June 2020 arXiv papers — page 13

Marco Gullieuszik, Bianca M. Poggianti, Sean L. McGee, Alessia Moretti

Using MUSE observations from the GASP survey, we study 54 galaxies undergoing ram-pressure stripping (RPS) spanning a wide range in galaxy mass and host cluster mass. We use this rich sample to study how the star formation rate (SFR) in the tails of stripped gas depends on the properties of the galaxy and its host cluster. We show that the interplay between

Sergio Morales-Tejera, Karl Landsteiner

We study the chiral vortical effect far from equilibrium in a strongly coupled holographic field theory. Rotation is represented as a perturbation via a gravito-magnetic field on top of a five-dimensional charged AdS Vaidya metric. We also introduce a momentum relaxation mechanism by linear scalar field backgrounds and study the CVE dynamics as function of t

N. Sahakyan

The origin of the multiwavelength emission from the high-synchrotron-peaked BL Lac 1ES 1218+304 is studied using the data from {\it Swift UVOT/XRT}, {\it NuSTAR} and {\it Fermi-LAT}. A detailed temporal and spectral analysis of the data observed during 2008-2020 in the $γ$-ray ($>100$ MeV), X-ray (0.3-70 keV), and optical/UV bands is performed. The $γ$-ray s

Maxim Lyutikov

We discuss coherent free electron laser (FEL) operating during explosive reconnection events in magnetized pair plasma of magnetar magnetospheres. The model explains many salient features of Fast Radio Bursts/magnetars' radio emission: temporal coincidence of radio and high energy bursts, high efficiency of conversion of plasma kinetic energy into cohere

Aleksandr Parkin, Oleg Grinchuk

Special cameras that provide useful features for face anti-spoofing are desirable, but not always an option. In this work we propose a method to utilize the difference in dynamic appearance between bona fide and spoof samples by creating artificial modalities from RGB videos. We introduce two types of artificial transforms: rank pooling and optical flow, com

Mitsuhiro Miyazaki, Janet Page

Let $P$ be a finite poset, $K$ a field, and $O(P)$ (resp. $C(P)$) the order (resp. chain) polytope of $P$. We study the non-Gorenstein locus of $E_K[O(P)]$ (resp. $E_K[C(P)]$), the Ehrhart ring of $O(P)$ (resp. $C(P)$) over $K$, which are each normal toric rings associated $P$. In particular, we show that the dimension of non-Gorenstein loci of $E_K[O(P)]$ a

Yichao Liu, Alessandro Fontanella, Ping Wu, Riccardo M. G. Ferrari

Floating Offshore Wind Turbines (FOWTs) are more prone to suffer from faults and failures than bottom-fixed counterparts due to the severe wind and wave loads typical of deep water sites. In particular, mooring line faults may lead to unacceptably high operation and maintenance costs due to the limited accessibility of FOWTs. Detecting the mooring line fault

Albacete Colombo J. F., Drake J. J., Filócomo A., Wright N. J

The Cygnus\,OB2 region, $\sim 3.5-5~\text{Myr}$ old, contains one of the most significant populations of massive stars of the Milky Way. Such stars substantially contribute to producing large scale soft ($<2~\text{keV}$) diffuse X-ray emission. We also detected hard ($>3~\text{keV}$) diffuse X-ray emission in the direction of the pulsar PSR\,J2032+4127. The

Rafal Maciula, Antoni Szczurek

We discuss the role of intrinsic charm (IC) in the nucleon for forward production of $c$-quark (or $\bar c$-antiquark) in proton-proton collisions for low and high energies. The calculations are performed in collinear-factorization approach with on-shell partons, $k_T$-factorization approach with off-shell partons as well as in a hybrid approach using collin

Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder

Deep learning based physical layer design, i.e., using dense neural networks as encoders and decoders, has received considerable interest recently. However, while such an approach is naturally training data-driven, actions of the wireless channel are mimicked using standard channel models, which only partially reflect the physical ground truth. Very recently

Liam H. Harris, Stephanie Perkins, Paul A. Roach

Bishop independence concerns determining the maximum number of bishops that can be placed on a board such that no bishop can attack any other bishop. This paper presents the solution to the bishop independence problem, determining the bishop independence number, for all sizes of boards on the surface of a square prism.

Nan Ge, Richard Bamler, Danfeng Hong, Xiao Xiang Zhu

This paper addresses the general problem of single-look multi-master SAR tomography. For this purpose, we establish the single-look multi-master data model, analyze its implications for single and double scatterers, and propose a generic inversion framework. The core of this framework is nonconvex sparse recovery, for which we develop two algorithms: one ext

Madhu Gupta, Rohit Kumar Mishra, Souvik Roy

We present a new nonlinear optimization approach for the sparse reconstruction of single-photon absorption and two-photon absorption coefficients in photoacoustic tomography (PAT). This framework comprises of minimizing an objective functional involving a least squares fit of the interior pressure field data corresponding to two boundary source functions, wh

A. Dobrotka, H. Negoro, P. Konopka

AIMS: We studied unique data of a nova-like system MV Lyr during transition from the high to low state and vice versa taken by the Kepler space telescope. We were interested in evolution of frequency components found previously by Scaringi et al. in different data also obtained by Kepler. METHODS: We divided the light curve into 10 day segments and investiga

Shenglan Liu, Yang Yu

Manifold Learning occupies a vital role in the field of nonlinear dimensionality reduction and its ideas also serve for other relevant methods. Graph-based methods such as Graph Convolutional Networks (GCN) show ideas in common with manifold learning, although they belong to different fields. Inspired by GCN, we introduce neighbor propagation into LLE and pr

Matteo Lucchini, Shunsuke A. Sato, Giacinto D. Lucarelli, Bruno Moio

The electro-optical properties of most semiconductors and insulators of technological interest are dominated by the presence of electron-hole quasiparticles called excitons. The manipulation of these hydrogen-like quasi-particles in dielectrics, has received great interest under the name excitonics that is expected to be of great potential for a variety of a

Xichuan Zhou, Yicong Peng, Chunqiao Long, Fengbo Ren

Monocular multi-object detection and localization in 3D space has been proven to be a challenging task. The MoNet3D algorithm is a novel and effective framework that can predict the 3D position of each object in a monocular image and draw a 3D bounding box for each object. The MoNet3D method incorporates prior knowledge of the spatial geometric correlation o

John Vandermeer, Zachary Hajian-Forooshani, Nicholas Medina, Ivette Perfecto

Ecological systems, as is often noted, are complex. Equally notable is the generalization that complex systems tend to be oscillatory, whether Huygens simple patterns of pendulum entrainment or the twisted chaotic orbits of Lorenz convection rolls. The analytics of oscillators may thus provide insight into the structure of ecological systems. One of the most

Eric W. Hester, Louis-Alexandre Couston, Benjamin Favier, Keaton J. Burns

We develop and analyse the first second-order phase-field model to combine melting and dissolution in multi-component flows. This provides a simple and accurate way to simulate challenging phase-change problems in existing codes. Phase-field models simplify computation by describing separate regions using a smoothed phase field. The phase field eliminates th

Panagiotis Charalampopoulos, Jakub Radoszewski, Wojciech Rytter, Tomasz Waleń

The notions of periodicity and repetitions in strings, and hence these of runs and squares, naturally extend to two-dimensional strings. We consider two types of repetitions in 2D-strings: 2D-runs and quartics (quartics are a 2D-version of squares in standard strings). Amir et al. introduced 2D-runs, showed that there are $O(n^3)$ of them in an $n \times n$

Jaesik Yoon, Gautam Singh, Sungjin Ahn

When tasks change over time, meta-transfer learning seeks to improve the efficiency of learning a new task via both meta-learning and transfer-learning. While the standard attention has been effective in a variety of settings, we question its effectiveness in improving meta-transfer learning since the tasks being learned are dynamic and the amount of context

Christin David

Spatial interaction effects between charge carriers in ionic systems play a sizable role beyond a classical Maxwellian description. We develop a nonlocal, two-fluid, hydrodynamic theory of charges and study ionic plasmon effects, i. e. collective charge oscillations in electrolytes. Ionic spatial dispersion arises from both positive and negative charge dynam

Gabriëlle Ras, Luca Ambrogioni, Pim Haselager, Marcel A. J. van Gerven

In this paper we introduce the temporally factorized 3D convolution (3TConv) as an interpretable alternative to the regular 3D convolution (3DConv). In a 3TConv the 3D convolutional filter is obtained by learning a 2D filter and a set of temporal transformation parameters, resulting in a sparse filter where the 2D slices are sequentially dependent on each ot

Yuto Minami, Eiichiro Komatsu

We develop a strategy to determine the cosmic birefringence and miscalibrated polarization angles simultaneously using the observed $EB$ polarization power spectra of the cosmic microwave background and the Galactic foreground emission. We extend the methodology of Y. Minami et al. (Prog. Theor. Exp. Phys. $\mathbf{2019}$, 083E02, 2019), which was developed

Yu. D. Fomin, E. N. Tsiok, V. N. Ryzhov

We investigate a behavior of a core-softened system in a thin slit pore (the width of the pore is equil to three diameters of the particles). In previous studies it was shown that strongly confined systems form crystalline phases which consist of several triangular or square layers. These phases can be also considered as cuts of FCC or HCP structures. We sho

Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke

In this work we focus on the well-known Euclidean Traveling Salesperson Problem (TSP) and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per-instance algorithm selection (AS). We evolve instances with 1,000 nodes where the solvers show strongly different performance profiles. These instances serve as a basis for an explo

Antti Suni, Sofoklis Kakouros, Martti Vainio, Juraj Šimko

Recent advances in deep learning methods have elevated synthetic speech quality to human level, and the field is now moving towards addressing prosodic variation in synthetic speech.Despite successes in this effort, the state-of-the-art systems fall short of faithfully reproducing local prosodic events that give rise to, e.g., word-level emphasis and phrasal

M. C. Rodriguez

We review very nice mechanism to generate masses to all the neutrinos in the Minimal Supersymmetric Standard Model (MSSM) without break $R$-parity. In consequence we get viable axion as Dark Matter candidate and at the same time solve the $μ$-problem in a similar way as done in the Next to Minimal Supersymmetric Model (NMSSM).

Atac Imamoglu, Ovidiu Cotlet, Richard Schmidt

The elementary optical excitations of a two-dimensional electron or hole system have been identified as exciton-Fermi-polarons. Nevertheless, the connection between the bound state of an exciton and an electron, termed trion, and exciton-polarons is subject of ongoing debate. Here, we use an analogy to the Tavis-Cummings model of quantum optics to show that

Yong Shao, Xiang-Dong Li

We present a systematic study of the X-ray binaries (XRBs) containing a black hole (BH) and a non-degenerate companion, in which mass transfer takes place via either capturing the companion&#39;s wind or Roche lobe overflow (RLO). As shown in our previous work that focusing on the formation and evolution of detached BH binaries, our assumed models relevant t

Christin David, James P. Connolly, Christian Chaverri Ramos, F. Javier García de Abajo

Random Al and Ag nanoparticle distributions are studied on varying substrates, where we exploit the nanosphere self-aggregation method (NSA) for fabrication. Relying on the measured particle size distributions of these samples, we develop a theoretical model that can be applied to arbitrary random nanostructure layers as is demonstrated for several distinct

Sushil Dubey, Sukh Veer, Seshagiri Rao R, Chirag Kalelkar

Rheological properties of a material often require to be probed under extensional deformation. Examples include fibrous materials such as spider-silk, high-molecular weight polymer melts, and the contractile response of living cells. Such materials have strong molecular-level anisotropies which are either inherent or are induced by an imposed extension. Howe

Jean-Benoit Delbrouck, Noé Tits, Mathilde Brousmiche, Stéphane Dupont

Understanding expressed sentiment and emotions are two crucial factors in human multimodal language. This paper describes a Transformer-based joint-encoding (TBJE) for the task of Emotion Recognition and Sentiment Analysis. In addition to use the Transformer architecture, our approach relies on a modular co-attention and a glimpse layer to jointly encode one

Arjan van der Schaft, Dimitri Jeltsema

A consequence of the Second Law of thermodynamics is that no thermodynamic system with a single heat source at constant temperature can convert heat into mechanical work in a recurrent manner. First we note that this is equivalent to cyclo-passivity at the mechanical port of the thermodynamic system, while the temperature at the thermal port of the system is

A. M. Romanovskaya, T. A. Ryabchikova, D. V. Shulyak

We present the results of a self-consistent spectroscopic analysis of the atmosphere of Ap-star HD 108662 based on high resolution spectrum and low resolution spectrophotometric observations. Magnetic field effects, such as Zeeman broadening and polarized line formation, were taking into account in the analysis of spectral line profiles. We derived abundance

Hendry F. Chame, Ahmadreza Ahmadi, Jun Tani

Human-robot interaction is becoming an interesting area of research in cognitive science, notably, for the study of social cognition. Interaction theorists consider primary intersubjectivity a non-mentalist, pre-theoretical, non-conceptual sort of processes that ground a certain level of communication and understanding, and provide support to higher-level co

Maxime De Bois, Mehdi Ammi, Mounîm A. El Yacoubi

Due to the sensitive nature of diabetes-related data, preventing them from being shared between studies, progress in the field of glucose prediction is hard to assess. To address this issue, we present GLYFE (GLYcemia Forecasting Evaluation), a benchmark of machine-learning-based glucose-predictive models. To ensure the reproducibility of the results and the

M. Cobal, C. De Dominicis, M. Fabbrichesi, E. Gabrielli

We study the decay of the $Z$ vector boson into a photon and a massless (invisible) dark photon in high-energy collisions. The photon can be used as trigger for the event, while the dark photon is detected indirectly as missing momentum in the event final state. We investigate the possibility of searching for such a dark photon at the LHC, HL-LHC and future

Thierry Cazenave, Flávio Dickstein, Ivan Naumkin, Fred B. Weissler

We study the existence of sign-changing solutions to the nonlinear heat equation $\partial _t u = Δu + |u|^αu$ on ${\mathbb R}^N $, $N\ge 3$, with $\frac {2} {N-2} < α<α_0$, where $α_0=\frac {4} {N-4+2\sqrt{ N-1 } }\in (\frac {2} {N-2}, \frac {4} {N-2})$, which are singular at $x=0$ on an interval of time. In particular, for certain $μ>0$ that can be arbitra

Majdouline Borji, Christoph Kopper

The flow equations of the renormalization group allow to analyse the perturbative $n$-point functions of renormalizable quantum filed theories. Rigorous bounds implying renormalizability permit to control large momentum behaviour, infrared singularities and large order behaviour in the number of loops and the number of arguments $n$. In this paper, we analys

Maxime De Bois, Mounîm A. El Yacoubi, Mehdi Ammi

Deep learning has yet to revolutionize general practices in healthcare, despite promising results for some specific tasks. This is partly due to data being in insufficient quantities hurting the training of the models. To address this issue, data from multiple health actors or patients could be combined by capitalizing on their heterogeneity through the use

Shu Wu, Feng Yu, Xueli Yu, Qiang Liu

The CTR (Click-Through Rate) prediction plays a central role in the domain of computational advertising and recommender systems. There exists several kinds of methods proposed in this field, such as Logistic Regression (LR), Factorization Machines (FM) and deep learning based methods like Wide&Deep, Neural Factorization Machines (NFM) and DeepFM. However, su

Mengfei He

When a solid plate is withdrawn from a partially wetting liquid, a liquid layer dewets the moving substrate. High-speed imaging reveals alternating thin and thick regions in the entrained layer in the transverse direction at steady state. This paper systematically compares this situation to the reversed process, forced wetting, where a solid entrains an air

Chuandong Lin, Kai Hong Luo, Linlin Fei, Sauro Succi

We propose a multi-component discrete Boltzmann model (DBM) for premixed, nonpremixed, or partially premixed nonequilibrium reactive flows. This model is suitable for both subsonic and supersonic flows with or without chemical reaction and/or external force. A two-dimensional sixteen-velocity model is constructed for the DBM. In the hydrodynamic limit, the D

Christin David, Marten Richter, Andreas Knorr, Inez M. Weidinger

We have investigated the plasmonic enhancement of the radiation field at various nanostructured multilayer devices, that may be applied in surface enhanced Raman spectroscopy. We apply an image dipole method to describe the effect of surface morphology on the field enhancement in a quasistatic limit. In particular, we compare the performance of a nanostructu

Zhan Wang, Guang-Ming Zhang, Yi-feng Yang, Fu-Chun Zhang

We report theoretical predictions on the pairing symmetry of the newly discovered superconducting nickelate Nd$_{1-x}$Sr$_{x}$NiO$_{2}$ based on the renormalized mean-field theory for a generalized model Hamiltonian proposed in [Phys. Rev. B \textbf{101}, 020501(R)]. For practical values of the key parameters, we find a transition between a gapped ($d+is$)-w

Jandre Albertyn, Ling Cheng, Adnan M. Abu-Mahfouz

Increasing electricity prices in South Africa and the imminent threat of load shedding due to the overloaded power grid has led to a need for Demand Side Management (DSM) devices like smart grids. For smart grids to perform to their peak, their energy management controller (EMC) systems need to be optimized. Current solutions for DSM and optimization of the

L. Consolino, A. Campa, M. De Regis, F. Cappelli

Full phase control of THz emitting quantum cascade laser (QCL) combs has recently been demonstrated, opening new perspectives for even the most demanding applications. In this framework, simplifying the set-ups for control of these devices will help to accelerate their spreading in many fields. We report a new way to control the emission frequencies of a THz

Viviana del Barco, Andrei Moroianu, Alberto Raffero

We consider left-invariant (purely) coclosed G$_2$-structures on 7-dimensional 2-step nilpotent Lie groups. According to the dimension of the commutator subgroup, we obtain various criteria characterizing the Riemannian metrics induced by left-invariant purely coclosed G$_2$-structures. Then, we use them to determine the isomorphism classes of 2-step nilpote

Ali Hebbal, Loic Brevault, Mathieu Balesdent, El-Ghazali Talbi

Multi-fidelity approaches combine different models built on a scarce but accurate data-set (high-fidelity data-set), and a large but approximate one (low-fidelity data-set) in order to improve the prediction accuracy. Gaussian Processes (GPs) are one of the popular approaches to exhibit the correlations between these different fidelity levels. Deep Gaussian

Christopher H. Cashen, Charlotte Hoffmann

We give experimental support for a conjecture of Louder and Wilton saying that words of imprimitivity rank greater than two yield hyperbolic one-relator groups.

R. C. Teixeira, A. Larrouy, A. Muni, L. Lachaud

Alkaline earth Rydberg atoms are very promising tools for quantum technologies. Their highly excited outer electron provides them with the remarkable properties of Rydberg atoms and, notably, with a huge coupling to external fields or to other Rydberg atoms while the ionic core retains an optically active electron. However, low angular-momentum Rydberg state

Christopher Goes

The interblockchain communication protocol (IBC) is an end-to-end, connection-oriented, stateful protocol for reliable, ordered, and authenticated communication between modules on separate distributed ledgers. IBC is designed for interoperation between heterogenous ledgers arranged in an unknown, dynamic topology, operating with varied consensus algorithms a

Dimiter Prodanov

The present work demonstrates the connections between the Burgers, diffusion, and Schroedinger&#39;s equations. The starting point is a formulation of the stochastic mechanics, which is modeled along the lines of the scale relativity theory. The resulting statistical description obeys the Fokker-Planck equation. This paper further demonstrates the connection

Yasin Hasanoğlu, Cihangir Özemir

We consider a family of higher-order Boussinesq equations with an arbitrary nonlinearity. We determine the classes of equations so that a certain type of Lie symmetry algebra is admitted in this family. In case of a quadratic nonlinearity we provide several exact solutions, some of which are in terms of elliptic functions.

Projesh Nath Choudhury, M. Rajesh Kannan, K. C. Sivakumar

Let $H$ be a real Hilbert space. In this short note, using some of the properties of bounded linear operators with closed range defined on $H$, certain bounds for a specific convex subset of the solution set of infinite linear complementarity problems, are established.

Kazuya Koyama

The Brans-Dicke theory of gravity is one of the oldest ideas to extend general relativity by introducing a non-minimal coupling between the scalar field and gravity. The Solar System tests put tight constraints on the theory. In order to evade these constraints, various screening mechanisms have been proposed. These screening mechanisms allow the scalar fiel

Ayman A. El-Zoka, Se-Ho Kim, Sylvain Deville, Roger C. Newman

Transmission electron microscopy has undergone a revolution in recent years with the possibility to perform routine cryo-imaging of biological materials and (bio)chemical systems, as well as the possibility to image liquids via dedicated reaction cells or graphene-sandwiching. These approaches however typically require imaging a large number of specimens and

Pradip Sircar, Rakesh Kumar Sharma

In this paper, we propose a novel approach for parametric modeling of electroencephalographic (EEG) signals. It is demonstrated that the EEG signal is a mono-component non-stationary signal whose amplitude and phase (frequency) can be expressed as functions of time. We present detailed strategy for estimation of the parameters of the proposed model with high

Martin Aleksandrov, Toby Walsh

This paper combines two key ingredients for online algorithms - competitive analysis (e.g. the competitive ratio) and advice complexity (e.g. the number of advice bits needed to improve online decisions) - in the context of a simple online fair division model where items arrive one by one and are allocated to agents via some mechanism. We consider four such

Martin Aleksandrov, Toby Walsh

Two simple and attractive mechanisms for the fair division of indivisible goods in an online setting are LIKE and BALANCED LIKE. We study some fundamental computational problems concerning the outcomes of these mechanisms. In particular, we consider what expected outcomes are possible, what outcomes are necessary, and how to compute their exact outcomes. In

Mohammad Mohammadamini, Driss Matrouf

The explosion of available speech data and new speaker modeling methods based on deep neural networks (DNN) have given the ability to develop more robust speaker recognition systems. Among DNN speaker modelling techniques, x-vector system has shown a degree of robustness in noisy environments. Previous studies suggest that by increasing the number of speaker

Ariyoshi Kunitomo, Akika Nakamichi, Tetsuya Hara

The structure of geomagnetism is very complex, and there are still some problems left in magnetohydrodynamics (MHD) simulations. Recently, the macro spin model has been suggested. This is the idea that geomagnetism is described by interaction with many local dynamo elements (macro-spins). This model can reproduce some features of geomagnetism by solving equa

Kai Wang, Da-Bin Lin, Yun Wang, Lu-yao Jiang

It is generally believed that the variability of photospheric emission in gamma-ray bursts (GRBs) traces that of the jet power. This work further investigates the variability of photospheric emission in a variable jet. By setting a constant $η$ (dimensionless entropy of the jet), we find that the light curve of the photospheric emission shows a ``tracking&#3

Martin Aleksandrov, Toby Walsh

We consider fair division problems where indivisible items arrive one-by-one in an online fashion and are allocated immediately to agents who have additive utilities over these items. Many existing offline mechanisms do not work in this online setting. In addition, many existing axiomatic results often do not transfer from the offline to the online setting.

Ce Wang, Haiwei Li, Zhenqi Hao, Xintong Li

In this work we train a neural network to identify impurities in the experimental images obtained by the scanning tunneling microscope measurements. The neural network is first trained with large number of simulated data and then the trained neural network is applied to identify a set of experimental images taken at different voltages. We use the convolution

Martin Aleksandrov, Toby Walsh

We study the fair division of items to agents supposing that agents can form groups. We thus give natural generalizations of popular concepts such as envy-freeness and Pareto efficiency to groups of fixed sizes. Group envy-freeness requires that no group envies another group. Group Pareto efficiency requires that no group can be made better off without anoth

Martin Aleksandrov, Toby Walsh

We study a new but simple model for online fair division in which indivisible items arrive one-by-one and agents have monotone utilities over bundles of the items. We consider axiomatic properties of mechanisms for this model such as strategy-proofness, envy-freeness, and Pareto efficiency. We prove a number of impossibility results that justify why we consi

Silke Klemm, Lucrezia Ravera

A longstanding open problem in mathematical physics has been that of finding an action principle for the Einstein-Weyl (EW) equations. In this paper, we present for the first time such an action principle in three dimensions in which the Weyl vector is not exact. More precisely, our model contains, in addition to the Weyl nonmetricity, a traceless part. If t

Dania Marabissi, Lorenzo Mucchi, Stefano Caputo, Francesca Nizzi

One of the main revolutionary features of 5G networks is the ultra-low latency that will enable new services such as those for the future smart vehicles. The 5G technology will be able to support extreme-low latency. Thanks to new technologies and the wide flexible architecture that integrates new spectra and access technologies. In particular, Visible Light

Qianni Jiang, Yue Shi, Morten H. Christensen, Joshua Sanchez

We present a systematic study of the nematic fluctuations in the iron chalcogenide superconductor Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ ($0 \leq x \leq 0.53$) using the elastoresistivity technique. Near $x = 0$, in proximity to the double-stripe magnetic order of Fe$_{1+y}$Te, a diverging $B_{1g}$ nematic susceptibility is observed. Upon increasing $x$, despite the a

Andres Cotorruelo, Mehdi Hosseinzadeh, Daniel R. Ramirez, Daniel Limon

The goal of this paper is to present a systematic method to compute reference dependent positively invariant sets for systems subject to constraints. To this end, we first characterize these sets as level sets of reference dependent Lyapunov functions. Based on this characterization and using Sum of Squares (SOS) theory, we provide a polynomial certificate f

Francis Filbet

In this paper we present a spectral collocation method for the fast evaluation of the Landau collision operator for plasma physics, which allows us to obtain spectrally accurate numerical solutions. The method is inspired by the seminal work [36], but it is specifically designed for Coulombian interactions, taking into account the particular structure of the

Maxim V. Gorkunov, Alexander A. Antonov, Yuri S. Kivshar

We demonstrate that rotationally symmetric chiral metasurfaces can support arbitrarily sharp resonances with the maximum optical chirality determined by precise shaping of bound states in the continuum (BICs). Being uncoupled from one circular polarisation of light and resonantly coupled to its counterpart, a metasurface hosting the chiral BIC resonance exhi

Said Hamadène, Tingshu Mu

In this paper we study a zero-sum switching game and its verification theorems expressed in terms of either a system of Reflected Backward Stochastic Differential Equations (RBSDEs in short) with bilateral interconnected obstacles or a system of parabolic partial differential equations (PDEs in short) with bilateral interconnected obstacles as well. We show

Abdoul Karim Sane

This article first answers to questions about connectedness of a new family of graphs on unicellular maps. Answering these questions goes through a description of the mapping class group as surgeries on unicellular maps. We also show how unicellular maps encode subgroups of the mapping group and provide filtrations of the mapping class group. These facts add

Philippe Laurençot

Existence and non-existence of integrable stationary solutions to Smoluchowski&#39;s coagulation equation with source are investigated when the source term is integrable with an arbitrary support in (0, $\infty$). Besides algebraic upper and lower bounds, a monotonicity condition is required for the coagulation kernel. Connections between integrability prope

Abigail Goldsteen, Gilad Ezov, Ariel Farkash

Machine learning models often pose a threat to the privacy of individuals whose data is part of the training set. Several recent attacks have been able to infer sensitive information from trained models, including model inversion or attribute inference attacks. These attacks are able to reveal the values of certain sensitive features of individuals who parti

Jing Sun, Daxin Nie, Weihua Deng

The Feynman-Kac equation governs the distribution of the statistical observable -- functional, having wide applications in almost all disciplines. After overcoming challenges from the time-space coupled nonlocal operator and the possible low regularity of functional, this paper develops the high-order fully discrete scheme for the backward fractional Feynman

Kai Xiong, Supeng Leng, Xiaosha Chen, Chongwen Huang

Transportation system is facing a sharp disruption since the Connected Autonomous Vehicles (CAVs) can free people from driving and provide good driving experience with the aid of Vehicle-to-Vehicle (V2V) communications. Although CAVs bring benefits in terms of driving safety, vehicle string stability, and road traffic throughput, most existing work aims at i

Chunhua Jia, Wenhai Yi, Yu Wu, Hui Huang

We present a work-flow which aims at capturing residents&#39; abnormal activities through the passenger flow of elevator in multi-storey residence buildings. Camera and sensors (hall sensor, photoelectric sensor, gyro, accelerometer, barometer, and thermometer) with internet connection are mounted in elevator to collect image and data. Computer vision algori

Jannik Fischbach, Benedikt Hauptmann, Lukas Konwitschny, Dominik Spies

System behavior is often based on causal relations between certain events (e.g. If event1, then event2). Consequently, those causal relations are also textually embedded in requirements. We want to extract this causal knowledge and utilize it to derive test cases automatically and to reason about dependencies between requirements. Existing NLP approaches fai

Irina Ignatiouk-Robert

We investigate Martin boundary for a non-centered random walk on ${\mathbb Z}^d$ killed up on the time $τ_\vartheta$ of the first exit from a convex cone with a vertex at $0$. The approach combines large deviation estimates, the ratio limite theorem and the ladder height process. The results are applied to identify the Martin boundary for a random walk kille

Ana Arnal, Fernando Casas, Cristina Chiralt

We get compact expressions for the Baker--Campbell--Hausdorff series $Z = \log(\e^X \, \e^Y)$ in terms of right-nested commutators. The reduction in the number of terms originates from two facts: (i) we use as a starting point an explicit expression directly involving independent commutators and (ii) we derive a complete set of identities arising among right

Christian Romen, Andreas M. Läuchli

Quantum magnets with a large SU($N$) symmetry are a promising playground for the discovery of new forms of exotic quantum matter. Motivated by recent experimental efforts to study SU($N$) quantum magnetism in samples of ultracold fermionic alkaline-earth-like atoms in optical lattices, we study here the temperature dependence of spin correlations in the SU($

Inna Roitberg, Alexander Sakhnovich

The results on the inversion of convolution operators as well as Toeplitz (and block Toeplitz) matrices in the $1$-D (one-dimensional) case are classical and have numerous applications. Last year, we considered the $2$-D case of Toeplitz-block Toeplitz (TBT) matrices, described a minimal information, which is necessary to recover the inverse matrices, and ga

Stefan Sauter, Céline Torres

We study wave propagation phenomena modelled in the frequency domain by the Helmholtz equation in heterogeneous media with focus on media with discontinuous, highly oscillating wave speed. We restrict to problems with spherical symmetry and will derive explicit representations of the Green&#39;s operator and stability estimates which are explicit in the freq

Aditi Shenvi, Jim Q. Smith

Chain Event Graphs (CEGs) are a family of event-based graphical models that represent context-specific conditional independences typically exhibited by asymmetric state space problems. The class of continuous time dynamic CEGs (CT-DCEGs) provides a factored representation of longitudinally evolving trajectories of a process in continuous time. Temporal evide

Axel Berg, Magnus Oskarsson, Mark O&#39;Connor

Regression via classification (RvC) is a common method used for regression problems in deep learning, where the target variable belongs to a set of continuous values. By discretizing the target into a set of non-overlapping classes, it has been shown that training a classifier can improve neural network accuracy compared to using a standard regression approa

Aidin Ferdowsi, Mohamed A. Abd-Elmagid, Walid Saad, Harpreet S. Dhillon

In this paper, an unmanned aerial vehicle (UAV)-assisted wireless network is considered in which a battery-constrained UAV is assumed to move towards energy-constrained ground nodes to receive status updates about their observed processes. The UAV&#39;s flight trajectory and scheduling of status updates are jointly optimized with the objective of minimizing

Yangyang Liu, Yongjia Wang, Ying Cui, Chen-Jun Xia

The $NΔ\to NN$ cross sections, which take into account the $Δ$-mass dependence of M-matrix and momentum $p_{NΔ}$, are applied on the calculation of pion production within the framework of the UrQMD model. Our study shows that UrQMD calculations with the $Δ$-mass dependent $NΔ\to NN$ cross sections enhance the pion multiplicities and decrease the $π^-/π^+$ ra

Yuto Moriwaki

In physics, it is believed that the consistency of two dimensional conformal field theory follows from the bootstrap equation. In this paper, we introduce the notion of a full vertex algebra by analyzing the bootstrap equation, which is a &#34;real analytic&#34; generalization of a $\mathbb{Z}$-graded vertex algebra. We also give a mathematical formulation o

Kai Xiong, Supeng Leng, Chongwen Huang, Chau Yuen

With the rapid development of autonomous driving technologies, it becomes difficult to reconcile the conflict between ever-increasing demands for high process rate in the intelligent automotive tasks and resource-constrained on-board processors. Fortunately, vehicular edge computing (VEC) has been proposed to meet the pressing resource demands. Due to the de

Taiwo Kolajo, Olawande Daramola, Ayodele Adebiyi, Seth Aaditeshwar

Most of the previous studies on the semantic analysis of social media feeds have not considered the issue of ambiguity that is associated with slangs, abbreviations, and acronyms that are embedded in social media posts. These noisy terms have implicit meanings and form part of the rich semantic context that must be analysed to gain complete insights from soc

Izaskun Jimenez-Serra, Alejandro Baez-Rubio, Jesus Martin-Pintado, Qizhou Zhang

Theories of massive star formation predict that massive protostars accrete gas through circumstellar disks. Although several cases have been found already thanks to high-angular resolution interferometry, it remains unknown the internal physical structure of these disks and, in particular, whether they present warps or internal holes as observed in low-mass

Shih-Ying Hsu, Sheng-Yuan Liu, Tie Liu, Dipen Sahu

We report the detection of four new hot corino sources, G211.47-19.27S, G208.68-19.20N1, G210.49-19.79W and G192.12-11.10 from a survey study of Planck Galactic Cold Clumps in the Orion Molecular Cloud Complex with the Atacama Compact Array (ACA). Three sources had been identified as low mass Class 0 protostars in the Herschel Orion Protostar Survey (HOPS).

W. J. Szajnowski

It is shown that a random binary process with impulse-like autocorrelation can be generated by randomizing the length of symbols occurring in a random Bernoulli process. Such randomization is achieved by random (or judiciously designed irregular) sampling of the output of a source that supplies a symmetric random binary waveform. One practical configuration

Vincent E. Sacksteder

Research on high-$T_c$ superconductors has generally not focused on analysis of the topological structure of electronic bands in these materials. In this article we collate and discuss several well-known experimental observables that signal that certain signatures of topology may be present. The topological signatures suggested by experiment include dimensio

Yanran Wang, Takashi Hikihara

Clustering formation has been observed in many organisms in Nature. It has the desirable properties for designing energy efficient protocols for Wireless Senor Networks (WSNs). In this paper, we present a new approach for energy efficient WSNs protocol which investigate how cluster formation of sensors response to external time-invariant energy potential. In

Dmitry Badziahin, Jeffrey Shallit

We give an optimal version of the classical ``three-gap theorem&#39;&#39; on the fractional parts of $n θ$, in the case where $θ$ is an irrational number that is badly approximable. As a consequence, we deduce a version of Kronecker&#39;s inhomogeneous approximation theorem in one dimension for badly approximable numbers. We apply these results to obtain an