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arxiv_dataset-98001805.06955
Coupling Levy measures and comparison principles for viscosity solutions math.AP We prove new comparison principles for viscosity solutions of non-linear integro-differential equations. The operators to which the method applies include but are not limited to those of L\'evy-It\^o type. The main idea is to use an optimal transport map to couple two different L\'evy measures, and use the resulting coupling in a doubling of variables argument
arxiv topic:math.AP
arxiv_dataset-98011805.07055
Surjectivity in Fr\'echet spaces math.FA We prove surjectivity result in Fr\'echet spaces of Nash-Moser type. That is, with uniform estimates over all semimorms. Our method works for functions which are only continuous and G\^ateaux differentiable like in the recent result of Ekeland. We present the results in multi-valued setting exploring the relevant notions of map regularity.
arxiv topic:math.FA
arxiv_dataset-98021805.07155
Partial Cartesian Graph Product cs.PL math.CO In this paper we define a new product-like binary operation on directed graphs, and we discuss some of its properties. We also briefly discuss its application in constructing the subtyping relation in generic nominally-typed object-oriented programming languages.
arxiv topic:cs.PL math.CO
arxiv_dataset-98031805.07255
A convergent finite difference scheme for the Ostrovsky--Hunter equation with Dirichlet boundary conditions math.AP We prove convergence of a finite difference scheme to the unique entropy solution of a general form of the Ostrovsky--Hunter equation on a bounded domain with non-homogeneous Dirichlet boundary conditions. Our scheme is an extension of monotone schemes for conservation laws to the equation at hand. The convergence result at the center of this article also proves existence of entropy solutions for the initial-boundary value prob lem for the general Ostrovsky--Hunter equation. Additionally, we show uniqueness using Kru\v{z}kov's doubling of variables technique. We also include numerical examples to confirm the convergence results and determine rates of convergence experimentally.
arxiv topic:math.AP
arxiv_dataset-98041805.07355
The Sub-Geometric Phases in Density Matrix quant-ph In this letter, the generalization of geometric phase in density matrix is presented, we show that the extended sub-geometric phase have unified expression whatever in adiabatic or nonadiabatic procedure, the relations between them and the usual Berry phase or Aharonov-Anandan phase are established. We also demonstrated the influence of sub-geometric phases on the physical observables. Finally, our treatment is naturally used to investigate the geometric phase in mixed state.
arxiv topic:quant-ph
arxiv_dataset-98051805.07455
Subspace Selection via DR-Submodular Maximization on Lattices cs.DS The subspace selection problem seeks a subspace that maximizes an objective function under some constraint. This problem includes several important machine learning problems such as the principal component analysis and sparse dictionary selection problem. Often, these problems can be solved by greedy algorithms. Here, we are interested in why these problems can be solved by greedy algorithms, and what classes of objective functions and constraints admit this property. To answer this question, we formulate the problems as optimization problems on lattices. Then, we introduce a new class of functions, directional DR-submodular functions, to characterize the approximability of problems. We see that the principal component analysis, sparse dictionary selection problem, and these generalizations have directional DR-submodularities. We show that, under several constraints, the directional DR-submodular function maximization problem can be solved efficiently with provable approximation factors.
arxiv topic:cs.DS
arxiv_dataset-98061805.07555
Second-order photonic topological insulator with corner states cond-mat.mtrl-sci Higher-order topological insulators (HOTIs) which go beyond the description of conventional bulk-boundary correspondence, broaden the understanding of topological insulating phases. Being mainly focused on electronic materials, HOTIs have not been found in photonic systems yet. In this article, we propose a type of two-dimensional second-order photonic crystals with zero-dimensional corner states and one-dimensional boundary states for optical frequencies. All of these states are topologically non-trivial and can be understood based on the theory of topological polarization. Moreover, by tuning the easily-fabricated structure of the photonic crystals, we can realize different topological phases with unique topological boundary states straightforwardly. Our result can be generalized to higher dimensions and provides unprecedented venues for higher-order photonic topological insulators and semimetals.
arxiv topic:cond-mat.mtrl-sci
arxiv_dataset-98071805.07655
Coboundaries of nonconventional ergodic averages math.DS Let $(X,\mathcal{A}, \mu)$ be a probability measure space and let $T_i,$ $1\leq i\leq H,$ be invertible bi measurable measure preserving transformations on this measure space. We give a sufficient condition for the product of $H$ bounded functions $f_1, f_2, ..., f_H$ to be a coboundary. This condition turns out to be also necessary when one seeks bounded coboundaries.
arxiv topic:math.DS
arxiv_dataset-98081805.07755
Dunkl jump processes: relaxation and a phase transition math-ph math.MP math.PR Dunkl processes are multidimensional Markov processes defined through the use of Dunkl operators. These processes have discontinuities, and they can be separated into their continuous (radial) part, and their discontinuous (jump) part. While radial Dunkl processes have been studied thoroughly due to their relationship to families of stochastic particle systems such as the Dyson model and Wishart-Laguerre processes, Dunkl jump processes have gone largely unnoticed after the initial work of Gallardo, Yor and Chybiryakov. We study the dynamical properties of these processes, and we derive their master equation. By calculating the asymptotic behavior of their total jump rate, we find that the jump processes of types $A_{N-1}$ and $B_N$ undergo a phase transition when the parameter $\beta$ decreases toward one in the bulk scaling limit. In addition, we show that the relaxation behavior of these processes is given by a non-trivial power law, and formulate a conjecture for the jump rate asymptotics based on numerical simulations.
arxiv topic:math-ph math.MP math.PR
arxiv_dataset-98091805.07855
Squares of Tribonacci numbers math.CO We prove some identities for the squares of generalized Tribonacci numbers. Various summation identities involving these numbers are derived.
arxiv topic:math.CO
arxiv_dataset-98101805.07955
Regularity for fully nonlinear integro-differential operators with kernels of variable orders math.AP We consider fully nonlinear elliptic integro-differential operators with kernels of variable orders, which generalize the integro-differential operators of the fractional Laplacian type in \cite{CS}. Since the order of differentiability of the kernel is not characterized by a single number, we use the constant \begin{align*} C_\varphi = \left( \int_{\mathbb{R}^n} \frac{1-\cos y_1}{\vert y \vert^n \varphi (\vert y \vert)} \, dy \right)^{-1} \end{align*} instead of $2-\sigma$, where $\varphi$ satisfies a weak scaling condition. We obtain the uniform Harnack inequality and H\"older estimates of viscosity solutions to the nonlinear integro-differential equations.
arxiv topic:math.AP
arxiv_dataset-98111805.08055
Higher spin supercurrents in anti-de Sitter space hep-th math-ph math.MP We propose higher spin supercurrent multiplets for ${\cal N}=1$ supersymmetric field theories in four-dimensional anti-de Sitter space (AdS). Their explicit realisations are derived for various supersymmetric theories, including a model of $N$ massive chiral scalar superfields with an arbitrary mass matrix. We also present new off-shell gauge formulations for the massless ${\cal N}=1$ supersymmetric multiplet of integer superspin $s$ in AdS, where $s =2,3,\dots$, as well as for the massless gravitino multiplet (superspin $s=1$) which requires special consideration.
arxiv topic:hep-th math-ph math.MP
arxiv_dataset-98121805.08155
Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry cond-mat.mtrl-sci The Gibbs energy, G, determines the equilibrium conditions of chemical reactions and materials stability. Despite this fundamental and ubiquitous role, G has been tabulated for only a small fraction of known inorganic compounds, impeding a comprehensive perspective on the effects of temperature and composition on materials stability and synthesizability. Here, we use the SISSO (sure independence screening and sparsifying operator) approach to identify a simple and accurate descriptor to predict G for stoichiometric inorganic compounds with ~50 meV/atom (~1 kcal/mol) resolution, and with minimal computational cost, for temperatures ranging from 300-1800 K. We then apply this descriptor to ~30,000 known materials curated from the Inorganic Crystal Structure Database (ICSD). Using the resulting predicted thermochemical data, we generate thousands of temperature-dependent phase diagrams to provide insights into the effects of temperature and composition on materials synthesizability and stability and to establish the temperature-dependent scale of metastability for inorganic compounds.
arxiv topic:cond-mat.mtrl-sci
arxiv_dataset-98131805.08255
Algorithmic and algebraic aspects of unshuffling permutations cs.DS math.CO A permutation is said to be a square if it can be obtained by shuffling two order-isomorphic patterns. The definition is intended to be the natural counterpart to the ordinary shuffle of words and languages. In this paper, we tackle the problem of recognizing square permutations from both the point of view of algebra and algorithms. On the one hand, we present some algebraic and combinatorial properties of the shuffle product of permutations. We follow an unusual line consisting in defining the shuffle of permutations by means of an unshuffling operator, known as a coproduct. This strategy allows to obtain easy proofs for algebraic and combinatorial properties of our shuffle product. We besides exhibit a bijection between square $(213,231)$-avoiding permutations and square binary words. On the other hand, by using a pattern avoidance criterion on directed perfect matchings, we prove that recognizing square permutations is {\bf NP}-complete.
arxiv topic:cs.DS math.CO
arxiv_dataset-98141805.08355
Opening the black box of deep learning cs.LG stat.ML The great success of deep learning shows that its technology contains profound truth, and understanding its internal mechanism not only has important implications for the development of its technology and effective application in various fields, but also provides meaningful insights into the understanding of human brain mechanism. At present, most of the theoretical research on deep learning is based on mathematics. This dissertation proposes that the neural network of deep learning is a physical system, examines deep learning from three different perspectives: microscopic, macroscopic, and physical world views, answers multiple theoretical puzzles in deep learning by using physics principles. For example, from the perspective of quantum mechanics and statistical physics, this dissertation presents the calculation methods for convolution calculation, pooling, normalization, and Restricted Boltzmann Machine, as well as the selection of cost functions, explains why deep learning must be deep, what characteristics are learned in deep learning, why Convolutional Neural Networks do not have to be trained layer by layer, and the limitations of deep learning, etc., and proposes the theoretical direction and basis for the further development of deep learning now and in the future. The brilliance of physics flashes in deep learning, we try to establish the deep learning technology based on the scientific theory of physics.
arxiv topic:cs.LG stat.ML
arxiv_dataset-98151805.08455
Context-Aware Sequence-to-Sequence Models for Conversational Systems cs.CL cs.AI This work proposes a novel approach based on sequence-to-sequence (seq2seq) models for context-aware conversational systems. Exist- ing seq2seq models have been shown to be good for generating natural responses in a data-driven conversational system. However, they still lack mechanisms to incorporate previous conversation turns. We investigate RNN-based methods that efficiently integrate previous turns as a context for generating responses. Overall, our experimental results based on human judgment demonstrate the feasibility and effectiveness of the proposed approach.
arxiv topic:cs.CL cs.AI
arxiv_dataset-98161805.08555
MoMEMta, a modular toolkit for the Matrix Element Method at the LHC hep-ph hep-ex The Matrix Element Method has proven to be a powerful method to optimally exploit the information available in detector data. Its widespread use is nevertheless impeded by its complexity and the associated computing time. MoMEMta, a C++ software package to compute the integrals at the core of the method, provides a versatile implementation of the Matrix Element Method to both the theory and experiment communities. Its modular structure covers the needs of experimental analysis workflows at the LHC without compromising ease of use on simpler and smaller simulated samples used for phenomenological studies. With respect to existing tools, MoMEMta improves on usability and flexibility. In this paper, we present version 1.0 of MoMEMta, together with examples illustrating the wide range of applications at the LHC accessible for the first time with a single tool.
arxiv topic:hep-ph hep-ex
arxiv_dataset-98171805.08655
The first 62 AGN observed with SDSS-IV MaNGA - II: resolved stellar populations astro-ph.GA We present spatially resolved stellar population age maps, average radial profiles and gradients for the first 62 Active Galactic Nuclei (AGN) observed with SDSS-IV MaNGA to study the effects of the active nuclei on the star formation history of the host galaxies. These results, derived using the STARLIGHT code, are compared with a control sample of non-active galaxies matching the properties of the AGN hosts. We find that the fraction of young stellar populations (SP) in high-luminosity AGN is higher in the inner ($R \leq 0.5\,R_e$) regions when compared with the control sample; low-luminosity AGN, on the other hand, present very similar fractions of young stars to the control sample hosts for the entire studied range ($1\,R_e$). The fraction of intermediate age SP of the AGN hosts increases outwards, with a clear enhancement when compared with the control sample. The inner region of the galaxies (AGN and control galaxies) presents a dominant old SP, whose fraction decreases outwards. We also compare our results (differences between AGN and control galaxies) for the early and late-type hosts and find no significant differences. In summary, our results suggest that the most luminous AGN seems to have been triggered by a recent supply of gas that has also triggered recent star formation ($t\,\leq\,40\,Myrs$) in the central region.
arxiv topic:astro-ph.GA
arxiv_dataset-98181805.08755
Energy-aware tree network formation among computationally weak nodes cs.NI cs.DC We study the fundamental problem of distributed network formation among mobile agents of limited computational power that aim to achieve energy balance by wirelessly transmitting and receiving energy in a peer-to-peer manner. Specifically, we design simple distributed protocols consisting of a small number of states and interaction rules for the formation of arbitrary and k-ary tree networks. Furthermore, we evaluate (theoretically and also using computer simulations) a plethora of energy redistribution protocols that exploit different levels of knowledge in order to achieve desired energy distributions among the agents which require that every agent has exactly or at least twice the energy of the agents of higher depth, according to the structure of the network. Our study shows that without using any knowledge about the network structure, such energy distributions cannot be achieved in a timely manner, meaning that there might be high energy loss during the redistribution process. On the other hand, only a few extra bits of information seem to be enough to guarantee quick convergence to energy distributions that satisfy particular properties, yielding low energy loss.
arxiv topic:cs.NI cs.DC
arxiv_dataset-98191805.08855
Rate-Optimal Denoising with Deep Neural Networks cs.IT cs.LG eess.SP math.IT math.OC Deep neural networks provide state-of-the-art performance for image denoising, where the goal is to recover a near noise-free image from a noisy observation. The underlying principle is that neural networks trained on large datasets have empirically been shown to be able to generate natural images well from a low-dimensional latent representation of the image. Given such a generator network, a noisy image can be denoised by i) finding the closest image in the range of the generator or by ii) passing it through an encoder-generator architecture (known as an autoencoder). However, there is little theory to justify this success, let alone to predict the denoising performance as a function of the network parameters. In this paper we consider the problem of denoising an image from additive Gaussian noise using the two generator based approaches. In both cases, we assume the image is well described by a deep neural network with ReLU activations functions, mapping a $k$-dimensional code to an $n$-dimensional image. In the case of the autoencoder, we show that the feedforward network reduces noise energy by a factor of $O(k/n)$. In the case of optimizing over the range of a generative model, we state and analyze a simple gradient algorithm that minimizes a non-convex loss function, and provably reduces noise energy by a factor of $O(k/n)$. We also demonstrate in numerical experiments that this denoising performance is, indeed, achieved by generative priors learned from data.
arxiv topic:cs.IT cs.LG eess.SP math.IT math.OC
arxiv_dataset-98201805.08955
Coded Caching via Line Graphs of Bipartite Graphs cs.IT math.IT We present a coded caching framework using line graphs of bipartite graphs. A clique cover of the line graph describes the uncached subfiles at users. A clique cover of the complement of the square of the line graph gives a transmission scheme that satisfies user demands. We then define a specific class of such caching line graphs, for which the subpacketization, rate, and uncached fraction of the coded caching problem can be captured via its graph theoretic parameters. We present a construction of such caching line graphs using projective geometry. The presented scheme has a rate bounded from above by a constant with subpacketization level $q^{O((log_qK)^2)}$ and uncached fraction $\Theta(\frac{1}{\sqrt{K}})$, where $K$ is the number of users and $q$ is a prime power. We also present a subpacketization-dependent lower bound on the rate of coded caching schemes for a given broadcast setup.
arxiv topic:cs.IT math.IT
arxiv_dataset-98211805.09055
Grounding the Semantics of Part-of-Day Nouns Worldwide using Twitter cs.CL The usage of part-of-day nouns, such as 'night', and their time-specific greetings ('good night'), varies across languages and cultures. We show the possibilities that Twitter offers for studying the semantics of these terms and its variability between countries. We mine a worldwide sample of multilingual tweets with temporal greetings, and study how their frequencies vary in relation with local time. The results provide insights into the semantics of these temporal expressions and the cultural and sociological factors influencing their usage.
arxiv topic:cs.CL
arxiv_dataset-98221805.09155
AdGraph: A Graph-Based Approach to Ad and Tracker Blocking cs.CY cs.LG User demand for blocking advertising and tracking online is large and growing. Existing tools, both deployed and described in research, have proven useful, but lack either the completeness or robustness needed for a general solution. Existing detection approaches generally focus on only one aspect of advertising or tracking (e.g. URL patterns, code structure), making existing approaches susceptible to evasion. In this work we present AdGraph, a novel graph-based machine learning approach for detecting advertising and tracking resources on the web. AdGraph differs from existing approaches by building a graph representation of the HTML structure, network requests, and JavaScript behavior of a webpage, and using this unique representation to train a classifier for identifying advertising and tracking resources. Because AdGraph considers many aspects of the context a network request takes place in, it is less susceptible to the single-factor evasion techniques that flummox existing approaches. We evaluate AdGraph on the Alexa top-10K websites, and find that it is highly accurate, able to replicate the labels of human-generated filter lists with 95.33% accuracy, and can even identify many mistakes in filter lists. We implement AdGraph as a modification to Chromium. AdGraph adds only minor overhead to page loading and execution, and is actually faster than stock Chromium on 42% of websites and AdBlock Plus on 78% of websites. Overall, we conclude that AdGraph is both accurate enough and performant enough for online use, breaking comparable or fewer websites than popular filter list based approaches.
arxiv topic:cs.CY cs.LG
arxiv_dataset-98231805.09255
Cache-Aware QoE-Traffic Optimization in Mobile Edge Assisted Adaptive Video Streaming cs.NI Multi-access edge computing (MEC) enables placing video content at the edge of the network aiming to improve the quality of experience (QoE) of the mobile clients. Video content caching at edge servers also reduces traffic in the backhaul of the mobile network, hence reducing operational costs for mobile network operators (MNOs). However, minimizing the rate of cache misses and maximizing the average video quality may sometimes be at odds with each other, particularly when the cache size is constrained. Our objective in this article is two fold: First, we explore the impact of fixed video content caching on the optimal QoE of mobile clients in a setup where servers at mobile network edge handle bitrate selection. Second, we want to investigate the effect of cache replacement on QoE-traffic trade-off. An integer nonlinear programming (INLP) optimization model is formulated for the problem of jointly maximizing the QoE, the fairness as well as minimizing overall data traffic on the origin video server. Due to its NP-Hardness, we then present a low complexity greedy-based algorithm with minimum need for parameter tuning which can be easily deployed. We show through simulations that the joint optimization indeed enables striking a desired trade-off between traffic reduction and QoE. The results also reveal that with fixed cached contents, the impact of caching on the QoE is proportional to the desired operational point of MNO. Furthermore, the effect of cache replacement on QoE is less noticeable compared to its effect on backhaul traffic when cache size is constrained.
arxiv topic:cs.NI
arxiv_dataset-98241805.09355
Scoring Lexical Entailment with a Supervised Directional Similarity Network cs.CL cs.LG cs.NE We present the Supervised Directional Similarity Network (SDSN), a novel neural architecture for learning task-specific transformation functions on top of general-purpose word embeddings. Relying on only a limited amount of supervision from task-specific scores on a subset of the vocabulary, our architecture is able to generalise and transform a general-purpose distributional vector space to model the relation of lexical entailment. Experiments show excellent performance on scoring graded lexical entailment, raising the state-of-the-art on the HyperLex dataset by approximately 25%.
arxiv topic:cs.CL cs.LG cs.NE
arxiv_dataset-98251805.09455
On BPS World Volume, RR Couplings and their $\alpha'$ Corrections in type IIB hep-th gr-qc hep-ph We compute the asymmetric and symmetric correlation functions of a four point amplitude of a gauge field, a scalar field and a closed string Ramond-Ramond (RR) for different non-vanishing BPS branes. All world volume, Taylor and pull-back couplings and their all order $\alpha'$ corrections have also been explored. Due to various symmetry structures, different restricted BPS Bianchi identities have also been constructed. The prescription of exploring all the corrections of two closed string RR couplings in type IIB is given. We obtain the closed form of the entire S-matrix elements of two closed string RR and a gauge field on the world volume of BPS branes in type IIB. All the correlation functions of $< V_{A^{0}(x_1)}V_{C^{-1}(z_1,\bar{z}_1)}V_{C^{-1}(z_2,\bar{z}_2)}>$ are also revealed accordingly. The algebraic forms for the most general case of the integrations $\int d^2z |z-i|^{a} |z+i|^{b} (z - \bar{z})^{c} (z + \bar{z})^{d}$ on upper half plane are derived in terms of Pochhammer and some analytic functions. Lastly, we generate various singularity structures in both effective field theory and IIB string theory, producing different contact interactions as well as their $\alpha'$ higher derivative corrections.
arxiv topic:hep-th gr-qc hep-ph
arxiv_dataset-98261805.09555
Phase Retrieval via Polytope Optimization: Geometry, Phase Transitions, and New Algorithms cs.IT math.IT We study algorithms for solving quadratic systems of equations based on optimization methods over polytopes. Our work is inspired by a recently proposed convex formulation of the phase retrieval problem, which estimates the unknown signal by solving a simple linear program over a polytope constructed from the measurements. We present a sharp characterization of the high-dimensional geometry of the aforementioned polytope under Gaussian measurements. This characterization allows us to derive asymptotically exact performance guarantees for PhaseMax, which also reveal a phase transition phenomenon with respect to its sample complexity. Moreover, the geometric insights gained from our analysis lead to a new nonconvex formulation of the phase retrieval problem and an accompanying iterative algorithm, which we call PhaseLamp. We show that this new algorithm has superior recovery performance over the original PhaseMax method. Finally, as yet another variation on the theme of performing phase retrieval via polytope optimization, we propose a weighted version of PhaseLamp and demonstrate, through numerical simulations, that it outperforms several state-of-the-art algorithms under both generic Gaussian measurements as well as more realistic Fourier-type measurements that arise in phase retrieval applications.
arxiv topic:cs.IT math.IT
arxiv_dataset-98271805.09655
Global-Locally Self-Attentive Dialogue State Tracker cs.CL cs.AI Dialogue state tracking, which estimates user goals and requests given the dialogue context, is an essential part of task-oriented dialogue systems. In this paper, we propose the Global-Locally Self-Attentive Dialogue State Tracker (GLAD), which learns representations of the user utterance and previous system actions with global-local modules. Our model uses global modules to share parameters between estimators for different types (called slots) of dialogue states, and uses local modules to learn slot-specific features. We show that this significantly improves tracking of rare states and achieves state-of-the-art performance on the WoZ and DSTC2 state tracking tasks. GLAD obtains 88.1% joint goal accuracy and 97.1% request accuracy on WoZ, outperforming prior work by 3.7% and 5.5%. On DSTC2, our model obtains 74.5% joint goal accuracy and 97.5% request accuracy, outperforming prior work by 1.1% and 1.0%.
arxiv topic:cs.CL cs.AI
arxiv_dataset-98281805.09755
Microreversibility, nonequilibrium current fluctuations, and response theory cond-mat.stat-mech Microreversibility rules the fluctuations of the currents flowing across open systems in nonequilibrium (or equilibrium) steady states. As a consequence, the statistical cumulants of the currents and their response coefficients at arbitrary orders in the deviations from equilibrium obey time-reversal symmetry relations. It is shown that these relations allow us to systematically reduce the amount of independent quantities that need to be measured experimentally or computed theoretically in order to fully characterize the linear and nonlinear transport properties of general open systems. This reduction is shown to approach one half for quantities of arbitrarily high orders.
arxiv topic:cond-mat.stat-mech
arxiv_dataset-98291805.09855
MINLO t-channel single-top plus jet hep-ph We present a next-to-leading order accurate simulation of t-channel single-top plus jet production matched to parton showers via the POWHEG method. The calculation underlying the simulation is enhanced with a process-specific implementation of the multi-scale improved NLO (MINLO) method, such that it gives physical predictions all through phase space, including regions where the jet additional to the t-channel single-top process is unresolved. We further describe a tuning procedure for the MINLO Sudakov form factor, fitting the coefficient of the first subleading term in its exponent using an artificial neural-network. The latter tuning, implemented as a straightforward event-by-event reweighting, renders the MINLO simulation NLO accurate for t-channel single-top observables, in addition to those of the analogous single-top plus jet process.
arxiv topic:hep-ph
arxiv_dataset-98301805.09955
Continuous-stage Runge-Kutta methods based on weighted orthogonal polynomials math.NA We develop continuous-stage Runge-Kutta methods based on weighted orthogonal polynomials in this paper. There are two main highlighted merits for developing such methods: Firstly, we do not need to study the tedious solution of multi-variable nonlinear algebraic equations associated with order conditions; Secondly, the well-known weighted interpolatory quadrature theory appeared in every numerical analysis textbook can be directly and conveniently used. By introducing weight function, various orthogonal polynomials can be used in the construction of Runge-Kutta-type methods. It turns out that new families of Runge-Kutta-type methods with special properties (e.g., symplectic, symmetric etc.) can be constructed in batches, and hopefully it may produce new applications in numerical ordinary differential equations.
arxiv topic:math.NA
arxiv_dataset-98311805.10055
Parabolicity criteria and characterization results for submanifolds of bounded mean curvature in model manifolds with weights math.DG math.AP Let $P$ be a submanifold properly immersed in a rotationally symmetric manifold having a pole and endowed with a weight $e^h$. The aim of this paper is twofold. First, by assuming certain control on the $h$-mean curvature of $P$, we establish comparisons for the $h$-capacity of extrinsic balls in $P$, from which we deduce criteria ensuring the $h$-parabolicity or $h$-hyperbolicity of $P$. Second, we employ functions with geometric meaning to describe submanifolds of bounded $h$-mean curvature which are confined into some regions of the ambient manifold. As a consequence, we derive half-space and Bernstein-type theorems generalizing previous ones. Our results apply for some relevant $h$-minimal submanifolds appearing in the singularity theory of the mean curvature flow.
arxiv topic:math.DG math.AP
arxiv_dataset-98321805.10155
Bistability of a slow mechanical oscillator coupled to a laser-driven two-level system cond-mat.mes-hall quant-ph It has been recently proposed that single molecule spectroscopy could be employed to detect the motion of nano-mechanical resonators. Estimates of the coupling constant (g) between the molecular two-level system and the oscillator indicate that it can reach values much larger than the mechanical resonating pulsation (omega_m) and the two-level system linewidth (Gamma). Other experimental realization of the same system are also approching this strong coupling regim. In this paper we investigate the behavior of the system in the limit for slow mechanical oscillator omega_m << Gamma}. We find that, for sufficiently large coupling, the system undergoes a bistability reminiscent of that observed in optical cavities coupled to mechanical resonators.
arxiv topic:cond-mat.mes-hall quant-ph
arxiv_dataset-98331805.10255
Parallel Architecture and Hyperparameter Search via Successive Halving and Classification cs.CV cs.AI cs.LG cs.NE We present a simple and powerful algorithm for parallel black box optimization called Successive Halving and Classification (SHAC). The algorithm operates in $K$ stages of parallel function evaluations and trains a cascade of binary classifiers to iteratively cull the undesirable regions of the search space. SHAC is easy to implement, requires no tuning of its own configuration parameters, is invariant to the scale of the objective function and can be built using any choice of binary classifier. We adopt tree-based classifiers within SHAC and achieve competitive performance against several strong baselines for optimizing synthetic functions, hyperparameters and architectures.
arxiv topic:cs.CV cs.AI cs.LG cs.NE
arxiv_dataset-98341805.10355
What Face and Body Shapes Can Tell About Height cs.CV Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance, however, it is also very challenging due to the absence of absolute scale information. We tackle the rarely addressed case, where camera parameters and scene geometry is unknown. To nevertheless resolve the inherent scale ambiguity, we infer height from statistics that are intrinsic to human anatomy and can be estimated from images directly, such as articulated pose, bone length proportions, and facial features. Our contribution is twofold. First, we experiment with different machine learning models to capture the relation between image content and human height. Second, we show that performance is predominantly limited by dataset size and create a new dataset that is three magnitudes larger, by mining explicit height labels and propagating them to additional images through face recognition and assignment consistency. Our evaluation shows that monocular height estimation is possible with a MAE of 5.56cm.
arxiv topic:cs.CV
arxiv_dataset-98351805.10455
Cosmological backreaction and its dependence on spacetime foliation gr-qc astro-ph.CO hep-th The subject of cosmological backreaction in General Relativity is often approached by coordinate-dependent and metric-based analyses. We present in this letter an averaging formalism for the scalar parts of Einstein's equations that is coordinate-independent and only functionally depends on a metric. This formalism is applicable to general 3+1 foliations of spacetime for an arbitrary fluid with tilted flow. We clarify the dependence on spacetime foliation and argue that this dependence is weak in cosmological settings. We also introduce a new set of averaged equations that feature a global cosmological time despite the generality of the setting, and we put the statistical nature of effective cosmologies into perspective.
arxiv topic:gr-qc astro-ph.CO hep-th
arxiv_dataset-98361805.10555
Molecular dynamics studies of interaction between asphaltenes and solvents physics.chem-ph Understanding of the molecular interaction between asphaltenes and other molecules, which may act as its solvents, provides insights into the nature of its stability in petroleum fluids and its phase transitions. Molecular dynamics simulations were performed and reported here on systems consisting of a single asphaltene molecule and pure solvents. Three types of asphaltenes with different architectures, molecular weights, and heteroatoms content were investigated. Water and ortho-xylene were selected to be the interacting solvents. All simulations were performed by using GROMACS software. OPLS_AA potential model for hydrocarbons and SPC/E potential model for water were used in simulations. It was shown that the polar functional groups in asphaltenes were responsible for generating hydrogen bonds (HBs) between asphaltenes and water. It was also demonstrated that both electrostatic (ES) and van der Waals (vdW) interaction energies between asphaltenes and water had important roles. On the contrary, ES between asphaltenes and ortho-xylene had a minor effect as compared with the vdW. In all cases, potential energies increased rather slightly when the pressure was boosted. Moreover, they decreased noticeably when the temperature was raised. HBs between asphaltenes and water were not influenced by pressure change. Additionally, they increased slightly when the temperature was dropped.
arxiv topic:physics.chem-ph
arxiv_dataset-98371805.10655
On Late Time Tails in an Extreme Reissner-Nordstr\"om Black Hole: Frequency Domain Analysis gr-qc hep-th In this brief note, we revisit the study of the leading order late time decay tails of massless scalar perturbations outside an extreme Reissner-Nordstr\"om black hole. Previous authors have analysed this problem in the time domain; we analyse the problem in the frequency domain. We first consider initial perturbations with generic regular behaviour across the horizon on characteristic surfaces. For this set-up, we reproduce some of the previous results of Sela [arXiv:1510.06169] using Fourier methods. Next, we consider related initial data on $t=\mbox{const}$ hypersurfaces, and present decay results at timelike infinity, near future null infinity, and near the future horizon. Along the way, using the $r_* \to -r_*$ inversion symmetry of the extreme Reissner-Nordstr\"om spacetime, we relate the higher multipole Aretakis and Newman-Penrose constants for a massless scalar in this background.
arxiv topic:gr-qc hep-th
arxiv_dataset-98381805.10755
Dual Policy Iteration cs.LG stat.ML Recently, a novel class of Approximate Policy Iteration (API) algorithms have demonstrated impressive practical performance (e.g., ExIt from [2], AlphaGo-Zero from [27]). This new family of algorithms maintains, and alternately optimizes, two policies: a fast, reactive policy (e.g., a deep neural network) deployed at test time, and a slow, non-reactive policy (e.g., Tree Search), that can plan multiple steps ahead. The reactive policy is updated under supervision from the non-reactive policy, while the non-reactive policy is improved with guidance from the reactive policy. In this work we study this Dual Policy Iteration (DPI) strategy in an alternating optimization framework and provide a convergence analysis that extends existing API theory. We also develop a special instance of this framework which reduces the update of non-reactive policies to model-based optimal control using learned local models, and provides a theoretically sound way of unifying model-free and model-based RL approaches with unknown dynamics. We demonstrate the efficacy of our approach on various continuous control Markov Decision Processes.
arxiv topic:cs.LG stat.ML
arxiv_dataset-98391805.10855
Kinetic energy densities based on the fourth order gradient expansion: performance in different classes of materials and improvement via machine learning physics.comp-ph cond-mat.mtrl-sci We study the performance of fourth-order gradient expansions of the kinetic energy density (KED) in semi-local kinetic energy functionals depending on the density-dependent variables. The formal fourth-order expansion is convergent for periodic systems and small molecules but does not improve over the second-order expansion (Thomas-Fermi term plus one-ninth of von Weizs\"acker term). Linear fitting of the expansion coefficients somewhat improves on the formal expansion. The tuning of the fourth order expansion coefficients allows for better reproducibility of Kohn-Sham kinetic energy density than the tuning of the second-order expansion coefficients alone. The possibility of a much more accurate match with the Kohn-Sham kinetic energy density by using neural networks trained using the terms of the 4th order expansion as density-dependent variables is demonstrated. We obtain ultra-low fitting errors without overfitting. Small single hidden layer neural networks can provide good accuracy in separate KED fits of each compound, while for joint fitting of KEDs of multiple compounds multiple hidden layers were required to achieve good fit quality. The critical issue of data distribution is highlighted. We also show the critical role of pseudopotentials in the performance of the expansion, where in the case of a too rapid decay of the valence density at the nucleus with some pseudopotentials, numeric instabilities arise.
arxiv topic:physics.comp-ph cond-mat.mtrl-sci
arxiv_dataset-98401805.10955
Propagation of solutions of the Porous Medium Equation with reaction and their travelling wave behaviour math.AP We consider reaction-diffusion equations of porous medium type, with different kind of reaction terms, and nonnegative bounded initial data. For all the reaction terms under consideration there are initial data for which the solution converges to 1 uniformly in compact sets for large times. We will characterize for which reaction terms this happens for all nontrivial nonnegative initial data, and for which ones there are also solutions converging uniformly to 0. Problems in this family have a unique (up to translations) travelling wave with a finite front and we will see how its speed gives the asymptotic velocity of all the solutions with compactly supported initial data. We will also prove in the one-dimensional case that solutions with bounded compactly supported initial data converging to 1 do so approaching a translation of this unique traveling wave. We will prove a similar result for non-compactly supported initial data in a certain class.
arxiv topic:math.AP
arxiv_dataset-98411805.11055
Local properties of the surface measure of convex bodies math.MG It is well known that any measure in S^2 satisfying certain simple conditions is the surface measure of a bounded convex body in R^3. It is also known that a local perturbation of the surface measure may lead to a nonlocal perturbation of the corresponding convex body. We prove that, under mild conditions on a convex body, there are families of perturbations of its surface measure forming line segments, with the original measure at the midpoint, leading to local perturbations of the body. Moreover, there is, in a sense, a huge amount of such families. We apply this result to Newton's problem of minimal resistance for convex bodies.
arxiv topic:math.MG
arxiv_dataset-98421805.11155
Unsupervised Learning of Artistic Styles with Archetypal Style Analysis stat.ML cs.CV cs.LG In this paper, we introduce an unsupervised learning approach to automatically discover, summarize, and manipulate artistic styles from large collections of paintings. Our method is based on archetypal analysis, which is an unsupervised learning technique akin to sparse coding with a geometric interpretation. When applied to deep image representations from a collection of artworks, it learns a dictionary of archetypal styles, which can be easily visualized. After training the model, the style of a new image, which is characterized by local statistics of deep visual features, is approximated by a sparse convex combination of archetypes. This enables us to interpret which archetypal styles are present in the input image, and in which proportion. Finally, our approach allows us to manipulate the coefficients of the latent archetypal decomposition, and achieve various special effects such as style enhancement, transfer, and interpolation between multiple archetypes.
arxiv topic:stat.ML cs.CV cs.LG
arxiv_dataset-98431805.11255
Succinct data structure for dynamic trees with faster queries cs.DS Navarro and Sadakane [TALG 2014] gave a dynamic succinct data structure for storing an ordinal tree. The structure supports tree queries in either $O(\log n/\log\log n)$ or $O(\log n)$ time, and insertion or deletion of a single node in $O(\log n)$ time. In this paper we improve the result of Navarro and Sadakane by reducing the time complexities of some queries (e.g.\ degree and level\_ancestor) from $O(\log n)$ to $O(\log n/\log\log n)$.
arxiv topic:cs.DS
arxiv_dataset-98441805.11355
Authentication protocol based on collective quantum steering quant-ph It is well known that certain quantum correlations like quantum steering exhibit a monogamous relationship. In this paper, we exploit the asymmetric nature of quantum steering and show that there exist states which exhibit a polygamous correlation, known as collective correlation [He and Reid, Phys. Rev. Lett. 111, 250403 (2013)], where the state of one party, Alice, can be steered only by the joint effort of the other two parties, Bob and Charlie. As an example, we explicitly single out a particular set of $3$ qubit states which exhibit this polygamous relationship, known as collective steerability. We provide a recipe to identify the complete set of such states. We also provide a possible application of such states to an information theoretic task, termed as quantum key authentication (QKA) protocol. QKA can also be used in conjunction with other well known cryptography protocols to improve their security and we provide one such example with quantum private comparison (QPC).
arxiv topic:quant-ph
arxiv_dataset-98451805.11455
The Mid-Frequency Square Kilometre Array Phase Synchronisation System astro-ph.IM This paper describes the technical details and practical implementation of the Mid-Frequency Square Kilometre Array (SKA) phase synchronisation system. Over a four-year period, the system has been tested on metropolitan fibre-optic networks, on long-haul overhead fibre at the South African SKA site, and on existing telescopes in Australia to verify its functional performance. The tests have shown that the system exceed the 1-second SKA coherence loss requirement by a factor 2560, the 60-second coherence loss requirement by a factor of 239, and the 10-minute phase drift requirement by almost five orders-of-magnitude. The paper also reports on tests showing that the system can operate within specification over the all required operating conductions, including maximum fibre link distance, temperature range, temperature gradient, relative humidity, wind speed, seismic resilience, electromagnetic compliance, frequency offset, and other operational requirements.
arxiv topic:astro-ph.IM
arxiv_dataset-98461805.11555
Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites cs.AI Workforce Scheduling and Routing Problems (WSRP) are very common in many practical domains, and usually, have a number of objectives. Illumination algorithms such as Map-Elites (ME) have recently gained traction in application to {\em design} problems, in providing multiple diverse solutions as well as illuminating the solution space in terms of user-defined characteristics, but typically require significant computational effort to produce the solution archive. We investigate whether ME can provide an effective approach to solving WSRP, a {\em repetitive} problem in which solutions have to be produced quickly and often. The goals of the paper are two-fold. The first is to evaluate whether ME can provide solutions of competitive quality to an Evolutionary Algorithm (EA) in terms of a single objective function, and the second to examine its ability to provide a repertoire of solutions that maximise user choice. We find that very small computational budgets favour the EA in terms of quality, but ME outperforms the EA at larger budgets, provides a more diverse array of solutions, and lends insight to the end-user.
arxiv topic:cs.AI
arxiv_dataset-98471805.11655
Some generalizations of frames in Hilbert modules math.OA math.FA Frames play significant role in various areas of science and engineering. In this paper, we introduce the concepts of frames for $End_{\mathcal{A}}^{\ast}(\mathcal{H, K})$ and their generalizations. Moreover, we obtain some new results for generalized frames in Hilbert modules.
arxiv topic:math.OA math.FA
arxiv_dataset-98481805.11755
Collisional Disruption of Planetesimals in the Gravity Regime with iSALE Code: Comparison with SPH code for Purely Hydrodynamic Bodies astro-ph.EP In most of the previous studies related to collisional disruption of planetesimals in the gravity regime, Smoothed Particle Hydrodynamics (SPH) simulations have been used. On the other hand, impact simulations using grid-based hydrodynamic code have not been sufficiently performed. In the present study, we execute impact simulations in the gravity regime using the shock-physics code iSALE, which is a grid-based Eulerian hydrocode. We examine the dependence of the critical specific impact energy Q_RD* on impact conditions for a wide range of specific impact energy (Q_R) from disruptive collisions to erosive collisions, and compare our results with previous studies. We find collision outcomes of the iSALE simulation agree well with those of the SPH simulation. Detailed analysis mainly gives three results. (1) The value of Q_RD* depends on numerical resolution, and is close to convergence with increasing numerical resolution. The difference in converged value of Q_RD* between the iSALE code and the SPH code is within 30%. (2) Ejected mass normalized by total mass (M_ej/M_tot) generally depends on various impact conditions. However, when Q_R is normalized by Q_RD* that is calculated for each impact simulation, M_ej/M_tot can be scaled by Q_R/Q_RD*, and is independent of numerical resolution, impact velocity and target size. (3) This similarity law for Q_R/Q_RD* is confirmed for a wide range of specific impact energy. We also derive a semi-analytic formula for Q_RD* based on the similarity law and the crater scaling law. We find that the semi-analytic formula for the case with a non-porous object is consistent with numerical results.
arxiv topic:astro-ph.EP
arxiv_dataset-98491805.11855
Rational extension of Newton diagram for the positivity of ${}_1F_2$ hypergeometric functions and Askey-Szeg\"o problem math.CA We present a rational extension of Newton diagram for the positivity of ${}_1F_2$ generalized hypergeometric functions. As an application, we give upper and lower bounds for the transcendental roots $\beta(\alpha)$ of \begin{align*} \int_0^{j_{\alpha, 2}} t^{-\beta} J_\alpha(t) dt = 0\qquad(-1<\alpha\le 1/2), \end{align*} where $j_{\alpha, 2}$ denotes the second positive zero of Bessel function $J_\alpha$.
arxiv topic:math.CA
arxiv_dataset-98501805.11955
Simplicity of algebras via epsilon-strong systems math.RA We obtain sufficient criteria for simplicity of systems, that is, rings $R$ that are equipped with a family of additive subgroups $R_s$, for $s \in S$, where $S$ is a semigroup, satisfying $R = \sum_{s \in S} R_s$ and $R_s R_t \subseteq R_{st}$, for $s,t \in S$. These criteria are specialized to obtain sufficient criteria for simplicity of, what we call, s-unital epsilon-strong systems, that is systems where $S$ is an inverse semigroup, $R$ is coherent, in the sense that for all $s,t \in S$ with $s \leq t$, the inclusion $R_s \subseteq R_t$ holds, and for each $s \in S$, the $R_s R_{s^*}$-$R_{s^*}R_s$-bimodule $R_s$ is s-unital. As an aplication of this, we obtain generalizations of recent criteria for simplicity of skew inverse semigroup rings, by Beuter, Goncalves, \"{O}inert and Royer, and then, in turn, for Steinberg algebras, over non-commutative rings, by Brown, Farthing, Sims, Steinberg, Clark and Edie-Michel.
arxiv topic:math.RA
arxiv_dataset-98511805.12055
Extragalactic photon--axion-like particle oscillations up to 1000 TeV astro-ph.HE hep-ph Axion-like particles (ALPs) are attracting increasing interest since, among other things, they are a prediction of many extensions of the standard model of elementary particles physics and in particular of superstrings and superbranes. Remarkably, depending on the set of their parameter space, they strongly increase the photon transparency in the very-high energy band. The recent discovery of photon dispersion on the CMB requires a substantial modification of the previous picture: this is indeed the goal of the present paper. We compute the photon survival probability from a blazar to us exactly, and we plot it versus the observed energy for 7 simulated blazars at different $z$ and 4 values of a model parameter. Our predictions can be tested by the new generation of $\gamma$-ray observatories like CTA, HAWC, GAMMA-400, LHAASO, TAIGA-HiSCORE and HERD. Finally, for our guessed values of $m_a$ and $g_{\gamma \gamma a}$ our ALP can be detected in the upgrade of ALPS II at DESY, the planned experiments IAXO, STAX and ABRACADABRA as well as with other techniques.
arxiv topic:astro-ph.HE hep-ph
arxiv_dataset-98521805.12155
The plane-wave spectrum from the worldsheet hep-th We study string theory on $\mathrm{AdS}_3$ backgrounds with mixed flux using the hybrid formalism of Berkovits, Vafa and Witten. We solve the worldsheet description of the theory completely in the plane-wave limit. This constitutes a direct derivation of the plane-wave spectrum from the worldsheet with mixed flux.
arxiv topic:hep-th
arxiv_dataset-98531805.12255
Bose-Einstein condensation of alpha clusters and new soft mode in 12C--52Fe 4N nuclei in field theoretical superfluid cluster model nucl-th Bose-Einstein condensation of alpha clusters in light and medium-heavy nuclei is studied in the frame of the field theoretical superfluid cluster model. The order parameter of the phase transition from the Wigner phase to the Nambu-Goldstone phase is a superfluid amplitude, square of the moduli of which is the superfluid density distribution. The zero mode operators due to the spontaneous symmetry breaking of the global phase in the finite number of alpha clusters are rigorously treated. The theory is systematically applied to N alpha nuclei from12C-52Fe at various condensation rates. In 12C it is found that the energy levels of the gas-like well-developed alpha cluster states above the Hoyle state are reproduced well in agreement with experiment for realistic condensation rates of alpha clusters. The electric E2 and E0 transitions are calculated and found to be sensitive to the condensation rates. The profound raison d'etre of the alpha cluster gas-like states above the Hoyle state, whose structure has been interpreted geometrically in the nuclear models without the order parameter such as the cluster models or ab initio calculations, is revealed. It is found that in addition to the Bogoliubov-de Gennes vibrational mode states collective states of the zero mode operators appear systematically at low excitation energies from the N alpha threshold energy. These collective states, new-type soft modes in nuclei due to the Bose-Einstein condensation of the alpha clusters, emerge systematically in light and medium-heavy mass regions and are also located at high excitation energies from the ground state in contrast to the traditional concept of soft mode in the low excitation energy region.
arxiv topic:nucl-th
arxiv_dataset-98541805.12355
Deep-Energy: Unsupervised Training of Deep Neural Networks cs.LG stat.ML The success of deep learning has been due, in no small part, to the availability of large annotated datasets. Thus, a major bottleneck in current learning pipelines is the time-consuming human annotation of data. In scenarios where such input-output pairs cannot be collected, simulation is often used instead, leading to a domain-shift between synthesized and real-world data. This work offers an unsupervised alternative that relies on the availability of task-specific energy functions, replacing the generic supervised loss. Such energy functions are assumed to lead to the desired label as their minimizer given the input. The proposed approach, termed "Deep Energy", trains a Deep Neural Network (DNN) to approximate this minimization for any chosen input. Once trained, a simple and fast feed-forward computation provides the inferred label. This approach allows us to perform unsupervised training of DNNs with real-world inputs only, and without the need for manually-annotated labels, nor synthetically created data. "Deep Energy" is demonstrated in this paper on three different tasks -- seeded segmentation, image matting and single image dehazing -- exposing its generality and wide applicability. Our experiments show that the solution provided by the network is often much better in quality than the one obtained by a direct minimization of the energy function, suggesting an added regularization property in our scheme.
arxiv topic:cs.LG stat.ML
arxiv_dataset-98551805.12455
p-p, p-$\Lambda$ and $\Lambda$-$\Lambda$ correlations studied via femtoscopy in pp reactions at $\sqrt{s}$ = 7 TeV nucl-ex hep-ex We report on the first femtoscopic measurement of baryon pairs, such as p-p, p-$\Lambda$ and $\Lambda$-$\Lambda$, measured by ALICE at the Large Hadron Collider (LHC) in proton-proton collisions at $\sqrt{s}$ = 7 TeV. This study demonstrates the feasibility of such measurements in pp collisions at ultrarelativistic energies. The femtoscopy method is employed to constrain the hyperon-nucleon and hyperon-hyperon interactions, which are still rather poorly understood. A new method to evaluate the influence of residual correlations induced by the decays of resonances and experimental impurities is hereby presented. The p-p, p-$\Lambda$ and $\Lambda$-$\Lambda$ correlation functions were fitted simultaneously with the help of a new tool developed specifically for the femtoscopy analysis in small colliding systems 'Correlation Analysis Tool using the Schr\"odinger Equation' (CATS). Within the assumption that in pp collisions the three particle pairs originate from a common source, its radius is found to be equal to $r_{0} = 1.125\pm0.018$ (stat) $^{+0.058}_{-0.035}$ (syst) fm. The sensitivity of the measured p-$\Lambda$ correlation is tested against different scattering parameters which are defined by the interaction among the two particles, but the statistics is not sufficient yet to discriminate among different models. The measurement of the $\Lambda$-$\Lambda$ correlation function constrains the phase space spanned by the effective range and scattering length of the strong interaction. Discrepancies between the measured scattering parameters and the resulting correlation functions at LHC and RHIC energies are discussed in the context of various models.
arxiv topic:nucl-ex hep-ex
arxiv_dataset-98561805.12555
The integer quantum Hall plateau transition is a current algebra after all math-ph cond-mat.dis-nn hep-th math.MP The scaling behavior near the transition between plateaus of the Integer Quantum Hall Effect (IQHE) has traditionally been interpreted on the basis of a two-parameter renormalization group (RG) flow conjectured from Pruisken's non-linear sigma model. Yet, the conformal field theory (CFT) describing the critical point remained elusive, and only fragments of a quantitative analytical understanding existed up to now. In the present paper we carry out a detailed analysis of the current-current correlation function for the conductivity tensor, initially in the Chalker-Coddington network model for the IQHE plateau transition and then in its exact reformulation as a supersymmetric vertex model. We develop a heuristic argument for the continuum limit of the non-local conductivity response function at criticality and thus identify a non-Abelian current algebra at level n = 4. Based on precise lattice expressions for the CFT primary fields we predict the multifractal scaling exponents of critical wavefunctions to be q(1-q)/4. The Lagrangian of the RG fixed-point theory for r retarded and r advanced replicas is proposed to be the GL(r|r)_4 Wess-Zumino-Witten model deformed by a truly marginal perturbation. The latter emerges from the non-linear sigma model by a natural scenario of spontaneous symmetry breaking.
arxiv topic:math-ph cond-mat.dis-nn hep-th math.MP
arxiv_dataset-98571806.0006
The Mullins effect in the wrinkling behavior of highly stretched thin films cond-mat.soft Recent work demonstrates that finite-deformation nonlinear elasticity is essential in the accurate modeling of wrinkling in highly stretched thin films. Geometrically exact models predict an isola-center bifurcation, indicating that for a bounded interval of aspect ratios only, stable wrinkles appear and then disappear as the macroscopic strain is increased. This phenomenon has been verified in experiments. In addition, recent experiments revealed the following striking phenomenon: For certain aspect ratios for which no wrinkling occurred upon the first loading, wrinkles appeared during the first unloading and again during all subsequent cyclic loading. Our goal here is to present a simple pseudo-elastic model, capturing the stress softening and residual strain observed in the experiments, that accurately predicts wrinkling behavior on the first loading that differs from that under subsequent cyclic loading. In particular for specific aspect ratios, the model correctly predicts the scenario of no wrinkling during first loading with wrinkling occurring during unloading and for all subsequent cyclic loading.
arxiv topic:cond-mat.soft
arxiv_dataset-98581806.0016
Sparse Multiband Signal Acquisition Receiver with Co-prime Sampling eess.SP cs.IT math.IT Cognitive radio (CR) requires spectrum sensing over a broad frequency band. One of the crucial tasks in CR is to sample wideband signal at high sampling rate. In this paper, we propose an acquisition receiver with co-prime sampling technique for wideband sparse signals, which occupy a small part of band range. In this proposed acquisition receiver, we use two low speed analog-to-digital converters (ADCs) to capture a common sparse multiband signal, whose band locations are unknown. The two ADCs are synchronously clocked at co-prime sampling rates. The obtained samples are re-sequenced into a group of uniform sequences with low rate. We derive the mathematical model for the receiver in the frequency domain and present its signal reconstruction algorithm. Compared to the existing sub-Nyquist sampling techniques, such as multi-coset sampling and modulated wideband converter, the proposed approach has a simple system architecture and can be implemented with only two samplers. Experimental results are reported to demonstrate the feasibility and advantage of the proposed model. For sparse multiband signal with unknown spectral support, the proposed system requires a sampling rate much lower than Nyquist rate, while produces satisfactory reconstruction.
arxiv topic:eess.SP cs.IT math.IT
arxiv_dataset-98591806.0026
The Proximal Alternating Minimization Algorithm for two-block separable convex optimization problems with linear constraints math.OC math.NA The Alternating Minimization Algorithm (AMA) has been proposed by Tseng to solve convex programming problems with two-block separable linear constraints and objectives, whereby (at least) one of the components of the latter is assumed to be strongly convex. The fact that one of the subproblems to be solved within the iteration process of AMA does not usually correspond to the calculation of a proximal operator through a closed formula, affects the implementability of the algorithm. In this paper we allow in each block of the objective a further smooth convex function and propose a proximal version of AMA, called Proximal AMA, which is achieved by equipping the algorithm with proximal terms induced by variable metrics. For suitable choices of the latter, the solving of the two subproblems in the iterative scheme can be reduced to the computation of proximal operators. We investigate the convergence of the proposed algorithm in a real Hilbert space setting and illustrate its numerical performances on two applications in image processing and machine learning.
arxiv topic:math.OC math.NA
arxiv_dataset-98601806.0036
Towards a new system for drowsiness detection based on eye blinking and head posture estimation cs.CV eess.IV Driver drowsiness problem is considered as one of the most important reasons that increases road accidents number. We propose in this paper a new approach for realtime driver drowsiness in order to prevent road accidents. The system uses a smart video camera that takes drivers faces images and supervises the eye blink (open and close) state and head posture to detect the different drowsiness states. Face and eye detection are done by Viola and Jones technique.
arxiv topic:cs.CV eess.IV
arxiv_dataset-98611806.0046
Assessing Perturbativity and Vacuum Stability in High-Scale Leptogenesis hep-ph We consider the requirements that all coupling constants remain perturbative and the electroweak vacuum metastable up to the Planck scale in high-scale thermal leptogenesis, in the context of a type-I seesaw mechanism. We find a large region of the model parameter space that satisfies these conditions in combination with producing the baryon asymmetry of the Universe. We demonstrate these conditions require ${\rm Tr}[Y_N^\dagger Y_N] \lesssim 0.66$ on the neutrino Yukawa matrix. We also investigate this scenario in the presence of a large number $N_F$ of coloured Majorana octet fermions in order to make quantum chromodynamics asymptotically safe in the ultraviolet.
arxiv topic:hep-ph
arxiv_dataset-98621806.0056
High-dimensional measurement-device-independent quantum key distribution based on spatial basis physics.optics Improving the secret key rate is one of the vital issues in practical applications of quantum key distribution (QKD). In this paper, we propose an experimental scheme of high-dimensional measurement-device-independent quantum key distribution (MDI-QKD) based on spatial basis aiming to increase the key rate. Two groups of discrete position basis and momentum basis are applied as conjugate spaces to generate quantum secret key. The position states are transmitted by single-mode fibers and represented by the index of the fiber, while the momentum state is a coherent superposition of the position states characterized by the phase gradient. The measurement of each momentum basis is realized by multi-slit diffraction. This experimental proposal can be implemented with standard optical elements. In addition to an enhanced key rate in a higher dimension, this high-dimensional MDI-QKD exhibits a comparable security level/performance compared to conventional polarization-based MDI-QKD.
arxiv topic:physics.optics
arxiv_dataset-98631806.0066
Flavourful Axion Phenomenology hep-ph We present a comprehensive discussion of the phenomenology of flavourful axions, including both standard Peccei-Quinn (PQ) axions, associated with the solution to the strong $CP$ problem, and non-standard axion-like particles (ALPs). We give the flavourful axion-fermion and axion-photon couplings and calculate the branching ratios of heavy meson ($K$, $D$, $B$) decays involving a flavourful axion. We also calculate the mixing between axions and heavy mesons $ K^0 $, $ D^0 $, $ B^0 $ and $ B_s^0 $, which affects the meson oscillation probability and mass difference. Mixing also contributes to meson decays into axions and axion decays into two photons, and may be relevant for ALPs. We discuss charged lepton flavour-violating decays involving final state axions of the form $\ell_1 \to \ell_2 a (\gamma) $, as well as $ \mu \to eee $ and $ \mu-e $ conversion. Finally we describe the phenomenology of a particular "A to Z" Pati-Salam model, in which PQ symmetry arises accidentally due to discrete flavour symmetry. Here all axion couplings are fixed by a fit to flavour data, leading to sharp predictions and correlations between flavour-dependent observables.
arxiv topic:hep-ph
arxiv_dataset-98641806.0076
Efficient Time-Evolving Stream Processing at Scale cs.DC Time-evolving stream datasets exist ubiquitously in many real-world applications where their inherent hot keys often evolve over times. Nevertheless, few existing solutions can provide efficient load balance on these time-evolving datasets while preserving low memory overhead. In this paper, we present a novel grouping approach (named FISH), which can provide the efficient time-evolving stream processing at scale. The key insight of this work is that the keys of time-evolving stream data can have a skewed distribution within any bounded distance of time interval. This enables to accurately identify the recent hot keys for the real-time load balance within a bounded scope. We therefore propose an epoch-based recent hot key identification with specialized intra-epoch frequency counting (for maintaining low memory overhead) and inter-epoch hotness decaying (for suppressing superfluous computation). We also propose to heuristically infer the accurate information of remote workers through computation rather than communication for cost-efficient worker assignment. We have integrated our approach into Apache Storm. Our results on a cluster of 128 nodes for both synthetic and real-world stream datasets show that FISH significantly outperforms state-of-the-art with the average and the 99th percentile latency reduction by 87.12% and 76.34% (vs. W-Choices), and memory overhead reduction by 99.96% (vs. Shuffle Grouping).
arxiv topic:cs.DC
arxiv_dataset-98651806.0086
Optimizing weighted ensemble sampling of steady states math.NA cs.NA We propose parameter optimization techniques for weighted ensemble sampling of Markov chains in the steady-state regime. Weighted ensemble consists of replicas of a Markov chain, each carrying a weight, that are periodically resampled according to their weights inside of each of a number of bins that partition state space. We derive, from first principles, strategies for optimizing the choices of weighted ensemble parameters, in particular the choice of bins and the number of replicas to maintain in each bin. In a simple numerical example, we compare our new strategies with more traditional ones and with direct Monte Carlo.
arxiv topic:math.NA cs.NA
arxiv_dataset-98661806.0096
The Capacity Constrained Facility Location problem cs.GT cs.AI We initiate the study of the capacity constrained facility location problem from a mechanism design perspective. The capacity constrained setting leads to a new strategic environment where a facility serves a subset of the population, which is endogenously determined by the ex-post Nash equilibrium of an induced subgame and is not directly controlled by the mechanism designer. Our focus is on mechanisms that are ex-post dominant-strategy incentive compatible (DIC) at the reporting stage. We provide a complete characterization of DIC mechanisms via the family of Generalized Median Mechanisms (GMMs). In general, the social welfare optimal mechanism is not DIC. Adopting the worst-case approximation measure, we attain tight lower bounds on the approximation ratio of any DIC mechanism. The well-known median mechanism is shown to be optimal among the family of DIC mechanisms for certain capacity ranges. Surprisingly, the framework we introduce provides a new characterization for the family of GMMs, and is responsive to gaps in the current social choice literature highlighted by Border and Jordan (1983) and Barbar{\`a}, Mass{\'o} and Serizawa (1998).
arxiv topic:cs.GT cs.AI
arxiv_dataset-98671806.0106
Sharp multiplier theorem for multidimensional Bessel operators math.FA Consider the multidimensional Bessel operator $$B f(x) = -\sum_{j=1}^N \left(\partial_j^2 f(x) +\frac{\alpha_j}{x_j} \partial_j f(x)\right), \quad x\in(0,\infty)^N. $$ Let $d = \sum_{j=1}^N \max(1,\alpha_j+1)$ be the homogeneous dimension of the space $(0,\infty)^N$ equipped with the measure $x_1^{\alpha_1}... x_N^{\alpha_N} dx_1...dx_N$. In the general case $\alpha_1,...,\alpha_N >-1$ we prove multiplier theorems for spectral multipliers $m(B)$ on $L^{1,\infty}$ and the Hardy space $H^1$. We assume that $m$ satisfies the classical H\"ormander condition $$\sup_{t>0} \left||\eta(\cdot) m(t\cdot)\right||_{W^{2,\beta}(\mathbb{R})}<\infty$$ with $\beta > d/2$. Furthermore, we investigate imaginary powers $B^{ib}$, $b\in \mathbb{R}$, and prove some lower estimates on $L^{1,\infty}$ and $L^p$, $1<p<2$. As a consequence, we deduce that our multiplier theorem is sharp.
arxiv topic:math.FA
arxiv_dataset-98681806.0116
On effective field theory of F-theory beyond leading order hep-th We construct a proposal for effective bosonic field theory at order $ \alpha'^3 $ in twelve dimensions, whose compactification on a circle and on a torus respectively yields eleven-dimensional and type IIB supergravity theories at eight-derivative level. The couplings $ ({\partial {G_5}})^2 R^2 $, $ ({\partial {F_4}})^2 R^2 $, $ ({\partial {F_4}})^4 $, $ ({\partial {G_5}})^4 $ and $ ({\partial {G_5}})^2({\partial {F_4}})^2 $ in twelve-dimensional supergravity are determined with this requirement that an ansatz of these couplings should admits a consistent truncation to the eleven-dimensional and type IIB supergravity theories. The self-duality condition of the five-form field strength in twelve dimensions is also understood by considering the RR five-form field strength of type IIB theory at linear order.
arxiv topic:hep-th
arxiv_dataset-98691806.0126
Digging Into Self-Supervised Monocular Depth Estimation cs.CV stat.ML Per-pixel ground-truth depth data is challenging to acquire at scale. To overcome this limitation, self-supervised learning has emerged as a promising alternative for training models to perform monocular depth estimation. In this paper, we propose a set of improvements, which together result in both quantitatively and qualitatively improved depth maps compared to competing self-supervised methods. Research on self-supervised monocular training usually explores increasingly complex architectures, loss functions, and image formation models, all of which have recently helped to close the gap with fully-supervised methods. We show that a surprisingly simple model, and associated design choices, lead to superior predictions. In particular, we propose (i) a minimum reprojection loss, designed to robustly handle occlusions, (ii) a full-resolution multi-scale sampling method that reduces visual artifacts, and (iii) an auto-masking loss to ignore training pixels that violate camera motion assumptions. We demonstrate the effectiveness of each component in isolation, and show high quality, state-of-the-art results on the KITTI benchmark.
arxiv topic:cs.CV stat.ML
arxiv_dataset-98701806.0136
Evaluating Impact of Human Errors on the Availability of Data Storage Systems cs.PF cs.DC In this paper, we investigate the effect of incorrect disk replacement service on the availability of data storage systems. To this end, we first conduct Monte Carlo simulations to evaluate the availability of disk subsystem by considering disk failures and incorrect disk replacement service. We also propose a Markov model that corroborates the Monte Carlo simulation results. We further extend the proposed model to consider the effect of automatic disk fail-over policy. The results obtained by the proposed model show that overlooking the impact of incorrect disk replacement can result up to three orders of magnitude unavailability underestimation. Moreover, this study suggests that by considering the effect of human errors, the conventional believes about the dependability of different RAID mechanisms should be revised. The results show that in the presence of human errors, RAID1 can result in lower availability compared to RAID5.
arxiv topic:cs.PF cs.DC
arxiv_dataset-98711806.0146
Dynamic Function-on-Scalars Regression stat.ME We develop a modeling framework for dynamic function-on-scalars regression, in which a time series of functional data is regressed on a time series of scalar predictors. The regression coefficient function for each predictor is allowed to be dynamic, which is essential for applications where the association between predictors and a (functional) response is time-varying. For greater modeling flexibility, we design a nonparametric reduced-rank functional data model with an unknown functional basis expansion, which is data-adaptive and, unlike most existing methods, modeled as unknown for appropriate uncertainty quantification. Within a Bayesian framework, we introduce shrinkage priors that simultaneously (i) regularize time-varying regression coefficient functions to be locally static, (ii) effectively remove unimportant predictor variables from the model, and (iii) reduce sensitivity to the dimension of the functional basis. A simulation analysis confirms the importance of these shrinkage priors, with notable improvements over existing alternatives. We develop a novel projection-based Gibbs sampling algorithm, which offers unrivaled computational scalability for fully Bayesian functional regression. We apply the proposed methodology (i) to analyze the time-varying impact of macroeconomic variables on the U.S. yield curve and (ii) to characterize the effects of socioeconomic and demographic predictors on age-specific fertility rates in South and Southeast Asia.
arxiv topic:stat.ME
arxiv_dataset-98721806.0156
Sharp quadrature error bounds for the nearest-neighbor discretization of the regularized stokeslet boundary integral equation physics.flu-dyn math.NA The method of regularized stokeslets is a powerful numerical method to solve the Stokes flow equations for problems in biological fluid mechanics. A recent variation of this method incorporates a nearest-neighbor discretization to improve accuracy and efficiency while maintaining the ease-of-implementation of the original meshless method. This method contains three sources of numerical error, the regularization error associated from using the regularized form of the boundary integral equations (with parameter $\varepsilon$), and two sources of discretization error associated with the force and quadrature discretizations (with lengthscales $h_f$ and $h_q$). A key issue to address is the quadrature error: initial work has not fully explained observed numerical convergence phenomena. In the present manuscript we construct sharp quadrature error bounds for the nearest-neighbor discretisation, noting that the error for a single evaluation of the kernel depends on the smallest distance ($\delta$) between these discretization sets. The quadrature error bounds are described for two cases: with disjoint sets ($\delta>0$) being close to linear in $h_q$ and insensitive to $\varepsilon$, and contained sets ($\delta=0$) being quadratic in $h_q$ with inverse dependence on $\varepsilon$. The practical implications of these error bounds are discussed with reference to the condition number of the matrix system for the nearest-neighbor method, with the analysis revealing that the condition number is insensitive to $\varepsilon$ for disjoint sets, and grows linearly with $\varepsilon$ for contained sets. Error bounds for the general case ($\delta\geq 0$) are revealed to be proportional to the sum of the errors for each case.
arxiv topic:physics.flu-dyn math.NA
arxiv_dataset-98731806.0166
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization cs.LG stat.ML Asynchronous momentum stochastic gradient descent algorithms (Async-MSGD) is one of the most popular algorithms in distributed machine learning. However, its convergence properties for these complicated nonconvex problems is still largely unknown, because of the current technical limit. Therefore, in this paper, we propose to analyze the algorithm through a simpler but nontrivial nonconvex problem - streaming PCA, which helps us to understand Aync-MSGD better even for more general problems. Specifically, we establish the asymptotic rate of convergence of Async-MSGD for streaming PCA by diffusion approximation. Our results indicate a fundamental tradeoff between asynchrony and momentum: To ensure convergence and acceleration through asynchrony, we have to reduce the momentum (compared with Sync-MSGD). To the best of our knowledge, this is the first theoretical attempt on understanding Async-MSGD for distributed nonconvex stochastic optimization. Numerical experiments on both streaming PCA and training deep neural networks are provided to support our findings for Async-MSGD.
arxiv topic:cs.LG stat.ML
arxiv_dataset-98741806.0176
Predictive Accuracy of Markers or Risk Scores for Interval Censored Survival Data stat.ME Methods for the evaluation of the predictive accuracy of biomarkers with respect to survival outcomes subject to right censoring have been discussed extensively in the literature. In cancer and other diseases, survival outcomes are commonly subject to interval censoring by design or due to the follow up schema. In this paper, we present an estimator for the area under the time-dependent receiver operating characteristic ROC curve for interval censored data based on a nonparametric sieve maximum likelihood approach. We establish the asymptotic properties of the proposed estimator, and illustrate its finite-sample properties using a simulation study. The application of our method is illustrated using data from a cancer clinical study. An open-source R package to implement the proposed method is available on CRAN.
arxiv topic:stat.ME
arxiv_dataset-98751806.0186
Composite Weyl semimetal as a parent state for three dimensional topologically ordered phases cond-mat.str-el cond-mat.mes-hall We introduce (3+1) dimensional models of short-range-interacting electrons that form a strongly correlated many-body state whose low-energy excitations are relativistic neutral fermions coupled to an emergent gauge field, $\text{QED}_{4}$. We discuss the properties of this critical state and its instabilities towards exotic phases such as a gapless `composite' Weyl semimetal and fully gapped topologically ordered phases that feature anyonic point-like as well as line-like excitations. These fractionalized phases describe electronic insulators. They may be further enriched by symmetries which results in the formation of non-trivial surface states.
arxiv topic:cond-mat.str-el cond-mat.mes-hall
arxiv_dataset-98761806.0196
Pressure-induced Frustration of Magnetic Coupling in Elemental Europium cond-mat.str-el Applying linear response and the magnetic force theorem in correlated density functional theory, the inter-sublattice exchange constants of antiferromagnetic Eu are calculated and found to vanish near the pressure of P$_c$=82 GPa, just where magnetic order is observed experimentally to be lost. The Eu $4f^7$ moment remains unchanged at high pressure, again in agreement with spectroscopic measurements, leaving the picture of perfect frustration of interatomic Ruderman-Kittel-Kasuya-Yoshida couplings in a broad metallic background, leaving a state of electrons strongly exchange coupled to arbitrarily oriented, possibly quasistatic local moments. This strongly frustrated state gives way to superconductivity at T$_c$=1.7K, observed experimentally. These phenomena, and free energy considerations related to correlations, suggest an unusual phase of matter that is discussed within the scenarios of the Doniach Kondo lattice phase diagram, the metallic spin glass class, and itinerant spin liquid or spin gas systems.
arxiv topic:cond-mat.str-el
arxiv_dataset-98771806.0206
Effective definability of Kolchin polynomials math.AC While the natural model-theoretic ranks available in differentially closed fields (of characteristic zero), namely Lascar and Morley rank, are known not to be definable in families of differential varieties; in this note we show that the differential-algebraic rank given by the Kolchin polynomial is in fact definable. As a byproduct, we are able to prove that the property of being weakly irreducible for a differential variety is also definable in families. The question of full irreducibility remains open, it is known to be equivalent to the generalized Ritt problem.
arxiv topic:math.AC
arxiv_dataset-98781806.0216
Deep Bayesian regression models stat.ME Regression models are used for inference and prediction in a wide range of applications providing a powerful scientific tool for researchers and analysts from different fields. In many research fields the amount of available data as well as the number of potential explanatory variables is rapidly increasing. Variable selection and model averaging have become extremely important tools for improving inference and prediction. However, often linear models are not sufficient and the complex relationship between input variables and a response is better described by introducing non-linearities and complex functional interactions. Deep learning models have been extremely successful in terms of prediction although they are often difficult to specify and potentially suffer from overfitting. The aim of this paper is to bring the ideas of deep learning into a statistical framework which yields more parsimonious models and allows to quantify model uncertainty. To this end we introduce the class of deep Bayesian regression models (DBRM) consisting of a generalized linear model combined with a comprehensive non-linear feature space, where non-linear features are generated just like in deep learning but combined with variable selection in order to include only important features. DBRM can easily be extended to include latent Gaussian variables to model complex correlation structures between observations, which seems to be not easily possible with existing deep learning approaches. Two different algorithms based on MCMC are introduced to fit DBRM and to perform Bayesian inference. The predictive performance of these algorithms is compared with a large number of state of the art algorithms. Furthermore we illustrate how DBRM can be used for model inference in various applications.
arxiv topic:stat.ME
arxiv_dataset-98791806.0226
Dual-Mode Operation of an Optical Lattice Clock Using Strontium and Ytterbium Atoms physics.atom-ph We have developed an optical lattice clock that can operate in dual modes: a strontium (Sr) clock mode and an ytterbium (Yb) clock mode. Dual-mode operation of the Sr-Yb optical lattice clock is achieved by alternately cooling and trapping $^{87}$Sr and $^{171}$Yb atoms inside the vacuum chamber of the clock. Optical lattices for Sr and Yb atoms were arranged with horizontal and vertical configurations, respectively, resulting in a small distance of the order of 100 $\mu$m between the trapped Sr and Yb atoms. The $^{1}$S$_{0}$-$^{3}$P$_{0}$ clock transitions in the trapped atoms were interrogated in turn and the clock lasers were stabilized to the transitions. We demonstrated the frequency ratio measurement of the Sr and Yb clock transitions by using the dual-mode operation of the Sr-Yb optical lattice clock. The dual-mode operation can reduce the uncertainty of the blackbody radiation shift in the frequency ratio measurement, because both Sr and Yb atoms share the same blackbody radiation.
arxiv topic:physics.atom-ph
arxiv_dataset-98801806.0236
Effective virtual and residual properties of some arithmetic hyperbolic 3-manifolds math.GT math.GR We give an effective upper bound, for certain arithmetic hyperbolic 3-manifold groups obtained from a quadratic form construction, on the minimal index of a subgroup that embeds in a fixed 6-dimensional right-angled reflection group, stabilizing a totally geodesic subspace. In particular, for manifold groups in any fixed commensurability class we show that the index of such a subgroup is asymptotically smaller than any fractional power of the volume of the manifold. We also give effective bounds on the geodesic residual finiteness growths of closed hyperbolic manifolds that totally geodesically immerse in non-compact right-angled reflection orbifolds, extending work of the third author from the compact case. The first result gives examples to which the second applies, and for these we give explicit bounds on geodesic residual finiteness growth.
arxiv topic:math.GT math.GR
arxiv_dataset-98811806.0246
The effect of the choice of neural network depth and breadth on the size of its hypothesis space cs.LG stat.ML We show that the number of unique function mappings in a neural network hypothesis space is inversely proportional to $\prod_lU_l!$, where $U_{l}$ is the number of neurons in the hidden layer $l$.
arxiv topic:cs.LG stat.ML
arxiv_dataset-98821806.0256
Automaticity of the sequence of the last nonzero digits of $n!$ in a fixed base math.NT In 2011 Deshouillers and Ruzsa tried to argument that the sequence of the last nonzero digit of $n!$ in base 12 is not automatic. This statement was proved few years later by Deshoulliers. In this paper we provide alternate proof that lets us generalize the problem and give an exact characterization in which bases the sequence of the last nonzero digits of $n!$ is automatic.
arxiv topic:math.NT
arxiv_dataset-98831806.0266
Analyzing Traffic Delay at Unmanaged Intersections cs.MA At an unmanaged intersection, it is important to understand how much traffic delay may be caused as a result of microscopic vehicle interactions. Conventional traffic simulations that explicitly track these interactions are time-consuming. Prior work introduced an analytical traffic model for unmanaged intersections. The traffic delay at the intersection is modeled as an event-driven stochastic process, whose dynamics encode microscopic vehicle interactions. This paper studies the traffic delay in a two-lane intersection using the model. We perform rigorous analyses concerning the distribution of traffic delay under different scenarios. We then discuss the relationships between traffic delay and multiple factors such as traffic flow density, unevenness of traffic flows, temporal gaps between two consecutive vehicles, and the passing order.
arxiv topic:cs.MA
arxiv_dataset-98841806.0276
Quasiconformal features and Fredholm eigenvalues of convex polygons math.CV An important open problem in geometric complex analysis is to find algorithms for explicit determination of basic functionals intrinsically connected with conformal and quasiconformal maps, such as their Teichmuller and Grunsky norms, Fredholm eigenvalues and the quasireflection coefficient. This has not been solved even for convex polygons. This case has intrinsic interest in view of the connection of such polygons with the geometry of the universal Teichmuller space. We provide a new approach, based on affine transformations of univalent functions.
arxiv topic:math.CV
arxiv_dataset-98851806.0286
Ideals in Rings and Intermediate Rings of Measurable Functions math.FA math.AC math.GN The set of all maximal ideals of the ring $\mathcal{M}(X,\mathcal{A})$ of real valued measurable functions on a measurable space $(X,\mathcal{A})$ equipped with the hull-kernel topology is shown to be homeomorphic to the set $\hat{X}$ of all ultrafilters of measurable sets on $X$ with the Stone-topology. This yields a complete description of the maximal ideals of $\mathcal{M}(X,\mathcal{A})$ in terms of the points of $\hat{X}$. It is further shown that the structure spaces of all the intermediate subrings of $\mathcal{M}(X,\mathcal{A})$ containing the bounded measurable functions are one and the same and are compact Hausdorff zero-dimensional spaces. It is observed that when $X$ is a $P$-space, then $C(X) = \mathcal{M}(X,\mathcal{A})$ where $\mathcal{A}$ is the $\sigma$-algebra consisting of the zero-sets of $X$.
arxiv topic:math.FA math.AC math.GN
arxiv_dataset-98861806.0296
Representation Learning of Entities and Documents from Knowledge Base Descriptions cs.CL cs.NE In this paper, we describe TextEnt, a neural network model that learns distributed representations of entities and documents directly from a knowledge base (KB). Given a document in a KB consisting of words and entity annotations, we train our model to predict the entity that the document describes and map the document and its target entity close to each other in a continuous vector space. Our model is trained using a large number of documents extracted from Wikipedia. The performance of the proposed model is evaluated using two tasks, namely fine-grained entity typing and multiclass text classification. The results demonstrate that our model achieves state-of-the-art performance on both tasks. The code and the trained representations are made available online for further academic research.
arxiv topic:cs.CL cs.NE
arxiv_dataset-98871806.0306
2K(2\nu)-Capture in Xe-124: Results of Data Processing for an Exposure of 37.7 kg x day nucl-ex physics.ins-det The results of the experimental search for two-neutrino $2K$-capture in $^{124}$Xe with a large copper proportional counter obtained by processing the data for an exposure of 37.7 kg$\times$day are presented. The experimental setup is located at the Underground Low-Background Laboratory of the Baksan Neutrino Observatory at a depth of 4900 m w.e. The combination of methods of selection of useful signals with a unique set of characteristics and the event topology taken into account allowed us to suppress the background in the energy region of interest. A new half-life limit for $2K(2\nu)$-capture in $^{124}$Xe was determined: T$_{1/2}\geq7.7\cdot10^{21}$ yrs (90\% C.L.).
arxiv topic:nucl-ex physics.ins-det
arxiv_dataset-98881806.0316
Reducing Metadata Leakage from Encrypted Files and Communication with PURBs cs.CR Most encrypted data formats leak metadata via their plaintext headers, such as format version, encryption schemes used, number of recipients who can decrypt the data, and even the recipients' identities. This leakage can pose security and privacy risks to users, e.g., by revealing the full membership of a group of collaborators from a single encrypted e-mail, or by enabling an eavesdropper to fingerprint the precise encryption software version and configuration the sender used. We propose that future encrypted data formats improve security and privacy hygiene by producing $\textit{Padded Uniform Random Blobs}$ or PURBs: ciphertexts indistinguishable from random bit strings to anyone without a decryption key. A PURB's content leaks $\textit{nothing at all}$, even the application that created it, and is padded such that even its length leaks as little as possible. Encoding and decoding ciphertexts with $\textit{no}$ cleartext markers presents efficiency challenges, however. We present cryptographically agile encodings enabling legitimate recipients to decrypt a PURB efficiently, even when encrypted for any number of recipients' public keys and/or passwords, and when these public keys are from different cryptographic suites. PURBs employ Padm\'e, a~novel padding scheme that limits information leakage via ciphertexts of maximum length $M$ to a practical optimum of $O(\log \log M)$ bits, comparable to padding to a power of two, but with lower overhead of at most $12\%$ and decreasing with larger payloads.
arxiv topic:cs.CR
arxiv_dataset-98891806.0326
DBBRBF- Convalesce optimization for software defect prediction problem using hybrid distribution base balance instance selection and radial basis Function classifier cs.SE Software is becoming an indigenous part of human life with the rapid development of software engineering, demands the software to be most reliable. The reliability check can be done by efficient software testing methods using historical software prediction data for development of a quality software system. Machine Learning plays a vital role in optimizing the prediction of defect-prone modules in real life software for its effectiveness. The software defect prediction data has class imbalance problem with a low ratio of defective class to non-defective class, urges an efficient machine learning classification technique which otherwise degrades the performance of the classification. To alleviate this problem, this paper introduces a novel hybrid instance-based classification by combining distribution base balance based instance selection and radial basis function neural network classifier model (DBBRBF) to obtain the best prediction in comparison to the existing research. Class imbalanced data sets of NASA, Promise and Softlab were used for the experimental analysis. The experimental results in terms of Accuracy, F-measure, AUC, Recall, Precision, and Balance show the effectiveness of the proposed approach. Finally, Statistical significance tests are carried out to understand the suitability of the proposed model.
arxiv topic:cs.SE
arxiv_dataset-98901806.0336
Band gap and band offset of Ga$_2$O$_3$ and (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys cond-mat.mtrl-sci Ga$_2$O$_3$ and (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys are promising materials for solar-blind UV photodetectors and high-power transistors. Basic key parameters in the device design, such as band gap variation with alloy composition and band offset between Ga$_2$O$_3$ and (Al$_x$Ga$_{1-x}$)$_2$O$_3$, are yet to be established. Using density functional theory with the HSE hybrid functional, we compute formation enthalpies, band gaps, and band edge positions of (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys in the monoclinic ($\beta$) and corundum ($\alpha$) phases. We find the formation enthlapies of (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloys are significantly lower than of (In$_x$Ga$_{1-x}$)$_2$O$_3$, and that (Al$_x$Ga$_{1-x}$)$_2$O$_3$ with $x$=0.5 can be considered as an ordered compound AlGaO$_3$ in the monoclinic phase, with Al occupying the octahedral sites and Ga occupying the tetrahedral sites. The direct band gaps of the alloys range from 4.69 to 7.03 eV for $\beta$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$ and from 5.26 to 8.56 eV for $\alpha$-(Al$_x$Ga$_{1-x}$)$_2$O$_3$. Most of the band offset of the (Al$_x$Ga$_{1-x}$)$_2$O$_3$ alloy arises from the discontinuity in the conduction band. Our results are used to explain the available experimental data, and consequences for designing modulation-doped field effect transistors (MODFETs) based on (Al$_x$Ga$_{1-x}$)$_2$O$_3$/Ga$_2$O$_3$ are discussed.
arxiv topic:cond-mat.mtrl-sci
arxiv_dataset-98911806.0346
The calculation of differential and total cross sections for $W^+ W^- \gamma$ production process in proton-proton collisions at LHC energies hep-ph The vector bosons production at the Large Hadron Collider makes it possible to investigate in detail the basic structure of electroweak interactions. Besides the LHC with a good accuracy will be measure production of weak bosons ($pp \to W^+W^-$). The production of weak bosons with photon ($pp \to W^+W^-\gamma$) provides an increasingly powerful handle at higher center-of-mass energies. We present phenomenological results for $WW\gamma$ production in proton-proton interaction at the Large Hadron Collider. In this paper, we calculate the total and differential cross sections. We consider the dependence of differential cross section distributions on transverse momentum and rapidity particles, which are produced in the final state ($W^+$ and $W^-$). We consider several important distributions, which are included in the search for new physics at the Large Hadron Collider. The results for transverse momentum distributions, rapidity distributions and total cross section are presented.
arxiv topic:hep-ph
arxiv_dataset-98921806.0356
Semantic Correspondence: A Hierarchical Approach cs.CV Establishing semantic correspondence across images when the objects in the images have undergone complex deformations remains a challenging task in the field of computer vision. In this paper, we propose a hierarchical method to tackle this problem by first semantically targeting the foreground objects to localize the search space and then looking deeply into multiple levels of the feature representation to search for point-level correspondence. In contrast to existing approaches, which typically penalize large discrepancies, our approach allows for significant displacements, with the aim to accommodate large deformations of the objects in scene. Localizing the search space by semantically matching object-level correspondence, our method robustly handles large deformations of objects. Representing the target region by concatenated hypercolumn features which take into account the hierarchical levels of the surrounding context, helps to clear the ambiguity to further improve the accuracy. By conducting multiple experiments across scenes with non-rigid objects, we validate the proposed approach, and show that it outperforms the state of the art methods for semantic correspondence establishment.
arxiv topic:cs.CV
arxiv_dataset-98931806.0366
High Performance and Scalable AWG for Superconducting Quantum Computing eess.SP quant-ph Superconducting quantum computer is manufactured based on semiconductor process which makes qubits integration possible. At the same time, this kind of qubit exhibits high performance fidelity, de-coherence time, scalability and requires a programmable arbitrary waveform generator (AWG). This paper presents implementation of an AWG which composed of two gigabit samples per second (GSPS) sampling rate, 16 bit vertical resolution digital to analog converters (DACs). The AWG integrated with separate microwave devices onto a metal plate for the scale-up consideration. A special waveform sequence output controller is designed to realize seamless waveform switching and arbitrary waveform generator. The jitter in multiple AWG channels is around 10ps, Integral nonlinearity (INL) as well as differential nonlinearity (DNL) is about 2 LSB, and the qubit performance of the de-coherence time (T2*) achieved 33% promotion over that of a commercial 1 GSPS, 14 bit AWG.
arxiv topic:eess.SP quant-ph
arxiv_dataset-98941806.0376
Effects of quark-matter symmetry energy on hadron-quark coexistence in neutron-star matter nucl-th We examine the effects of the isovector-vector coupling and hypercharge-vector coupling in quark matter on hadron-quark coexistence in neutron-star matter. The relativistic mean field theory with the TM1 parameter set and an extended TM1 parameter set are used to describe hadronic matter, and the Nambu-Jona-Lasinio model with scalar, isoscalar-vector, isovector-vector and hypercharge-vector couplings is used to describe deconfined quark matter. The hadron-quark phase transition is constructed via the Gibbs conditions for phase equilibrium. The isovector-vector and hypercharge-vector couplings in quark matter enhance the symmetry energy and hypercharge symmetry energy in neutron-star matter, while their effects are found to be suppressed at high densities by the strange quarks. As a result, the hadron-quark mixed phase shrinks with only isovector-vector coupling and moves to higher density with isovector-vector and hypercharge-vector couplings. The maximum mass of neutron-star increases slightly with isovector-vector and hypercharge-vector couplings.
arxiv topic:nucl-th
arxiv_dataset-98951806.0386
Air-Ground Integrated Vehicular Network Slicing with Content Pushing and Caching cs.NI cs.IT math.IT In this paper, an Air-Ground Integrated VEhicular Network (AGIVEN) architecture is proposed, where the aerial High Altitude Platforms (HAPs) proactively push contents to vehicles through large-area broadcast while the ground roadside units (RSUs) provide high-rate unicast services on demand. To efficiently manage the multi-dimensional heterogeneous resources, a service-oriented network slicing approach is introduced, where the AGIVEN is virtually divided into multiple slices and each slice supports a specific application with guaranteed quality of service (QoS). Specifically, the fundamental problem of multi-resource provisioning in AGIVEN slicing is investigated, by taking into account typical vehicular applications of location-based map and popularity-based content services. For the location-based map service, the capability of HAP-vehicle proactive pushing is derived with respect to the HAP broadcast rate and vehicle cache size, wherein a saddle point exists indicating the optimal communication-cache resource trading. For the popular contents of common interests, the average on-board content hit ratio is obtained, with HAPs pushing newly generated contents to keep on-board cache fresh. Then, the minimal RSU transmission rate is derived to meet the average delay requirements of each slice. The obtained analytical results reveal the service-dependent resource provisioning and trading relationships among RSU transmission rate, HAP broadcast rate, and vehicle cache size, which provides guidelines for multi-resource network slicing in practice. Simulation results demonstrate that the proposed AGIVEN network slicing approach matches the multi-resources across slices, whereby the RSU transmission rate can be saved by 40% while maintaining the same QoS.
arxiv topic:cs.NI cs.IT math.IT
arxiv_dataset-98961806.0396
AGIL: Learning Attention from Human for Visuomotor Tasks cs.CV cs.AI cs.LG When intelligent agents learn visuomotor behaviors from human demonstrations, they may benefit from knowing where the human is allocating visual attention, which can be inferred from their gaze. A wealth of information regarding intelligent decision making is conveyed by human gaze allocation; hence, exploiting such information has the potential to improve the agents' performance. With this motivation, we propose the AGIL (Attention Guided Imitation Learning) framework. We collect high-quality human action and gaze data while playing Atari games in a carefully controlled experimental setting. Using these data, we first train a deep neural network that can predict human gaze positions and visual attention with high accuracy (the gaze network) and then train another network to predict human actions (the policy network). Incorporating the learned attention model from the gaze network into the policy network significantly improves the action prediction accuracy and task performance.
arxiv topic:cs.CV cs.AI cs.LG
arxiv_dataset-98971806.0406
Strange superconductivity near an antiferromagnetic heavy fermion quantum critical point cond-mat.supr-con The heavy fermion CeMIn5 family with M = Co, Rh, Ir provide a prototypical example of strange superconductors with unconventional d-wave pairing and strange metal normal state, emerged near an antiferromagnetic quantum critical point. The microscopic origin of strange superconductor and its link to antiferromagnetic quantum criticality and strange metal state are still open issues. We propose a microscopic mechanism for strange superconductor, based on the coexistence and competition between the Kondo correlation and the quasi-2d short-ranged antiferromagnetic resonating-valence-bond spin-liquid near the antiferromagnetic quantum critical point via a large-N Kondo-Heisenberg model and renormalization group analysis beyond the mean-field level. We find the coexistence (competition) between the two types of correlations well explains the overall features of superconducting and strange metal state. The interplay of these two effects provides a qualitative understanding on how superconductivity emerges from the SM state and the observed superconducting phase diagrams for CeMIn5 near the anti-ferromagnetic quantum critical point.
arxiv topic:cond-mat.supr-con
arxiv_dataset-98981806.0416
Evolved stars in the Local Group galaxies - II. AGB, RSG stars and dust production in IC10 astro-ph.SR astro-ph.GA We study the evolved stellar population of the Local Group galaxy IC10, with the aim of characterizing the individual sources observed and to derive global information on the galaxy, primarily the star formation history and the dust production rate. To this aim, we use evolutionary sequences of low- and intermediate-mass ($M < 8~M_{\odot}$) stars, evolved through the asymptotic giant branch phase, with the inclusion of the description of dust formation. We also use models of higher mass stars. From the analysis of the distribution of stars in the observational planes obtained with IR bands, we find that the reddening and distance of IC10 are $E(B-V)=1.85$ mag and $d=0.77$ Mpc, respectively. The evolved stellar population is dominated by carbon stars, that account for $40\%$ of the sources brighter than the tip of the red giant branch. Most of these stars descend from $\sim 1.1-1.3~M_{\odot}$ progenitors, formed during the major epoch of star formation, which occurred $\sim 2.5$ Gyr ago. The presence of a significant number of bright stars indicates that IC10 has been site of significant star formation in recent epochs and currently hosts a group of massive stars in the core helium-burning phase. Dust production in this galaxy is largely dominated by carbon stars; the overall dust production rate estimated is $7\times 10^{-6}~M_{\odot}$/yr.
arxiv topic:astro-ph.SR astro-ph.GA
arxiv_dataset-98991806.0426
On the diameter and incidence energy of iterated total graphs math.SP math.CO The total graph of $G$, $\mathcal T(G)$ is the graph whose set of vertices is the union of the sets of vertices and edges of $G$, where two vertices are adjacent if and only if they stand for either incident or adjacent elements in $G$. Let $\mathcal{T}^1(G)=\mathcal{T}(G)$, the total graph of $G$. For $k\geq2$, the $k\text{-}th$ iterated total graph of $G$, $\mathcal{T}^k(G)$, is defined recursively as $\mathcal{T}^k(G)=\mathcal{T}(\mathcal{T}^{k-1}(G)).$ If $G$ is a connected graph its diameter is the maximum distance between any pair of vertices in $G$. The incidence energy $IE(G)$ of $G$ is the sum of the singular values of the incidence matrix of $G$. In this paper for a given integer $k$ we establish a necessary and sufficient condition under which $diam(\mathcal{T}^{r+1}(G))>k-r,$ $r\geq0$. In addition, bounds for the incidence energy of the iterated graph $\mathcal{T}^{r+1}(G)$ are obtained, provided $G$ to be a regular graph. Finally, new families of non-isomorphic cospectral graphs are exhibited.
arxiv topic:math.SP math.CO