December 2020 arXiv papers — page 64

M. Hamed Mohammady

A thermally isolated quantum system undergoes unitary evolution by interacting with an external work source. The two-point energy measurement (TPM) protocol defines the work exchanged between the system and the work source by performing ideal energy measurements on the system before, and after, the unitary evolution. However, the ideal energy measurements us

Oliver Sheridan-Methven, Michael Giles

For random variables produced through the inverse transform method, approximate random variables are introduced, which are produced by approximations to a distribution's inverse cumulative distribution function. These approximations are designed to be computationally inexpensive, and much cheaper than exact library functions, and thus highly suitable for use

Praveen Kumar Maroju, Cesare Grazioli, Michele Di Fraia, Matteo Moioli

Attosecond pulses are fundamental for the investigation of valence and core-electron dynamics on their natural timescale. At present the reproducible generation and characterisation of attosecond waveforms has been demonstrated only through the process of high-order harmonic generation. Several methods for the shaping of attosecond waveforms have been propos

Jørgen Bang-Jensen, Thomas Schweser, Michael Stiebitz

Let $D$ be a digraph, let $p \geq 1$ be an integer, and let $f: V(D) \to \mathbb{N}_0^p$ be a vector function with $f=(f_1,f_2,\ldots,f_p)$. We say that $D$ has an $f$-partition if there is a partition $(D_1,D_2,\ldots,D_p)$ into induced subdigraphs of $D$ such that for all $i \in [1,p]$, the digraph $D_i$ is weakly $f_i$-degenerate, that is, in every non-em

Cynthia Shen, Mario Krenn, Sagi Eppel, Alan Aspuru-Guzik

Computer-based de-novo design of functional molecules is one of the most prominent challenges in cheminformatics today. As a result, generative and evolutionary inverse designs from the field of artificial intelligence have emerged at a rapid pace, with aims to optimize molecules for a particular chemical property. These models 'indirectly' explore the chemi

Arshia Momeni, Justinas Rumbutis, Andrew J. Tolley

We consider a broad class of massive four dimensional effective theories describing an infinite tower of charged massive spin 1 states, interacting with massless spin 1 and spin 0. The spectrum is chosen to be the same as that appears in the Kaluza-Klein theory reduction of 5d Yang-Mills to ensure the absence of any spurious poles in a possible double copy f

Wenliang Li

We present a factorized decomposition of 4-point scalar conformal blocks near the lightcone, which applies to arbitrary intermediate spin and general spacetime dimensions. Then we discuss the systematic expansion in large intermediate spin and the resummations of the large-spin tails of Regge trajectories. The basic integrals for the Lorentzian inversion are

E. Plachy, A. Pál, A. Bódi, P. Szabó

We present the first analysis of Cepheid stars observed by the TESS space mission in Sectors 1 to 5. Our sample consists of 25 pulsators: ten fundamental mode, three overtone and two double-mode classical Cepheids, plus three Type II and seven anomalous Cepheids. The targets were chosen from fields with different stellar densities, both from the Galactic fie

Harshit Rampal, Aman Mohanty

Modern Neural Networks are eminent in achieving state of the art performance on tasks under Computer Vision, Natural Language Processing and related verticals. However, they are notorious for their voracious memory and compute appetite which further obstructs their deployment on resource limited edge devices. In order to achieve edge deployment, researchers

Ahsan Al Zaki Khan, Gursel Serpen

In this paper, we present a study that proposes a three-stage classifier model which employs a machine learning algorithm to develop an intrusion detection and identification system for tens of different types of attacks against industrial SCADA networks. The machine learning classifier is trained and tested on the data generated using the laboratory prototy

Jisuke Kubo, Jeffrey Kuntz, Manfred Lindner, Jonas Rezacek

In the quest for unification of the Standard Model with gravity, classical scale invariance can be utilized to dynamically generate the Planck mass $M_\mathrm{Pl}$. Then, the relation of Planck scale physics to the scale of electroweak symmetry breaking $\mu_H$ requires further explanation. In this paper, we propose a model that uses the spontaneous breaking

Lóránt Farkas

An asynchronous multiple access error exponent result implicates a new result for time invariant trellis codes of memory 1.

Kyrylo Bondarenko, Alexey Boyarsky, Marco Nikolic, Josef Pradler

When the Dark Matter mass is below the eV-scale, its cosmological occupation number exceeds the ones of photons from the cosmic microwave background as well as of relic neutrinos. If such Dark Matter decays to pairs of neutrinos, it implies that experiments that seek the detection of the cosmic neutrino background may as well be sensitive to this additional

Jonas Rohnke, Tom Merritt, Jaime Lorenzo-Trueba, Adam Gabrys

Recently the state-of-the-art text-to-speech synthesis systems have shifted to a two-model approach: a sequence-to-sequence model to predict a representation of speech (typically mel-spectrograms), followed by a 'neural vocoder' model which produces the time-domain speech waveform from this intermediate speech representation. This approach is capable of synt

Manuel López-Radcenco, Jean-Marc Delouis, Laurent Vibert

In the present work, we propose a neural network based data inversion approach to reduce structured contamination sources, with a particular focus on the mapmaking for Planck High Frequency Instrument (Planck-HFI) data and the removal of large-scale systematic effects within the produced sky maps. The removal of contamination sources is rendered possible by

William Cerny, Wendy L. Freedman, Barry F. Madore, Finian Ashmead

Using high precision ground-based photometry for 46 low-reddening Galactic globular clusters, in conjunction with Gaia DR2 proper motions for member star selection, we have calibrated the zero point of the tip of the red giant branch (TRGB) method at two optical ($VI$) and three near-infrared ($JHK$) wavelengths. In doing so, we utilized the sharply-defined

Xuanhong Chen, Kairui Feng, Naiyuan Liu, Bingbing Ni

AI-for-science approaches have been applied to solve scientific problems (e.g., nuclear fusion, ecology, genomics, meteorology) and have achieved highly promising results. Spatial precipitation downscaling is one of the most important meteorological problem and urgently requires the participation of AI. However, the lack of a well-organized and annotated lar

Vijay Prakash Dwivedi, Xavier Bresson

We propose a generalization of transformer neural network architecture for arbitrary graphs. The original transformer was designed for Natural Language Processing (NLP), which operates on fully connected graphs representing all connections between the words in a sequence. Such architecture does not leverage the graph connectivity inductive bias, and can perf

Thomas Appelquist, James Ingoldby, Maurizio Piai

We analyze a composite Higgs model based on the confining $SU(3)$ gauge theory with $N_f = 8$ Dirac fermions in the fundamental representation. This gauge theory has been studied on the lattice and shown to be well described by a dilaton effective field theory (EFT). Here we modify the EFT by assigning standard-model quantum numbers such that four of the com

Mourad Choulli

We study some hybrid inverse problems associated to BVP's for Schr\"odinger and Helmholtz type equations. The inverse problems we consider consist in the determination of coefficients from the knowledge of internal energies. We establish local Lipschitz stability inequalities as well as conditional H\"older stability inequalities.

Jens Lundell, Enric Corona, Tran Nguyen Le, Francesco Verdoja

While there exists many methods for manipulating rigid objects with parallel-jaw grippers, grasping with multi-finger robotic hands remains a quite unexplored research topic. Reasoning and planning collision-free trajectories on the additional degrees of freedom of several fingers represents an important challenge that, so far, involves computationally costl

S. N. Fedotkin, A. G. Magner, U. V. Grygoriev

Equation of state with quantum statistics corrections is derived for a multi-component gas of particles interacting through the repulsive and attractive van der Waals (vdW) forces up to first few orders over a small parameter $\delta \approx \hbar^3 n(mT)^{-3/2}[g(1- bn)]^{-1}$, where $n$ and $T$ are the particle number density and temperature, $m$ and $g$ t

Gursel Serpen, Zhenning Gao

This paper presents an approach for low-cost simulation modeling for application development for wireless sensor networks. Computational complexity of simulating wireless sensor networks can be very high and as such must be carefully managed. Application-level code prototyping with reasonable accuracy and fidelity can be accomplished through simulation that

Yuki Matsuoka, Yasuya Nakayama, Toshihisa Kajiwara

We investigate previously unclarified effects of fluid elasticity on shear-thickening in dilute suspensions in an Oldroyd-B viscoelastic fluid using a novel direct numerical simulation based on the smoothed profile method. Fluid elasticity is determined by the Weissenberg number Wi and by viscosity ratio $1-\beta=\eta_p/(\eta_s+\eta_p)$ which measures the co

Jan Moser

In this paper new classes of $L_2$-orthogonal functions are constructed as iterated $L_2$-orthogonal systems. In order to do this we use the theory of the Riemann's zeta-function as well as our theory of Jacob's ladders. The main result is new one in the theory of the Riemann's zeta-function and simultaneously in the theory of $L_2$-orthogonal systems.

Yuanbin Jin, Jiangwei Yan, Shah Jee Rahman, Jie Li

We report an experimental observation of a record-breaking ultra-high rotation frequency about 6 GHz in an optically levitated nanoparticle system. We optically trap a nanoparticle in the gravity direction with a high numerical aperture (NA) objective lens, which shows significant advantages in compensating the influences of the scattering force and the phot

Sanja Štajner, Seren Yenikent, Marc Franco-Salvador

When two people pay attention to each other and are interested in what the other has to say or write, they almost instantly adapt their writing/speaking style to match the other. For a successful interaction with a user, chatbots and dialogue systems should be able to do the same. We propose a framework consisting of five psycholinguistic textual characteris

Daniel Steffensen, Morten H. Christensen, Brian M. Andersen, Panagiotis Kotetes

We present a detailed investigation of the topological phases and Majorana fermion (MF) excitations that arise from the bulk interplay between (un)conventional one/two-band spin-singlet superconductivity and a number of magnetic texture crystals. The latter define inhomogeneous magnetization profiles which consist of a periodically-repeating primitive cell.

Alexey Mints

We present estimates of distances, ages and masses for over 6 million stars. These estimates are derived from the combination of spectrophotometric data and Gaia eDR3 parallaxes. For that, we used the previously published Unified tool to estimate Distances, Ages, and Masses (UniDAM).

Akshay Shetty, Grace Xingxin Gao

Trajectory planning under uncertainty is an active research topic. Previous works predict state and state estimation uncertainties along trajectories to check for collision safety. They assume either stochastic or bounded sensing uncertainties. However, GNSS pseudoranges are typically modeled to contain stochastic uncertainties with additional biases in urba

Meng-Hao Guo, Jun-Xiong Cai, Zheng-Ning Liu, Tai-Jiang Mu

The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Transformer(PCT) for point cloud learning. PCT is based on Transformer, which achieves huge success in natural language processing and displays great potential in image processing. It

Piet Lammers

The interest is in models of integer-valued height functions on shift-invariant planar graphs whose maximum degree is three. We prove delocalisation for models induced by convex nearest-neighbour potentials, under the condition that each potential function is an excited potential, that is, a convex symmetric potential function $V$ with the property that $V(\

Nauros Romim, Mosahed Ahmed, Hriteshwar Talukder, Md Saiful Islam

Social media sites such as YouTube and Facebook have become an integral part of everyone's life and in the last few years, hate speech in the social media comment section has increased rapidly. Detection of hate speech on social media websites faces a variety of challenges including small imbalanced data sets, the findings of an appropriate model and also th

Simone Ciani, Sunra Mosconi, Vincenzo Vespri

We prove a Harnack inequality for positive solutions of a parabolic equation with slow anisotropic spatial diffusion. After identifying its natural scalings, we reduce the problem to a Fokker-Planck equation and construct a self-similar Barenblatt solution. We exploit translation invariance to obtain positivity near the origin via a self-iteration method and

Stephan Wong, Sang Soon Oh

Topological edge modes, which are robust against disorders, have been used to enhance the spatial stability of lasers. Recently, it was revealed that topological lasers can be further stabilized using a novel topological phase in non-Hermitian photonic topological insulators. Here we propose a procedure to realize topologically protected modes extended over

Manuela Sisti, Francesco Finelli, Giorgio Pedrazzi, Matteo Faganello

Kinetic turbulence in magnetized space plasmas has been extensively studied via in situ observations, numerical simulations and theoretical models. In this context, a key point concerns the formation of coherent current structures and their disruption through magnetic reconnection. We present automatic techniques aimed at detecting reconnection events in lar

D. A. Mayoh, A. D. Hillier, G. Balakrishnan, M. R. Lees

Time-reversal symmetry breaking (TRSB) with a Bardeen-Cooper-Schrieffer (BCS) -like superconductivity occurs in a small, but growing number of noncentrosymmetric (NCS) materials, although the mechanism is poorly understood. We present heat capacity, magnetization, resistivity, and muon spin resonance/relaxation ($\mu$SR) measurements on polycrystalline sampl

Elisabetta Valiante, Maritza Hernandez, Amin Barzegar, Helmut G. Katzgraber

Recently, there has been considerable interest in solving optimization problems by mapping these onto a binary representation, sparked mostly by the use of quantum annealing machines. Such binary representation is reminiscent of a discrete physical two-state system, such as the Ising model. As such, physics-inspired techniques -- commonly used in fundamental

Davide Ferrari, Angela Sara Cacciapuoti, Michele Amoretti, Marcello Caleffi

In distributed quantum computing architectures, with the network and communications functionalities provided by the Quantum Internet, remote quantum processing units (QPUs) can communicate and cooperate for executing computational tasks that single NISQ devices cannot handle by themselves. To this aim, distributed quantum computing requires a new generation

Marcel Wienöbst, Max Bannach, Maciej Liśkiewicz

Counting and uniform sampling of directed acyclic graphs (DAGs) from a Markov equivalence class are fundamental tasks in graphical causal analysis. In this paper, we show that these tasks can be performed in polynomial time, solving a long-standing open problem in this area. Our algorithms are effective and easily implementable. Experimental results show tha

Fabien Jacques

A signed graph is a simple graph with two types of edges. Switching a vertex $v$ of a signed graph corresponds to changing the type of each edge incident to $v$. A homomorphism from a signed graph $G$ to another signed graph $H$ is a mapping $\varphi: V(G) \rightarrow V(H)$ such that, after switching any number of the vertices of $G$, $\varphi$ maps every ed

Abhishek Kumar, Gerardo Ortiz, Philip Richerme, Babak Seradjeh

We introduce the concept of a Floquet gauge pump whereby a dynamically engineered Floquet Hamiltonian is employed to reveal the inherent degeneracy of the ground state in interacting systems. We demonstrate this concept in a one-dimensional XY model with periodically driven couplings and transverse field. In the high-frequency limit, we obtain the Floquet Ha

F. Batsch, P. Muggli, R. Agnello, C. C. Ahdida

We use a relativistic ionization front to provide various initial transverse wakefield amplitudes for the self-modulation of a long proton bunch in plasma. We show experimentally that, with sufficient initial amplitude ($\ge(4.1\pm0.4)$ MV/m), the phase of the modulation along the bunch is reproducible from event to event, with 3 to 7% (of 2$\pi$) rms variat

Sándor Z. Kiss, Csaba Sándor

Two infinite sets $A$ and $B$ of nonnegative integers are called additive complements if their sumset contains every nonnegative integer. In 1964, Danzer constructed infinite additive complements $A$ and $B$ with $A(x)B(x) = (1 + o(1))x$ as $x \rightarrow \infty$, where $A(x)$ and $B(x)$ denote the counting function of the sets $A$ and $B$, respectively. In

Jay Taylor

The irreducible characters of a finite reductive group are partitioned into Harish-Chandra series that are labelled by cuspidal pairs. In this note, we describe how one can algorithmically calculate those cuspidal pairs using results of Lusztig.

Ricard Durall, Avraam Chatzimichailidis, Peter Labus, Janis Keuper

Generative adversarial networks (GANs) provide state-of-the-art results in image generation. However, despite being so powerful, they still remain very challenging to train. This is in particular caused by their highly non-convex optimization space leading to a number of instabilities. Among them, mode collapse stands out as one of the most daunting ones. Th

A. de Giorgi, S. Vogl

The Kaluza-Klein (KK) decomposition of higher-dimensional gravity gives rise to a tower of KK-gravitons in the effective four-dimensional (4D) theory. Such massive spin-2 fields are known to be connected with unitarity issues and easily lead to a breakdown of the effective theory well below the naive scale of the interaction. However, the breakdown of the ef

A. P. Saiko, R. Fedaruk, S. A. Markevich

In the framework of the nonsecular perturbation theory based on the Bogoliubov averaging method, an optomechanical system with an asymmetric anharmonic mechanical resonator is studied. The cross-Kerr interaction and the Kerr-like self-interaction of photons and vibration quanta arise in the Hamiltonian. These interactions are induced by both cubic and quarti

Christian Schroeder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini

Extreme precipitation events, such as violent rainfall and hail storms, routinely ravage economies and livelihoods around the developing world. Climate change further aggravates this issue. Data-driven deep learning approaches could widen the access to accurate multi-day forecasts, to mitigate against such events. However, there is currently no benchmark dat

I. L. Buchbinder, E. A. Ivanov, V. A. Ivanovskiy

We develop a novel bi-harmonic $\mathcal{N}=4$ superspace formulation of the $\mathcal{N}=4$ supersymmetric Yang-Mills theory (SYM) in four dimensions. In this approach, the $\mathcal{N}=4$ SYM superfield constraints are solved in terms of on-shell $\mathcal {N}=2$ harmonic superfields. Such an approach provides a convenient tool of constructing the manifest

Maxwell Fishman, Debdeep Jena

As recent additions to the catalog of 2D crystals, silicene and other silicene-class crystals have numerous unique properties currently being investigated and considered for use in novel device applications. In this paper, we investigate electronic and transport properties of silicene in a field effect transistor geometry. We find that the Berry curvature of

Sadique Adnan Siddiqui, Axel Vierling, Karsten Berns

This paper addresses the problem of dense depth predictions from sparse distance sensor data and a single camera image on challenging weather conditions. This work explores the significance of different sensor modalities such as camera, Radar, and Lidar for estimating depth by applying Deep Learning approaches. Although Lidar has higher depth-sensing abiliti

Luka Daoud, Muhammad Kamran Latif, H S. Jacinto, Nader Rafla

The scale invariant feature transform (SIFT) algorithm is considered a classical feature extraction algorithm within the field of computer vision. SIFT keypoint descriptor matching is a computationally intensive process due to the amount of data consumed. In this work, we designed a novel fully pipelined hardware accelerator architecture for SIFT keypoint de

Gaetano Campi, Antonio Valletta, Andrea Perali, Augusto Marcelli

So far most of the analysis of coronavirus 2020 epidemic data has been focusing on a short-time window and consequently a quantitative test of statistical physical laws of Coronavirus Epidemics with Containment Measures (CEwCM) is currently lacking. Here we report a quantitative analysis of CEwCM over 230 days, covering the full-time lapse of the first epide

T. J. Boyle, M. Walker, A. Ruiz, E. Schierle

The La-based '214' cuprates host several symmetry breaking phases including superconductivity, charge and spin order in the form of stripes, and a structural othorhombic-to-tetragonal phase transition. Therefore, these materials are an ideal system to study the effects of uniaxial stress onto the various correlations that pervade the cuprate phase diagram. W

N. Bethencourt de León, G. Chachamis, A. Sabio Vera

The 13 TeV run of the LHC has provided a unique opportunity to explore multi-jet final states with unprecedented accuracy. An interesting region for study is that of events where one jet is tagged in the forward direction and another one in the backward direction and a plethora of low energy mini-jets populate the possibly large rapidity span in between them

Sabah Al-Fedaghi

This study introduces another application of software engineering tools, conceptual modeling, which can be applied to other fields of research. One way to strengthen the relationship between software engineering and other fields is to develop a good way to perform conceptual modeling that is capable of addressing the peculiarities of these fields of study. T

Simon Martiel, Timothée Goubault de Brugière

Qubit routing is a key problematic related to quantum circuit compilation. It consists in rewriting a quantum circuit by adding the least possible number of instructions to make the circuit compliant with some architecture's connectivity constraints. Usually, this problem is tackled via either SWAP insertion techniques or re-synthesis of portions of the circ

Alexander Egiazarov, Fabio Massimo Zennaro, Vasileios Mavroeidis

Threat detection of weapons and aggressive behavior from live video can be used for rapid detection and prevention of potentially deadly incidents such as terrorism, general criminal offences, or even domestic violence. One way for achieving this is through the use of artificial intelligence and, in particular, machine learning for image analysis. In this pa

Runhuan Feng, Pingping Jiang, Hans Volkmer

The joint distribution of a geometric Brownian motion and its time-integral was derived in a seminal paper by Yor (1992) using Lamperti's transformation, leading to explicit solutions in terms of modified Bessel functions. In this paper, we revisit this classic result using the simple Laplace transform approach in connection to the Heun differential equation

Giuseppe de Vito, Lapo Turrini, Caroline Müllenbroich, Pietro Ricci

Light-sheet fluorescence microscopy (LSFM) enables real-time whole-brain functional imaging in zebrafish larvae. Conventional one photon LSFM can however induce undesirable visual stimulation due to the use of visible excitation light. The use of two-photon (2P) excitation, employing near-infrared invisible light, provides unbiased investigation of neuronal

Francisco Cuevas-Pacheco, Jean-François Coeurjolly, Marie-Hélène Descary

Estimating the first-order intensity function in point pattern analysis is an important problem, and it has been approached so far from different perspectives: parametrically, semiparametrically or nonparametrically. Our approach is close to a semiparametric one. Motivated by eye-movement data, we introduce a convolution type model where the log-intensity is

Sanchari Bhattacharyyaa, Shimon Bershtein, Bharat V. Adkara, Jaie Woodarda

The relationship between sequence variation and phenotype is poorly understood. Here we use metabolomic analysis to elucidate the molecular mechanism underlying the filamentous phenotype of E. coli strains that carry destabilizing mutations in the Dihydrofolate Reductase (DHFR). We find that partial loss of DHFR activity causes SOS response indicative of DNA

Junsik Bae, Junho Choi, Bongsuk Kwon

We study the formation of singularity for the Euler-Poisson system equipped with the Boltzmann relation, which describes the dynamics of ions in an electrostatic plasma. In general, it is known that smooth solutions to nonlinear hyperbolic equations fail to exist globally in time. We establish criteria for $C^1$ blow-up of the Euler-Poisson system, both for

Adrian Pacheco-Pozo, Igor M. Sokolov

We discuss large deviation properties of continuous-time random walks (CTRW) and present a general expression for the large deviation rate in CTRW in terms of the corresponding rates for the distributions of steps' lengths and waiting times. In the case of Gaussian distribution of steps' lengths the general expression reduces to a sequence of two Legendre tr

A. Alimi, S. Deslauriers-Gauthier, F. Matuschke, A. Müller

Three dimensional Polarized Light Imaging (3D-PLI) is an optical technique which allows mapping the spatial fiber architecture of fibrous postmortem tissues, at sub-millimeter resolutions. Here, we propose an analytical and fast approach to compute the fiber orientation distribution (FOD) from high-resolution vector data provided by 3D-PLI. The FOD is modele

Saba Dadsetan, Gisele Rose, Naira Hovakimyan, Jennifer Hobbs

Early, precise detection of nutrient deficiency stress (NDS) has key economic as well as environmental impact; precision application of chemicals in place of blanket application reduces operational costs for the growers while reducing the amount of chemicals which may enter the environment unnecessarily. Furthermore, earlier treatment reduces the amount of l

Rohan Pramanick, Swarup Sangiri, Utpal Sarkar

A generalized connection between the quantum mechanical Bargmann invariants and the geometric phases was established for the Dirac fermions. We extend that formalism for the Majorana fermions by defining proper quantum mechanical ray and Hilbert spaces. We then relate both the Dirac and Majorana type Bargmann invariants to the rephasing invariant measures of

Pierre Schapira

We introduce the category of b-analytic manifolds, a natural tool to define constructible sheaves and functions up to infinity. We study with some details the operations on these objects and also recall the Radon transform for constructible functions.

Conor Meade

We establish optimal $(p,q)$ ranges for two types of estimates associated to three dimensional complex polynomial curves. These are the estimates for the weighted restriction of the Fourier Transform to a complex polynomial curve, and the weighted Convolution Operator associated to a complex polynomial curve. Establishing these estimates comes down to establ

Thibault Formal, Benjamin Piwowarski, Stéphane Clinchant

Transformer-based models are nowadays state-of-the-art in ad-hoc Information Retrieval, but their behavior is far from being understood. Recent work has claimed that BERT does not satisfy the classical IR axioms. However, we propose to dissect the matching process of ColBERT, through the analysis of term importance and exact/soft matching patterns. Even if t

Lede Xian, Ammon Fischer, Martin Claassen, Jin Zhang

We demonstrate that the concept of moir\'e flat bands can be generalized to achieve electronic band engineering in all three spatial dimensions. For many two dimensional van der Waals materials, twisting two adjacent layers with respect to each other leads to flat electronic bands in the two corresponding spatial directions -- a notion sometimes referred to

Alexander Glauner

In the classical static optimal reinsurance problem, the cost of capital for the insurer's risk exposure determined by a monetary risk measure is minimized over the class of reinsurance treaties represented by increasing Lipschitz retained loss functions. In this paper, we consider a dynamic extension of this reinsurance problem in discrete time which can be

Tian Lan, Xian-Ling Mao, Xiaoyan Gao, Wei Wei

We study the coarse-grained selection module in retrieval-based chatbot. Coarse-grained selection is a basic module in a retrieval-based chatbot, which constructs a rough candidate set from the whole database to speed up the interaction with customers. So far, there are two kinds of approaches for coarse-grained selection module: (1) sparse representation; (

Alberto Parravicini, Arnaud Delamare, Marco Arnaboldi, Marco D. Santambrogio

GPUs are readily available in cloud computing and personal devices, but their use for data processing acceleration has been slowed down by their limited integration with common programming languages such as Python or Java. Moreover, using GPUs to their full capabilities requires expert knowledge of asynchronous programming. In this work, we present a novel G

Ngai-Fung Ng, Sai-Kee Yeung

The goal of the paper is to study the limiting behavior of the Weierstrass measures on a smooth curve of genus $g\geqslant 2$ as the curve approaches a certain nodal stable curve represented by a point in the Deligne-Mumford compactification $\bar{\mathcal M}_g$ of the moduli $\mathcal{M}_g$, including irreducible ones or those of compact type. As a conseque

Nazanin Fouladgar, Kary Främling

In this work, we report the practical and theoretical aspects of Explainable AI (XAI) identified in some fundamental literature. Although there is a vast body of work on representing the XAI backgrounds, most of the corpuses pinpoint a discrete direction of thoughts. Providing insights into literature in practice and theory concurrently is still a gap in thi

Jean-Louis Clerc, Khalid Koufany

Let $\mathbb S$ be a Clifford module for the complexified Clifford algebra $\mathbb{C}\ell(\mathbb R^n)$, $\mathbb S'$ its dual, $\rho$ and $\rho'$ be the corresponding representations of the spin group ${\rm Spin}(n)$. The group $G= {\rm Spin}(1,n+1)$ is a (twofold) covering of the conformal group of $\mathbb R^n$. For $\lambda, \mu\in \mathbb C$, let $\pi_

Emma S. Simpson, Jennifer L. Wadsworth, Jonathan A. Tawn

Vine copulas are a type of multivariate dependence model, composed of a collection of bivariate copulas that are combined according to a specific underlying graphical structure. Their flexibility and practicality in moderate and high dimensions have contributed to the popularity of vine copulas, but relatively little attention has been paid to their extremal

David Mitrouskas

We analyze the ground state energy for N fermions in a two-dimensional box interacting with an impurity particle via two-body point interactions. We allow for mass ratios M > 1.225 between the impurity mass and the mass of a fermion and consider arbitrarily large box sizes while keeping the Fermi energy fixed. Our main result shows that the ground state ener

David Arnas, Richard Linares

This work introduces the use of the Koopman operator theory to generate approximate analytical solutions for the zonal harmonics problem of a satellite orbiting a non-spherical celestial body. Particularly, the solution proposed directly provides the osculating evolution of the system under the effects of any order of the zonal harmonics, and can be automate

Takashi Komatsu, Norio Konno, Iwao Sato

We define a correlated random walk (CRW) induced from the time evolution matrix (the Grover matrix) of the Grover walk on a graph $G$, and present a formula for the characteristic polynomial of the transition probability matrix of this CRW by using a determinant expression for the generalized weighted zeta function of $G$. As applications, we give the spectr

L. Maunoury, O. Kamalou, J. F. Cam, S. Damoy

The SPIRAL1 charge breeder is now under operation. Radioactive beam has already been delivered [1] to Physicist for performing experiment. Although charge breeding efficiencies demonstrated high performances for stable ion beams, those efficiencies regarding radioactive ion beams were found, in the first experiments, lower than expected. The beam optics, pri

Pádraig MacCarron, Paul J. Maher, Michael Quayle

A survey can be represented by a bipartite network as it has two types of nodes, participants and items in which participants can only interact with items. We introduce an agreement threshold to take a minimal projection of the participants linked by shared responses in order to identify opinion-based groups. We show that in American National Election Studie

Mafalda Jotta Garcia, Julien Moulin, Steffen Wittrock, Sumito Tsunegi

Performance of magnetoresistive sensors is today mainly limited by their 1/f low-frequency noise. Here, we study this noise component in vortex-based TMR sensors. We compare the noise level in different magnetization configurations of the device, i.e vortex state or uniform parallel or antiparallel states. We find that the vortex state is at least an order o

Pavel S. Prudnikov

Paul Chernoff in 1968 proposed his approach to approximations of one-parameter operator semigroups while trying to give a rigorous mathematical meaning to Feynman's path integral formulation of quantum mechanics. In early 2000's Oleg Smolyanov noticed that Chernoff's theorem may be used to obtain approximations to solutions of initial-value problems for line

Nicolas Martinet, Tiago Castro, Joachim Harnois-Déraps, Eric Jullo

NonGaussian cosmic shear statistics based on weak-lensing aperture mass ($M_{\rm ap}$) maps can outperform the classical shear two-point correlation function ($\gamma$-2PCF) in terms of cosmological constraining power. However, reaching the full potential of these new estimators requires accurate modeling of the physics of baryons as the extra nonGaussian in

Ayush Bharti, Francois-Xavier Briol, Troels Pedersen

Calibrating stochastic radio channel models to new measurement data is challenging when the likelihood function is intractable. The standard approach to this problem involves sophisticated algorithms for extraction and clustering of multipath components, following which, point estimates of the model parameters can be obtained using specialized estimators. We

Thiago de Paiva

The twisted torus knots K(p, q; r, s) are obtained by performing a sequence of s full twists on r adjacent strands of (p, q)-torus knots. Morimoto asked whether all twisted torus knots with essential tori in the exterior fit into one of two families. We prove that the answer to this question is no, by finding two different new families of toroidal twisted to

Owen G. Ward, Jing Wu, Tian Zheng, Anna L. Smith

Group-based social dominance hierarchies are of essential interest in animal behavior research. Studies often record aggressive interactions observed over time, and models that can capture such dynamic hierarchy are therefore crucial. Traditional ranking methods summarize interactions across time, using only aggregate counts. Instead, we take advantage of th

Anh Truong, Austin Walters, Jeremy Goodsitt

Named Entity Recognition has been extensively investigated in many fields. However, the application of sensitive entity detection for production systems in financial institutions has not been well explored due to the lack of publicly available, labeled datasets. In this paper, we use internal and synthetic datasets to evaluate various methods of detecting NP

M. H. Al-Hashimi, U. -J. Wiese

For a particle in a box, the operator $- i \partial_x$ is not Hermitean. We provide an alternative construction of a momentum operator $p = p_R + i p_I$, which has a Hermitean component $p_R$ that can be extended to a self-adjoint operator, as well as an anti-Hermitean component $i p_I$. This leads to a description of momentum measurements performed on a par

Vasilis Krokos, Viet Bui Xuan, Stéphane P. A. Bordas, Philippe Young

Multiscale computational modelling is challenging due to the high computational cost of direct numerical simulation by finite elements. To address this issue, concurrent multiscale methods use the solution of cheaper macroscale surrogates as boundary conditions to microscale sliding windows. The microscale problems remain a numerically challenging operation

Christin Bobe, Johannes Keller, Ellen Van De Vijver

For many geophysical measurements, such as direct current or electromagnetic induction methods, information fades away with depth. This has to be taken into account when interpreting models estimated from such measurements. For that reason, a measurement sensitivity analysis and determining the depth of investigation are standard steps during geophysical dat

Brendan Keith

A number of non-standard finite element methods have been proposed in recent years, each of which derives from a specific class of PDE-constrained norm minimization problems. The most notable examples are $\mathcal{L}\mathcal{L}^*$ methods. In this work, we argue that all high-order methods in this class should be expected to deliver substandard uniform h-re

Chaoqing Tang

Authentication and encryption are traditionally treated as two separate processes in wireless networks, this paper integrates user authentication into the process of solving eavesdropping attacks. A compressed sensing (CS)-based framework is proposed which manipulates the measurement matrix of CS to safeguard secure computationally. The framework is also cap

D. Spérone-Longin, P. Jablonka, F. Combes, G. Castignani

We investigate how the galaxy reservoirs of molecular gas fuelling star formation are transformed while the host galaxies infall onto galaxy cluster cores. As part of the Spatially Extended ESO Distant Cluster Survey (SEEDisCS), we present CO(3-2) observations of 27 star-forming galaxies obtained with the Atacama Large Millimeter Array (ALMA). These sources

Matthew Steinberg, Javier Prior

Hyperinvariant tensor networks (hyMERA) were introduced as a way to combine the successes of perfect tensor networks (HaPPY) and the multiscale entanglement renormalization ansatz (MERA) in simulations of the AdS/CFT correspondence. Although this new class of tensor network shows much potential for simulating conformal field theories arising from hyperbolic

Pascal Pernot, Andreas Savin

The distribution of errors is a central object in the assesment and benchmarking of computational chemistry methods. The popular and often blind use of the mean unsigned error as a benchmarking statistic leads to ignore distributions features that impact the reliability of the tested methods. We explore how the Gini coefficient offers a global representation

Michael Buballa, Lennart Kurth, Marc Wagner, Marc Winstel

The phase diagram of the Gross-Neveu model in $2+1$ space-time dimensions at non-zero temperature and chemical potential is studied in the limit of infinitely many flavors, focusing on the possible existence of inhomogeneous phases, where the order parameter $\sigma$ is non-uniform in space. To this end, we analyze the stability of the energetically favored