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null | {
"abstract": " Predictive models allow subject-specific inference when analyzing disease\nrelated alterations in neuroimaging data. Given a subject's data, inference can\nbe made at two levels: global, i.e. identifiying condition presence for the\nsubject, and local, i.e. detecting condition effect on each individual\nmeasurement extracted from the subject's data. While global inference is widely\nused, local inference, which can be used to form subject-specific effect maps,\nis rarely used because existing models often yield noisy detections composed of\ndispersed isolated islands. In this article, we propose a reconstruction\nmethod, named RSM, to improve subject-specific detections of predictive\nmodeling approaches and in particular, binary classifiers. RSM specifically\naims to reduce noise due to sampling error associated with using a finite\nsample of examples to train classifiers. The proposed method is a wrapper-type\nalgorithm that can be used with different binary classifiers in a diagnostic\nmanner, i.e. without information on condition presence. Reconstruction is posed\nas a Maximum-A-Posteriori problem with a prior model whose parameters are\nestimated from training data in a classifier-specific fashion. Experimental\nevaluation is performed on synthetically generated data and data from the\nAlzheimer's Disease Neuroimaging Initiative (ADNI) database. Results on\nsynthetic data demonstrate that using RSM yields higher detection accuracy\ncompared to using models directly or with bootstrap averaging. Analyses on the\nADNI dataset show that RSM can also improve correlation between\nsubject-specific detections in cortical thickness data and non-imaging markers\nof Alzheimer's Disease (AD), such as the Mini Mental State Examination Score\nand Cerebrospinal Fluid amyloid-$\\beta$ levels. Further reliability studies on\nthe longitudinal ADNI dataset show improvement on detection reliability when\nRSM is used.\n",
"title": "Reconstructing Subject-Specific Effect Maps"
} | null | null | null | null | true | null | 1 | null | Default | null | null |
null | {
"abstract": " Rotation invariance and translation invariance have great values in image\nrecognition tasks. In this paper, we bring a new architecture in convolutional\nneural network (CNN) named cyclic convolutional layer to achieve rotation\ninvariance in 2-D symbol recognition. We can also get the position and\norientation of the 2-D symbol by the network to achieve detection purpose for\nmultiple non-overlap target. Last but not least, this architecture can achieve\none-shot learning in some cases using those invariance.\n",
"title": "Rotation Invariance Neural Network"
} | null | null | null | null | true | null | 2 | null | Default | null | null |
null | {
"abstract": " We introduce and develop the notion of spherical polyharmonics, which are a\nnatural generalisation of spherical harmonics. In particular we study the\ntheory of zonal polyharmonics, which allows us, analogously to zonal harmonics,\nto construct Poisson kernels for polyharmonic functions on the union of rotated\nballs. We find the representation of Poisson kernels and zonal polyharmonics in\nterms of the Gegenbauer polynomials. We show the connection between the\nclassical Poisson kernel for harmonic functions on the ball, Poisson kernels\nfor polyharmonic functions on the union of rotated balls, and the Cauchy-Hua\nkernel for holomorphic functions on the Lie ball.\n",
"title": "Spherical polyharmonics and Poisson kernels for polyharmonic functions"
} | null | null | [
"Mathematics"
]
| null | true | null | 3 | null | Validated | null | null |
null | {
"abstract": " The stochastic Landau--Lifshitz--Gilbert (LLG) equation coupled with the\nMaxwell equations (the so called stochastic MLLG system) describes the creation\nof domain walls and vortices (fundamental objects for the novel nanostructured\nmagnetic memories). We first reformulate the stochastic LLG equation into an\nequation with time-differentiable solutions. We then propose a convergent\n$\\theta$-linear scheme to approximate the solutions of the reformulated system.\nAs a consequence, we prove convergence of the approximate solutions, with no or\nminor conditions on time and space steps (depending on the value of $\\theta$).\nHence, we prove the existence of weak martingale solutions of the stochastic\nMLLG system. Numerical results are presented to show applicability of the\nmethod.\n",
"title": "A finite element approximation for the stochastic Maxwell--Landau--Lifshitz--Gilbert system"
} | null | null | null | null | true | null | 4 | null | Default | null | null |
null | {
"abstract": " Fourier-transform infra-red (FTIR) spectra of samples from 7 plant species\nwere used to explore the influence of preprocessing and feature extraction on\nefficiency of machine learning algorithms. Wavelet Tensor Train (WTT) and\nDiscrete Wavelet Transforms (DWT) were compared as feature extraction\ntechniques for FTIR data of medicinal plants. Various combinations of signal\nprocessing steps showed different behavior when applied to classification and\nclustering tasks. Best results for WTT and DWT found through grid search were\nsimilar, significantly improving quality of clustering as well as\nclassification accuracy for tuned logistic regression in comparison to original\nspectra. Unlike DWT, WTT has only one parameter to be tuned (rank), making it a\nmore versatile and easier to use as a data processing tool in various signal\nprocessing applications.\n",
"title": "Comparative study of Discrete Wavelet Transforms and Wavelet Tensor Train decomposition to feature extraction of FTIR data of medicinal plants"
} | null | null | null | null | true | null | 5 | null | Default | null | null |
null | {
"abstract": " Let $\\Omega \\subset \\mathbb{R}^n$ be a bounded domain satisfying a\nHayman-type asymmetry condition, and let $ D $ be an arbitrary bounded domain\nreferred to as \"obstacle\". We are interested in the behaviour of the first\nDirichlet eigenvalue $ \\lambda_1(\\Omega \\setminus (x+D)) $. First, we prove an\nupper bound on $ \\lambda_1(\\Omega \\setminus (x+D)) $ in terms of the distance\nof the set $ x+D $ to the set of maximum points $ x_0 $ of the first Dirichlet\nground state $ \\phi_{\\lambda_1} > 0 $ of $ \\Omega $. In short, a direct\ncorollary is that if \\begin{equation} \\mu_\\Omega := \\max_{x}\\lambda_1(\\Omega\n\\setminus (x+D)) \\end{equation} is large enough in terms of $ \\lambda_1(\\Omega)\n$, then all maximizer sets $ x+D $ of $ \\mu_\\Omega $ are close to each maximum\npoint $ x_0 $ of $ \\phi_{\\lambda_1} $.\nSecond, we discuss the distribution of $ \\phi_{\\lambda_1(\\Omega)} $ and the\npossibility to inscribe wavelength balls at a given point in $ \\Omega $.\nFinally, we specify our observations to convex obstacles $ D $ and show that\nif $ \\mu_\\Omega $ is sufficiently large with respect to $ \\lambda_1(\\Omega) $,\nthen all maximizers $ x+D $ of $ \\mu_\\Omega $ contain all maximum points $ x_0\n$ of $ \\phi_{\\lambda_1(\\Omega)} $.\n",
"title": "On maximizing the fundamental frequency of the complement of an obstacle"
} | null | null | [
"Mathematics"
]
| null | true | null | 6 | null | Validated | null | null |
null | {
"abstract": " We observed the newly discovered hyperbolic minor planet 1I/`Oumuamua (2017\nU1) on 2017 October 30 with Lowell Observatory's 4.3-m Discovery Channel\nTelescope. From these observations, we derived a partial lightcurve with\npeak-to-trough amplitude of at least 1.2 mag. This lightcurve segment rules out\nrotation periods less than 3 hr and suggests that the period is at least 5 hr.\nOn the assumption that the variability is due to a changing cross section, the\naxial ratio is at least 3:1. We saw no evidence for a coma or tail in either\nindividual images or in a stacked image having an equivalent exposure time of\n9000 s.\n",
"title": "On the rotation period and shape of the hyperbolic asteroid 1I/`Oumuamua (2017) U1 from its lightcurve"
} | null | null | null | null | true | null | 7 | null | Default | null | null |
null | {
"abstract": " The ability of metallic nanoparticles to supply heat to a liquid environment\nunder exposure to an external optical field has attracted growing interest for\nbiomedical applications. Controlling the thermal transport properties at a\nsolid-liquid interface then appears to be particularly relevant. In this work,\nwe address the thermal transport between water and a gold surface coated by a\npolymer layer. Using molecular dynamics simulations, we demonstrate that\nincreasing the polymer density displaces the domain resisting to the heat flow,\nwhile it doesn't affect the final amount of thermal energy released in the\nliquid. This unexpected behavior results from a trade-off established by the\nincreasing polymer density which couples more efficiently with the solid but\ninitiates a counterbalancing resistance with the liquid.\n",
"title": "Adverse effects of polymer coating on heat transport at solid-liquid interface"
} | null | null | null | null | true | null | 8 | null | Default | null | null |
null | {
"abstract": " We model large-scale ($\\approx$2000km) impacts on a Mars-like planet using a\nSmoothed Particle Hydrodynamics code. The effects of material strength and of\nusing different Equations of State on the post-impact material and temperature\ndistributions are investigated. The properties of the ejected material in terms\nof escaping and disc mass are analysed as well. We also study potential\nnumerical effects in the context of density discontinuities and rigid body\nrotation. We find that in the large-scale collision regime considered here\n(with impact velocities of 4km/s), the effect of material strength is\nsubstantial for the post-impact distribution of the temperature and the\nimpactor material, while the influence of the Equation of State is more subtle\nand present only at very high temperatures.\n",
"title": "SPH calculations of Mars-scale collisions: the role of the Equation of State, material rheologies, and numerical effects"
} | null | null | null | null | true | null | 9 | null | Default | null | null |
null | {
"abstract": " Time varying susceptibility of host at individual level due to waning and\nboosting immunity is known to induce rich long-term behavior of disease\ntransmission dynamics. Meanwhile, the impact of the time varying heterogeneity\nof host susceptibility on the shot-term behavior of epidemics is not\nwell-studied, even though the large amount of the available epidemiological\ndata are the short-term epidemics. Here we constructed a parsimonious\nmathematical model describing the short-term transmission dynamics taking into\naccount natural-boosting immunity by reinfection, and obtained the explicit\nsolution for our model. We found that our system show \"the delayed epidemic\",\nthe epidemic takes off after negative slope of the epidemic curve at the\ninitial phase of epidemic, in addition to the common classification in the\nstandard SIR model, i.e., \"no epidemic\" as $\\mathcal{R}_{0}\\leq1$ or normal\nepidemic as $\\mathcal{R}_{0}>1$. Employing the explicit solution we derived the\ncondition for each classification.\n",
"title": "$\\mathcal{R}_{0}$ fails to predict the outbreak potential in the presence of natural-boosting immunity"
} | null | null | null | null | true | null | 10 | null | Default | null | null |
null | {
"abstract": " We present a systematic global sensitivity analysis using the Sobol method\nwhich can be utilized to rank the variables that affect two quantity of\ninterests -- pore pressure depletion and stress change -- around a\nhydraulically-fractured horizontal well based on their degree of importance.\nThese variables include rock properties and stimulation design variables. A\nfully-coupled poroelastic hydraulic fracture model is used to account for pore\npressure and stress changes due to production. To ease the computational cost\nof a simulator, we also provide reduced order models (ROMs), which can be used\nto replace the complex numerical model with a rather simple analytical model,\nfor calculating the pore pressure and stresses at different locations around\nhydraulic fractures. The main findings of this research are: (i) mobility,\nproduction pressure, and fracture half-length are the main contributors to the\nchanges in the quantities of interest. The percentage of the contribution of\neach parameter depends on the location with respect to pre-existing hydraulic\nfractures and the quantity of interest. (ii) As the time progresses, the effect\nof mobility decreases and the effect of production pressure increases. (iii)\nThese two variables are also dominant for horizontal stresses at large\ndistances from hydraulic fractures. (iv) At zones close to hydraulic fracture\ntips or inside the spacing area, other parameters such as fracture spacing and\nhalf-length are the dominant factors that affect the minimum horizontal stress.\nThe results of this study will provide useful guidelines for the stimulation\ndesign of legacy wells and secondary operations such as refracturing and infill\ndrilling.\n",
"title": "A global sensitivity analysis and reduced order models for hydraulically-fractured horizontal wells"
} | null | null | null | null | true | null | 11 | null | Default | null | null |
null | {
"abstract": " \"Three is a crowd\" is an old proverb that applies as much to social\ninteractions, as it does to frustrated configurations in statistical physics\nmodels. Accordingly, social relations within a triangle deserve special\nattention. With this motivation, we explore the impact of topological\nfrustration on the evolutionary dynamics of the snowdrift game on a triangular\nlattice. This topology provides an irreconcilable frustration, which prevents\nanti-coordination of competing strategies that would be needed for an optimal\noutcome of the game. By using different strategy updating protocols, we observe\ncomplex spatial patterns in dependence on payoff values that are reminiscent to\na honeycomb-like organization, which helps to minimize the negative consequence\nof the topological frustration. We relate the emergence of these patterns to\nthe microscopic dynamics of the evolutionary process, both by means of\nmean-field approximations and Monte Carlo simulations. For comparison, we also\nconsider the same evolutionary dynamics on the square lattice, where of course\nthe topological frustration is absent. However, with the deletion of diagonal\nlinks of the triangular lattice, we can gradually bridge the gap to the square\nlattice. Interestingly, in this case the level of cooperation in the system is\na direct indicator of the level of topological frustration, thus providing a\nmethod to determine frustration levels in an arbitrary interaction network.\n",
"title": "Role-separating ordering in social dilemmas controlled by topological frustration"
} | null | null | null | null | true | null | 12 | null | Default | null | null |
null | {
"abstract": " We study the exciton magnetic polaron (EMP) formation in (Cd,Mn)Se/(Cd,Mg)Se\ndiluted-magnetic-semiconductor quantum wells using time-resolved\nphotoluminescence (PL). The magnetic field and temperature dependencies of this\ndynamics allow us to separate the non-magnetic and magnetic contributions to\nthe exciton localization. We deduce the EMP energy of 14 meV, which is in\nagreement with time-integrated measurements based on selective excitation and\nthe magnetic field dependence of the PL circular polarization degree. The\npolaron formation time of 500 ps is significantly longer than the corresponding\nvalues reported earlier. We propose that this behavior is related to strong\nself-localization of the EMP, accompanied with a squeezing of the heavy-hole\nenvelope wavefunction. This conclusion is also supported by the decrease of the\nexciton lifetime from 600 ps to 200 - 400 ps with increasing magnetic field and\ntemperature.\n",
"title": "Dynamics of exciton magnetic polarons in CdMnSe/CdMgSe quantum wells: the effect of self-localization"
} | null | null | null | null | true | null | 13 | null | Default | null | null |
null | {
"abstract": " The classical Eilenberg correspondence, based on the concept of the syntactic\nmonoid, relates varieties of regular languages with pseudovarieties of finite\nmonoids. Various modifications of this correspondence appeared, with more\ngeneral classes of regular languages on one hand and classes of more complex\nalgebraic structures on the other hand. For example, classes of languages need\nnot be closed under complementation or all preimages under homomorphisms, while\nmonoids can be equipped with a compatible order or they can have a\ndistinguished set of generators. Such generalized varieties and pseudovarieties\nalso have natural counterparts formed by classes of finite (ordered) automata.\nIn this paper the previous approaches are combined. The notion of positive\n$\\mathcal C$-varieties of ordered semiautomata (i.e. no initial and final\nstates are specified) is introduced and their correspondence with positive\n$\\mathcal C$-varieties of languages is proved.\n",
"title": "On Varieties of Ordered Automata"
} | null | null | null | null | true | null | 14 | null | Default | null | null |
null | {
"abstract": " Using low-temperature Magnetic Force Microscopy (MFM) we provide direct\nexperimental evidence for spontaneous vortex phase (SVP) formation in\nEuFe$_2$(As$_{0.79}$P$_{0.21}$)$_2$ single crystal with the superconducting\n$T^{\\rm 0}_{\\rm SC}=23.6$~K and ferromagnetic $T_{\\rm FM}\\sim17.7$~K transition\ntemperatures. Spontaneous vortex-antivortex (V-AV) pairs are imaged in the\nvicinity of $T_{\\rm FM}$. Also, upon cooling cycle near $T_{\\rm FM}$ we observe\nthe first-order transition from the short period domain structure, which\nappears in the Meissner state, into the long period domain structure with\nspontaneous vortices. It is the first experimental observation of this scenario\nin the ferromagnetic superconductors. Low-temperature phase is characterized by\nmuch larger domains in V-AV state and peculiar branched striped structures at\nthe surface, which are typical for uniaxial ferromagnets with perpendicular\nmagnetic anisotropy (PMA). The domain wall parameters at various temperatures\nare estimated.\n",
"title": "Direct Evidence of Spontaneous Abrikosov Vortex State in Ferromagnetic Superconductor EuFe$_2$(As$_{1-x}$P$_x$)$_2$ with $x=0.21$"
} | null | null | null | null | true | null | 15 | null | Default | null | null |
null | {
"abstract": " The recent discovery that the exponent of matrix multiplication is determined\nby the rank of the symmetrized matrix multiplication tensor has invigorated\ninterest in better understanding symmetrized matrix multiplication. I present\nan explicit rank 18 Waring decomposition of $sM_{\\langle 3\\rangle}$ and\ndescribe its symmetry group.\n",
"title": "A rank 18 Waring decomposition of $sM_{\\langle 3\\rangle}$ with 432 symmetries"
} | null | null | null | null | true | null | 16 | null | Default | null | null |
null | {
"abstract": " The process that leads to the formation of the bright star forming sites\nobserved along prominent spiral arms remains elusive. We present results of a\nmulti-wavelength study of a spiral arm segment in the nearby grand-design\nspiral galaxy M51 that belongs to a spiral density wave and exhibits nine gas\nspurs. The combined observations of the(ionized, atomic, molecular, dusty)\ninterstellar medium (ISM) with star formation tracers (HII regions, young\n<10Myr stellar clusters) suggest (1) no variation in giant molecular cloud\n(GMC) properties between arm and gas spurs, (2) gas spurs and extinction\nfeathers arising from the same structure with a close spatial relation between\ngas spurs and ongoing/recent star formation (despite higher gas surface\ndensities in the spiral arm), (3) no trend in star formation age either along\nthe arm or along a spur, (4) evidence for strong star formation feedback in gas\nspurs: (5) tentative evidence for star formation triggered by stellar feedback\nfor one spur, and (6) GMC associations (GMAs) being no special entities but the\nresult of blending of gas arm/spur cross-sections in lower resolution\nobservations. We conclude that there is no evidence for a coherent star\nformation onset mechanism that can be solely associated to the presence of the\nspiral density wave. This suggests that other (more localized) mechanisms are\nimportant to delay star formation such that it occurs in spurs. The evidence of\nstar formation proceeding over several million years within individual spurs\nimplies that the mechanism that leads to star formation acts or is sustained\nover a longer time-scale.\n",
"title": "The PdBI Arcsecond Whirlpool Survey (PAWS). The Role of Spiral Arms in Cloud and Star Formation"
} | null | null | [
"Physics"
]
| null | true | null | 17 | null | Validated | null | null |
null | {
"abstract": " We describe a variant construction of the unstable Adams spectral the\nsequence for a space $Y$, associated to any free simplicial resolution of\n$H^*(Y;R)$ for $R=\\mathbb{F}_p$ or $\\mathbb{Q}$. We use this construction to\ndescribe the differentials and filtration in the spectral sequence in terms of\nappropriate systems of higher cohomology operations.\n",
"title": "Higher structure in the unstable Adams spectral sequence"
} | null | null | null | null | true | null | 18 | null | Default | null | null |
null | {
"abstract": " When investigators seek to estimate causal effects, they often assume that\nselection into treatment is based only on observed covariates. Under this\nidentification strategy, analysts must adjust for observed confounders. While\nbasic regression models have long been the dominant method of statistical\nadjustment, more robust methods based on matching or weighting have become more\ncommon. Of late, even more flexible methods based on machine learning methods\nhave been developed for statistical adjustment. These machine learning methods\nare designed to be black box methods with little input from the researcher.\nRecent research used a data competition to evaluate various methods of\nstatistical adjustment and found that black box methods out performed all other\nmethods of statistical adjustment. Matching methods with covariate\nprioritization are designed for direct input from substantive investigators in\ndirect contrast to black methods. In this article, we use a different research\ndesign to compare matching with covariate prioritization to black box methods.\nWe use black box methods to replicate results from five studies where matching\nwith covariate prioritization was used to customize the statistical adjustment\nin direct response to substantive expertise. We find little difference across\nthe methods. We conclude with advice for investigators.\n",
"title": "Comparing Covariate Prioritization via Matching to Machine Learning Methods for Causal Inference using Five Empirical Applications"
} | null | null | null | null | true | null | 19 | null | Default | null | null |
null | {
"abstract": " Assigning homogeneous boundary conditions, such as acoustic impedance, to the\nthermoviscous wave equations (TWE) derived by transforming the linearized\nNavier-Stokes equations (LNSE) to the frequency domain yields a so-called\nHelmholtz solver, whose output is a discrete set of complex eigenfunction and\neigenvalue pairs. The proposed method -- the inverse Helmholtz solver (iHS) --\nreverses such procedure by returning the value of acoustic impedance at one or\nmore unknown impedance boundaries (IBs) of a given domain via spatial\nintegration of the TWE for a given real-valued frequency with assigned\nconditions on other boundaries. The iHS procedure is applied to a second-order\nspatial discretization of the TWEs derived on an unstructured grid with\nstaggered grid arrangement. The momentum equation only is extended to the\ncenter of each IB face where pressure and velocity components are co-located\nand treated as unknowns. One closure condition considered for the iHS is the\nassignment of the surface gradient of pressure phase over the IBs,\ncorresponding to assigning the shape of the acoustic waveform at the IB. The\niHS procedure is carried out independently for each frequency in order to\nreturn the complete broadband complex impedance distribution at the IBs in any\ndesired frequency range. The iHS approach is first validated against Rott's\ntheory for both inviscid and viscous, rectangular and circular ducts. The\nimpedance of a geometrically complex toy cavity is then reconstructed and\nverified against companion full compressible unstructured Navier-Stokes\nsimulations resolving the cavity geometry and one-dimensional impedance test\ntube calculations based on time-domain impedance boundary conditions (TDIBC).\nThe iHS methodology is also shown to capture thermoacoustic effects, with\nreconstructed impedance values quantitatively in agreement with thermoacoustic\ngrowth rates.\n",
"title": "Acoustic Impedance Calculation via Numerical Solution of the Inverse Helmholtz Problem"
} | null | null | null | null | true | null | 20 | null | Default | null | null |
null | {
"abstract": " The impact of random fluctuations on the dynamical behavior a complex\nbiological systems is a longstanding issue, whose understanding would shed\nlight on the evolutionary pressure that nature imposes on the intrinsic noise\nlevels and would allow rationally designing synthetic networks with controlled\nnoise. Using the Itō stochastic differential equation formalism, we performed\nboth analytic and numerical analyses of several model systems containing\ndifferent molecular species in contact with the environment and interacting\nwith each other through mass-action kinetics. These systems represent for\nexample biomolecular oligomerization processes, complex-breakage reactions,\nsignaling cascades or metabolic networks. For chemical reaction networks with\nzero deficiency values, which admit a detailed- or complex-balanced steady\nstate, all molecular species are uncorrelated. The number of molecules of each\nspecies follow a Poisson distribution and their Fano factors, which measure the\nintrinsic noise, are equal to one. Systems with deficiency one have an\nunbalanced non-equilibrium steady state and a non-zero S-flux, defined as the\nflux flowing between the complexes multiplied by an adequate stoichiometric\ncoefficient. In this case, the noise on each species is reduced if the flux\nflows from the species of lowest to highest complexity, and is amplified is the\nflux goes in the opposite direction. These results are generalized to systems\nof deficiency two, which possess two independent non-vanishing S-fluxes, and we\nconjecture that a similar relation holds for higher deficiency systems.\n",
"title": "Deciphering noise amplification and reduction in open chemical reaction networks"
} | null | null | null | null | true | null | 21 | null | Default | null | null |
null | {
"abstract": " Rare regions with weak disorder (Griffiths regions) have the potential to\nspoil localization. We describe a non-perturbative construction of local\nintegrals of motion (LIOMs) for a weakly interacting spin chain in one\ndimension, under a physically reasonable assumption on the statistics of\neigenvalues. We discuss ideas about the situation in higher dimensions, where\none can no longer ensure that interactions involving the Griffiths regions are\nmuch smaller than the typical energy-level spacing for such regions. We argue\nthat ergodicity is restored in dimension d > 1, although equilibration should\nbe extremely slow, similar to the dynamics of glasses.\n",
"title": "Many-Body Localization: Stability and Instability"
} | null | null | null | null | true | null | 22 | null | Default | null | null |
null | {
"abstract": " The Fault Detection and Isolation Tools (FDITOOLS) is a collection of MATLAB\nfunctions for the analysis and solution of fault detection and model detection\nproblems. The implemented functions are based on the computational procedures\ndescribed in the Chapters 5, 6 and 7 of the book: \"A. Varga, Solving Fault\nDiagnosis Problems - Linear Synthesis Techniques, Springer, 2017\". This\ndocument is the User's Guide for the version V1.0 of FDITOOLS. First, we\npresent the mathematical background for solving several basic exact and\napproximate synthesis problems of fault detection filters and model detection\nfilters. Then, we give in-depth information on the command syntax of the main\nanalysis and synthesis functions. Several examples illustrate the use of the\nmain functions of FDITOOLS.\n",
"title": "Fault Detection and Isolation Tools (FDITOOLS) User's Guide"
} | null | null | null | null | true | null | 23 | null | Default | null | null |
null | {
"abstract": " Detectability of discrete event systems (DESs) is a question whether the\ncurrent and subsequent states can be determined based on observations. Shu and\nLin designed a polynomial-time algorithm to check strong (periodic)\ndetectability and an exponential-time (polynomial-space) algorithm to check\nweak (periodic) detectability. Zhang showed that checking weak (periodic)\ndetectability is PSpace-complete. This intractable complexity opens a question\nwhether there are structurally simpler DESs for which the problem is tractable.\nIn this paper, we show that it is not the case by considering DESs represented\nas deterministic finite automata without non-trivial cycles, which are\nstructurally the simplest deadlock-free DESs. We show that even for such very\nsimple DESs, checking weak (periodic) detectability remains intractable. On the\ncontrary, we show that strong (periodic) detectability of DESs can be\nefficiently verified on a parallel computer.\n",
"title": "Complexity of Deciding Detectability in Discrete Event Systems"
} | null | null | null | null | true | null | 24 | null | Default | null | null |
null | {
"abstract": " Let $X$ be a partially ordered set with the property that each family of\norder intervals of the form $[a,b],[a,\\rightarrow )$ with the finite\nintersection property has a nonempty intersection. We show that every directed\nsubset of $X$ has a supremum. Then we apply the above result to prove that if\n$X$ is a topological space with a partial order $\\preceq $ for which the order\nintervals are compact, $\\mathcal{F}$ a nonempty commutative family of monotone\nmaps from $X$ into $X$ and there exists $c\\in X$ such that $c\\preceq Tc$ for\nevery $T\\in \\mathcal{F}$, then the set of common fixed points of $\\mathcal{F}$\nis nonempty and has a maximal element. The result, specialized to the case of\nBanach spaces gives a general fixed point theorem that drops almost all\nassumptions from the recent results in this area. An application to the theory\nof integral equations of Urysohn's type is also given.\n",
"title": "The Knaster-Tarski theorem versus monotone nonexpansive mappings"
} | null | null | null | null | true | null | 25 | null | Default | null | null |
null | {
"abstract": " Efficient methods are proposed, for computing integrals appeaing in\nelectronic structure calculations. The methods consist of two parts: the first\npart is to represent the integrals as contour integrals and the second one is\nto evaluate the contour integrals by the Clenshaw-Curtis quadrature. The\nefficiency of the proposed methods is demonstrated through numerical\nexperiments.\n",
"title": "Efficient methods for computing integrals in electronic structure calculations"
} | null | null | null | null | true | null | 26 | null | Default | null | null |
null | {
"abstract": " We present a novel sound localization algorithm for a non-line-of-sight\n(NLOS) sound source in indoor environments. Our approach exploits the\ndiffraction properties of sound waves as they bend around a barrier or an\nobstacle in the scene. We combine a ray tracing based sound propagation\nalgorithm with a Uniform Theory of Diffraction (UTD) model, which simulate\nbending effects by placing a virtual sound source on a wedge in the\nenvironment. We precompute the wedges of a reconstructed mesh of an indoor\nscene and use them to generate diffraction acoustic rays to localize the 3D\nposition of the source. Our method identifies the convergence region of those\ngenerated acoustic rays as the estimated source position based on a particle\nfilter. We have evaluated our algorithm in multiple scenarios consisting of a\nstatic and dynamic NLOS sound source. In our tested cases, our approach can\nlocalize a source position with an average accuracy error, 0.7m, measured by\nthe L2 distance between estimated and actual source locations in a 7m*7m*3m\nroom. Furthermore, we observe 37% to 130% improvement in accuracy over a\nstate-of-the-art localization method that does not model diffraction effects,\nespecially when a sound source is not visible to the robot.\n",
"title": "Diffraction-Aware Sound Localization for a Non-Line-of-Sight Source"
} | null | null | null | null | true | null | 27 | null | Default | null | null |
null | {
"abstract": " In this paper we introduce the notion of $\\zeta$-crossbreeding in a set of\n$\\zeta$-factorization formulas and also the notion of complete hybrid formula\nas the final result of that crossbreeding. The last formula is used as a\ncriterion for selection of families of $\\zeta$-kindred elements in class of\nreal continuous functions.\nDedicated to recalling of Gregory Mendel's pea-crossbreeding.\n",
"title": "Jacob's ladders, crossbreeding in the set of $ζ$-factorization formulas and selection of families of $ζ$-kindred real continuous functions"
} | null | null | null | null | true | null | 28 | null | Default | null | null |
null | {
"abstract": " We consider the problem of estimating the $L_1$ distance between two discrete\nprobability measures $P$ and $Q$ from empirical data in a nonasymptotic and\nlarge alphabet setting. When $Q$ is known and one obtains $n$ samples from $P$,\nwe show that for every $Q$, the minimax rate-optimal estimator with $n$ samples\nachieves performance comparable to that of the maximum likelihood estimator\n(MLE) with $n\\ln n$ samples. When both $P$ and $Q$ are unknown, we construct\nminimax rate-optimal estimators whose worst case performance is essentially\nthat of the known $Q$ case with $Q$ being uniform, implying that $Q$ being\nuniform is essentially the most difficult case. The \\emph{effective sample size\nenlargement} phenomenon, identified in Jiao \\emph{et al.} (2015), holds both in\nthe known $Q$ case for every $Q$ and the $Q$ unknown case. However, the\nconstruction of optimal estimators for $\\|P-Q\\|_1$ requires new techniques and\ninsights beyond the approximation-based method of functional estimation in Jiao\n\\emph{et al.} (2015).\n",
"title": "Minimax Estimation of the $L_1$ Distance"
} | null | null | null | null | true | null | 29 | null | Default | null | null |
null | {
"abstract": " We investigate the density large deviation function for a multidimensional\nconservation law in the vanishing viscosity limit, when the probability\nconcentrates on weak solutions of a hyperbolic conservation law conservation\nlaw. When the conductivity and dif-fusivity matrices are proportional, i.e. an\nEinstein-like relation is satisfied, the problem has been solved in [4]. When\nthis proportionality does not hold, we compute explicitly the large deviation\nfunction for a step-like density profile, and we show that the associated\noptimal current has a non trivial structure. We also derive a lower bound for\nthe large deviation function, valid for a general weak solution, and leave the\ngeneral large deviation function upper bound as a conjecture.\n",
"title": "Density large deviations for multidimensional stochastic hyperbolic conservation laws"
} | null | null | null | null | true | null | 30 | null | Default | null | null |
null | {
"abstract": " Large deep neural networks are powerful, but exhibit undesirable behaviors\nsuch as memorization and sensitivity to adversarial examples. In this work, we\npropose mixup, a simple learning principle to alleviate these issues. In\nessence, mixup trains a neural network on convex combinations of pairs of\nexamples and their labels. By doing so, mixup regularizes the neural network to\nfavor simple linear behavior in-between training examples. Our experiments on\nthe ImageNet-2012, CIFAR-10, CIFAR-100, Google commands and UCI datasets show\nthat mixup improves the generalization of state-of-the-art neural network\narchitectures. We also find that mixup reduces the memorization of corrupt\nlabels, increases the robustness to adversarial examples, and stabilizes the\ntraining of generative adversarial networks.\n",
"title": "mixup: Beyond Empirical Risk Minimization"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 31 | null | Validated | null | null |
null | {
"abstract": " In 1978 Brakke introduced the mean curvature flow in the setting of geometric\nmeasure theory. There exist multiple variants of the original definition. Here\nwe prove that most of them are indeed equal. One central point is to correct\nthe proof of Brakke's §3.5, where he develops an estimate for the evolution\nof the measure of time-dependent test functions.\n",
"title": "Equality of the usual definitions of Brakke flow"
} | null | null | null | null | true | null | 32 | null | Default | null | null |
null | {
"abstract": " With recent advancements in drone technology, researchers are now considering\nthe possibility of deploying small cells served by base stations mounted on\nflying drones. A major advantage of such drone small cells is that the\noperators can quickly provide cellular services in areas of urgent demand\nwithout having to pre-install any infrastructure. Since the base station is\nattached to the drone, technically it is feasible for the base station to\ndynamic reposition itself in response to the changing locations of users for\nreducing the communication distance, decreasing the probability of signal\nblocking, and ultimately increasing the spectral efficiency. In this paper, we\nfirst propose distributed algorithms for autonomous control of drone movements,\nand then model and analyse the spectral efficiency performance of a drone small\ncell to shed new light on the fundamental benefits of dynamic repositioning. We\nshow that, with dynamic repositioning, the spectral efficiency of drone small\ncells can be increased by nearly 100\\% for realistic drone speed, height, and\nuser traffic model and without incurring any major increase in drone energy\nconsumption.\n",
"title": "Dynamic Base Station Repositioning to Improve Spectral Efficiency of Drone Small Cells"
} | null | null | null | null | true | null | 33 | null | Default | null | null |
null | {
"abstract": " Electronic health records (EHR) contain a large variety of information on the\nclinical history of patients such as vital signs, demographics, diagnostic\ncodes and imaging data. The enormous potential for discovery in this rich\ndataset is hampered by its complexity and heterogeneity.\nWe present the first study to assess unsupervised homogenization pipelines\ndesigned for EHR clustering. To identify the optimal pipeline, we tested\naccuracy on simulated data with varying amounts of redundancy, heterogeneity,\nand missingness. We identified two optimal pipelines: 1) Multiple Imputation by\nChained Equations (MICE) combined with Local Linear Embedding; and 2) MICE,\nZ-scoring, and Deep Autoencoders.\n",
"title": "An Unsupervised Homogenization Pipeline for Clustering Similar Patients using Electronic Health Record Data"
} | null | null | [
"Quantitative Biology"
]
| null | true | null | 34 | null | Validated | null | null |
null | {
"abstract": " Artificial Neural Network computation relies on intensive vector-matrix\nmultiplications. Recently, the emerging nonvolatile memory (NVM) crossbar array\nshowed a feasibility of implementing such operations with high energy\nefficiency, thus there are many works on efficiently utilizing emerging NVM\ncrossbar array as analog vector-matrix multiplier. However, its nonlinear I-V\ncharacteristics restrain critical design parameters, such as the read voltage\nand weight range, resulting in substantial accuracy loss. In this paper,\ninstead of optimizing hardware parameters to a given neural network, we propose\na methodology of reconstructing a neural network itself optimized to resistive\nmemory crossbar arrays. To verify the validity of the proposed method, we\nsimulated various neural network with MNIST and CIFAR-10 dataset using two\ndifferent specific Resistive Random Access Memory (RRAM) model. Simulation\nresults show that our proposed neural network produces significantly higher\ninference accuracies than conventional neural network when the synapse devices\nhave nonlinear I-V characteristics.\n",
"title": "Deep Neural Network Optimized to Resistive Memory with Nonlinear Current-Voltage Characteristics"
} | null | null | [
"Computer Science"
]
| null | true | null | 35 | null | Validated | null | null |
null | {
"abstract": " In this work, we establish a full single-letter characterization of the\nrate-distortion region of an instance of the Gray-Wyner model with side\ninformation at the decoders. Specifically, in this model an encoder observes a\npair of memoryless, arbitrarily correlated, sources $(S^n_1,S^n_2)$ and\ncommunicates with two receivers over an error-free rate-limited link of\ncapacity $R_0$, as well as error-free rate-limited individual links of\ncapacities $R_1$ to the first receiver and $R_2$ to the second receiver. Both\nreceivers reproduce the source component $S^n_2$ losslessly; and Receiver $1$\nalso reproduces the source component $S^n_1$ lossily, to within some prescribed\nfidelity level $D_1$. Also, Receiver $1$ and Receiver $2$ are equipped\nrespectively with memoryless side information sequences $Y^n_1$ and $Y^n_2$.\nImportant in this setup, the side information sequences are arbitrarily\ncorrelated among them, and with the source pair $(S^n_1,S^n_2)$; and are not\nassumed to exhibit any particular ordering. Furthermore, by specializing the\nmain result to two Heegard-Berger models with successive refinement and\nscalable coding, we shed light on the roles of the common and private\ndescriptions that the encoder should produce and what they should carry\noptimally. We develop intuitions by analyzing the developed single-letter\noptimal rate-distortion regions of these models, and discuss some insightful\nbinary examples.\n",
"title": "Rate-Distortion Region of a Gray-Wyner Model with Side Information"
} | null | null | null | null | true | null | 36 | null | Default | null | null |
null | {
"abstract": " This work discusses the numerical approximation of a nonlinear\nreaction-advection-diffusion equation, which is a dimensionless form of the\nWeertman equation. This equation models steadily-moving dislocations in\nmaterials science. It reduces to the celebrated Peierls-Nabarro equation when\nits advection term is set to zero. The approach rests on considering a\ntime-dependent formulation, which admits the equation under study as its\nlong-time limit. Introducing a Preconditioned Collocation Scheme based on\nFourier transforms, the iterative numerical method presented solves the\ntime-dependent problem, delivering at convergence the desired numerical\nsolution to the Weertman equation. Although it rests on an explicit\ntime-evolution scheme, the method allows for large time steps, and captures the\nsolution in a robust manner. Numerical results illustrate the efficiency of the\napproach for several types of nonlinearities.\n",
"title": "Fourier-based numerical approximation of the Weertman equation for moving dislocations"
} | null | null | null | null | true | null | 37 | null | Default | null | null |
null | {
"abstract": " There are many web-based visualization systems available to date, each having\nits strengths and limitations. The goals these systems set out to accomplish\ninfluence design decisions and determine how reusable and scalable they are.\nWeave is a new web-based visualization platform with the broad goal of enabling\nvisualization of any available data by anyone for any purpose. Our open source\nframework supports highly interactive linked visualizations for users of\nvarying skill levels. What sets Weave apart from other systems is its\nconsideration for real-time remote collaboration with session history. We\nprovide a detailed account of the various framework designs we considered with\ncomparisons to existing state-of-the-art systems.\n",
"title": "Design Decisions for Weave: A Real-Time Web-based Collaborative Visualization Framework"
} | null | null | null | null | true | null | 38 | null | Default | null | null |
null | {
"abstract": " We present an investigation of the supernova remnant (SNR) G306.3$-$0.9 using\narchival multi-wavelength data. The Suzaku spectra are well described by\ntwo-component thermal plasma models: The soft component is in ionization\nequilibrium and has a temperature $\\sim$0.59 keV, while the hard component has\ntemperature $\\sim$3.2 keV and ionization time-scale $\\sim$$2.6\\times10^{10}$\ncm$^{-3}$ s. We clearly detected Fe K-shell line at energy of $\\sim$6.5 keV\nfrom this remnant. The overabundances of Si, S, Ar, Ca, and Fe confirm that the\nX-ray emission has an ejecta origin. The centroid energy of the Fe-K line\nsupports that G306.3$-$0.9 is a remnant of a Type Ia supernova (SN) rather than\na core-collapse SN. The GeV gamma-ray emission from G306.3$-$0.9 and its\nsurrounding were analyzed using about 6 years of Fermi data. We report about\nthe non-detection of G306.3$-$0.9 and the detection of a new extended gamma-ray\nsource in the south-west of G306.3$-$0.9 with a significance of\n$\\sim$13$\\sigma$. We discuss several scenarios for these results with the help\nof data from other wavebands to understand the SNR and its neighborhood.\n",
"title": "Suzaku Analysis of the Supernova Remnant G306.3-0.9 and the Gamma-ray View of Its Neighborhood"
} | null | null | null | null | true | null | 39 | null | Default | null | null |
null | {
"abstract": " Previous approaches to training syntax-based sentiment classification models\nrequired phrase-level annotated corpora, which are not readily available in\nmany languages other than English. Thus, we propose the use of tree-structured\nLong Short-Term Memory with an attention mechanism that pays attention to each\nsubtree of the parse tree. Experimental results indicate that our model\nachieves the state-of-the-art performance in a Japanese sentiment\nclassification task.\n",
"title": "Japanese Sentiment Classification using a Tree-Structured Long Short-Term Memory with Attention"
} | null | null | null | null | true | null | 40 | null | Default | null | null |
null | {
"abstract": " Mean-field Variational Bayes (MFVB) is an approximate Bayesian posterior\ninference technique that is increasingly popular due to its fast runtimes on\nlarge-scale datasets. However, even when MFVB provides accurate posterior means\nfor certain parameters, it often mis-estimates variances and covariances.\nFurthermore, prior robustness measures have remained undeveloped for MFVB. By\nderiving a simple formula for the effect of infinitesimal model perturbations\non MFVB posterior means, we provide both improved covariance estimates and\nlocal robustness measures for MFVB, thus greatly expanding the practical\nusefulness of MFVB posterior approximations. The estimates for MFVB posterior\ncovariances rely on a result from the classical Bayesian robustness literature\nrelating derivatives of posterior expectations to posterior covariances and\ninclude the Laplace approximation as a special case. Our key condition is that\nthe MFVB approximation provides good estimates of a select subset of posterior\nmeans---an assumption that has been shown to hold in many practical settings.\nIn our experiments, we demonstrate that our methods are simple, general, and\nfast, providing accurate posterior uncertainty estimates and robustness\nmeasures with runtimes that can be an order of magnitude faster than MCMC.\n",
"title": "Covariances, Robustness, and Variational Bayes"
} | null | null | [
"Statistics"
]
| null | true | null | 41 | null | Validated | null | null |
null | {
"abstract": " In this paper, we empirically study models for pricing Italian sovereign\nbonds under a reduced form framework, by assuming different dynamics for the\nshort-rate process. We analyze classical Cox-Ingersoll-Ross and Vasicek\nmulti-factor models, with a focus on optimization algorithms applied in the\ncalibration exercise. The Kalman filter algorithm together with a maximum\nlikelihood estimation method are considered to fit the Italian term-structure\nover a 12-year horizon, including the global financial crisis and the euro area\nsovereign debt crisis. Analytic formulas for the gradient vector and the\nHessian matrix of the likelihood function are provided.\n",
"title": "Are multi-factor Gaussian term structure models still useful? An empirical analysis on Italian BTPs"
} | null | null | [
"Quantitative Finance"
]
| null | true | null | 42 | null | Validated | null | null |
null | {
"abstract": " Ballistic point contact (BPC) with zigzag edges in graphene is a main\ncandidate of a valley filter, in which the polarization of the valley degree of\nfreedom can be selected by using a local gate voltage. Here, we propose to\ndetect the valley filtering effect by Andreev reflection. Because electrons in\nthe lowest conduction band and the highest valence band of the BPC possess\nopposite chirality, the inter-band Andreev reflection is strongly suppressed,\nafter multiple scattering and interference. We draw this conclusion by both the\nscattering matrix analysis and the numerical simulation. The Andreev reflection\nas a function of the incident energy of electrons and the local gate voltage at\nthe BPC is obtained, by which the parameter region for a perfect valley filter\nand the direction of valley polarization can be determined. The Andreev\nreflection exhibits an oscillatory decay with the length of the BPC, indicating\na negative correlation to valley polarization.\n",
"title": "Probing valley filtering effect by Andreev reflection in zigzag graphene nanoribbon"
} | null | null | null | null | true | null | 43 | null | Default | null | null |
null | {
"abstract": " Sparse superposition (SS) codes were originally proposed as a\ncapacity-achieving communication scheme over the additive white Gaussian noise\nchannel (AWGNC) [1]. Very recently, it was discovered that these codes are\nuniversal, in the sense that they achieve capacity over any memoryless channel\nunder generalized approximate message-passing (GAMP) decoding [2], although\nthis decoder has never been stated for SS codes. In this contribution we\nintroduce the GAMP decoder for SS codes, we confirm empirically the\nuniversality of this communication scheme through its study on various channels\nand we provide the main analysis tools: state evolution and potential. We also\ncompare the performance of GAMP with the Bayes-optimal MMSE decoder. We\nempirically illustrate that despite the presence of a phase transition\npreventing GAMP to reach the optimal performance, spatial coupling allows to\nboost the performance that eventually tends to capacity in a proper limit. We\nalso prove that, in contrast with the AWGNC case, SS codes for binary input\nchannels have a vanishing error floor in the limit of large codewords.\nMoreover, the performance of Hadamard-based encoders is assessed for practical\nimplementations.\n",
"title": "Generalized Approximate Message-Passing Decoder for Universal Sparse Superposition Codes"
} | null | null | [
"Computer Science",
"Mathematics"
]
| null | true | null | 44 | null | Validated | null | null |
null | {
"abstract": " When developing general purpose robots, the overarching software architecture\ncan greatly affect the ease of accomplishing various tasks. Initial efforts to\ncreate unified robot systems in the 1990s led to hybrid architectures,\nemphasizing a hierarchy in which deliberative plans direct the use of reactive\nskills. However, since that time there has been significant progress in the\nlow-level skills available to robots, including manipulation and perception,\nmaking it newly feasible to accomplish many more tasks in real-world domains.\nThere is thus renewed optimism that robots will be able to perform a wide array\nof tasks while maintaining responsiveness to human operators. However, the top\nlayer in traditional hybrid architectures, designed to achieve long-term goals,\ncan make it difficult to react quickly to human interactions during goal-driven\nexecution. To mitigate this difficulty, we propose a novel architecture that\nsupports such transitions by adding a top-level reactive module which has\nflexible access to both reactive skills and a deliberative control module. To\nvalidate this architecture, we present a case study of its application on a\ndomestic service robot platform.\n",
"title": "LAAIR: A Layered Architecture for Autonomous Interactive Robots"
} | null | null | null | null | true | null | 45 | null | Default | null | null |
null | {
"abstract": " We propose an approach to estimate 3D human pose in real world units from a\nsingle RGBD image and show that it exceeds performance of monocular 3D pose\nestimation approaches from color as well as pose estimation exclusively from\ndepth. Our approach builds on robust human keypoint detectors for color images\nand incorporates depth for lifting into 3D. We combine the system with our\nlearning from demonstration framework to instruct a service robot without the\nneed of markers. Experiments in real world settings demonstrate that our\napproach enables a PR2 robot to imitate manipulation actions observed from a\nhuman teacher.\n",
"title": "3D Human Pose Estimation in RGBD Images for Robotic Task Learning"
} | null | null | [
"Computer Science"
]
| null | true | null | 46 | null | Validated | null | null |
null | {
"abstract": " We extend the work of Fouvry, Kowalski and Michel on correlation between\nHecke eigenvalues of modular forms and algebraic trace functions in order to\nestablish an asymptotic formula for a generalized cubic moment of modular\nL-functions at the central point s = 1/2 and for prime moduli q. As an\napplication, we exploit our recent result on the mollification of the fourth\nmoment of Dirichlet L-functions to derive that for any pair\n$(\\omega_1,\\omega_2)$ of multiplicative characters modulo q, there is a\npositive proportion of $\\chi$ (mod q) such that $L(\\chi, 1/2 ), L(\\chi\\omega_1,\n1/2 )$ and $L(\\chi\\omega_2, 1/2)$ are simultaneously not too small.\n",
"title": "Simultaneous non-vanishing for Dirichlet L-functions"
} | null | null | null | null | true | null | 47 | null | Default | null | null |
null | {
"abstract": " Nonclassical states of a quantized light are described in terms of\nGlauber-Sudarshan P distribution which is not a genuine classical probability\ndistribution. Despite several attempts, defining a uniform measure of\nnonclassicality (NC) for the single mode quantum states of light is yet an open\ntask. In our previous work [Phys. Rev. A 95, 012330 (2017)] we have shown that\nthe existing well-known measures fail to quantify the NC of single mode states\nthat are generated under multiple NC-inducing operations. Recently, Ivan et.\nal. [Quantum. Inf. Process. 11, 853 (2012)] have defined a measure of\nnon-Gaussian character of quantum optical states in terms of Wehrl entropy.\nHere, we adopt this concept in the context of single mode NC. In this paper, we\npropose a new quantification of NC for the single mode quantum states of light\nas the difference between the total Wehrl entropy of the state and the maximum\nWehrl entropy arising due to its classical characteristics. This we achieve by\nsubtracting from its Wehrl entropy, the maximum Wehrl entropy attainable by any\nclassical state that has same randomness as measured in terms of von-Neumann\nentropy. We obtain analytic expressions of NC for most of the states, in\nparticular, all pure states and Gaussian mixed states. However, the evaluation\nof NC for the non-Gaussian mixed states is subject to extensive numerical\ncomputation that lies beyond the scope of the current work. We show that, along\nwith the states generated under single NC-inducing operations, also for the\nbroader class of states that are generated under multiple NC-inducing\noperations, our quantification enumerates the NC consistently.\n",
"title": "Wehrl Entropy Based Quantification of Nonclassicality for Single Mode Quantum Optical States"
} | null | null | null | null | true | null | 48 | null | Default | null | null |
null | {
"abstract": " Following the recent progress in image classification and captioning using\ndeep learning, we develop a novel natural language person retrieval system\nbased on an attention mechanism. More specifically, given the description of a\nperson, the goal is to localize the person in an image. To this end, we first\nconstruct a benchmark dataset for natural language person retrieval. To do so,\nwe generate bounding boxes for persons in a public image dataset from the\nsegmentation masks, which are then annotated with descriptions and attributes\nusing the Amazon Mechanical Turk. We then adopt a region proposal network in\nFaster R-CNN as a candidate region generator. The cropped images based on the\nregion proposals as well as the whole images with attention weights are fed\ninto Convolutional Neural Networks for visual feature extraction, while the\nnatural language expression and attributes are input to Bidirectional Long\nShort- Term Memory (BLSTM) models for text feature extraction. The visual and\ntext features are integrated to score region proposals, and the one with the\nhighest score is retrieved as the output of our system. The experimental\nresults show significant improvement over the state-of-the-art method for\ngeneric object retrieval and this line of research promises to benefit search\nin surveillance video footage.\n",
"title": "Attention-based Natural Language Person Retrieval"
} | null | null | [
"Computer Science"
]
| null | true | null | 49 | null | Validated | null | null |
null | {
"abstract": " Real time large scale streaming data pose major challenges to forecasting, in\nparticular defying the presence of human experts to perform the corresponding\nanalysis. We present here a class of models and methods used to develop an\nautomated, scalable and versatile system for large scale forecasting oriented\ntowards safety and security monitoring. Our system provides short and long term\nforecasts and uses them to detect safety and security issues in relation with\nmultiple internet connected devices well in advance they might take place.\n",
"title": "Large Scale Automated Forecasting for Monitoring Network Safety and Security"
} | null | null | [
"Statistics"
]
| null | true | null | 50 | null | Validated | null | null |
null | {
"abstract": " Machine learning algorithms such as linear regression, SVM and neural network\nhave played an increasingly important role in the process of scientific\ndiscovery. However, none of them is both interpretable and accurate on\nnonlinear datasets. Here we present contextual regression, a method that joins\nthese two desirable properties together using a hybrid architecture of neural\nnetwork embedding and dot product layer. We demonstrate its high prediction\naccuracy and sensitivity through the task of predictive feature selection on a\nsimulated dataset and the application of predicting open chromatin sites in the\nhuman genome. On the simulated data, our method achieved high fidelity recovery\nof feature contributions under random noise levels up to 200%. On the open\nchromatin dataset, the application of our method not only outperformed the\nstate of the art method in terms of accuracy, but also unveiled two previously\nunfound open chromatin related histone marks. Our method can fill the blank of\naccurate and interpretable nonlinear modeling in scientific data mining tasks.\n",
"title": "Contextual Regression: An Accurate and Conveniently Interpretable Nonlinear Model for Mining Discovery from Scientific Data"
} | null | null | null | null | true | null | 51 | null | Default | null | null |
null | {
"abstract": " We consider multi-time correlators for output signals from linear detectors,\ncontinuously measuring several qubit observables at the same time. Using the\nquantum Bayesian formalism, we show that for unital (symmetric) evolution in\nthe absence of phase backaction, an $N$-time correlator can be expressed as a\nproduct of two-time correlators when $N$ is even. For odd $N$, there is a\nsimilar factorization, which also includes a single-time average. Theoretical\npredictions agree well with experimental results for two detectors, which\nsimultaneously measure non-commuting qubit observables.\n",
"title": "Multi-time correlators in continuous measurement of qubit observables"
} | null | null | null | null | true | null | 52 | null | Default | null | null |
null | {
"abstract": " Constraint Handling Rules is an effective concurrent declarative programming\nlanguage and a versatile computational logic formalism. CHR programs consist of\nguarded reactive rules that transform multisets of constraints. One of the main\nfeatures of CHR is its inherent concurrency. Intuitively, rules can be applied\nto parts of a multiset in parallel. In this comprehensive survey, we give an\noverview of concurrent and parallel as well as distributed CHR semantics,\nstandard and more exotic, that have been proposed over the years at various\nlevels of refinement. These semantics range from the abstract to the concrete.\nThey are related by formal soundness results. Their correctness is established\nas correspondence between parallel and sequential computations. We present\ncommon concise sample CHR programs that have been widely used in experiments\nand benchmarks. We review parallel CHR implementations in software and\nhardware. The experimental results obtained show a consistent parallel speedup.\nMost implementations are available online. The CHR formalism can also be used\nto implement and reason with models for concurrency. To this end, the Software\nTransaction Model, the Actor Model, Colored Petri Nets and the Join-Calculus\nhave been faithfully encoded in CHR. Under consideration in Theory and Practice\nof Logic Programming (TPLP).\n",
"title": "Parallelism, Concurrency and Distribution in Constraint Handling Rules: A Survey"
} | null | null | null | null | true | null | 53 | null | Default | null | null |
null | {
"abstract": " Many people are suffering from voice disorders, which can adversely affect\nthe quality of their lives. In response, some researchers have proposed\nalgorithms for automatic assessment of these disorders, based on voice signals.\nHowever, these signals can be sensitive to the recording devices. Indeed, the\nchannel effect is a pervasive problem in machine learning for healthcare. In\nthis study, we propose a detection system for pathological voice, which is\nrobust against the channel effect. This system is based on a bidirectional LSTM\nnetwork. To increase the performance robustness against channel mismatch, we\nintegrate domain adversarial training (DAT) to eliminate the differences\nbetween the devices. When we train on data recorded on a high-quality\nmicrophone and evaluate on smartphone data without labels, our robust detection\nsystem increases the PR-AUC from 0.8448 to 0.9455 (and 0.9522 with target\nsample labels). To the best of our knowledge, this is the first study applying\nunsupervised domain adaptation to pathological voice detection. Notably, our\nsystem does not need target device sample labels, which allows for\ngeneralization to many new devices.\n",
"title": "Robustness against the channel effect in pathological voice detection"
} | null | null | [
"Computer Science"
]
| null | true | null | 54 | null | Validated | null | null |
null | {
"abstract": " Computing a basis for the exponent lattice of algebraic numbers is a basic\nproblem in the field of computational number theory with applications to many\nother areas. The main cost of a well-known algorithm\n\\cite{ge1993algorithms,kauers2005algorithms} solving the problem is on\ncomputing the primitive element of the extended field generated by the given\nalgebraic numbers. When the extended field is of large degree, the problem\nseems intractable by the tool implementing the algorithm. In this paper, a\nspecial kind of exponent lattice basis is introduced. An important feature of\nthe basis is that it can be inductively constructed, which allows us to deal\nwith the given algebraic numbers one by one when computing the basis. Based on\nthis, an effective framework for constructing exponent lattice basis is\nproposed. Through computing a so-called pre-basis first and then solving some\nlinear Diophantine equations, the basis can be efficiently constructed. A new\ncertificate for multiplicative independence and some techniques for decreasing\ndegrees of algebraic numbers are provided to speed up the computation. The new\nalgorithm has been implemented with Mathematica and its effectiveness is\nverified by testing various examples. Moreover, the algorithm is applied to\nprogram verification for finding invariants of linear loops.\n",
"title": "An Effective Framework for Constructing Exponent Lattice Basis of Nonzero Algebraic Numbers"
} | null | null | null | null | true | null | 55 | null | Default | null | null |
null | {
"abstract": " Investigating the emergence of a particular cell type is a recurring theme in\nmodels of growing cellular populations. The evolution of resistance to therapy\nis a classic example. Common questions are: when does the cell type first\noccur, and via which sequence of steps is it most likely to emerge? For growing\npopulations, these questions can be formulated in a general framework of\nbranching processes spreading through a graph from a root to a target vertex.\nCells have a particular fitness value on each vertex and can transition along\nedges at specific rates. Vertices represents cell states, say \\mic{genotypes\n}or physical locations, while possible transitions are acquiring a mutation or\ncell migration. We focus on the setting where cells at the root vertex have the\nhighest fitness and transition rates are small. Simple formulas are derived for\nthe time to reach the target vertex and for the probability that it is reached\nalong a given path in the graph. We demonstrate our results on \\mic{several\nscenarios relevant to the emergence of drug resistance}, including: the\norderings of resistance-conferring mutations in bacteria and the impact of\nimperfect drug penetration in cancer.\n",
"title": "Competing evolutionary paths in growing populations with applications to multidrug resistance"
} | null | null | null | null | true | null | 56 | null | Default | null | null |
null | {
"abstract": " Stimuli-responsive materials that modify their shape in response to changes\nin environmental conditions -- such as solute concentration, temperature, pH,\nand stress -- are widespread in nature and technology. Applications include\nmicro- and nanoporous materials used in filtration and flow control. The\nphysiochemical mechanisms that induce internal volume modifications have been\nwidely studies. The coupling between induced volume changes and solute\ntransport through porous materials, however, is not well understood. Here, we\nconsider advective and diffusive transport through a small channel linking two\nlarge reservoirs. A section of stimulus-responsive material regulates the\nchannel permeability, which is a function of the local solute concentration. We\nderive an exact solution to the coupled transport problem and demonstrate the\nexistence of a flow regime in which the steady state is reached via a damped\noscillation around the equilibrium concentration value. Finally, the\nfeasibility of an experimental observation of the phenomena is discussed.\nPlease note that this version of the paper has not been formally peer reviewed,\nrevised or accepted by a journal.\n",
"title": "Transient flows in active porous media"
} | null | null | [
"Physics"
]
| null | true | null | 57 | null | Validated | null | null |
null | {
"abstract": " Today's landscape of robotics is dominated by vertical integration where\nsingle vendors develop the final product leading to slow progress, expensive\nproducts and customer lock-in. Opposite to this, an horizontal integration\nwould result in a rapid development of cost-effective mass-market products with\nan additional consumer empowerment. The transition of an industry from vertical\nintegration to horizontal integration is typically catalysed by de facto\nindustry standards that enable a simplified and seamless integration of\nproducts. However, in robotics there is currently no leading candidate for a\nglobal plug-and-play standard.\nThis paper tackles the problem of incompatibility between robot components\nthat hinder the reconfigurability and flexibility demanded by the robotics\nindustry. Particularly, it presents a model to create plug-and-play robot\nhardware components. Rather than iteratively evolving previous ontologies, our\nproposed model answers the needs identified by the industry while facilitating\ninteroperability, measurability and comparability of robotics technology. Our\napproach differs significantly with the ones presented before as it is\nhardware-oriented and establishes a clear set of actions towards the\nintegration of this model in real environments and with real manufacturers.\n",
"title": "An information model for modular robots: the Hardware Robot Information Model (HRIM)"
} | null | null | null | null | true | null | 58 | null | Default | null | null |
null | {
"abstract": " Machine learning models, especially based on deep architectures are used in\neveryday applications ranging from self driving cars to medical diagnostics. It\nhas been shown that such models are dangerously susceptible to adversarial\nsamples, indistinguishable from real samples to human eye, adversarial samples\nlead to incorrect classifications with high confidence. Impact of adversarial\nsamples is far-reaching and their efficient detection remains an open problem.\nWe propose to use direct density ratio estimation as an efficient model\nagnostic measure to detect adversarial samples. Our proposed method works\nequally well with single and multi-channel samples, and with different\nadversarial sample generation methods. We also propose a method to use density\nratio estimates for generating adversarial samples with an added constraint of\npreserving density ratio.\n",
"title": "Detecting Adversarial Samples Using Density Ratio Estimates"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 59 | null | Validated | null | null |
null | {
"abstract": " We study the query complexity of cake cutting and give lower and upper bounds\nfor computing approximately envy-free, perfect, and equitable allocations with\nthe minimum number of cuts. The lower bounds are tight for computing connected\nenvy-free allocations among n=3 players and for computing perfect and equitable\nallocations with minimum number of cuts between n=2 players.\nWe also formalize moving knife procedures and show that a large subclass of\nthis family, which captures all the known moving knife procedures, can be\nsimulated efficiently with arbitrarily small error in the Robertson-Webb query\nmodel.\n",
"title": "The Query Complexity of Cake Cutting"
} | null | null | null | null | true | null | 60 | null | Default | null | null |
null | {
"abstract": " This paper studies the emotion recognition from musical tracks in the\n2-dimensional valence-arousal (V-A) emotional space. We propose a method based\non convolutional (CNN) and recurrent neural networks (RNN), having\nsignificantly fewer parameters compared with the state-of-the-art method for\nthe same task. We utilize one CNN layer followed by two branches of RNNs\ntrained separately for arousal and valence. The method was evaluated using the\n'MediaEval2015 emotion in music' dataset. We achieved an RMSE of 0.202 for\narousal and 0.268 for valence, which is the best result reported on this\ndataset.\n",
"title": "Stacked Convolutional and Recurrent Neural Networks for Music Emotion Recognition"
} | null | null | null | null | true | null | 61 | null | Default | null | null |
null | {
"abstract": " We consider previous models of Timed, Probabilistic and Stochastic Timed\nAutomata, we introduce our model of Timed Automata with Polynomial Delay and we\ncharacterize the expressiveness of these models relative to each other.\n",
"title": "Timed Automata with Polynomial Delay and their Expressiveness"
} | null | null | null | null | true | null | 62 | null | Default | null | null |
null | {
"abstract": " We present muon spin rotation measurements on superconducting Cu intercalated\nBi$_2$Se$_3$, which was suggested as a realization of a topological\nsuperconductor. We observe a clear evidence of the superconducting transition\nbelow 4 K, where the width of magnetic field distribution increases as the\ntemperature is decreased. The measured broadening at mK temperatures suggests a\nlarge London penetration depth in the $ab$ plane ($\\lambda_{\\mathrm{eff}}\\sim\n1.6$ $\\mathrm{\\mu}$m). We show that the temperature dependence of this\nbroadening follows the BCS prediction, but could be consistent with several gap\nsymmetries.\n",
"title": "Superconducting properties of Cu intercalated Bi$_2$Se$_3$ studied by Muon Spin Spectroscopy"
} | null | null | null | null | true | null | 63 | null | Default | null | null |
null | {
"abstract": " Here we reveal details of the interaction between human lysozyme proteins,\nboth native and fibrils, and their water environment by intense terahertz time\ndomain spectroscopy. With the aid of a rigorous dielectric model, we determine\nthe amplitude and phase of the oscillating dipole induced by the THz field in\nthe volume containing the protein and its hydration water. At low\nconcentrations, the amplitude of this induced dipolar response decreases with\nincreasing concentration. Beyond a certain threshold, marking the onset of the\ninteractions between the extended hydration shells, the amplitude remains fixed\nbut the phase of the induced dipolar response, which is initially in phase with\nthe applied THz field, begins to change. The changes observed in the THz\nresponse reveal protein-protein interactions me-diated by extended hydration\nlayers, which may control fibril formation and may have an important role in\nchemical recognition phenomena.\n",
"title": "Time-domain THz spectroscopy reveals coupled protein-hydration dielectric response in solutions of native and fibrils of human lyso-zyme"
} | null | null | null | null | true | null | 64 | null | Default | null | null |
null | {
"abstract": " We report on experimentally measured light shifts of superconducting flux\nqubits deep-strongly coupled to LC oscillators, where the coupling constants\nare comparable to the qubit and oscillator resonance frequencies. By using\ntwo-tone spectroscopy, the energies of the six lowest levels of each circuit\nare determined. We find huge Lamb shifts that exceed 90% of the bare qubit\nfrequencies and inversions of the qubits' ground and excited states when there\nare a finite number of photons in the oscillator. Our experimental results\nagree with theoretical predictions based on the quantum Rabi model.\n",
"title": "Inversion of Qubit Energy Levels in Qubit-Oscillator Circuits in the Deep-Strong-Coupling Regime"
} | null | null | null | null | true | null | 65 | null | Default | null | null |
null | {
"abstract": " We describe a novel weakly supervised deep learning framework that combines\nboth the discriminative and generative models to learn meaningful\nrepresentation in the multiple instance learning (MIL) setting. MIL is a weakly\nsupervised learning problem where labels are associated with groups of\ninstances (referred as bags) instead of individual instances. To address the\nessential challenge in MIL problems raised from the uncertainty of positive\ninstances label, we use a discriminative model regularized by variational\nautoencoders (VAEs) to maximize the differences between latent representations\nof all instances and negative instances. As a result, the hidden layer of the\nvariational autoencoder learns meaningful representation. This representation\ncan effectively be used for MIL problems as illustrated by better performance\non the standard benchmark datasets comparing to the state-of-the-art\napproaches. More importantly, unlike most related studies, the proposed\nframework can be easily scaled to large dataset problems, as illustrated by the\naudio event detection and segmentation task. Visualization also confirms the\neffectiveness of the latent representation in discriminating positive and\nnegative classes.\n",
"title": "Deep Multiple Instance Feature Learning via Variational Autoencoder"
} | null | null | null | null | true | null | 66 | null | Default | null | null |
null | {
"abstract": " We establish the C^{1,1} regularity of quasi-psh envelopes in a Kahler class,\nconfirming a conjecture of Berman.\n",
"title": "Regularity of envelopes in Kähler classes"
} | null | null | null | null | true | null | 67 | null | Default | null | null |
null | {
"abstract": " Let $M$ be a complex manifold of dimension $n$ with smooth connected boundary\n$X$. Assume that $\\overline M$ admits a holomorphic $S^1$-action preserving the\nboundary $X$ and the $S^1$-action is transversal and CR on $X$. We show that\nthe $\\overline\\partial$-Neumann Laplacian on $M$ is transversally elliptic and\nas a consequence, the $m$-th Fourier component of the $q$-th Dolbeault\ncohomology group $H^q_m(\\overline M)$ is finite dimensional, for every\n$m\\in\\mathbb Z$ and every $q=0,1,\\ldots,n$. This enables us to define\n$\\sum^{n}_{j=0}(-1)^j{\\rm dim\\,}H^q_m(\\overline M)$ the $m$-th Fourier\ncomponent of the Euler characteristic on $M$ and to study large $m$-behavior of\n$H^q_m(\\overline M)$. In this paper, we establish an index formula for\n$\\sum^{n}_{j=0}(-1)^j{\\rm dim\\,}H^q_m(\\overline M)$ and Morse inequalities for\n$H^q_m(\\overline M)$.\n",
"title": "$S^1$-equivariant Index theorems and Morse inequalities on complex manifolds with boundary"
} | null | null | null | null | true | null | 68 | null | Default | null | null |
null | {
"abstract": " Reinforcement learning methods require careful design involving a reward\nfunction to obtain the desired action policy for a given task. In the absence\nof hand-crafted reward functions, prior work on the topic has proposed several\nmethods for reward estimation by using expert state trajectories and action\npairs. However, there are cases where complete or good action information\ncannot be obtained from expert demonstrations. We propose a novel reinforcement\nlearning method in which the agent learns an internal model of observation on\nthe basis of expert-demonstrated state trajectories to estimate rewards without\ncompletely learning the dynamics of the external environment from state-action\npairs. The internal model is obtained in the form of a predictive model for the\ngiven expert state distribution. During reinforcement learning, the agent\npredicts the reward as a function of the difference between the actual state\nand the state predicted by the internal model. We conducted multiple\nexperiments in environments of varying complexity, including the Super Mario\nBros and Flappy Bird games. We show our method successfully trains good\npolicies directly from expert game-play videos.\n",
"title": "Internal Model from Observations for Reward Shaping"
} | null | null | null | null | true | null | 69 | null | Default | null | null |
null | {
"abstract": " In this paper we are interested in the class of n-ary operations on an\narbitrary chain that are quasitrivial, symmetric, nondecreasing, and\nassociative. We first provide a description of these operations. We then prove\nthat associativity can be replaced with bisymmetry in the definition of this\nclass. Finally we investigate the special situation where the chain is finite.\n",
"title": "Characterizations of quasitrivial symmetric nondecreasing associative operations"
} | null | null | null | null | true | null | 70 | null | Default | null | null |
null | {
"abstract": " We propose a new multivariate dependency measure. It is obtained by\nconsidering a Gaussian kernel based distance between the copula transform of\nthe given d-dimensional distribution and the uniform copula and then\nappropriately normalizing it. The resulting measure is shown to satisfy a\nnumber of desirable properties. A nonparametric estimate is proposed for this\ndependency measure and its properties (finite sample as well as asymptotic) are\nderived. Some comparative studies of the proposed dependency measure estimate\nwith some widely used dependency measure estimates on artificial datasets are\nincluded. A non-parametric test of independence between two or more random\nvariables based on this measure is proposed. A comparison of the proposed test\nwith some existing nonparametric multivariate test for independence is\npresented.\n",
"title": "Multivariate Dependency Measure based on Copula and Gaussian Kernel"
} | null | null | null | null | true | null | 71 | null | Default | null | null |
null | {
"abstract": " The pyrochlore metal Cd2Re2O7 has been recently investigated by\nsecond-harmonic generation (SHG) reflectivity. In this paper, we develop a\ngeneral formalism that allows for the identification of the relevant tensor\ncomponents of the SHG from azimuthal scans. We demonstrate that the secondary\norder parameter identified by SHG at the structural phase transition is the\nx2-y2 component of the axial toroidal quadrupole. This differs from the 3z2-r2\nsymmetry of the atomic displacements associated with the I-4m2 crystal\nstructure that was previously thought to be its origin. Within the same\nformalism, we suggest that the primary order parameter detected in the SHG\nexperiment is the 3z2-r2 component of the magnetic quadrupole. We discuss the\ngeneral mechanism driving the phase transition in our proposed framework, and\nsuggest experiments, particularly resonant X-ray scattering ones, that could\nclarify this issue.\n",
"title": "The nature of the tensor order in Cd2Re2O7"
} | null | null | [
"Physics"
]
| null | true | null | 72 | null | Validated | null | null |
null | {
"abstract": " In evolutionary biology, the speciation history of living organisms is\nrepresented graphically by a phylogeny, that is, a rooted tree whose leaves\ncorrespond to current species and branchings indicate past speciation events.\nPhylogenies are commonly estimated from molecular sequences, such as DNA\nsequences, collected from the species of interest. At a high level, the idea\nbehind this inference is simple: the further apart in the Tree of Life are two\nspecies, the greater is the number of mutations to have accumulated in their\ngenomes since their most recent common ancestor. In order to obtain accurate\nestimates in phylogenetic analyses, it is standard practice to employ\nstatistical approaches based on stochastic models of sequence evolution on a\ntree. For tractability, such models necessarily make simplifying assumptions\nabout the evolutionary mechanisms involved. In particular, commonly omitted are\ninsertions and deletions of nucleotides -- also known as indels.\nProperly accounting for indels in statistical phylogenetic analyses remains a\nmajor challenge in computational evolutionary biology. Here we consider the\nproblem of reconstructing ancestral sequences on a known phylogeny in a model\nof sequence evolution incorporating nucleotide substitutions, insertions and\ndeletions, specifically the classical TKF91 process. We focus on the case of\ndense phylogenies of bounded height, which we refer to as the taxon-rich\nsetting, where statistical consistency is achievable. We give the first\npolynomial-time ancestral reconstruction algorithm with provable guarantees\nunder constant rates of mutation. Our algorithm succeeds when the phylogeny\nsatisfies the \"big bang\" condition, a necessary and sufficient condition for\nstatistical consistency in this context.\n",
"title": "Efficient and consistent inference of ancestral sequences in an evolutionary model with insertions and deletions under dense taxon sampling"
} | null | null | null | null | true | null | 73 | null | Default | null | null |
null | {
"abstract": " Subject of research is complex networks and network systems. The network\nsystem is defined as a complex network in which flows are moved. Classification\nof flows in the network is carried out on the basis of ordering and continuity.\nIt is shown that complex networks with different types of flows generate\nvarious network systems. Flow analogues of the basic concepts of the theory of\ncomplex networks are introduced and the main problems of this theory in terms\nof flow characteristics are formulated. Local and global flow characteristics\nof networks bring closer the theory of complex networks to the systems theory\nand systems analysis. Concept of flow core of network system is introduced and\ndefined how it simplifies the process of its investigation. Concepts of kernel\nand flow core of multiplex are determined. Features of operation of multiplex\ntype systems are analyzed.\n",
"title": "Flow Characteristics and Cores of Complex Network and Multiplex Type Systems"
} | null | null | null | null | true | null | 74 | null | Default | null | null |
null | {
"abstract": " We study the effect of domain growth on the orientation of striped phases in\na Swift-Hohenberg equation. Domain growth is encoded in a step-like parameter\ndependence that allows stripe formation in a half plane, and suppresses\npatterns in the complement, while the boundary of the pattern-forming region is\npropagating with fixed normal velocity. We construct front solutions that leave\nbehind stripes in the pattern-forming region that are parallel to or at a small\noblique angle to the boundary.\nTechnically, the construction of stripe formation parallel to the boundary\nrelies on ill-posed, infinite-dimensional spatial dynamics. Stripes forming at\na small oblique angle are constructed using a functional-analytic, perturbative\napproach. Here, the main difficulties are the presence of continuous spectrum\nand the fact that small oblique angles appear as a singular perturbation in a\ntraveling-wave problem. We resolve the former difficulty using a farfield-core\ndecomposition and Fredholm theory in weighted spaces. The singular perturbation\nproblem is resolved using preconditioners and boot-strapping.\n",
"title": "Pattern-forming fronts in a Swift-Hohenberg equation with directional quenching - parallel and oblique stripes"
} | null | null | null | null | true | null | 75 | null | Default | null | null |
null | {
"abstract": " This paper discusses minimum distance estimation method in the linear\nregression model with dependent errors which are strongly mixing. The\nregression parameters are estimated through the minimum distance estimation\nmethod, and asymptotic distributional properties of the estimators are\ndiscussed. A simulation study compares the performance of the minimum distance\nestimator with other well celebrated estimator. This simulation study shows the\nsuperiority of the minimum distance estimator over another estimator. KoulMde\n(R package) which was used for the simulation study is available online. See\nsection 4 for the detail.\n",
"title": "Generalized Minimum Distance Estimators in Linear Regression with Dependent Errors"
} | null | null | null | null | true | null | 76 | null | Default | null | null |
null | {
"abstract": " Mobile edge clouds (MECs) bring the benefits of the cloud closer to the user,\nby installing small cloud infrastructures at the network edge. This enables a\nnew breed of real-time applications, such as instantaneous object recognition\nand safety assistance in intelligent transportation systems, that require very\nlow latency. One key issue that comes with proximity is how to ensure that\nusers always receive good performance as they move across different locations.\nMigrating services between MECs is seen as the means to achieve this. This\narticle presents a layered framework for migrating active service applications\nthat are encapsulated either in virtual machines (VMs) or containers. This\nlayering approach allows a substantial reduction in service downtime. The\nframework is easy to implement using readily available technologies, and one of\nits key advantages is that it supports containers, which is a promising\nemerging technology that offers tangible benefits over VMs. The migration\nperformance of various real applications is evaluated by experiments under the\npresented framework. Insights drawn from the experimentation results are\ndiscussed.\n",
"title": "Live Service Migration in Mobile Edge Clouds"
} | null | null | null | null | true | null | 77 | null | Default | null | null |
null | {
"abstract": " Analog black/white hole pairs, consisting of a region of supersonic flow,\nhave been achieved in a recent experiment by J. Steinhauer using an elongated\nBose-Einstein condensate. A growing standing density wave, and a checkerboard\nfeature in the density-density correlation function, were observed in the\nsupersonic region. We model the density-density correlation function, taking\ninto account both quantum fluctuations and the shot-to-shot variation of atom\nnumber normally present in ultracold-atom experiments. We find that quantum\nfluctuations alone produce some, but not all, of the features of the\ncorrelation function, whereas atom-number fluctuation alone can produce all the\nobserved features, and agreement is best when both are included. In both cases,\nthe density-density correlation is not intrinsic to the fluctuations, but\nrather is induced by modulation of the standing wave caused by the\nfluctuations.\n",
"title": "Induced density correlations in a sonic black hole condensate"
} | null | null | null | null | true | null | 78 | null | Default | null | null |
null | {
"abstract": " Let $K$ be a function field over a finite field $k$ of characteristic $p$ and\nlet $K_{\\infty}/K$ be a geometric extension with Galois group $\\mathbb{Z}_p$.\nLet $K_n$ be the corresponding subextension with Galois group\n$\\mathbb{Z}/p^n\\mathbb{Z}$ and genus $g_n$. In this paper, we give a simple\nexplicit formula $g_n$ in terms of an explicit Witt vector construction of the\n$\\mathbb{Z}_p$-tower. This formula leads to a tight lower bound on $g_n$ which\nis quadratic in $p^n$. Furthermore, we determine all $\\mathbb{Z}_p$-towers for\nwhich the genus sequence is stable, in the sense that there are $a,b,c \\in\n\\mathbb{Q}$ such that $g_n=a p^{2n}+b p^n +c$ for $n$ large enough. Such genus\nstable towers are expected to have strong stable arithmetic properties for\ntheir zeta functions. A key technical contribution of this work is a new\nsimplified formula for the Schmid-Witt symbol coming from local class field\ntheory.\n",
"title": "Genus growth in $\\mathbb{Z}_p$-towers of function fields"
} | null | null | null | null | true | null | 79 | null | Default | null | null |
null | {
"abstract": " We study the evolution of spin-orbital correlations in an inhomogeneous\nquantum system with an impurity replacing a doublon by a holon orbital degree\nof freedom. Spin-orbital entanglement is large when spin correlations are\nantiferromagnetic, while for a ferromagnetic host we obtain a pure orbital\ndescription. In this regime the orbital model can be mapped on spinless\nfermions and we uncover topological phases with zero energy modes at the edge\nor at the domain between magnetically inequivalent regions.\n",
"title": "Topological Phases emerging from Spin-Orbital Physics"
} | null | null | null | null | true | null | 80 | null | Default | null | null |
null | {
"abstract": " For autonomous agents to successfully operate in the real world, anticipation\nof future events and states of their environment is a key competence. This\nproblem has been formalized as a sequence extrapolation problem, where a number\nof observations are used to predict the sequence into the future. Real-world\nscenarios demand a model of uncertainty of such predictions, as predictions\nbecome increasingly uncertain -- in particular on long time horizons. While\nimpressive results have been shown on point estimates, scenarios that induce\nmulti-modal distributions over future sequences remain challenging. Our work\naddresses these challenges in a Gaussian Latent Variable model for sequence\nprediction. Our core contribution is a \"Best of Many\" sample objective that\nleads to more accurate and more diverse predictions that better capture the\ntrue variations in real-world sequence data. Beyond our analysis of improved\nmodel fit, our models also empirically outperform prior work on three diverse\ntasks ranging from traffic scenes to weather data.\n",
"title": "Accurate and Diverse Sampling of Sequences based on a \"Best of Many\" Sample Objective"
} | null | null | null | null | true | null | 81 | null | Default | null | null |
null | {
"abstract": " End-to-end approaches have drawn much attention recently for significantly\nsimplifying the construction of an automatic speech recognition (ASR) system.\nRNN transducer (RNN-T) is one of the popular end-to-end methods. Previous\nstudies have shown that RNN-T is difficult to train and a very complex training\nprocess is needed for a reasonable performance. In this paper, we explore RNN-T\nfor a Chinese large vocabulary continuous speech recognition (LVCSR) task and\naim to simplify the training process while maintaining performance. First, a\nnew strategy of learning rate decay is proposed to accelerate the model\nconvergence. Second, we find that adding convolutional layers at the beginning\nof the network and using ordered data can discard the pre-training process of\nthe encoder without loss of performance. Besides, we design experiments to find\na balance among the usage of GPU memory, training circle and model performance.\nFinally, we achieve 16.9% character error rate (CER) on our test set which is\n2% absolute improvement from a strong BLSTM CE system with language model\ntrained on the same text corpus.\n",
"title": "Exploring RNN-Transducer for Chinese Speech Recognition"
} | null | null | null | null | true | null | 82 | null | Default | null | null |
null | {
"abstract": " Elasticity is a cloud property that enables applications and its execution\nsystems to dynamically acquire and release shared computational resources on\ndemand. Moreover, it unfolds the advantage of economies of scale in the cloud\nthrough a drop in the average costs of these shared resources. However, it is\nstill an open challenge to achieve a perfect match between resource demand and\nprovision in autonomous elasticity management. Resource adaptation decisions\nessentially involve a trade-off between economics and performance, which\nproduces a gap between the ideal and actual resource provisioning. This gap, if\nnot properly managed, can negatively impact the aggregate utility of a cloud\ncustomer in the long run. To address this limitation, we propose a technical\ndebt-aware learning approach for autonomous elasticity management based on a\nreinforcement learning of elasticity debts in resource provisioning; the\nadaptation pursues strategic decisions that trades off economics against\nperformance. We extend CloudSim and Burlap to evaluate our approach. The\nevaluation shows that a reinforcement learning of technical debts in elasticity\nobtains a higher utility for a cloud customer, while conforming expected levels\nof performance.\n",
"title": "A Debt-Aware Learning Approach for Resource Adaptations in Cloud Elasticity Management"
} | null | null | null | null | true | null | 83 | null | Default | null | null |
null | {
"abstract": " This is an exposition of homotopical results on the geometric realization of\nsemi-simplicial spaces. We then use these to derive basic foundational results\nabout classifying spaces of topological categories, possibly without units. The\ntopics considered include: fibrancy conditions on topological categories; the\neffect on classifying spaces of freely adjoining units; approximate notions of\nunits; Quillen's Theorems A and B for non-unital topological categories; the\neffect on classifying spaces of changing the topology on the space of objects;\nthe Group-Completion Theorem.\n",
"title": "Semi-simplicial spaces"
} | null | null | null | null | true | null | 84 | null | Default | null | null |
null | {
"abstract": " Answer Set Programming (ASP) is a well-established declarative paradigm. One\nof the successes of ASP is the availability of efficient systems.\nState-of-the-art systems are based on the ground+solve approach. In some\napplications this approach is infeasible because the grounding of one or few\nconstraints is expensive. In this paper, we systematically compare alternative\nstrategies to avoid the instantiation of problematic constraints, that are\nbased on custom extensions of the solver. Results on real and synthetic\nbenchmarks highlight some strengths and weaknesses of the different strategies.\n(Under consideration for acceptance in TPLP, ICLP 2017 Special Issue.)\n",
"title": "Constraints, Lazy Constraints, or Propagators in ASP Solving: An Empirical Analysis"
} | null | null | null | null | true | null | 85 | null | Default | null | null |
null | {
"abstract": " The advances in geometric approaches to optical devices due to transformation\noptics has led to the development of cloaks, concentrators, and other devices.\nIt has also been shown that transformation optics can be used to gravitational\nfields from general relativity. However, the technique is currently constrained\nto linear devices, as a consistent approach to nonlinearity (including both the\ncase of a nonlinear background medium and a nonlinear transformation) remains\nan open question. Here we show that nonlinearity can be incorporated into\ntransformation optics in a consistent way. We use this to illustrate a number\nof novel effects, including cloaking an optical soliton, modeling nonlinear\nsolutions to Einstein's field equations, controlling transport in a Debye\nsolid, and developing a set of constitutive to relations for relativistic\ncloaks in arbitrary nonlinear backgrounds.\n",
"title": "A Unified Approach to Nonlinear Transformation Materials"
} | null | null | null | null | true | null | 86 | null | Default | null | null |
null | {
"abstract": " We investigate crack propagation in a simple two-dimensional visco-elastic\nmodel and find a scaling regime in the relation between the propagation\nvelocity and energy release rate or fracture energy, together with lower and\nupper bounds of the scaling regime. On the basis of our result, the existence\nof the lower and upper bounds is expected to be universal or model-independent:\nthe present simple simulation model provides generic insight into the physics\nof crack propagation, and the model will be a first step towards the\ndevelopment of a more refined coarse-grained model. Relatively abrupt changes\nof velocity are predicted near the lower and upper bounds for the scaling\nregime and the positions of the bounds could be good markers for the\ndevelopment of tough polymers, for which we provide simple views that could be\nuseful as guiding principles for toughening polymer-based materials.\n",
"title": "Stationary crack propagation in a two-dimensional visco-elastic network model"
} | null | null | null | null | true | null | 87 | null | Default | null | null |
null | {
"abstract": " The fundamental group $\\pi$ of a Kodaira fibration is, by definition, the\nextension of a surface group $\\Pi_b$ by another surface group $\\Pi_g$, i.e. \\[\n1 \\rightarrow \\Pi_g \\rightarrow \\pi \\rightarrow \\Pi_b \\rightarrow 1. \\]\nConversely, we can inquire about what conditions need to be satisfied by a\ngroup of that sort in order to be the fundamental group of a Kodaira fibration.\nIn this short note we collect some restriction on the image of the classifying\nmap $m \\colon \\Pi_b \\to \\Gamma_g$ in terms of the coinvariant homology of\n$\\Pi_g$. In particular, we observe that if $\\pi$ is the fundamental group of a\nKodaira fibration with relative irregularity $g-s$, then $g \\leq 1+ 6s$, and we\nshow that this effectively constrains the possible choices for $\\pi$, namely\nthat there are group extensions as above that fail to satisfy this bound, hence\ncannot be the fundamental group of a Kodaira fibration. In particular this\nprovides examples of symplectic $4$--manifolds that fail to admit a Kähler\nstructure for reasons that eschew the usual obstructions.\n",
"title": "A note on the fundamental group of Kodaira fibrations"
} | null | null | [
"Mathematics"
]
| null | true | null | 88 | null | Validated | null | null |
null | {
"abstract": " Transistors incorporating single-wall carbon nanotubes (CNTs) as the channel\nmaterial are used in a variety of electronics applications. However, a\ncompetitive CNT-based technology requires the precise placement of CNTs at\npredefined locations of a substrate. One promising placement approach is to use\nchemical recognition to bind CNTs from solution at the desired locations on a\nsurface. Producing the chemical pattern on the substrate is challenging. Here\nwe describe a one-step patterning approach based on a highly photosensitive\nsurface monolayer. The monolayer contains chromophopric group as light\nsensitive body with heteroatoms as high quantum yield photolysis center. As\ndeposited, the layer will bind CNTs from solution. However, when exposed to\nultraviolet (UV) light with a low dose (60 mJ/cm2) similar to that used for\nconventional photoresists, the monolayer cleaves and no longer binds CNTs.\nThese features allow standard, wafer-scale UV lithography processes to be used\nto form a patterned chemical monolayer without the need for complex substrate\npatterning or monolayer stamping.\n",
"title": "Photo-Chemically Directed Self-Assembly of Carbon Nanotubes on Surfaces"
} | null | null | null | null | true | null | 89 | null | Default | null | null |
null | {
"abstract": " This paper derives two new optimization-driven Monte Carlo algorithms\ninspired from variable splitting and data augmentation. In particular, the\nformulation of one of the proposed approaches is closely related to the\nalternating direction method of multipliers (ADMM) main steps. The proposed\nframework enables to derive faster and more efficient sampling schemes than the\ncurrent state-of-the-art methods and can embed the latter. By sampling\nefficiently the parameter to infer as well as the hyperparameters of the\nproblem, the generated samples can be used to approximate Bayesian estimators\nof the parameters to infer. Additionally, the proposed approach brings\nconfidence intervals at a low cost contrary to optimization methods.\nSimulations on two often-studied signal processing problems illustrate the\nperformance of the two proposed samplers. All results are compared to those\nobtained by recent state-of-the-art optimization and MCMC algorithms used to\nsolve these problems.\n",
"title": "Split-and-augmented Gibbs sampler - Application to large-scale inference problems"
} | null | null | [
"Statistics"
]
| null | true | null | 90 | null | Validated | null | null |
null | {
"abstract": " Yes, but only for a parameter value that makes it almost coincide with the\nstandard model. We reconsider the cosmological dynamics of a generalized\nChaplygin gas (gCg) which is split into a cold dark matter (CDM) part and a\ndark energy (DE) component with constant equation of state. This model, which\nimplies a specific interaction between CDM and DE, has a $\\Lambda$CDM limit and\nprovides the basis for studying deviations from the latter. Including matter\nand radiation, we use the (modified) CLASS code \\cite{class} to construct the\nCMB and matter power spectra in order to search for a gCg-based concordance\nmodel that is in agreement with the SNIa data from the JLA sample and with\nrecent Planck data. The results reveal that the gCg parameter $\\alpha$ is\nrestricted to $|\\alpha|\\lesssim 0.05$, i.e., to values very close to the\n$\\Lambda$CDM limit $\\alpha =0$. This excludes, in particular, models in which\nDE decays linearly with the Hubble rate.\n",
"title": "Does a generalized Chaplygin gas correctly describe the cosmological dark sector?"
} | null | null | null | null | true | null | 91 | null | Default | null | null |
null | {
"abstract": " The interest in the extracellular vesicles (EVs) is rapidly growing as they\nbecame reliable biomarkers for many diseases. For this reason, fast and\naccurate techniques of EVs size characterization are the matter of utmost\nimportance. One increasingly popular technique is the Nanoparticle Tracking\nAnalysis (NTA), in which the diameters of EVs are calculated from their\ndiffusion constants. The crucial assumption here is that the diffusion in NTA\nfollows the Stokes-Einstein relation, i.e. that the Mean Square Displacement\n(MSD) of a particle grows linearly in time (MSD $\\propto t$). However, we show\nthat NTA violates this assumption in both artificial and biological samples,\ni.e. a large population of particles show a strongly sub-diffusive behaviour\n(MSD $\\propto t^\\alpha$, $0<\\alpha<1$). To support this observation we present\na range of experimental results for both polystyrene beads and EVs. This is\nalso related to another problem: for the same samples there exists a huge\ndiscrepancy (by the factor of 2-4) between the sizes measured with NTA and with\nthe direct imaging methods, such as AFM. This can be remedied by e.g. the\nFinite Track Length Adjustment (FTLA) method in NTA, but its applicability is\nlimited in the biological and poly-disperse samples. On the other hand, the\nmodels of sub-diffusion rarely provide the direct relation between the size of\na particle and the generalized diffusion constant. However, we solve this last\nproblem by introducing the logarithmic model of sub-diffusion, aimed at\nretrieving the size data. In result, we propose a novel protocol of NTA data\nanalysis. The accuracy of our method is on par with FTLA for small\n($\\simeq$200nm) particles. We apply our method to study the EVs samples and\ncorroborate the results with AFM.\n",
"title": "The effects of subdiffusion on the NTA size measurements of extracellular vesicles in biological samples"
} | null | null | null | null | true | null | 92 | null | Default | null | null |
null | {
"abstract": " The processes of the averaged regression quantiles and of their modifications\nprovide useful tools in the regression models when the covariates are not fully\nunder our control. As an application we mention the probabilistic risk\nassessment in the situation when the return depends on some exogenous\nvariables. The processes enable to evaluate the expected $\\alpha$-shortfall\n($0\\leq\\alpha\\leq 1$) and other measures of the risk, recently generally\naccepted in the financial literature, but also help to measure the risk in\nenvironment analysis and elsewhere.\n",
"title": "Empirical regression quantile process with possible application to risk analysis"
} | null | null | null | null | true | null | 93 | null | Default | null | null |
null | {
"abstract": " We study primordial perturbations from hyperinflation, proposed recently and\nbased on a hyperbolic field-space. In the previous work, it was shown that the\nfield-space angular momentum supported by the negative curvature modifies the\nbackground dynamics and enhances fluctuations of the scalar fields\nqualitatively, assuming that the inflationary background is almost de Sitter.\nIn this work, we confirm and extend the analysis based on the standard approach\nof cosmological perturbation in multi-field inflation. At the background level,\nto quantify the deviation from de Sitter, we introduce the slow-varying\nparameters and show that steep potentials, which usually can not drive\ninflation, can drive inflation. At the linear perturbation level, we obtain the\npower spectrum of primordial curvature perturbation and express the spectral\ntilt and running in terms of the slow-varying parameters. We show that\nhyperinflation with power-law type potentials has already been excluded by the\nrecent Planck observations, while exponential-type potential with the exponent\nof order unity can be made consistent with observations as far as the power\nspectrum is concerned. We also argue that, in the context of a simple $D$-brane\ninflation, the hyperinflation requires exponentially large hyperbolic extra\ndimensions but that masses of Kaluza-Klein gravitons can be kept relatively\nheavy.\n",
"title": "Primordial perturbations from inflation with a hyperbolic field-space"
} | null | null | null | null | true | null | 94 | null | Default | null | null |
null | {
"abstract": " Vanadium pentoxide (V2O5), the most stable member of vanadium oxide family,\nexhibits interesting semiconductor to metal transition in the temperature range\nof 530-560 K. The metallic behavior originates because of the reduction of V2O5\nthrough oxygen vacancies. In the present report, V2O5 nanorods in the\northorhombic phase with crystal orientation of (001) are grown using vapor\ntransport process. Among three nonequivalent oxygen atoms in a VO5 pyramidal\nformula unit in V2O5 structure, the role of terminal vanadyl oxygen (OI) in the\nformation of metallic phase above the transition temperature is established\nfrom the temperature-dependent Raman spectroscopic studies. The origin of the\nmetallic behavior of V2O5 is also understood due to the breakdown of pdpi bond\nbetween OI and nearest V atom instigated by the formation of vanadyl OI\nvacancy, confirmed from the downward shift of the bottom most split-off\nconduction bands in the material with increasing temperature.\n",
"title": "Role of Vanadyl Oxygen in Understanding Metallic Behavior of V2O5(001) Nanorods"
} | null | null | null | null | true | null | 95 | null | Default | null | null |
null | {
"abstract": " In this paper, we presented a novel convolutional neural network framework\nfor graph modeling, with the introduction of two new modules specially designed\nfor graph-structured data: the $k$-th order convolution operator and the\nadaptive filtering module. Importantly, our framework of High-order and\nAdaptive Graph Convolutional Network (HA-GCN) is a general-purposed\narchitecture that fits various applications on both node and graph centrics, as\nwell as graph generative models. We conducted extensive experiments on\ndemonstrating the advantages of our framework. Particularly, our HA-GCN\noutperforms the state-of-the-art models on node classification and molecule\nproperty prediction tasks. It also generates 32% more real molecules on the\nmolecule generation task, both of which will significantly benefit real-world\napplications such as material design and drug screening.\n",
"title": "Graph Convolution: A High-Order and Adaptive Approach"
} | null | null | null | null | true | null | 96 | null | Default | null | null |
null | {
"abstract": " A variety of representation learning approaches have been investigated for\nreinforcement learning; much less attention, however, has been given to\ninvestigating the utility of sparse coding. Outside of reinforcement learning,\nsparse coding representations have been widely used, with non-convex objectives\nthat result in discriminative representations. In this work, we develop a\nsupervised sparse coding objective for policy evaluation. Despite the\nnon-convexity of this objective, we prove that all local minima are global\nminima, making the approach amenable to simple optimization strategies. We\nempirically show that it is key to use a supervised objective, rather than the\nmore straightforward unsupervised sparse coding approach. We compare the\nlearned representations to a canonical fixed sparse representation, called\ntile-coding, demonstrating that the sparse coding representation outperforms a\nwide variety of tilecoding representations.\n",
"title": "Learning Sparse Representations in Reinforcement Learning with Sparse Coding"
} | null | null | null | null | true | null | 97 | null | Default | null | null |
null | {
"abstract": " Motivated by Perelman's Pseudo Locality Theorem for the Ricci flow, we prove\nthat if a Riemannian manifold has Ricci curvature bounded below in a metric\nball which moreover has almost maximal volume, then in a smaller ball (in a\nquantified sense) it holds an almost-euclidean isoperimetric inequality. The\nresult is actually established in the more general framework of non-smooth\nspaces satisfying local Ricci curvature lower bounds in a synthetic sense via\noptimal transportation.\n",
"title": "Almost euclidean Isoperimetric Inequalities in spaces satisfying local Ricci curvature lower bounds"
} | null | null | null | null | true | null | 98 | null | Default | null | null |
null | {
"abstract": " We bound an exponential sum that appears in the study of irregularities of\ndistribution (the low-frequency Fourier energy of the sum of several Dirac\nmeasures) by geometric quantities: a special case is that for all $\\left\\{ x_1,\n\\dots, x_N\\right\\} \\subset \\mathbb{T}^2$, $X \\geq 1$ and a universal $c>0$ $$\n\\sum_{i,j=1}^{N}{ \\frac{X^2}{1 + X^4 \\|x_i -x_j\\|^4}} \\lesssim \\sum_{k \\in\n\\mathbb{Z}^2 \\atop \\|k\\| \\leq X}{ \\left| \\sum_{n=1}^{N}{ e^{2 \\pi i\n\\left\\langle k, x_n \\right\\rangle}}\\right|^2} \\lesssim \\sum_{i,j=1}^{N}{ X^2\ne^{-c X^2\\|x_i -x_j\\|^2}}.$$ Since this exponential sum is intimately tied to\nrather subtle distribution properties of the points, we obtain nonlocal\nstructural statements for near-minimizers of the Riesz-type energy. In the\nregime $X \\gtrsim N^{1/2}$ both upper and lower bound match for\nmaximally-separated point sets satisfying $\\|x_i -x_j\\| \\gtrsim N^{-1/2}$.\n",
"title": "Exponential Sums and Riesz energies"
} | null | null | null | null | true | null | 99 | null | Default | null | null |
null | {
"abstract": " We investigate the effect of dimensional crossover in the ground state of the\nantiferromagnetic spin-$1$ Heisenberg model on the anisotropic triangular\nlattice that interpolates between the regime of weakly coupled Haldane chains\n($J^{\\prime}\\! \\!\\ll\\!\\! J$) and the isotropic triangular lattice\n($J^{\\prime}\\!\\!=\\!\\!J$). We use the density-matrix renormalization group\n(DMRG) and Schwinger boson theory performed at the Gaussian correction level\nabove the saddle-point solution. Our DMRG results show an abrupt transition\nbetween decoupled spin chains and the spirally ordered regime at\n$(J^{\\prime}/J)_c\\sim 0.42$, signaled by the sudden closing of the spin gap.\nComing from the magnetically ordered side, the computation of the spin\nstiffness within Schwinger boson theory predicts the instability of the spiral\nmagnetic order toward a magnetically disordered phase with one-dimensional\nfeatures at $(J^{\\prime}/J)_c \\sim 0.43$. The agreement of these complementary\nmethods, along with the strong difference found between the intra- and the\ninterchain DMRG short spin-spin correlations; for sufficiently large values of\nthe interchain coupling, suggests that the interplay between the quantum\nfluctuations and the dimensional crossover effects gives rise to the\none-dimensionalization phenomenon in this frustrated spin-$1$ Hamiltonian.\n",
"title": "One dimensionalization in the spin-1 Heisenberg model on the anisotropic triangular lattice"
} | null | null | null | null | true | null | 100 | null | Default | null | null |
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