November 2022 arXiv papers — page 149

Haici Yang, Wootaek Lim, Minje Kim

Low and ultra-low-bitrate neural speech coding achieves unprecedented coding gain by generating speech signals from compact speech features. This paper introduces additional coding efficiency in neural speech coding by reducing the temporal redundancy existing in the frame-level feature sequence via a recurrent neural predictor. The prediction can achieve a

Raphaël Ruimy

We link smooth Artin motives to \'etale local systems and Artin representations. We then construct the ordinary motivic t-structure on Artin motives with integral coefficients and show that the $\ell$-adic realization functor is t-exact.

Alex Morehead, Jianlin Cheng

The field of geometric deep learning has had a profound impact on the development of innovative and powerful graph neural network architectures. Disciplines such as computer vision and computational biology have benefited significantly from such methodological advances, which has led to breakthroughs in scientific domains such as protein structure prediction

Thimo Maria Kasper

The present contribution derives an explicit expression for (a version of) every uni- and multi-variate conditional distribution (i.e., Markov kernel) of Archimedean copulas and uses this representation to generalize a recently established result, saying that in the class of multivariate Archimedean copulas standard uniform convergence implies weak convergen

Adam Ginsburg, Brett A. McGuire, Patricio Sanhueza, Fernando Olguin

Molecular lines tracing the orbital motion of gas in a well-defined disk are valuable tools for inferring both the properties of the disk and the star it surrounds. Lines that arise only from a disk, and not also from the surrounding molecular cloud core that birthed the star or from the outflow it drives, are rare. Several such emission lines have recently

Giannis Nikolentzos, Michail Chatzianastasis, Michalis Vazirgiannis

In recent years, graph neural networks (GNNs) have emerged as a promising tool for solving machine learning problems on graphs. Most GNNs are members of the family of message passing neural networks (MPNNs). There is a close connection between these models and the Weisfeiler-Leman (WL) test of isomorphism, an algorithm that can successfully test isomorphism

Limeng Xia

The generalized quantum Euclidean group $\oq(\frak{b}_{m,n})$ is a natural generalization of the quantum Euclidean group $\oq(\frak{b}_{1,1})$. The Heisenberg double $\od(\frak{b}_{m,n})$ of $\oq(\frak{b}_{m,n})$ is the smash product of $\oq(\frak{b}_{m,n})$ with its Hopf dual $\ou(\frak{b}_{m,n})$. In this paper, we study the weight modules, the prime spect

Jian Xue, Peidong Wang, Jinyu Li, Eric Sun

In this paper, we introduce our work of building a Streaming Multilingual Speech Model (SM2), which can transcribe or translate multiple spoken languages into texts of the target language. The backbone of SM2 is Transformer Transducer, which has high streaming capability. Instead of human labeled speech translation (ST) data, SM2 models are trained using wea

Benjamin J. Qureshi, Jordan Juritz, Jenny M. Poulton, Adrian Beersing-Vasquez

Polymers consisting of more than one type of monomer, known as copolymers, are vital to both living and synthetic systems. Copolymerisation has been studied theoretically in a number of contexts, often by considering a Markov process in which monomers are added or removed from the growing tip of a long copolymer. To date, the analysis of the most general mod

A. Mouhoub, F. Millo, C. Chappert, J. -V. Kim

The interlayer exchange coupling confers specific properties to Synthetic Antiferromagnets that make them suitable for several applications of spintronics. The efficient use of this magnetic configuration requires an in-depth understanding of the magnetic properties and their correlation with the material structure. Here we establish a reliable procedure to

Randolf Altmeyer, Anton Tiepner, Martin Wahl

The coefficients in a second order parabolic linear stochastic partial differential equation (SPDE) are estimated from multiple spatially localised measurements. Assuming that the spatial resolution tends to zero and the number of measurements is non-decreasing, the rate of convergence for each coefficient depends on its differential order and is faster for

Micaela B. Bagley, Steven L. Finkelstein, Anton M. Koekemoer, Henry C. Ferguson

We present the data release and data reduction process for the Epoch 1 NIRCam observations for the Cosmic Evolution Early Release Science Survey (CEERS). These data consist of NIRCam imaging in six broadband filters (F115W, F150W, F200W, F277W, F356W and F444W) and one medium band filter (F410M) over four pointings, obtained in parallel with primary CEERS MI

Taketo Sano, Kouki Sato

We give a family of slice-torus invariants $\tilde{ss}_c$, each defined from the $c$-divisibility of the reduced Lee class in a variant of reduced Khovanov homology, parameterized by prime elements $c$ in any principal ideal domain $R$. For the special case $(R, c) = (F[H], H)$ where $F$ is any field, we prove that $\tilde{ss}_c$ coincides with the Rasmussen

Sunanda, Reetanjali Moharana, Pratik Majumdar

TXS 0506+056, a source of the extreme energy neutrino event, IceCube-170922A, was observed on 22 September 2017. The Fermi-LAT detector reported high energy (HE) $\gamma$-ray flare between 100 MeV and 100 GeV starting from 15 September 2017 from this source. Several attempts to trace the very high energy (VHE) gamma-ray counterparts around the IceCube-170922

Areg Ghazaryan, Tobias Holder, Erez Berg, Maksym Serbyn

Motivated by the recent discoveries of superconductivity in bilayer and trilayer graphene, we theoretically investigate superconductivity and other interaction-driven phases in multilayer graphene stacks. To this end, we study the density of states of multilayer graphene with up to four layers at the single-particle band structure level in the presence of a

ALICE Collaboration

This document describes the plans of the ALICE Collaboration for a major upgrade of its detector, referred to as ALICE 3, which is proposed for physics data-taking in the LHC Run 5 and beyond. ALICE 3 will enable an extensive programme to fully exploit the LHC for the study of the properties of strongly interacting matter with high-energy nuclear collisions.

Hiroaki Matsueda, Yukiya Ide, Sadamichi Maekawa

We derive damping equations of motion for interacting two-spin states from a spin-boson model in order to examine qubit dynamics in quantum computers. On the basis of the composite operator method, we develop the Caldeira-Leggett approach for open quantum systems so that the entanglement dynamics originated from the two-spin correlation can be taken. We demo

Paul Didier, Toon van Waterschoot, Simon Doclo, Marc Moonen

Sampling rate offsets (SROs) between devices in a heterogeneous wireless acoustic sensor network (WASN) can hinder the ability of distributed adaptive algorithms to perform as intended when they rely on coherent signal processing. In this paper, we present an SRO estimation and compensation method to allow the deployment of the distributed adaptive node-spec

Javad Hassannataj Joloudari, Sadiq Hussain, Mohammad Ali Nematollahi, Rouhollah Bagheri

The free flow of information has been accelerated by the rapid development of social media technology. There has been a significant social and psychological impact on the population due to the outbreak of Coronavirus disease (COVID-19). The COVID-19 pandemic is one of the current events being discussed on social media platforms. In order to safeguard societi

Galien Grosjean, Scott Waitukaitis

Models for same-material contact electrification in granular media often rely on a local charge-driving parameter whose spatial variations lead to a stochastic origin for charge exchange. Measuring the charge transfer from individual granular spheres after contacts with substrates of the same material, we find that the charge-driving parameter is global, not

Samuel Klein, John Andrew Raine, Tobias Golling

Normalizing flows are constructed from a base distribution with a known density and a diffeomorphism with a tractable Jacobian. The base density of a normalizing flow can be parameterised by a different normalizing flow, thus allowing maps to be found between arbitrary distributions. We demonstrate and explore the utility of this approach and show it is part

Samuel Klein, Tobias Golling

The sensitivity of many physics analyses can be enhanced by constructing discriminants that preferentially select signal events. Such discriminants become much more useful if they are uncorrelated with a set of protected attributes. In this paper we show that a normalizing flow conditioned on the protected attributes can be used to find a decorrelated repres

Shreyas Malpathak, Nandini Ananth

Mixed Quantum Classical (MQC)-IVR is a recently introduced semiclassical framework that allows for selective quantization of the modes of a complex system. In the quantum limit, MQC reproduces the semiclassical Double Herman-Kluk IVR results, accurately capturing nuclear quantum coherences and conserving zero-point energy. However, in the classical limit, wh

Zhaonan Dong, Moritz Hauck, Roland Maier

In this work, we propose a high-order multiscale method for an elliptic model problem with rough and possibly highly oscillatory coefficients. Convergence rates of higher order are obtained using the regularity of the right-hand side only. Hence, no restrictive assumptions on the coefficient, the domain, or the exact solution are required. In the spirit of t

Yibo Wang, Congying Xia, Guan Wang, Philip Yu

The explosion of e-commerce has caused the need for processing and analysis of product titles, like entity typing in product titles. However, the rapid activity in e-commerce has led to the rapid emergence of new entities, which is difficult to be solved by general entity typing. Besides, product titles in e-commerce have very different language styles from

Alexandre Artaud, Nicolas Rougemaille, Sergio Vlaic, Vincent T. Renard

Unlike conventional two-dimensional (2D) semiconductor superlattices, moir\'{e} patterns in 2D materials are flexible and their electronic, magnetic, optical, and mechanical properties depend on their topography. Within a continuous+atomistic theory treating 2D materials as crystalline elastic membranes, we abandon the flat-membrane scenario usually assumed

Richard D. Gill, Justo P. Lambare

Marian Kupczynski(MK)is the author of a controversial paper published (2020) in the journal Frontiers in Physics. The work is built around a mathematical claim by MK which is actually false, and MK's logical reasoning around his claim is also incorrect. The same claim was made by him in several other recent papers published in other journals. A proof that th

Shitao Li, Minjia Shi, Jon-Lark Kim

The hull of a linear code over finite fields is the intersection of the code and its dual, and linear codes with small hulls have applications in computational complexity and information protection. Linear codes with the smallest hull are LCD codes, which have been widely studied. Recently, several papers were devoted to related LCD codes over finite fields

Zhao-Sai Jia, Mao-Jun Yan, Zhen-Hua Zhang, Pan-Pan Shi

Starting from the hypothesis that the $T_{cc}^+$ discovered at LHCb is a $D^{\ast+} D^0/D^{\ast 0}D^+$ hadronic molecule, we consider the partial width of its heavy quark spin partner, the $T_{cc}^{\ast +}$ as a $D^{\ast +} D^{\ast 0}$ shallow bound state, decaying into the $D^{\ast}D\pi$ final states including the contributions of the $D^{\ast} D$ and $D^{\

Benny Avelin, Lauri Viitasaari

In this article we prove that estimator stability is enough to show that leave-one-out cross validation is a sound procedure, by providing concentration bounds in a general framework. In particular, we provide concentration bounds beyond Lipschitz continuity assumptions on the loss or on the estimator. We obtain our results by relying on random variables wit

Janek Bevendorff, Philipp Sauer, Lukas Gienapp, Wolfgang Kircheis

The rapidly growing volume of scientific publications offers an interesting challenge for research on methods for analyzing the authorship of documents with one or more authors. However, most existing datasets lack scientific documents or the necessary metadata for constructing new experiments and test cases. We introduce SMAuC, a comprehensive, metadata-ric

Vidhi Lalchand, Wessel P. Bruinsma, David R. Burt, Carl E. Rasmussen

The kernel function and its hyperparameters are the central model selection choice in a Gaussian proces (Rasmussen and Williams, 2006). Typically, the hyperparameters of the kernel are chosen by maximising the marginal likelihood, an approach known as Type-II maximum likelihood (ML-II). However, ML-II does not account for hyperparameter uncertainty, and it i

Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Zhiyun Xue

Lung segmentation in chest X-rays (CXRs) is an important prerequisite for improving the specificity of diagnoses of cardiopulmonary diseases in a clinical decision support system. Current deep learning models for lung segmentation are trained and evaluated on CXR datasets in which the radiographic projections are captured predominantly from the adult populat

Jannes Quer, Enric Ribera Borrell

In this paper the connection between stochastic optimal control and reinforcement learning is investigated. Our main motivation is to apply importance sampling to sampling rare events which can be reformulated as an optimal control problem. By using a parameterised approach the optimal control problem becomes a stochastic optimization problem which still rai

Nan Liang, Zihao Li, Xiaoyao Xie, Puxun Wu

In this paper, we calibrate the Amati relation (the $E_{\rm p}$-${E}_{\rm iso}$ correlation) of gamma-ray bursts (GRBs) in a cosmology-independent way. By using Gaussian process to reconstruct the smoothed luminosity distance from the Pantheon type Ia supernovae (SNe Ia) sample, we utilize the reconstructed results to calibrate the $E_{\rm p}$-${E}_{\rm iso}

Sayantan Paul, Arijit Chakrabarti

We consider a high-dimensional sparse normal means model where the goal is to estimate the mean vector assuming the proportion of non-zero means is unknown. We model the mean vector by a one-group global-local shrinkage prior belonging to a broad class of such priors that includes the horseshoe prior. We address some questions related to asymptotic propertie

Mike Cummings, Adam Van Tuyl

Using the geometric vertex decomposition property first defined by Knutson, Miller, and Yong, a recursive definition for geometrically vertex decomposable ideals was given by Klein and Rajchgot. We introduce the Macaulay2 package GeometricDecomposability which provides a suite of tools to experiment and test the geometric vertex decomposability property of a

J. Trautmann, D. Yankelev, V. Klüsener, A. J. Park

We present a detailed investigation of the ultranarrow magnetic-quadrupole $^{1}\mathrm{S}_0$-$^{3}\mathrm{P}_2$ transition in neutral strontium and show how it can be made accessible for quantum simulation and quantum computation. By engineering the light shift in a one-dimensional optical lattice, we perform high-resolution spectroscopy and observe the cha

Valentin Blomer, Junxian Li

We study the value distribution of diagonal forms in k variables and degree d with random real coefficients and positive integer variables, normalized so that mean spacing is one. We show that the l-correlation of almost all such forms is Poissonian when k is large enough depending on l and d.

Anaelia Ovalle, Evan Czyzycki, Cho-Jui Hsieh

Intentionally crafted adversarial samples have effectively exploited weaknesses in deep neural networks. A standard method in adversarial robustness assumes a framework to defend against samples crafted by minimally perturbing a sample such that its corresponding model output changes. These sensitivity attacks exploit the model's sensitivity toward task-irre

Miao Yu, Liangjian Wen, Xiang Zhou, Wuming Luo

Energy nonlinearity and resolution in liquid scintillator (LS) detectors are correlated and particle-dependent. A unified energy response model for liquid scintillator detectors has been presented in details. This model has advanced a data-driven approach to calibrate the particle-dependent energy response, using both the monoenergetic $\gamma$-ray sources a

Paul Lartaud, Philippe Humbert, Josselin Garnier

In a fissile material, the inherent multiplicity of neutrons born through induced fissions leads to correlations in their detection statistics. The correlations between neutrons can be used to trace back some characteristics of the fissile material. This technique known as neutron noise analysis has applications in nuclear safeguards or waste identification.

Xitao Yu, Xiaoqing Hu, Jiaqi Zhou, Xinyu Zhang

Imaging the charge distributions and structures of molecules and clusters will promote the understanding of the dynamics of the quantum system. Here, we report a method by using an Ar atom as a tip to probe the charge distributions of benzene (Bz) cations in gas phase. Remarkably, the measured charge distributions of Bz cation (QH =0.204,QC=-0.037)and dicati

Gabriel A. Gerez S., Roberto Di Remigio Eikås, Stig Rune Jensen, Magnar Bjørgve

We present a multiwavelet-based implementation of a quantum/classical polarizable continuum model. The solvent model uses a diffuse solute-solvent boundary and a position-dependent permittivity, lifting the sharp-boundary assumption underlying many existing continuum solvation models. We are able to include both surface and volume polarization effects in the

Frans M. Aben, Nicolas Brantut

Shear rupture and fault slip in crystalline rocks like granite produce large dilation, impacting the spatiotemporal evolution of fluid pressure in the crust during the seismic cycle. To explore how fluid pressure variations are coupled to rock deformation and fault slip, we conducted laboratory experiments under upper crustal conditions while monitoring acou

Hoang Ky Nguyen

In our recent publication (Phys. Rev. D 106, 104004 (2022)), we advanced a program that Buchdahl originated but prematurely abandoned circa 1962 (Nuovo Cimento 23, 141 (1962)). Therein we obtained an exhaustive class of metrics that constitute the branch of non-trivial solutions to the pure $R^{2}$ field equation in vacuo. The Buchdahl-inspired metrics in ge

Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise, Frederic Dufaux

Following the advent of immersive technologies and the increasing interest in representing interactive geometrical format, 3D Point Clouds (PC) have emerged as a promising solution and effective means to display 3D visual information. In addition to other challenges in immersive applications, objective and subjective quality assessments of compressed 3D cont

Ming-yan Gong, Bin Lyu

The expectation--maximization (EM) algorithm updates all of the parameter estimates simultaneously, which is not applicable to direction of arrival (DOA) estimation in unknown nonuniform noise. In this work, we present several efficient EM-type algorithms, which update the parameter estimates sequentially, for solving both the deterministic and stochastic ma

Le Hu, Andrew N. Jordan

Starting with the quantum brachistochrone problem of the infinitesimal form, we solve the minimal time and corresponding time-dependent Hamiltonian to drive a pure quantum state with limited resources along arbitrary pre-assigned trajectories. It is also shown that out of all possible trajectories, with limited resources, which are physically accessible and

M. Ragragui, L. B. Drissi, S. Lounis, E. H. Saidi

Using density functional theory based methods we report the structural, electronic and topological properties of the FCC crystal compound TmBi. This material is found to be dynamically stable and shows a non magnetic semimetalic character. By tuning the spin-orbit coupling, we observe a significant change in the band structure, and the occurrence of band inv

Didier Lairez

Introducing the Boltzmann distribution very early in a statistical thermodynamics course (in the spirit of Feynmann) has many didactic advantages, in particular that of easily deriving the Gibbs entropy formula. In this note, a short derivation is proposed from the fundamental postulate of statistical mechanics and basics calculations accessible to undergrad

Bilal Kousar, Damon J. Carrad, Lukas Stampfer, Peter Krogstrup

Implementing superconductors capable of proximity-inducing a large energy-gap in semiconductors in the presence of strong magnetic fields is a major goal towards applications of semiconductor/superconductor hybrid materials in future quantum information technologies. Here, we study the performance of devices consisting of InAs nanowires in electrical contact

M. D. Burke, Maxence Grandadam, J. P. F. LeBlanc

We present a method to accelerate the numerical evaluation of spatial integrals of Feynman diagrams when expressed on the real frequency axis. This can be realized through use of a renormalized perturbation expansion with a constant but complex renormalization shift. The complex shift acts as a regularization parameter for the numerical integration of otherw

Shikha Singh, Kamal Lodaya, Deepak Khemani

In dynamic epistemic logic (Van Ditmarsch, Van Der Hoek, & Kooi, 2008) it is customary to use an action frame (Baltag & Moss, 2004; Baltag, Moss, & Solecki, 1998) to describe different views of a single action. In this article, action frames are extended to add or remove agents, we call these agent-update frames. This can be done selectively so that only som

Francisco J. Soltero, Pablo Fernández-Blanco, J. Ignacio Hidalgo

Technical indicators use graphic representations of data sets by applying various mathematical formulas to financial time series of prices. These formulas comprise a set of rules and parameters whose values are not necessarily known and depend on many factors: the market in which it operates, the size of the time window, and others. This paper focuses on the

Elio Marconi, Emanuela Radici, Federico Stra

We prove the stability of entropy solutions of nonlinear conservation laws with respect to perturbations of the initial datum, the space-time dependent flux and the entropy inequalities. Such a general stability theorem is motivated by the study of problems in which the flux $P[u](t,x,u)$ depends possibly non-locally on the solution itself. For these problem

Atanu Bhatta, Taniya Mandal

We compute the exact retarded Green's functions in thermal $CFT$s with chemical potential and angular momenta using holography respectively. We consider the field equations satisfied by the quasi-normal modes in both charged and rotating black holes in $AdS$ spacetime and mapped them to the Heun equations by appropriate changes of variables. The AGT correspo

Zurab Aghdgomelashvili

In this article one of the fundamental problems of Diophantine (integer) planar geometric figures, the Task max n(k), is considered.

Dongchao Yang, Songxiang Liu, Jianwei Yu, Helin Wang

Expressive text-to-speech (TTS) can synthesize a new speaking style by imiating prosody and timbre from a reference audio, which faces the following challenges: (1) The highly dynamic prosody information in the reference audio is difficult to extract, especially, when the reference audio contains background noise. (2) The TTS systems should have good general

George Kenison

Hypergeometric sequences are rational-valued sequences that satisfy first-order linear recurrence relations with polynomial coefficients; that is, $\langle u_n \rangle_{n=0}^\infty$ is hypergeometric if it satisfies a first-order linear recurrence of the form $p(n)u_{n+1} = q(n)u_{n}$ with polynomial coefficients $p,q\in\mathbb{Z}[x]$ and $u_0\in\mathbb{Q}$.

Stanisław Cichomski, Adam Osękowski

Let $X_1$, $X_2$, $\ldots$, $X_n$ be a sequence of coherent random variables, i.e., satisfying the equalities $$ X_j=\mathbb{P}(A|\mathcal{G}_j),\qquad j=1,\,2,\,\ldots,\,n,$$ almost surely for some event $A$. The paper contains the proof of the estimate $$\mathbb{P}\Big(\max_{1\le i < j\le n}|X_i-X_j|\ge \delta\Big) \leq \frac{n(1-\delta)}{2-\delta} \wedge

Daniel Adolfsson, Martin Magnusson, Anas Alhashimi, Achim J. Lilienthal

This paper presents an accurate, highly efficient, and learning-free method for large-scale odometry estimation using spinning radar, empirically found to generalize well across very diverse environments -- outdoors, from urban to woodland, and indoors in warehouses and mines - without changing parameters. Our method integrates motion compensation within a s

Moallison F. Cavalcante, Rodrigo G. Pereira, Maria C. O. Aguiar

We study the real-time dynamics of the Kondo effect after a quantum quench in which a magnetic impurity is coupled to two metallic Hubbard chains. Using an effective field theory approach, we find that for noninteracting electrons the charge current across the impurity is given by a scaling function that involves the Kondo time. In the interacting case, we s

Yuhang Gai, Bing Wang, Jiwen Zhang, Dan Wu

Robotic force-based compliance control is a preferred approach to achieve high-precision assembly tasks. When the geometric features of assembly objects are asymmetric or irregular, reinforcement learning (RL) agents are gradually incorporated into the compliance controller to adapt to complex force-pose mapping which is hard to model analytically. Since for

Richard H. Day, Oleg V. Pavlov

Existence theory in economics is usually in real domains such as the findings of chaotic trajectories in models of economic growth, tatonnement, or overlapping generations models. Computational examples, however, sometimes converge rapidly to cyclic orbits when in theory they should be nonperiodic almost surely. We explain this anomaly as the result of digit

Maria Axenovich, Christian Winter

Given partially ordered sets (posets) $(P, \leq_P)$ and $(P', \leq_{P'})$, we say that $P'$ contains a copy of $P$ if for some injective function $f\colon P\rightarrow P'$ and for any $A, B\in P$, $A\leq _P B$ if and only if $f(A)\leq_{P'} f(B)$. For any posets $P$ and $Q$, the poset Ramsey number $R(P,Q)$ is the least positive integer $N$ such that no matte

Insong Choe, George H. Hitching, Jaehyun Hong

The variety of minimal rational tangents associated to Hecke curves was used by J.-M.Hwang [8] to prove the simplicity of the tangent bundle on the moduli of vector bundles over a curve. In this paper, we use the tangent maps of the symplectic and orthogonal Hecke curves to prove an analogous result for symplectic and orthogonal bundles. In particular, we sh

Luke Boegner, Garrett Vanhoy, Phillip Vallance, Manbir Gulati

Applications of deep learning to the radio frequency (RF) domain have largely concentrated on the task of narrowband signal classification after the signals of interest have already been detected and extracted from a wideband capture. To encourage broader research with wideband operations, we introduce the WidebandSig53 (WBSig53) dataset which consists of 55

Andrius Popovas

With the advance of supercomputers we can now afford simulations with very large ranges of scales. In astrophysical applications, e.g. simulating Solar, stellar and planetary atmospheres, interstellar medium, etc; physical quantities, like gas pressure, density, temperature, plasma $\beta$, Mach, Reynolds numbers can vary by orders of magnitude. This require

Jyatsnasree Bora, Umananda Dev Goswami

The tentative Gravitational Wave Echo (GWE) at a frequency of about $72\,Hz$ has been recently claimed at $4.2\sigma$ significance level in the GW170817 event. GWEs can be used as a tool to study the characteristics of ultra-compact stellar objects. Considering the final ultra-compact, post-merger object as a strange star, the GWE frequency can be calculated

Ambika Shorny, Fritz Steiner, Helmut Hörner, Sarah M. Skoff

Currently the extent of nanoplastic in the environment can only be estimated by extrapolation from the plastic waste that can be detected. To be able to quantify the whole extent of the problem, detection methods have to be developed that can also identify particles that are smaller than 1 $\mu$m. Here we employ surface-enhanced Raman scattering (SERS) to im

Frederik Hennig, Markus Holzer, Ulrich Rüde

The scientific code generation package lbmpy supports the automated design and the efficient implementation of lattice Boltzmann methods (LBMs) through metaprogramming. It is based on a new, concise calculus for describing multiple relaxation-time LBMs, including techniques that enable the numerically advantageous subtraction of the constant background compo

Stanisław Cichomski, Adam Osękowski

Let $\xi$ be an integrable random variable defined on $(\Omega, \mathcal{F}, \mathbb{P})$. Fix $k\in \mathbb{Z}_+$ and let $\{\mathcal{G}_{i}^{j}\}_{1\le i \le n, 1\le j \le k}$ be a reference family of sub-$\sigma$-fields of $\mathcal{F}$, such that $\{\mathcal{G}_{i}^{j}\}_{1\le i \le n}$ is a filtration for each $j\in \{1,2,\dots,k\}$. In this article we

Ingrid Beltita, Daniel Beltita

We study continuous selections of the set-valued map that takes every skew-symmetric bilinear form on a vector space to its corresponding set of maximal isotropic subspaces. Applications are made to establishing continuity properties of the Vergne polarizing subalgebras of completely solvable Lie algebras in terms of Schubert cells of suitable Grassmann mani

Chen-Chou Lo, Patrick Vandewalle

Recently, transformer networks have outperformed traditional deep neural networks in natural language processing and show a large potential in many computer vision tasks compared to convolutional backbones. In the original transformer, readout tokens are used as designated vectors for aggregating information from other tokens. However, the performance of usi

Biswadev Roy, A. Karoui, B. Vlahovic, M. H. Wu

We have analyzed a limited sample set of 120 GHz, and 150 GHz time-resolved millimeter wave (mmW) photoconductive decay (mmPCD) signals of 300 nm thick air-stable encapsulated perovskite film (methyl-ammonium lead halide) excited using a pulsed 532-nm laser with fluence 10.6 micro-Joules per cm-2. We correlated 12 parameters derived directly from acquired mm

Angel Daza, Antske Fokkens, Tomaž Erjavec

Abbreviations present a significant challenge for NLP systems because they cause tokenization and out-of-vocabulary errors. They can also make the text less readable, especially in reference printed books, where they are extensively used. Abbreviations are especially problematic in low-resource settings, where systems are less robust to begin with. In this p

Paulo Cleber Farias da Silva Filho, Jose Ribamar Dantas Silveira Junior, Bricio Warney de Freitas Alves, Fernando Jose Silva Lima Filho

In this study, we report on the analysis of 701 stars in a solar vicinity defined in three categories namely subsolar, solar, and supersolar with rotation periods between 1 and 70 days, based on rotational modulation signatures inferred from time series from the Kepler mission's Public Archives. In our analysis, we performed an initial selection based on the

Hariom Sogarwal, Prashant Shukla

The particle showers produced in the atmosphere due to the interactions of primary cosmic particles require a thorough understanding in the backdrop of searches for rare interactions. In this work, we made a comprehensive study of air shower simulations using various combinations of hadronic models and particle transport code of the CORSIKA package. The prim

Helena Grete Lillepalu, Antonio Racioppi

We study a generalized version of hilltop inflation where the standard hilltop potential has been raised to a power and we allow fractional numbers for both the original hilltop power ($m$) and the overall exponent ($n$). In the parameter space studied, agreement with the latest experimental constraints favors high values for $m$ and low values for $n$. Fina

Kacper Dębski, Piotr T. Grochowski, Rafał Demkowicz-Dobrzański, Andrzej Dragan

Time dilation is a difference in measured time between two clocks that either move with different velocities or experience different gravitational potentials. Both of these effects stem from the theory of relativity and are usually associated with classically defined trajectories, characterized by position, momentum, and acceleration. However, when spatial d

Sanchayan Bhowal, Ramkrishna Jyoti Samanta, Arnob Ray, Sirshendu Bhattacharyya

Animal groups collaborate with one another throughout their lives to better comprehend their surroundings. Here, we try to model, using continuous random walks, how the entire process of birth, reproduction, and death might impact the searching process. We attempt to simulate an ecosystem where the post-reproductive foragers leave their colonies to discover

Aleksandr Chuklin, Justin Zhao, Mihir Kale

One of the biggest challenges of natural language generation (NLG) is the proper handling of named entities. Named entities are a common source of grammar mistakes such as wrong prepositions, wrong article handling, or incorrect entity inflection. Without factoring linguistic representation, such errors are often underrepresented when evaluating on a small s

S. D. Clarke, A. Sanchez-Monge, G. M. Williams, A. D. P. Howard

We present an analysis of the outer Galaxy giant molecular filament (GMF) G214.5-1.8 (G214.5) using Herschel data. We find that G214.5 has a mass of $\sim$ 16,000 M$_{\odot}$, yet hosts only 15 potentially protostellar 70 $\mu$m sources, making it highly quiescent compared to equally massive clouds such as Serpens and Mon R2. We show that G214.5 has a unique

Marcin Nawrocki, Pouyan Fotouhi Tehrani, Raphael Hiesgen, Jonas Mücke

In this paper, we revisit the performance of the QUIC connection setup and relate the design choices for fast and secure connections to common Web deployments. We analyze over 1M Web domains with 272k QUIC-enabled services and find two worrying results. First, current practices of creating, providing, and fetching Web certificates undermine reduced round tri

Kristina Tesch, Timo Gerkmann

In a scenario with multiple persons talking simultaneously, the spatial characteristics of the signals are the most distinct feature for extracting the target signal. In this work, we develop a deep joint spatial-spectral non-linear filter that can be steered in an arbitrary target direction. For this we propose a simple and effective conditioning mechanism,

Yucong Lin, Jinhua Su, Yuhang Li, Yuhao Wei

Deep learning methods have contributed substantially to the rapid advancement of medical image segmentation, the quality of which relies on the suitable design of loss functions. Popular loss functions, including the cross-entropy and dice losses, often fall short of boundary detection, thereby limiting high-resolution downstream applications such as automat

Serge Cantat, Romain Dujardin

We study the hyperbolicity properties of the action of a non-elementary automorphism group on a compact complex surface, with an emphasis on K3 and Enriques surfaces. A first result is that when such a group contains parabolic elements, Zariski diffuse invariant measures automatically have non-zero Lyapunov exponents. In combination with our previous work, t

Josef Gullholm, Jil Klünder, Julie Rowlett, Jonathan Stålberg

Given a fixed budget for player salaries, what is the distribution of salaries of the top scoring teams? We investigated this question using the wealth of data available from fantasy premier league football (soccer). Using the players' data from past seasons, for several seasons and several different budget constraints, we identified the highest scoring fant

Yan Wen, Lei Zhang, Xiangli Meng, Xujiong Ye

Besides the complex nature of colonoscopy frames with intrinsic frame formation artefacts such as light reflections and the diversity of polyp types/shapes, the publicly available polyp segmentation training datasets are limited, small and imbalanced. In this case, the automated polyp segmentation using a deep neural network remains an open challenge due to

Sofia Rizou, Antonia Paflioti, Angelos Theofilatos, Athena Vakali

Named Entity Recognition and Intent Classification are among the most important subfields of the field of Natural Language Processing. Recent research has lead to the development of faster, more sophisticated and efficient models to tackle the problems posed by those two tasks. In this work we explore the effectiveness of two separate families of Deep Learni

Nashiba Parbin, Dhruba Jyoti Gogoi, Jyatsnasree Bora, Umananda Dev Goswami

The current study aims to examine the impact of the boundary term on the bending angle of light for a static spherically symmetric black hole in the modified gravity described by the $f(\mathcal{T}, \mathcal{B})$ function. To accomplish this objective, we employ the Ishihara \textit{et al.}~method, which enables us to compute the deflection angle of light fo

Chris Halcrow, Egor Babaev

We construct and study two kink theories. One contains a static 2-kink configuration with controllable binding energy. The other contains a locally stable non-topological solution, which we call a lavion. The new models are 1D analogs of non-integrable systems in higher dimensions such as the Skyrme model and realistic vortex systems. To help construct the t

Boaz Carmeli, Ron Meir, Yonatan Belinkov

The field of emergent communication aims to understand the characteristics of communication as it emerges from artificial agents solving tasks that require information exchange. Communication with discrete messages is considered a desired characteristic, for both scientific and applied reasons. However, training a multi-agent system with discrete communicati

Zoltán Péli

We summarize our analysis for the vacuum stability of the superweak extension of the standard model. The parameter space allowed by the $W$-boson mass measurements and collider searches for a new scalar particle are also presented. The final result is a well defined non-vanishing portion of the parameter space, where the vacuum is stable, the couplings are p

Hadi Kharaghani, Sho Suda

Let $n$ be the order of a (quaternary) Hadamard matrix. It is shown that the existence of a projective plane of order $n$ is equivalent to the existence of a balancedly multi-splittable (quaternary) Hadamard matrix of order $n^2$.

Alejandro Sánchez-Roncero, Òscar Garibo-i-Ortsa, J. Alberto Conejero, Hamidreza Eivazi

The 2030 Agenda of the United Nations (UN) revolves around the Sustainable Development Goals (SDGs). A critical step towards that objective is identifying whether scientific production aligns with the SDGs' achievement. To assess this, funders and research managers need to manually estimate the impact of their funding agenda on the SDGs, focusing on accuracy

Lukas Struppek, Dominik Hintersdorf, Kristian Kersting

While text-to-image synthesis currently enjoys great popularity among researchers and the general public, the security of these models has been neglected so far. Many text-guided image generation models rely on pre-trained text encoders from external sources, and their users trust that the retrieved models will behave as promised. Unfortunately, this might n

François Bienvenu, Jean-Jil Duchamps

We introduce a biologically natural, mathematically tractable model of random phylogenetic network to describe evolution in the presence of hybridization. One of the features of this model is that the hybridization rate of the lineages correlates negatively with their phylogenetic distance. We give formulas / characterizations for quantities of biological in

Khamosh Yadav, A. Y. Deo, Madhu, Dhananjaya Sahoo

Yrast and near-yrast states above the known 25/2$^{+}$ isomer in $^{207}$At are established for the first time. The level scheme is extended up to 47/2$\hbar$ and 6.5 MeV with the addition of about 60 new $\gamma$-ray transitions. The half-life of the 25/2$^{+}$ isomer is revisited and a value of $T_{1/2}$ = 107.5(9) ns is deduced. Evidence of a hitherto uno