December 2020 arXiv papers — page 108

Maice Costa, Yalin Sagduyu, Tugba Erpek, Muriel Médard

We consider a wireless communication network with an adaptive scheme to select the number of packets to be admitted and encoded for each transmission, and characterize the information timeliness. For a network of erasure channels and discrete time, we provide closed form expressions for the Average and Peak Age of Information (AoI) as functions of admission

Babak Vajdi Hokmabad, Suropriya Saha, Jaime Agudo-Canalejo, Ramin Golestanian

A common feature of biological self-organization is how active agents communicate with each other or their environment via chemical signaling. Such communications, mediated by self-generated chemical gradients, have consequences for both individual motility strategies and collective migration patterns. Here, in a purely physicochemical system, we use self-pr

Barun Maity, Poonam Chandra

We report the lowest frequency measurements of gamma-ray burst (GRB) 171205A with the upgraded Giant Metrewave Radio Telescope (uGMRT) covering a frequency range from 250--1450 MHz and a period of $4-937$ days. It is the first GRB afterglow detected at 250--500 MHz frequency range and the second brightest GRB detected with the uGMRT. Even though the GRB is o

Kursat Rasim Mestav, Xinyi Wang, Lang Tong

A deep learning approach is proposed to detect data and system anomalies using high-resolution continuous point-on-wave (CPOW) or phasor measurements. Both the anomaly and anomaly-free measurement models are assumed to have unknown temporal dependencies and probability distributions. Historical training samples are assumed for the anomaly-free model, while n

S. Bottoni, N. Cieplicka-Oryńczak, S. Leoni, B. Fornal

We present recent results on the structure of the one-valence-particle $^{41}$Ca and $^{49}$Ca, and one-valence-hole $^{47}$Ca, nuclei. The isotopes of interest were populated via the cold-neutron capture reactions $^{40}$Ca(n,$\gamma$), $^{48}$Ca(n,$\gamma$) and $^{46}$Ca(n,$\gamma$), respectively. The experiments were performed at the Institut Laue-Langevi

Yu-Chih Huang, Shin-Lin Shieh, Yu-Pin Hsu, Hao-Ping Cheng

In this paper, the problem of using uncoordinated multiple access (UMA) to serve a massive amount of heterogeneous users is investigated. Leveraging the heterogeneity, we propose a novel UMA protocol, called iterative collision resolution for slotted ALOHA (IRSA) with non-orthogonal multiple access (NOMA), to improve the conventional IRSA. In addition to the

Vinod N. Rao, R. Srikanth

Counterfactual quantum key distribution (QKD) enables two parties to share a secret key using an interaction-free measurement. Here, we point out that the efficiency of counterfactual QKD protocols can be enhanced by including non-counterfactual bits. This inclusion potentially gives rise to the possibility of noiseless attacks, in which Eve can gain knowled

Gal Vardi, Ohad Shamir

Understanding the implicit regularization (or implicit bias) of gradient descent has recently been a very active research area. However, the implicit regularization in nonlinear neural networks is still poorly understood, especially for regression losses such as the square loss. Perhaps surprisingly, we prove that even for a single ReLU neuron, it is impossi

Lior Gishboliner, Michael Krivelevich, Peleg Michaeli

We study the multicolour discrepancy of spanning trees and Hamilton cycles in graphs. As our main result, we show that under very mild conditions, the $r$-colour spanning-tree discrepancy of a graph $G$ is equal, up to a constant, to the minimum $s$ such that $G$ can be separated into $r$ equal parts by deleting $s$ vertices. This result arguably resolves th

Nicolas R. Bertini, Neven Bilic, Davi C. Rodrigues

We consider an action for gravity that, in addition to the Einstein-Hilbert term, contains a function of the Ricci scalar and the Gauss-Bonnet invariant. The specific form of the function considered is motivated by holographic cosmology. At background level the field equations imply modified Friedmann equations of the same form as those in the holographic co

Mahdi Sadeghi, Fabian Schrodt, Sebastian Otte, Martin V. Butz

The ability to flexibly bind features into coherent wholes from different perspectives is a hallmark of cognition and intelligence. Importantly, the binding problem is not only relevant for vision but also for general intelligence, sensorimotor integration, event processing, and language. Various artificial neural network models have tackled this problem wit

A. E. Phillips, M. Baggioli, T. W. Sirk, K. Trachenko

We present a theory of viscoelasticity of amorphous media, which takes into account the effects of confinement along one of three spatial dimensions. The framework is based on the nonaffine extension of lattice dynamics to amorphous systems, or nonaffine response theory. The size effects due to the confinement are taken into account via the nonaffine part of

S. I. Eidelman, A. V. Nefediev, P. N. Pakhlov, V. I. Zhukova

In 2018 the Belle II experiment, aimed at detailed studies of B-mesons, started operation at the electron-positron collider SuperKEKB at KEK (Japan). This was preceded by a long and quite successful work of the B-factories of previous generations, including the Belle experiment for which Belle II is a successor. This experiment is unique and has no analogues

Adam Hutchinson, Silvia Dalla, Timo Laitinen, Georgia A. de Nolfo

Gamma-ray emission during long-duration gamma-ray flare (LDGRF) events is thought to be caused mainly by $>$300 MeV protons interacting with the ambient plasma at or near the photosphere. Prolonged periods of the gamma-ray emission have prompted the suggestion that the source of the energetic protons is acceleration at a coronal mass ejection (CME)-driven sh

Benjamin Knorr, Chris Ripken

Affine gravity is a connection-based formulation of gravity that does not involve a metric. After a review of basic properties of affine gravity, we compute the tree-level scattering amplitude of scalar particles interacting gravitationally via the connection in a curved spacetime. We find that, while classically equivalent to general relativity, affine grav

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

The first observation of the suppressed semileptonic $B_s^0 \to K^-\mu^+\nu_\mu$ decay is reported. Using a data sample recorded in {\it pp} collisions in 2012 with the LHCb detector, corresponding to an integrated luminosity of 2 $\mathrm{fb}^{-1}$, the branching fraction \mbox{$\mathcal{B}(B_s^0 \to K^-\mu^+\nu_\mu)$} is measured to be $(1.06\pm0.05~(\math

Feliu Serra-Burriel, Pedro Delicado, Andrew T. Prata, Fernando M. Cucchietti

Wildfires have become one of the biggest natural hazards for environments worldwide. The effects of wildfires are heterogeneous, meaning that the magnitude of their effects depends on many factors such as geographical region, climate and land cover/vegetation type. Yet, which areas are more affected by these events remains unclear. Here we present a novel ap

L. V. Bravina, G. Kh. Eyyubova, V. L. Korotkikh, I. P. Lokhtin

Data from the Large Hadron Collider on elliptic flow correlations at low and high $p_T$ from Pb+Pb collisions at $\sqrt{s_{NN}} = 5.02$~TeV are analyzed and interpreted in the framework of the HYDJET++ model. This model allows us to describe simultaneously the region of both low and high transverse momenta and, therefore, to reproduce the experimentally obse

Iván Pérez, Enrique Vallejo, Ramón Beivide

Minimizing latency and power are key goals in the design of NoC routers. Different proposals combine lookahead routing and router bypass to skip the arbitration and buffering, reducing router delay. However, the conditions to use them requires completely empty buffers in the intermediate routers. This restricts the amount of flits that use the bypass pipelin

Marcin Bury, Alexei Prokudin, Alexey Vladimirov

We perform the global analysis of polarized Semi-Inclusive Deep Inelastic Scattering (SIDIS), pion-induced polarized Drell-Yan (DY), and $W^\pm/Z$ boson production data and extract the Sivers function for $u$, $d$, $s$ and for sea-quarks. We use the framework of transverse momentum dependent factorization at N$^3$LO accuracy. The Qiu-Sterman function is dete

Xin-Yi Pan, Christian Kurtsiefer, Alexander Ling, James A. Grieve

The temperature dependence of the refractive indices of potassium titanyl phosphate (KTP) are shown to enable quasi-phasematched type II spontaneous parametric downconversion (SPDC) with low temperature sensitivity. Calculations show the effect to be maximised for emission of photons at around 1165nm, as well as producing potentially useful regions for wavel

Maike Scholtes, Lukas Westhofen, Lara Ruth Turner, Katrin Lotto

Verification and validation of automated driving functions impose large challenges. Currently, scenario-based approaches are investigated in research and industry, aiming at a reduction of testing efforts by specifying safety relevant scenarios. To define those scenarios and operate in a complex real-world design domain, a structured description of the envir

Benjamin Rossman

We establish nearly tight bounds on the expected shrinkage of decision lists and DNF formulas under the $p$-random restriction $\mathbf R_p$ for all values of $p \in [0,1]$. For a function $f$ with domain $\{0,1\}^n$, let $\mathrm{DL}(f)$ denote the minimum size of a decision list that computes $f$. We show that \[ \mathbb E[\ \mathrm{DL}(f{\upharpoonright}\

Nemanja Stefan Perović, Le-Nam Tran, Marco Di Renzo, Mark F. Flanagan

The main difficulty concerning optimizing the mutual information (MI) in reconfigurable intelligent surface (RIS)-aided communication systems with discrete signaling is the inability to formulate this optimization problem in an analytically tractable manner. Therefore, we propose to use the cutoff rate (CR) as a more tractable metric for optimizing the MI an

Wenting Cheng, Emil Prodan, Camelia Prodan

Quantum Hall physics has been theoretically predicted in 4-dimensions and higher. In hypothetical 2n-dimensions, the topological characters of both the bulk and the boundary are manifested as quantized non-linear transport coefficients that connect, respectively, to the n-th Chern number of the bulk gap projection and to the n-th winding number of the Weyl s

Antonio Remiro-Azócar, Anna Heath, Gianluca Baio

This commentary regards a recent simulation study conducted by Aouni, Gaudel-Dedieu and Sebastien, evaluating the performance of different versions of matching-adjusted indirect comparison (MAIC) in an anchored scenario with a common comparator. The simulation study uses survival outcomes and the Cox proportional hazards regression as the outcome model. It c

Sebastian J. Vidal, Paula Cadavid, Pablo M. Rodriguez

Evolution algebras are non-associative algebras. In this work we provide an extension of this class of algebras, in the context of Hilbert spaces, capable to deal with infinite-dimensional spaces. We illustrate the applicability of our approach by discussing a connection with discrete-time Markov chains with countable state space.

Sander Beckers

In previous work with Joost Vennekens I proposed a definition of actual causation that is based on certain plausible principles, thereby allowing the debate on causation to shift away from its heavy focus on examples towards a more systematic analysis. This paper contributes to that analysis in two ways. First, I show that our definition is in fact a formali

Daniele Antonio Di Pietro, Jérôme Droniou, André Harnist

We derive novel error estimates for Hybrid High-Order (HHO) discretizations of Leray-Lions problems set in W^(1,p) with p in (1,2]. Specifically, we prove that, depending on the degeneracy of the problem, the convergence rate may vary between (k+1)(p-1) and (k+1), with k denoting the degree of the HHO approximation. These regime-dependent error estimates are

Hao Pan, Zhi-Wei Sun

For each $n=0,1,2,\ldots$, the central trinomial coefficient $T_n$ is the coefficient of $x^n$ in the expansion of $(x^2+x+1)^n$. Let $p>3$ be a prime, and let $n$ be any positive integer. In 2016, the second author conjectured that the quotient $(T_{pn}-T_n)/(pn)^2$ is always a $p$-adic integer. In this paper, we confirm this conjecture, and further prove t

Isinsu Katircioglu, Helge Rhodin, Jörg Spörri, Mathieu Salzmann

Self-supervised detection and segmentation of foreground objects aims for accuracy without annotated training data. However, existing approaches predominantly rely on restrictive assumptions on appearance and motion. For scenes with dynamic activities and camera motion, we propose a multi-camera framework in which geometric constraints are embedded in the fo

R. Ringle, G. Bollen, K. Lund, C. Nicoloff

Linear gas stoppers are widely used to convert high-energy, rare-isotope beams and reaction products into low-energy beams with small transverse emittance and energy spread. Stopping of the high-energy ions is achieved through interaction with a buffer gas, typically helium, generating large quantities of He$^+$/e$^-$ pairs. The Advanced Cryogenic Gas Stoppe

Zhihao Xia, Michaël Gharbi, Federico Perazzi, Kalyan Sunkavalli

We introduce a neural network-based method to denoise pairs of images taken in quick succession, with and without a flash, in low-light environments. Our goal is to produce a high-quality rendering of the scene that preserves the color and mood from the ambient illumination of the noisy no-flash image, while recovering surface texture and detail revealed by

Enrico Cannizzaro, Andrea Caputo, Laura Sberna, Paolo Pani

We investigate the linear dynamics of an electromagnetic field propagating in curved spacetime in the presence of plasma. The dynamical equations are generically more involved and richer than the effective Proca equation adopted as a model in previous work. We discuss the general equations and focus on the case of a cold plasma in the background of a spheric

Noga Alon, Michael Krivelevich

We prove that for every graph $H$ of maximum degree at most $3$ and for every positive integer $q$ there is a finite $f=f(H,q)$ such that every $K_f$-minor contains a subdivision of $H$ in which every edge is replaced by a path whose length is divisible by $q$. For the case of cycles we show that for $f=O(q \log q)$ every $K_f$-minor contains a cycle of leng

Jürg Fröhlich, Antti Knowles, Benjamin Schlein, Vedran Sohinger

We study interacting Bose gases in thermal equilibrium on a lattice. We establish convergence of the grand canonical Gibbs states of such gases to their mean-field (classical field) and large-mass (classical particle) limits. The former is a classical field theory for a complex scalar field with quartic self-interaction. The latter is a classical theory of p

Daniel Najer, Natasha Tomm, Alisa Javadi, Alexander R. Korsch

We present a surface passivation method that reduces surface-related losses by almost two orders of magnitude in a highly miniaturized GaAs open microcavity. The microcavity consists of a curved dielectric distributed Bragg reflector (DBR) with radius $\sim 10$ $\mu$m paired with a GaAs-based heterostructure. The heterostructure consists of a semiconductor D

Eric T. Mortenson

Using a heuristic that relates Appell--Lerch functions to divergent partial theta functions one can expand Hecke-type double-sums in terms of Appell--Lerch functions. We give examples where the heuristic can be used as a guide to evaluate analogous triple-sums in terms of Appell--Lerch functions or false theta functions.

Erwan Le Merrer, Benoit Morgan, Gilles Trédan

Shadow banning consists for an online social network in limiting the visibility of some of its users, without them being aware of it. Twitter declares that it does not use such a practice, sometimes arguing about the occurrence of "bugs" to justify restrictions on some users. This paper is the first to address the plausibility or not of shadow banning on a m

Aikan Shykhmamedov, Efrosiniia Karatetskaia, Alexey Kazakov, Nataliya Stankevich

We study bifurcation mechanisms for the appearance of hyperchaotic attractors in three-dimensional diffeomorphisms, i.e., such attractors whose orbits have two positive Lyapunov exponents in numerical experiments. In order to possess this property periodic orbits belonging to the attractor should have two-dimensional unstable invariant manifolds. For realiza

Alex Bäuerle, Patrick Albus, Raphael Störk, Tina Seufert

Due to the success of deep learning (DL) and its growing job market, students and researchers from many areas are interested in learning about DL technologies. Visualization has proven to be of great help during this learning process. While most current educational visualizations are targeted towards one specific architecture or use case, recurrent neural ne

Jaap-Henk Hoepman

As a response to the COVID-19 pandemic digital contact tracing has been proposed as a tool to support the health authorities in their quest to determine who has been in close and sustained contact with a person infected by the coronavirus. In April 2020 Google and Apple released the Google Apple Exposure Notification (GAEN) framework, as a decentralised and

Ming-Zhu Liu, Li-Sheng Geng

The $D^{(\ast)}\Xi_{cc}^{(\ast)}$ system and $\bar{\Xi}_{cc}^{(\ast)}\Xi_{cc}^{(\ast)}$ system can be related to the $D^{(\ast)}\bar{D}^{(\ast)}$ system via heavy anti-quark di-quark symmetry (HADS). In this work, we employ a contact-range effective field theory to systematically investigate the likely existence of molecules in these systems in terms of the

Jaan Einasto

We study biasing as a physical phenomenon by analysing power spectra (PS) and correlation functions (CF) of simulated galaxy samples and dark matter (DM) samples. We apply an algorithm based on the local densities of particles, $\rho$, to form populations of simulated galaxies, using particles with $\rho \ge \rho_0$. We calculate two-point CF of projected (2

Manisha Luthra, Boris Koldehofe, Jonas Höchst, Patrick Lampe

Emerging network architectures like Information-centric Networking (ICN) offer simplicity in the data plane by addressing named data. Such flexibility opens up the possibility to move data processing inside network elements for high-performance computation, known as in-network processing. However, existing ICN architectures are limited in terms of data plane

Carl-Henrik Dahlqvist, Olivier Absil

High-contrast imaging (HCI) is one of the most challenging techniques for exoplanet detection. It relies on sophisticated data processing to reach high contrasts at small angular separations. Most data processing techniques of this type are based on the angular differential imaging (ADI) observing strategy to perform the reference PSF subtraction, and genera

Yuanwei Liu, Xiao Liu, Xinyu Gao, Xidong Mu

The ongoing surge in applications of robotics brings both opportunities and challenges for the fifth-generation (5G) and beyond (B5G) of communication networks. This article focuses on 5G/B5G-enabled terrestrial robotic communications with an emphasis on distinct characteristics of such communications. Firstly, signal and spatial modeling for robotic communi

C. M. Raduta, A. A. Raduta

The Bogoliubov transformation for a monopole boson induces an unitary transformation connecting the Fock spaces of initial and correlated boson-s. Here we provide a very simple method for deriving the analytical expression for the overlap matrix of the basis states generating the two boson spaces.

Adrián Llinares, Dragan Vukotić

We prove two sharp estimates for the subspace of a standard weighted Bergman space that consists of functions vanishing at a given point (with prescribed multiplicity).

Ben Wang, Liang Xu, Lijian Zhang

As a method to extract information from optical system, imaging can be viewed as a parameter estimation problem. The fundamental precision in locating one emitter or estimating the separation between two incoherent emitters is bounded below by the multiparameter quantum Cramer-Rao bound (QCRB).Multiparameter QCRB gives an intrinsic bound in parameter estimat

Apostolos Chalkis, Emmanouil Christoforou, Ioannis Z. Emiris, Theodore Dalamagas

We discuss and extend a powerful, geometric framework to represent the set of portfolios, which identifies the space of asset allocations with the points lying in a convex polytope. Based on this viewpoint, we survey certain state-of-the-art tools from geometric and statistical computing in order to handle important and difficult problems in digital finance.

Anurag Chowdhury, Arun Ross, Prabu David

Automatic speaker recognition algorithms typically characterize speech audio using short-term spectral features that encode the physiological and anatomical aspects of speech production. Such algorithms do not fully capitalize on speaker-dependent characteristics present in behavioral speech features. In this work, we propose a prosody encoding network calle

Stephen Lindsly, Maya Gupta, Cooper Stansbury, Indika Rajapakse

The mammalian adaptive immune system has evolved over millions of years to become an incredibly effective defense against foreign antigens. The adaptive immune system's humoral response creates plasma B cells and memory B cells, each with their own immunological objectives. The affinity maturation process is widely viewed as a heuristic to solve the global o

Mikhail I. Katsnelson, Vitaly Vanchurin

It was recently shown that the Madelung equations, that is, a hydrodynamic form of the Schr\"odinger equation, can be derived from a canonical ensemble of neural networks where the quantum phase was identified with the free energy of hidden variables. We consider instead a grand canonical ensemble of neural networks, by allowing an exchange of neurons with a

Chang Hyun Park, Ilias Vougioukas, Andreas Sandberg, David Black-Schaffer

As memory capacity has outstripped TLB coverage, large data applications suffer from frequent page table walks. We investigate two complementary techniques for addressing this cost: reducing the number of accesses required and reducing the latency of each access. The first approach is accomplished by opportunistically "flattening" the page table: merging two

Alejandro Aviles, Georgios Valogiannis, Mario A. Rodriguez-Meza, Jorge L. Cervantes-Cota

We develop a framework to compute the redshift space power spectrum (PS), with kernels beyond Einstein-de Sitter (EdS), that can be applied to a wide variety of generalized cosmologies. We build upon a formalism that was recently employed for standard cosmology in Chen, Vlah & White (2020), and utilize an expansion of the density-weighted velocity moment gen

P. Nieves, J. Tranchida, S. Arapan, D. Legut

We present a methodology based on the N\'{e}el model to build a classical spin-lattice Hamiltonian for cubic crystals capable of describing magnetic properties induced by the spin-orbit coupling like magnetocrystalline anisotropy and anisotropic magnetostriction, as well as exchange magnetostriction. Taking advantage of the analytical solutions of the N\'{e}

Manisha Luthra, Johannes Pfannmüller, Boris Koldehofe, Jonas Höchst

Information-centric Networking (ICN) is an emerging Internet architecture that offers promising features, such as in-network caching and named data addressing, to support the edge computing paradigm, in particular Internet-of-Things (IoT) applications. ICN can benefit from Complex Event Processing (CEP), which is an in-network processing paradigm to specify

Milko Estrada, Francisco Tello-Ortiz

We provide a new regular black hole solution in $(2+1)$ dimensions with presence of matter fields in the energy momentum tensor, having its core a flat or (A)dS structure. Since the first law of thermodynamics for regular black holes is modified by the presence of the matter fields, we provide a new version of the first law, where a local definition of the v

Quan Yu, Xinzhen Zhang, Zheng-Hai Huang

Recently, a tensor factorization based method for a low tubal rank tensor completion problem of a third order tensor was proposed, which performed better than some existing methods. Tubal rank is only defined on one mode of third order tensor without low rank structure in the other two modes. That is, low rank structures on the other two modes are missing. M

Yi Xiang Marcus Tan, Penny Chong, Jiamei Sun, Ngai-Man Cheung

Few-shot classifiers excel under limited training samples, making them useful in applications with sparsely user-provided labels. Their unique relative prediction setup offers opportunities for novel attacks, such as targeting support sets required to categorise unseen test samples, which are not available in other machine learning setups. In this work, we p

Junyan Cao, Mihai Paun

The current paper represents the first part: it contains the results concerning the lifting of twisted canonical sections defined on an infinitesimal neighborhood of the central fiber of a smooth, proper K\"ahler family which verify a natural L2 condition.

Hugo Lhachemi, Christophe Prieur

This paper investigates the output feedback setpoint regulation control of a reaction-diffusion equation by means of boundary control. The considered reaction-diffusion plant may be open-loop unstable. The proposed control strategy consists of the coupling of a finite-dimensional observer and a PI controller in order to achieve the boundary setpoint regulati

Jouni J. Takalo

We show that the time series of sunspot-group areas has a gap, the so-called Gnevyshev gap (GG), between ascending and descending phases of the cycle and especially so for the even-numbered cycles. For the odd cycles this gap is less obvious, and is only a small decline after the maximum of the cycle. We resample the cycles to have the same length of 3945 da

Jaider Blanco, Bernardo Uribe, Konrad Waldorf

We use Segal-Mitchison's cohomology of topological groups to define a convenient model for topological gerbes. We introduce multiplicative gerbes over topological groups in this setup and we define its representations. For a specific choice of representation, we construct its category of endomorphisms and we show that it induces a new multiplicative gerbe ov

Siegfried Hörmann, Fatima Jammoul

In practice most functional data cannot be recorded on a continuum, but rather at discrete time points. It is also quite common that these measurements come with an additive error, which one would like eliminate for the statistical analysis. When the measurements for each functional datum are taken on the same grid, the underlying signal-plus-noise model can

Junru Ma, Jinquan Luo

Symbol-pair codes are proposed to combat pair-errors in symbol-pair read channels. The minimum symbol-pair distance is of significance in determining the error-correcting capability of a symbol-pair code. Maximum distance separable (MDS) symbol-pair codes are optimal in the sense that such codes can achieve the Singleton bound. In this paper, two new classes

Hai-Liang Li, Ling-Yun Shou

A fluid-particle model is investigated in the present paper, which consists of the compressible Navier-Stokes equations coupled with the Vlasov equation though a nonlinear drag force. We consider the initial value problem for the one-dimensional compressible Navier-Stokes-Vlasov system and establish the global existence and uniqueness of the weak solution fo

Bernd Sturmfels, Simon Telen

We relate scattering amplitudes in particle physics to maximum likelihood estimation for discrete models in algebraic statistics. The scattering potential plays the role of the log-likelihood function, and its critical points are solutions to rational function equations. We study the ML degree of low-rank tensor models in statistics, and we revisit physical

Tewodros Amdeberhan, Adriana Duncan, Victor H. Moll, Vaishavi Sharma

Motivated by an expression by Persson and Strang on an integral involving Legendre polynomials, stating that the square of $P_{2n+1}(x)/x$ integrated over $[-1,1]$ is always $2$, we present analog results for Hermite, Chebyshev, Laguerre and Gegenbauer polynomials as well as the original Legendre polynomial with even index.

Takahiro Hashinaga, Toru Kajigaya

Let $M=G/K$ be a Hermitian symmetric space of noncompact type. We provide a way of constructing $K$-equivariant embeddings from $M$ to its tangent space $T_oM$ at the origin by using the polarity of the $K$-action. As an application, we reconstruct the $K$-equivariant holomorphic embedding so called the Harish-Chandra realization and the $K$-equivariant symp

Shichao Zhang, Jiaye Li

KNN classification is an improvisational learning mode, in which they are carried out only when a test data is predicted that set a suitable K value and search the K nearest neighbors from the whole training sample space, referred them to the lazy part of KNN classification. This lazy part has been the bottleneck problem of applying KNN classification due to

Kristóf Bérczi, Tamás Schwarcz

Given a matroid together with a coloring of its ground set, a subset of its elements is called rainbow colored if no two of its elements have the same color. We show that if a binary matroid of rank $r$ is colored with exactly $r$ colors, then $M$ either contains a rainbow colored circuit or a monochromatic cut. As the class of binary matroids is closed unde

V. Baru, E. Epelbaum, A. A. Filin, C. Hanhart

The dipion transitions $\Upsilon(10860)\to\pi^+\pi^-\Upsilon(nS)$ ($n=1,2,3$) are studied in the framework of a unitary and analytic coupled-channel formalism previously developed for analysing experimental data on the bottomoniumlike states $Z_b(10610)$ and $Z_b(10650)$ [Phys. Rev. D 98, 074023 (2018)] and predicting the properties of their spin partners [P

Wenqing Zhang, Yang Qiu, Minghui Liao, Rui Zhang

Scene text detection, which is one of the most popular topics in both academia and industry, can achieve remarkable performance with sufficient training data. However, the annotation costs of scene text detection are huge with traditional labeling methods due to the various shapes of texts. Thus, it is practical and insightful to study simpler labeling metho

Kiwoon Choi, Sang Hui Im, Chang Sub Shin

The axion is a light pseudoscalar particle postulated to solve issues with the Standard Model, including the strong CP problem and the origin of dark matter. In recent years, there has been remarkable progress in the physics of axions in several directions. An unusual type of axion-like particle termed the relaxion was proposed as a new solution to the weak

Harry Desmond, Jeremy Sakstein, Bhuvnesh Jain

We perform a novel test of General Relativity by measuring the gravitational constant in the Large Magellanic Cloud (LMC). The LMC contains six well-studied Cepheid variable stars in detached eclipsing binaries. Radial velocity and photometric observations enable a complete orbital solution, and precise measurements of the Cepheids' periods permit detail

Ujjwal Upadhyay, Prerana Mukherjee

Traditional adversarial attacks rely upon the perturbations generated by gradients from the network which are generally safeguarded by gradient guided search to provide an adversarial counterpart to the network. In this paper, we propose a novel mechanism of generating adversarial examples where the actual image is not corrupted rather its latent space repre

Xicheng Zhang

In this paper we study the global boundedness for the solutions to a class of possibly degenerate parabolic equations by De-Giorgi's iteration. As applications, we show the existence of weak solutions for possibly degenerate stochastic differential equations with singular diffusion and drift coefficients. Moreover, by the Markov selection theorem of Krylov [

Michael Merz, Liran Wang, Thomas Wolf, Peter Nagel

Nematic phase transitions in high-temperature superconductors have a strong impact on the electronic properties of these systems. BaFe$_2$As$_2$,\@ with an established nematic transition around 137 K induced by magnetic fluctuations, and BaNi$_2$As$_2$,\@ a non-magnetic analog of BaFe$_2$As$_2$ with a structural transition in the same temperature range,\@ sh

Daniel Cunnington, Alessandra Russo, Mark Law, Jorge Lobo

Inductive Logic Programming (ILP) systems learn generalised, interpretable rules in a data-efficient manner utilising existing background knowledge. However, current ILP systems require training examples to be specified in a structured logical format. Neural networks learn from unstructured data, although their learned models may be difficult to interpret an

Dilnoza Muslimova, Hans van Kippersluis, Cornelius A. Rietveld, Stephanie von Hinke

This paper shows how nature (i.e., one's genetic endowments) and nurture (i.e., one's environment) interact in producing educational attainment. Genetic endowments are measured using a polygenic score for educational attainment, while we use birth order as an important environmental determinant of educational attainment. Since genetic endowments are randomly

Zhijian Qiao, Hanjiang Hu, Weiang Shi, Siyuan Chen

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition mo

Marco Medici, Søren Marcus Pedersen, Maurizio Canavari, Thomas Anken

To develop precision agriculture (PA) to its full potential and make agriculture progress toward sustainability and resilience, appropriate criteria for the economic assessment are recognised as being one of the most significant issues requiring urgent and ongoing attention. In this work, we develop a web-tool supporting the assessment of the net economic be

Clinton T. Conley, Jan Grebík, Oleg Pikhurko

For an $r$-tuple $(\gamma_1,\ldots,\gamma_r)$ of special orthogonal $d\times d$ matrices, we say that the Euclidean $(d-1)$-dimensional sphere $S^{d-1}$ is $(\gamma_1,\ldots,\gamma_r)$-divisible if there is a subset $A\subseteq S^{d-1}$ such that its translations by the rotations $\gamma_1,\ldots,\gamma_r$ partition the sphere. Motivated by some old open que

Vincent Bouget, Dominique Béréziat, Julien Brajard, Anastase Charantonis

Short- or mid-term rainfall forecasting is a major task with several environmental applications such as agricultural management or flood risk monitoring. Existing data-driven approaches, especially deep learning models, have shown significant skill at this task, using only rainfall radar images as inputs. In order to determine whether using other meteorologi

Xing Huang, Feng-Yu Wang

By using Zvonkin's transformation and a two-step fixed point argument in distributions, the well-posedness and regularity estimates are derived for singular McKean-Vlasov SDEs with distribution dependent noise, where the drift contains a term growing linearly in space and distribution and a locally integrable term independent of distribution, while the noise

Renato Maria Prisco, Francesco Tramontano

We propose a novel local subtraction scheme for the computation of Next-to-Leading Order contributions to theoretical predictions for scattering processes in perturbative Quantum Field Theory. With respect to well known schemes proposed since many years that build upon the analysis of the real radiation matrix elements, our construction starts from the loop

Rishi Hazra, Sonu Dixit, Sayambhu Sen

Recently, there has been a great deal of research in emergent communication on artificial agents interacting in simulated environments. Recent studies have revealed that, in general, emergent languages do not follow the compositionality patterns of natural language. To deal with this, existing works have proposed a limited channel capacity as an important co

Haijun Liu, Yanxia Chai, Xiaoheng Tan, Dong Li

In this letter, we propose a conceptually simple and effective dual-granularity triplet loss for visible-thermal person re-identification (VT-ReID). In general, ReID models are always trained with the sample-based triplet loss and identification loss from the fine granularity level. It is possible when a center-based loss is introduced to encourage the intra

Yuexin Wu, Xiaolei Huang

Rating prediction is a core problem in recommender systems to quantify user's preferences towards items, however, rating imbalance naturally roots in real-world user ratings that cause biased predictions and lead to poor performance on tail ratings. While existing approaches in the rating prediction task deploy weighted cross-entropy to re-weight training sa

Giorgio Picci, Wenqi Cao, Anders Lindquist

We study modeling and identification of processes with a spectral density matrix of low rank. Equivalently, we consider processes having an innovation of reduced dimension for which Prediction Error Methods (PEM) algorithms are not directly applicable. We show that these processes admit a special feedback structure with a deterministic feedback channel which

Matteo Castiglioni, Nicola Gatti

We focus on the scenario in which an agent can exploit his information advantage to manipulate the outcome of an election. In particular, we study district-based elections with two candidates, in which the winner of the election is the candidate that wins in the majority of the districts. District-based elections are adopted worldwide (e.g., UK and USA) and

Bernardo González Merino, Rafael Villa

We give a uniform approximation of the characteristic function of the boundary of a centrally symmetric n-dimensional compact and convex set by homogeneous polynomials of even degree $d$ fulfilling $|g_d-1|\leq E/d^{1/2-\beta}$, for every $\beta>0$, large enough $d$, and some constant $E$ only depending on $n$ and $K$. In particular, this proves a conjecture

Srijita Pal, Somnath Bharadwaj, Abhik Ghosh, Samir Choudhuri

We apply the Tapered Gridded Estimator (TGE) for estimating the cosmological 21-cm power spectrum from $150 \, {\rm MHz}$ GMRT observations which corresponds to the neutral hydrogen (HI) at redshift $z = 8.28$. Here TGE is used to measure the Multi-frequency Angular Power Spectrum (MAPS) $C_{\ell}(\Delta\nu)$ first, from which we estimate the 21-cm power spe

Eef van Beveren, George Rupp

The low and approximately equal masses of the scalar mesons $f_0(980)$ and $a_0(980)$, as well as their relatively small decay widths, are impossible to understand in terms of standard $P$-wave quark-antiquark states. Here, these mesons are studied in a unitarised quark-meson model, together with the other light isoscalar scalar $f_0(500)$, as members of a c

Andrey L. Kutepov

A detailed account of the implementation of equations of the Relativistic Density Functional Theory (RDFT) using basis sets of APW/LAPW type with flexible extensions provided by local orbitals is given. Earlier discoveries of the importance of the High Derivative Local Orbital (HDLO) extension of APW/LAPW basis set for enhancing the accuracy of DFT calculati

Philipp Isserstedt, Christian S. Fischer, Thorsten Steinert

We present a method to compute thermodynamic quantities within functional continuum frameworks that is independent of the employed truncation. As a proof of principle, we first apply it to a Nambu-Jona-Lasinio model in mean-field approximation. Then, we use the method with solutions obtained from a coupled set of truncated Dyson-Schwinger equations for the q

Mohsen Moradi, Amir Mozammel, Kangjian Qin, Erdal Arikan

Performance and complexity of sequential decoding of polarization-adjusted convolutional (PAC) codes is studied. In particular, a performance and computational complexity comparison of PAC codes with 5G polar codes and convolutional codes is given. A method for bounding the complexity of sequential decoding of PAC codes is proposed.

Tung Ten Yong

In this paper, we show that Quantum Mechanics does not admit ontological models, in the sense that the quantum state of a system cannot correspond to a set of physical states representing the independent reality of the system. We show, via two thought experiments based on the Wigner's friend scenario, that if the ontic state of physical systems in the lab is