December 2020 arXiv papers — page 48

Anneleen De Schepper, Jeroen Schillewaert, Hendrik Van Maldeghem, Magali Victoor

Parapolar spaces are point-line geometries introduced as a geometric approach to (exceptional) algebraic groups. We characterize a wide class of Lie geometries as parapolar spaces satisfying a simple intersection property. In particular many of the exceptional Lie incidence geometries occur. {In an appendix, we extend our result to the locally disconnected c

Silvia Bertoluzza, Ilaria Perugia, Daniele Prada

We introduce a new stabilization for discontinuous Galerkin methods for the Poisson problem on polygonal meshes, which induces optimal convergence rates in the polynomial approximation degree $p$. In the setting of [S. Bertoluzza and D. Prada, A polygonal discontinuous Galerkin method with minus one stabilization, ESAIM Math. Mod. Numer. Anal. (DOI: 10.1051/

Michael Tsamparlis, Antonios Mitsopoulos

A theorem is proved which determines the first integrals of the form $I=K_{ab}(t,q)\dot{q}^{a}\dot{q}^{b}+K_{a}(t,q)\dot{q}^{a}+K(t,q)$ of autonomous holonomic systems using only the collineations of the kinetic metric which is defined by the kinetic energy or the Lagrangian of the system. It is shown how these first integrals can be associated via the inver

Suting Zhao, Christian Northe, René Meyer

We consider symmetry-resolved entanglement entropy in AdS${}_3$/CFT${}_2$ coupled to $U(1)$ Chern-Simons theory. We identify the holographic dual of the charged moments in the two-dimensional conformal field theory as a charged Wilson line in the bulk of AdS${}_3$, namely the Ryu-Takayanagi geodesic minimally coupled to the $U(1)$ Chern-Simons gauge field. W

Qi Wang

In this paper, we investigate the effect of dispersal and advection on the dynamics of a predator-prey model. More precisely, we show that the linear stability of the semi-trivial steady state is determined by the dispersal rate, the mortality rate of the predator and the advection rate. We point out that compared to homogeneous intrinsic growth rate and car

Fabrizio Catanese, Wenfei Liu

In this paper, we investigate automorphisms of compact K\"ahler manifolds with different levels of topological triviality. In particular, we provide several examples of smooth complex projective surfaces X whose groups of $C^\infty$-isotopically trivial automorphisms, resp. cohomologically trivial automorphisms, have a number of connected components which ca

Benjamin Sorkin, Haim Diamant

We study the Brownian motion of an assembly of mobile inclusions embedded in a fluid membrane. The motion includes the dispersal of the assembly, accompanied by the diffusion of its center of mass. Usually, the former process is much faster than the latter, since the diffusion coefficient of the center of mass is inversely proportional to the number of parti

Ronaldo Garcia, Dan Reznik

We compare loci types and invariants across Poncelet families interscribed in three distinct concentric Ellipse pairs: (i) ellipse-incircle, (ii) circumcircle-inellipse, and (iii) homothetic. Their metric properties are mostly identical to those of 3 well-studied families: elliptic billiard (confocal pair), Chapple's poristic triangles, and the Brocard poris

Piotr Ostropolski-Nalewaja, Jerzy Marcinkowski, David Carral, Sebastian Rudolph

This paper is about (first order) query rewritability in the context of theory-mediated query answering. The starting point of our journey is the FUS/FES conjecture, saying that if a theory is core-terminating (FES) and admits query rewriting (BDD, FUS) then it is uniformly bounded. We show that this conjecture is true for a wide class of "local" BDD theorie

Michele Guerrini, Enrique Delgado Aznar, Caterina Cocchi

The peculiar electronic and optical properties of covalent organic frameworks (COFs) are largely determined by protonation, a ubiquitous phenomenon in the solution environment in which they are synthesized. The resulting effects are non-trivial and appear to be crucial for the intriguing functionalities of these materials. In the quantum-mechanical framework

Antonino Drago

A new mathematics, the constructive one, characterizes a singular limit as undecidable. Hence, a singular limit between two theories actually represents a difference between two different kinds of mathematics. This particular situation suggests a mathematical definition of the notion of incommensurability. As a consequence of the resulting incommensurabiliti

Jenny List

Beam polarisation is an integral part of the physics case of future Linear Colliders. In this contribution, important examples from Higgs coupling measurements, top and electroweak physics at high energies, the Z pole program as well as from searches for production of new particles will be reviewed. The full exploitation of its advantages requires the polari

Satyadev Nandakumar, Subin Pulari

We initiate the study of effective pointwise ergodic theorems in resource-bounded settings. Classically, the convergence of the ergodic averages for integrable functions can be arbitrarily slow. In contrast, we show that for a class of PSPACE L1 functions, and a class of PSPACE computable measure-preserving ergodic transformations, the ergodic average exists

M. Hidalgo-Soria, E. Barkai, S. Burov

We study a two state ``jumping diffusivity'' model for a Brownian process alternating between two different diffusion constants, $D_{+}>D_{-}$, with random waiting times in both states whose distribution is rather general. In the limit of long measurement times Gaussian behavior with an effective diffusion coefficient is recovered. We show that for equilibri

Jakub Káninský

The classical spacetime is usually described by a differentiable manifold with infinitely many degrees of freedom. Occasionally though, it is useful to consider an approximation whose number of degrees of freedom is finite. There are several discrete models of spacetime like that, some of which have been used to build a (simplified) representation of a black

Mustafa Zhuhair Gheni Yousif, HeeChang Lim

The turbulent flow past a wall-mounted square cylinder with an aspect ratio of four was investigated with the aid of Spalart-Allmaras improved delayed detached-eddy simulation (S-A IDDES) and proper orthogonal decomposition (POD). The Reynolds number was equal to 12,000 (based on the free-stream velocity and obstacle width). This study focused on analysing t

Anas Elbaz, Riazul Arefin, Emilie Sakat, Binbin Wang

GeSn alloys are nowadays considered as the most promising materials to build Group IV laser sources on silicon (Si) in a full complementary metal oxide semiconductor-compatible approach. Recent GeSn laser developments rely on increasing the band structure directness, by increasing the Sn content in thick GeSn layers grown on germanium (Ge) virtual substrates

Tongxin Li, Bo Sun, Yue Chen, Zixin Ye

Aggregators have emerged as crucial tools for the coordination of distributed, controllable loads. To be used effectively, an aggregator must be able to communicate the available flexibility of the loads they control, as known as the aggregate flexibility to a system operator. However, most of existing aggregate flexibility measures often are slow-timescale

Mengshi Qi, Edoardo Remelli, Mathieu Salzmann, Pascal Fua

Deep learning-solutions for hand-object 3D pose and shape estimation are now very effective when an annotated dataset is available to train them to handle the scenarios and lighting conditions they will encounter at test time. Unfortunately, this is not always the case, and one often has to resort to training them on synthetic data, which does not guarantee

Bing Huang, Lin Zhuang

Understanding how electronic structure determines the reactivity of solid surface, is a central topic of modern surface science. This is mostly commonly done through some intermediate quantity termed descriptor. However, such descriptors are very scarce for solid surface compared to for molecule, likely due to their significantly more complex electronic stru

Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani

Policy gradient methods have become one of the most popular classes of algorithms for multi-agent reinforcement learning. A key challenge, however, that is not addressed by many of these methods is multi-agent credit assignment: assessing an agent's contribution to the overall performance, which is crucial for learning good policies. We propose a novel algor

M. Wais, J. Kaufmann, M. Battiato, K. Held

We compute scattering rates for electrons in the two-dimensional Hubbard model for a one-orbital metal and a two-orbital band insulator by means of the Boltzmann scattering equation (BSE) and dynamical mean-field theory (DMFT). As an intermediate method between both, we also consider the BSE without momentum conservation. In the weak interaction regime and f

James Wright

In this paper we develop a theory for oscillatory integrals with complex phases. When $f:{\mathbb C}^n \to {\mathbb C}$, we evaluate this phase function on the basic character ${\rm e}(z) := e^{2\pi i x} e^{2\pi i y}$ of ${\mathbb C} \simeq {\mathbb R}^2$ (here $z = x+iy \in {\mathbb C}$ or $z = (x,y) \in {\mathbb R}^2$) and consider oscillatory integrals of

Enrico M. Brehm, Matteo Broccoli

We discuss a computer implementation of a recursive formula to calculate correlation functions of descendant states in two-dimensional CFT. This allows us to obtain any $N$-point function of vacuum descendants, or to express the correlator as a differential operator acting on the respective primary correlator in case of non-vacuum descendants. With this tool

Urko Petralanda, Mads Kruse, Hugh Simons, Thomas Olsen

We study the influence of oxygen vacancies on the formation of charged 180$^\circ$ domain walls in ferroelectric BaTiO$_3$ using first principles calculations. We show that it is favorable for vacancies to assemble in crystallographic planes, and that such clustering is accompanied by the formation of a charged domain wall. The domain wall has negative bound

Mingyuan Jiu, Hichem Sahbi

Context modeling is one of the most fertile subfields of visual recognition which aims at designing discriminant image representations while incorporating their intrinsic and extrinsic relationships. However, the potential of context modeling is currently underexplored and most of the existing solutions are either context-free or restricted to simple handcra

Yuxia Liang, Jonathan R. Partington

Let $\{T(t)\}_{t\geq0}$ be a $C_0$-semigroup on an infinite dimensional separable Hilbert space; a suitable definition of near $\{T(t)^*\}_{t\geq0}$ invariance of a subspace is presented in this paper. A series of prototypical examples for minimal nearly $\{S(t)^*\}_{t\geq0}$ invariant subspaces for the shift semigroup $\{S(t)\}_{t\geq0}$ on $L^2(0,\infty)$

Yu Liu, Yu Yu, Baojiu Li

Plenty of crucial information about our Universe is encoded in the cosmic large-scale structure (LSS). However, the extractions of these information are usually hindered by the nonlinearities of the LSS, which can be largely alleviated by various techniques known as the reconstruction. In realistic applications, the efficiencies of these methods are always d

Marzieh Bahmani, Daniel Kikoła, Leszek Kosarzewski

We present a method for the measurement of parameters of elastic and inelastic interactions of charmonium with hadrons. In this technique, we use femtoscopic analysis of charmonium-hadron correlations at low relative momentum and the Lednicky-Lyuboshitz analytical model to extract the interaction parameters. We argue that such a study is already feasible in

Mainak Ghosh, Amalendu Krishna

We prove an extension of the Kato-Saito class field theory for smooth projective schemes over a finite field to schemes with singularities. As an application, we obtain Bloch's formula for the Chow groups of 0-cycles on such schemes. We identify the Chow group of 0-cycles on a normal projective scheme over an algebraically closed field to the Suslin homology

Semonti Bhattacharyya, Golrokh Akhgar, Matt Gebert, Julie Karel

Inducing long-range magnetic order in three-dimensional topological insulators can gap the Diraclike metallic surface states, leading to exotic new phases such as the quantum anomalous Hall effect or the axion insulator state. These magnetic topological phases can host robust, dissipationless charge and spin currents or unique magnetoelectric behavior, which

Lin Sok

We define the Euclidean hull of a linear code $C$ as the intersection of $C$ and its Euclidean dual $C^\perp$. The hull with low dimensions gets much interest due to its crucial role in determining the complexity of algorithms for computing the automorphism group of a linear code and checking permutation equivalence of two linear codes. It has been recently

Sveinung Erland, Jevgenijs Kaupužs, Albert Steiner, Eitan Bachmat

Airlines use different boarding policies to organize the queue of passengers waiting to enter the airplane. We analyze three policies in the many-passenger limit by a geometric representation of the queue position and row designation of each passenger and apply a Lorentzian metric to calculate the total boarding time. The boarding time is governed by the tim

Mohannad Aldughaim, Kaled Alshmrany, Rafael Menezes, Lucas Cordeiro

Bounded model checking (BMC) is vital for finding program property violations. For unsafe programs, BMC can quickly find an execution path from an initial state to the violated state that refutes a given safety property. However, BMC techniques struggle to falsify programs that contain loops. BMC needs to incrementally unfold the program loops up to the boun

R. Klas, A. Kirsche, M. Gebhardt, J. Buldt

High harmonic generation (HHG) enables coherent extreme-ultraviolet (XUV) radiation with ultra-short pulse duration in a table-top setup. This has already enabled a plethora of applications. Nearly all of these applications would benefit from a high photon flux to increase the signal-to-noise ratio and decrease measurement times. In addition, shortest pulses

Yaman Kumar, Swati Aggarwal, Debanjan Mahata, Rajiv Ratn Shah

In the era of MOOCs, online exams are taken by millions of candidates, where scoring short answers is an integral part. It becomes intractable to evaluate them by human graders. Thus, a generic automated system capable of grading these responses should be designed and deployed. In this paper, we present a fast, scalable, and accurate approach towards automat

Yuto Takaki, Kosuke Mitarai, Makoto Negoro, Keisuke Fujii

We propose a method for learning temporal data using a parametrized quantum circuit. We use the circuit that has a similar structure as the recurrent neural network which is one of the standard approaches employed for this type of machine learning task. Some of the qubits in the circuit are utilized for memorizing past data, while others are measured and ini

Maxime El-Masri, Jérôme Morio, Florian Simatos

Rare event probability estimation is an important topic in reliability analysis. Stochastic methods, such as importance sampling, have been developed to estimate such probabilities but they often fail in high dimension. In this paper, we propose a new cross-entropy-based importance sampling algorithm to improve rare event probability estimation in high dimen

Tiziana Cattai, Gaetano Scarano, Marie-Constance Corsi, Danielle S. Bassett

Functional connectivity (FC) can be represented as a network, and is frequently used to better understand the neural underpinnings of complex tasks such as motor imagery (MI) detection in brain-computer interfaces (BCIs). However, errors in the estimation of connectivity can affect the detection performances. In this work, we address the problem of denoising

D Bhanu Prakash, Bishal Chhetri, D K K Vamsi, Balasubramanian S

The dynamics of COVID-19 in India are captured using a set of delay differential equations by dividing a constant population into six compartments. The equilibrium points are calculated and stability analysis is performed. Sensitivity analysis is performed on the parameters of the model. Bifurcation analysis is performed and the critical delay is calculated.

Subhadeep Roy, Soumyajyoti Biswas

We study the local load sharing fiber bundle model and its energy burst statistics. While it is known that the avalanche size distribution of the model is exponential, we numerically show here that the avalanche size ($s$) and the corresponding energy burst ($E$) in this version of the model have a non-linear relation ($E\sim s^{\gamma}$). Numerical results

Nils Roth, Daniel A. Horke, Jannik Lübke, Amit K. Samanta

An aerodynamic lens injector was developed specifically for the needs of single-particle diffractive imaging experiments at free-electron lasers. Its design allows for quick changes of injector geometries and focusing properties in order to optimize injection for specific individual samples. Here, we present results of its first use at the FLASH free-electro

Jan Kiethe, Lars Timm, Haggai Landa, Dimitri Kalincev

We investigate the normal mode spectrum of a trapped ion chain at the symmetry-breaking linear to zigzag transition and at finite temperatures. For this purpose we modulate the amplitude of the Doppler cooling laser in order to excite and measure mode oscillations. The expected mode softening at the critical point, a signature of the second-order transition,

Katja Kustura, Oriol Romero-Isart, Carlos Gonzalez-Ballestero

We derive a Born-Markov master equation describing the dissipation induced by a bath of lossy but coherently driven two-level systems (TLS) coupled to a bosonic system via Jaynes-Cummings interaction. We analytically derive all the master equation rates. We characterize these rates for the particular case of a single-mode system coupled to identical TLS. We

Jayanta Sarkar

In this article, we study certain type of boundary behaviour of positive solutions of the heat equation on the upper half-space of $\R^{n+1}$. We prove that the existence of the parabolic limit of a positive solution of the heat equation at a point in the boundary is equivalent to the existence of the strong derivative of the boundary measure of the solution

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in security, healthcare, and finance. However, to achieve impressive performance, these algorithms employ very deep network

Yang Zhao, Wenchao Zhai, Jun Zhao, Tinghao Zhang

While fifth-generation (5G) communications are being rolled out worldwide, sixth-generation (6G) communications have attracted much attention from both the industry and the academia. Compared with 5G, 6G will have a wider frequency band, higher transmission rate, spectrum efficiency, greater connection capacity, shorter delay, broader coverage, and more robu

Françoise Liorzou, Pierre Touboul, Manuel Rodrigues, Gilles Métris

Dedicated accelerometers have been developed for the MICROSCOPE mission taking into account the specific range of acceleration to be measured on board the satellite. Considering one micro-g and even less as the full range of the instrument, leads to a customized concept and a high performance electronics for the sensing and servo-actuations of the accelerome

Giovanni Coppola

We studied Ramanujan series $\sum_{q=1}^{\infty}G(q)c_q(a)$, where $c_q(a)$ is the well-known Ramanujan sum and the complex numbers $G(q)$, as $q\in$N, are the Ramanujan coefficients; of course, we mean, implicitly, that the series converges pointwise, in all natural $a$, as its partial sums $\sum_{q\le Q}G(q)c_q(a)$ converge in C, when $Q\to \infty$. Motiva

Cheeun Hong, Heewon Kim, Sungyong Baik, Junghun Oh

Quantizing deep convolutional neural networks for image super-resolution substantially reduces their computational costs. However, existing works either suffer from a severe performance drop in ultra-low precision of 4 or lower bit-widths, or require a heavy fine-tuning process to recover the performance. To our knowledge, this vulnerability to low precision

Lijie Li

Modern semiconductor materials are increasingly used in multidisciplinary systems demonstrating cross-interactions between mechanical strains and electronic potentials, which gives rise to ubiquitous applications in high sensitivity, self-powered sensor devices. One of fundamental prerequisites for such semiconductor materials to exhibit piezoelectric proper

Clara Menzen, Manon Kok, Kim Batselier

Multiway data often naturally occurs in a tensorial format which can be approximately represented by a low-rank tensor decomposition. This is useful because complexity can be significantly reduced and the treatment of large-scale data sets can be facilitated. In this paper, we find a low-rank representation for a given tensor by solving a Bayesian inference

Ognjen Jovanovic, Metodi Plamenov Yankov, Francesco Da Ros, Darko Zibar

Training of autoencoders using the back-propagation algorithm is challenging for non-differential channel models or in an experimental environment where gradients cannot be computed. In this paper, we study a gradient-free training method based on the cubature Kalman filter. To numerically validate the method, the autoencoder is employed to perform geometric

Maxence Grandadam, Catherine Pépin

We compare the pole structure of the electronic Green's function obtained by Cluster Dynamical Mean Field Theory to the results from the fractionalized Pair Density Wave idea. In the superconducting phase, we can consider the system in a state with coexistence of Superconducting and Charge order. Writing the Green's function in a way analogous to the previou

Heewon Kim, Sungyong Baik, Myungsub Choi, Janghoon Choi

Diverse user preferences over images have recently led to a great amount of interest in controlling the imagery effects for image restoration tasks. However, existing methods require separate inference through the entire network per each output, which hinders users from readily comparing multiple imagery effects due to long latency. To this end, we propose a

Sotatsu Yanagimoto, Naoki Yamamoto, Takumi Sannomiya, Keiichirou Akiba

We measured the second-order correlation function of the cathodoluminescence intensity and investigated the Purcell effect by comparing the lifetimes of quantum emitters with and without metal structure. The increase in the electromagnetic local density of state due to the coupling of a quantum emitter with a plasmonic structure causes a shortening of the em

Kaled M. Alshmrany, Rafael S. Menezes, Mikhail R. Gadelha, Lucas C. Cordeiro

We describe and evaluate a novel white-box fuzzer for C programs named FuSeBMC, which combines fuzzing and symbolic execution, and applies Bounded Model Checking (BMC) to find security vulnerabilities in C programs. FuSeBMC explores and analyzes C programs (1) to find execution paths that lead to property violations and (2) to incrementally inject labels to

Gregory Fletcher Cox

When parameters are weakly identified, bounds on the parameters may provide a valuable source of information. Existing weak identification estimation and inference results are unable to combine weak identification with bounds. Within a class of minimum distance models, this paper proposes identification-robust inference that incorporates information from bou

Tuan Minh Pham, Andrew C. Alexander, Jan Korbel, Rudolf Hanel

Recent attempts to understand the origin of social fragmentation are based on spin models which include terms accounting for two social phenomena: homophily -- the tendency for people with similar opinions to establish positive relations -- and social balance -- the tendency for people to establish balanced triadic relations. Spins represent attribute vector

Majid Rafiei, Wil M. P. van der Aalst

Process mining employs event logs to provide insights into the actual processes. Event logs are recorded by information systems and contain valuable information helping organizations to improve their processes. However, these data also include highly sensitive private information which is a major concern when applying process mining. Therefore, privacy prese

Evangelos Mitsokapas, Benjamin Schäfer, Rosemary J. Harris, Christian Beck

The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at sever

Luiz Sena, Erickson Alves, Iury Bessa, Eddie Filho

Implementations of artificial neural networks (ANNs) might lead to failures, which are hardly predicted in the design phase since ANNs are highly parallel and their parameters are barely interpretable. Here, we develop and evaluate a novel symbolic verification framework using incremental bounded model checking (BMC), satisfiability modulo theories (SMT), an

Shrikant Utagi, Subhashish Banerjee, R. Srikanth

The non-Markovianity of the stochastic process called the quantum semi-Markov (QSM) process is studied using a recently proposed quantification of memory based on the deviation from semigroup evolution, that provides a unified description of divisible and indivisible channels. This is shown to bring out the property of QSM processes to exhibit memory effects

Francesco Fambri

In this work we introduce a novel semi-implicit structure-preserving finite-volume/finite-difference scheme for the viscous and resistive equations of magnetohydrodynamics (MHD) based on an appropriate 3-split of the governing PDE system, which is decomposed into a first convective subsystem, a second subsystem involving the coupling of the velocity field wi

Yi-Cai Zhang

In this work, a Josephson relation is generalized to a multi-component fermion superfluid. Superfluid density is expressed through a two-particle Green function for pairing channels. When the system has only one gapless collective excitation mode, the Josephson relation is simplified, which is given in terms of the order parameters and the trace of two-parti

Bernd Hofmann, Christopher Hofmann, Peter Mathé, Robert Plato

The analysis of Tikhonov regularization for nonlinear ill-posed equations with smoothness promoting penalties is an important topic in inverse problem theory. With focus on Hilbert scale models, the case of oversmoothing penalties, i.e., when the penalty takes an infinite value at the true solution gained increasing interest. The considered nonlinearity stru

Gabriel Ziegler

New binary classification tests are often evaluated relative to a pre-established test. For example, rapid Antigen tests for the detection of SARS-CoV-2 are assessed relative to more established PCR tests. In this paper, I argue that the new test can be described as producing ambiguous information when the pre-established is imperfect. This allows for a phen

Tahira Iqbal, Arslan Shaukat, Usman Akram, Zartasha Mustansar

Among various medical imaging tools, chest radiographs are the most important and widely used diagnostic tool for detection of thoracic pathologies. Research is being carried out in order to propose robust automatic diagnostic tool for detection of pathologies from chest radiographs. Artificial Intelligence techniques especially deep learning methodologies h

Shintaro Yamamoto, Anne Lauscher, Simone Paolo Ponzetto, Goran Glavaš

Providing visual summaries of scientific publications can increase information access for readers and thereby help deal with the exponential growth in the number of scientific publications. Nonetheless, efforts in providing visual publication summaries have been few and far apart, primarily focusing on the biomedical domain. This is primarily because of the

Siyuan Cheng, Yingqi Liu, Shiqing Ma, Xiangyu Zhang

Trojan (backdoor) attack is a form of adversarial attack on deep neural networks where the attacker provides victims with a model trained/retrained on malicious data. The backdoor can be activated when a normal input is stamped with a certain pattern called trigger, causing misclassification. Many existing trojan attacks have their triggers being input space

Yi Ding, Wei Zheng, Guozheng Wu, Ji Geng

When diagnosing the brain tumor, doctors usually make a diagnosis by observing multimodal brain images from the axial view, the coronal view and the sagittal view, respectively. And then they make a comprehensive decision to confirm the brain tumor based on the information obtained from multi-views. Inspired by this diagnosing process and in order to further

B. A. van Tiggelen, S. E. Skipetrov

In this work we include the elastic scattering of longitudinal electromagnetic waves in transport theory using a medium filled with point-like, electric dipoles. The interference between longitudinal and transverse waves creates two new channels among which one allows energy transport. This picture is worked out by extending the independent scattering framew

Sebastian Murk, Daniel R. Terno

The existence of black holes is one of the key predictions of general relativity (GR) and therefore a basic consistency test for modified theories of gravity. In the case of spherical symmetry in GR the existence of an apparent horizon and its regularity is consistent with only two distinct classes of physical black holes. Here we derive constraints that any

S. Feng, M. Cucuzzella, T. Bouman, L. Steg

In this paper, we bridge two disciplines: systems & control and environmental psychology. We develop second order Behavior and Personal norm (BP) based models (which are consistent with some studies on opinion dynamics) for describing and predicting human activities related to the final use of energy, where psychological variables, financial incentives and s

Zhengyu Zhao, Zhuoran Liu, Martha Larson

Achieving transferability of targeted attacks is reputed to be remarkably difficult. Currently, state-of-the-art approaches are resource-intensive because they necessitate training model(s) for each target class with additional data. In our investigation, we find, however, that simple transferable attacks which require neither additional data nor model train

Nikheel Soni, Reza Malekian, Arnav Thakur

As the amount of data that needs to be processed in real-time due to recent application developments increase, the need for a new computing paradigm is required. Edge computing resolves this issue by offloading computing resources required by intelligent transportation systems such as the Internet of Vehicles from the cloud closer to the end devices to impro

Víctor Almeida, Jorge J. Betancor

We prove variation and oscillation $L^p$-inequalities associated with fractional derivatives of certain semigroups of operators and with the family of truncations of Riesz transforms in the inverse Gaussian setting. We also study these variational $L^p$-inequalities in a Banach-valued context by considering Banach spaces with the UMD-property and whose marti

Mehrdad Farahani, Mohammad Gharachorloo, Mohammad Manthouri

Text summarization is one of the most critical Natural Language Processing (NLP) tasks. More and more researches are conducted in this field every day. Pre-trained transformer-based encoder-decoder models have begun to gain popularity for these tasks. This paper proposes two methods to address this task and introduces a novel dataset named pn-summary for Per

Maksym V. Strikha, Anatolii I. Kurchak, Anna N. Morozovska

The work estimates the minimum channel length of the MOSFET transistor, which is the bacis device of modern electronics. Taking into account the real shape of potential barrier in the channel shows that the electron tunnels through a region significantly shorter than the physical length of the channel in the presence of drain voltage, and so the available es

Joan Bagaria, Trevor Wilson

We give a level-by-level analysis of the Weak Vop\v{e}nka Principle for definable classes of relational structures (WVP), in accordance with the complexity of their definition, and we determine the large-cardinal strength of each level. Thus, in particular we show that WVP for $\Sigma_2$-definable classes is equivalent to the existence of a strong cardinal.

E. Monteblanco, A. Solignac, C. Chopin, J. Moulin

In this manuscript we propose a theoretical model where the magneto-resistive elements are modelled as fluctuating resistances to correct the output voltage noise of tunnel magnetic junction (MTJ) from standard electronic circuits. This model is validated on single elements, partial and full Wheatstone bridge circuits, giving rise to a correction factor affe

Guofeng Tang

In this paper, we present martingale decomposition on time scales. We establish the related backward stochastic dynamic equations on time scales (this paper BS$\nabla$E for short, concerning $\nabla$-integral on time scales) which unify backward stochastic differential equations and backward stochastic difference equations. We prove the existence and uniquen

Kjetil Thøgersen, Einat Aharonov, Fabian Barras, François Renard

We present a minimal one-dimensional model for the transition from crack-like to pulse-like propagation of frictional rupture. In its non-dimensional form, the model depends on only two free parameters: the non-dimensional pre-stress and an elasticity ratio that accounts for the finite height of the system. The model contains stable slip pulse solutions for

Muneki Yasuda, Kaiji Sekimoto

Evaluating expectations on an Ising model (or Boltzmann machine) is essential for various applications, including statistical machine learning. However, in general, the evaluation is computationally difficult because it involves intractable multiple summations or integrations; therefore, it requires approximation. Monte Carlo integration (MCI) is a well-know

Yuval Shalev, Amichai Painsky, Irad Ben-Gal

Estimating the entropy of a discrete random variable is a fundamental problem in information theory and related fields. This problem has many applications in various domains, including machine learning, statistics and data compression. Over the years, a variety of estimation schemes have been suggested. However, despite significant progress, most methods sti

Fabien Besnard

We apply Connes-Chamseddine spectral action to the $U(1)_{\rm B-L}$- extension of the Standard Model. We show that in order for the scalar potential to reach its minimum for a non-zero value of the new complex scalar field, thus triggering the breaking of B-L symmetry, a constraint on the quartic coupling constants must be satisfied at unification scale. We

Pranesh Vallabh, Nazanin Malekian, Reza Malekian, Ting-Mei Li

Personalized fall detection system is shown to provide added and more benefits compare to the current fall detection system. The personalized model can also be applied to anything where one class of data is hard to gather. The results show that adapting to the user needs, improve the overall accuracy of the system. Future work includes detection of the smart

Nadezhda V. Timofeeva

A procedure resolving a torsion-free coherent sheaf on a nonsingular $N$-dimensional projective algebraic variety into a locally free sheaf on a projective scheme of certain class is proposed. This is a higher-dimensional analog of the resolution (called the standard resolution in previous works of the author) of coherent sheaves on a surface. The method is

Xuanhong Chen, Ziang Liu, Ting Qiu, Bingbing Ni

Prevailing image-translation frameworks mostly seek to process images via the end-to-end style, which has achieved convincing results. Nonetheless, these methods lack interpretability and are not scalable on different image-translation tasks (e.g., style transfer, HDR, etc.). In this paper, we propose an interpretable knowledge-based image-translation framew

Gianluca Rizzi, Domenico Tallarico, Patrizio Neff, Angela Madeo

In this paper we show that an enriched continuum model of the micromorphic type (Relaxed Micromorphic Model) can be used to model metamaterials' response in view of their use for meta-structural design. We focus on the fact that the reduced model's structure, coupled with the introduction of well-posed interface conditions, allows us to easily test different

Zerui Zhang, Tran Giang Nam

In this paper, we first study properties of the lower central chains for Novikov algebras. Then we show that for every Lie nilpotent Novikov algebra~$\mathcal{N}$, the ideal of~$\mathcal{N}$ generated by the set~$\{ab - ba\mid a, b\in \mathcal{N}\}$ is nilpotent. We secondly provide necessary and sufficient conditions on the graph $E$ and the field $K$ for w

Ricardo Monteiro, Donal O'Connell, David Peinador Veiga, Matteo Sergola

The three-point amplitude is the key building block in the on-shell approach to scattering amplitudes. We show that the classical objects computed by massive three-point amplitudes in gauge theory and gravity are Newman-Penrose scalars in a split-signature spacetime, where three-point amplitudes can be defined for real kinematics. In fact, the quantum state

Charles Alexandre Bédard

It has been more than 20 years since Deutsch and Hayden proved the locality of quantum theory, using the Heisenberg picture of quantum computational networks. Of course, locality holds even in the face of entanglement and Bell's theorem. Today, most researchers in quantum foundations are still convinced not only that a local description of quantum systems ha

Tom Tseng, Laxman Dhulipala, Julian Shun

SCAN (Structural Clustering Algorithm for Networks) is a well-studied, widely used graph clustering algorithm. For large graphs, however, sequential SCAN variants are prohibitively slow, and parallel SCAN variants do not effectively share work among queries with different SCAN parameter settings. Since users of SCAN often explore many parameter settings to f

Xinyu Zhang, Xinlong Wang, Jia-Wang Bian, Chunhua Shen

Person search aims to localize and identify a specific person from a gallery of images. Recent methods can be categorized into two groups, i.e., two-step and end-to-end approaches. The former views person search as two independent tasks and achieves dominant results using separately trained person detection and re-identification (Re-ID) models. The latter pe

Francesca Arici, Jens Kaad

Motivated by the study of symmetries of C*-algebras, as well as by multivariate operator theory, we introduce the notion of an SU(2)-equivariant subproduct system of Hilbert spaces. We analyse the resulting Toeplitz and Cuntz-Pimsner algebras and provide results about their topological invariants through Kasparov's bivariant K-theory. In particular, starting

Shengqi Geng

With the gradual application of infrared night vision vehicle assistance system in automatic driving, the accuracy of the collected infrared images of pedestrians is gradually improved. In this paper, the migration learning method is used to apply YOLOv3 model to realize pedestrian target detection in infrared images. The target detection model YOLOv3 is mig

Haichao Zhang, Kuangrong Hao, Lei Gao, Bing Wei

Deep neural networks (DNNs) have achieved remarkable success in computer vision; however, training DNNs for satisfactory performance remains challenging and suffers from sensitivity to empirical selections of an optimization algorithm for training. Stochastic gradient descent (SGD) is dominant in training a DNN by adjusting neural network weights to minimize

Alberto Ramos

We present ADerrors.jl, a software for linear error propagation and analysis of Monte Carlo data. Although the focus is in data analysis in Lattice QCD, where estimates of the observables have to be computed from Monte Carlo samples, the software also deals with variables with uncertainties, either correlated or uncorrelated. Thanks to automatic differentiat

Andrea Fioraldi

Fuzz testing proved its great effectiveness in finding software bugs in the latest years, however, there are still open challenges. Coverage-guided fuzzers suffer from the fact that covering a program point does not ensure the trigger of a fault. Other more sensitive techniques that in theory should cope with this problem, such as the coverage of the memory