July 2019 arXiv papers — page 113

Maarten Van Damme, Laurens Vanderstraeten, Jacopo De Nardis, Jutho Haegeman

We develop a method based on tensor networks to create localized single particle excitations on top of strongly-correlated quantum spin chains. In analogy to the problem of creating localized Wannier modes, this is achieved by optimizing the gauge freedom of momentum excitations on top of matrix product states. The corresponding wavepackets propagate almost

Richard A Lockhart

Priors in which a large number of parameters are specified to be independent are dangerous; they make it hard to learn from data. I present a couple of examples from the literature and work through a bit of large sample theory to show what happens.

Suraj Shankar, M. Cristina Marchetti

Topological defects play a prominent role in the physics of two-dimensional materials. When driven out of equilibrium in active nematics, disclinations can acquire spontaneous self-propulsion and drive self-sustained flows upon proliferation. Here we construct a general hydrodynamic theory for a two-dimensional active nematic interrupted by a large number of

Amir Djalalian-Assl

Here I report on comparisons between two different techniques in fabricating arrays of subwavelength cross-shaped apertures in metallic screens. The aim was to determine the most appropriate fabrication technique to be used considering the cost, ease of fabrication and accuracy in which the apertures were created. Some interesting physical effects are observ

Azadeh Fattahi, Julio F. Navarro, Carlos S. Frenk

We study the Local Group (LG) dwarf galaxy population predicted by the \apostle $Λ$CDM cosmological hydrodynamics simulations. These indicate that: (i)~the total mass within $3$ Mpc of the Milky Way-Andromeda midpoint ($M_{\rm 3Mpc}$) typically exceeds $\sim 3$ times the sum of the virial masses ($M_{\rm 200crit}$) of the two primaries and (ii)~the dwarf gal

Carmelo Cisto, Manuel Delgado, Pedro A. García-Sánchez

We provide algorithms for performing computations in generalized numerical semigroups, that is, submonoids of $\mathbb{N}^{d}$ with finite complement in $\mathbb{N}^{d}$. These semigroups are affine semigroups, which in particular implies that they are finitely generated. For a given finite set of elements in $\mathbb{N}^d$ we show how to deduce if the monoi

Christophe Charlier, Maurice Duits, Arno B. J. Kuijlaars, Jonatan Lenells

We study a one-parameter family of probability measures on lozenge tilings of large regular hexagons that interpolates between the uniform measure on all possible tilings and a particular fully frozen tiling. The description of the asymptotic behavior can be separated into two regimes: the low and the high temperature regime. Our main results are the computa

E. Marini, F. Dell'Agli, D. A. García-Hernández, M. A. T. Groenewegen

We study a group of evolved M-stars in the Large Magellanic Cloud, characterized by a peculiar spectral energy distribution. While the $9.7~μ$m feature arises from silicate particles, the whole infrared data seem to suggest the presence of an additional featureless dust species. We propose that the circumstellar envelopes of these sources are characterized b

M. E. Shirokov

We describe an universal method for quantitative continuity analysis of entropic characteristics of energy-constrained quantum systems and channels. It gives asymptotically tight continuity bounds for basic characteristics of quantum systems of wide class (including multi-mode quantum oscillators) and channels between such systems under the energy constraint

Hernán Vivas

We establish sharp $C^{2s}$ interior regularity estimates for solutions of fully nonlinear nonlocal equations with bounded right hand side. More precisely, we show that if $I$ is a fully nonlinear nonlocal concave or convex elliptic operator and $f\in L^\infty(B_1)$ then \[ Iu=f\quad\textrm{ in }\quad B_1 \quad \Rightarrow\quad u\in C^{2s}(B_{1/2}). \] This

Adalberto Claudio Quiros, Roderick Murray-Smith, Ke Yuan

Histopathological images of tumors contain abundant information about how tumors grow and how they interact with their micro-environment. Better understanding of tissue phenotypes in these images could reveal novel determinants of pathological processes underlying cancer, and in turn improve diagnosis and treatment options. Advances of Deep learning makes it

Ran Huo

We study the free-streaming effect in a light freeze-in dark matter model. Naturally in the dark sector one can find dark matter related coupling, and such coupling may induce dark matter self-scattering. In case that such scattering is subdominant, the dark matter partition function is not thermal but determined by the freeze-in process, yet its high moment

Mathias Pétréolle, Alan D. Sokal

We introduce the generic Lah polynomials $L_{n,k}(ϕ)$, which enumerate unordered forests of increasing ordered trees with a weight $ϕ_i$ for each vertex with $i$ children. We show that, if the weight sequence $ϕ$ is Toeplitz-totally positive, then the triangular array of generic Lah polynomials is totally positive and the sequence of row-generating polynomia

Chris Good, Joel Mitchell, Joe Thomas

We give a reformulation of the inverse shadowing property with respect to the class of all pseudo-orbits. This reformulation bears witness to the fact that the property is far stronger than might initially seem. We give some implications of this reformulation, in particular showing that systems with inverse shadowing are not sensitive. Finally we show that,

Arthur P. Guillaumin, Adam M. Sykulski, Sofia C. Olhede, Frederik J. Simons

We provide a computationally and statistically efficient method for estimating the parameters of a stochastic covariance model observed on a regular spatial grid in any number of dimensions. Our proposed method, which we call the Debiased Spatial Whittle likelihood, makes important corrections to the well-known Whittle likelihood to account for large sources

Chris Good, Joel Mitchell, Joe Thomas

We look at the preservation of various notions of shadowing in discrete dynamical systems under inverse limits, products, factor maps and the induced maps for symmetric products and hyperspaces. The shadowing properties we consider are the following: shadowing, h-shadowing, eventual shadowing, orbital shadowing, strong orbital shadowing, the first and second

Luis F. Alday, Johan Henriksson, Mark van Loon

We apply the methods of modern analytic bootstrap to the critical $O(N)$ model in a $1/N$ expansion. At infinite $N$ the model possesses higher spin symmetry which is weakly broken as we turn on $1/N$. By studying consistency conditions for the correlator of four fundamental fields we derive the CFT-data for all the (broken) currents to order $1/N$, and the

Tianxi Li, Cheng Qian, Elizaveta Levina, Ji Zhu

Graphical models are commonly used to represent conditional dependence relationships between variables. There are multiple methods available for exploring them from high-dimensional data, but almost all of them rely on the assumption that the observations are independent and identically distributed. At the same time, observations connected by a network are b

Ricardo F. Ferreira, Sandro Gallo, Frédéric Paccaut

It is well-known that there always exists at least one stationary measure compatible with a continuous g-function g. Here we prove that if the set of discontinuities of the g-function g has null measure under a candidate measure obtained by some asymptotic procedure, then this candidate measure is compatible with g. We explore several implications of this re

Hui Xiao, Ion Grama, Quansheng Liu

Let $(g_{n})_{n\geq 1}$ be a sequence of independent and identically distributed (i.i.d.) $d\times d$ real random matrices. For $n\geq 1$ set $G_n = g_n \ldots g_1$. Given any starting point $x=\mathbb R v\in\mathbb{P}^{d-1}$, consider the Markov chain $X_n^x = \mathbb R G_n v $ on the projective space $\mathbb P^{d-1}$ and the norm cocycle $\sigma(G_n, x)=

Michael Lechner, Gabriel Okasa

In this paper we develop a new machine learning estimator for ordered choice models based on the random forest. The proposed Ordered Forest flexibly estimates the conditional choice probabilities while taking the ordering information explicitly into account. In addition to common machine learning estimators, it enables the estimation of marginal effects as w

Leonard Henckel, Emilija Perković, Marloes H. Maathuis

Covariate adjustment is a commonly used method for total causal effect estimation. In recent years, graphical criteria have been developed to identify all valid adjustment sets, that is, all covariate sets that can be used for this purpose. Different valid adjustment sets typically provide total effect estimates of varying accuracies. Restricting ourselves t

Blake C. Stacey

I summarize a research program that aims to reconstruct quantum theory from a fundamental physical principle that, while a quantum system has no intrinsic hidden variables, it can be understood using a reference measurement. This program reduces the physical question of why the quantum formalism is empirically successful to the mathematical question of why c

Yan Dolinsky, Benjamin Gottesman, Ori Gurel-Gurevich

We study the minimization of the expected costs under stochastic constraint at the terminal time. The first and the main result says that for a power type of costs, the value function is the minimal positive solution of a second order semi--linear ordinary differential equation (ODE). Moreover, we establish the optimal control. In the second example we show

Youmna Farag, Helen Yannakoudakis

We address the task of assessing discourse coherence, an aspect of text quality that is essential for many NLP tasks, such as summarization and language assessment. We propose a hierarchical neural network trained in a multi-task fashion that learns to predict a document-level coherence score (at the network's top layers) along with word-level grammatica

I. Adagideli, F. Hassler, A. Grabsch, M. Pacholski

A $2π$ phase shift across a Josephson junction in a topological superconductor injects vortices into the chiral edge modes at opposite ends of the junction. When two vortices are fused they transfer charge into a metal contact. We calculate the time dependent current profile for the fusion process, which consists of $\pm e/2$ charge pulses that flip sign if

Miguel Escobar Azor, Léa Brooke, Stefano Evangelisti, Thierry Leininger

In this work we investigate Wigner localization at very low densities by means of the exact diagonalization of the Hamiltonian. This yields numerically exact results. In particular, we study a quasi-one-dimensional system of two electrons that are confined to a ring by three-dimensional gaussians placed along the ring perimeter. To characterize the Wigner lo

Bas Edixhoven, Pierre Parent

We complete the description of semistable models for modular curves associated with maximal subgroups of $\mathrm{GL}_2 ({\mathbb F}_p )$ (for $p$ any prime, $p>5$). That is, in the new cases of non-split Cartan modular curves and exceptional subgroups, we identify the irreducible components and singularities of the reduction mod $p$, and the complete local

Ryosuke Sato

Motivated by the recent work of Chigusa, Moroi, and Shoji, we propose a new simple gradient flow equation to derive the bounce solution which contributes to the decay of the false vacuum. Our discussion utilizes the discussion of Coleman, Glaser, and Martin and we solve a minimization problem of the kinetic energy while fixing the potential energy. The bounc

Yin Chen, Runxuan Zhang

Let $\mathfrak{g}$ be a finite-dimensional complex Lie algebra and $\textrm{HLie}_{m}(\mathfrak{g})$ be the affine variety of all multiplicative Hom-Lie algebras on $\mathfrak{g}$. We use a method of computational ideal theory to describe $\textrm{HLie}_{m}(\mathfrak{gl}_{n}(\mathbb{C}))$, showing that $\textrm{HLie}_{m}(\mathfrak{gl}_{2}(\mathbb{C}))$ consi

Shaohua Li, Yong Liu, Xiuchao Sui, Cheng Chen

Deep learning for medical image classification faces three major challenges: 1) the number of annotated medical images for training are usually small; 2) regions of interest (ROIs) are relatively small with unclear boundaries in the whole medical images, and may appear in arbitrary positions across the x,y (and also z in 3D images) dimensions. However often

Anwoy Maitra

We provide a sufficient condition for the continuous extension of isometries for the Kobayashi distance between bounded convex domains in complex Euclidean spaces having boundaries that are only slightly more regular than $\mathcal{C}^1$. This is a generalization of a recent result by A. Zimmer.

Harold Blum, Yuchen Liu, Chenyang Xu

In this paper, we prove the openness of K-semistability in families of log Fano pairs by showing that the stability threshold is a constructible function on the fibers. We also prove that any special test configuration arises from a log canonical place of a bounded complement and establish properties of any minimizer of the stability threshold.

Valentin Leplat, Nicolas Gillis, Man Shun Ang

Considering a mixed signal composed of various audio sources and recorded with a single microphone, we consider on this paper the blind audio source separation problem which consists in isolating and extracting each of the sources. To perform this task, nonnegative matrix factorization (NMF) based on the Kullback-Leibler and Itakura-Saito $β$-divergences is

Wei-Chih Huang, Kin-Wang Ng, Tzu-Chiang Yuan

We study the loop-induced circularly polarized gamma rays from dark matter annihilation using the effective dark matter theory approach. Both neutral scalar and fermionic dark matter annihilating into monochromatic diphoton and $Z$-photon final states are considered. To generate the circular polarization asymmetry, $P$ and $CP$ symmetries must be violated in

Martino Bardi, Ermal Feleqi, Pierpaolo Soravia

In this paper we relax the current regularity theory for the eikonal equation by using the recent theory of { set-valued} iterated Lie brackets. We give sufficient conditions for small time local attainability of general, symmetric, nonlinear systems, which have as a consequence the Hoelder regularity of the minimum time function in optimal control. We then

Xavier Caicedo, Eduardo Duenez, Jose Iovino

The concept of metastable convergence was identified by Tao;it allows converting theorems about convergence into stronger theorems about uniform convergence. The Uniform Metastability Principle (UMP) states that if $T$ is a theorem about convergence, then the fact that $T$ is valid implies automatically that its (stronger) uniform version is valid, provided

Yurong You, Yuanyuan Gong, Hang Li, Zefang Li

In this work, we reported the observation of a novel planar topological Hall effect (PTHE) in single crystal of Fe3GeTe2, a paradigmatic two-dimensional ferromagnet with strong uniaxial anisotropy. The Hall effect and magnetoresistance varied periodically when the external magnetic field rotated in the ac (or bc) plane, while the PTHE emerged and maintained

Anna C. Tasolamprou, Alexandros Pitilakis, Sergi Abadal, Odysseas Tsilipakos

Software-defined metasurfaces are electromagnetically ultra-thin, artificial components that can provide engineered and externally controllable functionalities. The control over these functionalities is enabled by the metasurface tunability, which is implemented by embedded electronic circuits that modify locally the surface resistance and reactance. Integra

Herodotos Herodotou, Elena Kakoulli

Data-intensive platforms such as Hadoop and Spark are routinely used to process massive amounts of data residing on distributed file systems like HDFS. Increasing memory sizes and new hardware technologies (e.g., NVRAM, SSDs) have recently led to the introduction of storage tiering in such settings. However, users are now burdened with the additional complex

Lynton Ardizzone, Carsten Lüth, Jakob Kruse, Carsten Rother

In this work, we address the task of natural image generation guided by a conditioning input. We introduce a new architecture called conditional invertible neural network (cINN). The cINN combines the purely generative INN model with an unconstrained feed-forward network, which efficiently preprocesses the conditioning input into useful features. All paramet

Gabor Szabo

We provide the rigorous foundations for a categorical approach to the classification of C*-dynamics up to cocycle conjugacy. Given a locally compact group $G$, we consider a category of (twisted) $G$-C*-algebras, where morphisms between two objects are allowed to be equivariant maps or exterior equivalences, which leads to the concept of so-called cocycle mo

Natalia Accomazzo, Francesco Di Plinio, Ioannis Parissis

A recent result by Parcet and Rogers is that finite order lacunarity characterizes the boundedness of the maximal averaging operator associated to an infinite set of directions in $\mathbb{R}^n$. Their proof is based on geometric-combinatorial coverings of fat hyperplanes by two-dimensional wedges. Seminal results by Nagel-Stein-Wainger relied on geometric c

Mareike Dunz, Tristan Matalla-Wagner, Markus Meinert

Electrical switching and readout of antiferromagnets allows to exploit the unique properties of antiferromagnetic materials in nanoscopic electronic devices. Here we report experiments on the spin-orbit torque induced electrical switching of a polycrystalline, metallic antiferromagnet with low anisotropy and high Néel temperature. We demonstrate the switchin

David Zimmerer, Fabian Isensee, Jens Petersen, Simon Kohl

An assumption-free automatic check of medical images for potentially overseen anomalies would be a valuable assistance for a radiologist. Deep learning and especially Variational Auto-Encoders (VAEs) have shown great potential in the unsupervised learning of data distributions. In principle, this allows for such a check and even the localization of parts in

Tomoya Gake, Yu Kumagai, Christoph Freysoldt, Fumiyasu Oba

A correction method for vertical transition levels (VTLs) involving defect states calculated with a supercell technique is formulated and its effectiveness is systematically verified with ten defects in prototypical materials: cubic-BN, GaN, MgO, and 3C-SiC. Without any corrections, the absolute errors are around 1 eV with moderate size supercells in most ca

Vincent G. A. Böning, Huanchen Hu, Laurent Gizon

Context. Solar gravity modes (g modes) are buoyancy waves trapped in the solar radiative zone that have been very difficult to detect at the surface. Solar g modes would complement solar pressure modes (p modes) in probing the central regions of the Sun, for example the core rotation rate. Aims. A detection of g modes using changes in the large frequency sep

Leigh N. Fletcher, Ravit Helled, Elias Roussos, Geraint Jones

Uranus and Neptune, and their diverse satellite and ring systems, represent the least explored environments of our Solar System, and yet may provide the archetype for the most common outcome of planetary formation throughout our galaxy. Ice Giants will be the last remaining class of Solar System planet to have a dedicated orbital explorer, and international

Valentino Magnani, Andreas Minne

We establish the optimal $C_{H}^{1,1}$ interior regularity of solutions to \[ Δ_{H}u=fχ_{\{u\ne0\}}, \] where $Δ_{H}$ denotes the sub-Laplacian operator in a stratified group. We assume the weakest regularity condition on $f$, namely $f*Γ$ is $C_{H}^{1,1}$, where $Γ$ is the fundamental solution of $Δ_{H}$. The $C_{H}^{1,1}$ regularity is understood in the se

Juan-Andrés Pérez-Rúa, Kaushik Das, Mathias Stolpe, Nicolaos A. Cutululis

A mathematical program for global optimization of the cable layout of Offshore Wind Farms (OWFs) is presented. The model consists on a Mixed Integer Linear Program (MILP). Modern branch-and-cut solvers are able to solve large-scale instances, defined by more than hundred Wind Turbines (WTs), and a reasonable number of Offshore Substations (OSSs). In addition

Caitlin Jones, Tommaso Guaita, Angelo Bassi

Spontaneous collapse models are proposed modifications to quantum mechanics which aim to solve the measurement problem. In this article we will consider models which attempt to extend a specific spontaneous collapse model, the Ghirardi-Rimini-Weber model (GRW), to be consistent with special relativity. We will present a condition that a relativistic GRW mode

Simon Apers

Expansion testing aims to decide whether an $n$-node graph has expansion at least $Φ$, or is far from any such graph. We propose a quantum expansion tester with complexity $\widetilde{O}(n^{1/3}Φ^{-1})$. This accelerates the $\widetilde{O}(n^{1/2}Φ^{-2})$ classical tester by Goldreich and Ron [Algorithmica '02], and combines the $\widetilde{O}(n^{1/3}Φ^{

Ilaria Perugia, Joachim Schöberl, Paul Stocker, Christoph Wintersteiger

We present a space-time Trefftz discontinuous Galerkin method for approximating the acoustic wave equation semi-explicitly on tent pitched meshes. DG Trefftz methods use discontinuous test and trial functions, which solve the wave equation locally. Tent pitched meshes allow to solve the equation elementwise, allowing locally optimal advances in time. The met

Ansgar Denner, Stefan Dittmaier, Mathieu Pellen, Christopher Schwan

The calculation of electroweak corrections to processes with jets in the final state involves contributions of low-virtuality photons leading to jets in the final state via the singular splitting $γ^* \to q\bar q$. These singularities can be absorbed into a photon-to-jet "fragmentation function", better called "conversion function", since the

Stefan Tappe

We provide existence and uniqueness of global (and local) mild solutions for a general class of semilinear stochastic partial differential equations driven by Wiener processes and Poisson random measures under local Lipschitz and linear growth (or local boundedness, resp.) conditions. The so-called "method of the moving frame" allows us to reduce the SPDE pr

Madita Willsch, Dennis Willsch, Fengping Jin, Hans De Raedt

The performance of the quantum approximate optimization algorithm is evaluated by using three different measures: the probability of finding the ground state, the energy expectation value, and a ratio closely related to the approximation ratio. The set of problem instances studied consists of weighted MaxCut problems and 2-satisfiability problems. The Ising

Pierre Bergé, Benjamin Mouscadet, Arpad Rimmel, Joanna Tomasik

The parameterized complexity of counting minimum cuts stands as a natural question because Ball and Provan showed its #P-completeness. For any undirected graph $G=(V,E)$ and two disjoint sets of its vertices $S,T$, we design a fixed-parameter tractable algorithm which counts minimum edge $(S,T)$-cuts parameterized by their size $p$. Our algorithm operates on

Stefan Tappe

The goal of this review article is to provide a survey about the foundations of semilinear stochastic partial differential equations. In particular, we provide a detailed study of the concepts of strong, weak and mild solutions, establish their connections, and review a standard existence- and uniqueness result. The proof of the existence result is based on

Pablo Pascual Campo, Alberto Brihuega, Lauri Anttila, Matias Turunen

In this paper, new digital predistortion (DPD) solutions for power amplifier (PA) linearization are proposed, with particular emphasis on reduced processing complexity in future 5G and beyond wideband radio systems. The first proposed method, referred to as the spline-based Hammerstein (SPH) approach, builds on complex spline-interpolated lookup table (LUT)

Toshinori Kobayashi

Let R be a Gorenstein local domain of dimension one. We show that a nonfree maximal Cohen--Macaulay R-module M possessing more than one nonfree indecomposable summand in the middle term of the almost split sequence ending in M has a nonvanishing self extension. In other words, we show that the Huneke--Wiegand conjecture is affirmative for such R-modules M.

Eyal Neuman, Xinghua Zheng

We consider a branching random walk on $\mathbb{Z}$ started by $n$ particles at the origin, where each particle disperses according to a mean-zero random walk with bounded support and reproduces with mean number of offspring $1+θ/n$. For $t\geq 0$, we study $M_{nt}$, the rightmost position reached by the branching random walk up to generation $[nt]$. Under c

Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist

Learning by experience in Multi-Agent Systems (MAS) is a difficult and exciting task, due to the lack of stationarity of the environment, whose dynamics evolves as the population learns. In order to design scalable algorithms for systems with a large population of interacting agents (e.g. swarms), this paper focuses on Mean Field MAS, where the number of age

Madhavun Candadai, Eduardo J. Izquierdo

This paper introduces \texttt{infotheory}: a package written in C++ and usable from Python and C++, for multivariate information theoretic analyses of discrete and continuous data. This package allows the user to study the relationship between components of a complex system simply from the data recorded during its operation, using the tools of information th

Yang-guang Yang, Jun Song, Feng-lan Shao, Zuo-tang Liang

We present a new method of solving the probability distribution for baryons, antibaryons and mesons at the hadronization of constituent quark and antiquark system. The hadronization is governed by the quark combination rule in the quark combination model developed by the Shandong Group. We use the method of the generating function to derive the outcome of th

Levon Barseghyan, Maura Coughlin, Francesca Molinari, Joshua C. Teitelbaum

We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between choice sets and preferences. We first characterize the sharp identification regi

Persi Diaconis, Brett Kolesnik

We introduce and study randomized sequential importance sampling algorithms for estimating the number of perfect matchings in bipartite graphs. In analyzing their performance, we establish various non-standard central limit theorems. We expect our methods to be useful for other applied problems.

Jorge Arrieta, Marco Polin, Ramón Saleta-Piersanti, Idan Tuval

Microorganismal motility is often characterised by complex responses to environmental physico-chemical stimuli. Although the biological basis of these responses is often not well understood, their exploitation already promises novel avenues to directly control the motion of living active matter at both the individual and collective level. Here we leverage th

Joachim Toft, Rüya Üster, Elmira Nabizadeh, Serap Öztop

We deduce continuity, compactness and invariance properties for quasi-Banach Orlicz modulation spaces. We characterize such spaces in terms of Gabor expansions and by their images under the Bargmann transform.

Dana Tudor, Livius Trache, Alexandra I. Chilug, Ionut C. Stefanescu

We present a facility for direct measurements at low and very low energies typical for nuclear astrophysics (NA). The facility consists of a small and robust tandem accelerator where irradiations are made, and an ultra-low background laboratory located in a salt mine where very low radio-activities can be measured. Both belong to Horia Hulubei National Insti

Chirag Modi, Martin White, Anze Slosar, Emanuele Castorina

Upcoming 21-cm intensity surveys will use the hyperfine transition in emission to map out neutral hydrogen in large volumes of the universe. Unfortunately, large spatial scales are completely contaminated with spectrally smooth astrophysical foregrounds which are orders of magnitude brighter than the signal. This contamination also leaks into smaller radial

Parinaz Kasebzadeh, Gustaf Hendeby, Fredrik Gustafsson

An approach for computing unique gait signature using measurements collected from body-worn inertial measurement units (IMUs) is proposed. The gait signature represents one full cycle of the human gait, and is suitable for off-line or on-line classification of the gait mode. The signature can also be used to jointly classify the gait mode and the device mode

Aniket Agrawal, Teppei Okumura, Toshifumi Futamase

We show that peculiar velocities of Type Ia supernovae can be used to derive constraints on the sum of neutrino masses, $Σm_ν$, and dark energy equation of state, $w = w_0+w_a(1-a)$, from measurements of the magnitude-redshift relation, complementary to galaxy redshift and weak lensing surveys. Light from a supernova propagates through a perturbed Universe s

Altug Sisman, Alhun Aydin, Jonas Fransson

We propose a mechanism for nanoscale energy conversion, an electric voltage induced by a temperature gradient in a junction composed of the same material having exactly the same geometric sizes, but distinct shapes. The proposed effect appears as a result of only temperature and shape difference, hence it is called thermoshape effect. For GaAs quantum confin

D. A. Green

A revised catalogue of Galactic supernova remnants (SNRs) is presented, along with some simple statistics of their properties. Six new SNRs have been added to the catalogue since the previous published version from 2014, and six entries have been removed, as they have been identified as HII regions, leaving the number of entries in the catalogue at 294. Some

Tsz Kin Lam, Shigehiko Schamoni, Stefan Riezler

We propose an interactive-predictive neural machine translation framework for easier model personalization using reinforcement and imitation learning. During the interactive translation process, the user is asked for feedback on uncertain locations identified by the system. Responses are weak feedback in the form of "keep" and "delete" edits,

Quanzhen Ding, Rupak Chatterjee, Yuping Huang, Ting Yu

Temporal modes of photonic quantum states provide a new framework to develop a robust free-space quantum key distribution (QKD) scheme in a maritime environment. We show that the high-dimensional temporal modes can be used to fulfill a persistent communication channel to achieve high photon-efficiency even in severe weather conditions. We identify the parame

Arthur Charpentier, Alfred Galichon, Lucas Vernet

This article presents a set of tools for the modeling of a spatial allocation problem in a large geographic market and gives examples of applications. In our settings, the market is described by a network that maps the cost of travel between each pair of adjacent locations. Two types of agents are located at the nodes of this network. The buyers choose the m

Jacob Focke, Leslie Ann Goldberg, Stanislav Živný

A retraction is a homomorphism from a graph $G$ to an induced subgraph $H$ of $G$ that is the identity on $H$. In a long line of research, retractions have been studied under various algorithmic settings. Recently, the problem of approximately counting retractions was considered. We give a complete trichotomy for the complexity of approximately counting retr

Fen-Fen Yang

The Harnack and log Harnack inequalities for stochastic differential equation driven by $G$-Brownian motion with multiplicative noise are derived by means of coupling by change of mesure. All of the above results extend the existing ones in the linear expectation setting. Moreover, the gradient estimate generalize the nonlinear results appeared in [11].

Jonathan Rohleder

Given a Schrödinger operator with a real-valued potential on a bounded, convex domain or a bounded interval we prove inequalities between the eigenvalues corresponding to Neumann and Dirichlet boundary conditions, respectively. The obtained inequalities depend partially on monotonicity and convexity properties of the potential. The results are counterparts o

Lucas Brivadis, Jean-Paul Gauthier, Ludovic Sacchelli, Ulysse Serres

Control-affine output systems generically present observability singularities, i.e. inputs that make the system unobservable. This proves to be a difficulty in the context of output feedback stabilization, where this issue is usually discarded by uniform observability assumptions for state feedback stabilizable systems. Focusing on state feedback stabilizabl

Vincent Margot, Jean-Patrick Baudry, Frédéric Guilloux, Olivier Wintenberger

In this paper, we introduce a novel method to generate interpretable regression function estimators. The idea is based on called data-dependent coverings. The aim is to extract from the data a covering of the feature space instead of a partition. The estimator predicts the empirical conditional expectation over the cells of the partitions generated from the

Syed Faisal ur Rahman

This paper constraints dynamic dark energy equation of state (EoS) parameters using the type Ia supernovae from Union 2.1 dataset. The paper also discusses the dependency of dynamic dark energy EoS parameters on the chosen or assumed value of the Hubble Constant. To understand the correlation between the Hubble Constant values and measured dynamic dark energ

Amina Mecherbet

In this paper, we consider $N$ clusters of pairs of particles sedimenting in a viscous fluid. The particles are assumed to be rigid spheres and inertia of both particles and fluid are neglected. The distance between each two particles forming the cluster is comparable to their radii $\frac{1}{N}$ while the minimal distance between the pairs is of order $N^{-

Mazena Mackoit-Sinkeviciene, Marek Maciaszek, Chris G. Van de Walle, Audrius Alkauskas

We propose that the carbon dimer defect in hexagonal boron nitride gives rise to the ubiquitous narrow luminescence band with a zero-phonon line of 4.08 eV (usually labeled the 4.1 eV band). Our first-principles calculations are based on hybrid density functionals that provide a reliable description of wide band-gap materials. The calculated zero-phonon line

Stephen Lack, Giacomo Tendas

Regular and exact categories were first introduced by Michael Barr in 1971; since then, the theory has developed and found many applications in algebra, geometry, and logic. In particular, a small regular category determines a certain theory, in the sense of logic, whose models are the regular functors into Set. Barr further showed that each small and regula

Junjie Cao, Zi Lin, Weiwei Sun, Xiaojun Wan

We present a phenomenon-oriented comparative analysis of the two dominant approaches in task-independent semantic parsing: classic, knowledge-intensive and neural, data-intensive models. To reflect state-of-the-art neural NLP technologies, we introduce a new target structure-centric parser that can produce semantic graphs much more accurately than previous d

Alessio Savini

We introduce the notion of pullback along a measurable cocycle and we use it to extend the Borel invariant studied by Bucher, Burger and Iozzi to the world of measurable cocycles. The Borel invariant is constant along cohomology classes and has bounded absolute value. This allows to define maximal cocycles. We conclude by proving that maximal cocycles are ac

Umut Kamber, Anders Bergman, Andreas Eich, Diana Iuşan

Spin glasses are a highly complex magnetic state of matter, intricately linked to spin frustration and structural disorder. They exhibit no long-range order and exude aging phenomena, distinguishing them from quantum spin liquids. We report a new type of spin glass state, the spin-Q glass, observable in bulk-like crystalline metallic neodymium thick films. U

Mohit Singh, Neha Gawande, Y. S. Mayya, Rochish Thaokar

The breakup pathway of Rayleigh fission of a charged drop is unequivocally demonstrated by first of its kind, continuous, high-speed imaging of a drop levitated in an AC quadrupole trap. The experimental observations consistently exhibited asymmetric, sub-critical Rayleigh breakup with an upward (i.e. opposite to the direction of gravity) ejection of a jet f

Vojtěch Trávníček, Karol Bartkiewicz, Antonín Černoch, Karel Lemr

We report on experimental measurement of the Hilbert-Schmidt distance between two two-qubit states by many-particle interference. We demonstrate that our three-step method for measuring distances in Hilbert space is far less complex than reconstructing density matrices and that it can be applied in quantum-enhanced machine learning to reduce the complexity o

Elisa Hartmann

This paper studies the asymptotic product of two metric spaces. It is well defined if one of the spaces is visual or if both spaces are geodesic. In this case the asymptotic product is the pullback of a limit diagram in the coarse category. Using this product construction we can define a homotopy theory on coarse metric spaces in a natural way. We prove that

Konstantinos Makantasis, Antonios Liapis, Georgios N. Yannakakis

Is it possible to predict the affect of a user just by observing her behavioral interaction through a video? How can we, for instance, predict a user's arousal in games by merely looking at the screen during play? In this paper we address these questions by employing three dissimilar deep convolutional neural network architectures in our attempt to learn

Zhibo Chen, Jun Shi, Weiping Li

In High Efficiency Video Coding (HEVC), excellent rate-distortion (RD) performance is achieved in part by having a flexible quadtree coding unit (CU) partition and a large number of intra-prediction modes. Such an excellent RD performance is achieved at the expense of much higher computational complexity. In this paper, we propose a learned fast HEVC intra c

Kewei Zhang, Antonio Orlando, Elaine Crooks

Compensated convex transforms have been introduced for extended real-valued functions defined over $\mathbb{R}^n$. In their application to image processing, interpolation, and shape interrogation, where one deals with functions defined over a bounded domain, one was making the implicit assumption that the function coincides with its transform at the boundary

Yu. V. Krasnikova, V. N. Glazkov, A. Ponomaryov, S. A. Zvyagin

We have studied electron spin resonance (ESR) absorption spectra for the nonmagnetically diluted strong-leg spin ladder magnet ({C}$_{7}$H$_{10}$N)$_{2}$Cu$_{(1-x)}$Zn$_{x}$Br$_{4}$ (abbreviated as DIMPY) down to 450 mK. Formation of the clusters with non-zero net magnetization is confirmed; the cluster-cluster interaction is evidenced by the concentration d

Zhichao Fu, Tianlong Ma, Yingbin Zheng, Hao Ye

Image deblurring is a fundamental and challenging low-level vision problem. Previous vision research indicates that edge structure in natural scenes is one of the most important factors to estimate the abilities of human visual perception. In this paper, we resort to human visual demands of sharp edges and propose a two-phase edge-aware deep network to impro

Nicola Garofalo, Giulio Tralli

In this paper we establish optimal isoperimetric inequalities for a nonlocal perimeter adapted to the fractional powers of a class of Kolmogorov-Fokker-Planck operators which are of interest in physics. These operators are very degenerate and do not possess a variational structure. The prototypical example was introduced by Kolmogorov in his 1938 paper on br

Andrey Dymov, Sergei Kuksin

In this paper we continue to study small amplitude solutions of the damped cubic NLS equation, driven by a random force (the study was initiated in our previous work [A.Dymov, S.Kuksin, Comm. Math. Phys.'2021] and continued in [A.Dymov, S.Kuksin, A.Maiocchi, S.Vladuts, arXiv:2104.11967]). We write solutions of the equation as formal series in the amplitu

Shuhao Xia, Yuanming Shi

Although deep learning has shown its powerful performance in many applications, the mathematical principles behind neural networks are still mysterious. In this paper, we consider the problem of learning a one-hidden-layer neural network with quadratic activations. We focus on the under-parameterized regime where the number of hidden units is smaller than th