March 2020 arXiv papers — page 99

Yao Shen

Gentile statistics describes fractional statistical systems in the occupation number representation. Anyon statistics researches those systems in the winding number representation. Both of them are intermediate statistics between Bose-Einstein and Fermi-Dirac statistics. The second quantization of Gentile statistics shows a lot of advantages. According to th

Jeff Ens, Philippe Pasquier

Modelling human perception of musical similarity is critical for the evaluation of generative music systems, musicological research, and many Music Information Retrieval tasks. Although human similarity judgments are the gold standard, computational analysis is often preferable, since results are often easier to reproduce, and computational methods are much

Nora Bloise, Loredana Petecchia, Gabriele Ceccarelli, Lorenzo Fassina

Human bone marrow-derived mesenchymal stem cells (hBM-MSCs) are considered a great promise in the repair and regeneration of bone. Considerable efforts have been oriented towards uncovering the best strategy to promote stem cells osteogenic differentiation. In previous studies, hBM-MSCs exposed to physical stimuli such as pulsed electromagnetic fields (PEMFs

Oguz Yildiz

We prove that the mapping class group of a closed connected orientable surface of genus $g$ is generated by two elements of order $g$ for $g\geq 6$. Moreover, for $g\geq 7$ we found a generating set of two elements, of order $g$ and $g'$ which is the least divisor of $g$ such that $g'>2$. Furthermore, we proved that it is generated by two elements of

Zuheng Ming, Jean-Christophe Burie, Muhammad Muzzamil Luqman

Face recognition of realistic visual images has been well studied and made a significant progress in the recent decade. Unlike the realistic visual images, the face recognition of the caricatures is far from the performance of the visual images. This is largely due to the extreme non-rigid distortions of the caricatures introduced by exaggerating the facial

Kenneth Leerbeck, Peder Bacher, Rune Junker, Goran Goranović

A machine learning algorithm is developed to forecast the CO2 emission intensities in electrical power grids in the Danish bidding zone DK2, distinguishing between average and marginal emissions. The analysis was done on data set comprised of a large number (473) of explanatory variables such as power production, demand, import, weather conditions etc. colle

Thiernithi Variddhisai, Danilo Mandic

The concept of a random process has been recently extended to graph signals, whereby random graph processes are a class of multivariate stochastic processes whose coefficients are matrices with a \textit{graph-topological} structure. The system identification problem of a random graph process therefore revolves around determining its underlying topology, or

Suat Gumussoy, Wim Michiels

We design fixed-order strong H-infinity controllers for general time-delay systems. The designer chooses the controller order and may introduce constant time-delays in the controller. We represent the closed-loop system of the plant and the controller as delay differential algebraic equations (DDAEs). This representation deals with any interconnection of sys

Sindhu Kutty, Mark Guzdial

Undergraduates are unlikely to even consider graduate research in Computer Science if they do not know what Computer Science research is. Many programs aimed at introducing undergraduate to research are structured like graduate research programs, with a small number of undergraduates working with a faculty advisor. Further, females, under-represented minorit

Mirko Trisolini, Hugh G. Lewis, Camilla Colombo

The space environment around the Earth is populated by more than 130 million objects of 1 mm in size and larger, and future predictions shows that this amount is destined to increase, even if mitigation measures are implemented at a far better rate than today. These objects can hit and damage a spacecraft or its components. It is thus necessary to assess the

Jie Wu, Decao Yin, Halvor Lie, Signe Riemer-Sørensen

Slender marine structures such as deep-water riser systems are continuously exposed to currents leading to vortex-induced vibrations (VIV) of the structure. This may result in amplified drag loads and fast accumulation of fatigue damage. Consequently, accurate prediction of VIV responses is of great importance for the safe design and operation of marine rise

Shin-ichi Kurokawa, Yutaka Hamaoka, Kyo Kageura, Jun Makino

We point out serious inconsistencies of the first paper of the series, written by Makoto Miyazaki and Ryugo Hayano, which discusses the correlation between the personal doses of the citizens of Date City measured by glass badges with the ambient dose rates measured by six airborne surveys. The last of the six airborne survey was made in the period of 2014 Q3

Joe Kennedy, Lucas Lombriser

Positivity bounds provide conditions that a consistent UV-completion exists for a quantum field theory. We examine their application to Horndeski gravity models reconstructed from the effective field theory (EFT) of dark energy. This enables us to assess whether particular phenomenological parameterizations of the EFT functions reconstruct theories that resp

Nicolás P. Müller, Marc-Etienne Brachet, Alexandros Alexakis, Pablo D. Mininni

We present numerical evidence of a critical-like transition in an out-of-equilibrium mean-field description of a quantum system. By numerically solving the Gross-Pitaevskii equation we show that quantum turbulence displays an abrupt change between three-dimensional (3D) and two-dimensional (2D) behavior. The transition is observed both in quasi-2D flows in c

Lucia Cavallaro, Annamaria Ficara, Pasquale De Meo, Giacomo Fiumara

Compared to other types of social networks, criminal networks present hard challenges, due to their strong resilience to disruption, which poses severe hurdles to law-enforcement agencies. Herein, we borrow methods and tools from Social Network Analysis to (i) unveil the structure of Sicilian Mafia gangs, based on two real-world datasets, and (ii) gain insig

Qun Wang

This article investigates the dynamical behaviours of the $n$-vortex problem with vorticity $\mathbfΓ$ on a Riemann sphere $\mathbb{S}^2$ equipped with an arbitrary metric $g$. From perspectives of Riemannian geometry and symplectic geometry, we study the invariant orbits and prove that with some constraints on vorticity $\mathbfΓ$, the $n$-vortex problem po

Joe Gildea, Abidin Kaya, Rhian Taylor, Alexander Tylyshchak

In this paper, we construct self-dual codes from a construction that involves both block circulant matrices and block quadratic residue circulant matrices. We provide conditions when this construction can yield self-dual codes. We construct self-dual codes of various lengths over F2 and F2 + uF2. Using extensions, neighbours and sequences of neighbours, we c

Ramya Selvaraj, V. Swaminathan, A. Durga Devi, K. Krishnakumar

In this article, we study the generalised Kudryashov method for the time fractional generalized Burgers-Fisher equation (GBF). Using traveling wave transformation, the time fractional GBF is transformed to nonlinear ordinary differential equation (ODE). Later, in the nonlinear ODE of timefractional GBF, the generalized Kudryashov and power series method is a

Ramya Selvaraj, V. Swaminathan, A. Durga Devi, K. Krishnakumar

In this article, we study the Lie point symmetries for the time fractional generalized Burgers-Fisher (GBF) equation. While getting an appropriate combination of symmetries, the time fractional partial differential equation has been transformed to nonlinear fractional ordinary differential equations (ODE) using Erdelyi-Kober differential operator. Furthermor

Paolo Pozzi, Jonathan Mapelli

Phase-only spatial light modulators can be employed to structure laser light in complex three dimensional focusing patterns, with a variety of applications. While spatial light modulators have typical refresh frequencies of tens of Hz, the computation time of three dimensional holograms ranges between a few seconds and a few minutes, therefore limiting the u

Subhrajit Sinha, Sai Pushpak Nandanoori, Enoch Yeung

With the advancement of sensing and communication in power networks, high-frequency real-time data from a power network can be used as a resource to develop better monitoring capabilities. In this work, a systematic approach based on data-driven operator theoretic methods involving Koopman operator is proposed for the online identification of power system dy

Maryam Asadi-Aghbolaghi, Reza Azad, Mahmood Fathy, Sergio Escalera

Medical image segmentation has been very challenging due to the large variation of anatomy across different cases. Recent advances in deep learning frameworks have exhibited faster and more accurate performance in image segmentation. Among the existing networks, U-Net has been successfully applied on medical image segmentation. In this paper, we propose an e

Zaoli Chen, Gennady Samorodnitsky

We study clustering of the extremes in a stationary sequence with subexponential tails in the maximum domain of attraction of the Gumbel We obtain functional limit theorems in the space of random sup-measures and in the space $D(0,\infty)$. The limits have the Gumbel distribution if the memory is only moderately long. However, as our results demonstrate rath

Mohammad Naghashnejad, Hamidreza Shabgard

A computational fluid dynamics (CFD) model is developed to simulate the dynamics of meniscus formation and capillary flow between vertical parallel plates. The arbitrary Lagrangian-Eulerian (ALE) approach was employed to predict and reconstruct the exact shape of the meniscus. The model was used to simulate the rise of water and the evolution of the meniscus

Juergen Rathmann

We derive new bounds for the Castelnuovo-Mumford regularity of the ideal sheaf of a complex projective manifold of any dimension. They depend linearly on the coefficients of the Hilbert polynomial, and are optimal for rational scrolls, but most likely not for other varieties. Our proof is based on an observation of Lazarsfeld in his approach for surfaces and

Max Van Kleek

It's the year 2020, and every space and place on- and off-line has been augmented with digital things that observe, record, transmit, and compute, for the purposes of recording endless data traces of what is happening in the world. Individually, these things (and the invisible services the power them) have reached considerable sophistication in their abi

Max Chiswick, Sam Ganzfried

Building on recent research for prediction of hurricane trajectories using recurrent neural networks (RNNs), we have developed improved methods and generalized the approach to predict Bayesian intervals in addition to simple point estimates. Tropical storms are capable of causing severe damage, so accurately predicting their trajectories can bring significan

Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai

We propose a new method for video object segmentation (VOS) that addresses object pattern learning from unlabeled videos, unlike most existing methods which rely heavily on extensive annotated data. We introduce a unified unsupervised/weakly supervised learning framework, called MuG, that comprehensively captures intrinsic properties of VOS at multiple granu

Vít Novotný, Eniafe Festus Ayetiran, Michal Štefánik, Petr Sojka

Since the seminal work of Mikolov et al., word embeddings have become the preferred word representations for many natural language processing tasks. Document similarity measures extracted from word embeddings, such as the soft cosine measure (SCM) and the Word Mover's Distance (WMD), were reported to achieve state-of-the-art performance on semantic text

Milagros Izquierdo, Gareth A. Jones, Sebastián Reyes-Carocca

We classify compact Riemann surfaces of genus $g$, where $g-1$ is a prime $p$, which have a group of automorphisms of order $ρ(g-1)$ for some integer $ρ\ge 1$, and determine isogeny decompositions of the corresponding Jacobian varieties. This extends results of Belolipetzky and the second author for $ρ>6$, and of the first and third authors for $ρ=3, 4, 5$ a

Stewart Jamieson, Jonathan P. How, Yogesh Girdhar

We present a novel POMDP problem formulation for a robot that must autonomously decide where to go to collect new and scientifically relevant images given a limited ability to communicate with its human operator. From this formulation we derive constraints and design principles for the observation model, reward model, and communication strategy of such a rob

Timothy Duff, Kathlén Kohn, Anton Leykin, Tomas Pajdla

We present a complete classification of minimal problems for generic arrangements of points and lines in space observed partially by three calibrated perspective cameras when each line is incident to at most one point. This is a large class of interesting minimal problems that allows missing observations in images due to occlusions and missed detections. The

Alexander I Nesterov, Gennady P Berman, Manuel A Rodríguez Fernández, Xidi Wang

We propose a new type of the Unruh-DeWitt detector which measures the decoherence of the reduced density matrix of the detector interacting with the massless quantum scalar field. We find that the decoherence decay rates are different in the inertial and accelerated reference frames. We show that the exponential phase decay can be observed for relatively low

Isaac E. Weintraub, Meir Pachter, Eloy Garcia

Pursuit and evasion conflicts represent challenging problems with important applications in aerospace and robotics. In pursuit-evasion problems, synthesis of intelligent actions must consider the adversary's potential strategies. Differential game theory provides an adequate framework to analyze possible outcomes of the conflict without assuming particul

Steven N. Evans, Mehdi Ouaki

Given a two-sided real-valued Lévy process $(X_t)_{t \in \mathbb{R}}$, define processes $(L_t)_{t \in \mathbb{R}}$ and $(M_t)_{t \in \mathbb{R}}$ by $L_t := \sup\{h \in \mathbb{R} : h - α(t-s) \le X_s \text{ for all } s \le t\} = \inf\{X_s + α(t-s) : s \le t\}$, $t \in \mathbb{R}$, and $M_t := \sup \{ h \in \mathbb{R} : h - α|t-s| \leq X_s \text{ for all } s

Yan Cui, Michael Levine, Zhou Zhou

We propose a difference-based nonparametric methodology for the estimation and inference of the time-varying auto-covariance functions of a locally stationary time series when it is contaminated by a complex trend with both abrupt and smooth changes. Simultaneous confidence bands (SCB) with asymptotically correct coverage probabilities are constructed for th

Shreyank N Gowda, Chun Yuan

Minute pixel changes in an image drastically change the prediction that the deep learning model makes. One of the most significant problems that could arise due to this, for instance, is autonomous driving. Many methods have been proposed to combat this with varying amounts of success. We propose a 3 step method for defending such attacks. First, we denoise

Matteo Cinelli, Walter Quattrociocchi, Alessandro Galeazzi, Carlo Michele Valensise

We address the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab. We analyze engagement and interest in the COVID-19 topic and provide a differential assessment on the evolution of the discourse on a global scale for each platform and their users. We fit information spreading with epidemic

Jonathan H. Clark, Eunsol Choi, Michael Collins, Dan Garrette

Confidently making progress on multilingual modeling requires challenging, trustworthy evaluations. We present TyDi QA---a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs. The languages of TyDi QA are diverse with regard to their typology---the set of linguistic features each language expresses---such th

Philip Kortum, Michael D. Byrne, Julie Whitmore

The question of whether or not voters actually verify ballots produced by ballot marking devices (BMDs) is presently the subject of some controversy. Recent studies (e.g., Bernhard, et al. 2020) suggest the verification rate is low. What is not clear from previous research is whether this is more a result of voters being unable to do so accurately or whether

Xiaoyu He, Ray Li

Recently, Farnik asked whether the hat guessing number $\text{HG}(G)$ of a graph $G$ could be bounded as a function of its degeneracy $d$, and Bosek, Dudek, Farnik, Grytczuk and Mazur showed that $\text{HG}(G)\ge 2^d$ is possible. We show that for all $d\ge 1$ there exists a $d$-degenerate graph $G$ for which $\text{HG}(G) \ge 2^{2^{d-1}}$. We also give a ne

Nisha Panwar, Shantanu Sharma, Peeyush Gupta, Dhrubajyoti Ghosh

The growing deployment of Internet of Things (IoT) systems aims to ease the daily life of end-users by providing several value-added services. However, IoT systems may capture and store sensitive, personal data about individuals in the cloud, thereby jeopardizing user-privacy. Emerging legislation, such as California's CalOPPA and GDPR in Europe, support

Xing Shi Cai, Guillem Perarnau

We show that the diameter of the directed configuration model with $n$ vertices rescaled by $\log n$ converges in probability to a constant. Our assumptions are the convergence of the in- and out-degree of a uniform random vertex in distribution, first and second moment. Our result extends previous results on the diameter of the model and applies to many oth

Lars Kristiansen, Juvenal Murwanashyaka

We study first-order concatenation theory with bounded quantifiers. We give axiomatizations with interesting properties, and we prove some normal-form results. Finally, we prove a number of decidability and undecidability results.

Vineetha Warriyar K. V., Waleed Almutiry, Rob Deardon

In this article, we introduce the R package EpiILM, which provides tools for simulation from, and inference for, discrete-time individual-level models of infectious disease transmission proposed by Deardon et al. (2010). The inference is set in a Bayesian framework and is carried out via Metropolis-Hastings Markov chain Monte Carlo (MCMC). For its fast imple

XRISM Science Team

This white paper was prepared by members of the XRISM Science Team for the benefit of the general astronomical community. This paper describes the capabilities of XRISM, offers a sampling of the many science topics that the mission will address, and discusses the synergies of XRISM with the plethora of planned and existing facilities in the 2020s and beyond.

Donny R. Bárcenas, Joel Kuperman, Marcelo N. Kuperman

In this work we analyze an evolutionary game that incorporates the ideas presented by Cipolla in his work \textit{The fundamental laws of human stupidity}. The game considers four strategies, three of them are inherent to the player behavior and can evolve via an imitation dynamics, while the fourth one is associated to an eventual behavior that can be adopt

A. J. Czejdo, J. E. Drut, Y. Hou, J. R. McKenney

Using a coarse temporal lattice approximation, we calculate the first few terms of the virial expansion of a three-species fermion system with a three-body contact interaction in $d$ spatial dimensions, both in homogeneous space as well as in a harmonic trapping potential of frequency $ω$. Using the three-body problem to renormalize, we report analytic resul

Bohan Wu, Feng Xu, Zhanpeng He, Abhi Gupta

Recent advances in deep reinforcement learning (RL) have demonstrated its potential to learn complex robotic manipulation tasks. However, RL still requires the robot to collect a large amount of real-world experience. To address this problem, recent works have proposed learning from expert demonstrations (LfD), particularly via inverse reinforcement learning

Leslie A. Young, Felipe Braga-Ribas, Robert E. Johnson

At 30-50 K, the temperatures typical for surfaces in the Kuiper Belt (e.g. Stern & Trafton 2008), only seven species have sublimation pressures higher than 1 nbar (Fray & Schmitt 2009): Ne, N$_2$, CO, Ar, O$_2$, CH$_4$, and Kr. Of these, N$_2$, CO, and CH$_4$ have been detected or inferred on the surfaces of Trans-Neptunian Objects (TNOs). The presence of te

Philip Argyres, Mario Martone

We give a non-technical summary of the classification program, very dear to the hearts of both authors, of four dimensional $\mathcal{N}=2$ superconformal field theories (SCFTs) based on the study of their Coulomb branch geometries. We outline the main ideas behind this program, review the most important results thus far obtained, and the prospects for futur

Mohit Srinivasan, Amogh Dabholkar, Samuel Coogan, Patricio Vela

Control barrier functions are mathematical constructs used to guarantee safety for robotic systems. When integrated as constraints in a quadratic programming optimization problem, instantaneous control synthesis with real-time performance demands can be achieved for robotics applications. Prevailing use has assumed full knowledge of the safety barrier functi

Yixin Wang, David M. Blei

Wang and Blei (2019) studies multiple causal inference and proposes the deconfounder algorithm. The paper discusses theoretical requirements and presents empirical studies. Several refinements have been suggested around the theory of the deconfounder. Among these, Imai and Jiang clarified the assumption of "no unobserved single-cause confounders." Us

Chang-Chun Chen, Patrick H. Diamond

A theory of potential vorticity (PV) mixing in a disordered (tangled) magnetic field is presented. The analysis is in the context of $β$-plane MHD, with a special focus on the physics of momentum transport in the stably stratified, quasi-2D solar tachocline. A physical picture of mean PV evolution by vorticity advection and tilting of magnetic fields is prop

Ivan Chajda, Helmut Länger

Orthomodular posets form an algebraic formalization of the logic of quantum mechanics. The question is how to introduce the connective implication in such a logic. We show that this is possible when the orthomodular poset in question is of finite height. The main point is that the corresponding algebra, called implication orthomodular poset, i.e. a poset equ

Navyasri Reddy, Samyak Jain, Pradeep Yarlagadda, Vineet Gandhi

Learning computational models for visual attention (saliency estimation) is an effort to inch machines/robots closer to human visual cognitive abilities. Data-driven efforts have dominated the landscape since the introduction of deep neural network architectures. In deep learning research, the choices in architecture design are often empirical and frequently

Andre He, Benjamin Nachman, Wibe A. de Jong, Christian W. Bauer

In addition to readout errors, two-qubit gate noise is the main challenge for complex quantum algorithms on noisy intermediate-scale quantum (NISQ) computers. These errors are a significant challenge for making accurate calculations for quantum chemistry, nuclear physics, high energy physics, and other emerging scientific and industrial applications. There a

N. K. -R. Kevlahan, R. A. Khan

Accurate mapping of ocean bathymetry is a multi-faceted process, needed for safe and efficient navigation on shipping routes and for predicting tsunami waves. Currently available bathymetry data does not always provide the resolution to capture dynamics of such nonlinear waves accurately. However collection of accurate mapping data is difficult, costly, and

Miles E. Lopes, N. Benjamin Erichson, Michael W. Mahoney

In order to compute fast approximations to the singular value decompositions (SVD) of very large matrices, randomized sketching algorithms have become a leading approach. However, a key practical difficulty of sketching an SVD is that the user does not know how far the sketched singular vectors/values are from the exact ones. Indeed, the user may be forced t

Antonio Di Crescenzo, Luca Paolillo

In reliability theory and survival analysis, the residual entropy is known as a measure suitable to describe the dynamic information content in stochastic systems conditional on survival. Aiming to analyze the variability of such information content, in this paper we introduce the variance of the residual lifetimes, "residual varentropy" in short. Af

Hao Tang, Tian-Shen He, Ruo-Xi Shi, Yan-Yan Zhu

Google PageRank is a prevalent and useful algorithm for ranking the significance of nodes or websites in a network, and a recent quantum counterpart for PageRank algorithm has been raised to suggest a higher accuracy of ranking comparing to Google PageRank. The quantum PageRank algorithm is essentially based on quantum stochastic walks and can be expressed u

Yemi Ojo, Jeremy Watson, Ioannis Lestas

Inverter-based microgrids are an important technology for sustainable electrical power systems and typically use droop-controlled grid-forming inverters to interface distributed energy resources to the network and control the voltage and frequency. Ensuring stability of such microgrids is a key issue, which requires the use of appropriate models for analysis

Yijie Xu, Yun Zong, Kedar Hippalgaonkar

Solid state lithium- and sodium-ion batteries utilize solid ionicly conducting compounds as electrolytes. However, the ionic conductivity of such materials tends to be lower than their liquid counterparts, necessitating research efforts into finding suitable alternatives. The process of electrolyte screening is often based on a mixture of domain expertise an

Chandra Sharma, George Amariucai

Due to the recent popularity of online social networks, coupled with people's propensity to disclose personal information in an effort to achieve certain gratifications, the problem of navigating the tradeoff between privacy and utility attracted a lot of recent interest and generated a rich body of research. A critical prerequisite to solving the proble

Raphael Thiago, Renan Souza, L. Azevedo, E. Soares

Machine Learning (ML) has increased its role, becoming essential in several industries. However, questions around training data lineage, such as "where has the dataset used to train this model come from?"; the introduction of several new data protection legislation; and, the need for data governance requirements, have hindered the adoption of ML mode

Mathis Fricke, Beatrice Fickel, Maximilian Hartmann, Dirk Gründing

We investigate the dynamics of spreading in a regime where the shape of the drop is close to a spherical cap. The latter simplification is applicable in the late (viscous) stage of spreading for highly viscous drops with a diameter below the capillary length. Moreover, it applies to the spreading of a drop on a swellable polymer brush, where the complex inte

Martin P. Martinov, Rowan M. Thomson

Purpose: This work introduces a new lattice geometry library, egs_lattice, into the EGSnrc Monte Carlo code, which can be used for both modeling very large (previously unfeasible) quantities of geometries and establishing recursive boundary conditions. The reliability of egs_lattice, as well as EGSnrc in general, is cross-validated and tested. Methods: New B

Sebastian Goette, Martin Kerin, Krishnan Shankar

In a recent article, the authors constructed a six-parameter family of highly connected 7-manifolds which admit an SO(3)-invariant metric of non-negative sectional curvature. Each member of this family is the total space of a Seifert fibration with generic fibre $S^3$ and, in particular, has the cohomology ring of an $S^3$-bundle over $S^4$. In the present a

Colin Orion Chandler, Jay K. Kueny, Chadwick A. Trujillo, David E. Trilling

Centaurs are minor planets thought to have originated in the outer Solar System region known as the Kuiper Belt. Active Centaurs enigmatically display comet-like features (e.g., tails, comae) even though they orbit in the gas giant region where it is too cold for water to readily sublimate. Only 18 active Centaurs have been identified since 1927 and, consequ

P. Karpov, R. Verdel, Y. -P. Huang, M. Schmitt

Disorder-free localization has been recently introduced as a mechanism for ergodicity breaking in low-dimensional homogeneous lattice gauge theories caused by local constraints imposed by gauge invariance. We show that also genuinely interacting systems in two spatial dimensions can become nonergodic as a consequence of this mechanism. Specifically, we prove

Eric David Kramer, Eric Kuflik, Noam Levi, Nadav Joseph Outmezguine

We propose a new thermal freezeout mechanism which results in dark matter masses exceeding the unitarity bound by many orders of magnitude, without violating perturbative unitarity or modifying the standard cosmology. The process determining the relic abundance is $χζ^\dagger \to ζζ$, where $χ$ is the dark matter candidate. For $ m_ζ< m_χ< 3 m_ζ$, $χ$ is cos

Robin Schäfer, Imre Hagymási, Roderich Moessner, David J. Luitz

Frustrated three dimensional quantum magnets are notoriously impervious to theoretical analysis. Here we use a combination of three computational methods to investigate the three dimensional pyrochlore $S=1/2$ quantum antiferromagnet, an archetypical frustrated magnet, at finite temperature, $T$: canonical typicality for a finite cluster of $2\times 2 \times

Gary J. Melnick, Volker Tolls, Ronald L. Snell, Michael J. Kaufman

The depth-dependent abundance of both gas-phase and solid-state water within dense, quiescent, molecular clouds is important to both the cloud chemistry and gas cooling. Where water is in the gas phase, it&#39;s free to participate in the network of ion-neutral reactions that lead to a host of oxygen-bearing molecules, and its many ortho and para energy leve

Aritra De, Christopher Plumberg, Joseph I. Kapusta

We study the propagation and diffusion of electric charge fluctuations in the Bjorken hydrodynamic model with both white and Catteneo noise using purely numerical methods. We show that a global lattice of noise fluctuations is required to fully calculate the two-point correlators of charge. We solve the stochastic differential equations that arise from the c

Michael Farber, Daisuke Kishimoto, Donald Stanley

We examine the rationality conjecture which states that (a) the formal power series $\sum_{r\ge 1} \tc_{r+1}(X)\cdot x^r$ represents a rational function of $x$ with a single pole of order 2 at $x=1$ and (b) the leading coefficient of the pole equals $\cat(X)$. Here $X$ is a finite CW-complex and for $r\ge 2$ the symbol $\tc_r(X)$ denotes its $r$-th sequentia

Haoyun Ying, Keheng Mao, Klaus Mosegaard

The Markov Chain Monte Carlo (MCMC) methods are popular when considering sampling from a high-dimensional random variable $\mathbf{x}$ with possibly unnormalised probability density $p$ and observed data $\mathbf{d}$. However, MCMC requires evaluating the posterior distribution $p(\mathbf{x}|\mathbf{d})$ of the proposed candidate $\mathbf{x}$ at each iterati

J. Dorrington, K. Strommen

Euro-Atlantic regimes are typically identified using either the latitude of the eddy-driven jet, or clustering algorithms in the phase space of 500hPa geopotential height (Z500). However, while robust trimodality is visibly apparent in jet latitude indices, Z500 clusters require highly sensitive significance tests to distinguish them from autocorrelated nois

Subhrajit Sinha, Sai P. Nandanoori, Enoch Yeung

In this paper, we develop the Koopman operator theory for dynamical systems with symmetry. In particular, we investigate how the Koopman operator and eigenfunctions behave under the action of the symmetry group of the underlying dynamical system. Further, exploring the underlying symmetry, we propose an algorithm to construct a global Koopman operator from l

Jesus Inarrea

We report on a theoretical study on the rise of strong peaks at the harmonics of the cyclotron resonance in the irradiated magnetoresistance in ultraclean two-dimensional electron systems. The motivation is the experimental observation of a totally unexpected strong resistance peak showing up at the second harmonic. We extend the radiation-driven electron or

Ivan Vulić, Simon Baker, Edoardo Maria Ponti, Ulla Petti

We introduce Multi-SimLex, a large-scale lexical resource and evaluation benchmark covering datasets for 12 typologically diverse languages, including major languages (e.g., Mandarin Chinese, Spanish, Russian) as well as less-resourced ones (e.g., Welsh, Kiswahili). Each language dataset is annotated for the lexical relation of semantic similarity and contai

Yutaro Shigeto, Yuya Yoshikawa, Jiaqing Lin, Akikazu Takeuchi

In recent years, automatic video caption generation has attracted considerable attention. This paper focuses on the generation of Japanese captions for describing human actions. While most currently available video caption datasets have been constructed for English, there is no equivalent Japanese dataset. To address this, we constructed a large-scale Japane

Nina Taherimakhsousi, Benjamin P. MacLeod, Fraser G. L. Parlane, Thomas D. Morrissey

The sensitivity of thin-film materials and devices to defects motivates extensive research into the optimization of film morphology. This research could be accelerated by automated experiments that characterize the response of film morphology to synthesis conditions. Optical imaging can resolve morphological defects in thin films and is readily integrated in

Carlos Ramirez, Luis A. Medina-Amayo

A novel efficient method to calculate the scattering matrix (SM) of arbitrary tight-binding Hamiltonians is proposed, including cases with multiterminal structures. In particular, the SM of two kind of fundamental structures are given, which can be used to obtain the SM of bigger systems iteratively. Also, a procedure to obtain the SM of layer-composed perio

Julio Alberto Dias, Guilherme Machado, Alessandro Soares, Joaquim Dias Garcia

In this paper, we propose a non-parametric Bayesian network method to generate synthetic scenarios of hourly generation for variable renewable energy(VRE) plants. The methodology consists of a non-parametric estimation of the probability distribution of VRE generation, followed by an inverse probability integral transform, in order to obtain normally distrib

Ze-Min Huang, Bo Han

Based on the supersymmetric quantum mechanical approach, we have systematically studied both the $U\left(1\right)$ gauge anomaly and the diffeomorphism anomaly in Weyl systems with torsion, curvature and external electromagnetic fields. These anomalies relate to the chiral current (or current) non-conservation and chiral energy-momentum (or energy-momentum)

Xueyang Wang, Xiya Zhang, Yinheng Zhu, Yuchen Guo

We present PANDA, the first gigaPixel-level humAN-centric viDeo dAtaset, for large-scale, long-term, and multi-object visual analysis. The videos in PANDA were captured by a gigapixel camera and cover real-world scenes with both wide field-of-view (~1 square kilometer area) and high-resolution details (~gigapixel-level/frame). The scenes may contain 4k head

G. Ramalho, M. T. Peña

We develop a covariant model for the $γ^\ast N \to N(1535)$ transition in the timelike kinematical region, the region where the square momentum transfer $q^2$ is positive. Our starting point is the covariant spectator quark model constrained by data in the spacelike kinematical region ($Q^2 = -q^2 >0$). The model is used to estimate the contributions of vale

Sally Giuseppe Arcidiacono, Salvatore Corrente, Salvatore Greco

In this paper we propose a new multiple criteria decision aiding method to deal with sorting problems in which alternatives are evaluated on criteria structured in a hierarchical way and presenting interactions. The underlying preference model of the proposed method is the Choquet integral, while the hierarchical structure of the criteria is taken into accou

Flavio Cirillo, David Gómez, Luis Diez, Ignacio Elicegui Maestro

Smart cities solutions are often monolithically implemented, from sensors data handling through to the provided services. The same challenges are regularly faced by different developers, for every new solution in a new city. Expertise and know-how can be re-used and the effort shared. In this article we present the methodologies to minimize the efforts of im

Leila Sharifan, Somayeh Moradi

We introduce a family of squarefree monomial ideals associated to finite simple graphs, whose monomial generators correspond to closed neighborhood of vertices of the underlying graph. Any such ideal is called the closed neighborhood ideal of the graph. We study some algebraic invariants of these ideals like Castelnuovo-Mumford regularity and projective dime

A. Bershadskii

The atmospheric temperature inhomogeneities are the main cause of the index of refraction variations resulting in strong fluctuations of intensity of the laser beams propagating through the atmosphere. It is shown that the Kolmogorov-Bolgiano-Obukhov phenomenology of the thermal (buoyancy driven) convection can effectively describe this process in the frames

Markus Bläser, Christian Ikenmeyer, Meena Mahajan, Anurag Pandey

Nisan showed in 1991 that the width of a smallest noncommutative single-(source,sink) algebraic branching program (ABP) to compute a noncommutative polynomial is given by the ranks of specific matrices. This means that the set of noncommutative polynomials with ABP width complexity at most $k$ is Zariski-closed, an important property in geometric complexity

Reza Barazideh, Omid Semiari, Solmaz Niknam, Balasubramaniam Natarajan

Emerging wireless services with extremely high data rate requirements, such as real-time extended reality applications, mandate novel solutions to further increase the capacity of future wireless networks. In this regard, leveraging large available bandwidth at terahertz frequency bands is seen as a key enabler. To overcome the large propagation loss at thes

Walter R. C. Somerville, Adam D. Law, Marcel Rey, Nicolas Vogel

Hard-core/soft shell (HCSS) particles have been shown to self-assemble into a remarkably rich variety of structures under compression due to the simple interplay between the hard-core and soft-shoulder length scales in their interactions. Most studies in this area model the soft shell interaction as a square shoulder potential. Although appealing from a theo

Anuj Sharma, Syed Mohammed Arshad Zaidi

Graphs and their traversal is becoming significant as it is applicable to various areas of mathematics, science and technology. Various problems in fields as varied as biochemistry (genomics), electrical engineering (communication networks), computer science (algorithms and computation) can be modeled as Graph problems. Real world scenarios including communi

Dmitry Duplyakin, Alexandru Uta, Aleksander Maricq, Robert Ricci

All computing infrastructure suffers from performance variability, be it bare-metal or virtualized. This phenomenon originates from many sources: some transient, such as noisy neighbors, and others more permanent but sudden, such as changes or wear in hardware, changes in the underlying hypervisor stack, or even undocumented interactions between the policies

Nicolò Ruggeri, Caterina De Bacco

We perform an extensive analysis of how sampling impacts the estimate of several relevant network measures. In particular, we focus on how a sampling strategy optimized to recover a particular spectral centrality measure impacts other topological quantities. Our goal is on one hand to extend the analysis of the behavior of TCEC [Ruggeri2019], a theoretically

Richard Tran, David Patrick, Michael Geyer, Amanda Fernandez

With the rise in popularity of machine and deep learning models, there is an increased focus on their vulnerability to malicious inputs. These adversarial examples drift model predictions away from the original intent of the network and are a growing concern in practical security. In order to combat these attacks, neural networks can leverage traditional ima

Magdalena Larfors, Robin Schneider

We use deep reinforcement learning to explore a class of heterotic $SU(5)$ GUT models constructed from line bundle sums over Complete Intersection Calabi Yau (CICY) manifolds. We perform several experiments where A3C agents are trained to search for such models. These agents significantly outperform random exploration, in the most favourable settings by a fa

Alaa Armiti-Juber

We study the process of two-phase flow in thin porous media domains of Brinkman-type. This is generally described by a model of coupled, mixed-type differential equations of fluids&#39; saturation and pressure. To reduce the model complexity, different approaches that utilize the thin geometry of the domain have been suggested. We focus on a reduced model th