December 2020 arXiv papers — page 86

Mingzhou Yin, Roy S. Smith

The low-complexity assumption in linear systems can often be expressed as rank deficiency in data matrices with generalized Hankel structure. This makes it possible to denoise the data by estimating the underlying structured low-rank matrix. However, standard low-rank approximation approaches are not guaranteed to perform well in estimating the noise-free ma

Amit Klein

We analyze the prandom pseudo random number generator (PRNG) in use in the Linux kernel (which is the kernel of the Linux operating system, as well as of Android) and demonstrate that this PRNG is weak. The prandom PRNG is in use by many "consumers" in the Linux kernel. We focused on three consumers at the network level -- the UDP source port generation algo

Vajira Thambawita, Steven Hicks, Pål Halvorsen, Michael A. Riegler

Segmentation of findings in the gastrointestinal tract is a challenging but also an important task which is an important building stone for sufficient automatic decision support systems. In this work, we present our solution for the Medico 2020 task, which focused on the problem of colon polyp segmentation. We present our simple but efficient idea of using a

David Rossell, Oriol Abril, Anirban Bhattacharya

We propose the approximate Laplace approximation (ALA) to evaluate integrated likelihoods, a bottleneck in Bayesian model selection. The Laplace approximation (LA) is a popular tool that speeds up such computation and equips strong model selection properties. However, when the sample size is large or one considers many models the cost of the required optimiz

Moritz Beller, Vince Orgovan, Spencer Buja, Thomas Zimmermann

To improve software developers' productivity has been the holy grail of software engineering research. But before we can claim to have improved it, we must first be able to measure productivity. This is far from trivial. In fact, two separate research lines on software engineers' productivity have co-existed almost in complete isolation for a long time: auto

Nando Metzger

3D city models can be generated from aerial images. However, the calculated DSMs suffer from noise, artefacts, and data holes that have to be manually cleaned up in a time-consuming process. This work presents an approach that automatically refines such DSMs. The key idea is to teach a neural network the characteristics of urban area from reference data. In

Jaco Fuchs, Nicolas Douguet, Stefan Donsa, Fernando Martin

Realistic attosecond wave packets have complex profiles that, in dispersive conditions, rapidly broaden or split into multiple components. Such behaviors are encoded in sharp features of the wave packet spectral phase. Here, we exploit the quantum beating between one- and two-photon transitions in an attosecond photoionization experiment to measure the photo

Iva Laginja, Remi Soummer, Laurent M. Mugnier, Laurent Pueyo

This paper presents the setup for empirical validations of the Pair-based Analytical model for Segmented Telescope Imaging from Space (PASTIS) tolerancing model for segmented coronagraphy. We show the hardware configuration of the High-contrast imager for Complex Aperture Telescopes (HiCAT) testbed on which these experiments will be conducted at an intermedi

Oliver Atkinson, Christoph Englert, Panagiotis Stylianou

Sizeable exotic Higgs boson production through gluon fusion via top quark loops is correlated with large Higgs decay probabilities into top quark final states, if these are kinematically accessible. It is known that $gg\to S \to t\bar t$ is particularly susceptible to signal-background interference effects that can significantly impact discovery sensitivitie

Dhiman Bhowmick, Abhinava Chatterjee, Prasanta K. Panigrahi, Pinaki Sengupta

We demonstrate that low-lying triplon excitations in a bilayer Heisenberg antiferromagnet provide a promising avenue to realize magnetic analogs of twisted superfluid and supersolid phases that were recently reported for two-component ultracold atomic condensate in an optical lattice. Using a cluster Gutzwiller mean-field theory, we establish that Dzyaloshin

Ravi Joshi, Michele Fumagalli, Raghunathan Srianand, Pasquier Noterdaeme

We report the detection of the host galaxy of a damped Ly$\alpha$ system (DLA) with log N(HI) $ [\rm cm^{-2}]$ = $21.0 \pm 0.10$ at $z \approx 3.0091$ towards the background quasar SDSS J011852+040644 using the Palomar Cosmic Web Imager (PCWI) at the Hale (P200) telescope. We detect Ly$\alpha$ emission in the dark core of the DLA trough at a 3.3$\sigma$ conf

Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie

Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the wild. Despite their ubiquity in the real-world deployments, these distribution shifts are under-represented in the datasets widely used in the ML community today. To address this

Laura J. Murphy, Jose H. Groh, Sylvia Ekstrom, Georges Meynet

Understanding the nature of the first stars is key to understanding the early universe. With new facilities such as JWST we may soon have the first observations of the earliest stellar populations, but to understand these observations we require detailed theoretical models. Here we compute a grid of stellar evolution models using the Geneva code with the aim

Mingzhe Li, Xiuying Chen, Min Yang, Shen Gao

Eye-catching headlines function as the first device to trigger more clicks, bringing reciprocal effect between producers and viewers. Producers can obtain more traffic and profits, and readers can have access to outstanding articles. When generating attractive headlines, it is important to not only capture the attractive content but also follow an eye-catchi

Mannque Rho

I discuss how the axial current coupling constant $g_A$ renormalized in scale symmetric chiral EFT defined at a chiral matching scale impacts on the axial current matrix elements on beta decays in nuclei with and without neutrinos. The "quenched" $g_A$ observed in nuclear superallowed Gamow-Teller transitions, a long-standing puzzle in nuclear physics, is sh

Petr Kosenko, Giulio Tiozzo

We prove that the hitting measure is singular with respect to Lebesgue measure for any random walk on a cocompact Fuchsian group generated by translations joining opposite sides of a symmetric hyperbolic polygon. Moreover, the Hausdorff dimension of the hitting measure is strictly less than 1. A similar statement is proven for Coxeter groups. Along the way,

Yuyue Yan, Tomohisa Hayakawa

The stability property of the loss-aversion-based noncooperative switched systems with quadratic payoffs is investigated. In this system, each agent adopts the lower sensitivity parameter in the myopic pseudo-gradient dynamics for the case of losing utility than gaining utility, and both systems' dynamics and switching events (conditions) are depending on ag

Andrea Lucchini, Luca Sabatini, Pablo Spiga

We show that, for every transitive group $G$ of degree $n\ge 2$, the largest abelian quotient of $G$ has cardinality at most $4^{n/\sqrt{\log_2 n}}$. This gives a positive answer to a 1989 outstanding question of L\'aszl\'o Kov\'acs and Cheryl Praeger.

Soumya Chakrabarti

We consider an extended scalar-tensor theory of gravity where the action has two interacting scalar fields, a Brans-Dicke field which makes the effective Newtonian constant a function of coordinates and a Higgs field which has derivative and non-derivative interaction with the lagrangian. There is a non-trivial interaction between the two scalar fields which

Giacomo Mauro D'Ariano, Federico Faggin

We explore definite theoretical assertions about consciousness, starting from a non-reductive psycho-informational solution of David Chalmers's 'hard problem', based on the hypothesis that a fundamental property of 'information' is its experience by the supporting 'system'. The kind of information involved in consciousness needs to be quantum for multiple re

Alexander C. Forse, Céline Merlet, Clare P. Grey, John M. Griffin

Porous carbonaceous materials have many important industrial applications including energy storage, water purification, and adsorption of volatile organic compounds. Most of their applications rely upon the adsorption of molecules or ions within the interior pore volume of the carbon particles. Understanding the behaviour and properties of adsorbate species

Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu

Cycle-consistent training is widely used for jointly learning a forward and inverse mapping between two domains of interest without the cumbersome requirement of collecting matched pairs within each domain. In this regard, the implicit assumption is that there exists (at least approximately) a ground-truth bijection such that a given input from either domain

A. Zuevsky

Using recursion formulas for vertex operator algebra higher genus characters with formal parameters identified with local coordinates around marked points on a Riemann surface of arbitrary genus, we introduce the notion of a vertex operator cluster algebra structure. Cluster elements and mutation rules are explicitly defined, and the simplest example of a ve

Xiuying Chen, Zhi Cui, Jiayi Zhang, Chen Wei

In multi-turn dialog, utterances do not always take the full form of sentences \cite{Carbonell1983DiscoursePA}, which naturally makes understanding the dialog context more difficult. However, it is essential to fully grasp the dialog context to generate a reasonable response. Hence, in this paper, we propose to improve the response generation performance by

Vasiliki Evdoridou, Leticia Pardo-Simón, David J. Sixsmith

The set of points where an entire function achieves its maximum modulus is known as the maximum modulus set. In 1951, Hayman studied the structure of this set near the origin. Following work of Blumenthal, he showed that, near zero, the maximum modulus set consists of a collection of disjoint analytic curves, and provided an upper bound for the number of the

S. Neshatpour, T. Hurth, F. Mahmoudi

One of the main indications for New Physics in rare $B$-decays is deduced from the tension between experimental and Standard Model predictions of the angular analysis of the $B^0 \to K^{*0} \mu^+\mu^-$ decay. There are however possible non-local hadronic effects which in principle can also explain these tensions. In this work, we consider a statistical appro

N. H. Crisp, P. C. E. Roberts, S. Livadiotti, A. Macario Rojas

The Satellite for Orbital Aerodynamics Research (SOAR) is a CubeSat mission, due to be launched in 2021, to investigate the interaction between different materials and the atmospheric flow regime in very low Earth orbits (VLEO). Improving knowledge of the gas-surface interactions at these altitudes and identification of novel materials that can minimise drag

Sam Baguley, Leif Doering, Andreas Kyprianou

The theory of one-dimensional stochastic differential equations driven by Brownian motion is classical and has been largely understood for several decades. For stochastic differential equations with jumps the picture is still incomplete, and even some of the most basic questions are only partially understood. In the present article we study existence and uni

Neeraj Kumar, Srishti Goel, Ankur Narang, Mujtaba Hasan

Audio to Video generation is an interesting problem that has numerous applications across industry verticals including film making, multi-media, marketing, education and others. High-quality video generation with expressive facial movements is a challenging problem that involves complex learning steps for generative adversarial networks. Further, enabling on

G. A. Bobkov, I. V. Bobkova, A. M. Bobkov, Akashdeep Kamra

We theoretically investigate domain wall motion in an antiferromagnetic insulator layer caused by thermally generated spin currents in an adjacent spin-split superconductor layer. An uncompensated antiferromagnet interface enables the two crucial ingredients underlying the mechanism - spin splitting in the superconductor and absorption of spin currents by th

Alexandre Anahory Simoes, David Martín de Diego, Manuel Lainz Valcázar, Manuel de León

In this article, we continue the program started in our previous article of exploring an important class of thermodynamic systems from a geometric point of view. In order to model the time evolution of systems verifying the two laws of thermodynamics, we show that the notion of evolution vector field is adequate to appropriately describe such systems. Our fo

Alexander Uzhinskiy, Gennady Ososkov, Pavel Goncharov, Andrey Nechaevskiy

Triplet loss function is one of the options that can significantly improve the accuracy of the One-shot Learning tasks. Starting from 2015, many projects use Siamese networks and this kind of loss for face recognition and object classification. In our research, we focused on two tasks related to vegetation. The first one is plant disease detection on 25 clas

Lennart Gehrmann

Recently, Gekeler proved that the group of invertible analytic functions modulo constant functions on Drinfeld's upper half space is isomorphic to the dual of an integral generalized Steinberg representation. In this note we show that the group of invertible functions is the dual of a universal extension of that Steinberg representation. As an application, w

Fengmiao Bian, Jingwei Liang, Xiaoqun Zhang

Alternating direction method of multipliers (ADMM) is a popular first-order method owing to its simplicity and efficiency. However, similar to other proximal splitting methods, the performance of ADMM degrades significantly when the scale of the optimization problems to solve becomes large. In this paper, we consider combining ADMM with a class of stochastic

Arieh Iserles, Marcus Webb

Favard's theorem characterizes bases of functions $\{p_n\}_{n\in\mathbb{Z}_+}$ for which $x p_n(x)$ is a linear combination of $p_{n-1}(x)$, $p_n(x)$, and $p_{n+1}(x)$ for all $n \geq 0$ with $p_{0}\equiv1$ (and $p_{-1}\equiv 0$ by convention). In this paper we explore the differential analogue of this theorem, that is, bases of functions $\{\varphi_n\}_{n\i

Andreas Maurer, Daniela A. Parletta, Andrea Paudice, Massimiliano Pontil

Designing learning algorithms that are resistant to perturbations of the underlying data distribution is a problem of wide practical and theoretical importance. We present a general approach to this problem focusing on unsupervised learning. The key assumption is that the perturbing distribution is characterized by larger losses relative to a given class of

Konrad Schrempf

By representing elements in free fields (over a commutative field and a finite alphabet) using Cohn and Reutenauer's linear representations, we provide an algorithmic construction for the (partial) non-commutative (or Hausdorff-) derivative and show how it can be applied to the non-commutative version of the Newton iteration to find roots of matrix-valued ra

Pietro Bongini, Monica Bianchini, Franco Scarselli

Drug Discovery is a fundamental and ever-evolving field of research. The design of new candidate molecules requires large amounts of time and money, and computational methods are being increasingly employed to cut these costs. Machine learning methods are ideal for the design of large amounts of potential new candidate molecules, which are naturally represen

Kayode Olaleye, Benjamin van Niekerk, Herman Kamper

Developments in weakly supervised and self-supervised models could enable speech technology in low-resource settings where full transcriptions are not available. We consider whether keyword localisation is possible using two forms of weak supervision where location information is not provided explicitly. In the first, only the presence or absence of a word i

Johannes D. Johansson

The Lorentz aether theory was the mathematically equivalent precursor to the special theory of relativity (SR). It assumed the existence of a static aether filling space in which particles are affected by the Lorentz factor for length contraction to explain the null result of the Michelson-Morley experiment. However, it was early abandoned in favour of SR du

R. J. Morton, K. Mooroogen, V. M. J. Henriques

Sunspots have played a key role in aiding our understanding of magnetohydrodynamic (MHD) wave phenomenon in the Sun's atmosphere, and it is well known they demonstrate a number of wave phenomenon associated with slow MHD modes. Recent studies have shown that transverse wave modes are present throughout the majority of the chromosphere. Using high-resolution

Shuming Jia, Zhengshi Wang

Aerodynamic entrainment acts as the pioneer of saltation movement and is critical for understanding the development of aeolian phenomena. Here we performed direct numerical simulations on the aerodynamic lifting of surface particles on a random arranged sediment bed using the discrete element method, and provided evidence that particles do not leave the bed

Callum Hunter

In this paper we consider Quadratic Gravity as a low energy effective field theory of some unknown UV-complete theory of gravity. Using the spin-2 ghost pathology that occurs in Quadratic Gravity, we derive maximum value for the classical cut-off of the low energy effective field theory in various configurations. We then add on higher order, bottom-up, effec

Martina Hofmanova, Ujjwal Koley, Utsab Sarkar

We introduce a new concept of dissipative measure-valued martingale solutions to the stochastic compressible Euler equations. These solutions are weak in the probabilistic sense i.e., the probability space and the driving Wiener process are an integral part of the solution. We derive the relative energy inequality for the stochastic compressible Euler equati

Yury Malyshkin

We study the asymptotic behavior of the maximum degree in the evolving tree model with a choice based on both degree and fitness of a vertex. The tree is constructed in the following recursive way. Each vertex is assigned a parameter to it that is called a fitness of a vertex. We start from two vertices and an edge between them. On each step we consider a sa

Andrea Pizzo, Thomas Marzetta, Luca Sanguinetti

Holographic MIMO is a spatially-constrained MIMO system with a massive number of antennas, possibly thought of, in its ultimate form, as a spatially-continuous electromagnetic aperture. Accurate and tractable channel modeling is critical to understanding the full potential of this technology. This paper considers arbitrary spatially-stationary scattering and

Tobias Fehenberger, Helmut Griesser, Jörg-Peter Elbers

Probabilistic constellation shaping (PCS) offers a significant performance improvement over uniform signaling. It was recently discovered that long blocks are not required to achieve maximum shaping gain when transmitting over the nonlinear fiber channel because short-length PCS effectively mitigates fiber nonlinear interference (NLI). The reason for this be

Lisa van Staden, Herman Kamper

Many speech processing tasks involve measuring the acoustic similarity between speech segments. Acoustic word embeddings (AWE) allow for efficient comparisons by mapping speech segments of arbitrary duration to fixed-dimensional vectors. For zero-resource speech processing, where unlabelled speech is the only available resource, some of the best AWE approach

Hannah Lawrence, David A. Barmherzig, Henry Li, Michael Eickenberg

Phase retrieval is the inverse problem of recovering a signal from magnitude-only Fourier measurements, and underlies numerous imaging modalities, such as Coherent Diffraction Imaging (CDI). A variant of this setup, known as holography, includes a reference object that is placed adjacent to the specimen of interest before measurements are collected. The resu

Mehdi Dagdoug, Camelia Goga, David Haziza

Model-assisted estimators have attracted a lot of attention in the last three decades. These estimators attempt to make an efficient use of auxiliary information available at the estimation stage. A working model linking the survey variable to the auxiliary variables is specified and fitted on the sample data to obtain a set of predictions, which are then in

Li Ji, Zheng Lou, Jinlong Zhang, Keqiang Qiu

The CAFE (Census of warm-hot intergalactic medium, Accretion, and Feedback Explorer) and LyRIC (Lyman UV Radiation from Interstellar medium and Circum-galactic medium) have been proposed to the space agencies in China respectively. CAFE was first proposed in 2015 as a joint scientific CAS-ESA small space mission. LyRIC was proposed in 2019 as an independent

Elsa Rizk, Stefan Vlaski, Ali H. Sayed

Federated learning encapsulates distributed learning strategies that are managed by a central unit. Since it relies on using a selected number of agents at each iteration, and since each agent, in turn, taps into its local data, it is only natural to study optimal sampling policies for selecting agents and their data in federated learning implementations. Us

Václav Janiš, Antonín Klíč, Jiawei Yan

We study the low-temperature critical behavior of the one-dimensional Hubbard model near half filling caused by enhanced antiferromagnetic fluctuations. We use a mean-field-type approximation with a two-particle self-consistency renormalizing the bare interaction. It allows us to control a transition from high to low temperatures as well as from weak to stro

Adriano Franci, Maxime Cordy, Martin Gubri, Mike Papadakis

Graph-based Semi-Supervised Learning (GSSL) is a practical solution to learn from a limited amount of labelled data together with a vast amount of unlabelled data. However, due to their reliance on the known labels to infer the unknown labels, these algorithms are sensitive to data quality. It is therefore essential to study the potential threats related to

Stefan Karlsson, Adnan Čaušević, Daniel Sundmark

In recent years, GraphQL has become a popular way to expose web APIs. With its raise of adoption in industry, the quality of GraphQL APIs must be also assessed, as with any part of a software system, and preferably in an automated manner. However, there is currently a lack of methods to automatically generate tests to exercise GraphQL APIs. In this paper, we

Tianyang Cao, Shuang Zeng, Songge Zhao, Mairgup Mansur

Recent years have seen significant advancement in text generation tasks with the help of neural language models. However, there exists a challenging task: generating math problem text based on mathematical equations, which has made little progress so far. In this paper, we present a novel equation-to-problem text generation model. In our model, 1) we propose

Constantin Babenko, Frank Göhmann, Karol K. Kozlowski, Jesko Sirker

We apply the recently developed thermal form factor expansion method to evaluate the real-time longitudinal spin-spin correlation functions of the spin-$\frac{1}{2}$ XXZ chain in the antiferromagnetically ordered regime at temperature $T=0$. An analytical result containing all types of excitations in the model is obtained, without any approximations. This al

A. Boselli, A. Lupi, B. Epinat, P. Amram

We study the IB(s)m galaxy IC 3476 observed in the context of VESTIGE, a blind narrow-band Halpha+[NII] imaging survey of the Virgo cluster. The deep narrow-band (NB) image reveals a very pertubed ionised gas distribution, characterised by a prominent banana-shaped structure in the front of the galaxy formed of giant HII regions crossing the stellar disc, wi

Shang Shi, Huifang Min, Shihong Ding

In this technical communique, we propose a novel observer-based adaptive scheme to deal with the parameter estimation problem of biased sinusoidal signals. Different from the existing adaptive frequency estimation scheme, the proposed scheme can achieve fixed-time frequency estimation, whose convergence time is independent of the initial errors. Simulation e

Devsi Bantva, Samir Vaidya

Let $G$ be a simple finite connected graph of order $n$. The detour distance between two distinct vertices $u$ and $v$ denoted by $D(u,v)$ is the length of a longest $uv$-path in $G$. A hamiltonian coloring $h$ of a graph $G$ of order $n$ is a mapping $h : V(G) \rightarrow \{0,1,2,...\}$ such that $D(u,v) + |h(u)-h(v)| \geq n-1$, for every two distinct verti

Yu-Guo Liu, Lu Xu, Zhi Li

In this work, we investigate the quantum phase transition in a non-Hermitian XY spin chain. The phase diagram shows that the critical points of Ising phase transition expand into a critical transition zone after introducing a non-Hermitian effect. By analyzing the non-Hermitian gap and long-range correlation function, one can distinguish different phases by

Chandrachud B. V. Dash, Tapomoy Guha Sarkar, Anjan Kumar Sarkar

We propose the intensity mapping of the redshifted HI 21-cm signal from the post-reionization epoch as a cosmological probe of $f(R)$ gravity. We consider the Hu-Sawicki class of $f(R)$ gravity models characterized by a single parameter $f_{,R0}$. The $f(R)$ modification to gravity affects the post-reionization $21$-cm power spectrum through the change in th

Ziqi Pan, Li Niu, Jianfu Zhang, Liqing Zhang

The information bottleneck (IB) method is a technique for extracting information that is relevant for predicting the target random variable from the source random variable, which is typically implemented by optimizing the IB Lagrangian that balances the compression and prediction terms. However, the IB Lagrangian is hard to optimize, and multiple trials for

Janus J. Eriksen, Jürgen Gauss

The recent many-body expanded full configuration interaction (MBE-FCI) method is reviewed by critically assessing its advantages and drawbacks in the context of contemporary near-exact electronic structure theory. Besides providing a succinct summary of the history of MBE-FCI to date within a generalized and unified theoretical setting, its finer algorithmic

Osamu Fukushima, Jun-ichi Sakamoto, Kentaroh Yoshida

We derive the Faddeev-Reshetikhin (FR) model from a four-dimensional Chern- Simons theory with two order surface defects by following the work by Costello and Yamazaki [arXiv:1908.02289]. Then we present a trigonometric deformation of the FR model by employing a boundary condition with an R-operator of Drinfeld-Jimbo type. This is a generalization of the wor

Sébastien Gros, Mario Zanon

The combination of learning methods with Model Predictive Control (MPC) has attracted a significant amount of attention in the recent literature. The hope of this combination is to reduce the reliance of MPC schemes on accurate models, and to tap into the fast developing machine learning and reinforcement learning tools to exploit the growing amount of data

Hezhi Luo, Yuanyuan Chen, Xianye Zhang, Duan Li

We investigate the optimal portfolio deleveraging (OPD) problem with permanent and temporary price impacts, where the objective is to maximize equity while meeting a prescribed debt/equity requirement. We take the real situation with cross impact among different assets into consideration. The resulting problem is, however, a non-convex quadratic program with

Jianchao Xue, Marco Romoli, Federico Landini, Cristian Baccani

The Solar Corona Imager is an internally occulted coronagraph on board the ASO-S mission, which has the advantage of imaging the inner corona in H I {Lyman-\textalpha} (Ly-alpha) and white-light (WL) wavebands. However, scattering of solar disk light by the primary mirror (M1) becomes the main source of stray light. To study the methods of stray light suppre

Mikhail S. Kalenkov, Andrei D. Zaikin

We demonstrate that the supercurrent can be strongly enhanced in cross-like superconducting hybrid nanostructures (X-junctions) exposed to a temperature gradient. At temperatures T exceeding the Thouless energy of our X-junction the Josephson current decays algebraically with increasing T and can be further enhanced by a proper choice of the circuit topology

S. Dutta, S. Singh

The main purpose of this article is to introduce some new binomial difference sequence spaces of fractional order ${\tilde{\alpha}} $ along with infinite matrices. Some topological properties of these spaces are considered along with the Schauder basis and ${\alpha} -,\beta -$ and $\gamma -$duals of the spaces.

Debarghya Mukherjee, Aritra Guha, Justin Solomon, Yuekai Sun

Optimal transport (OT) measures distances between distributions in a way that depends on the geometry of the sample space. In light of recent advances in computational OT, OT distances are widely used as loss functions in machine learning. Despite their prevalence and advantages, OT loss functions can be extremely sensitive to outliers. In fact, a single adv

Simranpreet Kaur, Bindiya Arora, B. K. Sahoo

Atom interferometry is amongst the most advanced technologies that provides very high-precision measurements. There can exist a number of obscure forces that can interfere with the atoms used in this instrument. In the present work, we are probing possible roles of one such important forces, known as ``blackbody friction force (BBFF)'', that may affect the p

Lukas Kühne, Rudi Pendavingh, Geva Yashfe

This paper compares skew-linear and multilinear matroid representations. These are matroids that are representable over division rings and (roughly speaking) invertible matrices, respectively. The main tool is the von Staudt construction, by which we translate our problems to algebra. After giving an exposition of a simple variant of the von Staudt construct

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

The Born cross sections for the process $e^+e^- \to \eta^\prime \pi^{+}\pi^{-}$ at different center-of-mass energies between $2.00$ and $3.08$ GeV are reported with improved precision from an analysis of data samples collected with the BESIII detector operating at the BEPCII storage ring. An obvious structure is observed in the Born cross section line shape.

Antonio Costantini

We discuss the main features of the scalar sector of a class of BSM models with enlarged gauge symmetry, the so called 331 Models. The theoretical constraints on the scalar potential such as unitarity, perturbativity and boundedness-from-below, are presented, together with the analytical exact digitalization of the scalar sector. The phenomenology of exotic

João Magueijo, Tom Zlosnik

In the Einstein-Cartan framework the torsion-free conditions arise within the Hamiltonian treatment as second-class constraints. The standard strategy is to solve these constraints, eliminating the torsion from the classical theory, before quantization. Here we advocate leaving the torsion inside the other constraints before quantization, leading at first to

T. Ergin, L. Saha, P. Bhattacharjee, H. Sano

Star-forming (SF) regions embedded inside giant molecular clouds (GMCs) are potential contributors to Galactic gamma rays. The gamma-ray source 3FHL J1907.0+0713 is detected with a significance of roughly 13$\sigma$ in the 0.2 $-$ 300 GeV energy range after the removal of gamma-ray pulsation periods of PSR J1906+0722 from the Fermi-LAT data set of about 10 y

Xiaoyang Lyu, Liang Liu, Mengmeng Wang, Xin Kong

Self-supervised learning shows great potential in monoculardepth estimation, using image sequences as the only source ofsupervision. Although people try to use the high-resolutionimage for depth estimation, the accuracy of prediction hasnot been significantly improved. In this work, we find thecore reason comes from the inaccurate depth estimation inlarge gr

Yiwei Dong, Yuanqing Yang

Nanoparticles supporting a distinct series of Mie resonances have enabled a new class of nanoantennas and provide efficient ways to manipulate light at the nanoscale. The ability to flexibly tune the optical resonances and scattering directionality are particularly essential for various applications ranging from biosensing to nanolasers. In this paper, we in

Rim van Wersch, Steven Kelk, Simone Linz, Georgios Stamoulis

Phylogenetic trees are leaf-labelled trees used to model the evolution of species. Here we explore the practical impact of kernelization (i.e. data reduction) on the NP-hard problem of computing the TBR distance between two unrooted binary phylogenetic trees. This problem is better-known in the literature as the maximum agreement forest problem, where the go

Hu Hu, Xuesong Yang, Zeynab Raeesy, Jinxi Guo

Accents mismatching is a critical problem for end-to-end ASR. This paper aims to address this problem by building an accent-robust RNN-T system with domain adversarial training (DAT). We unveil the magic behind DAT and provide, for the first time, a theoretical guarantee that DAT learns accent-invariant representations. We also prove that performing the grad

T. Birkandan, M. Hortacsu

We study the solutions of the wave equation where a massless scalar field is coupled to the Wahlquist metric, a type-D solution. We first take the full metric and then write simplifications of the metric by taking some of the constants in the metric null. When we do not equate any of the arbitrary constants in the metric to zero, we find the solution is give

A. Manu, K. Narayan, Partha Paul

We study aspects of entanglement and extremal surfaces in various families of spacetimes exhibiting cosmological, Big-Crunch, singularities, in particular isotropic $AdS$ Kasner. The classical extremal surface dips into the bulk radial and time directions. Explicitly analysing the extremization equations in the semiclassical region far from the singularity,

Xuan Jin, Wei Su, Rong Zhang, Yuan He

Intellectual property protection(IPP) have received more and more attention recently due to the development of the global e-commerce platforms. brand recognition plays a significant role in IPP. Recent studies for brand recognition and detection are based on small-scale datasets that are not comprehensive enough when exploring emerging deep learning techniqu

Izumi Mizuno, Per Friberg, Ryan Berthold, Harriet Parsons

Namakanui is an instrument containing three inserts in an ALMA type Dewar. The three inserts are Alaihi, Uu and Aweoweo operating around 86, 230 and 345GHz. The receiver is being commissioned on the JCMT. It will be used for both Single dish and VLBI observations. We will present commissioning results and the system.

Lydia T. Liu, Feng Ruan, Horia Mania, Michael I. Jordan

We study two-sided matching markets in which one side of the market (the players) does not have a priori knowledge about its preferences for the other side (the arms) and is required to learn its preferences from experience. Also, we assume the players have no direct means of communication. This model extends the standard stochastic multi-armed bandit framew

Maxim Vashkevich, Yulia Rushkevich

Amyotrophic lateral sclerosis (ALS) is incurable neurological disorder with rapidly progressive course. Common early symptoms of ALS are difficulty in swallowing and speech. However, early acoustic manifestation of speech and voice symptoms is very variable, that making their detection very challenging, both by human specialists and automatic systems. This s

Matthew J. Holland

We study scalable alternatives to robust gradient descent (RGD) techniques that can be used when the losses and/or gradients can be heavy-tailed, though this will be unknown to the learner. The core technique is simple: instead of trying to robustly aggregate gradients at each step, which is costly and leads to sub-optimal dimension dependence in risk bounds

Kiyoaki Christopher Omori, Tsutomu T. Takeuchi

Aims. Interacting galaxies show unique irregularities in their kinematic structure. By investigating the spatially resolved kinematics and stellar population properties of galaxies that show irregularities, we can paint a detailed picture of the formation and evolutionary processes that took place during its lifetimes. Methods. In this work, we focus on gala

Federica Fanoni

We show that any infinite-type surface without planar ends admits arbitrarily large families of length isospectral hyperbolic structures. If the surface has infinite genus and its space of ends is self-similar, we construct an uncountable family of isospectral and quasiconformally distinct hyperbolic structures.

A. Zuevsky

For the double complex structure of grading-restricted vertex algebra cohomology defined in \cite{Huang}, we introduce a multiplication of elements of double complex spaces. We show that the orthogonality and bi-grading conditions applied on double complex spaces, provide in relation among mappings and actions of co-boundary operators. Thus, we endow the dou

Krzysztof Frączek, Vered Rom-Kedar

The ergodic properties of two uncoupled oscillators, a horizontal and vertical one, residing in a class of non rectangular star-shaped polygons with only vertical and horizontal boundaries and impacting elastically from its boundaries are studied. We prove that the iso-energy level sets topology changes non-trivially; the flow on level sets is always conjuga

Yihan Du, Siwei Wang, Longbo Huang

In this paper, we study a family of conservative bandit problems (CBPs) with sample-path reward constraints, i.e., the learner's reward performance must be at least as well as a given baseline at any time. We propose a One-Size-Fits-All solution to CBPs and present its applications to three encompassed problems, i.e. conservative multi-armed bandits (CMAB),

Diana Mateus, Radu Horaud, David Knossow, Fabio Cuzzolin

Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph. Spectral graph theory can be used to map these graphs onto lower dimensional spaces and match shapes by aligning their embeddings in virtue of their invariance to change of pose. Classical graph isomorphism schemes re

Ermyas Abebe, Yining Hu, Allison Irvin, Dileban Karunamoorthy

Permissioned ledger technologies have gained significant traction over the last few years. For practical reasons, their applications have focused on transforming narrowly scoped use-cases in isolation. This has led to a proliferation of niche, isolated networks that are quickly becoming data and value silos. To increase value across the broader ecosystem, th

Xin Tong

Following ideas of Kedlaya-Liu, we are going to consider extending our previous work to the context of more general adic spaces, which will be corresponding deformation of the relative $p$-adic Hodge structure over more general adic spaces. This means that the deformation could be also realized by an adic spaces (perfectoid, preperfectoid, relatively perfect

Keng-Hsien Chao, Rebecca deGraffenried, Mackenzie Lach, William Nelson

The magma ocean concept was first conceived to explain the geology of the Moon, but hemispherical or global oceans of silicate melt could be a widespread "lava world" phase of rocky planet accretion, and could persist on planets on short-period orbits around other stars. The formation and crystallization of magma oceans could be a defining stage in the assem

Xin Tong

This is our sequel to our previous work on the corresponding generalized Frobenius modules over some big multivariate Robba rings. We will go beyond our previous discussion where we focused on the corresponding analytic functions on polydiscs and polyannuli in the strictly affinoid situation, and general Hodge-Frobenius structures which are admissible in the

Hao Fu, Shaojun Zhou, Qihong Yang, Junjie Tang

The pre-training models such as BERT have achieved great results in various natural language processing problems. However, a large number of parameters need significant amounts of memory and the consumption of inference time, which makes it difficult to deploy them on edge devices. In this work, we propose a knowledge distillation method LRC-BERT based on co

Zu-Xing Yang, Wei Zuo, Peng Yin, Xiao-Hua Fan

We investigate the density distributions of finite nuclei employing a well-designed deep neural network method. We calculate the target nucleon density distributions with Skyrme density functional theories, which are used to train the networks. We find that the training with only about $10\%$ nuclei ($300-400$) is sufficient to describe the nucleon density d