specht modules for $\mathscr{H}_n$ and compute the vertices of certain Specht modules, before using this to give a classification of the vertices of blocks of $\mathscr{H}_n$ in any characteristic. Finally, we apply this classification to resolve the Dipper-Du conjecture about the structure of vertices of indecomposable $\mathscr{H}_n$-modules.
math.RT
let mathscrh_n denote the iwahorihecke algebra corresponding to the symmetric group mathfraks_n we set up a green correspondence for bimodules of these hecke algebras and a brauer correspondence between their blocks we examine specht modules for mathscrh_n and compute the vertices of certain specht modules before using this to give a classification of the vertices of blocks of mathscrh_n in any characteristic finally we apply this classification to resolve the dipperdu conjecture about the structure of vertices of indecomposable mathscrh_nmodules
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1,802.01407
Fixed point theorems involving numerical invariants
We exhibit invariants of smooth projective algebraic varieties with integer values, whose nonvanishing modulo p prevents the existence of an action without fixed points of certain finite p-groups. The case of base fields of characteristic p is included. Counterexamples are systematically provided to test the sharpness of our results.
math.AG
we exhibit invariants of smooth projective algebraic varieties with integer values whose nonvanishing modulo p prevents the existence of an action without fixed points of certain finite pgroups the case of base fields of characteristic p is included counterexamples are systematically provided to test the sharpness of our results
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1,802.01408
Independence of the grossone-based infinity methodology from non-standard analysis and comments upon logical fallacies in some texts asserting the opposite
This commentary considers non-standard analysis and a recently introduced computational methodology based on the notion of \G1 (this symbol is called \emph{grossone}). The latter approach was developed with the intention to allow one to work with infinities and infinitesimals numerically in a unique computational framework and in all the situations requiring these notions. Non-standard analysis is a classical purely symbolic technique that works with ultrafilters, external and internal sets, standard and non-standard numbers, etc. In its turn, the \G1-based methodology does not use any of these notions and proposes a more physical treatment of mathematical objects separating the objects from tools used to study them. It both offers a possibility to create new numerical methods using infinities and infinitesimals in floating-point computations and allows one to study certain mathematical objects dealing with infinity more accurately than it is done traditionally. In these notes, we explain that even though both methodologies deal with infinities and infinitesimals, they are independent and represent two different philosophies of Mathematics that are not in a conflict. It is proved that texts \cite{Flunks, Gutman_Kutateladze_2008, Kutateladze_2011} asserting that the \G1-based methodology is a part of non-standard analysis unfortunately contain several logical fallacies. Their attempt to prove that the \G1-based methodology is a part of non-standard analysis is similar to trying to show that constructivism can be reduced to the traditional mathematics.
math.GM
this commentary considers nonstandard analysis and a recently introduced computational methodology based on the notion of g1 this symbol is called emphgrossone the latter approach was developed with the intention to allow one to work with infinities and infinitesimals numerically in a unique computational framework and in all the situations requiring these notions nonstandard analysis is a classical purely symbolic technique that works with ultrafilters external and internal sets standard and nonstandard numbers etc in its turn the g1based methodology does not use any of these notions and proposes a more physical treatment of mathematical objects separating the objects from tools used to study them it both offers a possibility to create new numerical methods using infinities and infinitesimals in floatingpoint computations and allows one to study certain mathematical objects dealing with infinity more accurately than it is done traditionally in these notes we explain that even though both methodologies deal with infinities and infinitesimals they are independent and represent two different philosophies of mathematics that are not in a conflict it is proved that texts citeflunks gutman_kutateladze_2008 kutateladze_2011 asserting that the g1based methodology is a part of nonstandard analysis unfortunately contain several logical fallacies their attempt to prove that the g1based methodology is a part of nonstandard analysis is similar to trying to show that constructivism can be reduced to the traditional mathematics
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1,802.01409
Spatial control of carrier capture in two-dimensional materials: Beyond energy selection rules
Transition metal dichalcogenide monolayers have attracted wide attention due to their remarkable optical, electronic and mechanical properties. In these materials local strain distributions effectively form quasi zero-dimensional potentials, whose localized states may be populated by carrier capture from the continuum states. Using a recently developed Lindblad single-particle approach, here we study the phonon-induced carrier capture in a MoSe$_2$ monolayer. Although one decisive control parameter is the energy selection rule, which links the energy of the incoming carriers to that of the final state via the emitted phonon, we show that additionally the spatio-temporal dynamics plays a crucial role. By varying the direction of the incoming carriers with respect to the orientation of the localized potential, we introduce a new control mechanism for the carrier capture: the spatial control.
cond-mat.mes-hall
transition metal dichalcogenide monolayers have attracted wide attention due to their remarkable optical electronic and mechanical properties in these materials local strain distributions effectively form quasi zerodimensional potentials whose localized states may be populated by carrier capture from the continuum states using a recently developed lindblad singleparticle approach here we study the phononinduced carrier capture in a mose_2 monolayer although one decisive control parameter is the energy selection rule which links the energy of the incoming carriers to that of the final state via the emitted phonon we show that additionally the spatiotemporal dynamics plays a crucial role by varying the direction of the incoming carriers with respect to the orientation of the localized potential we introduce a new control mechanism for the carrier capture the spatial control
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1,802.0141
High resolution nanofocus X-ray source based on ultracold electrons from laser cooled-atoms
X-ray 3D tomography is So far limited to micron resolution because of the large focusing spot of the focused electron beam on the metal target. Here, we proposed a nanofocous X-ray 3D tomography system based on focused electrons from laser-cooled atoms in a nanoscale region of metal target in vacuum useful for 3D nanotomography and submicron volumetric imaging. We have shown the system has submicron resolution because of ability of focusing cold electrons to submicron size, the smaller the X-ray focal spot, the higher the resolution will be. In our system flux through the specimen of (photons/mm^2/s) can be improved by sub-micron focusing of X-ray radiation as well. In contrast, synchrotrons and X-ray tubes provide intense radiation beams, however, these attributes are not necessary for microtomography and the proposed sub-microfocus source compares favorably with respect to the radiation flux because of ability of sub-micron focusing of electrons from near-threshold photoionizing laser cooled atoms.
physics.ins-det physics.bio-ph
xray 3d tomography is so far limited to micron resolution because of the large focusing spot of the focused electron beam on the metal target here we proposed a nanofocous xray 3d tomography system based on focused electrons from lasercooled atoms in a nanoscale region of metal target in vacuum useful for 3d nanotomography and submicron volumetric imaging we have shown the system has submicron resolution because of ability of focusing cold electrons to submicron size the smaller the xray focal spot the higher the resolution will be in our system flux through the specimen of photonsmm2s can be improved by submicron focusing of xray radiation as well in contrast synchrotrons and xray tubes provide intense radiation beams however these attributes are not necessary for microtomography and the proposed submicrofocus source compares favorably with respect to the radiation flux because of ability of submicron focusing of electrons from nearthreshold photoionizing laser cooled atoms
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1,802.01411
Carrier-envelope-phase stable, high-contrast, double chirped-pulse-amplification laser system
We present the first carrier-envelope phase stable chirped pulse amplifier (CPA) featuring high temporal contrast for relativistic intensity laser-plasma interactions at 1 kHz repetition rate. The laser is based on a double-CPA architecture including XPW filtering technique and a high-energy grism-based compressor. 8 mJ, 22 fs pulses are produced with 10-11 temporal contrast at -20 ps and a CEP drift of 240 mrad RMS.
physics.optics
we present the first carrierenvelope phase stable chirped pulse amplifier cpa featuring high temporal contrast for relativistic intensity laserplasma interactions at 1 khz repetition rate the laser is based on a doublecpa architecture including xpw filtering technique and a highenergy grismbased compressor 8 mj 22 fs pulses are produced with 1011 temporal contrast at 20 ps and a cep drift of 240 mrad rms
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1,802.01412
The convexity of inclusions and gradient's concentration for Lam\'e systems with partially infinite coefficients
It is interesting to study the stress concentration between two adjacent stiff inclusions in composite materials, which can be modeled by the Lam\'e system with partially infinite coefficients. To overcome the difficulty from the lack of maximum principle for elliptic systems, we use the energy method and an iteration technique to study the gradient estimates of the solution. We first find a novel phenomenon that the gradient will not blow up any more once these two adjacent inclusions fail to be locally relatively strictly convex, namely, the top and bottom boundaries of the narrow region are partially "flat". This is contrary to our expectation. In order to further explore the blow-up mechanism of the gradient, we next investigate two adjacent inclusions with relative convexity of order m and finally reveal an underlying relationship between the blow-up rate of the stress and the order of the relative convexity of the subdomains in all dimensions.
math.AP
it is interesting to study the stress concentration between two adjacent stiff inclusions in composite materials which can be modeled by the lame system with partially infinite coefficients to overcome the difficulty from the lack of maximum principle for elliptic systems we use the energy method and an iteration technique to study the gradient estimates of the solution we first find a novel phenomenon that the gradient will not blow up any more once these two adjacent inclusions fail to be locally relatively strictly convex namely the top and bottom boundaries of the narrow region are partially flat this is contrary to our expectation in order to further explore the blowup mechanism of the gradient we next investigate two adjacent inclusions with relative convexity of order m and finally reveal an underlying relationship between the blowup rate of the stress and the order of the relative convexity of the subdomains in all dimensions
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1,802.01413
Nonconservative traceless type gravity
Extensions of the gravity theory in order to obtain traceless field equations have been widely considered in the literature. The leading example of such class of theories is the unimodular gravity, but there are other possibilities like the mimetic gravity and the Rastall gravity with a coupling parameter $\lambda = 1/2$. The unimodular gravity proposal is a very interesting approach in other to address the cosmological constant problem. When coupled to matter such theories may imply that the energy-momentum tensor is not divergence free anymore. In this paper, a unimodular type theory will be developed by evading the conservation $T^{\mu\nu}_{\, ; \mu}=0$. The cosmological consequences of the later, both at background as well as for scalar and tensor perturbations, are explored. Possible further extensions of this approach are discussed as well as its connection with the traditional unimodular gravity.
gr-qc astro-ph.CO hep-th
extensions of the gravity theory in order to obtain traceless field equations have been widely considered in the literature the leading example of such class of theories is the unimodular gravity but there are other possibilities like the mimetic gravity and the rastall gravity with a coupling parameter lambda 12 the unimodular gravity proposal is a very interesting approach in other to address the cosmological constant problem when coupled to matter such theories may imply that the energymomentum tensor is not divergence free anymore in this paper a unimodular type theory will be developed by evading the conservation tmunu_ mu0 the cosmological consequences of the later both at background as well as for scalar and tensor perturbations are explored possible further extensions of this approach are discussed as well as its connection with the traditional unimodular gravity
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1,802.01414
A Learning-based Approach to Joint Content Caching and Recommendation at Base Stations
Recommendation system is able to shape user demands, which can be used for boosting caching gain. In this paper, we jointly optimize content caching and recommendation at base stations to maximize the caching gain meanwhile not compromising the user preference. We first propose a model to capture the impact of recommendation on user demands, which is controlled by a user-specific psychological threshold. We then formulate a joint caching and recommendation problem maximizing the successful offloading probability, which is a mixed integer programming problem. We develop a hierarchical iterative algorithm to solve the problem when the threshold is known. Since the user threshold is unknown in practice, we proceed to propose an $\varepsilon$-greedy algorithm to find the solution by learning the threshold via interactions with users. Simulation results show that the proposed algorithms improve the successful offloading probability compared with prior works with/without recommendation. The $\varepsilon$-greedy algorithm learns the user threshold quickly, and achieves more than $1-\varepsilon$ of the performance obtained by the algorithm with known threshold.
cs.NI cs.LG
recommendation system is able to shape user demands which can be used for boosting caching gain in this paper we jointly optimize content caching and recommendation at base stations to maximize the caching gain meanwhile not compromising the user preference we first propose a model to capture the impact of recommendation on user demands which is controlled by a userspecific psychological threshold we then formulate a joint caching and recommendation problem maximizing the successful offloading probability which is a mixed integer programming problem we develop a hierarchical iterative algorithm to solve the problem when the threshold is known since the user threshold is unknown in practice we proceed to propose an varepsilongreedy algorithm to find the solution by learning the threshold via interactions with users simulation results show that the proposed algorithms improve the successful offloading probability compared with prior works withwithout recommendation the varepsilongreedy algorithm learns the user threshold quickly and achieves more than 1varepsilon of the performance obtained by the algorithm with known threshold
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1,802.01415
Big Data Analytics for Wireless and Wired Network Design: A Survey
Currently, the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers, Internet websites, and online services. This trend is continuing to develop in a quick and diverse manner in the form of big data. Big data analytics can process large amounts of raw data and extract useful, smaller-sized information, which can be used by different parties to make reliable decisions. In this paper, we conduct a survey on the role that big data analytics can play in the design of data communication networks. Integrating the latest advances that employ big data analytics with the networks control/traffic layers might be the best way to build robust data communication networks with refined performance and intelligent features. First, the survey starts with the introduction of the big data basic concepts, framework, and characteristics. Second, we illustrate the main network design cycle employing big data analytics. This cycle represents the umbrella concept that unifies the surveyed topics. Third, there is a detailed review of the current academic and industrial efforts toward network design using big data analytics. Forth, we identify the challenges confronting the utilization of big data analytics in network design. Finally, we highlight several future research directions. To the best of our knowledge, this is the first survey that addresses the use of big data analytics techniques for the design of a broad range of networks.
cs.NI stat.ML
currently the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers internet websites and online services this trend is continuing to develop in a quick and diverse manner in the form of big data big data analytics can process large amounts of raw data and extract useful smallersized information which can be used by different parties to make reliable decisions in this paper we conduct a survey on the role that big data analytics can play in the design of data communication networks integrating the latest advances that employ big data analytics with the networks controltraffic layers might be the best way to build robust data communication networks with refined performance and intelligent features first the survey starts with the introduction of the big data basic concepts framework and characteristics second we illustrate the main network design cycle employing big data analytics this cycle represents the umbrella concept that unifies the surveyed topics third there is a detailed review of the current academic and industrial efforts toward network design using big data analytics forth we identify the challenges confronting the utilization of big data analytics in network design finally we highlight several future research directions to the best of our knowledge this is the first survey that addresses the use of big data analytics techniques for the design of a broad range of networks
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1,802.01416
Conditioning of Finite Volume Element Method for Diffusion Problems with General Simplicial Meshes
The conditioning of the linear finite volume element discretization for general diffusion equations is studied on arbitrary simplicial meshes. The condition number is defined as the ratio of the maximal singular value of the stiffness matrix to the minimal eigenvalue of its symmetric part. This definition is motivated by the fact that the convergence rate of the generalized minimal residual method for the corresponding linear systems is determined by the ratio. An upper bound for the ratio is established by developing an upper bound for the maximal singular value and a lower bound for the minimal eigenvalue of the symmetric part. It is shown that the bound depends on three factors, the number of the elements in the mesh, the mesh nonuniformity measured in the Euclidean metric, and the mesh nonuniformity measured in the metric specified by the inverse diffusion matrix. It is also shown that the diagonal scaling can effectively eliminates the effects from the mesh nonuniformity measured in the Euclidean metric. Numerical results for a selection of examples in one, two, and three dimensions are presented.
math.NA
the conditioning of the linear finite volume element discretization for general diffusion equations is studied on arbitrary simplicial meshes the condition number is defined as the ratio of the maximal singular value of the stiffness matrix to the minimal eigenvalue of its symmetric part this definition is motivated by the fact that the convergence rate of the generalized minimal residual method for the corresponding linear systems is determined by the ratio an upper bound for the ratio is established by developing an upper bound for the maximal singular value and a lower bound for the minimal eigenvalue of the symmetric part it is shown that the bound depends on three factors the number of the elements in the mesh the mesh nonuniformity measured in the euclidean metric and the mesh nonuniformity measured in the metric specified by the inverse diffusion matrix it is also shown that the diagonal scaling can effectively eliminates the effects from the mesh nonuniformity measured in the euclidean metric numerical results for a selection of examples in one two and three dimensions are presented
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1,802.01417
Building machine learning force fields for nanoclusters
We assess Gaussian process (GP) regression as a technique to model interatomic forces in metal nanoclusters by analysing the performance of 2-body, 3-body and many-body kernel functions on a set of 19-atom Ni cluster structures. We find that 2-body GP kernels fail to provide faithful force estimates, despite succeeding in bulk Ni systems. However, both 3- and many-body kernels predict forces within a $\sim$0.1 eV/$\text{\AA}$ average error even for small training datasets, and achieve high accuracy even on out-of-sample, high temperature, structures. While training and testing on the same structure always provides satisfactory accuracy, cross-testing on dissimilar structures leads to higher prediction errors, posing an extrapolation problem. This can be cured using heterogeneous training on databases that contain more than one structure, which results in a good trade-off between versatility and overall accuracy. Starting from a 3-body kernel trained this way, we build an efficient non-parametric 3-body force field that allows accurate prediction of structural properties at finite temperatures, following a newly developed scheme [Glielmo et al. PRB 97, 184307 (2018)]. We use this to assess the thermal stability of Ni$_{19}$ nanoclusters at a fractional cost of full ab initio calculations.
physics.comp-ph
we assess gaussian process gp regression as a technique to model interatomic forces in metal nanoclusters by analysing the performance of 2body 3body and manybody kernel functions on a set of 19atom ni cluster structures we find that 2body gp kernels fail to provide faithful force estimates despite succeeding in bulk ni systems however both 3 and manybody kernels predict forces within a sim01 evtextaa average error even for small training datasets and achieve high accuracy even on outofsample high temperature structures while training and testing on the same structure always provides satisfactory accuracy crosstesting on dissimilar structures leads to higher prediction errors posing an extrapolation problem this can be cured using heterogeneous training on databases that contain more than one structure which results in a good tradeoff between versatility and overall accuracy starting from a 3body kernel trained this way we build an efficient nonparametric 3body force field that allows accurate prediction of structural properties at finite temperatures following a newly developed scheme glielmo et al prb 97 184307 2018 we use this to assess the thermal stability of ni_19 nanoclusters at a fractional cost of full ab initio calculations
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1,802.01418
Keplerian shear in ergodic theory
Many integrable physical systems exhibit Keplerian shear. We look at this phenomenon from the point of view of ergodic theory, where it can be seen as mixing conditionally to an invariant $\sigma$-algebra. In this context, we give a sufficient criterion for Keplerian shear to appear in a system, investigate its genericity and, in a few cases, its speed. Some additional, non-Hamiltonian, examples are discussed.
math.DS
many integrable physical systems exhibit keplerian shear we look at this phenomenon from the point of view of ergodic theory where it can be seen as mixing conditionally to an invariant sigmaalgebra in this context we give a sufficient criterion for keplerian shear to appear in a system investigate its genericity and in a few cases its speed some additional nonhamiltonian examples are discussed
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1,802.01419
Exponential functions of finite posets and the number of extensions with a fixed set of minimal points
We establish formulas for the number of all downsets (or equivalently, of all antichains) of a finite poset P. Then, using these numbers, we determine recursively and explicitly the number of all posets having a fixed set of minimal points and inducing the poset P on the non- minimal points. It turns out that these counting functions are closely related to a collection of downset numbers of certain subposets. Since any function of that kind is an exponential sum (with the number of minimal points as exponent), we call it the exponential function of the poset. Some linear equations, divisibility relations, upper and lower bounds, and asymptotical equalities for the counting functions are deduced. A list of all such exponential functions for posets with up to five points concludes the paper.
math.CO
we establish formulas for the number of all downsets or equivalently of all antichains of a finite poset p then using these numbers we determine recursively and explicitly the number of all posets having a fixed set of minimal points and inducing the poset p on the non minimal points it turns out that these counting functions are closely related to a collection of downset numbers of certain subposets since any function of that kind is an exponential sum with the number of minimal points as exponent we call it the exponential function of the poset some linear equations divisibility relations upper and lower bounds and asymptotical equalities for the counting functions are deduced a list of all such exponential functions for posets with up to five points concludes the paper
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1,802.0142
Experimental realization of noise-induced adiabaticity in nuclear magnetic resonance
The adiabatic evolution is the dynamics of an instantaneous eigenstate of a slowly varing Hamiltonian. Recently, an interesting phenomenon shows up that white noises can enhance and even induce adiabaticity, which is in contrast to previous perception that environmental noises always modify and even ruin a designed adiabatic passage. We experimentally realized a noise-induced adiabaticity in a nuclear magnetic resonance system. Adiabatic Hadamard gate and entangled state are demonstrated. The effect of noise on adiabaticity is experimentally exhibited and compared with the noise-free process. We utilized a noise-injected method, which can be applied to other quantum systems.
quant-ph
the adiabatic evolution is the dynamics of an instantaneous eigenstate of a slowly varing hamiltonian recently an interesting phenomenon shows up that white noises can enhance and even induce adiabaticity which is in contrast to previous perception that environmental noises always modify and even ruin a designed adiabatic passage we experimentally realized a noiseinduced adiabaticity in a nuclear magnetic resonance system adiabatic hadamard gate and entangled state are demonstrated the effect of noise on adiabaticity is experimentally exhibited and compared with the noisefree process we utilized a noiseinjected method which can be applied to other quantum systems
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1,802.01421
First-order Adversarial Vulnerability of Neural Networks and Input Dimension
Over the past few years, neural networks were proven vulnerable to adversarial images: targeted but imperceptible image perturbations lead to drastically different predictions. We show that adversarial vulnerability increases with the gradients of the training objective when viewed as a function of the inputs. Surprisingly, vulnerability does not depend on network topology: for many standard network architectures, we prove that at initialization, the $\ell_1$-norm of these gradients grows as the square root of the input dimension, leaving the networks increasingly vulnerable with growing image size. We empirically show that this dimension dependence persists after either usual or robust training, but gets attenuated with higher regularization.
stat.ML cs.CV cs.LG
over the past few years neural networks were proven vulnerable to adversarial images targeted but imperceptible image perturbations lead to drastically different predictions we show that adversarial vulnerability increases with the gradients of the training objective when viewed as a function of the inputs surprisingly vulnerability does not depend on network topology for many standard network architectures we prove that at initialization the ell_1norm of these gradients grows as the square root of the input dimension leaving the networks increasingly vulnerable with growing image size we empirically show that this dimension dependence persists after either usual or robust training but gets attenuated with higher regularization
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1,802.01422
Semiclassical approximation of the Wheeler-DeWitt equation: arbitrary orders and the question of unitarity
We extend the Born-Oppenheimer type of approximation scheme for the Wheeler-DeWitt equation of canonical quantum gravity to arbitrary orders in the inverse Planck mass squared. We discuss in detail the origin of unitarity violation in this scheme and show that unitarity can be restored by an appropriate modification which requires back reaction from matter onto the gravitational sector. In our analysis, we heavily rely on the gauge aspects of the standard Born-Oppenheimer scheme in molecular physics.
gr-qc quant-ph
we extend the bornoppenheimer type of approximation scheme for the wheelerdewitt equation of canonical quantum gravity to arbitrary orders in the inverse planck mass squared we discuss in detail the origin of unitarity violation in this scheme and show that unitarity can be restored by an appropriate modification which requires back reaction from matter onto the gravitational sector in our analysis we heavily rely on the gauge aspects of the standard bornoppenheimer scheme in molecular physics
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1,802.01423
Remarks on the self-shrinking Clifford torus
On the one hand, we prove that the Clifford torus in $\mathbb{C}^2$ is unstable for Lagrangian mean curvature flow under arbitrarily small Hamiltonian perturbations, even though it is Hamiltonian $F$-stable and locally area minimising under Hamiltonian variations. On the other hand, we show that the Clifford torus is rigid: it is locally unique as a self-shrinker for mean curvature flow, despite having infinitesimal deformations which do not arise from rigid motions. The proofs rely on analysing higher order phenomena: specifically, showing that the Clifford torus is not a local entropy minimiser even under Hamiltonian variations, and demonstrating that infinitesimal deformations which do not generate rigid motions are genuinely obstructed.
math.DG math.AP math.SG
on the one hand we prove that the clifford torus in mathbbc2 is unstable for lagrangian mean curvature flow under arbitrarily small hamiltonian perturbations even though it is hamiltonian fstable and locally area minimising under hamiltonian variations on the other hand we show that the clifford torus is rigid it is locally unique as a selfshrinker for mean curvature flow despite having infinitesimal deformations which do not arise from rigid motions the proofs rely on analysing higher order phenomena specifically showing that the clifford torus is not a local entropy minimiser even under hamiltonian variations and demonstrating that infinitesimal deformations which do not generate rigid motions are genuinely obstructed
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1,802.01424
Can Common Crawl reliably track persistent identifier (PID) use over time?
We report here on the results of two studies using two and four monthly web crawls respectively from the Common Crawl (CC) initiative between 2014 and 2017, whose initial goal was to provide empirical evidence for the changing patterns of use of so-called persistent identifiers. This paper focusses on the tooling needed for dealing with CC data, and the problems we found with it. The first study is based on over $10^{12}$ URIs from over $5 * 10^9$ pages crawled in April 2014 and April 2017, the second study adds a further $3 * 10^9$ pages from the April 2015 and April 2016 crawls. We conclude with suggestions on specific actions needed to enable studies based on CC to give reliable longitudinal information.
cs.DL cs.NI
we report here on the results of two studies using two and four monthly web crawls respectively from the common crawl cc initiative between 2014 and 2017 whose initial goal was to provide empirical evidence for the changing patterns of use of socalled persistent identifiers this paper focusses on the tooling needed for dealing with cc data and the problems we found with it the first study is based on over 1012 uris from over 5 109 pages crawled in april 2014 and april 2017 the second study adds a further 3 109 pages from the april 2015 and april 2016 crawls we conclude with suggestions on specific actions needed to enable studies based on cc to give reliable longitudinal information
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1,802.01425
SDN based Control and Management of WLANs in the 3GPP 5G Network
The exponential growth in mobile broadband usage [1] has catalyzed the need for high data rate communication systems. In this regard, activities for standardizing the next generation mobile broadband system, known as the Fifth Generation(5G) system are underway. The 5G system also enables the integration of Institute of Electrical and Electronic Engineers (IEEE) Wireless Local Area Networks (WLANs) for providing cost-effective broadband connectivity. It is therefore imperative to find solutions for control and management of WLANs, while providing seamless inter-working capabilities with the cellular network. In this paper, we propose a novel Software Defined Networking (SDN) based architecture for efficient control and management of IEEE WLANs while providing a mechanism for smooth integration of WLANs within the 5G system.
cs.NI
the exponential growth in mobile broadband usage 1 has catalyzed the need for high data rate communication systems in this regard activities for standardizing the next generation mobile broadband system known as the fifth generation5g system are underway the 5g system also enables the integration of institute of electrical and electronic engineers ieee wireless local area networks wlans for providing costeffective broadband connectivity it is therefore imperative to find solutions for control and management of wlans while providing seamless interworking capabilities with the cellular network in this paper we propose a novel software defined networking sdn based architecture for efficient control and management of ieee wlans while providing a mechanism for smooth integration of wlans within the 5g system
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1,802.01426
Temporal organization of magnetospheric fluctuations unveiled by recurrence patterns in the Dst index
Magnetic storms constitute the most remarkable large-scale phenomena of nonlinear magnetospheric dynamics. Studying the dynamical organization of macroscopic variability in terms of geomagnetic activity index data by means of complexity measures provides a promising approach for identifying the underlying processes and associated time-scales. Here, we apply a suite of characteristics from recurrence quantification analysis (RQA) and recurrence network analysis (RNA) in order to unveil some key nonlinear features of the hourly Disturbance storm-time (Dst) index during periods with magnetic storms and such of normal variability. Our results demonstrate that recurrence-based measures can serve as excellent tracers for changes in the dynamical complexity along non-stationary records of geomagnetic activity. In particular, trapping time (characterizing the typical length of "laminar phases" in the observed dynamics) and recurrence network transitivity (associated with the number of the system's effective dynamical degrees of freedom) allow for a very good discrimination between magnetic storm and quiescence phases. In general, some RQA and RNA characteristics distinguish between storm and non-storm times equally well or even better than other previously considered nonlinear characteristics like Hurst exponent or symbolic dynamics based entropy concepts. Our results point to future potentials of recurrence characteristics for unveiling temporal changes in the dynamical complexity of the magnetosphere.
physics.ao-ph nlin.CD
magnetic storms constitute the most remarkable largescale phenomena of nonlinear magnetospheric dynamics studying the dynamical organization of macroscopic variability in terms of geomagnetic activity index data by means of complexity measures provides a promising approach for identifying the underlying processes and associated timescales here we apply a suite of characteristics from recurrence quantification analysis rqa and recurrence network analysis rna in order to unveil some key nonlinear features of the hourly disturbance stormtime dst index during periods with magnetic storms and such of normal variability our results demonstrate that recurrencebased measures can serve as excellent tracers for changes in the dynamical complexity along nonstationary records of geomagnetic activity in particular trapping time characterizing the typical length of laminar phases in the observed dynamics and recurrence network transitivity associated with the number of the systems effective dynamical degrees of freedom allow for a very good discrimination between magnetic storm and quiescence phases in general some rqa and rna characteristics distinguish between storm and nonstorm times equally well or even better than other previously considered nonlinear characteristics like hurst exponent or symbolic dynamics based entropy concepts our results point to future potentials of recurrence characteristics for unveiling temporal changes in the dynamical complexity of the magnetosphere
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1,802.01427
Electroluminescence pulse shape and electron diffusion in liquid argon measured in a dual-phase TPC
We report the measurement of the longitudinal diffusion constant in liquid argon with the DarkSide-50 dual-phase time projection chamber. The measurement is performed at drift electric fields of 100 V/cm, 150 V/cm, and 200 V/cm using high statistics $^{39}$Ar decays from atmospheric argon. We derive an expression to describe the pulse shape of the electroluminescence signal (S2) in dual-phase TPCs. The derived S2 pulse shape is fit to events from the uppermost portion of the TPC in order to characterize the radial dependence of the signal. The results are provided as inputs to the measurement of the longitudinal diffusion constant DL, which we find to be (4.12 $\pm$ 0.04) cm$^2$/s for a selection of 140keV electron recoil events in 200V/cm drift field and 2.8kV/cm extraction field. To study the systematics of our measurement we examine datasets of varying event energy, field strength, and detector volume yielding a weighted average value for the diffusion constant of (4.09 $\pm$ 0.09) cm$^2$ /s. The measured longitudinal diffusion constant is observed to have an energy dependence, and within the studied energy range the result is systematically lower than other results in the literature.
physics.ins-det
we report the measurement of the longitudinal diffusion constant in liquid argon with the darkside50 dualphase time projection chamber the measurement is performed at drift electric fields of 100 vcm 150 vcm and 200 vcm using high statistics 39ar decays from atmospheric argon we derive an expression to describe the pulse shape of the electroluminescence signal s2 in dualphase tpcs the derived s2 pulse shape is fit to events from the uppermost portion of the tpc in order to characterize the radial dependence of the signal the results are provided as inputs to the measurement of the longitudinal diffusion constant dl which we find to be 412 pm 004 cm2s for a selection of 140kev electron recoil events in 200vcm drift field and 28kvcm extraction field to study the systematics of our measurement we examine datasets of varying event energy field strength and detector volume yielding a weighted average value for the diffusion constant of 409 pm 009 cm2 s the measured longitudinal diffusion constant is observed to have an energy dependence and within the studied energy range the result is systematically lower than other results in the literature
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1,802.01428
Re-thinking non-inferiority: a practical trial design for optimising treatment duration
Background: trials to identify the minimal effective treatment duration are needed in different therapeutic areas, including bacterial infections, TB and Hepatitis--C. However, standard non-inferiority designs have several limitations, including arbitrariness of non-inferiority margins, choice of research arms and very large sample sizes. Methods: we recast the problem of finding an appropriate non-inferior treatment duration in terms of modelling the entire duration-response curve within a pre-specified range. We propose a multi-arm randomised trial design, allocating patients to different treatment durations. We use fractional polynomials and spline-based methods to flexibly model the duration-response curve. We compare different methods in terms of a scaled version of the area between true and estimated prediction curves. We evaluate sensitivity to key design parameters, including sample size, number and position of arms. Results: a total sample size of $\sim 500$ patients divided into a moderate number of equidistant arms (5-7) is sufficient to estimate the duration-response curve within a $5\%$ error margin in $95\%$ of the simulations. Fractional polynomials provide similar or better results than spline-based methods in most scenarios. Conclusions: our proposed practical randomised trial design is an alternative to standard non-inferiority designs, avoiding many of their limitations, and yet being fairly robust to different possible duration-response curves. The trial outcome is the whole duration-response curve, which could be used by clinicians and policy makers to make informed decisions, facilitating a move away from a forced binary hypothesis testing paradigm.
stat.ME
background trials to identify the minimal effective treatment duration are needed in different therapeutic areas including bacterial infections tb and hepatitisc however standard noninferiority designs have several limitations including arbitrariness of noninferiority margins choice of research arms and very large sample sizes methods we recast the problem of finding an appropriate noninferior treatment duration in terms of modelling the entire durationresponse curve within a prespecified range we propose a multiarm randomised trial design allocating patients to different treatment durations we use fractional polynomials and splinebased methods to flexibly model the durationresponse curve we compare different methods in terms of a scaled version of the area between true and estimated prediction curves we evaluate sensitivity to key design parameters including sample size number and position of arms results a total sample size of sim 500 patients divided into a moderate number of equidistant arms 57 is sufficient to estimate the durationresponse curve within a 5 error margin in 95 of the simulations fractional polynomials provide similar or better results than splinebased methods in most scenarios conclusions our proposed practical randomised trial design is an alternative to standard noninferiority designs avoiding many of their limitations and yet being fairly robust to different possible durationresponse curves the trial outcome is the whole durationresponse curve which could be used by clinicians and policy makers to make informed decisions facilitating a move away from a forced binary hypothesis testing paradigm
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1,802.01429
Manuscripts in Time and Space: Experiments in Scriptometrics on an Old French Corpus
Witnesses of medieval literary texts, preserved in manuscript, are layered objects , being almost exclusively copies of copies. This results in multiple and hard to distinguish linguistic strata -- the author's scripta interacting with the scriptae of the various scribes -- in a context where literary written language is already a dialectal hybrid. Moreover, no single linguistic phenomenon allows to distinguish between different scriptae, and only the combination of multiple characteristics is likely to be significant [9] -- but which ones? The most common approach is to search for these features in a set of previously selected texts, that are supposed to be representative of a given scripta. This can induce a circularity, in which texts are used to select features that in turn characterise them as belonging to a linguistic area. To counter this issue, this paper offers an unsupervised and corpus-based approach, in which clustering methods are applied to an Old French corpus to identify main divisions and groups. Ultimately, scriptometric profiles are built for each of them.
cs.CL stat.AP
witnesses of medieval literary texts preserved in manuscript are layered objects being almost exclusively copies of copies this results in multiple and hard to distinguish linguistic strata the authors scripta interacting with the scriptae of the various scribes in a context where literary written language is already a dialectal hybrid moreover no single linguistic phenomenon allows to distinguish between different scriptae and only the combination of multiple characteristics is likely to be significant 9 but which ones the most common approach is to search for these features in a set of previously selected texts that are supposed to be representative of a given scripta this can induce a circularity in which texts are used to select features that in turn characterise them as belonging to a linguistic area to counter this issue this paper offers an unsupervised and corpusbased approach in which clustering methods are applied to an old french corpus to identify main divisions and groups ultimately scriptometric profiles are built for each of them
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1,802.0143
Nonlinear optical response of doped mono- and bilayer graphene: length gauge tight-binding model
We compute the nonlinear optical response of doped mono- and bilayer graphene using the full dispersion based on tight-binding models. The response is derived with the density matrix formalism using the length gauge and is valid for any periodic system, with arbitrary doping. By collecting terms that define effective nonlinear response tensors, we identify all nonlinear Drude-like terms (up to third-order) and show that all additional spurious divergences present in the induced current vanish. The nonlinear response of graphene comprises a large Drude-like divergence and three resonances that are tightly connected with transitions occurring in the vicinity of the Fermi level. The analytic solution derived using the Dirac approximation captures accurately the first- and third-order responses in graphene, even at very high doping levels. The quadratic response of gapped graphene is also strongly enhanced by doping, even for systems with small gaps such as commensurate structures of graphene on SiC. The nonlinear response of bilayer graphene is significantly richer, combining the resonances that stem from doping with its intrinsic strong low-energy resonances.
cond-mat.mes-hall
we compute the nonlinear optical response of doped mono and bilayer graphene using the full dispersion based on tightbinding models the response is derived with the density matrix formalism using the length gauge and is valid for any periodic system with arbitrary doping by collecting terms that define effective nonlinear response tensors we identify all nonlinear drudelike terms up to thirdorder and show that all additional spurious divergences present in the induced current vanish the nonlinear response of graphene comprises a large drudelike divergence and three resonances that are tightly connected with transitions occurring in the vicinity of the fermi level the analytic solution derived using the dirac approximation captures accurately the first and thirdorder responses in graphene even at very high doping levels the quadratic response of gapped graphene is also strongly enhanced by doping even for systems with small gaps such as commensurate structures of graphene on sic the nonlinear response of bilayer graphene is significantly richer combining the resonances that stem from doping with its intrinsic strong lowenergy resonances
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1,802.01431
Topological insulation in a ladder model with particle-hole and reflection symmetries
A two-legged ladder model, one dimensional, exhibiting the parity anomaly is constructed. The model belongs to the $C$ and $CI$ symmetry classes, depending on the parameters, but, due to reflection, it exhibits topological insulation. The model consists of two superimposed Creutz models with onsite potentials. The topological invariants for both cases are {\it mirror winding numbers,} which are nonzero individually in the topological phase, but sum to zero overall in both phases. We demonstrate the presence of edge states and quantized Hall response in the topological region. Our model exhibits two distinct topological regions, distinguished by the different types of reflection symmetries.
cond-mat.str-el cond-mat.mes-hall cond-mat.other
a twolegged ladder model one dimensional exhibiting the parity anomaly is constructed the model belongs to the c and ci symmetry classes depending on the parameters but due to reflection it exhibits topological insulation the model consists of two superimposed creutz models with onsite potentials the topological invariants for both cases are it mirror winding numbers which are nonzero individually in the topological phase but sum to zero overall in both phases we demonstrate the presence of edge states and quantized hall response in the topological region our model exhibits two distinct topological regions distinguished by the different types of reflection symmetries
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1,802.01432
A Class of M\"obius Iterated Function Systems
We give a procedure to produce M\"obius iterated function systems (MIFS) on the unit disc in the complex plane.
math.DS math.CA
we give a procedure to produce mobius iterated function systems mifs on the unit disc in the complex plane
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1,802.01433
Interactive Grounded Language Acquisition and Generalization in a 2D World
We build a virtual agent for learning language in a 2D maze-like world. The agent sees images of the surrounding environment, listens to a virtual teacher, and takes actions to receive rewards. It interactively learns the teacher's language from scratch based on two language use cases: sentence-directed navigation and question answering. It learns simultaneously the visual representations of the world, the language, and the action control. By disentangling language grounding from other computational routines and sharing a concept detection function between language grounding and prediction, the agent reliably interpolates and extrapolates to interpret sentences that contain new word combinations or new words missing from training sentences. The new words are transferred from the answers of language prediction. Such a language ability is trained and evaluated on a population of over 1.6 million distinct sentences consisting of 119 object words, 8 color words, 9 spatial-relation words, and 50 grammatical words. The proposed model significantly outperforms five comparison methods for interpreting zero-shot sentences. In addition, we demonstrate human-interpretable intermediate outputs of the model in the appendix.
cs.CL cs.AI cs.LG
we build a virtual agent for learning language in a 2d mazelike world the agent sees images of the surrounding environment listens to a virtual teacher and takes actions to receive rewards it interactively learns the teachers language from scratch based on two language use cases sentencedirected navigation and question answering it learns simultaneously the visual representations of the world the language and the action control by disentangling language grounding from other computational routines and sharing a concept detection function between language grounding and prediction the agent reliably interpolates and extrapolates to interpret sentences that contain new word combinations or new words missing from training sentences the new words are transferred from the answers of language prediction such a language ability is trained and evaluated on a population of over 16 million distinct sentences consisting of 119 object words 8 color words 9 spatialrelation words and 50 grammatical words the proposed model significantly outperforms five comparison methods for interpreting zeroshot sentences in addition we demonstrate humaninterpretable intermediate outputs of the model in the appendix
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1,802.01434
Invariance and conservation laws of some nonlinear Schrodinger equation with PT-symmetric potentials and inhomogeneous nonlinearity
In this paper, we construct and analyse the symmetries and conservation laws (conserved densities) of a model of a nonlinear Scrodinger equation with PT-symmetric potentials and inhomogeneity.
math-ph math.MP nlin.SI
in this paper we construct and analyse the symmetries and conservation laws conserved densities of a model of a nonlinear scrodinger equation with ptsymmetric potentials and inhomogeneity
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1,802.01435
A Method for Restoring the Training Set Distribution in an Image Classifier
Convolutional Neural Networks are a well-known staple of modern image classification. However, it can be difficult to assess the quality and robustness of such models. Deep models are known to perform well on a given training and estimation set, but can easily be fooled by data that is specifically generated for the purpose. It has been shown that one can produce an artificial example that does not represent the desired class, but activates the network in the desired way. This paper describes a new way of reconstructing a sample from the training set distribution of an image classifier without deep knowledge about the underlying distribution. This enables access to the elements of images that most influence the decision of a convolutional network and to extract meaningful information about the training distribution.
stat.ML cs.AI cs.CV
convolutional neural networks are a wellknown staple of modern image classification however it can be difficult to assess the quality and robustness of such models deep models are known to perform well on a given training and estimation set but can easily be fooled by data that is specifically generated for the purpose it has been shown that one can produce an artificial example that does not represent the desired class but activates the network in the desired way this paper describes a new way of reconstructing a sample from the training set distribution of an image classifier without deep knowledge about the underlying distribution this enables access to the elements of images that most influence the decision of a convolutional network and to extract meaningful information about the training distribution
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1,802.01436
Variational image compression with a scale hyperprior
We describe an end-to-end trainable model for image compression based on variational autoencoders. The model incorporates a hyperprior to effectively capture spatial dependencies in the latent representation. This hyperprior relates to side information, a concept universal to virtually all modern image codecs, but largely unexplored in image compression using artificial neural networks (ANNs). Unlike existing autoencoder compression methods, our model trains a complex prior jointly with the underlying autoencoder. We demonstrate that this model leads to state-of-the-art image compression when measuring visual quality using the popular MS-SSIM index, and yields rate-distortion performance surpassing published ANN-based methods when evaluated using a more traditional metric based on squared error (PSNR). Furthermore, we provide a qualitative comparison of models trained for different distortion metrics.
eess.IV cs.IT math.IT
we describe an endtoend trainable model for image compression based on variational autoencoders the model incorporates a hyperprior to effectively capture spatial dependencies in the latent representation this hyperprior relates to side information a concept universal to virtually all modern image codecs but largely unexplored in image compression using artificial neural networks anns unlike existing autoencoder compression methods our model trains a complex prior jointly with the underlying autoencoder we demonstrate that this model leads to stateoftheart image compression when measuring visual quality using the popular msssim index and yields ratedistortion performance surpassing published annbased methods when evaluated using a more traditional metric based on squared error psnr furthermore we provide a qualitative comparison of models trained for different distortion metrics
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1,802.01437
Transfer-matrix calculations of the effects of tension and torque constraints on DNA-protein interactions
Organization and maintenance of the chromosomal DNA in living cells strongly depends on the DNA interactions with a plethora of DNA-binding proteins. Single-molecule studies show that formation of nucleoprotein complexes on DNA by such proteins is frequently subject to force and torque constraints applied to the DNA. Although the existing experimental techniques allow to exert these type of mechanical constraints on individual DNA biopolymers, their exact effects in regulation of DNA-protein interactions are still not completely understood due to the lack of systematic theoretical methods able to efficiently interpret complex experimental observations. To fill this gap, we have developed a general theoretical framework based on the transfer-matrix calculations that can be used to accurately describe behaviour of DNA-protein interactions under force and torque constraints. Potential applications of the constructed theoretical approach are demonstrated by predicting how these constraints affect the DNA-binding properties of different types of architectural proteins. Obtained results provide important insights into potential physiological functions of mechanical forces in the chromosomal DNA organization by architectural proteins as well as into single-DNA manipulation studies of DNA-protein interactions.
q-bio.BM
organization and maintenance of the chromosomal dna in living cells strongly depends on the dna interactions with a plethora of dnabinding proteins singlemolecule studies show that formation of nucleoprotein complexes on dna by such proteins is frequently subject to force and torque constraints applied to the dna although the existing experimental techniques allow to exert these type of mechanical constraints on individual dna biopolymers their exact effects in regulation of dnaprotein interactions are still not completely understood due to the lack of systematic theoretical methods able to efficiently interpret complex experimental observations to fill this gap we have developed a general theoretical framework based on the transfermatrix calculations that can be used to accurately describe behaviour of dnaprotein interactions under force and torque constraints potential applications of the constructed theoretical approach are demonstrated by predicting how these constraints affect the dnabinding properties of different types of architectural proteins obtained results provide important insights into potential physiological functions of mechanical forces in the chromosomal dna organization by architectural proteins as well as into singledna manipulation studies of dnaprotein interactions
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1,802.01438
Studying Antimatter Gravity with Muonium
The gravitational acceleration of antimatter, gbar, has yet to be directly measured; an unexpected outcome of its measurement could change our understanding of gravity, the universe, and the possibility of a fifth force. Three avenues are apparent for such a measurement: antihydrogen, positronium, and muonium, the last requiring a precision atom interferometer and novel muonium beam under development. The interferometer and its few-picometer alignment and calibration systems appear feasible. With 100 nm grating pitch, measurements of gbar to 10%, 1%, or better can be envisioned. These could constitute the first gravitational measurements of leptonic matter, of 2nd-generation matter, and possibly, of antimatter.
physics.ins-det gr-qc hep-ex nucl-ex physics.atom-ph
the gravitational acceleration of antimatter gbar has yet to be directly measured an unexpected outcome of its measurement could change our understanding of gravity the universe and the possibility of a fifth force three avenues are apparent for such a measurement antihydrogen positronium and muonium the last requiring a precision atom interferometer and novel muonium beam under development the interferometer and its fewpicometer alignment and calibration systems appear feasible with 100 nm grating pitch measurements of gbar to 10 1 or better can be envisioned these could constitute the first gravitational measurements of leptonic matter of 2ndgeneration matter and possibly of antimatter
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1,802.01439
Efficiency of high-performance discontinuous Galerkin spectral element methods for under-resolved turbulent incompressible flows
The present paper addresses the numerical solution of turbulent flows with high-order discontinuous Galerkin methods for discretizing the incompressible Navier-Stokes equations. The efficiency of high-order methods when applied to under-resolved problems is an open issue in literature. This topic is carefully investigated in the present work by the example of the 3D Taylor-Green vortex problem. Our implementation is based on a generic high-performance framework for matrix-free evaluation of finite element operators with one of the best realizations currently known. We present a methodology to systematically analyze the efficiency of the incompressible Navier-Stokes solver for high polynomial degrees. Due to the absence of optimal rates of convergence in the under-resolved regime, our results reveal that demonstrating improved efficiency of high-order methods is a challenging task and that optimal computational complexity of solvers, preconditioners, and matrix-free implementations are necessary ingredients to achieve the goal of better solution quality at the same computational costs already for a geometrically simple problem such as the Taylor-Green vortex. Although the analysis is performed for a Cartesian geometry, our approach is generic and can be applied to arbitrary geometries. We present excellent performance numbers on modern, cache-based computer architectures achieving a throughput for operator evaluation of 3e8 up to 1e9 DoFs/sec on one Intel Haswell node with 28 cores. Compared to performance results published within the last 5 years for high-order DG discretizations of the compressible Navier-Stokes equations, our approach reduces computational costs by more than one order of magnitude for the same setup.
physics.flu-dyn physics.comp-ph
the present paper addresses the numerical solution of turbulent flows with highorder discontinuous galerkin methods for discretizing the incompressible navierstokes equations the efficiency of highorder methods when applied to underresolved problems is an open issue in literature this topic is carefully investigated in the present work by the example of the 3d taylorgreen vortex problem our implementation is based on a generic highperformance framework for matrixfree evaluation of finite element operators with one of the best realizations currently known we present a methodology to systematically analyze the efficiency of the incompressible navierstokes solver for high polynomial degrees due to the absence of optimal rates of convergence in the underresolved regime our results reveal that demonstrating improved efficiency of highorder methods is a challenging task and that optimal computational complexity of solvers preconditioners and matrixfree implementations are necessary ingredients to achieve the goal of better solution quality at the same computational costs already for a geometrically simple problem such as the taylorgreen vortex although the analysis is performed for a cartesian geometry our approach is generic and can be applied to arbitrary geometries we present excellent performance numbers on modern cachebased computer architectures achieving a throughput for operator evaluation of 3e8 up to 1e9 dofssec on one intel haswell node with 28 cores compared to performance results published within the last 5 years for highorder dg discretizations of the compressible navierstokes equations our approach reduces computational costs by more than one order of magnitude for the same setup
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1,802.0144
A Robotic "Social Media" Controlled Observatory for Education and Research
I describe the world's first robotic observatory to interact with its observers entirely using the social media platforms Facebook or Twitter. The telescope "tweets" what it's doing, posts live images, and responds to observer commands through a comprehensive command set. Observation requests are queued and observed by a responsive queue engine. Its architecture, social media based image processing capability and several usage examples are also described.
physics.ed-ph astro-ph.IM
i describe the worlds first robotic observatory to interact with its observers entirely using the social media platforms facebook or twitter the telescope tweets what its doing posts live images and responds to observer commands through a comprehensive command set observation requests are queued and observed by a responsive queue engine its architecture social media based image processing capability and several usage examples are also described
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1,802.01441
Survival amplitude, instantaneous energy and decay rate of an unstable system: Analytical results
We consider a model of a unstable state defined by the truncated Breit-Wigner energy density distribution function. An analytical form of the survival amplitude $a(t)$ of the state considered is found. Our attention is focused on the late time properties of $a(t)$ and on effects generated by the non--exponential behavior of this amplitude in the late time region: In 1957 Khalfin proved that this amplitude tends to zero as $t$ goes to the infinity more slowly than any exponential function of $t$. This effect can be described using a time-dependent decay rate $\gamma(t)$ and then the Khalfin result means that this $\gamma(t)$ is not a constant but at late times it tends to zero as $t$ goes to the infinity. It appears that the energy $E(t)$ of the unstable state behaves similarly: It tends to the minimal energy $E_{min}$ of the system as $t \to \infty$. Within the model considered we find two first leading time dependent elements of late time asymptotic expansions of $E(t)$ and $\gamma (t)$. We discuss also possible implications of such a late time asymptotic properties of $E(t)$ and $\gamma (t)$ and cases where these properties may manifest themselves.
quant-ph gr-qc hep-ph
we consider a model of a unstable state defined by the truncated breitwigner energy density distribution function an analytical form of the survival amplitude at of the state considered is found our attention is focused on the late time properties of at and on effects generated by the nonexponential behavior of this amplitude in the late time region in 1957 khalfin proved that this amplitude tends to zero as t goes to the infinity more slowly than any exponential function of t this effect can be described using a timedependent decay rate gammat and then the khalfin result means that this gammat is not a constant but at late times it tends to zero as t goes to the infinity it appears that the energy et of the unstable state behaves similarly it tends to the minimal energy e_min of the system as t to infty within the model considered we find two first leading time dependent elements of late time asymptotic expansions of et and gamma t we discuss also possible implications of such a late time asymptotic properties of et and gamma t and cases where these properties may manifest themselves
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1,802.01442
A Parameter Version of Forstneri\v{c}'s Splitting Lemma
We construct solution operators to the $\overline{\partial}$-equation that depend continuously on the domain. This is applied to derive a parameter version of Forstneri\v{c}'s splitting lemma: If both the maps and the domains they are defined on vary continuously with a parameter, then the maps obtained from Forstneri\v{c}'s splitting will depend continuously on the parameter as well.
math.CV
we construct solution operators to the overlinepartialequation that depend continuously on the domain this is applied to derive a parameter version of forstnerivcs splitting lemma if both the maps and the domains they are defined on vary continuously with a parameter then the maps obtained from forstnerivcs splitting will depend continuously on the parameter as well
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1,802.01443
Population transfer at exceptional points in spectra of the hydrogen atom in parallel electric and magnetic fields
We study the population transfer between resonance states for a time-dependent loop around exceptional points in spectra of the hydrogen atom in parallel electric and magnetic fields. Exceptional points are well-suited for population transfer mechanisms, since a closed loop around these in parameter space commutes eigenstates. We address the question how shape and duration of the dynamical parameter loop affects the transferred population, in order to optimize the latter. Since the full quantum dynamics of the expansion coefficients is time-consuming, we furthermore present an approximation method, based on a $2\times 2$ matrix.
quant-ph physics.atom-ph
we study the population transfer between resonance states for a timedependent loop around exceptional points in spectra of the hydrogen atom in parallel electric and magnetic fields exceptional points are wellsuited for population transfer mechanisms since a closed loop around these in parameter space commutes eigenstates we address the question how shape and duration of the dynamical parameter loop affects the transferred population in order to optimize the latter since the full quantum dynamics of the expansion coefficients is timeconsuming we furthermore present an approximation method based on a 2times 2 matrix
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1,802.01444
Inverse compton scattered merger-nova: late X-ray counterpart of gravitational wave signals from NS-NS/BH mergers
The recent observations of GW170817 and its electromagnetic (EM) counterparts show that double neutron star mergers could lead to rich and bright EM emissions. Recent numerical simulations suggest that neutron star and neutron star/black hole (NS-NS/BH) mergers would leave behind a central remnant surrounded by a mildly isotropic ejecta. The central remnant could launch a collimated jet and when the jet propagating through the ejecta, a mildly relativistic cocoon would be formed and the interaction between the cocoon and the ambient medium would accelerate electrons via external shock in a wide angle. So that the merger-nova photons (i.e., thermal emission from the ejecta) would be scattered into higher frequency via inverse compton (IC) process when they propagating through the cocoon shocked region. We find that the IC scattered component peaks at X-ray band and it will reach its peak luminosity in order of days (simultaneously with the merger-nova emission). With current X-ray detectors, such a late X-ray component could be detected out to 200 Mpc, depending on the merger remnant properties. It could serve as an important electromagnetic counterpart of gravitational wave signals from NS-NS/BH mergers. Nevertheless, simultaneous detection of such a late X-ray signal and the merger-nova signal could shed light on the cocoon properties and the concrete structure of the jet.
astro-ph.HE
the recent observations of gw170817 and its electromagnetic em counterparts show that double neutron star mergers could lead to rich and bright em emissions recent numerical simulations suggest that neutron star and neutron starblack hole nsnsbh mergers would leave behind a central remnant surrounded by a mildly isotropic ejecta the central remnant could launch a collimated jet and when the jet propagating through the ejecta a mildly relativistic cocoon would be formed and the interaction between the cocoon and the ambient medium would accelerate electrons via external shock in a wide angle so that the mergernova photons ie thermal emission from the ejecta would be scattered into higher frequency via inverse compton ic process when they propagating through the cocoon shocked region we find that the ic scattered component peaks at xray band and it will reach its peak luminosity in order of days simultaneously with the mergernova emission with current xray detectors such a late xray component could be detected out to 200 mpc depending on the merger remnant properties it could serve as an important electromagnetic counterpart of gravitational wave signals from nsnsbh mergers nevertheless simultaneous detection of such a late xray signal and the mergernova signal could shed light on the cocoon properties and the concrete structure of the jet
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1,802.01445
Road Segmentation in SAR Satellite Images with Deep Fully-Convolutional Neural Networks
Remote sensing is extensively used in cartography. As transportation networks grow and change, extracting roads automatically from satellite images is crucial to keep maps up-to-date. Synthetic Aperture Radar satellites can provide high resolution topographical maps. However roads are difficult to identify in these data as they look visually similar to targets such as rivers and railways. Most road extraction methods on Synthetic Aperture Radar images still rely on a prior segmentation performed by classical computer vision algorithms. Few works study the potential of deep learning techniques, despite their successful applications to optical imagery. This letter presents an evaluation of Fully-Convolutional Neural Networks for road segmentation in SAR images. We study the relative performance of early and state-of-the-art networks after carefully enhancing their sensitivity towards thin objects by adding spatial tolerance rules. Our models shows promising results, successfully extracting most of the roads in our test dataset. This shows that, although Fully-Convolutional Neural Networks natively lack efficiency for road segmentation, they are capable of good results if properly tuned. As the segmentation quality does not scale well with the increasing depth of the networks, the design of specialized architectures for roads extraction should yield better performances.
cs.CV
remote sensing is extensively used in cartography as transportation networks grow and change extracting roads automatically from satellite images is crucial to keep maps uptodate synthetic aperture radar satellites can provide high resolution topographical maps however roads are difficult to identify in these data as they look visually similar to targets such as rivers and railways most road extraction methods on synthetic aperture radar images still rely on a prior segmentation performed by classical computer vision algorithms few works study the potential of deep learning techniques despite their successful applications to optical imagery this letter presents an evaluation of fullyconvolutional neural networks for road segmentation in sar images we study the relative performance of early and stateoftheart networks after carefully enhancing their sensitivity towards thin objects by adding spatial tolerance rules our models shows promising results successfully extracting most of the roads in our test dataset this shows that although fullyconvolutional neural networks natively lack efficiency for road segmentation they are capable of good results if properly tuned as the segmentation quality does not scale well with the increasing depth of the networks the design of specialized architectures for roads extraction should yield better performances
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1,802.01446
Lorentz Distributed Noncommutative $F(T,T_G)$ Wormhole Solutions
The aim of this paper is to study static spherically symmetric noncommutative $F(T,T_G)$ wormhole solutions along with Lorentzian distribution. Here, $T$ and $T_G$ are torsion scalar and teleparallel equivalent Gauss-Bonnet term, respectively. We take a particular redshift function and two $F(T,T_G)$ models. We analyze the behavior of shape function and also examine null as well as weak energy conditions graphically. It is concluded that there exist realistic wormhole solutions for both models. We also study the stability of these wormhole solutions through equilibrium condition and found them stable.
gr-qc
the aim of this paper is to study static spherically symmetric noncommutative ftt_g wormhole solutions along with lorentzian distribution here t and t_g are torsion scalar and teleparallel equivalent gaussbonnet term respectively we take a particular redshift function and two ftt_g models we analyze the behavior of shape function and also examine null as well as weak energy conditions graphically it is concluded that there exist realistic wormhole solutions for both models we also study the stability of these wormhole solutions through equilibrium condition and found them stable
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1,802.01447
Mixed-Resolution Image Representation and Compression with Convolutional Neural Networks
In this paper, we propose an end-to-end mixed-resolution image compression framework with convolutional neural networks. Firstly, given one input image, feature description neural network (FDNN) is used to generate a new representation of this image, so that this image representation can be more efficiently compressed by standard codec, as compared to the input image. Furthermore, we use post-processing neural network (PPNN) to remove the coding artifacts caused by quantization of codec. Secondly, low-resolution image representation is adopted for high efficiency compression in terms of most of bit spent by image's structures under low bit-rate. However, more bits should be assigned to image details in the high-resolution, when most of structures have been kept after compression at the high bit-rate. This comes from a fact that the low-resolution image representation can't burden more information than high-resolution representation beyond a certain bit-rate. Finally, to resolve the problem of error back-propagation from the PPNN network to the FDNN network, we introduce to learn a virtual codec neural network to imitate two continuous procedures of standard compression and post-processing. The objective experimental results have demonstrated the proposed method has a large margin improvement, when comparing with several state-of-the-art approaches.
cs.CV
in this paper we propose an endtoend mixedresolution image compression framework with convolutional neural networks firstly given one input image feature description neural network fdnn is used to generate a new representation of this image so that this image representation can be more efficiently compressed by standard codec as compared to the input image furthermore we use postprocessing neural network ppnn to remove the coding artifacts caused by quantization of codec secondly lowresolution image representation is adopted for high efficiency compression in terms of most of bit spent by images structures under low bitrate however more bits should be assigned to image details in the highresolution when most of structures have been kept after compression at the high bitrate this comes from a fact that the lowresolution image representation cant burden more information than highresolution representation beyond a certain bitrate finally to resolve the problem of error backpropagation from the ppnn network to the fdnn network we introduce to learn a virtual codec neural network to imitate two continuous procedures of standard compression and postprocessing the objective experimental results have demonstrated the proposed method has a large margin improvement when comparing with several stateoftheart approaches
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1,802.01448
Hardening Deep Neural Networks via Adversarial Model Cascades
Deep neural networks (DNNs) are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs. Works on securing neural networks against adversarial examples achieve high empirical robustness on simple datasets such as MNIST. However, these techniques are inadequate when empirically tested on complex data sets such as CIFAR-10 and SVHN. Further, existing techniques are designed to target specific attacks and fail to generalize across attacks. We propose the Adversarial Model Cascades (AMC) as a way to tackle the above inadequacies. Our approach trains a cascade of models sequentially where each model is optimized to be robust towards a mixture of multiple attacks. Ultimately, it yields a single model which is secure against a wide range of attacks; namely FGSM, Elastic, Virtual Adversarial Perturbations and Madry. On an average, AMC increases the model's empirical robustness against various attacks simultaneously, by a significant margin (of 6.225% for MNIST, 5.075% for SVHN and 2.65% for CIFAR10). At the same time, the model's performance on non-adversarial inputs is comparable to the state-of-the-art models.
cs.LG cs.CR stat.ML
deep neural networks dnns are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs works on securing neural networks against adversarial examples achieve high empirical robustness on simple datasets such as mnist however these techniques are inadequate when empirically tested on complex data sets such as cifar10 and svhn further existing techniques are designed to target specific attacks and fail to generalize across attacks we propose the adversarial model cascades amc as a way to tackle the above inadequacies our approach trains a cascade of models sequentially where each model is optimized to be robust towards a mixture of multiple attacks ultimately it yields a single model which is secure against a wide range of attacks namely fgsm elastic virtual adversarial perturbations and madry on an average amc increases the models empirical robustness against various attacks simultaneously by a significant margin of 6225 for mnist 5075 for svhn and 265 for cifar10 at the same time the models performance on nonadversarial inputs is comparable to the stateoftheart models
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1,802.01449
Spin-orbit coupling induced magnetic anisotropy and large spin wave gap in $\rm Na Os O_3$
The role of spin-orbit coupling and Hund's rule coupling on magnetic ordering, anisotropy, and excitations are investigated within a minimal three-orbital model for the $5d^3$ compound $\rm Na Os O_3$. Asymmetry between the magnetic moments for the $xy$ and $xz,yz$ orbitals, arising from the hopping asymmetry generated by the $\rm Os O_6$ octahedral tilting and rotation, together with the weak correlation effect, are shown to be crucial for the large SOC induced magnetic anisotropy and spin wave gap observed in this compound. Due to the intrinsic SOC-induced changes in the electronic densities under rotation of the staggered field, their coupling with the orbital energy offset is also found to contribute significantly to the magnetic anisotropy energy.
cond-mat.str-el
the role of spinorbit coupling and hunds rule coupling on magnetic ordering anisotropy and excitations are investigated within a minimal threeorbital model for the 5d3 compound rm na os o_3 asymmetry between the magnetic moments for the xy and xzyz orbitals arising from the hopping asymmetry generated by the rm os o_6 octahedral tilting and rotation together with the weak correlation effect are shown to be crucial for the large soc induced magnetic anisotropy and spin wave gap observed in this compound due to the intrinsic socinduced changes in the electronic densities under rotation of the staggered field their coupling with the orbital energy offset is also found to contribute significantly to the magnetic anisotropy energy
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1,802.0145
Green function for gradient perturbation of unimodal L\'evy processes in the real line
We prove that the Green function of a generator of symmetric unimodal L\'evy processes with the weak lower scaling order bigger than one and the Green function of its gradient perturbations are comparable for bounded $C^{1,1}$ subsets of the real line if the drift function is from an appropriate Kato class.
math.AP math.PR
we prove that the green function of a generator of symmetric unimodal levy processes with the weak lower scaling order bigger than one and the green function of its gradient perturbations are comparable for bounded c11 subsets of the real line if the drift function is from an appropriate kato class
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1,802.01451
Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian
This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to-Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant linguistic phenomena of Slavic languages, which made the annotation process feasible and accurate. Errors in MT outputs were then annotated by two annotators following this taxonomy. Subsequently, we carried out a statistical analysis which showed that the best-performing system (neural) reduces the errors produced by the worst system (pure phrase-based) by more than half (54\%). Moreover, we conducted an additional analysis of agreement errors in which we distinguished between short (phrase-level) and long distance (sentence-level) errors. We discovered that phrase-based MT approaches are of limited use for long distance agreement phenomena, for which neural MT was found to be especially effective.
cs.CL cs.AI
this paper presents a quantitative finegrained manual evaluation approach to comparing the performance of different machine translation mt systems we build upon the wellestablished multidimensional quality metrics mqm error taxonomy and implement a novel method that assesses whether the differences in performance for mqm error types between different mt systems are statistically significant we conduct a case study for englishtocroatian a language direction that involves translating into a morphologically rich language for which we compare three mt systems belonging to different paradigms pure phrasebased factored phrasebased and neural first we design an mqmcompliant error taxonomy tailored to the relevant linguistic phenomena of slavic languages which made the annotation process feasible and accurate errors in mt outputs were then annotated by two annotators following this taxonomy subsequently we carried out a statistical analysis which showed that the bestperforming system neural reduces the errors produced by the worst system pure phrasebased by more than half 54 moreover we conducted an additional analysis of agreement errors in which we distinguished between short phraselevel and long distance sentencelevel errors we discovered that phrasebased mt approaches are of limited use for long distance agreement phenomena for which neural mt was found to be especially effective
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1,802.01452
Optimal Gaussian Metrology for Generic Multimode Interferometric Circuit
Bounds on the ultimate precision attainable in the estimation of a parameter in Gaussian quantum metrology are obtained when the average number of bosonic probes is fixed. We identify the optimal input probe state among generic (mixed in general) Gaussian states with a fixed average number of probe photons for the estimation of a parameter contained in a generic multimode interferometric optical circuit, namely, a passive linear circuit preserving the total number of photons. The optimal Gaussian input state is essentially a single-mode squeezed vacuum, and the ultimate precision is achieved by a homodyne measurement on the single mode. We also reveal the best strategy for the estimation when we are given $L$ identical target circuits and are allowed to apply passive linear controls in between with an arbitrary number of ancilla modes introduced.
quant-ph
bounds on the ultimate precision attainable in the estimation of a parameter in gaussian quantum metrology are obtained when the average number of bosonic probes is fixed we identify the optimal input probe state among generic mixed in general gaussian states with a fixed average number of probe photons for the estimation of a parameter contained in a generic multimode interferometric optical circuit namely a passive linear circuit preserving the total number of photons the optimal gaussian input state is essentially a singlemode squeezed vacuum and the ultimate precision is achieved by a homodyne measurement on the single mode we also reveal the best strategy for the estimation when we are given l identical target circuits and are allowed to apply passive linear controls in between with an arbitrary number of ancilla modes introduced
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1,802.01453
Reducing CMSO Model Checking to Highly Connected Graphs
Given a Counting Monadic Second Order (CMSO) sentence $\psi$, the CMSO$[\psi]$ problem is defined as follows. The input to CMSO$[\psi]$ is a graph $G$, and the objective is to determine whether $G\models \psi$. Our main theorem states that for every CMSO sentence $\psi$, if CMSO$[\psi]$ is solvable in polynomial time on "globally highly connected graphs", then CMSO$[\psi]$ is solvable in polynomial time (on general graphs). We demonstrate the utility of our theorem in the design of parameterized algorithms. Specifically we show that technical problem-specific ingredients of a powerful method for designing parameterized algorithms, recursive understanding, can be replaced by a black-box invocation of our main theorem. We also show that our theorem can be easily deployed to show fixed parameterized tractability of a wide range of problems, where the input is a graph $G$ and the task is to find a connected induced subgraph of $G$ such that "few" vertices in this subgraph have neighbors outside the subgraph, and additionally the subgraph has a CMSO-definable property.
cs.DS cs.CC cs.LO
given a counting monadic second order cmso sentence psi the cmsopsi problem is defined as follows the input to cmsopsi is a graph g and the objective is to determine whether gmodels psi our main theorem states that for every cmso sentence psi if cmsopsi is solvable in polynomial time on globally highly connected graphs then cmsopsi is solvable in polynomial time on general graphs we demonstrate the utility of our theorem in the design of parameterized algorithms specifically we show that technical problemspecific ingredients of a powerful method for designing parameterized algorithms recursive understanding can be replaced by a blackbox invocation of our main theorem we also show that our theorem can be easily deployed to show fixed parameterized tractability of a wide range of problems where the input is a graph g and the task is to find a connected induced subgraph of g such that few vertices in this subgraph have neighbors outside the subgraph and additionally the subgraph has a cmsodefinable property
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1,802.01454
Linear Stability of $f(R,\phi,X)$ Thick Branes: Tensor Perturbations
We explore thick branes in $f(R,\phi,X)$ gravity. We obtain the linear tensor perturbation equation of $f(R,\phi,X)$ branes and show that the branes are stable against the tensor perturbations under the condition of $\frac{\partial f(R,\phi,X)}{\partial R}>0$. In order to obtain thick brane solutions of the fourth-order field equations in this theory, we employ the reconstruction technique. We get exact solutions of the specific $f(R,\phi,X)$ thick brane generated by a non-canonical scalar field. It is shown that the zero mode of the graviton for the thick brane is localized under certain conditions. This implies that the four-dimensional Newtonian potential is recovered on the brane. The effects of the Kaluza-Klein modes of the graviton for the $f(R,\phi,X)$ thick brane are also discussed.
hep-th
we explore thick branes in frphix gravity we obtain the linear tensor perturbation equation of frphix branes and show that the branes are stable against the tensor perturbations under the condition of fracpartial frphixpartial r0 in order to obtain thick brane solutions of the fourthorder field equations in this theory we employ the reconstruction technique we get exact solutions of the specific frphix thick brane generated by a noncanonical scalar field it is shown that the zero mode of the graviton for the thick brane is localized under certain conditions this implies that the fourdimensional newtonian potential is recovered on the brane the effects of the kaluzaklein modes of the graviton for the frphix thick brane are also discussed
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1,802.01455
The value of ultrahigh resolution OCT in dermatology - delineating the dermo-epidermal junction, capillaries in the dermal papillae and vellus hairs
Optical coherence tomography (OCT) imaging of the skin is gaining recognition and is increasingly applied to dermatological research. A key dermatological parameter inferred from an OCT image is the epidermal (Ep) thickness as a thickened Ep can be an indicator of a skin disease. Agreement in the literature on the signal characters of Ep and the subjacent skin layer, the dermis (D), is evident. Ambiguities of the OCT signal interpretation in the literature is however seen for the transition region between the Ep and D, which from histology is known as the dermo-epidermal junction (DEJ); a distinct junction comprised by the lower surface of a single cell layer in epidermis connected to an even thinner basement membrane, attached to the underlying dermis. In this work we investigate the impact of an improved axial and lateral resolution on the applicability of OCT for imaging of the skin. To this goal, OCT images are compared produced by a commercial OCT system and by an in-house built ultrahigh resolution (UHR-) OCT system for dermatology. In 11 healthy volunteers, we investigate the DEJ signal characteristics. We perform a detailed analysis of the dark (low) signal band clearly seen for UHR-OCT in the DEJ region where we, by using a transition function, find the signal transition of axial sub-resolution character, which can be directly attributed to the exact location of DEJ, both in normal (thin/hairy) and glabrous (thick) skin. For selected healthy volunteers, we investigate the dermal papillae and the vellus hairs and identify distinct features that only UHR-OCT can resolve. Differences are seen in tracing hairs of diameter below 20mm, and in imaging the dermal papillae where capillary structures are identified in the hand palm, not previously reported in OCT studies and specifically for glabrous skin not reported in any other in vivo optical imaging studies.
physics.med-ph
optical coherence tomography oct imaging of the skin is gaining recognition and is increasingly applied to dermatological research a key dermatological parameter inferred from an oct image is the epidermal ep thickness as a thickened ep can be an indicator of a skin disease agreement in the literature on the signal characters of ep and the subjacent skin layer the dermis d is evident ambiguities of the oct signal interpretation in the literature is however seen for the transition region between the ep and d which from histology is known as the dermoepidermal junction dej a distinct junction comprised by the lower surface of a single cell layer in epidermis connected to an even thinner basement membrane attached to the underlying dermis in this work we investigate the impact of an improved axial and lateral resolution on the applicability of oct for imaging of the skin to this goal oct images are compared produced by a commercial oct system and by an inhouse built ultrahigh resolution uhr oct system for dermatology in 11 healthy volunteers we investigate the dej signal characteristics we perform a detailed analysis of the dark low signal band clearly seen for uhroct in the dej region where we by using a transition function find the signal transition of axial subresolution character which can be directly attributed to the exact location of dej both in normal thinhairy and glabrous thick skin for selected healthy volunteers we investigate the dermal papillae and the vellus hairs and identify distinct features that only uhroct can resolve differences are seen in tracing hairs of diameter below 20mm and in imaging the dermal papillae where capillary structures are identified in the hand palm not previously reported in oct studies and specifically for glabrous skin not reported in any other in vivo optical imaging studies
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1,802.01456
A strong averaging principle for L\'evy diffusions in foliated spaces with unbounded leaves
This article extends a strong averaging principle for L\'evy diffusions which live on the leaves of a foliated manifold subject to small transversal L\'evy type perturbation to the case of non-compact leaves. The main result states that the existence of $p$-th moments of the foliated L\'evy diffusion for $p\geq 2$ and an ergodic convergence of its coefficients in $L^p$ implies the strong $L^p$ convergence of the fast perturbed motion on the time scale $t/\epsilon$ to the system driven by the averaged coefficients. In order to compensate the non-compactness of the leaves we use an estimate of the dynamical system for each of the increments of the canonical Marcus equation derived in da Costa and Hoegele (2017), the boundedness of the coefficients in $L^p$ and a nonlinear Gronwall-Bihari type estimate. The price for the non-compactness are slower rates of convergence, given as $p$-dependent powers of $\epsilon$ strictly smaller than $1/4$.
math.DS
this article extends a strong averaging principle for levy diffusions which live on the leaves of a foliated manifold subject to small transversal levy type perturbation to the case of noncompact leaves the main result states that the existence of pth moments of the foliated levy diffusion for pgeq 2 and an ergodic convergence of its coefficients in lp implies the strong lp convergence of the fast perturbed motion on the time scale tepsilon to the system driven by the averaged coefficients in order to compensate the noncompactness of the leaves we use an estimate of the dynamical system for each of the increments of the canonical marcus equation derived in da costa and hoegele 2017 the boundedness of the coefficients in lp and a nonlinear gronwallbihari type estimate the price for the noncompactness are slower rates of convergence given as pdependent powers of epsilon strictly smaller than 14
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1,802.01457
Diverse Beam Search for Increased Novelty in Abstractive Summarization
Text summarization condenses a text to a shorter version while retaining the important informations. Abstractive summarization is a recent development that generates new phrases, rather than simply copying or rephrasing sentences within the original text. Recently neural sequence-to-sequence models have achieved good results in the field of abstractive summarization, which opens new possibilities and applications for industrial purposes. However, most practitioners observe that these models still use large parts of the original text in the output summaries, making them often similar to extractive frameworks. To address this drawback, we first introduce a new metric to measure how much of a summary is extracted from the input text. Secondly, we present a novel method, that relies on a diversity factor in computing the neural network loss, to improve the diversity of the summaries generated by any neural abstractive model implementing beam search. Finally, we show that this method not only makes the system less extractive, but also improves the overall rouge score of state-of-the-art methods by at least 2 points.
cs.CL
text summarization condenses a text to a shorter version while retaining the important informations abstractive summarization is a recent development that generates new phrases rather than simply copying or rephrasing sentences within the original text recently neural sequencetosequence models have achieved good results in the field of abstractive summarization which opens new possibilities and applications for industrial purposes however most practitioners observe that these models still use large parts of the original text in the output summaries making them often similar to extractive frameworks to address this drawback we first introduce a new metric to measure how much of a summary is extracted from the input text secondly we present a novel method that relies on a diversity factor in computing the neural network loss to improve the diversity of the summaries generated by any neural abstractive model implementing beam search finally we show that this method not only makes the system less extractive but also improves the overall rouge score of stateoftheart methods by at least 2 points
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1,802.01458
Image denoising with generalized Gaussian mixture model patch priors
Patch priors have become an important component of image restoration. A powerful approach in this category of restoration algorithms is the popular Expected Patch Log-Likelihood (EPLL) algorithm. EPLL uses a Gaussian mixture model (GMM) prior learned on clean image patches as a way to regularize degraded patches. In this paper, we show that a generalized Gaussian mixture model (GGMM) captures the underlying distribution of patches better than a GMM. Even though GGMM is a powerful prior to combine with EPLL, the non-Gaussianity of its components presents major challenges to be applied to a computationally intensive process of image restoration. Specifically, each patch has to undergo a patch classification step and a shrinkage step. These two steps can be efficiently solved with a GMM prior but are computationally impractical when using a GGMM prior. In this paper, we provide approximations and computational recipes for fast evaluation of these two steps, so that EPLL can embed a GGMM prior on an image with more than tens of thousands of patches. Our main contribution is to analyze the accuracy of our approximations based on thorough theoretical analysis. Our evaluations indicate that the GGMM prior is consistently a better fit formodeling image patch distribution and performs better on average in image denoising task.
eess.IV cs.CV math.ST stat.ML stat.TH
patch priors have become an important component of image restoration a powerful approach in this category of restoration algorithms is the popular expected patch loglikelihood epll algorithm epll uses a gaussian mixture model gmm prior learned on clean image patches as a way to regularize degraded patches in this paper we show that a generalized gaussian mixture model ggmm captures the underlying distribution of patches better than a gmm even though ggmm is a powerful prior to combine with epll the nongaussianity of its components presents major challenges to be applied to a computationally intensive process of image restoration specifically each patch has to undergo a patch classification step and a shrinkage step these two steps can be efficiently solved with a gmm prior but are computationally impractical when using a ggmm prior in this paper we provide approximations and computational recipes for fast evaluation of these two steps so that epll can embed a ggmm prior on an image with more than tens of thousands of patches our main contribution is to analyze the accuracy of our approximations based on thorough theoretical analysis our evaluations indicate that the ggmm prior is consistently a better fit formodeling image patch distribution and performs better on average in image denoising task
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1,802.01459
An information model for modular robots: the Hardware Robot Information Model (HRIM)
Today's landscape of robotics is dominated by vertical integration where single vendors develop the final product leading to slow progress, expensive products and customer lock-in. Opposite to this, an horizontal integration would result in a rapid development of cost-effective mass-market products with an additional consumer empowerment. The transition of an industry from vertical integration to horizontal integration is typically catalysed by de facto industry standards that enable a simplified and seamless integration of products. However, in robotics there is currently no leading candidate for a global plug-and-play standard. This paper tackles the problem of incompatibility between robot components that hinder the reconfigurability and flexibility demanded by the robotics industry. Particularly, it presents a model to create plug-and-play robot hardware components. Rather than iteratively evolving previous ontologies, our proposed model answers the needs identified by the industry while facilitating interoperability, measurability and comparability of robotics technology. Our approach differs significantly with the ones presented before as it is hardware-oriented and establishes a clear set of actions towards the integration of this model in real environments and with real manufacturers.
cs.RO
todays landscape of robotics is dominated by vertical integration where single vendors develop the final product leading to slow progress expensive products and customer lockin opposite to this an horizontal integration would result in a rapid development of costeffective massmarket products with an additional consumer empowerment the transition of an industry from vertical integration to horizontal integration is typically catalysed by de facto industry standards that enable a simplified and seamless integration of products however in robotics there is currently no leading candidate for a global plugandplay standard this paper tackles the problem of incompatibility between robot components that hinder the reconfigurability and flexibility demanded by the robotics industry particularly it presents a model to create plugandplay robot hardware components rather than iteratively evolving previous ontologies our proposed model answers the needs identified by the industry while facilitating interoperability measurability and comparability of robotics technology our approach differs significantly with the ones presented before as it is hardwareoriented and establishes a clear set of actions towards the integration of this model in real environments and with real manufacturers
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