November 2018 arXiv papers — page 8

Andreas Bächle, Geoffrey Janssens, Eric Jespers, Ann Kiefer

We show that $\mathcal{U}(\mathbb{Z}G)$, the unit group of the integral group ring $\mathbb{Z} G$, either satisfies Kazhdan's property (T) or is, up to commensurability, a non-trivial amalgamated product, in case $G$ is a finite group satisfying some mild conditions. Crucial in the proof is the construction of amalgamated decompositions of the elementary

Raphael Butez, David García-Zelada

We study the outliers for two models which have an interesting connection. On the one hand, we study a specific class of planar Coulomb gases which are determinantal. It corresponds to the case where the confining potential is the logarithmic potential of a radial probability measure. On the other hand, we study the zeros of random polynomials that appear to

Xibin Song, Peng Wang, Dingfu Zhou, Rui Zhu

Autonomous driving has attracted remarkable attention from both industry and academia. An important task is to estimate 3D properties(e.g.translation, rotation and shape) of a moving or parked vehicle on the road. This task, while critical, is still under-researched in the computer vision community - partially owing to the lack of large scale and fully-annot

Richard A. Fauli, Jean Rabault, Andreas Carlson

Wind dispersal of seeds is one essential mechanisms for plants to proliferate and to invade new territories. In this paper we present a methodology that combines 3D-printing, a minimal theoretical model and experiments to determine the shape of multi-winged autorotating seeds, fruits and other diaspores that provide them with the optimal wind dispersion pote

David Sprehn, Nathalie Wahl

We give an overview of the general framework of forms of Bak, Tits and Wall, when restricting to vector spaces over fields, and describe its relationship to the classical notions of Hermitian, alternating and quadratic forms. We then prove a version of Witt's lemma in this context, showing in particular that the action of the group of isometries of a spa

Xing-yuan Hou, Zong Wang, Ya-dong Gu, Jun-bao He

We report the observation of local superconductivity induced at the point contact formed between a normal metal tip and WC -- a triple point topological semimetal with super hardness. Remarkably, the maximum critical temperature is up to near 12 K but insensitive to the tip's magnetism. The lateral dimensions of the superconducting puddles were evaluated

Philipp Otte, Martin Frank

We introduce a structured approach to the construction of linear BGK-type collision operators ensuring that the resulting Lattice-Boltzmann methods are stable with respect to a weighted $L^2$-norm. The results hold for particular boundary conditions including periodic, bounce-back, and bounce-back with flipping of sign. This construction uses the equivalent

Maxime Fevrier, Mitja Mastnak, Alexandru Nica, Kamil Szpojankowski

We consider two extensions of free probability that have been studied in the research literature, and are based on the notions of c-freeness and respectively of infinitesimal freeness for noncommutative random variables. In a 2012 paper, Belinschi and Shlyakhtenko pointed out a connection between these two frameworks, at the level of their operations of 1-di

Erfan Zamanian, Julian Shun, Carsten Binnig, Tim Kraska

Distributed transactions on high-overhead TCP/IP-based networks were conventionally considered to be prohibitively expensive and thus were avoided at all costs. To that end, the primary goal of almost any existing partitioning scheme is to minimize the number of cross-partition transactions. However, with the new generation of fast RDMA-enabled networks, thi

Mou Wu, Naixue Xiong, Liansheng Tan

In this paper, we investigate the convergence performance of a cooperative diffusion Gauss-Newton (GN) method, which is widely used to solve the nonlinear least squares problems (NLLS) due to the low computation cost compared with Newton's method. This diffusion GN collects the diversity of temporalspatial information over the network, which is used on l

Janina Gärtner, Rainer Mandel, Wolfgang Reichel

In this paper we investigate the effect of nonlinear damping on the Lugiato-Lefever equation $$ ı\partial_t a = -(ı-ζ) a - da_{xx} -(1+ıκ)|a|^2a +ıf $$ on the torus or the real line. For the case of the torus it is shown that for small nonlinear damping $κ>0$ stationary spatially periodic solutions exist on branches that bifurcate from constant solutions whe

Filippos Kokkinos, Stamatios Lefkimmiatis

Modern inexpensive imaging sensors suffer from inherent hardware constraints which often result in captured images of poor quality. Among the most common ways to deal with such limitations is to rely on burst photography, which nowadays acts as the backbone of all modern smartphone imaging applications. In this work, we focus on the fact that every frame of

Huan Cao, She-Cheng Gao, Chao Zhang, Jian Wang

High-dimensional entanglement has demonstrated potential for increasing channel capacity and resistance to noise in quantum information processing. However, its distribution is a challenging task, imposing a severe restriction on its application. Here we report the first distribution of three-dimensional orbital angular momentum (OAM) entanglement via a 1-km

Erin R. Higgins, Jorick S. Vink

We aim to constrain massive star evolution models using the unique testbed eclipsing binary HD166734 with new grids of MESA stellar evolution models, adopting calibrated prescriptions of overshooting, mass loss, and rotation. We introduce a novel tool: the "mass-luminosity plane" or "M-L plane", as an equivalent to the traditional HR diagram,

Andreas Bächle, Geoffrey Janssens, Eric Jespers, Ann Kiefer

Let $G$ be a finite group and $\mathcal{U} (\mathbb{Z} G)$ the unit group of the integral group ring $\mathbb{Z} G$. We prove a unit theorem, namely a characterization of when $\mathcal{U}(\mathbb{Z}G)$ satisfies Kazhdan's property $(\operatorname{T})$, both in terms of the finite group $G$ and in terms of the simple components of the semisimple algebra

Bastian Hilder

We consider the one-dimensional Swift-Hohenberg equation coupled to a conservation law. As a parameter increases the system undergoes a Turing bifurcation. We study the dynamics near this bifurcation. First, we show that stationary, periodic solutions bifurcate from a homogeneous ground state. Second, we construct modulating traveling fronts which model an i

Yang Liu, Ning Chen, Yang Li

The critical temperature (${T}_\text{c}$) of superconductors varies a lot. The factors governing the ${T}_\text{c}$ may hold key clues to understand the nature of the superconductivity. Thereby, ${T}_\text{c}$-involved correlations, such as Matthias laws, Uemura law, and cuprates doping phase diagrams, have been of great concern. However, the electronic inte

Horatio Boedihardjo, Xi Geng, Nikolaos P. Souris

Solutions to linear controlled differential equations can be expressed in terms of iterated path integrals of the driving path. This collection of iterated integrals encodes essentially all information about the driving path. While upper bounds for iterated path integrals are well known, lower bounds are much less understood, and it is known only relatively

Niels Feld

We generalize Rost's theory of cycle modules using Milnor-Witt K-theory instead of the classical Milnor K-theory. We obtain a (quadratic) setting to study general cycle complexes and their (co)homology groups. The usual constructions are developed: proper pushfoward, (essentially) smooth pullback, long exact sequences, (coniveau) spectral sequences and p

Jakob Schneider

We show that every non-trivial compact connected group and every non-trivial general or special linear group over an infinite field admits a generating set such that the associated Cayley graph has infinite diameter.

Hila Levi, Shimon Ullman

An image is not just a collection of objects, but rather a graph where each object is related to other objects through spatial and semantic relations. Using relational reasoning modules, such as the non-local module \cite{wang2017non}, can therefore improve object detection. Current schemes apply such dedicated modules either to a specific layer of the botto

Giovanni Pinamonti, Fabian Paul, Frank Noé, Alex Rodriguez

The process of RNA base fraying (i.e. the transient opening of the termini of a helix) is involved in many aspects of RNA dynamics. We here use molecular dynamics simulations and Markov state models to characterize the kinetics of RNA fraying and its sequence and direction dependence. In particular, we first introduce a method for determining biomolecular dy

Zhi-Gang Wang, Zun-Yan Di

In this article, we construct both the $[sc]_T[\bar{s}\bar{c}]_A+[sc]_A[\bar{s}\bar{c}]_T$ type and $[sc]_T[\bar{s}\bar{c}]_V-[sc]_V[\bar{s}\bar{c}]_T$ type axialvector currents with $J^{PC}=1^{++}$ to study the mass of the $X(4140)$ with the QCD sum rules. The predicted masses support assigning the $X(4140)$ to be the $[sc]_T[\bar{s}\bar{c}]_V-[sc]_V[\bar{s

Imanol Schlag, Jürgen Schmidhuber

We combine Recurrent Neural Networks with Tensor Product Representations to learn combinatorial representations of sequential data. This improves symbolic interpretation and systematic generalisation. Our architecture is trained end-to-end through gradient descent on a variety of simple natural language reasoning tasks, significantly outperforming the latest

Juan R. Carmona, Jonnathan Rodríguez

Let $G$ be a graph on $n$ vertices and $λ_1\geq λ_2\geq \ldots \geq λ_n$ its eigenvalues. The Estrada index of $G$ is defined as $EE(G)=\sum_{i=1}^n e^{λ_i}.$ In this work, we using an increasing sequence converging to the $λ_1$ to obtain an increasing sequence of lower bounds for $EE(G)$. In addition, we generalize this succession for the Estrada index of a

Michael Finkelberg, Alexander Tsymbaliuk

We define an integral form of shifted quantum affine algebras of type $A$ and construct Poincaré-Birkhoff-Witt-Drinfeld bases for them. When the shift is trivial, our integral form coincides with the RTT integral form. We prove that these integral forms are closed with respect to the coproduct and shift homomorphisms. We prove that the homomorphism from our

Yan Liu, Rui-Yun Guo, Jing-Fei Zhang, Xin Zhang

We investigate whether the current Hubble parameter $H(z)$ measurements could help improve the constraints on dark energy on the basis of the mainstream cosmological probes including the type Ia supernovae (SN) observation, the cosmic microwave background anisotropies (CMB) observation, and the baryon acoustic oscillations (BAO) observation. For the current

Daria Smirnova, Sergey Kruk, Daniel Leykam, Elizaveta Melik-Gaykazyan

We study nonlinear effects in two-dimensional photonic metasurfaces supporting topologically-protected helical edge states at the nanoscale. We observe strong third-harmonic generation mediated by optical nonlinearities boosted by multipolar Mie resonances of silicon nanoparticles. Variation of the pump-beam wavelength enables independent high-contrast imagi

Anton Fuxjaeger, Vaishak Belle

Weighted model integration (WMI) extends weighted model counting (WMC) in providing a computational abstraction for probabilistic inference in mixed discrete-continuous domains. WMC has emerged as an assembly language for state-of-the-art reasoning in Bayesian networks, factor graphs, probabilistic programs and probabilistic databases. In this regard, WMI sh

Christine Dahn, Nils M. Kriege, Petra Mutzel, Julian Schilling

We propose two fixed-parameter tractable algorithms for the weighted Max-Cut problem on embedded 1-planar graphs parameterized by the crossing number $k$ of the given embedding. A graph is called 1-planar if it can be drawn in the plane with at most one crossing per edge. Our algorithms recursively reduce a 1-planar graph to at most $3^k$ planar graphs, usin

Ezio Vasselli

The basic aspects of the Aharonov-Bohm effect can be summarized by the remark that wavefunctions become sections of a line bundle with a flat connection (that is, a "flat potential"). Passing at the level of quantum field theory in curved spacetimes, we study the Dirac field interacting with a classical (background) flat potential and show that it ca

Davide Marucci, Matteo Carpentieri

The effects of a stably-stratified boundary layer on flow and dispersion in a bi-dimensional street canyon have been investigated experimentally in a wind tunnel in combination with differential wall heating. Laser-Doppler anemometry together with a fast flame ionisation detector and cold-wire anemometry were employed to sample velocities, concentration, tem

Lia Ahrens, Julian Ahrens, Hans D. Schotten

In this paper we propose a novel machine-learning method for anomaly detection applicable to data with periodic characteristics where randomly varying period lengths are explicitly allowed. A multi-dimensional time series analysis is conducted by training a data-adapted classifier consisting of deep convolutional neural networks performing phase classificati

Felix Aharonian, Giada Peron, Ruizhi Yang, Sabrina Casanova

High energy $γ$ rays from Giant Molecular Clouds (GMCs) carry direct information about the spatial and energy distributions of Galactic Cosmic Rays (CRs). The recently released catalogs of GMCs contain sufficiently massive clouds to be used as barometers for probing, through their $γ$-ray emission, the density of CRs throughout the Galactic Disk. Based on th

Joerg Jaeckel, Sebastian Schenk

Calculations of high multiplicity Higgs amplitudes exhibit a rapid growth that may signal an end of perturbative behavior or even the need for new physics phenomena. As a step towards this problem we consider the quantum mechanical equivalent of $1 \to n$ scattering amplitudes in a spontaneously broken $ϕ^4$-theory by extending our previous results on the qu

D. Petter, G. Natale, R. M. W. van Bijnen, A. Patscheider

We measure the excitation spectrum of a stable dipolar Bose--Einstein condensate over a wide momentum-range via Bragg spectroscopy. We precisely control the relative strength, $ε_{\rm dd}$, of the dipolar to the contact interactions and observe that the spectrum increasingly deviates from the linear phononic behavior for increasing $ε_{\rm dd}$. Reaching the

Xiaoyu Chen, Gerhard Reinelt, Guangming Dai, Andreas Spitz

We address the multi-satellite scheduling problem with limited observation capacities that arises from the need to observe a set of targets on the Earth's surface using imaging resources installed on a set of satellites. We define and analyze the conflict indicators of all available visible time windows of missions, as well as the feasible time intervals

ATLAS Collaboration

This paper presents measurements of $t\bar{t}$ production in association with additional $b$-jets in $pp$ collisions at the LHC at a centre-of-mass energy of 13 TeV. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 36.1 fb$^{-1}$. Fiducial cross-section measurements are performed in the dilepton and lepton-plus-jet

R. Thomas McCoy, Tal Linzen

Neural network models have shown great success at natural language inference (NLI), the task of determining whether a premise entails a hypothesis. However, recent studies suggest that these models may rely on fallible heuristics rather than deep language understanding. We introduce a challenge set to test whether NLI systems adopt one such heuristic: assumi

Camilo Moreno, Juan-Diego Urbina

We investigate the emergence of temperature $T$ in the system-plus-reservoir paradigm starting from the fundamental microcanonical scenario at total fixed energy $E$ where, contrary to the canonical approach, $T=T(E)$ is not a control parameter but a derived auxiliary concept. As shown by Schwinger for the regime of weak coupling $γ$ between subsystems, $T(E

C. J. F. van de Ven, G. C. Groenenboom, R. Reuvers, N. P. Landsman

Spontaneous symmetry breaking (SSB) is mathematically tied to some limit, but must physically occur, approximately, before the limit. Approximate SSB has been independently understood for Schroedinger operators with double well potential in the classical limit (Jona-Lasinio et al, 1981; Simon, 1985) and for quantum spin systems in the thermodynamic limit (An

Kilho Son, Jesse Hostetler, Sek Chai

Complex image processing and computer vision systems often consist of a processing pipeline of functional modules. We intend to replace parts or all of a target pipeline with deep neural networks to achieve benefits such as increased accuracy or reduced computational requirement. To acquire a large amount of labeled data necessary to train the deep neural ne

Aleksandar Mijatović, Veno Mramor, Gerónimo Uribe Bravo

We describe an exact simulation algorithm for the increments of Brownian motion on a sphere of arbitrary dimension, based on the skew-product decomposition of the process with respect to the standard geodesic distance. The radial process is closely related to a Wright-Fisher diffusion, increments of which can be simulated exactly using the recent work of Jen

V. Tadayon

This article has been removed by arXiv administrators due to falsified authorship.

Francesco Pace, Carlo Schimd, David F. Mota, Antonino Del Popolo

The evolution of the virial overdensity $Δ_{\rm vir}$ for $Λ$CDM and seven dynamical dark-energy models is investigated in the extended spherical collapse model (SCM). Here the virialization process is naturally achieved by introducing shear and rotation instead of using the virial theorem. We generalise two approaches proposed in the literature and show tha

Mikihiro Tanaka, Takayuki Itamochi, Kenichi Narioka, Ikuro Sato

This paper addresses the generation of referring expressions that not only refer to objects correctly but also let humans find them quickly. As a target becomes relatively less salient, identifying referred objects itself becomes more difficult. However, the existing studies regarded all sentences that refer to objects correctly as equally good, ignoring whe

Anna Jenčová, Martin Plávala

The aim of this paper is to show that there can be either only one or uncountably many contexts in any spectral effect algebra, answering a question posed in [S. Gudder, Convex and Sequential Effect Algebras, (2018), arXiv:1802.01265]. We also provide some results on the structure of spectral effect algebras and their state spaces and investigate the direct

Oylum Şeker, Tınaz Ekim, Z. Caner Taşkın

We consider the selective graph coloring problem, which is a generalization of the classical graph coloring problem. Given a graph together with a partition of its vertex set into clusters, we want to choose exactly one vertex per cluster so that the number of colors needed to color the selected set of vertices is minimized. This problem is known to be NP-ha

Nikolaj Roth, Bo B. Iversen

High-performing thermoelectric materials such as Zn$_4$Sb$_3$ and clathrates have atomic disorder as the root to their favorable properties. This makes it extremely difficult to understand and model their properties at a quantitative level, and thus effective structure-property relations are challenging to obtain. Cu$_{2-x}$Se is an intensely studied, cheap

Zeinab Rezaei, Habib Yousefi Dezdarani

Ferromagnetic spin ordering can take place in neutron stars. This phase transition alters the neutron star equation of state. Here, applying the scalar-tensor theories of gravity, we investigate the structure of neutron stars which are in the ferromagnetic phase. Considering the equation of state of ferromagnetic neutron matter with Skyrme-type interactions

Deepak Sirone, Pramod Subramanyan

Logic locking refers to a set of techniques that can protect integrated circuits (ICs) from counterfeiting, piracy and malicious functionality changes by an untrusted foundry. It achieves these goals by introducing new inputs, called key inputs, and additional logic to an IC such that the circuit produces the correct output only when the key inputs are set t

Nico Potyka

Probabilistic argumentation allows reasoning about argumentation problems in a way that is well-founded by probability theory. However, in practice, this approach can be severely limited by the fact that probabilities are defined by adding an exponential number of terms. We show that this exponential blowup can be avoided in an interesting fragment of episte

E. Erdal, A. Tesi, D. Vartsky, S. Bressler

First imaging results in liquid xenon of a Liquid Hole Multiplier (LHM) coupled to a Quad-Silicon Photomultiplier (SiPM) array are presented. Ionization electrons deposited in the noble liquid by 5.5 MeV alpha particles, are collected into the holes of a Thick Gas Electron Multiplier (THGEM) electrode having a xenon gas bubble trapped underneath. They drift

Akash Anand, Sameer Chavan, Shailesh Trivedi

The wandering subspace problem for an analytic norm-increasing $m$-isometry $T$ on a Hilbert space $\mathcal H$ asks whether every $T$-invariant subspace of $\mathcal H$ can be generated by a wandering subspace. An affirmative solution to this problem for $m=1$ is ascribed to Beurling-Lax-Halmos, while that for $m=2$ is due to Richter. In this paper, we capi

Manuel González-Navarrete, Rodrigo Lambert

We propose a model for diffusion of two opposite opinions. Here, the decision to be taken by each individual is a random variable which depends on the tendency of the population, as well on its own trend characteristic. The influence of the population trend can be positive, negative or non-existent in a random form. We prove a phase transition in the behavio

Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo

Embedded deep learning platforms have witnessed two simultaneous improvements. First, the accuracy of convolutional neural networks (CNNs) has been significantly improved through the use of automated neural-architecture search (NAS) algorithms to determine CNN structure. Second, there has been increasing interest in developing hardware accelerators for CNNs

David Saltiel, Eric Benhamou

In machine learning, Feature Selection (FS) is a major part of efficient algorithm. It fuels the algorithm and is the starting block for our prediction. In this paper, we present a new method, called Optimal Coordinate Ascent (OCA) that allows us selecting features among block and individual features. OCA relies on coordinate ascent to find an optimal soluti

Dante M. Kennes, Niclas Müller, Mikhail Pletyukhov, Clara Weber

We study one-dimensional (1D) Floquet topological insulators with chiral symmetry going beyond the standard rotating wave approximation. The occurrence of many anticrossings between Floquet replicas leads to a dramatic extension of phase diagram regions with stable topological edge states (TESs). We present an explicit construction of all TESs in terms of a

Cees de Valk, Johan Segers

For the basic case of $L_2$ optimal transport between two probability measures on a Euclidean space, the regularity of the coupling measure and the transport map in the tail regions of these measures is studied. For this purpose, Robert McCann's classical existence and uniqueness results are extended to a class of possibly infinite measures, finite outsi

Luca Fabbri, Manuel Tecchiolli

Torsion propagation and torsion-spin coupling are studied in the perspective of the Velo-Zwanziger method of analysis; specifically, we write the most extensive dynamics of the torsion tensor and the most exhaustive coupling that is permitted between torsion and spinors, and check the compatibility with constraints and hyperbolicity and causality of field eq

Motohiko Ezawa

Non-Hermitian skin-edge states emerge only at one edge in one-dimensional nonreciprocal chains, where all states are localized at the edge irrespective of eigenvalues. The bulk topological number is the winding number associated with the complex energy spectrum, which is well defined for metals. We study non-Hermitian nonreciprocal systems in higher dimensio

Joydeep Roy

Anomalies in recent LHCb, Belle and Babar measurements of $R_{D^{(*)}}$, and $R_{K^{(*)}}$ in $B$ decays may indicate the new physics beyond the Standard Model (SM). The leptoquarks ($LQ$) that couple to the $3^{\mathrm{rd}}$ generation quarks and leptons have been proposed as a viable new physics (NP) explanation. Such left-handed $LQ$s can couple to both b

L. M. Slad

A number of characteristics of the new fundamental interaction are described. The interaction is carried by a massless pseudoscalar boson and extends to at least the electron neutrino, proton, and neutron. A substantiation of the existence of such an interaction is supported by an good agreement between the theoretical and experimental rates of all the five

Daniel J. Trosten, Andreas S. Strauman, Michael Kampffmeyer, Robert Jenssen

The task of clustering unlabeled time series and sequences entails a particular set of challenges, namely to adequately model temporal relations and variable sequence lengths. If these challenges are not properly handled, the resulting clusters might be of suboptimal quality. As a key solution, we present a joint clustering and feature learning framework for

Xutong Ren, Lingxi Xie, Chen Wei, Siyuan Qiao

Computer vision is difficult, partly because the desired mathematical function connecting input and output data is often complex, fuzzy and thus hard to learn. Coarse-to-fine (C2F) learning is a promising direction, but it remains unclear how it is applied to a wide range of vision problems. This paper presents a generalized C2F framework by making two techn

Liron Levy, Moshe Goldstein

In recent years, tools from quantum information theory have become indispensable in characterizing many-body systems. In this work, we employ measures of entanglement to study the interplay between disorder and the topological phase in 1D systems of the Kitaev type, which can host Majorana end modes at their edges. We find that the entanglement entropy may a

Jun-Hyuk Kim, Jun-Ho Choi, Manri Cheon, Jong-Seok Lee

In recent years, single image super-resolution (SR) methods based on deep convolutional neural networks (CNNs) have made significant progress. However, due to the non-adaptive nature of the convolution operation, they cannot adapt to various characteristics of images, which limits their representational capability and, consequently, results in unnecessarily

Zhan-Chao Hu, Stephen H. Davis, Xin-Rong Zhang

Near the thermodynamic critical point, the physical properties of binary fluids exhibit large variations in response to small temperature and concentration differences, whose effects on the onset of double-diffusive convection are reported here. The vertical symmetry is broken, irregular penetrative instability occurs, and cat's eye patterns are identifi

Brendan Avent, Yatharth Dubey, Aleksandra Korolova

We explore the power of the hybrid model of differential privacy (DP), in which some users desire the guarantees of the local model of DP and others are content with receiving the trusted-curator model guarantees. In particular, we study the utility of hybrid model estimators that compute the mean of arbitrary real-valued distributions with bounded support.

Hiroaki Ishida, Roman Krutowski, Taras Panov

We describe the basic cohomology ring of the canonical holomorphic foliation on a moment-angle manifold, LVMB-manifold or any complex manifold with a maximal holomorphic torus action. Namely, we show that the basic cohomology has a description similar to the cohomology ring of a complete simplicial toric variety due to Danilov and Jurkiewicz. This settles a

Hayato Takahashi

In this paper we show the distributions of sliding block patterns for Bernoulli processes with finite alphabet, which is not based on the induction on sample size. We show a new inclusion-exclusion formula in multivariate generating function form on partially ordered sets, and show a simpler expression of generating functions of the number of pattern occurre

Siwen Jiang, Wenxuan Wei, Shihao Guo, Hongguang Fu

At present, the great achievements of convolutional neural network(CNN) in feature and metric learning have attracted many researchers. However, the vast majority of deep network architectures have been used to represent based on real values. The research of complex-valued networks is seldom concerned due to the absence of effective models and suitable dista

Valentina Brosco, Massimo Capone

The recent discovery of materials featuring strong Rashba spin-orbit coupling (RSOC) and strong electronic correlation raises questions about the interplay of Mott and Rashba physics. In this work, we employ cluster perturbation theory to investigate the spectral properties of the two-dimensional Hubbard model in the presence of a significant or large RSOC.

Deepak Sarma

In this article, we establish some bounds involving the largest two distance Pareto eigenvalues of a connected graph. Also we characterize all possible values for smallest six distance Pareto eigenvalues of a connected graph.

Qing Song, Yingqi Wu, Lu Yang

With the broad use of face recognition, its weakness gradually emerges that it is able to be attacked. So, it is important to study how face recognition networks are subject to attacks. In this paper, we focus on a novel way to do attacks against face recognition network that misleads the network to identify someone as the target person not misclassify incon

S. M. Troshin, N. E. Tyurin

The reflective scattering mode is supposed to play a significant role in hadron interactions at the LHC energy region and beyond. We discuss connection of this mode to the color conducting medium formation in hadron collisions and its role in centrality determination. The issues of centrality in view of the measurements at the LHC are relevant for enlighteni

Marco Edoardo Rosti, Stefano Olivieri, Arash A. Banaei, Luca Brandt

The flapping states of a flexible fiber fully coupled to a three-dimensional turbulent flow are investigated via state-of-the-art numerical methods. Two distinct flapping regimes are predicted by the phenomenological theory recently proposed by Rosti et al. [Phys. Rev. Lett. 121, 044501, 2018]: the under-damped regime, where the elasticity strongly affects t

Victor Volfson

The summation arithmetic functions with asymptotically independent summands are studied in the paper. We prove statements about the condition under which the summation arithmetic functions have asymptotically independent summands. It is also prove that the limiting distribution of the summation arithmetic function with asymptotically independent summands is

Yan Li, Xiaohua Zhu

In this paper, we compute Tian's $α_{m,k}^{K\times K}$-invariant on a polarized $G$-group compactification, where $K$ denotes a maximal compact subgroup of a connected complex reductive group $G$. We prove that Tian's conjecture (see Conjecture 1.1 below) is true for $α_{m,k}^{K\times K}$-invariant on such manifolds when $k=1$, but it fails in genera

Frank Göhmann, Salvish Goomanee, Karol K. Kozlowski, Junji Suzuki

This work develops a rigorous setting allowing one to prove several features related to the behaviour of the Heisenberg-Ising (or XXZ) spin-$1/2$ chain at finite temperature $T$. Within the quantum inverse scattering method the physically pertinent observables at finite $T$, such as the \textit{per}-site free energy or the correlation length, have been argue

Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse

Large-scale distributed training of deep neural networks suffer from the generalization gap caused by the increase in the effective mini-batch size. Previous approaches try to solve this problem by varying the learning rate and batch size over epochs and layers, or some ad hoc modification of the batch normalization. We propose an alternative approach using

Daniil Polykovskiy, Alexander Zhebrak, Benjamin Sanchez-Lengeling, Sergey Golovanov

Generative models are becoming a tool of choice for exploring the molecular space. These models learn on a large training dataset and produce novel molecular structures with similar properties. Generated structures can be utilized for virtual screening or training semi-supervised predictive models in the downstream tasks. While there are plenty of generative

Zhihua Liu, Pierre Magal

In this article we study a class of delay differential equations with infinite delay in weighted spaces of uniformly continuous functions. We focus on the integrated semigroup formulation of the problem and so doing we provide an spectral theory. As a consequence we obtain a local stability result and a Hopf bifurcation theorem for the semiflow generated by

Xiang Gao, Wei Hu, Jiaxiang Tang, Jiaying Liu

With the prevalence of accessible depth sensors, dynamic human body skeletons have attracted much attention as a robust modality for action recognition. Previous methods model skeletons based on RNN or CNN, which has limited expressive power for irregular skeleton joints. While graph convolutional networks (GCN) have been proposed to address irregular graph-

Audace A. V. Dossou-Olory, Stephan Wagner

The quantity that captures the asymptotic value of the maximum number of appearances of a given topological tree (a rooted tree with no vertices of outdegree $1$) $S$ with $k$ leaves in an arbitrary tree with sufficiently large number of leaves is called the inducibility of $S$. Its precise value is known only for some specific families of trees, most of the

Olivier Guédon, A. E. Litvak, K. Tatarko

Let $Γ$ be an $N\times n$ random matrix with independent entries and such that in each row entries are i.i.d. Assume also that the entries are symmetric, have unit variances, and satisfy a small ball probabilistic estimate uniformly. We investigate properties of the corresponding random polytope $Γ^* B_1^N$ in $\mathbb{R}$ (the absolute convex hull of rows o

Zilin Gao, Jiangtao Xie, Qilong Wang, Peihua Li

Deep Convolutional Networks (ConvNets) are fundamental to, besides large-scale visual recognition, a lot of vision tasks. As the primary goal of the ConvNets is to characterize complex boundaries of thousands of classes in a high-dimensional space, it is critical to learn higher-order representations for enhancing non-linear modeling capability. Recently, Gl

Huseyin Coskun

This article develops a new mathematical method for holistic analysis of nonlinear dynamic compartmental systems through the system decomposition theory. The method is based on the novel dynamic system and subsystem partitioning methodologies through which compartmental systems are decomposed to the utmost level. The dynamic system and subsystem partitioning

H. Ebrahim, M. Asadi, M. Ali-Akbari

The holographic complexity has been studied in a background which includes a critical point in the dual field theory. We have examined how the complexity rate and the saturation time of dynamical variables in the theory behave as one moves towards the critical point. Two significant results of our analysis are that (i) it takes more time for the complexity i

Yann Traonmilin, Jean-François Aujol

The sparse spike estimation problem consists in estimating a number of off-the-grid impulsive sources from under-determined linear measurements. Information theoretic results ensure that the minimization of a non-convex functional is able to recover the spikes for adequately chosen measurements (deterministic or random). To solve this problem, methods inspir

Yahui Sun

The Steiner tree problems are well-known NP-hard problems that have diverse applications. Duin et al. (2004) have intuitively proposed the widely-used transformation from the classical group Steiner tree problem to the classical Steiner tree problem in graphs. This transformation has not been rigorously proven so far. Specifically, the large M value that is

Manik Singhal, Tolunay Seyfi, Aly El Gamal

We study information theoretic models of interference networks that consist of K Base Station (BS) - Mobile Terminal (MT) pairs. Each BS is connected to the MT carrying the same index as well as L following MTs. We fix the value of L and study the per user Degrees of Freedom (puDoF) in large networks. We assume that each MT can be associated with N BSs, and

Ken Sakurada, Mikiya Shibuya, Weimin Wang

This paper presents a novel semantic scene change detection scheme with only weak supervision. A straightforward approach for this task is to train a semantic change detection network directly from a large-scale dataset in an end-to-end manner. However, a specific dataset for this task, which is usually labor-intensive and time-consuming, becomes indispensab

Tiantian Mao, Bin Wang, Ruodu Wang

In this paper, we analyze the set of all possible aggregate distributions of the sum of standard uniform random variables, a simply stated yet challenging problem in the literature of distributions with given margins. Our main results are obtained for two distinct cases. In the case of dimension two, we obtain four partial characterization results. An analyt

Alexey E. Rastegin

We accomplish studies of properly quantifying eavesdropper's information gain in individual attacks on the BB84 system of quantum key distribution. A noticeable sensitivity of conclusions to the choice of information measures is brightly revealed, when generalized state discrimination is used at the last stage. To realize her aims, Eve intrudes into the

Shang-Ta Yang, Fu-En Wang, Chi-Han Peng, Peter Wonka

We present a deep learning framework, called DuLa-Net, to predict Manhattan-world 3D room layouts from a single RGB panorama. To achieve better prediction accuracy, our method leverages two projections of the panorama at once, namely the equirectangular panorama-view and the perspective ceiling-view, that each contains different clues about the room layouts.

Christoph Saulder, Steffen Mieske, Eelco van Kampen, Werner W. Zeilinger

Context. Backreactions from large-scale inhomogeneities may provide an elegant explanation for the observed accelerated expansion of the universe without the need to introduce dark energy. Aims. We propose a cosmological test for a specific model of inhomogeneous cosmology, called timescape cosmology. Using large-scale galaxy surveys such as SDSS and 2MRS, w

Yaadhav Raaj, Haroon Idrees, Gines Hidalgo, Yaser Sheikh

We present an online approach to efficiently and simultaneously detect and track the 2D pose of multiple people in a video sequence. We build upon Part Affinity Field (PAF) representation designed for static images, and propose an architecture that can encode and predict Spatio-Temporal Affinity Fields (STAF) across a video sequence. In particular, we propos

Yi-Chen Zhang, Ziyang Chen, Christian Weedbrook, Song Yu

The continuous-variable quantum key distribution with entanglement in the middle, a semi-device-independent protocol, places the source at the untrusted third party between Alice and Bob, and thus has the advantage of high levels of security with the purpose of eliminating the assumptions about the source device. However, previous works considered the collec

Shujian Yu, Jose C. Principe

Feature selection aims to select the smallest feature subset that yields the minimum generalization error. In the rich literature in feature selection, information theory-based approaches seek a subset of features such that the mutual information between the selected features and the class labels is maximized. Despite the simplicity of this objective, there