October 2020 arXiv papers — page 39

Uyen Le, Dmitry E. Pelinovsky, Pascal Poullet

Dynamics of viscous shocks is considered in the modular Burgers equation, where the time evolution becomes complicated due to singularities produced by the modular nonlinearity. We prove that the viscous shocks are asymptotically stable under odd and general perturbations. For the odd perturbations, the proof relies on the reduction of the modular Burgers eq

Renato Higa, Pradeepa Premarathna, Gautam Rupak

The E1 and M1 contributions to $^7\mathrm{Be}(p,\gamma)^8\mathrm{B}$ at low energies are calculated in halo effective field theory. The excited $^7\mathrm{Be}^\star$ core is included as an explicit degree of freedom in a coupled-channels calculation. The E1 transition is calculated up to next-to-next-to-leading order. The leading contribution from M1 transit

Sam Shleifer, Alexander M. Rush

Recent state-of-the-art approaches to summarization utilize large pre-trained Transformer models. Distilling these models to smaller student models has become critically important for practical use; however there are many different distillation methods proposed by the NLP literature. Recent work on distilling BERT for classification and regression tasks show

Davis W. Muhwezi, James T. Wheeler

Biconformal gravity, based on gauging of the conformal group to 2n dimensions, reproduces n-dim scale-covariant general relativity on the co-tangent bundle in any dimension. We generalize this result to include Yang-Mills matter sources formulated as SU\left(N\right) gauge theories with a twisted action on the full 2n-dimensional biconformal space. We show t

Ihechukwu Chinyere, Bernard Oduoku Bainson

We study cyclically presented groups of type $\mathfrak{F}$ to determine when they are perfect. It turns out that to do so, it is enough to consider the Prishchepov groups, so modulo a certain conjecture, we classify the perfect Prishchepov groups $P(r,n,k,s,q)$ in terms of the defining integer parameters $r,n,k,s,q$. In particular, we obtain a classificatio

Ziyi Chen, Patrick De Causmaecker, Yajie Dou

The personnel rostering problem is the problem of finding an optimal way to assign employees to shifts, subject to a set of hard constraints which all valid solutions must follow, and a set of soft constraints which define the relative quality of valid solutions. The problem has received significant attention in the literature and is addressed by a large num

Brian Lawrence

A quadratic twist of the L-function associated with a modular form is known to satisfy a functional equation, which may be even or odd. A result due to Gross and Zagier explicitly computes the central value of the L-function or its derivative. In prime level when the functional equation is even, Michel and Ramakrishnan have used an averaging method to prove

Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji

Hierarchical SGD (H-SGD) has emerged as a new distributed SGD algorithm for multi-level communication networks. In H-SGD, before each global aggregation, workers send their updated local models to local servers for aggregations. Despite recent research efforts, the effect of local aggregation on global convergence still lacks theoretical understanding. In th

Rama Krishna Thelagathoti, Spyridon Mastorakis, Anant Shah, Harkeerat Bedi

In this work we investigate Named Data Networking's (NDN's) architectural properties and features, such as content caching and intelligent packet forwarding, in the context of a Content Delivery Network (CDN) workflows. More specifically, we evaluate NDN's properties for PoP (Point of Presence) to PoP and PoP to device connectivity. We use the Apache Traffic

Griffin Mooers, Mike Pritchard, Tom Beucler, Jordan Ott

We explore the potential of feed-forward deep neural networks (DNNs) for emulating cloud superparameterization in realistic geography, using offline fits to data from the Super Parameterized Community Atmospheric Model. To identify the network architecture of greatest skill, we formally optimize hyperparameters using ~250 trials. Our DNN explains over 70 per

Yann Pequignot, Mathieu Alain, Patrick Dallaire, Alireza Yeganehparast

It is crucial to detect when an instance lies downright too far from the training samples for the machine learning model to be trusted, a challenge known as out-of-distribution (OOD) detection. For neural networks, one approach to this task consists of learning a diversity of predictors that all can explain the training data. This information can be used to

Duncan Dauvergne, Sourav Sarkar, Bálint Virág

We show that geodesics in the directed landscape have $3/2$-variation and that weight functions along the geodesics have cubic variation. We show that the geodesic and its landscape environment around an interior point has a small-scale limit. This limit is given in terms of the directed landscape with Brownian-Bessel boundary conditions. The environments ar

Juan Cervino, Juan Andres Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro

In this paper we consider a problem known as multi-task learning, consisting of fitting a set of classifier or regression functions intended for solving different tasks. In our novel formulation, we couple the parameters of these functions, so that they learn in their task specific domains while staying close to each other. This facilitates cross-fertilizati

Florian Schanzenbächer

This thesis proposes mathematical traffic models and control laws for metro lines with one junction. The models are based on the ones developed for linear metro lines (without junction) in [12, 14]. The train dynamics are described with a discrete event traffic model. Two time constraints are considered. The first one imposes lower bounds on the train run an

Alphonse C. Sterling, Ronald L. Moore, Navdeep K. Panesar, Tanmoy Samanta

Many solar coronal jets result from erupting miniature-filament ("minifilament") magnetic flux ropes that reconnect with encountered surrounding far-reaching field. Many of those minifilament flux ropes are apparently built and triggered to erupt by magnetic flux cancelation. If that cancelation (or some other process) results in the flux rope's field having

Liyi Hsu, Fadi I. Baida, Abdoulaye Ndao

Over the last few years, optical nanoantennas are continuously attracting interest owing to their ability to efficiently confine, localize resonance, and significantly enhanced electromagnetic fields at subwavelength scale. However, such strong confinement can be further enhanced by using an appropriate combination of optical nanoantenna and Slanted Bound st

Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang

Adversarial Training is proved to be an efficient method to defend against adversarial examples, being one of the few defenses that withstand strong attacks. However, traditional defense mechanisms assume a uniform attack over the examples according to the underlying data distribution, which is apparently unrealistic as the attacker could choose to focus on

Beniamino Accattoli, Ugo Dal Lago, Gabriele Vanoni

Evaluating higher-order functional programs through abstract machines inspired by the geometry of the interaction is known to induce $\textit{space}$ efficiencies, the price being $\textit{time}$ performances often poorer than those obtainable with traditional, environment-based, abstract machines. Although families of lambda-terms for which the former is ex

John Leventides, Costas Poulios

The $3x+1$-problem (or Collatz problem) is a notorious conjecture in arithmetic. It can be viewed as iterating a map and, therefore, it is a dynamical system on the discrete space $\mathbb{N}$ of natural numbers. The emerging dynamical system is studied in the present work with methods from the theory of Koopman operators and $C^*$-algebras. This approach en

Rui Liu, Tianyi Wu, Barzan Mozafari

Adam is a widely used optimization method for training deep learning models. It computes individual adaptive learning rates for different parameters. In this paper, we propose a generalization of Adam, called Adambs, that allows us to also adapt to different training examples based on their importance in the model's convergence. To achieve this, we maintain

Luca Bombelli, B. B. Pilgrim

In this paper we will explore two different proposals for the action for causal sets: the Benincasa-Dowker action and a modified version of the chain action. We propose a variational principle for two-dimensional causal sets and use it for both actions to determine which causal sets at least on average satisfy a discrete version of the Einstein equation. Spe

Justin Y. J. Burton, Thomas Osburn

We present a new convenient framework for modeling Reissner-Nordstr\"om black hole perturbations from charged distributions of matter. Using this framework, we quantify how gravitational wave observations of compact binary systems would be affected if one or both components were charged. Our approach streamlines the (linearized) Einstein-Maxwell equations th

Ayushmaan Aggarwal, Niharika Bhattacharjee, Aadi Bhattacharya, Raka Bose

Over 30 million tons of deicing salt is applied on U.S. roads annually at a cost of roughly $1.2 billion and with significant negative environmental impact. Therefore, it is desirable to reduce salt use while maintaining winter road safety. Automatic adjustment of application rate in response to road, weather, traffic, and other conditions has the potential

J. J. P. Veerman, Tessa Whalen-Wagner, Ewan Kummel

The study of the dynamics of chemical reactions, and in particular phenomena such as oscillating reactions, has led to the recognition that many dynamical properties of a chemical reaction can be predicted from graph theoretical properties of a certain directed graph, called a Chemical Reaction Network (CRN). In this graph, the edges represent the reactions

Carlos Molina-Jimenez, Ioannis Sfyrakis, Linmao Song, Hazem Danny Al Nakib

The hype about Bitcoin has overrated the potential of smart contracts deployed on-blockchains (on-chains) and underrated the potential of smart contracts deployed on-Trusted Third Parties (on-TTPs). As a result, current research and development in this field is focused mainly on smart contract applications that use on-chain smart contracts. We argue that the

Fernanda Molina, Gustavo Betarte, Carlos Luna

Blockchain is an incipient technology that offers many strengths compared to traditional systems, such as decentralization, transparency and traceability. However, if the technology is to be used for processing personal data, complementary mechanisms must be identified that provide support for building systems that meet security and data protection requireme

Kwun Chung

Let $X$ be an elliptic curve or a ramifying hyperelliptic curve over $\mathbb F_q$. We will discuss how to factorize the coefficients of the exponential and logarithm series for a Hayes module over such a curve. This allows us to obtain $v$-adic convergence results for such exponential and logarithm series, for $v$ a 'finite' prime. As an application, we can

Huanyao Cun, Zichun Miao, Adrian Hemmi, Marcella Iannuzzi

The production of high-quality two-dimensional (2D) materials is essential for the ultimate performance of single layers and their hybrids. Hexagonal boron nitride (h-BN) is foreseen to become the key 2D hybrid and packaging material since it is insulating, tight, flat, transparent and chemically inert, though it is difficult to attain in ultimate quality. H

Srikanta Sannigrahi, Qi Zhang, Francesco Pilla, Bidroha Basu

Forest fires have a profound impact on the atmospheric environment and air quality across the ecosystems. The recent west coast forest fire in the United States of America (USA) has broken all the past records and caused severe environmental and public health burdens. As of middle September, nearly 6 million acres forest area were burned, and more than 25 ca

Linh Kästner, Samim Ahmadi, Florian Jonietz, Mathias Ziegler

Spot welding is a crucial process step in various industries. However, classification of spot welding quality is still a tedious process due to the complexity and sensitivity of the test material, which drain conventional approaches to its limits. In this paper, we propose an approach for quality inspection of spot weldings using images from laser thermograp

Bryce Chudomelka, Youngjoon Hong, Hyunwoo Kim, Jinyoung Park

Nonlinear differential equations are challenging to solve numerically and are important to understanding the dynamics of many physical systems. Deep neural networks have been applied to help alleviate the computational cost that is associated with solving these systems. We explore the performance and accuracy of various neural architectures on both linear an

Jakob J. Hollenstein, Erwan Renaudo, Matteo Saveriano, Justus Piater

Local policy search is performed by most Deep Reinforcement Learning (D-RL) methods, which increases the risk of getting trapped in a local minimum. Furthermore, the availability of a simulation model is not fully exploited in D-RL even in simulation-based training, which potentially decreases efficiency. To better exploit simulation models in policy search,

Ntokozo Sibonelo Khuzwayo, Fortuné Massamba

We investigate a class of locally conformal almost K\"ahler structures and prove that, under some conditions, this class is a subclass of almost K\"ahler structures. We show that a locally conformal almost K\"ahler manifold admits a canonical foliation whose leaves are hypersurfaces with mean curvature vector field proportional to the Lee vector field. The g

Andros Tjandra, Ruoming Pang, Yu Zhang, Shigeki Karita

We present an approach for unsupervised learning of speech representation disentangling contents and styles. Our model consists of: (1) a local encoder that captures per-frame information; (2) a global encoder that captures per-utterance information; and (3) a conditional decoder that reconstructs speech given local and global latent variables. Our experimen

Oğul Can, Yeti Z. Gürbüz, Berkin Yıldırım, A. Aydın Alatan

We propose an end-to-end learning approach to address deinterleaving of patterns in time series, in particular, radar signals. We link signal clustering problem to min-cost flow as an equivalent problem once the proper costs exist. We formulate a bi-level optimization problem involving min-cost flow as a sub-problem to learn such costs from the supervised tr

J. Jesus Aguilera-Verdugo, Roger J. Hernandez-Pinto, German Rodrigo, German F. R. Sborlini

The computation of multi-loop multi-leg scattering amplitudes plays a key role to improve the precision of theoretical predictions for particle physics at high-energy colliders. In this work, we focus on the mathematical properties of the novel integrand-level representation of Feynman integrals, which is based on the Loop-Tree Duality (LTD). We explore the

Sreyas Mohan, Ramon Manzorro, Joshua L. Vincent, Binh Tang

Denoising is a fundamental challenge in scientific imaging. Deep convolutional neural networks (CNNs) provide the current state of the art in denoising natural images, where they produce impressive results. However, their potential has barely been explored in the context of scientific imaging. Denoising CNNs are typically trained on real natural images artif

Da Wu

For parameters $n,\delta,B,C$, we obtained a sharp asymptotic formula for the number of $(n+\lfloor n^\delta\rfloor)^2$-dimensional binary contingency tables with non-uniform margins taking values of $\lfloor BCn\rfloor$ and $\lfloor Cn\rfloor$. Furthermore, we compared our sharp asymptotics with the classical independence heuristic estimate and proved that

Zijian Kuang, Xinran Tie

Video understanding is to recognize and classify different actions or activities appearing in the video. A lot of previous work, such as video captioning, has shown promising performance in producing general video understanding. However, it is still challenging to generate a fine-grained description of human actions and their interactions using state-of-the-

Dor Amran, Maayan Frid-Adar, Nimrod Sagie, Jannette Nassar

The outbreak of COVID-19 has lead to a global effort to decelerate the pandemic spread. For this purpose chest computed-tomography (CT) based screening and diagnosis of COVID-19 suspected patients is utilized, either as a support or replacement to reverse transcription-polymerase chain reaction (RT-PCR) test. In this paper, we propose a fully automated AI ba

Jorge Gamboa, Richard MacKenzie, Fernando Méndez

In the context of gravity in the strong-coupling regime, the propagation amplitude of gravity coupled to relativistic particles undergoing geodesic separation is calculated exactly. Geodesic separation gives rise to boundary terms associated with the h_\times and h_+ graviton components. At low temperatures the propagation amplitude vanishes, implying no gra

Sebastian Scherg, Thomas Kohlert, Pablo Sala, Frank Pollmann

The thermalization of isolated quantum many-body systems is deeply related to fundamental questions of quantum information theory. While integrable or many-body localized systems display non-ergodic behavior due to extensively many conserved quantities, recent theoretical studies have identified a rich variety of more exotic phenomena in between these two ex

Chin-Yi Chen, Hsin-Ying Tseng, Hesameddin Ilatikhameneh, Tarek A. Ameen

Triple heterojunction (THJ) TFETs have been proposed to resolve the low ON-current challenge of TFETs. However, the design space for THJ-TFETs is limited by fabrication challenges with respect to device dimensions and material interfaces. This work shows that the original THJ-TFET design with 12 nm body thickness has poor performance, because its sub-thresho

Christopher A. Mizzi, Laurence D. Marks

Triboelectricity has been known since antiquity, but the fundamental physics underlying this phenomenon lacks consensus. We present a flexoelectric model for triboelectricity where contact deformation induced band bending is the driving force for charge transfer. This framework is combined with first principles and finite element calculations to explore char

Emanuel A. Lazar, Amir Shoan

Perturbed lattices provide simple models for studying many physical systems. In this paper we study the distribution of Voronoi chains, blocks, and clusters with prescribed combinatorial features in the perturbed square lattice, generalizing earlier work. In particular, we obtain analytic results for the presence of hexagonally-ordered regions within a squar

T. F. Kieffer, M. Loss

The aim of this paper is to study, in dimensions 2 and 3, the pure-power non-linear Schr\"odinger equation with an external uniform magnetic field included. In particular, we derive a general criteria on the initial data and the power of the non-linearity so that the corresponding solution blows up in finite time, and we show that the time for blow up to occ

Joshua Yao-Yu Lin, Hang Yu, Warren Morningstar, Jian Peng

Dark matter substructures are interesting since they can reveal the properties of dark matter. Collisionless N-body simulations of cold dark matter show more substructures compared with the population of dwarf galaxy satellites observed in our local group. Therefore, understanding the population and property of subhalos at cosmological scale would be an inte

Jiusi Zhou, Shuping Dang, Basem Shihada, Mohamed-Slim Alouini

In this letter, we propose a power allocation scheme for relayed orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. The proposed power allocation scheme replies on artificial neural network (ANN) and deep learning to allocate transmit power among various subcarriers at the source and relay nodes. The objective of the power al

Rajdip Palit, Manoj B. Prajapati, Riddhi Shah

For a discrete group $G$ and the compact space Sub$_G$ of (closed) subgroups of $G$ endowed with the Chabauty topology, we study the dynamics of actions of automorphisms of $G$ on Sub$_G$ in terms of distality and expansivity. We also study the structure and properties of lattices $\Gamma$ in a connected Lie group. In particular, we show that the unique maxi

Guiping Zhou, Guannan Gao, Jingxiu Wang, Jun Lin

Coronal waves exist ubiquitously in the solar atmosphere. They are important not only in their own rich physics but also essential candidates of triggering magnetic eruptions in the remote. However, the later mechanism has never been directly confirmed. By revisiting the successive eruptions on 2012 March 7, fast-mode shocks are identified to account for the

Sydney N. Lavan, Adedayo M. Sanni, Aaron S. Rury, Zhen-Fei Liu

The facile synthesis and electronic properties of two-dimensional hybrid organic-inorganic perovskites (2D HOIPs) make these self-assembled systems an important class of energy materials. The basic building blocks of these materials include inorganic lattice frameworks that often consist of lead-halide octahedra and organic molecules possessing ammonium func

K. Narayan

We discuss aspects of generic 2-dimensional dilaton gravity theories. The 2-dim geometry is in general conformal to $AdS_2$ and has IR curvature singularities at zero temperature: this can be regulated by a black hole. The on-shell action is divergent: we discuss the holographic energy-momentum tensor by adding appropriate counterterms. For theories obtained

Jayakrishnan M. P. Nair, Debsuvra Mukhopadhyay, G. S. Agarwal

In the last few years, the great utility of PT-symmetric systems in sensing small perturbations has been recognized. Here, we propose an alternate method relevant to dissipative systems, especially those coupled to the vacuum of the electromagnetic fields. In such systems, which typically show anti-PT symmetry and do not require the incorporation of gain, va

Srikanth Chandar, Anish Reddy, Muvazima Mansoor, Suresh Jamadagni

In this paper, we present a novel approach to identify the Spatio-temporal and environmental features that influence the safety of a road and predict its accident proneness based on these features. A total of 14 features were compiled based on Time, Weather, and Location (TWL) specificity along a road. To determine the influence each of the 14 features carri

Ari Arapostathis, Anup Biswas, Prasun Roychowdhury

We study the generalized eigenvalue problem on the whole space for a class of integro-differential elliptic operators. The nonlocal operator is over a finite measure, but this has no particular structure. Some of our results even hold for singular kernels. The first part of the paper presents results concerning the existence of a principal eigenfunction. The

Ge Zhu, Fei Jiang, Zhiyao Duan

State-of-the-art text-independent speaker verification systems typically use cepstral features or filter bank energies as speech features. Recent studies attempted to extract speaker embeddings directly from raw waveforms and have shown competitive results. In this paper, we propose a novel multi-scale waveform encoder that uses three convolution branches wi

Paul Fassl, Vincent Lami, Felix J. Berger, Lukas M. Falk

The internal luminescence quantum efficiency ($Q_\mathrm{i}^\mathrm{lum}$) provides an excellent assessment of the optoelectronic quality of semiconductors. To determine $Q_\mathrm{i}^\mathrm{lum}$ of perovskite films from the experimentally accessible external luminescence quantum efficiency ($Q_\mathrm{e}^\mathrm{lum}$) it is essential to account for photo

J. A. Gil Granados, A. Muñoz Mateo, X. Viñas

We study the superfluid dynamics of the outer core of neutron stars by means of a hydrodynamic model made of a neutronic superfluid and a protonic superconductor, coupled by both the dynamic entrainment and the Skyrme SLy4 nucleon-nucleon interactions. The resulting nonlinear equations of motion are probed in the search for dynamical instabilities triggered

Daniel McDuff, Javier Hernandez, Erroll Wood, Xin Liu

Non-contact physiological measurement has the potential to provide low-cost, non-invasive health monitoring. However, machine vision approaches are often limited by the availability and diversity of annotated video datasets resulting in poor generalization to complex real-life conditions. To address these challenges, this work proposes the use of synthetic a

Mengjin Dong, Long Xie, Sandhitsu R. Das, Jiancong Wang

Volume change measures derived from longitudinal MRI (e.g. hippocampal atrophy) are a well-studied biomarker of disease progression in Alzheimer's Disease (AD) and are used in clinical trials to track the therapeutic efficacy of disease-modifying treatments. However, longitudinal MRI change measures can be confounded by non-biological factors, such as differ

D. O. Mora, M. Bourgoin, P. D. Mininni, M. Obligado

We analyze the vector nulls of velocity, Lagrangian acceleration, and vorticity, coming from direct numerical simulations of forced homogeneous isotropic turbulence at $Re_\lambda \in [40-610]$. We show that the clustering of velocity nulls is much stronger than those of acceleration and vorticity nulls. These acceleration and vorticity nulls, however, are d

Stefan Steinerberger

An easy consequence of Kantorovich-Rubinstein duality is the following: if $f:[0,1]^d \rightarrow \infty$ is Lipschitz and $\left\{x_1, \dots, x_N \right\} \subset [0,1]^d$, then $$ \left| \int_{[0,1]^d} f(x) dx - \frac{1}{N} \sum_{k=1}^{N}{f(x_k)} \right| \leq \left\| \nabla f \right\|_{L^{\infty}} \cdot W_1\left( \frac{1}{N} \sum_{k=1}^{N}{\delta_{x_k}} ,

Nicolaus Heuer, Clara Loeh

We show that, in dimension at least $4$, the set of locally finite simplicial volumes of oriented connected open manifolds is $[0, \infty]$. Moreover, we consider the case of tame open manifolds and some low-dimensional examples.

Dean Crnković, Doris Dumičić Danilović, Sanja Rukavina

The existence of a biplane with parameters $(121,16,2)$ is an open problem. Recently, it has been proved by Alavi, Daneshkhah and Praeger that the order of an automorphism group of a of possible biplane ${\mathcal D}$ of order $14$ divides $2^7\cdot3^2\cdot5\cdot7\cdot11\cdot13$. In this paper we show that such a biplane do not have an automorphism of order

Martin J. Neugebauer, Dominik M. Juraschek, Matteo Savoini, Pascal Engeler

In ionic Raman scattering, infrared-active phonons mediate a scattering process that results in the creation or destruction of a Raman-active phonon. This mechanism relies on nonlinear interactions between phonons and has in recent years been associated with a variety of emergent lattice-driven phenomena in complex transition-metal oxides, but the underlying

Priyamvada Jadaun, Leonard F. Register, Sanjay K. Banerjee

The spin Hall effect (SHE) is highly promising for spintronic applications, and the design of materials with large SHE can enable ultra-low power memory technology. Recently, 5d-transition metal oxides have been shown to demonstrate a large SHE. Here we report large values of SHE in four 5d-transition metal anti-perovskites which makes these anti-perovskites

Cheng Long, Xingzhou Tang, Robin L. B. Selinger, Jonathan V. Selinger

In 3D nematic liquid crystals, disclination lines have a range of geometric structures. Locally, they may resemble $+1/2$ or $-1/2$ defects in 2D nematic phases, or they may have 3D twist. Here, we analyze the structure in terms of the director deformation modes around the disclination, as well as the nematic order tensor inside the disclination core. Based

Sushant Dave, Arun Kumar Singh, Prathosh A. P., Brejesh Lall

This paper describes neural network based approaches to the process of the formation and splitting of word-compounding, respectively known as the Sandhi and Vichchhed, in Sanskrit language. Sandhi is an important idea essential to morphological analysis of Sanskrit texts. Sandhi leads to word transformations at word boundaries. The rules of Sandhi formation

Jhonny Mertz, Ingrid Nunes, Luca Della Toffola, Marija Selakovic

Application-level caching is a form of caching that has been increasingly adopted to satisfy performance and throughput requirements. The key idea is to store the results of a computation, to improve performance by reusing instead of recomputing those results. However, despite its provided gains, this form of caching imposes new design, implementation and ma

Jorge Navarro, Camilla Calì, Maria Longobardi, Fabrizio Durante

The univariate distorted distribution were introduced in risk theory to represent changes (distortions) in the expected distributions of some risks. Later they were also applied to represent distributions of order statistics, coherent systems, proportional hazard rate (PHR) and proportional reversed hazard rate (PRHR) models, etc. In this paper we extend thi

Mahdi Khojastehnia, Sergey Loyka

Several gaps and errors in [1] are identified and corrected. While accommodating these corrections, a rigours proof is given that the successive convex approximation algorithm in [1] for secrecy rate maximization (SRM) does generate an increasing and bounded sequence of true secrecy rates and hence converges. It is further shown that its convergence point is

Timur Abbasov, Konstantin Makarenko, Ivan Sherstov, Mikhail Axenov

The paper describes the results achieved in the development of the compact transportable fully automated optical clock based on a single 171Yb+ ion in a radiofrequency (RF) quadrupole trap. The resulted measurements demonstrated the 4.9E-16 output RF signal relative instability on 1000 s integration time with 298.1 kg weight, 0.921 volume, and 2.766 kW input

Arun Kumar Singh, Sushant Dave, Prathosh A. P., Brejesh Lall

This paper presents first benchmark corpus of Sanskrit Pratyaya (suffix) and inflectional words (padas) formed due to suffixes along with neural network based approaches to process the formation and splitting of inflectional words. Inflectional words spans the primary and secondary derivative nouns as the scope of current work. Pratyayas are an important dim

N. A. Ismailov, A. S. Dzhumadil'daev

An algebra is said to be a unary Leibniz algebra if every one-generated subalgebra is a Leibniz algebra. An algebra is said to be a binary Leibniz algebra if every two-generated subalgebra is a Leibniz algebra. We give characterizations of unary and binary Leibniz algebras in terms of identities.

Mohammad Bagher Heydari, Mohammad Hashem Vadjed Samiei

This article aims to study graphene-based resonators published in the literature. Graphene resonators are designed based on graphene conductivity, a variable parameter that can be changed by either electrostatic or magnetostatic gating. A historical review of plasmonic graphene resonators is presented in this paper, which can give physical insight to the res

Jia-Yuan Dai

We prove the existence of $m$-armed spiral wave solutions for the complex Ginzburg-Landau equation in the circular and spherical geometries. We establish a new global bifurcation approach and generalize the results of existence for rigidly-rotating spiral waves. Moreover, we prove the existence of two new patterns: frozen spirals in the circular and spherica

Jaymin Suhagiya, Deep Raval, Siddhi Vinayak Pandey, Jeet Patel

Forecasting the actual amount of electricity with respect to the need/demand of the load is always been a challenging task for each power plants based generating stations. Due to uncertain demand of electricity at receiving end of station causes several challenges such as: reduction in performance parameters of generating and receiving end stations, minimiza

Dmitry Egurnov, Dmitry I. Ignatov, Dmitry Tochilkin

In this paper, we describe versions of triclustering algorithms adapted for efficient calculations in distributed environments with MapReduce model or parallelisation mechanism provided by modern programming languages. OAC-family of triclustering algorithms shows good parallelisation capabilities due to the independent processing of triples of a triadic form

Christine Allen-Blanchette, Sushant Veer, Anirudha Majumdar, Naomi Ehrich Leonard

The dominant paradigms for video prediction rely on opaque transition models where neither the equations of motion nor the underlying physical quantities of the system are easily inferred. The equations of motion, as defined by Newton's second law, describe the time evolution of a physical system state and can therefore be applied toward the determination of

Arnaud Delaunoy, Antoine Wehenkel, Tanja Hinderer, Samaya Nissanke

Gravitational waves from compact binaries measured by the LIGO and Virgo detectors are routinely analyzed using Markov Chain Monte Carlo sampling algorithms. Because the evaluation of the likelihood function requires evaluating millions of waveform models that link between signal shapes and the source parameters, running Markov chains until convergence is ty

Ioannis Fudos, Margarita Ntousia, Vasiliki Stamati, Paschalis Charalampous

Additive manufacturing technologies are positioned to provide an unprecedented innovative transformation in how products are designed and manufactured. Due to differences in the technical specifications of AM technologies, the final fabricated parts can vary significantly from the original CAD models, therefore raising issues regarding accuracy, surface fini

Esteban Calzetta

We use a simple model consisting of energy-momentum tensor conservation and a Maxwell-Cattaneo equation for its viscous part to study nonlinear phenomena in a real relativistic fluid. We focus on new types of behavior without nonrelativistic equivalents, such as an entropy cascade driven by fluctuations in the tensor degrees of freedom of the theory. We writ

Régis de la Bretèche, Gérald Tenenbaum

Let $\varrho$ be a complex number and let $f$ be a multiplicative arithmetic function whose Dirichlet series takes the form $\zeta(s)^\varrho G(s)$, where $G$ is associated to a multiplicative function $g$. The classical Selberg-Delange method furnishes asymptotic estimates for averages of $f$ under assumptions of either analytic continuation for $G$, or abs

Guido Brückner, Vera Chekan

We investigate the problem of drawing two posets of the same ground set so that one is drawn from left to right and the other one is drawn from the bottom up. The input to this problem is a directed graph $G = (V, E)$ and two sets $X, Y$ with $X \cup Y = E$, each of which can be interpreted as a partial order of $V$. The task is to find a planar drawing of $

Jing Li, Lijuan Hu, Jing Lu, Lan Zhou

We consider two two-level systems (TLSs) coupled to the vacuum of guided modes confined in a rectangular waveguide. Two TLSs are fixed at different points in the waveguide and initially share an excitation. For the energy separation of the TLSs far away from the cutoff frequencies of transverse modes, two coupled delay-differential equations are obtained for

Onur Oktay

We numerically study the classical evolution of a Yang-Mills matrix model with two distinct mass deformation terms, which can be contemplated as a massive deformation of the bosonic part of the BFSS model. Through numerical analysis, it is shown that when the simulations are started from a certain set of initial conditions, thermalization occurs. Besides, an

Dieter Werthmüller, Raphael Rochlitz, Octavio Castillo-Reyes, Lindsey Heagy

Large-scale modelling of three-dimensional controlled-source electromagnetic (CSEM) surveys used to be feasible only for large companies and research consortia. This has changed over the last few years, and today there exists a selection of different open-source codes available to everyone. Using four different codes in the Python ecosystem, we perform simul

Dhruba Pujary, Camilo Thorne, Wilker Aziz

The detection and normalization of diseases in biomedical texts are key biomedical natural language processing tasks. Disease names need not only be identified, but also normalized or linked to clinical taxonomies describing diseases such as MeSH. In this paper we describe deep learning methods that tackle both tasks. We train and test our methods on the kno

Mark Edelman

The presence of the power-law memory is a significant feature of many natural (biological, physical, etc.) and social systems. Continuous and discrete fractional calculus is the instrument to describe the behavior of systems with the power-law memory. The existence of chaotic solutions is an intrinsic property of nonlinear dynamics (regular and fractional).

Qianqian Ma, Yang-Yu Liu, Alex Olshevsky

As a common strategy of contagious disease containment, lockdowns will inevitably weaken the economy. The ongoing COVID-19 pandemic underscores the trade-off arising from public health and economic cost. An optimal lockdown policy to resolve this trade-off is highly desired. Here we propose a mathematical framework of pandemic control through an optimal stab

Maria Katsova

We present a brief review of observational results contributing to modern ideas on the evolution of stellar activity. Basic laws, derived for both rotation-age and activity-rotation relationships, allow us to trace how the activity of low-mass stars changes with age during their stay on the main sequence. We focus on the evaluation of the activity properties

Wei He, Quanming Yao, Chao Li, Naoto Yokoya

Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) restoration, which includes the tasks of denoising, compressed HSI reconstruction and inpainting. Unfortunately, while its restoration performance benefits from more spectral bands, its runtime also substantially increases. In this paper, we

Yichen Fu, Xin Zhang, Hong Qin

We develop an Explicitly Solvable Energy-Conserving (ESEC) algorithm for the Stochastic Differential Equation (SDE) describing the pitch-angle scattering process in magnetized plasmas. The Cayley transform is used to calculate both the deterministic gyromotion and stochastic scattering, affording the algorithm to be explicitly solvable and exactly energy con

Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch

We consider the problem of using observational data to estimate the causal effects of linguistic properties. For example, does writing a complaint politely lead to a faster response time? How much will a positive product review increase sales? This paper addresses two technical challenges related to the problem before developing a practical method. First, we

Kuldeep S. Meel, Yash Pote, Sourav Chakraborty

Given a set of items $\mathcal{F}$ and a weight function $\mathtt{wt}: \mathcal{F} \mapsto (0,1)$, the problem of sampling seeks to sample an item proportional to its weight. Sampling is a fundamental problem in machine learning. The daunting computational complexity of sampling with formal guarantees leads designers to propose heuristics-based techniques fo

Zan-Xia Jin, Heran Wu, Chun Yang, Fang Zhou

Text-based visual question answering (VQA) requires to read and understand text in an image to correctly answer a given question. However, most current methods simply add optical character recognition (OCR) tokens extracted from the image into the VQA model without considering contextual information of OCR tokens and mining the relationships between OCR toke

Katelyn Gao, Ozan Sener

By searching for shared inductive biases across tasks, meta-learning promises to accelerate learning on novel tasks, but with the cost of solving a complex bilevel optimization problem. We introduce and rigorously define the trade-off between accurate modeling and optimization ease in meta-learning. At one end, classic meta-learning algorithms account for th

Alok Kumar Sinha, Saif Khan Mohammed, P. Raviteja, Yi Hong

We consider the problem of uplink timing synchronization for Orthogonal Time Frequency Space (OTFS) modulation based systems where information is embedded in the delay-Doppler (DD) domain. For this, we propose a novel Random Access (RA) preamble waveform based on OTFS modulation. We also propose a method to estimate the round-trip propagation delay between a

Xiyao Wang, Junge Zhang, Wenzhen Huang, Qiyue Yin

Model-based reinforcement learning (MBRL) is believed to have higher sample efficiency compared with model-free reinforcement learning (MFRL). However, MBRL is plagued by dynamics bottleneck dilemma. Dynamics bottleneck dilemma is the phenomenon that the performance of the algorithm falls into the local optimum instead of increasing when the interaction step

Hansjoerg Albrecher, Pierre-Olivier Goffard

Mining blocks on a blockchain equipped with a proof of work consensus protocol is well-known to be resource-consuming. A miner bears the operational cost, mainly electricity consumption and IT gear, of mining, and is compensated by a capital gain when a block is discovered. This paper aims at quantifying the profitability of mining when the possible event of