December 2020 arXiv papers — page 144

Tikhon Pshenitsyn

It is known that hyperedge replacement grammars are similar to string context-free grammars in the sense of definitions and properties. Therefore, we expect that there is a generalization of the well-known Greibach normal form from string grammars to hypergraph grammars. Such generalized normal forms are presented in several papers; however, they do not cove

Hans-Jörg Kreowski, Aaron Lye

Graph-based reaction systems were recently introduced as a generalization of the intensely studied set-based reaction systems. They deal with simple edge-labeled directed graphs, and dynamic semantics of graph-based reaction systems is defined by graph surfing as a novel kind of graph transformation where, in a single surf step, reactions are applied to a su

Dominique Duval, Rachid Echahed, Frédéric Prost

We consider the recommendations of the World Wide Web Consortium (W3C) about RDF framework and its associated query language SPARQL. We propose a new formal framework based on category theory which provides clear and concise formal definitions of the main basic features of RDF and SPARQL. We define RDF graphs as well as SPARQL basic graph patterns as objects

Okan Özkan

The concept of adverse conditions addresses systems interacting with an adversary environment and finds use also in the development of new technologies. We present an approach for modeling adverse conditions by graph transformation systems. In contrast to other approaches for graph-transformational interacting systems, the presented main constructs are graph

Christian Sandmann

Model repair is an essential topic in model-driven engineering. We present typed graph-repair programs for specific conditions; application to any typed graph yields a typed graph satisfying the condition. A model graph based on the Eclipse Modeling Framework (EMF), short EMF-model graph, is a typed graph satisfying some structural EMF-constraints. Applicati

Nils Weidmann, Anthony Anjorin, James Cheney

In the field of Model-Driven Engineering, there exist numerous tools that support various consistency management operations including model transformation, synchronisation and consistency checking. The supported operations, however, typically run completely in the background with only input and output made visible to the user. We argue that this often reduce

Juan Castorena, Diane Oyen, Ann Ollila, Carey Legget

This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and (2) get qualitative and quantitative measures of chemical content of a sample given a spectral signal (i.e., calibrate). O

Fatma Kachi, Chafia Bouanaka, Souheir Merkouche

Maintaining an acceptable level of quality of service in modern complex systems is challenging, particularly in the presence of various forms of uncertainty caused by changing execution context, unpredicted events, etc. Although self-adaptability is a well-established approach for modelling such systems, and thus enabling them to achieve functional and/or qu

Mario Gleirscher

Safety controllers are system or software components responsible for handling risk in many machine applications. This tool paper describes a use case and a workflow for YAP, a research tool for risk modelling and discrete-event safety controller design. The goal of this use case is to derive a safety controller from hazard analysis and risk assessment, to de

Rafael C. Cardoso, Louise A. Dennis, Marie Farrell, Michael Fisher

Software engineering of modular robotic systems is a challenging task, however, verifying that the developed components all behave as they should individually and as a whole presents its own unique set of challenges. In particular, distinct components in a modular robotic system often require different verification techniques to ensure that they behave as ex

Mehrnoosh Askarpour

Human-robot collaboration (HRC) is an emerging trend of robotics that promotes the co-presence and cooperation of humans and robots in common workspaces. Physical vicinity and interaction between humans and robots, combined with the uncertainty of human behaviour, could lead to undesired situations where humans are injured. Thus, safety is a priority for HRC

Kazunari Shima

The geometrical argument of the general relativity principle of Einstein is formulated in unstable Riemann space-time just inspired by the nonlinear representation of supersymmetry, which produces new Einstein-Hilbert type action.

Lei Zhang, Fei Zhou, Wei Wei, Yanning Zhang

Learning to generate a task-aware base learner proves a promising direction to deal with few-shot learning (FSL) problem. Existing methods mainly focus on generating an embedding model utilized with a fixed metric (eg, cosine distance) for nearest neighbour classification or directly generating a linear classier. However, due to the limited discriminative ca

Ji-Cheng Hou, Jiling Cao

In this paper, we introduce the concept of $Δ$-convexity in an abstract economy with all choice sets being general topological spaces. We give a new generalization of the classical Yannelis-Prabhakar equilibrium existence theorem in abstract economies by relaxing $SS$-convexity to $Δ$-convexity.

Xize Xu, Hermann Riecke

The synchronization of different $γ$-rhythms arising in different brain areas has been implicated in various cognitive functions. Here, we focus on the effect of the ubiquitous neuronal heterogeneity on the synchronization of PING (pyramidal-interneuronal network gamma) and ING (interneuronal network gamma) rhythms. The synchronization properties of rhythms

Ankit Goyal, Kaiyu Yang, Dawei Yang, Jia Deng

Understanding spatial relations (e.g., "laptop on table") in visual input is important for both humans and robots. Existing datasets are insufficient as they lack large-scale, high-quality 3D ground truth information, which is critical for learning spatial relations. In this paper, we fill this gap by constructing Rel3D: the first large-scale, human-

Wen Wang, Honglei Zhuang, Mi Zhou, Hanyu Liu

Education has a significant impact on both society and personal life. With the development of technology, online education has been growing rapidly over the past decade. While there are several online education studies on student behavior analysis, the course concept mining, and course recommendations (Feng, Tang, and Liu 2019; Pan et al. 2017), there is lit

Wei Zhang, Murray Campbell, Yang Yu, Sadhana Kumaravel

Human judgments of word similarity have been a popular method of evaluating the quality of word embedding. But it fails to measure the geometry properties such as asymmetry. For example, it is more natural to say "Ellipses are like Circles" than "Circles are like Ellipses". Such asymmetry has been observed from a psychoanalysis test called wo

Xin He, Yajing Liu, Kumar Ganesan, Arman Ahnood

A multispectral image camera captures image data within specific wavelength ranges in narrow wavelength bands across the electromagnetic spectrum. Images from a multispectral camera can extract additional information that the human eye or a normal camera fails to capture and thus may have important applications in precision agriculture, forestry, medicine an

Ayomikun Adeniran, Lauren Snider, Catherine Yan

Univariate delta Gončarov polynomials arise when the classical Gončarov interpolation problem in numerical analysis is modified by replacing derivatives with delta operators. When the delta operator under consideration is the backward difference operator, we acquire the univariate difference Gončarov polynomials, which have a combinatorial relation to lattic

Adair Lang, Michael Cantoni, Farhad Farokhi, Iman Shames

The motivation for this work stems from the problem of scheduling requests for flow at supply points along an automated network of open-water channels. The off-take flows are rigid-profile inputs to the system dynamics. In particular, the channel operator can only shift orders in time to satisfy constraints on the automatic response to changes in the load. T

Han-Sen Zhong, Hui Wang, Yu-Hao Deng, Ming-Cheng Chen

Gaussian boson sampling exploits squeezed states to provide a highly efficient way to demonstrate quantum computational advantage. We perform experiments with 50 input single-mode squeezed states with high indistinguishability and squeezing parameters, which are fed into a 100-mode ultralow-loss interferometer with full connectivity and random transformation

Craig Gidney

We improve the Toffoli count of low depth quantum adders, and analyze how their spacetime cost reacts to having a limited number of magic state factories. We present a block lookahead adder that parallelizes across blocks of bits of size $b$, instead of over all bits. The block lookahead adder achieves a Toffoli count of $3n + 5n/b$ for out of place addition

John M. Maheu, Thomas H. McCurdy, Yong Song

The COVID-19 pandemic has caused severe disruption to economic and financial activity worldwide. We assess what happened to the aggregate U.S. stock market during this period, including implications for both short and long-horizon investors. Using the model of Maheu, McCurdy and Song (2012), we provide smoothed estimates and out-of-sample forecasts associate

Shiguang Ma, Jie Qing

In this paper we present some extensions of the celebrated finite point conformal compactification theorem of Huber \cite{Hu57} for complete open surfaces to general dimensions based on the n-Laplace equations in conformal geometry. We are able to conclude a domain in the round sphere has to be the sphere deleted finitely many points if it can be endowed wit

Pengfei Zhang, Yingfei Gu, Alexei Kitaev

We argue that "stringy" effects in a putative gravity-dual picture for SYK-like models are related to the branching time, a kinetic coefficient defined in terms of the retarded kernel. A bound on the branching time is established assuming that the leading diagrams are ladders with thin rungs. Thus, such models are unlikely candidates for sub-AdS holo

Nicholas J Tierney, Dianne Cook, Tania Prvan

Longitudinal (panel) data provide the opportunity to examine temporal patterns of individuals, because measurements are collected on the same person at different, and often irregular, time points. The data is typically visualised using a "spaghetti plot", where a line plot is drawn for each individual. When overlaid in one plot, it can have the appea

Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, John Grundy

Artificial Intelligence/Machine Learning techniques have been widely used in software engineering to improve developer productivity, the quality of software systems, and decision-making. However, such AI/ML models for software engineering are still impractical, not explainable, and not actionable. These concerns often hinder the adoption of AI/ML models in s

Xiaohua Niu, Yang Xiang, Xiaodong Yan

In this paper, we present a phase field model for the self-climb motion of prismatic dislocation loops via vacancy pipe diffusion driven by elastic interactions. This conserved dynamics model is developed under the framework of the Cahn-Hilliard equation with incorporation of the climb force on dislocations, and is based on the dislocation self-climb velocit

Renyu Hu, Doug Lisman, Stuart Shaklan, Stefan Martin

High-contrast imaging enabled by a starshade in formation flight with a space telescope can provide a near-term pathway to search for and characterize temperate and small planets of nearby stars. NASA's Starshade Technology Development Activity to TRL5 (S5) is rapidly maturing the required technologies to the point at which starshades could be integrated

L. Koralov, S. Molchanov, B. Vainberg

The aim of this paper is to investigate the distribution of a continuous polymer in the presence of an attractive finitely supported potential. The most intricate behavior can be observed if we simultaneously and independently vary two parameters: the temperature, which approaches the critical value, and the length of the polymer chain, which tends to infini

Pedram Pakseresht, Sourabh V. Apte

A general, two-way coupled, point-particle formulation that accounts for the disturbance created by the dispersed particles in obtaining the undisturbed fluid flow field needed for accurate computation of the force closure models is presented. Specifically, equations for the disturbance field created by the presence of particles are first derived based on th

Ananth Goyal

We propose an approach to determine the continual progression of algorithmic efficiency, as an alternative to standard calculations of time complexity, likely, but not exclusively, when dealing with data structures with unknown maximum indexes and with algorithms that are dependent on multiple variables apart from just input size. The proposed method can eff

N. T. Bagraev, L. E. Klyachkin, A. M. Malyarenko, K. B. Taranets

A spectrometer based on silicon nanosandwiches (SNS) is proposed for problems of personalized medicine. SNS structures exhibit properties of terahertz (THz) emitter and receiver of the THz response of biological tissue. Measurements of the current-voltage curves of the SNS structure make it possible to analyze the spectral composition of the THz response of

Bryce Doerr, Richard Linares, Pingping Zhu, Silvia Ferrari

Controlling large swarms of robotic agents presents many challenges including, but not limited to, computational complexity due to a large number of agents, uncertainty in the functionality of each agent in the swarm, and uncertainty in the swarm's configuration. This work generalizes the swarm state using Random Finite Set (RFS) theory and solves a cent

Corentin Briat

Linear Parameter-Varying (LPV) systems with jumps and piecewise differentiable parameters is a class of hybrid LPV systems for which no tailored stability analysis and stabilization conditions have been obtained so far. We fill this gap here by proposing an approach based on a clock- and parameter-dependent Lyapunov function yielding stability conditions und

Yoshito Saito, Shintaro Adachi, Ryo Matsumoto, Masanori Nagao

Cuprate superconductor Bi2Sr2CaCu2O8+δ (BSCCO) has been a promising candidate of a coherent, continuous, and compact THz light source owing to its intrinsic Josephson junction inside the crystal structure. In this paper, we utilized BSCCO cross-whisker junctions to produce THz emitter device using the whisker crystals which can be easily obtained compared wi

S. I. Godunov, E. K. Karkaryan, V. A. Novikov, A. N. Rozanov

In the relatively recent CMS data, there is a hint on the existence of a resonance with the mass 28 GeV coupling to muons. Such a resonance should also couple to photons through the fermion loop, therefore it can be searched for in ultraperipheral collisions (UPC) of protons. We set an upper bound on the $X γγ$ coupling constant from the data on $μ^+ μ^-$ pa

Salva Rühling Cachay, Emma Erickson, Arthur Fender C. Bucker, Ernest Pokropek

Deep learning-based models have recently outperformed state-of-the-art seasonal forecasting models, such as for predicting El Niño-Southern Oscillation (ENSO). However, current deep learning models are based on convolutional neural networks which are difficult to interpret and can fail to model large-scale atmospheric patterns called teleconnections. Hence,

Zhenzhen Weng, Serena Yeung

The 3D world limits the human body pose and the human body pose conveys information about the surrounding objects. Indeed, from a single image of a person placed in an indoor scene, we as humans are adept at resolving ambiguities of the human pose and room layout through our knowledge of the physical laws and prior perception of the plausible object and huma

Ian Balitsky

The Drell-Yan hadronic tensor for electromagnetic (EM) current is calculated in the Sudakov region $s\gg Q^2\gg q_\perp^2$ with ${1\over Q^2}$ accuracy, first at the tree level and then with the double-log accuracy. It is demonstrated that in the leading order in $N_c$ the higher-twist quark-quark-gluon TMDs reduce to leading-twist TMDs due to QCD equation o

Alan W. McConnachie, Clare R. Higgs, Guillaume F. Thomas, Kim A. Venn

We measure systemic proper motions for distant dwarf galaxies in the Local Group and investigate if these isolated galaxies have ever had an interaction with the Milky Way or M31. We cross-match photometry of isolated, star forming, dwarf galaxies in the Local Group, taken as part of the {\it Solo} survey, with astrometric measurements from Gaia Data Release

Maria Nyamukuru, Kofi Odame

Non-invasive at-home monitoring of lung and lung airways health enables the early detection and tracking of respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD). Various proposed approaches estimate the respiratory rate and extract the respiratory waveform from an electrocardiogram (ECG) signal as a way to discreetly monitor lung

Dominik F. Bauer, Tom Russ, Barbara I. Waldkirch, Christian Tönnes

Sparsity of annotated data is a major limitation in medical image processing tasks such as registration. Registered multimodal image data are essential for the diagnosis of medical conditions and the success of interventional medical procedures. To overcome the shortage of data, we present a method that allows the generation of annotated multimodal 4D datase

CMS Collaboration

An inclusive search is presented for long-lived particles using displaced jets. The search uses a data sample collected with the CMS detector at the CERN LHC in 2017 and 2018, from proton-proton collisions at a center-of-mass energy of 13 TeV. The results of this search are combined with those of a previous search using a data sample collected with the CMS d

D. Reznik, I. Ahmadova

This article introduces software called Phonon Explorer that implements a data mining workflow for large datasets of the neutron scattering function, S(Q, ω), measured on time-of-flight neutron spectrometers. This systematic approach takes advantage of all useful data contained in the dataset. It includes finding Brillouin zones where specific phonons have t

Sergio Amat, David Levin, Juan Ruiz-Álvarez

Linear approximation approaches suffer from Gibbs oscillations when approximating functions with singularities. ENO-SR resolution is a local approach avoiding oscillations and with a full order of accuracy, but a loss of regularity of the approximant appears. The goal of this paper is to introduce a new approach having both properties of full accuracy and re

John Campbell, Tobias Neumann, Zack Sullivan

We present a calculation of t-channel single-top-quark production and decay in the five-flavor scheme at NNLO. Our results resolve a disagreement between two previous calculations of this process that found a difference in the inclusive cross section at the level of the NNLO coefficient itself. We compare in detail with the previous calculations at the inclu

Lukas J. Fiderer, Tommaso Tufarelli, Samanta Piano, Gerardo Adesso

The quantum Fisher information matrix is a central object in multiparameter quantum estimation theory. It is usually challenging to obtain analytical expressions for it because most calculation methods rely on the diagonalization of the density matrix. In this paper, we derive general expressions for the quantum Fisher information matrix which bypass matrix

Nejib Saadaoui

This paper develops a cohomology theory for Hom-Leibniz algebras using the $\beta$-Nijenhuis--Richardson bracket and applies it to classify non-abelian extensions. We introduce left, and right versions of the bracket, each defining a graded Lie algebra structure on the space of $\beta$-cochains. The main result establishes that equivalence classes of split e

Nikhil Kapoor, Andreas Bär, Serin Varghese, Jan David Schneider

Despite recent advancements, deep neural networks are not robust against adversarial perturbations. Many of the proposed adversarial defense approaches use computationally expensive training mechanisms that do not scale to complex real-world tasks such as semantic segmentation, and offer only marginal improvements. In addition, fundamental questions on the n

Daniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum

As humans interact with autonomous agents to perform increasingly complicated, potentially risky tasks, it is important to be able to efficiently evaluate an agent's performance and correctness. In this paper we formalize and theoretically analyze the problem of efficient value alignment verification: how to efficiently test whether the behavior of anoth

K. M. Taddei, L. Yin, L. D. Sanjeewa, Y. Li

Time reversal symmetry breaking Weyl semimetals are unique among Weyl materials in allowing the minimal number of Weyl points thus offering the clearest signatures of the associated physics. Here we present neutron diffraction, density functional theory and transport measurement results which indicate that EuCd$_2$As$_2$ , under ambient field, strain and pre

Lucy Simko, Jack Lucas Chang, Maggie Jiang, Ryan Calo

There is growing use of technology-enabled contact tracing, the process of identifying potentially infected COVID-19 patients by notifying all recent contacts of an infected person. Governments, technology companies, and research groups alike have been working towards releasing smartphone apps, using IoT devices, and distributing wearable technology to autom

Bao-Jun Cai, Bao-An Li

The unbound nature of pure neutron matter (PNM) requires intrinsic correlations between the symmetric nuclear matter (SNM) EOS parameters (incompressibility $K_0$, skewness $J_0$ and kurtosis $I_0$) and those (slope $L$, curvature $K_{\rm{sym}}$ and skewness $J_{\rm{sym}}$) characterizing the symmetry energy independent of any nuclear many-body theory. We in

Michael Thaler

People often receive good news that makes them feel better about the world around them, or bad news that makes them feel worse about it. This paper studies how the valence of news affects belief updating, absent functional and ego-relevant factors. Using experiments with over 1,500 participants and 5,600 observations, I test whether people engage in motivate

Diab W. Abueidda, Qiyue Lu, Seid Koric

Deep learning and the collocation method are merged and used to solve partial differential equations describing structures' deformation. We have considered different types of materials: linear elasticity, hyperelasticity (neo-Hookean) with large deformation, and von Mises plasticity with isotropic and kinematic hardening. The performance of this deep col

A. A. Miller, X. Hall

We present an update to the PanSTARRS-1 Point Source Catalog (PS1 PSC), which provides morphological classifications of PS1 sources. The original PS1 PSC adopted stringent detection criteria that excluded hundreds of millions of PS1 sources from the PSC. Here, we adapt the supervised machine learning methods used to create the PS1 PSC and apply them to diffe

Sobhan Soleymani, Baaria Chaudhary, Ali Dabouei, Jeremy Dawson

Although biometric facial recognition systems are fast becoming part of security applications, these systems are still vulnerable to morphing attacks, in which a facial reference image can be verified as two or more separate identities. In border control scenarios, a successful morphing attack allows two or more people to use the same passport to cross borde

Alessandro Montoli, Marco Antonelli, Brynmor Haskell, Pierre Pizzochero

A common way to calculate the glitch activity of a pulsar is an ordinary linear regression of the observed cumulative glitch history. This method however is likely to underestimate the errors on the activity, as it implicitly assumes a (long-term) linear dependence between glitch sizes and waiting times, as well as equal variance, i.e., homoscedasticity, in

Michael Thaler

Men and women systematically differ in their beliefs about their performance relative to others; in particular, men tend to be more overconfident. This paper provides support for one explanation for gender differences in overconfidence, performance-motivated reasoning, in which people distort how they process new information in ways that make them believe th

G. Quintero Angulo, L. C. Suárez González, A. Pérez Martínez, H. Pérez Rojas

We study the thermodynamic properties of a relativistic magnetized neutral vector boson gas at any temperature. By comparing the results with the low temperature and the non relativistic descriptions of this gas, we found that the fully relativistic case can be separated in two regimes according to temperature. For low temperatures, magnetic field effects do

Ian Covert, Su-In Lee

The Shapley value concept from cooperative game theory has become a popular technique for interpreting ML models, but efficiently estimating these values remains challenging, particularly in the model-agnostic setting. Here, we revisit the idea of estimating Shapley values via linear regression to understand and improve upon this approach. By analyzing the o

Daniela Oliveira, F. E. Brochero Martínez

Let $\mathbb F_q$ be a finite field with $q$ elements, where $q$ is a power of an odd prime $p$. In this paper we associate circulant matrices and quadratic forms with the Artin-Schreier curve $y^q - y= x \cdot F(x) - λ,$ where $F(x)$ is a $\mathbb F_q$-linearized polynomial and $λ\in \mathbb F_q$. Our results provide a characterization of the number of affi

Gaia Collaboration, A. G. A Brown, A. Vallenari, T. Prusti

We present the early installment of the third Gaia data release, Gaia EDR3, consisting of astrometry and photometry for 1.8 billion sources brighter than magnitude 21, complemented with the list of radial velocities from Gaia DR2. Gaia EDR3 contains celestial positions and the apparent brightness in G for approximately 1.8 billion sources. For 1.5 billion of

Raza Sabbir Sufian, Tianbo Liu, Arpon Paul

We investigate unpolarized and polarized gluon distributions and their applications to the Ioffe-time distributions, which are related to lattice QCD calculations of parton distribution functions. Guided by the counting rules based on the perturbative QCD at large momentum fraction $x$ and the color coherence of gluon couplings at small $x$, we parametrize g

Tara Brendle, Nathan Broaddus, Andrew Putman

Let $M_n$ be the connect sum of $n$ copies of $S^2 \times S^1$. A classical theorem of Laudenbach says that the mapping class group $\text{Mod}(M_n)$ is an extension of $\text{Out}(F_n)$ by a group $(\mathbb{Z}/2)^n$ generated by sphere twists. We prove that this extension splits, so $\text{Mod}(M_n)$ is the semidirect product of $\text{Out}(F_n)$ by $(\math

Chandan Biswas, Betsy Stovall

We show that the restriction and extension operators associated to the moment curve possess extremizers and that $L^p$-normalized extremizing sequences of these operators are precompact modulo symmetries.

Changhyoup Lee, Benjamin Lawrie, Raphael Pooser, Kwang-Geol Lee

The extraordinary sensitivity of plasmonic sensors is well known in the optics and photonics community. These sensors exploit simultaneously the enhancement and the localization of electromagnetic fields close to the interface between a metal and a dielectric. This enables, for example, the design of integrated biochemical sensors at scales far below the dif

Madhur Panwar, Shashank Shailabh, Milan Aggarwal, Balaji Krishnamurthy

Topic models have been widely used to learn text representations and gain insight into document corpora. To perform topic discovery, most existing neural models either take document bag-of-words (BoW) or sequence of tokens as input followed by variational inference and BoW reconstruction to learn topic-word distribution. However, leveraging topic-word distri

Dionysios Antypas, Oleg Tretiak, Ke Zhang, Antoine Garcon

Light scalar Dark Matter with scalar couplings to matter is expected within several scenarios to induce variations in the fundamental constants of nature. Such variations can be searched for, among other ways, via atomic spectroscopy. Sensitive atomic observables arise primarily due to possible changes in the fine-structure constant or the electron mass. Mos

Dennis Hansen, Jelle Hartong, Niels A. Obers, Gerben Oling

We reformulate the Palatini action for general relativity (GR) in terms of moving frames that exhibit local Galilean covariance in a large speed of light expansion. For this, we express the action in terms of variables that are adapted to a Galilean subgroup of the $GL(n,\mathbb{R})$ structure group of a general frame bundle. This leads to a novel Palatini-t

António Antunes, Miguel S. Costa, Tobias Hansen, Aaditya Salgarkar

We derive an optical theorem for perturbative CFTs which computes the double discontinuity of conformal correlators from the single discontinuities of lower order correlators, in analogy with the optical theorem for flat space scattering amplitudes. The theorem takes a purely multiplicative form in the CFT impact parameter representation used to describe hig

Gary Schmiedinghoff, Leanna Müller, Umesh Kumar, Götz S. Uhrig

Stable bound quantum states are ubiquitous in nature. Mostly, they result from the interaction of only pairs of particles, so called two-body interactions, even when large complex many-particle structures are formed. We show that three-particle bound states occur in a generic, experimentally accessible solid state system: antiferromagnetic spin ladders, rela

Abolhassan Mohammadi, Tayeb Golanbari, Jamil Enayati

The constraint of trans-Planckian censorship conjecture on brane inflation model is considered. The conjectures put an upper bound on the main parameter including temperature, inflation time, potential, and the tensor-to-scalar ratio parameter $r$. It is determined that the resulting constraint could be more stronger than what we have for the standard inflat

Sina Honari, Victor Constantin, Helge Rhodin, Mathieu Salzmann

In this paper we propose an unsupervised feature extraction method to capture temporal information on monocular videos, where we detect and encode subject of interest in each frame and leverage contrastive self-supervised (CSS) learning to extract rich latent vectors. Instead of simply treating the latent features of nearby frames as positive pairs and those

Davis Wertheimer, Luming Tang, Bharath Hariharan

In this paper we reformulate few-shot classification as a reconstruction problem in latent space. The ability of the network to reconstruct a query feature map from support features of a given class predicts membership of the query in that class. We introduce a novel mechanism for few-shot classification by regressing directly from support features to query

Burin Gumjudpai

We consider demand-side economy. Using Caratheodory's approach, we define empirical existence of equation of state (EoS) and coordinates. We found new insights of thermodynamics EoS, the {\it effect structure}. Rules are proposed as criteria in promoting and classifying an empirical law to EoS status. Four laws of thermodynamics are given for economics.

M. A. Green, J. W. Moffat

Renormalization group methods are applied to a scalar field within a finite, nonlocal quantum field theory formulated perturbatively in Euclidean momentum space. It is demonstrated that the triviality problem in scalar field theory, the Higgs boson mass hierarchy problem and the stability of the vacuum do not arise as issues in the theory. The scalar Higgs f

Benjamin Moore, Evelyne Smith-Roberge

We prove that every triangle-free $4$-critical graph $G$ satisfies $e(G) \geq \frac{5v(G)+2}{3}$. This result gives a unified proof that triangle-free planar graphs are $3$-colourable, and that graphs of girth at least five which embed in either the projective plane, torus, or Klein Bottle are $3$-colourable, which are results of Grötzsch, Thomassen, and Tho

Nikolai Karpov, Qin Zhang

Motivated by real-world applications such as fast fashion retailing and online advertising, the Multinomial Logit Bandit (MNL-bandit) is a popular model in online learning and operations research, and has attracted much attention in the past decade. However, it is a bit surprising that pure exploration, a basic problem in bandit theory, has not been well stu

Abhishek Bharatbhai Solanki, Simeon I. Bogdanov, Avinash Rustagi, Neil R. Dilley

Hybrid systems coupling quantum spin defects (QSD) and magnons can enable unique spintronic device functionalities and probes for magnetism. Here, we add electric field control of magnon-QSD coupling to such systems by integrating ferromagnet-ferroelectric multiferroic with nitrogen-vacancy (NV) center spins. Combining quantum relaxometry with ferromagnetic

Hugo Esquivel, Arun Prakash, Guang Lin

Uncertainty quantification techniques such as the time-dependent generalized polynomial chaos (TD-gPC) use an adaptive orthogonal basis to better represent the stochastic part of the solution space (aka random function space) in time. However, because the random function space is constructed using tensor products, TD-gPC-based methods are known to suffer fro

Boris Pestoni, Kathrin Altwegg, Hans Balsiger, Nora Hänni

The ESA Rosetta mission has allowed an extensive in-situ study of comet 67P/Churyumov-Gerasimenko. In measurements performed by the ram gauge of the on-board COmet Pressure Sensor (COPS), features have been observed that deviate from the nominal ram gauge signal. These are attributable to the sublimation of the volatile fraction of cometary icy particles con

Cliff B Jones, Alan Burns

The application considered is mixed-criticality scheduling. The core formal approaches used are Rely-Guarantee conditions and the Timeband framework; these are applied to give a layered description of job scheduling which includes resilience to jobs overrunning their expected execution time. A novel formal modelling idea is proposed to handle the relationshi

Pu Gao

We improve the estimates of the subgraph probabilities in a random regular graph. Using the improved results, we further improve the limiting distribution of the number of triangles in random regular graphs.

Maria Teresa Mercaldo, Francesco Giazotto, Mario Cuoco

We investigate the tunneling conductance of superconductor-insulator-normal metal (SIN) and superconductor-insulator-superconductor (SIS) heterostructures with one superconducting side of the junction that is electrically driven and can exhibit $π$-pairing through a modification of the surface inversion asymmetric couplings. In SIN tunneling we find that the

Fatemeh Davoudi, PegahSadat MirshafieKhozani, Ehsan Paki, Mojtaba Roshana

WASP-12 b, WASP-33 b, WASP-36 b, and WASP-46 b are four transiting planetary systems which we have studied. These systems' light curves were derived from observations made by the Transiting Light Exoplanet Survey Satellite (TESS) and some ground-based telescopes. We used Exofast-v1 to model these light curves and calculate mid-transit times. Also, we plo

Weinan E, Stephan Wojtowytsch

We use explicit representation formulas to show that solutions to certain partial differential equations lie in Barron spaces or multilayer spaces if the PDE data lie in such function spaces. Consequently, these solutions can be represented efficiently using artificial neural networks, even in high dimension. Conversely, we present examples in which the solu

Chaim Even-Zohar, Michael Farber, Lewis Mead

Motivated by potential applications in network theory, engineering and computer science, we study $r$-ample simplicial complexes. These complexes can be viewed as finite approximations to the Rado complex which has a remarkable property of {\it indestructibility,} in the sense that removing any finite number of its simplexes leaves a complex isomorphic to it

Peter J. Cameron, Natalia V. Maslova

The Gruenberg-Kegel graph $\Gamma(G)$ associated with a finite group $G$ has as vertices the prime divisors of $|G|$, with an edge from $p$ to $q$ if and only if $G$ contains an element of order $pq$. This graph has been the subject of much recent interest; one of our goals here is to give a survey of some of this material, relating to groups with the same G

Jie Ying Wu, Nural Yilmaz, Peter Kazanzides, Ugur Tumerdem

Measurement of environment interaction forces during robotic minimally-invasive surgery would enable haptic feedback to the surgeon, thereby solving one long-standing limitation. Estimating this force from existing sensor data avoids the challenge of retrofitting systems with force sensors, but is difficult due to mechanical effects such as friction and comp

Jize Zhang, Bhavya Kailkhura, T. Yong-Jin Han

In this paper, we leverage predictive uncertainty of deep neural networks to answer challenging questions material scientists usually encounter in machine learning based materials applications workflows. First, we show that by leveraging predictive uncertainty, a user can determine the required training data set size necessary to achieve a certain classifica

Neville Ryant, Prachi Singh, Venkat Krishnamohan, Rajat Varma

DIHARD III was the third in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variability in recording equipment, noise conditions, and conversational domain. Speaker diarization was evaluated under two speech activity conditions (diarization from a reference speech activity vs. diarization from scratch)

Zhijie Feng, S. Redner

We present and analyze a minimalist model for the vertical transport of people in a tall building by elevators. We focus on start-of-day operation in which people arrive at the ground floor of the building at a fixed rate. When an elevator arrives on the ground floor, passengers enter until the elevator capacity is reached, and then they are transported to t

Vikram V. Ramaswamy, Sunnie S. Y. Kim, Olga Russakovsky

Fairness in visual recognition is becoming a prominent and critical topic of discussion as recognition systems are deployed at scale in the real world. Models trained from data in which target labels are correlated with protected attributes (e.g., gender, race) are known to learn and exploit those correlations. In this work, we introduce a method for trainin

Ankush Khandelwal, Shaoming Xu, Xiang Li, Xiaowei Jia

Streamflow prediction is one of the key challenges in the field of hydrology due to the complex interplay between multiple non-linear physical mechanisms behind streamflow generation. While physics based models are rooted in rich understanding of the physical processes, a significant performance gap still remains which can be potentially addressed by leverag

Hamdy Mubarak, Sabit Hassan

Over the past few months, there were huge numbers of circulating tweets and discussions about Coronavirus (COVID-19) in the Arab region. It is important for policy makers and many people to identify types of shared tweets to better understand public behavior, topics of interest, requests from governments, sources of tweets, etc. It is also crucial to prevent

Jihua Huang, Amir Tamrakar

We propose a novel facial Anchors and Contours Estimation framework, ACE-Net, for fine-level face alignment tasks. ACE-Net predicts facial anchors and contours that are richer than traditional facial landmarks while overcoming ambiguities and inconsistencies in their definitions. We introduce a weakly supervised loss enabling ACE-Net to learn from existing f

Daniel Malz, Adam Smith

Previous theoretical and experimental research has shown that current NISQ devices constitute powerful platforms for analogue quantum simulation. With the exquisite level of control offered by state-of-the-art quantum computers, we show that one can go further and implement a wide class of Floquet Hamiltonians, or timedependent Hamiltonians in general. We th