March 2020 arXiv papers — page 92

Roberta Citro, Eugene Demler, Thierry Giamarchi, Michael Knap

Lattice modulation spectroscopy is a powerful tool for probing low-energy excitations of interacting many-body systems. By means of bosonization we analyze the absorbed power in a one dimensional interacting quantum gas of bosons or fermions, subjected to a periodic drive of the optical lattice. For these Tomonaga Luttinger liquids we find a universal $ω^3$

André Luiz Oliveira Bilobran, Alberto García-Cristóbal, Paulo Ventura dos Santos, Andrés Cantarero

We experimentally demonstrate the dynamical tuning of the acoustic field in a surface acoustic wave (SAW) cavity defined by a periodic arrangement of metal stripes on LiNbO3 substrate. Applying a DC voltage to the ends of the metal grid results in a temperature rise due to resistive heating that changes the frequency response of the device up to 0.3%, which

D. Turrini, A. Zinzi, J. A. Belinchon

Population studies of the orbital characteristics of exoplanets in multi-planet systems have highlighted the existence of an anticorrelation between the average orbital eccentricity of planets and the number of planets of their host system, that is, its multiplicity. This effect was proposed to reflect the varying levels of violence in the dynamical evolutio

Jorge González Cázares, Jevgenijs Ivanovs

We introduce two general non-parametric methods for recovering paths of the Brownian and jump components from high-frequency observations of a L\'evy process. The first procedure relies on reordering of independently sampled normal increments and thus avoids tuning parameters. The functionality of this method is a consequence of the small time predominance o

Pratik Nayak, Terry Cojean, Hartwig Anzt

With the commencement of the exascale computing era, we realize that the majority of the leadership supercomputers are heterogeneous and massively parallel even on a single node with multiple co-processors such as GPUs and multiple cores on each node. For example, ORNLs Summit accumulates six NVIDIA Tesla V100s and 42 core IBM Power9s on each node. Synchroni

Mahboube Mashhadi, Mohammad R. Garousi

It is known that the anomalous Chern-Simons (CS) coupling of O$_p$-plane is not consistent with the T-duality transformations. Compatibility of this coupling with the T-duality requires the inclusion of couplings involving one R-R field strength. In this paper we find such couplings at order $α'^2$. By requiring the R-R and NS-NS gauge invariances, we fi

Grzegorz Krzyżanowski, Marcin Magdziarz

Subdiffusion is a well established phenomenon in physics. In this paper we apply the subdiffusive dynamics to analyze financial markets. We focus on the financial aspect of time fractional diffusion model with moving boundary i.e. American and barrier option pricing in the subdiffusive Black-Scholes (B-S) model. Two computational methods for valuing American

Ali Devran Kara, Maxim Raginsky, Serdar Yuksel

We study continuity and robustness properties of infinite-horizon average expected cost problems with respect to (controlled) transition kernels, and applications of these results to the problem of robustness of control policies designed for approximate models applied to actual systems. We show that sufficient conditions presented in the literature for disco

Steffen Herbold, Alexander Trautsch, Fabian Trautsch

Context: Issue tracking systems are used to track and describe tasks in the development process, e.g., requested feature improvements or reported bugs. However, past research has shown that the reported issue types often do not match the description of the issue. Objective: We want to understand the overall maturity of the state of the art of issue type pred

Igor Mikolasek

Kaplan-Meier estimate, commonly known as product limit method (PLM), and maximum likelihood estimate (MLE) methods in general are often cited as means of stochastic highway capacity estimation. This article discusses their unsuitability for such application as properties of traffic flow do not meet the assumptions for use of the methods. They assume the obse

Mantas Zilinskas, Yamila Miguel, Paul Mollière, Shang-Min Tsai

We explore the chemistry and observability of nitrogen dominated atmospheres for ultra-short-period super-Earths. We base the assumption, that super-Earths could have nitrogen filled atmospheres, on observations of 55 Cnc e that favour a scenario with a high-mean-molecular-weight atmosphere. We take Titan's elemental budget as our starting point and usin

Taosha Fan, Todd Murphey

In this paper, we consider the problem of distributed pose graph optimization (PGO) that has extensive applications in multi-robot simultaneous localization and mapping (SLAM). We propose majorization minimization methods to distributed PGO and show that our proposed methods are guaranteed to converge to first-order critical points under mild conditions. Fur

Utsav Sadana, Puduru Viswanadha Reddy, Georges Zaccour

We consider a two-player linear-state differential game, where one player intervenes continuously in the game, while the other implements an impulse control. When the impulse instants are exogenous, we obtain the classical result in linear-state differential games that open-loop and feedback Nash equilibria coincide. When the impulse instants are endogenous,

Xiao Guo, Qiuhao Zhu, Liyan Zhou, Wei Yu

Kondo effect offers an important paradigm to understand strong correlated many-body physics. Although under intensive study, some of important properties of Kondo effect, in systems where both itinerant coupling and localized coupling play significant roles, are still elusive. Here we report evolution and universality of two stage Kondo effect, the simplest

F. F. Bruns, S. P. Vyatchanin, J. Dickmann, R. Glaser

Several sources of noise limit the sensitivity of current gravitational wave detectors. Currently, dominant noise sources include quantum noise and thermal Brownian noise, but future detectors will also be limited by other thermal noise channels. In this paper we study a thermal noise source which is caused by spatial charge carrier density variations in sem

Michael C. Birse

An approach is outline to constructing an optical potential that includes the effects of antisymmetry and target recoil. it is based on the retarded Green's function, which could make it a better starting point for applications to direct nuclear reactions, particularly when extended to coupled channels. Its form retains a simple connection to folding pot

Hans Rudolf Koslowski, Janina Schmitz, Christian Linsmeier

The dynamic behaviour of thermally driven segregation of Cr to the surface of WCrY smart alloy is studied with low energy ion scattering (LEIS). Sputtering the WCrY sample with 500 eV D$_2^+$ ions at room temperature results in preferential removal of the lighter alloy constituents and causes an almost pure W surface layer. At elevated temperatures above 700

Andronikos Paliathanasis

We perform a detailed analysis for the dynamics of Chiral cosmology in a spatially flat Friedmann-Lema\^{\i}tre-Robertson-Walker universe with a mixed potential term. The stationary points are categorized in four families. Previous results in the literature are recovered while new phases in the cosmological evolution are found. From our analysis we find nine

S. Wölk, P. Sekatski, W. Dür

We consider non-local sensing of scalar signals with specific spatial dependence in the Bayesian regime. We design schemes that allow one to achieve optimal scaling and are immune to noise sources with a different spatial dependence than the signal. This is achieved by using a sensor array of spatially separated sensors and constructing a multi-dimensional d

Junfa Liu, Juan Rojas, Zhijun Liang, Yihui Li

Spatio-temporal information is key to resolve occlusion and depth ambiguity in 3D pose estimation. Previous methods have focused on either temporal contexts or local-to-global architectures that embed fixed-length spatio-temporal information. To date, there have not been effective proposals to simultaneously and flexibly capture varying spatio-temporal seque

Vedran Brdar, Manfred Lindner, Stefan Vogl, Xun-Jie Xu

Given the elusive nature of neutrinos, their self-interaction is particularly difficult to probe. Nevertheless, upper limits on the strength of such an interaction can be set by using data from terrestrial experiments. In this work we focus on additional contributions to the invisible decay width of $Z$ boson as well as the leptonic $τ$ decay width in the pr

Semyon Yakubovich

A fractional power interpretation of the Laguerre derivative $(DxD)^α,\ D\equiv {d\over dx} $ is discussed. The corresponding fractional integrals are introduced. Mapping and semigroup properties, integral representations and Mellin transform analysis are presented. A relationship with the Riemann-Liouville fractional integrals is demonstrated. Finally, a se

Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang

Off-Policy Actor-Critic (Off-PAC) methods have proven successful in a variety of continuous control tasks. Normally, the critic's action-value function is updated using temporal-difference, and the critic in turn provides a loss for the actor that trains it to take actions with higher expected return. In this paper, we introduce a novel and flexible meta

Maximilian Pichler, Florian Hartig

1. Joint Species Distribution models (JSDMs) explain spatial variation in community composition by contributions of the environment, biotic associations, and possibly spatially structured residual covariance. They show great promise as a general analytical framework for community ecology and macroecology, but current JSDMs, even when approximated by latent v

James M. Hickey, Pietro G. Di Stefano, Vlasios Vasileiou

The ability to understand and trust the fairness of model predictions, particularly when considering the outcomes of unprivileged groups, is critical to the deployment and adoption of machine learning systems. SHAP values provide a unified framework for interpreting model predictions and feature attribution but do not address the problem of fairness directly

Song Bian, Tianchen Wang, Masayuki Hiromoto, Yiyu Shi

In this work, we propose ENSEI, a secure inference (SI) framework based on the frequency-domain secure convolution (FDSC) protocol for the efficient execution of privacy-preserving visual recognition. Our observation is that, under the combination of homomorphic encryption and secret sharing, homomorphic convolution can be obliviously carried out in the freq

Jack S. Baker, Tsuyoshi Miyazki, David R. Bowler

The perovskite oxides are known to be susceptible to structural distortions over a long wavelength when compared to their parent cubic structures. From an ab initio simulation perspective, this requires accurate calculations including many thousands of atoms; a task well beyond the remit of traditional plane wave-based density functional theory (DFT). We sug

Chuan-Qiang Chen, Li Chen, Ni Xiang

In this paper, we establish a priori estimates for a class of fully nonlinear equations with Neumann boundary conditions. By the continuity method, we have obtained the existence theorem for the Neumann problem.

YangGon Kim

We consider modular Lie algebras over algebraically closed field of characteristic $p \geq 7$. This paper purports to prove the conjecture that classical modular Lie algebras,in particular of $C_l$ and of $A_l$ type, should be a Park's Lie algebra, and so a Hypo- Lie algebra.

Kieran Greer

One of the most fundamental questions in Biology or Artificial Intelligence is how the human brain performs mathematical functions. How does a neural architecture that may organise itself mostly through statistics, know what to do? One possibility is to extract the problem to something more abstract. This becomes clear when thinking about how the brain handl

Daniel Sabsovich, Tobias Meng, Dmitry I. Pikulin, Raquel Queiroz

We study the effects of pseudo-magnetic fields on Weyl semimetals with over-tilted Weyl cones, or type II cones. We compare the phenomenology of the resulting pseudo-Landau levels in the type II Weyl semimetal to the known case of type I cones. We predict that due to the nature of the chiral Landau level resulting from a magnetic field, a pseudo-magnetic fie

Nguyen Van Minh, Hideaki Matsunaga, Nguyen Duc Huy, Vu Trong Luong

In this paper using a transform defined by the translation operator we introduce the concept of spectrum of sequences that are bounded by $n^ν$, where $ν$ is a natural number. We apply this spectral theory to study the asymptotic behavior of solutions of fractional difference equations of the form $Δ^αx(n)=Tx(n)+y(n)$, $n\in \mathbb{N}$, where $0<α\le 1$. On

Christoph Roch, Alexander Impertro, Thomy Phan, Thomas Gabor

Hybrid quantum-classical algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) are considered as one of the most encouraging approaches for taking advantage of near-term quantum computers in practical applications. Such algorithms are usually implemented in a variational form, combining a classical optimization method with a quantum machin

Brian Hopkins, Hua Wang

Agarwal introduced $n$-color compositions in 2000 and most subsequent research has focused on restricting which parts are allowed. Here we focus instead on restricting allowed colors. After three general results, giving recurrence formulas for the cases of given allowed colors, given prohibited colors, and colors satisfying modular conditions, we consider se

Sujoy Bhore, Jan-Henrik Haunert, Fabian Klute, Guangping Li

We study two new versions of independent and dominating set problems on vertex-colored interval graphs, namely $f$-Balanced Independent Set ($f$-BIS) and $f$-Balanced Dominating Set ($f$-BDS). Let $G=(V,E)$ be a vertex-colored interval graph with a color assignment function $\gamma \colon V \rightarrow \{1,\ldots,k\}$ that maps all vertices in $G$ onto $k$ c

Haixu Wang

The Hawkes process is a simple point process with wide applications in finance, social networks, criminology, seismology, and many other fields. The Hawkes process is defined for continuous-time setting. However, data is also recorded in a discrete-time scheme. In this paper, we study a discrete-time marked Hawkes process first proposed in (Xu et al., 2020),

Carsten Bauer

We assess numerical stabilization methods employed in fermion many-body quantum Monte Carlo simulations. In particular, we empirically compare various matrix decomposition and inversion schemes to gain control over numerical instabilities arising in the computation of equal-time and time-displaced Green&#39;s functions within the determinant quantum Monte Ca

Johannes Hosle, Alexander V. Kolesnikov, Galyna V. Livshyts

We study several of the recent conjectures in regards to the role of symmetry in the inequalities of Brunn-Minkowski type, such as the $L_p$-Brunn-Minkowski conjecture of Böröczky, Lutwak, Yang and Zhang, and the Dimensional Brunn-Minkowski conjecture of Gardner and Zvavitch, in a unified framework. We obtain several new results for these conjectures. We sho

Gabriele U. Varieschi

This paper introduces a possible alternative model of gravity based on the theory of fractional-dimension spaces and its applications to Newtonian gravity. In particular, Gauss&#39;s law for gravity as well as other fundamental classical laws are extended to a $D$-dimensional metric space, where $D$ can be a non-integer dimension. We show a possible connecti

Arnaud Guyader, Hugo Touchette

We present a complete framework for determining the asymptotic (or logarithmic) efficiency of estimators of large deviation probabilities and rate functions based on importance sampling. The framework relies on the idea that importance sampling in that context is fully characterized by the joint large deviations of two random variables: the observable defini

Ashwin Sah, Mehtaab Sawhney, Jonathan Tidor, Yufei Zhao

Bollob\'as and Riordan, in their paper "Metrics for sparse graphs," proposed a number of provocative conjectures extending central results of quasirandom graphs and graph limits to sparse graphs. We refute these conjectures by exhibiting a sequence of graphs with convergent normalized subgraph densities (and pseudorandom $C_4$-counts), but with no limit expr

Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak

We propose a simple interpolation-based method for the efficient approximation of gradients in neural ODE models. We compare it with the reverse dynamic method (known in the literature as &#34;adjoint method&#34;) to train neural ODEs on classification, density estimation, and inference approximation tasks. We also propose a theoretical justification of our

Alan D. Logan

The equaliser of a set of homomorphisms $S: F(a, b)\rightarrow F(\Delta)$ has rank at most two if $S$ contains an injective map, and is not finitely generated otherwise. This proves a strong form of Stallings' Equaliser Conjecture for the free group of rank two. Results are also obtained for pairs of homomorphisms $g, h:F(\Sigma)\rightarrow F(\Delta)$ when t

Leiv Andresen, Adrian Brandemuehl, Alex Hönger, Benson Kuan

This paper presents the perception, mapping, and planning pipeline implemented on an autonomous race car. It was developed by the 2019 AMZ driverless team for the Formula Student Germany (FSG) 2019 driverless competition, where it won 1st place overall. The presented solution combines early fusion of camera and LiDAR data, a layered mapping approach, and a p

D. S. Fernández, Á. G. López, J. M. Seoane, M. A. F. Sanjuán

We use the Hénon-Heiles system as a paradigmatic model for chaotic scattering to study the Lorentz factor effects on its transient chaotic dynamics. In particular, we focus on how time dilation occurs within the scattering region by measuring the time in a clock attached to the particle. We observe that the several events of time dilation that the particle u

Florian-Horia Vasilescu

We present an approach to the spectrum and analytic functional calculus for quaternionic linear operators, following the corresponding results concerning the real linear operators. In fact, the construction of the analytic functional calculus for real linear operators can be refined to get a similar construction for quaternionic linear ones, in a classical m

Ivan Debono, Dhiraj Kumar Hazra, Arman Shafieloo, George F. Smoot

With Planck cosmic microwave background observations, we established the spectral amplitude and tilt of the primordial power spectrum. Evidence of a red spectral tilt ($n_\mathrm{s}=0.96$) at $8σ$ provides strong support for the inflationary mechanism, especially the slow-roll of the effective scalar field in its nearly flat potential as the generator of sca

Jingjing Cai, Wei Liu, Ru Zong, Yangyang Dong

Sparse arrays have attracted a lot of interests recently for their capability of providing more degrees of freedom than traditional uniform linear arrays. For a mixture of circular and noncircular signals, most of the existing direction of arrival (DOA) estimation methods are based on various uniform arrays. Recently, a class of DOA estimation algorithms bas

Manolis Peponakis, Anna Mastora, Sarantos Kapidakis, Martin Doerr

This study considers the expressiveness (that is the expressive power or expressivity) of different types of Knowledge Organization Systems (KOS) and discusses its potential to be machine-processable in the context of the Semantic Web. For this purpose, the theoretical foundations of KOS are reviewed based on conceptualizations introduced by the Functional R

Sebastian Wallkotter, Silvia Tulli, Ginevra Castellano, Ana Paiva

The issue of how to make embodied agents explainable has experienced a surge of interest over the last three years, and, there are many terms that refer to this concept, e.g., transparency or legibility. One reason for this high variance in terminology is the unique array of social cues that embodied agents can access in contrast to that accessed by non-embo

Damien Tourret, Laszlo Sturz, Alexandre Viardin, Miha Založnik

We present a quantitative benchmark of multiscale models for dendritic growth simulations. We focus on approaches based on phase-field, dendritic needle network, and grain envelope dynamics. As a first step, we focus on isothermal growth of an equiaxed grain in a supersaturated liquid in three dimensions. A quantitative phase-field formulation for solidifica

Thomas Isensee, Damien Tourret

We present a first implementation of the Dendritic Needle Network (DNN) model for dendritic crystal growth in three dimensions including convective transport in the melt. The numerical solving of the Navier-Stokes equations is performed with finite differences and is validated by comparison with a classical benchmark in fluid mechanics for unsteady flow. We

Dongho Chae

In this paper we prove Liouville type theorem for the stationary Navier-Stokes equations in $\Bbb R^3$ under the assumptions on the relative decays of velocity, pressure and the head pressure. More precisely, we show that any smooth solution $(u,p)$ of the stationary Navier-Stokes equations satisfying $u(x) \to 0$ as $|x|\to +\infty$ and the condition of fin

Alessio Savini

Consider $n \geq 2$. In this paper we prove that the group $\text{PU}(n,1)$ is $1$-taut. This result concludes the study of $1$-tautness of rank-one Lie groups of non-compact type. Additionally the tautness property implies a classification of finitely generated groups which are $\text{L}^1$-measure equivalent to lattices of $\text{PU}(n,1)$. More precisely,

Minoru Hirose

In this paper, we investigate linear relations among regularized motivic iterated integrals on $\mathbb{P}^{1}\setminus\{0,1,\infty\}$ of depth two, which we call regularized motivic double zeta values. Some mysterious connections between motivic multiple zeta values and modular forms are known, e.g. Gangl--Kaneko--Zagier relation for the totally odd double

Ross J. Kang, Tom Kelly

Motivated both by recently introduced forms of list colouring and by earlier work on independent transversals subject to a local sparsity condition, we use the semi-random method to prove the following result. For any function $\mu$ satisfying $\mu(d)=o(d)$ as $d\to\infty$, there is a function $\lambda$ satisfying $\lambda(d)=d+o(d)$ as $d\to\infty$ such tha

Yang Huang, Yongtao Li, Lihua Feng, Weijun Liu

We present inequalities related to generalized matrix function for positive semidefinite block matrices. We introduce partial generalized matrix functions corresponding to partial traces, and then provide a unified extension of the recent inequalities due to Lin [Electron. J. Linear Algebra 27 (2014) 821-826], Zhang et al. [Linear Algebra Appl. 498 (2016) 99

Swaine L. Chen, Nico M. Temme

Stirling numbers of the first kind are used in the derivation of several population genetics statistics, which in turn are useful for testing evolutionary hypotheses directly from DNA sequences. Here, we explore the cumulative distribution function of these Stirling numbers, which enables a single direct estimate of the sum, using representations in terms of

David Bechara Senior

Given a compactly supported area-preserving diffeomorphism of the disk, we prove an integral formula relating the asymptotic action to the asymptotic winding number. As a corollary, we obtain a new proof of Fathi&#39;s integral formula for the Calabi homomorphism on the disk.

Majid Farzaneh, Rahil Mahdian Toroghi

Graph-based Transform (GT) has been recently leveraged successfully in the signal processing domain, specifically for compression purposes. In this paper, we employ the GBT, as well as the Singular Value Decomposition (SVD) with the goal to improve the robustness of audio watermarking against different attacks on the audio signals, such as noise and compress

Yoichi Sato, Yasuhiko Takegami, Takamune Asamoto, Yutaro Ono

[Objective] To develop a Computer-aided diagnosis (CAD) system for plane frontal hip X-rays with a deep learning model trained on a large dataset collected at multiple centers. [Materials and Methods]. We included 5295 cases with neck fracture or trochanteric fracture who were diagnosed and treated by orthopedic surgeons using plane X-rays or computed tomogr

Savi Virolainen

We introduce a new mixture autoregressive model which combines Gaussian and Student's $t$ mixture components. The model has very attractive properties analogous to the Gaussian and Student's $t$ mixture autoregressive models, but it is more flexible as it enables to model series which consist of both conditionally homoscedastic Gaussian regimes and condition

Matheus C. Teodoro, Lucas G. Collodel, Jutta Kunz

We report simulations regarding tidal disruption clouds orbiting spherically symmetric compact boson stars in two different regimes. First we consider clouds in three different bound orbits close to the boson star and analyze the mechanisms of debris formation for these. We infer from the simulations that the lifetimes of these hot-spots are longer for circu

Tomasz Beberok, Piotr Budzynski, Dong-O Kang

We provide a sufficient condition for the compactness of a Toeplitz operator acting on the Segal-Bargmann space of vector-valued functions written in terms of an associated operator-valued kernel.

Atreyee Kundu

This paper deals with stabilization of discrete-time switched linear systems when explicit knowledge of the state-space models of their subsystems is not available. Given the set of admissible switches between the subsystems, the admissible dwell times on the subsystems and a set of finite traces of state trajectories of the subsystems that satisfies certain

Haim Brezis, Jean Van Schaftingen, Po-Lam Yung

We establish the equivalence between the Sobolev semi-norm $\|\nabla u\|_{L^p}$ and a quantity obtained when replacing the strong $L^p$ by a weak $L^p$ norm in the Gagliardo semi-norm $|u|_{W^{s,p}}$ computed at $s = 1$. As corollaries we derive alternative estimates in some exceptional cases (involving $W^{1,1}$) where the "anticipated" fractional Sobolev a

Vinesh Vijayan, Biplab Ganguli

We have investigated synchronized pattern in a network of Thomas oscillators coupled with sinusoidal nonlinear coupling. Pattern like chimera states are not only observed for many non-locally coupled oscillators but there is a signature of it even for locally coupled few oscillators. For certain range of intermediate coupling, clusters are also observed. The

Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Duc Hoang

We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to digital circuits with FPGA firmware. Starting from benchmark models trained with floating point precision, we investigate different strategies to reduce the network&#39;s resource consumption by reducing t

Jelle Don, Serge Fehr, Christian Majenz

We revisit recent works by Don, Fehr, Majenz and Schaffner and by Liu and Zhandry on the security of the Fiat-Shamir transformation of $\Sigma$-protocols in the quantum random oracle model (QROM). Two natural questions that arise in this context are: (1) whether the results extend to the Fiat-Shamir transformation of multi-round interactive proofs, and (2) w

Ferdinand Jost, Pascal Peter, Joachim Weickert

Compressing piecewise smooth images is important for many data types such as depth maps in 3D videos or optic flow fields for motion compensation. Specialised codecs that rely on explicitly stored segmentations excel in this task since they preserve discontinuities between smooth regions. However, current approaches rely on ad hoc segmentations that lack a c

Xander Faber, Clayton Petsche

Let $\mathbb{F}_q(T)$ be the field of rational functions in one variable over a finite field. We introduce the notion of a totally $T$-adic function: one that is algebraic over $\mathbb{F}_q(T)$ and whose minimal polynomial splits completely over the completion $\mathbb{F}_q(\!(T)\!)$. We give two proofs that the height of a nonconstant totally $T$-adic func

Hiroki Ohata, Hideo Suganuma

We present the first study of the Abelian-projected gluonic-excitation energies for the static quark-antiquark (Q$\bar{\rm Q}$) system in SU(3) lattice QCD at the quenched level, using a $32^4$ lattice at $β= 6.0$. We investigate ground-state and three excited-state Q$\bar{\rm Q}$ potentials, using smeared link variables on the lattice. We find universal Abe

R. S. Akzyanov, D. A. Khokhlov, A. L. Rakhmanov

We study superconducting properties of the bulk states of a doped topological insulator. We obtain that the hexagonal warping stabilizes the nematic spin-triplet superconducting phase with $E_u$ pairing and the direction of the nematic order parameter which opens the full gap is the ground state. This order parameter exhibits non-BCS behavior. The ratio of t

Longfei Zheng, Chaochao Chen, Yingting Liu, Bingzhe Wu

Deep Neural Network (DNN) has been showing great potential in kinds of real-world applications such as fraud detection and distress prediction. Meanwhile, data isolation has become a serious problem currently, i.e., different parties cannot share data with each other. To solve this issue, most research leverages cryptographic techniques to train secure DNN m

D. A. Bignamini, S. Ferrari

Let $\mathcal{X}$ be a separable Hilbert space with norm $\|\cdot\|$ and let $T>0$. Let $Q$ be a linear, self-adjoint, positive, trace class operator on $\mathcal{X}$, let $F:\mathcal{X}\rightarrow \mathcal{X}$ be a (smooth enough) function and let $W(t)$ be a $\mathcal{X}$-valued cylindrical Wiener process. For $\alpha\in [0,1/2]$ we consider the operator $

Sihua Liang, Dušan D. Repovš, Binlin Zhang

In this paper we are concerned with the existence and multiplicity of solutions for the fractional Choquard-type Schrödinger-Kirchhoff equations with electromagnetic fields and critical nonlinearity: \begin{eqnarray*} \begin{cases} \varepsilon^{2s}M([u]_{s,A}^2)(-Δ)_{A}^su + V(x)u = (|x|^{-α}*F(|u|^2))f(|u|^2)u + |u|^{2_s^\ast-2}u,\ \ \ x\in \mathbb{R}^N,\\

Ignacio Ojeda, José Carlos Rosales

In this paper we introduce the notion of extension of a numerical semigroup. We provide a characterization of the numerical semigroups whose extensions are all arithmetic and we give an algorithm for the computation of the whole set of arithmetic extension of a given numerical semigroup. As by-product, new explicit formulas for the Frobenius number and the g

Philipp Hönicke, Ulrich Waldschläger, Thomas Wiesner, Markus Krämer

Grazing-Incidence X-ray fluorescence (GIXRF) analysis, which is closely related to total-reflection XRF, is a very powerful technique for the in-depth analysis of many types of technologically relevant samples, e.g. nanoparticle depositions, shallow dopant profiles, thin layered samples or even well-ordered nanostructures. However, the GIXRF based determinat

Daniel Lundén, Johannes Borgström, David Broman

Probabilistic programming is an approach to reasoning under uncertainty by encoding inference problems as programs. In order to solve these inference problems, probabilistic programming languages (PPLs) employ different inference algorithms, such as sequential Monte Carlo (SMC), Markov chain Monte Carlo (MCMC), or variational methods. Existing research on su

Dexiong Chen, Laurent Jacob, Julien Mairal

We introduce a family of multilayer graph kernels and establish new links between graph convolutional neural networks and kernel methods. Our approach generalizes convolutional kernel networks to graph-structured data, by representing graphs as a sequence of kernel feature maps, where each node carries information about local graph substructures. On the one

Jingcao Wu

We study the $\bar{\partial}$-Laplacian on forms taking values in $L^{k}$, a high power of a nef line bundle on a compact complex manifold, and give an estimate of the number of the eigenforms whose corresponding eigenvalues smaller than or equal to $λ$. In particular, the $λ=0$ case gives an asymptotic estimate for the order of the corresponding cohomology

Raul Epure, Delphine Pol

The purpose of this paper is to give new examples of families of free singularities. We first show that a generic equidimensional subspace arrangement is free. Furthermore, we show that a product of two reduced Cohen-Macaulay subspaces is free if and only if both subspaces are free.

Raditya Weda Bomantara

Higher-order topological materials with topologically protected states at the boundaries of their boundaries (hinges or corners) have attracted attention in recent years. In this paper, we utilize time-periodic driving to generate second-order topological superconductors out of systems which otherwise do not even allow second-order topological characterizati

Lin Jia, Kewen Li, Yu Jiang, Xin Guo

In December 2019, a novel coronavirus was found in a seafood wholesale market in Wuhan, China. WHO officially named this coronavirus as COVID-19. Since the first patient was hospitalized on December 12, 2019, China has reported a total of 78,824 confirmed CONID-19 cases and 2,788 deaths as of February 28, 2020. Wuhan&#39;s cumulative confirmed cases and deat

Paul-Marie Samson

Lott-Sturm-Villani theory of curvature on geodesic spaces has been extended to discrete graph spaces by C. L{\'e}onard by replacing W2-Wasserstein geodesics by Schr{\"o}odinger bridges in the definition of entropic curvature [23, 25, 24]. As a remarkable fact, as a temperature parameter goes to zero, these Schr{\"o}dinger bridges are supported by geodesics o

Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li

Object recognition techniques using convolutional neural networks (CNN) have achieved great success. However, state-of-the-art object detection methods still perform poorly on large vocabulary and long-tailed datasets, e.g. LVIS. In this work, we analyze this problem from a novel perspective: each positive sample of one category can be seen as a negative sam

Peter beim Graben, Markus Huber, Werner Meyer, Ronald Römer

Background / introduction. Vector symbolic architectures (VSA) are a viable approach for the hyperdimensional representation of symbolic data, such as documents, syntactic structures, or semantic frames. Methods. We present a rigorous mathematical framework for the representation of phrase structure trees and parse trees of context-free grammars (CFG) in Foc

Orr Shalit, Michael Skeide

These notes are the output of a decade of research on how the results about dilations of one-parameter CP-semigroups with the help of product systems, can be put forward to d-parameter semigroups - and beyond. While exisiting work on the two- and d-parameter case is based on the approach via the Arveson-Stinespring correspondence of a CP-map by Muhly and Sol

Genshun Dong, Yan Yan, Chunhua Shen, Hanzi Wang

Deep Convolutional Neural Networks (DCNNs) have recently shown outstanding performance in semantic image segmentation. However, state-of-the-art DCNN-based semantic segmentation methods usually suffer from high computational complexity due to the use of complex network architectures. This greatly limits their applications in the real-world scenarios that req

Naeem Paeedeh, Kamaledin Ghiasi-Shirazi

Many attempts took place to improve the adaptive filters that can also be useful to improve backpropagation (BP). Normalized least mean squares (NLMS) is one of the most successful algorithms derived from Least mean squares (LMS). However, its extension to multi-layer neural networks has not happened before. Here, we first show that it is possible to conside

Antonio L. R. Manesco, Jose L. Lado, Eduardo V. S. Ribeiro, Gabrielle Weber

Electronic correlations stemming from nearly flat bands in van der Waals materials have demonstrated to be a powerful playground to engineer artificial quantum matter, including superconductors, correlated insulators and topological matter. This phenomenology has been experimentally observed in a variety of twisted van der Waals materials, such as graphene a

Zhiyuan Fang, Tejas Gokhale, Pratyay Banerjee, Chitta Baral

Captioning is a crucial and challenging task for video understanding. In videos that involve active agents such as humans, the agent's actions can bring about myriad changes in the scene. Observable changes such as movements, manipulations, and transformations of the objects in the scene, are reflected in conventional video captioning. Unlike images, actions

Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt

Humans easily interpret expressions that describe unfamiliar situations composed from familiar parts (&#34;greet the pink brontosaurus by the ferris wheel&#34;). Modern neural networks, by contrast, struggle to interpret novel compositions. In this paper, we introduce a new benchmark, gSCAN, for evaluating compositional generalization in situated language un

Barnaby R. M. Norris, Jin Wei, Christopher H. Betters, Alison Wong

Adaptive optics (AO) is critical in astronomy, optical communications and remote sensing to deal with the rapid blurring caused by the Earth&#39;s turbulent atmosphere. But current AO systems are limited by their wavefront sensors, which need to be in an optical plane non-common to the science image and are insensitive to certain wavefront-error modes. Here

A. Jerkstrand, A. Wongwathanarat, H. -T. Janka, M. Gabler

Comparison of theoretical line profiles to observations provides important tests for supernova explosion models. We study the shapes of radioactive decay lines predicted by current 3D core-collapse explosion simulations, and compare these to observations of SN 1987A and Cas A. Both the widths and shifts of decay lines vary by several thousand kilometers per

Stefan Studer, Thanh Binh Bui, Christian Drescher, Alexander Hanuschkin

Machine learning is an established and frequently used technique in industry and academia but a standard process model to improve success and efficiency of machine learning applications is still missing. Project organizations and machine learning practitioners have a need for guidance throughout the life cycle of a machine learning application to meet busine

Chengrong Deng, Hong Chen, Jialun Ping

We use a color-magnetic interaction model (CMIM), a traditional constituent quark model (CQM) and a multiquark color flux-tube model (MCFTM) to systematically investigate the properties of the states $[Q_1Q_2][\bar{Q}_3\bar{Q}_4]$ ($Q=c,b$). The dynamical investigation indicates that the CMIM can not completely absorb QCD dynamical effects through the effect

Nobutaka Ito, Simon Godsill

This paper proposes a novel particle filter for tracking time-varying states of multiple targets jointly from superpositional data, which depend on the sum of contributions of all targets. Many conventional tracking methods rely on preprocessing for detection (e.g., thresholding), which severely limits tracking performance at a low signal-to-noise ratio (SNR

P. Giommi, Y. L. Chang, S. Turriziani, T. Glauch

We have analysed all the X-ray images centred on Gamma Ray Bursts generated by Swift over the last 15 years using automatic tools that do not require any expertise in X-ray astronomy, producing results in excellent agreement with previous findings. This work, besides presenting the largest medium-deep survey of the X-ray sky and a complete sample of blazars,

Jukka Ruohonen, Kalle Hjerppe

The General Data Protection Regulation (GDPR) was enforced in 2018. After this enforcement, many fines have already been imposed by national data protection authorities in the European Union (EU). This paper examines the individual GDPR articles referenced in the enforcement decisions, as well as predicts the amount of enforcement fines with available meta-d