January 2022 arXiv papers — page 117

Raphaël Lévy, Marcin Pęski, Nicolas Vieille

We consider social learning in a changing world. Society can remain responsive to state changes only if agents regularly act upon fresh information, which limits the value of social learning. When the state is close to persistent, a consensus whereby most agents choose the same action typically emerges. The consensus action is not perfectly correlated with t

Thomas Anderson, Adam Belay, Mosharaf Chowdhury, Asaf Cidon

The end of Dennard scaling and the slowing of Moore's Law has put the energy use of datacenters on an unsustainable path. Datacenters are already a significant fraction of worldwide electricity use, with application demand scaling at a rapid rate. We argue that substantial reductions in the carbon intensity of datacenter computing are possible with a sof

Md. Mahadi Hasan Sany, Mumenunnesa Keya, Sharun Akter Khushbu, Akm Shahariar Azad Rabby

The global world is crossing a pandemic situation where this is a catastrophic outbreak of Respiratory Syndrome recognized as COVID-19. This is a global threat all over the 212 countries that people every day meet with mighty situations. On the contrary, thousands of infected people live rich in mountains. Mental health is also affected by this worldwide cor

Sylvain Lannebère, David E. Fernandes, Tiago A. Morgado, Mário G. Silveirinha

Here, inspired by the operation of conventional semiconductor transistors, we introduce a novel class of bulk materials with nonreciprocal and non-Hermitian electromagnetic response. Our analysis shows that material nonlinearities combined with a static electric bias may lead to a linearized permittivity tensor that lacks the Hermitian and transpose symmetri

José Bonet, José Bonet

People unequivocally employ reviews to decide on purchasing an item or an experience on the internet. In that regard, the growing significance and number of opinions have led to the development of methods to assess their sentiment content automatically. However, it is not straightforward for the models to create a consensus value that embodies the agreement

Mengjing Wang, Aakash Kumar, Hao Dong, John M. Woods

The Weyl semimetal WTe$_{2}$ has shown several correlated electronic behaviors, such as the quantum spin Hall effect, superconductivity, ferroelectricity, and a possible exciton insulator state, all of which can be tuned by various physical and chemical approaches. Here, we discover a new electronic phase in WTe$_{2}$ induced by lithium intercalation. The ne

Winston Heap

Conditionally on the Riemann hypothesis we prove asymptotic formulae for mean values of various long Dirichlet polynomials involving the von Mangoldt function. Our results avoid the use of correlation sum estimates although in addition to the Riemann hypothesis we must assume that our Dirichlet polynomials have weights from a specific class whose transforms

Poonam Parhar, Ryan Sawasaki, Alberto Todeschini, Colorado Reed

With the effects of global climate change impacting the world, collective efforts are needed to reduce greenhouse gas emissions. The energy sector is the single largest contributor to climate change and many efforts are focused on reducing dependence on carbon-emitting power plants and moving to renewable energy sources, such as solar power. A comprehensive

A Andrasi, J C Taylor

Quantization of gauge fields by the BRST method requires sources in addition to fields, and a bilinear anti-bracket defined in terms of them. This bracket is a sort of generalization of a Poisson bracket in classical mechanics. Canonical transformations are also generalized as anti-canonical transformations. In this paper, we take the analogy with classical

Yuan Gao, Jean-Michel Roquejoffre

The nonequilibrium process in dislocation dynamics and its relaxation to the metastable transition profile is crucial for understanding the plastic deformation caused by line defects in materials. In this paper, we consider the full dynamics of a scalar dislocation model in two dimensions described by the bulk diffusion equation coupled with dynamic boundary

Ralf Hielscher, Tuomo Nyyssönen, Frank Niessen, Azdiar A. Gazder

The variant graph is a new, hybrid algorithm that combines the strengths of established global grain graph and local neighbor level voting approaches, while alleviating their shortcomings, to reconstruct parent grains from orientation maps of partially or fully phase-transformed microstructures. The variant graph algorithm is versatile and is capable of reco

Fábio Felix Dias, Moacir Antonelli Ponti, Rosane Minghim

This technical report details changes applied to a noise filter to facilitate its application and improve its results. The filter is applied to denoise natural sounds recorded in the wild and to generate an acoustic index used in soundscape analysis.

Aidyn Aitzhan, Arash G. Nouri, Peyman Givi, Hessam Babaee

The performance of the dynamically bi-orthogonal (DBO) decomposition for the reduced order modeling of turbulence-chemistry interactions is assessed. DBO is an on-the-fly low-rank approximation technique, in which the instantaneous composition matrix of the reactive flow field is decomposed into a set of orthonormal spatial modes, a set of orthonormal vector

Rafael M. Fernandes, Amalia I. Coldea, Hong Ding, Ian R. Fisher

Superconductivity is a remarkably widespread phenomenon observed in most metals cooled down to very low temperatures. The ubiquity of such conventional superconductors, and the wide range of associated critical temperatures, is readily understood in terms of the celebrated Bardeen-Cooper-Schrieffer (BCS) theory. Occasionally, however, unconventional supercon

Mirajul Islam, Nushrat Jahan Ria, Jannatul Ferdous Ani, Abu Kaisar Mohammad Masum

A deep learning model gives an incredible result for image processing by studying from the trained dataset. Spinach is a leaf vegetable that contains vitamins and nutrients. In our research, a Deep learning method has been used that can automatically identify spinach and this method has a dataset of a total of five species of spinach that contains 3785 image

Jayesh M Goyal, Nikole K Lewis, Hannah R Wakeford, Ryan J MacDonald

Thermal emission has now been observed from many dozens of exoplanet atmospheres, opening the gateway to population-level characterization. Here, we provide theoretical explanations for observed trends in $\textit{Spitzer}$ IRAC channel 1 (3.6 $μm$) and channel 2 (4.5 $μm$) photometric eclipse depths (EDs) across a population of 34 hot Jupiters. We apply pla

Théo Lacombe

This work studies how the introduction of the entropic regularization term in unbalanced Optimal Transport (OT) models may alter their homogeneity with respect to the input measures. We observe that in common settings (including balanced OT and unbalanced OT with Kullback-Leibler divergence to the marginals), although the optimal transport cost itself is not

S. Rostami, T. Vazifehshenas, T. Salavati-fard

We theoretically study the Coulomb drag resistivity and plasmon modes behavior for a system composed of two parallel p-type doped GaS monolayers with Mexican-hat valence energy band using the Boltzmann transport theory formalism. We investigate the effect of temperature,$\ T$, carrier density,$\ p$, and layer separation,$\ d$, on the plasmon modes and drag r

Ronald Mooiweer, Ian A. Clark, Eleanor A. Maguire, Martina F. Callaghan

Purpose: Universal Pulses (UPs) are excitation pulses that reduce the flip angle inhomogeneity in high field MRI systems without subject-specific optimization, originally developed for parallel transmit (PTX) systems at 7T. We investigated the potential benefits of UPs for single channel (SC) transmit systems at 3T, which are widely used for clinical and res

Jana N. Guenther

In recent years there has been much progress on the investigation of the QCD phase diagram with lattice QCD. This talk will focus on the developments in the last few years. Especially the addition of external influences and extended ranges of $T$ and $μ$ yield an increasing number of interesting results, a subset of which will be discussed. Many of these con

Li-Li Li, Fu-Hu Liu, Muhammad Waqas, Muhammad Ajaz

We analyzed the transverse momentum spectra of positively and negatively charged pions ($π^+$ and $π^-$), positively and negatively charged kaons ($K^+$ and $K^-$), protons and antiprotons ($p$ and $\bar p$), as well as $ϕ$ produced in mid-(pseudo)rapidity region in central nucleus--nucleus (AA) collisions over a center-of-mass energy range from 2.16 to 2760

A. Faure, P. Hily-Blant, C. Rist, G. Pineau des Forêts

The nuclear-spin chemistry of interstellar water is investigated using the University of Grenoble Alpes Astrochemical Network (UGAN). This network includes reactions involving the different nuclear-spin states of the hydrides of carbon, nitrogen, oxygen and sulphur, as well as their deuterated forms. Nuclear-spin selection rules are implemented within the sc

Richard J. Licata, Piyush M. Mehta

Machine learning (ML) has often been applied to space weather (SW) problems in recent years. SW originates from solar perturbations and is comprised of the resulting complex variations they cause within the systems between the Sun and Earth. These systems are tightly coupled and not well understood. This creates a need for skillful models with knowledge abou

Omar Khadir

In this work, we present a new simple way to encode/decode messages transmitted via a noisy channel and protected against errors by the Hamming method. We also propose a fast and efficient algorithm for the encoding and the decoding process which do not use neither the generator matrix nor the parity-check matrix of the Hamming code.

Cleison Correia de Amorim, Cleber Zanchettin

Sign language is an essential resource enabling access to communication and proper socioemotional development for individuals suffering from disabling hearing loss. As this population is expected to reach 700 million by 2050, the importance of the language becomes even more essential as it plays a critical role to ensure the inclusion of such individuals in

Yiftach Dayan

We study the collection of microsets of randomly constructed fractals, which in this paper, are referred to as Galton-Watson fractals. This is a model that generalizes Mandelbrot percolation, where Galton-Watson trees (whose offspring distribution is not necessarily binomial) are projected to $\mathbb{R}^d$ by a coding map which arises from an iterated funct

Bohdan M. Pavlyshenko

The article describes the use of deep Q-learning models in the problems of sales time series analytics. In contrast to supervised machine learning which is a kind of passive learning using historical data, Q-learning is a kind of active learning with goal to maximize a reward by optimal sequence of actions. Model free Q-learning approach for optimal pricing

Kristóf Bérczi, Matthias Mnich, Roland Vincze

A fundamental variant of the classical traveling salesman problem (TSP) is the so-called multiple TSP (mTSP), where a set of $m$ salesmen jointly visit all cities from a set of $n$ cities. The mTSP models many important real-life applications, in particular for vehicle routing problems. An extensive survey by Bektas (Omega 34(3), 2006) lists a variety of heu

Pierre Le Jeune, Anissa Mokraoui

Few-Shot Object Detection (FSOD) is a rapidly growing field in computer vision. It consists in finding all occurrences of a given set of classes with only a few annotated examples for each class. Numerous methods have been proposed to address this challenge and most of them are based on attention mechanisms. However, the great variety of classic object detec

Madita Willsch, Dennis Willsch, Kristel Michielsen

Quantum computing is a new emerging computer technology. Current quantum computing devices are at a development stage where they are gradually becoming suitable for small real-world applications. This lecture is devoted to the practical aspects of programming such quantum computing devices. The first part of these lecture notes focuses on programming gate-ba

Bohdan M. Pavlyshenko

The article describes the approaches for forming different predictive features of tweet data sets and using them in the predictive analysis for decision-making support. The graph theory as well as frequent itemsets and association rules theory is used for forming and retrieving different features from these datasests. The use of these approaches makes it pos

Mikhail G. Katz, Karl Kuhlemann, David Sherry, Monica Ugaglia

We examine some recent scholarship on Leibniz's philosophy of the infinitesimal calculus. We indicate difficulties that arise in articles by Bassler, Knobloch, and Arthur, due to a denial to Leibniz's infinitesimals of the status of mathematical entities violating Euclid V Definition 4.

Xuan-Huy Pham, Mazen Alamir, François Bonne

This paper explores some variations of a hierarchical control framework that has been recently proposed. The framework is dedicated to control a network of interconnected subsystems such as the ones describing cryogenic processes or power plants. Recent investigations showed that handling constraints and nonlinearities might challenge the real-time feasibili

Daniel Lehmann

A non-commutative, non-associative weakening of Girard's linear logic is developed for multiplicative and additive connectives. Additional assumptions capture the logic of quantic measurements.

N. Deily Nazar, T. Vazifehshenas, M. R. Ebrahimi, F. M. Peeters

Using first-principle many-body perturbation theory, we investigate the optical properties of 8- borophene at two levels of approximations; the GW method considering only the electron-electron interaction and the GW in combination with the Bethe-Salpeter equation including electron-hole coupling. The band structure exhibits anisotropic Dirac cones with semim

Ezequiel Smucler, Andrea Rotnitzky

We study the selection of adjustment sets for estimating the interventional mean under an individualized treatment rule. We assume a non-parametric causal graphical model with, possibly, hidden variables and at least one adjustment set comprised of observable variables. Moreover, we assume that observable variables have positive costs associated with them. W

V. Arvind Rameshwar, Navin Kashyap

This paper considers the input-constrained binary memoryless symmetric (BMS) channel, without feedback. The channel input sequence respects the $(d,\infty)$-runlength limited (RLL) constraint, which mandates that any pair of successive $1$s be separated by at least $d$ $0$s. We consider the problem of designing explicit codes for such channels. In particular

Bohdan M. Pavlyshenko

The paper describes the use of Bayesian regression for building time series models and stacking different predictive models for time series. Using Bayesian regression for time series modeling with nonlinear trend was analyzed. This approach makes it possible to estimate an uncertainty of time series prediction and calculate value at risk characteristics. A h

James Cadman, Cassandra Hall, Clémence Fontanive, Ken Rice

Observations of systems hosting close in ($<1$ AU) giant planets and brown dwarfs ($M\gtrsim7$ M$_{\rm Jup}$) find an excess of binary star companions, indicating that stellar multiplicity may play an important role in their formation. There is now increasing evidence that some of these objects may have formed via fragmentation in gravitationally unstable di

Damião J. Araújo, Rafayel Teymurazyan

Under a sharp asymptotic growth condition at infinity, we prove a Liouville type theorem for the inhomogeneous porous medium equation, provided it stays universally close to the heat equation. Additionally, for the homogeneous equation, we show that for the conclusion to hold, it is enough to assume the sharp asymptotic growth at infinity only in the space v

Maximilian Harl, Marvin Herchenbach, Sven Kruschel, Nico Hambauer

In recent years, large pre-trained deep neural networks (DNNs) have revolutionized the field of computer vision (CV). Although these DNNs have been shown to be very well suited for general image recognition tasks, application in industry is often precluded for three reasons: 1) large pre-trained DNNs are built on hundreds of millions of parameters, making de

M. Bogoya, S. E. Ekström, S. Serra-Capizzano

Under appropriate technical assumptions, the simple-loop theory allows to deduce various types of asymptotic expansions for the eigenvalues of Toeplitz matrices generated by a function $f$. Independently and under the milder hypothesis that $f$ is even and monotonic over $[0,π]$, matrix-less algorithms have been developed for the fast eigenvalue computation

Mahyar T. Moghaddam, Henry Muccini, Julie Dugdale, Mikkel Baun Kjærgaard

The Internet of Behaviors (IoB) puts human behavior at the core of engineering intelligent connected systems. IoB links the digital world to human behavior to establish human-driven design, development, and adaptation processes. This paper defines the novel concept by an IoB model based on a collective effort interacting with software engineers, human-comput

Girmaw Abebe Tadesse, William Ogallo, Catherine Wanjiru, Charles Wachira

Anomalous pattern detection aims to identify instances where deviation from normalcy is evident, and is widely applicable across domains. Multiple anomalous detection techniques have been proposed in the state of the art. However, there is a common lack of a principled and scalable feature selection method for efficient discovery. Existing feature selection

Zoya Dyka, Dan Kreiser, Ievgen Kabin, Peter Langendoerfer

In this paper we describe our flexible ECDSA design for elliptic curve over binary extended fields GF(2l). We investigated its resistance against Horizontal Collision Correlation Attacks (HCCA). Due to the fact that our design is based on the Montgomery kP algorithm using Lopez-Dahab projective coordinates the scalar k cannot be successful revealed using HCC

François Golse

These lectures notes are aimed at introducing the reader to some recent mathematical tools and results for the mean-field limit in statistical dynamics. As a warm-up, lecture 1 reviews the approach to the mean-field limit in classical mechanics following the ideas of W. Braun, K. Hepp and R.L. Dobrushin, based on the notions of phase space empirical measures

Vito Napolitano, Olga Polverino, Paolo Santonastaso, Ferdinando Zullo

This paper aims to study linear sets of minimum size in the projective line, that is $\mathbb{F}_q$-linear sets of rank $k$ in $\mathrm{PG}(1,q^n)$ admitting one point of weight one and having size $q^{k-1}+1$. Examples of these linear sets have been found by Lunardon and the second author (2000) and, more recently, by Jena and Van de Voorde (2021). However,

Mehrdad Kiamari, Bhaskar Krishnamachari, Muhammad Naveed, Seokgu Yun

We present Blizzard, a Byzantine Fault Tolerant (BFT) distributed ledger protocol that is aimed at making mobile devices first-class citizens in the consensus process. Blizzard introduces a novel two-tier architecture by having the mobile nodes communicate through online brokers, and includes a decentralized matching scheme to ensure each node connects to a

Laetitia Vincent, Elham M. T. Fadaly, Charles Renard, Wouter H. J. Peeters

The hexagonal-2H crystal phase of Ge recently emerged as a promising direct bandgap semiconductor in the mid-infrared range providing new prospects of additional optoelectronic functionalities of group-IV semiconductors (Ge and SiGe). The controlled synthesis of such hexagonal (2H) Ge phase is a challenge that can be overcome by using wurtzite GaAs nanowires

Tung Minh Phung, Jan Cloos

This work presents our approach to train a neural network to detect hate-speech texts in Hindi and Bengali. We also explore how transfer learning can be applied to learning these languages, given that they have the same origin and thus, are similar to some extend. Even though the whole experiment was conducted with low computational power, the obtained resul

Cong Ma, Wubin Wang, Xiaokun Zhao, Li Yu

Fully Field Programmable Gate Array (FPGA)based digitizer for high-resolution time and energy measurement is an attractive low cost solution for the readout electronics in positron emission computed tomography (PET)detector. In recent years, the FPGA based time-digital converter (FPGA-TDC) has been widely used for time measurement in the commercial PET scann

Nyaura Mwinyi Kibinda, Xiaohu Ge

The user-centric cooperative transmission provides a compelling way to alleviate frequent handovers caused by an ever-increasing number of randomly deployed base stations (BSs) in ultra-dense networks (UDNs). This paper proposes a new user-centric cooperative transmissions-based handover scheme, i.e., the group-cell handover (GCHO) scheme, with the aim of re

Minghui Xu, Zongrui Zou, Ye Cheng, Qin Hu

Decentralized learning involves training machine learning models over remote mobile devices, edge servers, or cloud servers while keeping data localized. Even though many studies have shown the feasibility of preserving privacy, enhancing training performance or introducing Byzantine resilience, but none of them simultaneously considers all of them. Therefor

Jieke Shi, Zhou Yang, Junda He, Bowen Xu

Statistical language models on source code have successfully assisted software engineering tasks. However, developers can create or pick arbitrary identifiers when writing source code. Freely chosen identifiers lead to the notorious out-of-vocabulary (OOV) problem that negatively affects model performance. Recently, Karampatsis et al. showed that using the B

Kohei Hayashi

We study equilibrium fluctuations for a class of totally asymmetric zero-range type interacting particle systems. As a main result, we show that density fluctuation of our process converges to the stationary energy solution of the stochastic Burgers equation. As a special case, microscopic system we consider here is related to $q$-totally asymmetric simple e

Emine Şeyma Kutluk

We use a trick similar to Weinberg&#39;s for adiabatic modes, in a Manton approximation for general relativity on manifolds with spatial boundary. This results in a description of the slow-time dependent solutions as null geodesics on the space of boundary diffeomorphisms, with respect to a metric we prove to be composed solely of the boundary data. We show

Lu Yang, Lingqiao Liu, Yunlong Wang, Peng Wang

Deep learning-based person Re-IDentification (ReID) often requires a large amount of training data to achieve good performance. Thus it appears that collecting more training data from diverse environments tends to improve the ReID performance. This paper re-examines this common belief and makes a somehow surprising observation: using more samples, i.e., trai

Dylan Zwick

This paper proves that when the $r \times r$ minors of an $m \times n$ matrix of indeterminates are not a tropical basis then the tropical prevariety has greater dimension than the tropical variety. It proves the same for the $r \times r$ minors of an $n \times n$ symmetric matrix of indeterminates when r > 4.

Matan Ostrovsky, Clark Barrett, Guy Katz

Convolutional neural networks have gained vast popularity due to their excellent performance in the fields of computer vision, image processing, and others. Unfortunately, it is now well known that convolutional networks often produce erroneous results - for example, minor perturbations of the inputs of these networks can result in severe classification erro

Laura Ketzer, Katja Poppenhaeger

We develop PLATYPOS (PLAneTarY PhOtoevaporation Simulator), a python code to perform planetary photoevaporative mass-loss calculations for close-in planets with hydrogen-helium envelopes atop Earth-like rocky cores. With physical and model parameters as input, PLATYPOS calculates the atmospheric mass loss and with it the radius evolution of a planet over tim

Chen Chen, Zhe Chen, Jing Zhang, Dacheng Tao

Although point-based networks are demonstrated to be accurate for 3D point cloud modeling, they are still falling behind their voxel-based competitors in 3D detection. We observe that the prevailing set abstraction design for down-sampling points may maintain too much unimportant background information that can affect feature learning for detecting objects.

Dongsheng Li, Xuemei Li, Kai Zhang

In this paper, a new method is represented to investigate boundary $W^{2,p}$ estimates for elliptic equations, which is, roughly speaking, to derive boundary $W^{2,p}$ estimates from interior $W^{2,p}$ estimates by Whitney decomposition. Using it, $W^{2,p}$ estimates on $C^{1,α}$ domains are obtained for nondivergence form linear elliptic equations and furth

Faheem Ullah, Imaduddin Mohammed, M. Ali Babar

Distributed data processing platforms (e.g., Hadoop, Spark, and Flink) are widely used to distribute the storage and processing of data among computing nodes of a cloud. The centralization of cloud resources has given birth to edge computing, which enables the processing of data closer to the data source instead of sending it to the cloud. However, due to re

Aditya Kumar Singh, B. Uma Shankar

Acquiring information on large areas on the earth&#39;s surface through satellite cameras allows us to see much more than we can see while standing on the ground. This assists us in detecting and monitoring the physical characteristics of an area like land-use patterns, atmospheric conditions, forest cover, and many unlisted aspects. The obtained images not

Ziqin Chen, Shu Liang

In this paper, we focus on an aggregative optimization problem under the communication bottleneck. The aggregative optimization is to minimize the sum of local cost functions. Each cost function depends on not only local state variables but also the sum of functions of global state variables. The goal is to solve the aggregative optimization problem through

Cong Ma, Xiaokun Zhao, Size Gao, Fengping Zhang

A PET scanner based on silicon photomultipliers (SiPMs) has been widely used as an advanced nuclear medicine imaging technique that yields quantitative images of regional in vivo biology and biochemistry. The compact size of the SiPM allows direct one to one coupling between the scintillation crystal and the photosensor, yielding better timing and energy res

Claudio Pisani

Given a fibration in groupoids d : D -> I, we define a fibered multicategory as a particular functor p : M -> I, where M has the same objects as D, and its arrows a : X -> Y should be thought of as families of arrows in the multicategory, indexed by pY. The key axiom extends the reindexing of objects, given by d, to a reindexing of arrows in M along pullback

Tian-Zhi Wang, Wen-Biao Liu

Thermal chaos under spatially/temporally periodic perturbations in the extended phase space of Bardeen-AdS black holes surrounded by quintessence dark energy is investigated. The occurring condition of chaos is obtained with the Melnikov integral. It is shown that spatial chaos is always supposed to occur even for a tiny spatially periodic perturbation impos

Toru Nishimura, Masakiyo Kitazawa, Teiji Kunihiro

We compute the modification of the photon self-energy due to dynamical diquark fluctuations developed near the critical temperature of the color superconductivity through the Aslamasov-Larkin, Maki-Thompson and density of states terms, which are responsible for the paraconductivity in metals at vanishing energy and momentum. It is shown that the rate has a s

Rana Shahout, Roy Friedman, Ran Ben Basat

Stream monitoring is fundamental in many data stream applications, such as financial data trackers, security, anomaly detection, and load balancing. In that respect, quantiles are of particular interest, as they often capture the user&#39;s utility. For example, if a video connection has high tail latency, the perceived quality will suffer, even if the avera

H. Abedi, S. Capozziello, M. Capriolo, A. M. Abbassi

We derive the gravitational energy-momentum pseudo-tensor $τ^μ_{\phantomμν}$ in both Palatini and metric approaches to $f(R)$ gravity. We then obtain the related cosmological gravitational energy density. Considering a flat Friedmann-Lemaître-Robertson-Walker spacetime, the energy density complex of matter and gravitation vanishes in the metric approach, but

A Pascal, J Novak, M Oertel

We perform simulations of the Kelvin-Helmholtz cooling phase of proto-neutron stars with a new numerical code in spherical symmetry and using the quasi-static approximation. We use for the first time the full set of charged-current neutrino-nucleon reactions, including neutron decay and modified Urca processes, together with the energy-dependent numerical re

Mikhail Moshkov

In this paper, we study arbitrary regular factorial languages over a finite alphabet $Σ$. For the set of words $L(n)$ of the length $n$ belonging to a regular factorial language $L$, we investigate the depth of decision trees solving the recognition and the membership problems deterministically and nondeterministically. In the case of recognition problem, fo

Alain Durmus, Éric Moulines

While the Metropolis Adjusted Langevin Algorithm (MALA) is a popular and widely used Markov chain Monte Carlo method, very few papers derive conditions that ensure its convergence. In particular, to the authors&#39; knowledge, assumptions that are both easy to verify and guarantee geometric convergence, are still missing. In this work, we establish $V$-unifo

Faheem Ullah, Shagun Dhingra, Xiaoyu Xia, M. Ali Babar

Distributed data processing frameworks (e.g., Hadoop, Spark, and Flink) are widely used to distribute data among computing nodes of a cloud. Recently, there have been increasing efforts aimed at evaluating the performance of distributed data processing frameworks hosted in private and public clouds. However, there is a paucity of research on evaluating the p

I. Breslavetz, A. Delhomme, T. Pelini, A. Pawbake

We present an experimental set-up developed to perform optical spectroscopy experiments (Raman scattering and photoluminescence measurements) with a micrometer spatial resolution, in an extreme environment of low temperature, high magnetic field and high pressure. This unique experimental setup, to the best of our knowledge, allows us to explore deeply the p

Rohan Narayan Rajmohan, Ahmed Kenawy, David DiVincenzo

Quantum circuit theory has emerged as an essential tool for the study of the dynamics of superconducting circuits. Recently, the problem of accounting for time-dependent driving via external magnetic fields was addressed by Riwar-DiVincenzo in their paper - &#39;Circuit quantization with time-dependent magnetic fields for realistic geometries&#39; in which t

Marcello Poletti

According to Aristotle &#34;time is the number of change with respect to the before and after&#34;. That&#39;s certainly a vague concept, but at the same time it&#39;s both simple and satisfying from a philosophical point of view: things do not change along time, but they do change and the measurement of such changes is what we call time. This deprives time

Jaydip Sen, Sidra Mehtab, Rajdeep Sen, Abhishek Dutta

Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding. In tune with the increasing importance and relevance of machine learning models, algorithms, and their applicat

Azam Imomov

Consider the continuous-time Markov Branching Process. In critical case we consider a situation when the generating function of intensity of transformation of particles has the infinite second moment, but its tail regularly varies in sense of Karamata. First we discuss limit properties of transition functions of the process. We prove local limit theorems and

Kento Yamamoto

In this paper, we define p-adic étale Tate twists for a modulus pair (X,D), where X is a regular semi-stable family and D is an effective Cartier divisor on X which is flat over a base scheme. The main result of this paper is an arithmetic duality of p-adic étale Tate twists for proper modulus pairs (X,D), which holds as a pro-system with respect to the mult

Dongnan Liu, Chaoyi Zhang, Yang Song, Heng Huang

Recent advances in unsupervised domain adaptation (UDA) techniques have witnessed great success in cross-domain computer vision tasks, enhancing the generalization ability of data-driven deep learning architectures by bridging the domain distribution gaps. For the UDA-based cross-domain object detection methods, the majority of them alleviate the domain bias

Hao Jiang, Calvin Murdock, Vamsi Krishna Ithapu

Augmented reality devices have the potential to enhance human perception and enable other assistive functionalities in complex conversational environments. Effectively capturing the audio-visual context necessary for understanding these social interactions first requires detecting and localizing the voice activities of the device wearer and the surrounding p

Mahmoud S. Fayed

Networks exist all around on the planet, and inside the brain of every living organism. On the city streets we see transport networks, inside homes and organizations we see water piping networks. And in the digital information age we see the rise of the computer networks and the mobile networks and their upgrade from generation to generation. We need network

Pengkai Zhu, Zhaowei Cai, Yuanjun Xiong, Zhuowen Tu

We present Contrastive Neighborhood Alignment (CNA), a manifold learning approach to maintain the topology of learned features whereby data points that are mapped to nearby representations by the source (teacher) model are also mapped to neighbors by the target (student) model. The target model aims to mimic the local structure of the source representation s

Zhaoyang Wang, Ping Lin

In this paper, a nonlinear system of fractional ordinary differential equations with multiple scales in time is investigated. We are interested in the effective long-term computation of the solution. The main challenge is how to obtain the solution of the coupled problem at a lower computational cost. We analysize a multiscale method for the nonlinear system

Paul May, Hossein Moradi Rekabdarkolaee

Dimension reduction is an important tool for analyzing high-dimensional data. The predictor envelope is a method of dimension reduction for regression that assumes certain linear combinations of the predictors are immaterial to the regression. The method can result in substantial gains in estimation efficiency and prediction accuracy over traditional maximum

Haodong Zhu, Junyu Xia, Yi Huang, Minglong Li

We fabricate two kinds of 100% fill factor compound eye structures using direct laser writing, including conventional compound eyes (CVCEs) with the same focal length of each microlens unit, and specially designed confocal compound eyes (CFCEs). For CFCEs, the focal length of each microlens unit is determined by its position and is equal to the distance betw

Cai-Yun Ma, Yu-Feng Wu

We prove that for all $s\in(0,d)$ and $c\in (0,1)$ there exists a self-similar set $E\subset \mathbb{R}^d$ with Hausdorff dimension $s$ such that $\mathcal{H}^s(E)=c|E|^s$. This answers a question raised by Zhiying Wen[16].

Samer Houri, Motoki Asano, Hajime Okamoto, Hiroshi Yamaguchi

This work presents a frequency multiplexed 3-limit cycles network in a multimode microelectromechanical nonlinear resonator. The network is composed of libration limit cycles and behaves in an analogous manner to a phase oscillator network. The libration limit cycles, being of low frequency, interact through the stress tuning of the resonator, and result in

Tsubasa Ichikawa

We present a bibliometric analysis of the research papers on quantum computation and quantum algorithms published in 1985-2020. We identify three distinct periods from the trend of the annual number of published papers, and show the 20 top contributing countries in each period in terms of the number of publications and the number of total citations. The bibl

Zipei Zhuang

For a connected cobordism S between two knots K1,K2 in S3, we establish an inequality involving the number of local maxima, the genus of S, and the torsion orders of Kht(K1),Kht(K2), where Kht denotes Lee&#39;s perturbation of Khovanov homology. This shows that the torsion order gives a lower bound for the band-unlinking number.

Thad A. Gleason, Eric L. Peters, John A. Evans

We introduce a new hybridized discontinuous Galerkin method for the incompressible magnetohydrodynamics equations. If particular velocity, pressure, magnetic field, and magnetic pressure spaces are employed for both element and trace solution fields, we arrive at an energy stable method which returns pointwise divergence-free velocity fields and magnetic fie

Atul Singh Arora, Alexandru Gheorghiu, Uttam Singh

An important theoretical problem in the study of quantum computation, that is also practically relevant in the context of near-term quantum devices, is to understand the computational power of hybrid models, that combine poly-time classical computation with short-depth quantum computation. Here, we consider two such models: CQ_d which captures the scenario o

David F. Rentería-Estrada, Roger J. Hernández-Pinto, German F. R. Sborlini

Parton distribution functions are crucial to understand the internal kinematics of hadrons. There are currently a large number of distribution functions on the market, and thanks to today&#39;s technology, performing computational analysis of the differential cross-sections has become more accessible. Despite technological advances, accurately accessing to t

Weili Wang, Chengchao Liang, Qianbin Chen, Lun Tang

As the network slicing is one of the critical enablers in communication networks, one anomalous physical node (PN) or physical link (PL) in substrate networks that carries multiple virtual network elements can cause significant performance degradation of multiple network slices. To recover the substrate networks from anomaly within a short time, rapid and ac

Yevgeniy Kovchegov, Guochen Xu, Ilya Zaliapin

Invariant Galton-Watson (IGW) tree measures is a one-parameter family of critical Galton-Watson measures invariant with respect to a large class of tree reduction operations. Such operations include the generalized dynamical pruning (also known as hereditary reduction in a real tree setting) that eliminates descendant subtrees according to the value of an ar

Yoshihiko Okamoto, Tomoya Kanematsu, Yuki Kubota, Takeshi Yajima

Sintered samples of a spinel oxide LiFeCr4O8, where Cr3+ and Fe3+ ions have localized moments, were found to show a large magnetic-field-induced volume increase approaching 500 ppm by applying a magnetic field of 9 T. This large volume increase appeared only at around 30 K. At 30 K, a spin-reorientation transition from ferrimagnetic to conical order occurs,

Haley Adams, Holly Gagnon, Sarah Creem-Regehr, Jeanine Stefanucci

The information provided to a person&#39;s visual system by extended reality (XR) displays is not a veridical match to the information provided by the real world. Due in part to graphical limitations in XR head-mounted displays (HMDs), which vary by device, our perception of space may be altered. However, we do not yet know which properties of virtual object

Huanfei Zheng, Jonathon M. Smereka, Dariusz Mikulski, Stephanie Roth

Multi-robot bounding overwatch requires timely coordination of robot team members. Symbolic motion planning (SMP) can provide provably correct solutions for robot motion planning with high-level temporal logic task requirements. This paper aims to develop a framework for safe and reliable SMP of multi-robot systems (MRS) to satisfy complex bounding overwatch