October 2020 arXiv papers — page 83

Tianyi Yao, Genevera I. Allen

Feature selection often leads to increased model interpretability, faster computation, and improved model performance by discarding irrelevant or redundant features. While feature selection is a well-studied problem with many widely-used techniques, there are typically two key challenges: i) many existing approaches become computationally intractable in huge

Xianghao Zhan, Yuzhe Liu, Samuel J. Raymond, Hossein Vahid Alizadeh

Objective: Many recent studies have suggested that brain deformation resulting from a head impact is linked to the corresponding clinical outcome, such as mild traumatic brain injury (mTBI). Even though several finite element (FE) head models have been developed and validated to calculate brain deformation based on impact kinematics, the clinical application

Biao Zhang, Ivan Titov, Barry Haddow, Rico Sennrich

Information in speech signals is not evenly distributed, making it an additional challenge for end-to-end (E2E) speech translation (ST) to learn to focus on informative features. In this paper, we propose adaptive feature selection (AFS) for encoder-decoder based E2E ST. We first pre-train an ASR encoder and apply AFS to dynamically estimate the importance o

Donald V. Reames

In a field overflowing with beautiful images of the Sun, solar energetic particle (SEP) events are a hidden asset, perhaps a secret weapon, that can sample the solar corona and carry away unique imprints of its most bizarre and violent physics. Only recently have we found that the abundances of the elements in SEPs carry a wealth of data, not only on their o

Zhiyuan Li, Yi Zhang, Sanjeev Arora

Convolutional neural networks often dominate fully-connected counterparts in generalization performance, especially on image classification tasks. This is often explained in terms of 'better inductive bias'. However, this has not been made mathematically rigorous, and the hurdle is that the fully connected net can always simulate the convolutional ne

Boyan Sirakov, Philippe Souplet

We develop a new, unified approach to the following two classical questions on elliptic PDE: the strong maximum principle for equations with non-Lipschitz nonlinearities, and the at most exponential decay of solutions in the whole space or exterior domains. Our results apply to divergence and nondivergence operators with locally unbounded lower-order coeffic

F. N. Womack, P. W. Adams, G. Catelani

We report spin-polarized tunneling density of states measurements of the proximity modulated superconductor-insulator transition in ultra thin Be-Al bilayers. The bilayer samples consisted of a Be film of varying thickness, $d_\mathrm{Be}=\,$0.8-4.5 nm, on which a 1 nm thick capping layer of Al was deposited. Detailed measurements of the Zeeman splitting of

P. Adsley, V. O. Nesterenko, M. Kimura, L. M. Donaldson

Nuclei in the $sd$-shell demonstrate a remarkable interplay of cluster and mean-field phenomena. The $N=Z$ nuclei, such as $^{24}$Mg and $^{28}$Si, have been the focus of the theoretical study of both these phenomena in the past. The cluster and vortical mean-field phenomena can be probed by excitation of isoscalar monopole and dipole states in scattering of

Taylor A. Howell, Chunjiang Fu, Zachary Manchester

We present an approach for approximately solving discrete-time stochastic optimal-control problems by combining direct trajectory optimization, deterministic sampling, and policy optimization. Our feedback motion-planning algorithm uses a quasi-Newton method to simultaneously optimize a reference trajectory, a set of deterministically chosen sample trajector

Subhankar Dey, Hakan Doga

In this paper, we give a combinatorial description of the concordance invariant $\varepsilon$ defined by Hom in \cite{hom2011knot}, prove some properties of this invariant using grid homology techniques. We also compute $\varepsilon$ of $(p,q)$ torus knots and prove that $\varepsilon(\mathbb{G}_+)=1$ if $\mathbb{G}_+$ is a grid diagram for a positive braid.

Amrit Romana, John Bandon, Noelle Carlozzi, Angela Roberts

Huntington disease (HD) is a fatal autosomal dominant neurocognitive disorder that causes cognitive disturbances, neuropsychiatric symptoms, and impaired motor abilities (e.g., gait, speech, voice). Due to its progressive nature, HD treatment requires ongoing clinical monitoring of symptoms. Individuals with the gene mutation which causes HD may exhibit a ra

Abhijit Champanerkar, Ilya Kofman

Dasbach and Lin proved a "volumish theorem" for alternating links. We prove the analogue for alternating link diagrams on surfaces, which provides bounds on the hyperbolic volume of a link in a thickened surface in terms of coefficients of its reduced Jones-Krushkal polynomial. Along the way, we show that certain coefficients of the 4-variable Krushkal polyn

Hasmik Poghosyan

In this paper we investigate different ways of deriving the A-cycle period as a series in instanton counting parameter $q$ for ${\cal N}=2$ SYM with up to four antifundamental hypermultiplets in NS limit of $Ω$ background. We propose a new method for calculating the period and demonstrate its efficiency by explicit calculations. The new way of doing instanto

Mike A. Botchev, Leonid A. Knizhnerman, Eugene E. Tyrtyshnikov

An efficient Krylov subspace algorithm for computing actions of the $φ$ matrix function for large matrices is proposed. This matrix function is widely used in exponential time integration, Markov chains and network analysis and many other applications. Our algorithm is based on a reliable residual based stopping criterion and a new efficient restarting proce

Igor Marinković, Maxwell Drimmer, Bas Hensen, Simon Gröblacher

The rapid development of quantum information processors has accelerated the demand for technologies that enable quantum networking. One promising approach uses mechanical resonators as an intermediary between microwave and optical fields. Signals from a superconducting, topological, or spin qubit processor can then be converted coherently to optical states a

Katarzyna Macieszczak, Dominic C. Rose

We consider Markovian dynamics of a finitely dimensional open quantum system featuring a weak unitary symmetry, i.e., when the action of a unitary symmetry on the space of density matrices commutes with the master operator governing the dynamics. We show how to encode the weak symmetry in quantum stochastic dynamics of the system by constructing a weakly sym

Sudip Mukherjee, Soumyajyoti Biswas, Arnab Chatterjee, Bikas K. Chakrabarti

We show using scaling arguments and Monte Carlo simulations that a class of binary interacting models of opinion evolution belong to the Ising universality class in presence of an annealed noise term of finite amplitude. While the zero noise limit is known to show an active-absorbing transition, addition of annealed noise induces a continuous order-disorder

Takuo Matsubara, Chris J. Oates, François-Xavier Briol

Bayesian neural networks attempt to combine the strong predictive performance of neural networks with formal quantification of uncertainty associated with the predictive output in the Bayesian framework. However, it remains unclear how to endow the parameters of the network with a prior distribution that is meaningful when lifted into the output space of the

Tomasz Wąs, Oskar Skibski

This paper examines the fundamental problem of identifying the most important nodes in a network. We use an axiomatic approach to this problem. Specifically, we propose six simple properties and prove that PageRank is the only centrality measure that satisfies all of them. Our work gives new conceptual and theoretical foundations of PageRank that can be used

Kathakali Biswas, Soumyajyoti Biswas, Parongama Sen

The electoral college of voting system for the US presidential election is analogous to a coarse graining procedure commonly used to study phase transitions in physical systems. In a recent paper, opinion dynamics models manifesting a phase transition, were shown to be able to explain the cases when a candidate winning more number of popular votes could stil

LHCb collaboration, R. Aaij, C. Abellán Beteta, T. Ackernley

A measurement of $CP$-violating observables is performed using the decays $B^\pm\to D K^\pm$ and $B^\pm\to D π^\pm$, where the $D$ meson is reconstructed in one of the self-conjugate three-body final states $K_{\mathrm S}π^+π^-$ and $K_{\mathrm S}K^+K^-$ (commonly denoted $K_{\mathrm S} h^+h^-$). The decays are analysed in bins of the $D$-decay phase space,

Sebastián Reyes-Carocca

Let $m \geqslant 6$ be an even integer. In this short note we prove that the Jacobian variety of a quasiplatonic Riemann surface with associated group of automorphisms isomorphic to $C_2^2 \rtimes_2 C_m$ admits complex multiplication. We then extend this result to provide a criterion under which the Jacobian variety of a quasiplatonic Riemann surface admits

Peter L. Bartlett, Philip M. Long

We consider bounds on the generalization performance of the least-norm linear regressor, in the over-parameterized regime where it can interpolate the data. We describe a sense in which any generalization bound of a type that is commonly proved in statistical learning theory must sometimes be very loose when applied to analyze the least-norm interpolant. In

Tomohide Masuda, Matthew Ragoza, David Ryan Koes

Deep generative models have been applied with increasing success to the generation of two dimensional molecules as SMILES strings and molecular graphs. In this work we describe for the first time a deep generative model that can generate 3D molecular structures conditioned on a three-dimensional (3D) binding pocket. Using convolutional neural networks, we en

Yuriy Tykhyy

We classified finite orbits of monodromies of the Fuchsian system for five $2\times 2$ matrices. The explicit proof of this result is given. We have proposed a conjecture for a similar classification for $6$ or more $2\times 2$ matrices. Cases in which all monodromy matrices have a common eigenvector are excluded from the consideration. To classify the finit

David Marasco, Bree Barnett Dreyfuss

In the spring of 2018 the Northern California/Nevada section of the American Association of Physics Teachers was alerted to a local high school's plans to eliminate physics for the following school year. As part of the campaign to support the school's efforts to sustain physics in the following year, the physics offerings from the surrounding schools

Daniele Angella, Francesco Pediconi

We investigate the geometry of Hermitian manifolds endowed with a compact Lie group action by holomorphic isometries with principal orbits of codimension one. In particular, we focus on a special class of these manifolds constructed by following B\'erard-Bergery which includes, among the others, the holomorphic line bundles on $\mathbb C\mathbb P^{m-1}$, the

A. Hijano, T. van den Berg, D. Frustaglia, D. Bercioux

We present a theory of conducting quantum networks that accounts for Abelian and non-Abelian fields acting on spin carriers. We apply this approach to model the conductance of mesoscopic spin interferometers of different geometry (such as squares and rings), reproducing recent experimental findings in nanostructured InAsGa quantum wells subject to Rashba spi

Matteo Springolo, Miquel Royo, Massimiliano Stengel

Building on recent developments in electronic-structure methods, we define and calculate the flexoelectric response of two-dimensional (2D) materials fully from first principles. In particular, we show that the open-circuit voltage response to a flexural deformation is a fundamental linear-response property of the crystal that can be calculated within the pr

Jean-Philippe Anker, Hong-Wei Zhang

We establish sharp pointwise kernel estimates and dispersive properties for the wave equation on noncompact symmetric spaces of general rank. This is achieved by combining the stationary phase method and the Hadamard parametrix, and in particular, by introducing a subtle spectral decomposition, which allows us to overcome a well-known difficulty in higher ra

Poonam Yadav, Angelo Feraudo, Budi Arief, Siamak F. Shahandashti

The popularity of the Internet of Things (IoT) devices makes it increasingly important to be able to fingerprint them, for example in order to detect if there are misbehaving or even malicious IoT devices in one's network. The aim of this paper is to provide a systematic categorisation of machine learning augmented techniques that can be used for fingerp

Tomas Svensson

Mass concentrations of birds, or lack of such, is a phenomenon of great ecological and domestic significance. Apart from being and indicator for e.g. food availability, ecological change and population size, it is also a source of conflict between humans and birds. Moreover, massive gatherings or colonies of birds also get the attention of the public -- eith

Andrii Babii, Xi Chen, Eric Ghysels, Rohit Kumar

We study the binary choice problem in a data-rich environment with asymmetric loss functions. The econometrics literature covers nonparametric binary choice problems but does not offer computationally attractive solutions in data-rich environments. The machine learning literature has many algorithms but is focused mostly on loss functions that are independen

Enamul Haque

The demand for green energy increases day by day due to environmental concern and thermoelectric (TE) materials are one of the eco-friendly energy resources. Few authors reported high TE performance in TmCu$_3$Ch$_4$, reaching the figure of merit (ZT) above 2 at 1000K, from first-principles calculations neglecting electron-phonon scattering, spin-orbit coupl

B. G. Carlsson, J. Rotureau

In this letter we present a new expression for the overlaps of wavefunctions in Hartree-Fock-Bogoliubov based theories. Starting from the Pfaffian formula by Bertsch et al (Phys. Rev. Lett. 108,042505 (2012)), an exact and computationally stable formula for overlaps is derived. We illustrate the convenience of this new formulation with a numerical applicatio

Alexander Mielke, Mark A. Peletier, Artur Stephan

We consider nonlinear reaction systems satisfying mass-action kinetics with slow and fast reactions. It is known that the fast-reaction-rate limit can be described by an ODE with Lagrange multipliers and a set of nonlinear constraints that ask the fast reactions to be in equilibrium. Our aim is to study the limiting gradient structure which is available if t

Shin-Liang Chen, Nikolai Miklin, Costantino Budroni, Yueh-Nan Chen

Incompatible measurements, i.e., measurements that cannot be simultaneously performed, are necessary to observe nonlocal correlations. It is natural to ask, e.g., how incompatible the measurements have to be to achieve a certain violation of a Bell inequality. In this work, we provide the direct link between Bell nonlocality and the quantification of measure

Fatima Ezzahra Airod, Houda Chafnaji, Halim Yanikomeroglu

The Release 16 completion unlocks the road to an exciting phase pertain to the sixth generation (6G) era. Meanwhile, to sustain far-reaching applications with unprecedented challenges in terms of latency and reliability, much interest is already getting intensified toward physical layer specifications of 6G. In support of this vision, this work exhibits the

Simon Barth, Andreas Bitter, Semjon Vugalter

We study virtual levels of $N$-particle Schr\"odinger operators and prove that if the particles are one-dimensional and $N\ge 3$, then virtual levels at the bottom of the essential spectrum correspond to eigenvalues. The same is true for two-dimensional particles if $N\ge 4$. These results are applied to prove the non-existence of the Efimov effect in system

Tyler Corbett, Michael Trott

We verify Standard Model Effective Field Theory Ward identities to one loop order when background field gauge is used to quantize the theory. The results we present lay the foundation of next to leading order automatic generation of results in the SMEFT, in both the perturbative and non-perturbative expansion using the geoSMEFT formalism, and background fiel

Filip P. Adamus

The main goal of this paper is to analyse the influence of cracks on the azimuthal variations of amplitude. We restrict our investigation to a single set of vertical, circular, and flat cavities aligned along a horizontal axis. Such cracks are embedded in either isotropic surroundings or transversely isotropic background with a vertical symmetry axis. We emp

Florian Richter, Shihao Shen, Fei Liu, Jingbin Huang

Autonomous robotic surgery has seen significant progression over the last decade with the aims of reducing surgeon fatigue, improving procedural consistency, and perhaps one day take over surgery itself. However, automation has not been applied to the critical surgical task of controlling tissue and blood vessel bleeding--known as hemostasis. The task of hem

Abdullah Alsalemi, Ayman Al-Kababji, Yassine Himeur, Faycal Bensaali

Energy efficiency is a crucial factor in the well-being of our planet. In parallel, Machine Learning (ML) plays an instrumental role in automating our lives and creating convenient workflows for enhancing behavior. So, analyzing energy behavior can help understand weak points and lay the path towards better interventions. Moving towards higher performance, c

Jonas Kornprobst, Thomas F. Eibert

A new low-order discretization scheme for the identity operator in the magnetic field integral equation (MFIE) is discussed. Its concept is derived from the weak-form representation of combined sources which are discretized with Rao-Wilton-Glisson (RWG) functions. The resulting MFIE overcomes the accuracy problem of the classical MFIE while it maintains fast

Claudius Heyer

Let $\mathbf{G}$ be a connected reductive group defined over a locally compact non-archimedean field $F$, let $\mathbf{P}$ be a parabolic subgroup with Levi $\mathbf{M}$ and compatible with a pro-$p$ Iwahori subgroup of $G := \mathbf{G}(F)$. Let $R$ be a commutative unital ring. We introduce the parabolic pro-$p$ Iwahori--Hecke $R$-algebra $\mathcal{H}_R(P)$

Soufian Abja, Sławomir Dinew, Guillaume Olive

We prove sharp uniform estimates for strong supersolutions of a large class of fully nonlinear degenerate elliptic complex equations. Our findings rely on ideas of Kuo and Trudinger who dealt with degenerate linear equations in the real setting. We also exploit the pluripotential theory for the complex Monge-Ampère operator as well as suitably tailored theor

Andrey Kormilitzin, Nemanja Vaci, Qiang Liu, Hao Ni

In this work we addressed the problem of capturing sequential information contained in longitudinal electronic health records (EHRs). Clinical notes, which is a particular type of EHR data, are a rich source of information and practitioners often develop clever solutions how to maximise the sequential information contained in free-texts. We proposed a system

Haozhou Wang, James Henderson, Paola Merlo

Generative adversarial networks (GANs) have succeeded in inducing cross-lingual word embeddings -- maps of matching words across languages -- without supervision. Despite these successes, GANs' performance for the difficult case of distant languages is still not satisfactory. These limitations have been explained by GANs' incorrect assumption that so

Peter D. Turney

Conway's Game of Life is the best-known cellular automaton. It is a classic model of emergence and self-organization, it is Turing-complete, and it can simulate a universal constructor. The Game of Life belongs to the set of semi-totalistic cellular automata, a family with 262,144 members. Many of these automata may deserve as much attention as the Game

H. Clement, T. Skorodko, E. Doroshkevich

The isoscalar single-pion production exhibits a broad bump in the energy dependence of the total cross section, which does not correspond to the usual opening of the $N^*(1440)$ production channel with subsequent pion decay. In arxiv:2102.05575 it was interpreted as a narrow Breit-Wigner structure, which leads in a sequential single-pion production process t

Yuchen Liu, Qiang Hu, Douglas M. Blough

Due to the rapid densification of small cells in 5G and beyond cellular networks, deploying wired high-bandwidth connections to every small cell base station is difficult, particularly in older metropolitan areas where infrastructure for fiber deployment is lacking. For this reason, mmWave wireless backhaul is being considered as a cost-effective and flexibl

Tomoyuki Arakawa, Jethro van Ekeren, Anne Moreau

We give a simple description of the closure of the nilpotent orbits appearing as associated varieties of admissible affine vertex algebras in terms of primitive ideals.

Theophilus Agama

In this paper, we formulate and prove several variants of the Erd\H{o}s-Tur\'{a}n additive bases conjecture.

Raphal Goll, Andreas Rückriegel, Peter Kopietz

Using a functional renormalization group approach we show that at low temperatures and in a certain range of magnetic fields the longitudinal dynamic structure factor of quantum Heisenberg ferromagnets in dimensions $D\leq 2$ exhibits a well-defined quasi-particle peak with linear dispersion that we identify as zero-magnon sound. In $D>2$ the larger phase sp

F. Darabi, M. Golmohammadi, A. Rezaei-Aghdam

In this paper, we use the Hojman symmetry approach to find new $(2+1)$-dimensional $f(R)$ gravity solutions, in comparison to Noether symmetry approach. In the special case of Hojman symmetry vector $X=R$, we recover $(2+1)$-dimensional BTZ black hole and generalized $(2+1)$-dimensional BTZ black hole solutions, obtained by Noether symmetry approach, and the

Suhas Thejaswi, Juho Lauri, Aristides Gionis

We study a family of reachability problems under waiting-time restrictions in temporal and vertex-colored temporal graphs. Given a temporal graph and a set of source vertices, we find the set of vertices that are reachable from a source via a time-respecting path, where the difference in timestamps between consecutive edges is at most a resting time. Given a

Jemima M. Tabeart, Sarah L. Dance, Amos S. Lawless, Nancy K. Nichols

Data assimilation algorithms combine prior and observational information, weighted by their respective uncertainties, to obtain the most likely posterior of a dynamical system. In variational data assimilation the posterior is computed by solving a nonlinear least squares problem. Many numerical weather prediction (NWP) centres use full observation error cov

Stefano Filipazzi, Joe Waldron

A conjecture, known as the Shokurov-Koll\'ar connectedness principle, predicts the following. Let $(X,B)$ be a pair, and let $f \colon X \rightarrow S$ be a contraction with $-(K_X + B)$ nef over $S$; then, for any point $s \in S$, the intersection $f^{-1} (s) \cap \mathrm{Nklt}(X,B)$ has at most two connected components, where $\mathrm{Nklt}(X,B)$ denotes t

Suney Toste, David Holcman

We derive asymptotic formulas for the mean exit time $\barτ^{N}$ of the fastest among $N$ identical independently distributed Brownian particles to an absorbing boundary for various initial distributions (partially uniformly and exponentially distributed). Depending on the tail of the initial distribution, we report here a continuous algebraic decay law for

Arnaud le Febvrier, Ludvig Landalv, Thomas Liersch, David Sandmark

Magnetron sputtering is a widely used physical vapor deposition technique. Reactive sputtering is used for the deposition of, e.g, oxides, nitrides and carbides. In fundamental research, versatility is essential when designing or upgrading a deposition chamber. Furthermore, automated deposition systems are the norm in industrial production, but relatively un

Cedric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu

In our experience of working with domain experts who are using today's AutoML systems, a common problem we encountered is what we call "unrealistic expectations" -- when users are facing a very challenging task with a noisy data acquisition process, while being expected to achieve startlingly high accuracy with machine learning (ML). Many of these are predes

Arno Kret, Sug Woo Shin

We prove the existence of $\mathrm{GSpin}_{2n}$-valued Galois representations corresponding to cohomological cuspidal automorphic representations of certain quasi-split forms of $\mathrm{GSO}_{2n}$ under the local hypotheses that there is a Steinberg component and that the archimedean parameters are regular for the standard representation. This is based on t

Mike Ludkovski, Yuri Saporito

We investigate a machine learning approach to option Greeks approximation based on Gaussian process (GP) surrogates. The method takes in noisily observed option prices, fits a nonparametric input-output map and then analytically differentiates the latter to obtain the various price sensitivities. Our motivation is to compute Greeks in cases where direct comp

Miriam Galbiati, Luca Persichetti, Paola Gori, Olivia Pulci

Combining scanning tunneling microscopy and angle-resolved photoemission spectroscopy, we demonstrate how to tune the doping of epitaxial graphene from p to n by exploiting the structural changes that occur spontaneously on the Ge surface upon thermal annealing. Furthermore, using first principle calculations we build a model that successfully reproduces the

Bert Jüttler, Niels Lubbes, Josef Schicho

We present a method for computing projective isomorphisms between rational surfaces that are given in terms of their parametrizations. The main idea is to reduce the computation of such projective isomorphisms to five base cases by modifying the parametric maps such that the components of the resulting maps have lower degree. Our method can be used to comput

Cuican Yu, Zihui Zhang, Huibin Li

Deep learning methods have brought many breakthroughs to computer vision, especially in 2D face recognition. However, the bottleneck of deep learning based 3D face recognition is that it is difficult to collect millions of 3D faces, whether for industry or academia. In view of this situation, there are many methods to generate more 3D faces from existing 3D

Florian Dittrich, Thomas Speck, Peter Virnau

Lattice models allow for a computationally efficient investigation of motility-induced phase separation (MIPS) compared to off-lattice systems. Simulations are less demanding and thus bigger systems can be accessed with higher accuracy and better statistics. In equilibrium, lattice and off-lattice models with comparable interactions belong to the same univer

Yizhou Liu, Tobias Holder, Binghai Yan

Twisted bilayer graphene (TBG) exhibits fascinating correlation-driven phenomena like the superconductivity and Mott insulating state, with flat bands and a chiral lattice structure. We find by quantum transport calculations that the chirality leads to a giant unidirectional magnetoresistance (UMR) in TBG, where the unidirectionality refers to the resistance

Alessandro De Gregorio, Francesco Iafrate

The aim of this paper is to introduce an adaptive penalized estimator for identifying the true reduced parametric model under the sparsity assumption. In particular, we deal with the framework where the unpenalized estimator of the structural parameters needs simultaneously multiple rates of convergence (i.e. the so-called mixed-rates asymptotic behavior). W

Jack S. Calcut, Jun Li

Gonz{á}lez-Acu{ñ}a showed that Artin presentations characterize closed, orientable $3$-manifold groups. Winkelnkemper later discovered that each Artin presentation determines a smooth, compact, simply-connected $4$-manifold. We utilize triangle groups to find all Artin presentations on two generators that present the trivial group. We then determine all smoo

Arnaud Durand, Nicole Schweikardt, Luc Segoufin

A class of relational databases has low degree if for all $\delta>0$, all but finitely many databases in the class have degree at most $n^{\delta}$, where $n$ is the size of the database. Typical examples are databases of bounded degree or of degree bounded by $\log n$. It is known that over a class of databases having low degree, first-order boolean queries

Amit Sharma

In this paper we study compact closed categories within the context of homotopical algebra. We construct two new model category structures by localizing two (Quillen equivalent) model categories of symmetric monoidal categories with the objective of establishing the free compact closed category on one generator as a fibrant replacement of the free symmetric

Harang Ju, Dale Zhou, Ann S. Blevins, David M. Lydon-Staley

Philosophers of science have long postulated how collective scientific knowledge grows. Empirical validation has been challenging due to limitations in collecting and systematizing large historical records. Here, we capitalize on the largest online encyclopedia to formulate knowledge as growing networks of articles and their hyperlinked inter-relations. We d

Emanuele Dolera, Edoardo Mainini

In Bayesian statistics, a continuity property of the posterior distribution with respect to the observable variable is crucial as it expresses well-posedness, i.e., stability with respect to errors in the measurement of data. Essentially, this requires to analyze the continuity of a probability kernel or, equivalently, of a conditional probability distributi

Martin Kreuzer, Le Ngoc Long, Lorenzo Robbiano

Given an affine algebra $R=P/I$, where $P=K[x_1,\dots,x_n]$ is a polynomial ring over a field $K$ and $I$ is an ideal in $P$, we study re-embeddings of the affine scheme ${\rm Spec}(R)$, i.e., presentations $R \cong P'/I'$ such that $P'$ is a polynomial ring in fewer indeterminates. To find such re-embeddings, we use polynomials $f_i$ in the idea

Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr

Outcomes with a natural order commonly occur in prediction tasks and often the available input data are a mixture of complex data like images and tabular predictors. Deep Learning (DL) models are state-of-the-art for image classification tasks but frequently treat ordinal outcomes as unordered and lack interpretability. In contrast, classical ordinal regress

H. Berthoumieux, G. Monet, R. Blossey

We study the classic problem of ion solvation within the continuum theory of Dipolar-Poisson models. In this approach an ion is treated as a point charge within a sea of point dipoles. Both the standard Dipolar-Poisson model as well as the Dipolar-Poisson-Langevin model, which keeps the dipolar density fixed, are non-convex functionals of the scalar electros

Feng Dai, Andriy Prymak

This paper studies a new Whitney type inequality on a compact domain $Ω\subset {\mathbb{R}}^d$ that takes the form $$\inf_{Q\in Π_{r-1}^d({\mathcal{E}})} \|f-Q\|_p \leq C(p,r,Ω) ω_{\mathcal{E}}^r(f,{\rm diam}(Ω))_p,\ \ r\in {\mathbb{N}},\ \ 0<p\leq \infty,$$ where $ω_{\mathcal{E}}^r(f, t)_p$ denotes the $r$-th order directional modulus of smoothness of $f\in

Satoya Imai, Nikolai Wyderka, Andreas Ketterer, Otfried Gühne

If only limited control over a multiparticle quantum system is available, a viable method to characterize correlations is to perform random measurements and consider the moments of the resulting probability distribution. We present systematic methods to analyze the different forms of entanglement with these moments in an optimized manner. First, we find the

Li Yuan, Shuning Chang, Xuecheng Nie, Ziyuan Huang

Video-based human pose estimation in crowded scenes is a challenging problem due to occlusion, motion blur, scale variation and viewpoint change, etc. Prior approaches always fail to deal with this problem because of (1) lacking of usage of temporal information; (2) lacking of training data in crowded scenes. In this paper, we focus on improving human pose e

Jiewen Xiao, Binghai Yan

Discoveries of topological states and topological materials reshape our understanding of physics and materials over the last 15 years. First-principles calculations have been playing a significant role in bridging the theory of topology and experiments by predicting realistic topological materials. In this article, we overview the first-principles methodolog

B. Aimard, L. Aizawa, C. Alt, J. Asaadi

The $3 \times 1 \times 1$ m$^3$ demonstrator is a dual phase liquid argon time projection chamber that has recorded cosmic rays events in 2017 at CERN. The light signal in these detectors is crucial to provide precise timing capabilities. The performances of the photon detection system, composed of five PMTs, are discussed. The collected scintillation and el

Selim Bahadır, Didem Gözüpek, Oğuz Doğan

A sequence of vertices in a graph $G$ without isolated vertices is called a total dominating sequence if every vertex $v$ in the sequence has a neighbor which is adjacent to no vertex preceding $v$ in the sequence, and at the end every vertex of $G$ has at least one neighbor in the sequence. Minimum and maximum lengths of a total dominating sequence is the t

Svjetlana Fajfer, David Susič

We investigate nucleon decays to light invisible fermion mediated by the coloured scalar $\bar S_1= (\bar 3, 1, -2/3)$ and compare them with the results coming from the mediation of $S_1 = (\bar 3,1,1/3)$. In the case of $\bar S_1= (\bar 3, 1, -2/3)$ up-like quarks couple to the invisible fermion, while in the case of $S_1 = (\bar 3,1,1/3)$ the down-like qua

Thilo M. Siewert, Matthias Schmidt-Rubart, Dominik J. Schwarz

The Cosmic Radio Dipole is of fundamental interest to cosmology. Recent studies revealed open questions about the nature of the observed Cosmic Radio Dipole. We use simulated source count maps to test a linear and a quadratic estimator for its possible biases in the estimated dipole amplitude with respect to the masking procedure. We find a superiority of th

Benjamin Geiger, Juan Diego Urbina, Klaus Richter

We consider the fate of $1/N$ expansions in unstable many-body quantum systems, as realized by a quench across criticality, and show the emergence of ${\rm e}^{2λt}/N$ as a renormalized parameter ruling the quantum-classical transition and accounting nonperturbatively for the local divergence rate $λ$ of mean-field solutions. In terms of ${\rm e}^{2λt}/N$, q

Li Yuan, Shuning Chang, Ziyuan Huang, Yichen Zhou

This paper presents our solution to ACM MM challenge: Large-scale Human-centric Video Analysis in Complex Events\cite{lin2020human}; specifically, here we focus on Track3: Crowd Pose Tracking in Complex Events. Remarkable progress has been made in multi-pose training in recent years. However, how to track the human pose in crowded and complex environments ha

Maximilian Bachl, Joachim Fabini, Tanja Zseby

Low delay is an explicit requirement for applications such as cloud gaming and video conferencing. Delay-based congestion control can achieve the same throughput but significantly smaller delay than loss-based one and is thus ideal for these applications. However, when a delay- and a loss-based flow compete for a bottleneck, the loss-based one can monopolize

Michal Szanecki, Andrzej Niedzwiecki, Andrzej A. Zdziarski

We investigate the X-ray spectrum of the Seyfert galaxy NGC 4151 using the simultaneous Suzaku/NuSTAR observation and flux-resolved INTEGRAL spectra supplemented by Suzaku and XMM observations. Our best spectral solution indicates that the narrow Fe Kalpha line is produced in Compton-thin matter at the distance of several hundred gravitational radii. In such

Yinhao Li, Yutaro Iwamoto, Lanfen Lin, Rui Xu

Deep learning-based super-resolution (SR) techniques have generally achieved excellent performance in the computer vision field. Recently, it has been proven that three-dimensional (3D) SR for medical volumetric data delivers better visual results than conventional two-dimensional (2D) processing. However, deepening and widening 3D networks increases trainin

Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike

Solving optimization tasks based on functions and losses with a topological flavor is a very active, growing field of research in data science and Topological Data Analysis, with applications in non-convex optimization, statistics and machine learning. However, the approaches proposed in the literature are usually anchored to a specific application and/or to

Mathieu Blondel, Arthur Mensch, Jean-Philippe Vert

Computing the discrepancy between time series of variable sizes is notoriously challenging. While dynamic time warping (DTW) is popularly used for this purpose, it is not differentiable everywhere and is known to lead to bad local optima when used as a &#34;loss&#34;. Soft-DTW addresses these issues, but it is not a positive definite divergence: due to the b

Alexander Gheorghiu, Sonia Marin

The logic of Bunched Implications (BI) freely combines additive and multiplicative connectives, including implications; however, despite its well-studied proof theory, proof-search in BI has always been a difficult problem. The focusing principle is a restriction of the proof-search space that can capture various goal-directed proof-search procedures. In thi

Piotr Homola, Dmitriy Beznosko, Gopal Bhatta, Lukasz Bibrzycki

The Cosmic Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic ray ensembles (CRE): groups of a minimum of two CR with a common primary interaction vertex or the same parent particle. The CREDO program embraces testing known CR and CRE scenarios, and preparing t

Javier Hidalgo-Carrió, Daniel Gehrig, Davide Scaramuzza

Event cameras are novel sensors that output brightness changes in the form of a stream of asynchronous events instead of intensity frames. Compared to conventional image sensors, they offer significant advantages: high temporal resolution, high dynamic range, no motion blur, and much lower bandwidth. Recently, learning-based approaches have been applied to e

Javier Esparza, Stefan Kiefer, Jan Kretinsky, Maximilian Weininger

We study runtime monitoring of $\omega$-regular properties. We consider a simple setting in which a run of an unknown finite-state Markov chain $\mathcal M$ is monitored against a fixed but arbitrary $\omega$-regular specification $\varphi$. The purpose of monitoring is to keep aborting runs that are "unlikely" to satisfy the specification until $\mathcal M$

Vili Hätönen, Fiona Melzer

Decades of research on climate have provided a consensus that human activity has changed the climate and we are currently heading into a climate crisis. While public discussion and research efforts on climate change mitigation have increased, potential solutions need to not only be discussed but also effectively deployed. For preventing mismanagement and hol

Mohammed Mouçouf

We study the set $\mathcal{L}_{F}$ of all $F$-vector spaces $L(P)$ where $P$ is monic and splits over $F$ and $L(Q)$ denotes the set of linear recurrence sequences over $F$ with characteristic polynomial $Q$. We show that $\mathcal{L}_{F}$ can be endowed with two structures of graded commutative semiring. This study allows us to obtain, in compact forms, the

Mallika Irene Suresh, Philip St. J. Russell, Francesco Tani

We present a technique that uses noisy broadband pulse bursts generated by modulational instability to probe nonlinear processes, including infrared-inactive Raman transitions, in molecular gases. These processes imprint correlations between different regions of the noisy spectrum, which can be detected by acquiring single shot spectra and calculating the Pe

Shenxing Zhang

A linear recurrence sequence in a cyclotomic field produces a sequence of the generating fields of each term. We show that the later sequence is periodic after removing the first finite terms, and give a bound of its period. This can be applied to exponential sums.