November 2022 arXiv papers — page 3

I. Krichever, A. Zabrodin

We further develop the approach to many-body systems based on finding conditions of existence of meromorphic solutions to certain linear partial differential and difference equations which serve as auxiliary linear problems for nonlinear integrable equations such as KP, BKP, CKP and different versions of the Toda lattice. These conditions imply equations of

Mohammad Naser Lessani, Zhenlong Li, Jiqiu Deng, Zhiyong Guo

Multiple geographical feature label placement (MGFLP) has been a fundamental problem in geographic information visualization for decades. The nature of label positioning is proven an NP-hard problem, where the complexity of such a problem is directly influenced by the volume of input datasets. Advances in computer technology and robust approaches have addres

Arkadev Chattopadhyay, Nikhil S. Mande, Swagato Sanyal, Suhail Sherif

We show that the deterministic decision tree complexity of a (partial) function or relation $f$ lifts to the deterministic parity decision tree (PDT) size complexity of the composed function/relation $f \circ g$ as long as the gadget $g$ satisfies a property that we call stifling. We observe that several simple gadgets of constant size, like Indexing on 3 in

Neetu Raj Singh Chundawat

In this work we consider the implications of current $b \to s \ell^+ \ell^-$ ($\ell=e,\,\mu$) measurements on several $B \to K^* \tau^+ \tau^-$ observables under the assumption that the possible new physics can have both universal as well as nonuniversal couplings to leptons. For new physics solutions which provide a good fit to all $b \to s \ell^+ \ell^-$ d

Daniel Kaplan, Tobias Holder, Binghai Yan

The quantum geometry has significant consequences in determining transport and optical properties in quantum materials. Here, we use a semiclassical formalism coupled with perturbative corrections unifying the nonlinear anomalous Hall effect (NLAHE) and nonreciprocal magnetoresistance (NMR, longitudinal resistance) from the quantum geometry. In the dc limit,

Z. Feizi Mangoudehi

In this research, we are interested in constraining the nonlinear interacting and noninteracting Tsallis holographic dark energy (THDE) with Ricci horizon cutoff by employing three observational datasets. To this aim, the THDE with Ricci horizon considering the noninteraction and nonlinear interaction terms will be fitted by the SNe Ia, SNe Ia+H(z), and SNe

Paul Beame, Sajin Koroth

Query-to-communication lifting theorems, which connect the query complexity of a Boolean function to the communication complexity of an associated `lifted' function obtained by composing the function with many copies of another function known as a gadget, have been instrumental in resolving many open questions in computational complexity. Several important c

Frank Volmer, Manfred Ersfeld, Paulo E. Faria Junior, Lutz Waldecker

We identify an optical excitation mechanism that transfers a valley polarization from photo-excited electron-hole pairs to free charge carriers in twisted WSe$_2$/MoSe$_2$ heterobilayers. For small twist angles, the valley lifetimes of the charge carriers are surprisingly short, despite the occurrence of interlayer excitons with their presumably long recombi

Jackson Melchert, Keyi Zhang, Yuchen Mei, Mark Horowitz

The architecture of a coarse-grained reconfigurable array (CGRA) interconnect has a significant effect on not only the flexibility of the resulting accelerator, but also its power, performance, and area. Design decisions that have complex trade-offs need to be explored to maintain efficiency and performance across a variety of evolving applications. This pap

Mohammed K. Alqedra, Sebastian P. Horvath, Adam Kinos, Andreas Walther

Quantum memories for quantum communication need to be able to store photons for an extended time and then to release them on demand. This can be achieved in atomic frequency comb ensemble based quantum memories by control pulses that transfer the excitation to and from long-lived spin states. However, such pulses can give rise to coherent and incoherent nois

Daniel Fejgin, Simon Doclo

Recently, a relative transfer function (RTF)-vector-based method has been proposed to estimate the direction of arrival (DOA) of a target speaker for a binaural hearing aid setup, assuming the availability of external microphones. This method exploits the external microphones to estimate the RTF vector corresponding to the binaural hearing aid and constructs

Rui Pan, Shizhe Diao, Jianlin Chen, Tong Zhang

In this paper, we present ExtremeBERT, a toolkit for accelerating and customizing BERT pretraining. Our goal is to provide an easy-to-use BERT pretraining toolkit for the research community and industry. Thus, the pretraining of popular language models on customized datasets is affordable with limited resources. Experiments show that, to achieve the same or

Yohai Trabelsi, Abhijin Adiga, Sarit Kraus, S. S. Ravi

Applications such as employees sharing office spaces over a workweek can be modeled as problems where agents are matched to resources over multiple rounds. Agents' requirements limit the set of compatible resources and the rounds in which they want to be matched. Viewing such an application as a multi-round matching problem on a bipartite compatibility graph

Yu Li, Muxi Chen, Yannan Liu, Daojing He

Deep Active Learning (DAL) has been advocated as a promising method to reduce labeling costs in supervised learning. However, existing evaluations of DAL methods are based on different settings, and their results are controversial. To tackle this issue, this paper comprehensively evaluates 19 existing DAL methods in a uniform setting, including traditional f

Paras Koundal

The IceCube Neutrino Observatory is a multi-component detector embedded deep within the South-Pole Ice. This proceeding will discuss an analysis from an integrated operation of IceCube and its surface array, IceTop, to estimate cosmic-ray composition. The work will describe a novel graph neural network based approach for estimating the mass of primary cosmic

Victor Kac, Johan van de Leur

The first part of the paper is devoted to two descriptions of all polynomial tau-functions of the KP hierarchy: by a generalized Jacobi-Trudy formula, and a generalized Giambelli formula. We use the latter formula in the second part to obtain all polynomial tau-functions of the CKP hierarchy and its n-reductions. In particular, for n=3 we find all polynomial

Dongji Gao, Jiatong Shi, Shun-Po Chuang, Leibny Paola Garcia

This paper describes the ESPnet Unsupervised ASR Open-source Toolkit (EURO), an end-to-end open-source toolkit for unsupervised automatic speech recognition (UASR). EURO adopts the state-of-the-art UASR learning method introduced by the Wav2vec-U, originally implemented at FAIRSEQ, which leverages self-supervised speech representations and adversarial traini

Shuhan Jiang

In this paper, we provide the notions of connection $1$-forms and curvature $2$-forms on graphs. We prove a Weitzenb\"ock formula for connection Laplacians in this setting. We also define a discrete Yang-Mills functional and study its Euler-Lagrange equations.

Salvatore Capozziello, Rocco D'Agostino

The cosmographic technique is a powerful model-independent tool for distinguishing between competing cosmological scenarios. The key strengths and weaknesses of standard cosmography are discussed in view of healing the convergence problem endangering the high-redshift expansions of cosmological distances. We focus especially on rational cosmographic approxim

Yaniv Leviathan, Matan Kalman, Yossi Matias

Inference from large autoregressive models like Transformers is slow - decoding K tokens takes K serial runs of the model. In this work we introduce speculative decoding - an algorithm to sample from autoregressive models faster without any changes to the outputs, by computing several tokens in parallel. At the heart of our approach lie the observations that

Chris Verhoek, Hossam S. Abbas, Roland Tóth

We demonstrate that direct data-driven control of nonlinear systems can be successfully accomplished via a behavioral approach that builds on a Linear Parameter-Varying (LPV) system concept. An LPV data-driven representation is used as a surrogate LPV form of the data-driven representation of the original nonlinear system. The LPV data-driven control design

Yu. B. Ivanov

The ring structures that appear in Au+Au collisions at collision energies $\sqrt{s_{NN}}=$ 3 -- 30 GeV are studied. The calculations are performed within the model of three-fluid dynamics. It is demonstrated that a pare of vortex rings are formed, one at forward and another at backward rapidities, in ultra-central Au+Au collisions at $\sqrt{s_{NN}}>$ 4 GeV.

Julien Demange-Chryst, François Bachoc, Jérôme Morio

Some classical uncertainty quantification problems require the estimation of multiple expectations. Estimating all of them accurately is crucial and can have a major impact on the analysis to perform, and standard existing Monte Carlo methods can be costly to do so. We propose here a new procedure based on importance sampling and control variates for estimat

Fábio Reis, Sandra Alves, Mário Florido

Non-idempotent intersection types provide quantitative information about typed programs, and have been used to obtain time and space complexity measures. Intersection type systems characterize termination, so restrictions need to be made in order to make typability decidable. One such restriction consists in using a notion of finite rank for the idempotent i

Péter Diviánszky, István Márton, Erika Bene, Tamás Vértesi

We address the problem of testing the quantumness of two-dimensional systems in the prepare-and-measure (PM) scenario, using a large number of preparations and a large number of measurement settings, with binary outcome measurements. In this scenario, we introduce constants, which we relate to the Grothendieck constant of order 3. We associate them with the

Kelson Kaj, Kevin A. Cremin, Ian Hammock, Jacob Schalch

Terahertz nonlinear optics is a viable method to interrogate collective phenomena in quantum materials spanning ferroelectrics, charge-density waves, and superconductivity. In superconductors this includes the Higgs amplitude and Josephson phase modes. We have investigated the nonlinear c-axis response of optimally doped La$_{1.85}$Sr$_{0.15}$CuO$_4$ using h

Johan Bijnens, Nils Hermansson-Truedsson, Antonio Rodríguez-Sánchez

The muon anomalous magnetic moment continues to attract attention due to the possible tension between the experimentally measured value and the theoretical Standard Model prediction. With the aim to reduce the uncertainty on the hadronic light-by-light contribution to the magnetic moment, we derive short-distance constraints in the Melnikov-Vainshtein regime

Chris Verhoek, Roland Tóth, Hossam S. Abbas

The framework of linear parameter-varying (LPV) systems has shown to be a powerful tool for the design of controllers for complex nonlinear systems using linear tools. In this work, we derive novel methods that allow to synthesize LPV state-feedback controllers directly from only a single sequence of data and guarantee stability and performance of the closed

S. Nandy, Z. Lenarčič, E. Ilievski, M. Mierzejewski

The isotropic Heisenberg chain represents a particular case of an integrable many-body system exhibiting superdiffusive spin transport at finite temperatures. Here, we show that this model has distinct properties also at finite magnetization $m\ne0$, even upon introducing the SU(2) invariant perturbations. Specifically, we observe nonmonotonic dependence of

Christian H. X. Ali Mehmeti-Göpel, Jan Disselhoff

We perform an empirical study of the behaviour of deep networks when fully linearizing some of its feature channels through a sparsity prior on the overall number of nonlinear units in the network. In experiments on image classification and machine translation tasks, we investigate how much we can simplify the network function towards linearity before perfor

Jean Panaioti Jordanou, Eric Aislan Antonelo, Eduardo Camponogara, Eduardo Gildin

Echo State Networks (ESN) are a type of Recurrent Neural Network that yields promising results in representing time series and nonlinear dynamic systems. Although they are equipped with a very efficient training procedure, Reservoir Computing strategies, such as the ESN, require high-order networks, i.e., many neurons, resulting in a large number of states t

Tobias Ilg, Hans Peter Büchler

We study the behavior of the excitation spectrum across the quantum phase transition from a superfluid to a supersolid phase of a dipolar Bose gas confined to a one-dimensional geometry. Including the leading beyond-mean-field effects within an effective Hamiltonian, the analysis is based on Bogoliubov theory with several order parameters accounting for the

S. A. Yost, S. Jadach, B. F. L. Ward, Z. Wąs

KKMChh adapts the CEEX (Coherent Exclusive Exponentiation) formalism of the Monte Carlo Program KKMC for Z boson production and decay to hadron scattering. Amplitude-level soft photon exponentiation of initial and final state radiation, together with initial-final interference, is matched to a perturbative calculation to second order next-to-leading logarith

Thomas Lam

The second-order singularly-perturbed problem concerns the integral functional $\int_\Omega \varepsilon_n^{-1}W(u) + \varepsilon_n^3\|\nabla^2u\|^2\,dx$ for a bounded open set $\Omega \subseteq \mathbb{R}^N$, a sequence $\varepsilon_n \to 0^+$ of positive reals, and a function $W:\mathbb{R} \to [0,\infty)$ with exactly two distinct zeroes. This functional is

Andrew Campbell, Kyle Luh, Sean O'Rourke, Santiago Arenas-Velilla

A Laplacian matrix is a real symmetric matrix whose row and column sums are zero. We investigate the limiting distribution of the largest eigenvalues of a Laplacian random matrix with Gaussian entries. Unlike many classical matrix ensembles, this random matrix model contains dependent entries. Our main results show that the extreme eigenvalues of this model

Frederik Pahde, Galip Ümit Yolcu, Alexander Binder, Wojciech Samek

Explainable AI (XAI) is slowly becoming a key component for many AI applications. Rule-based and modified backpropagation XAI approaches however often face challenges when being applied to modern model architectures including innovative layer building blocks, which is caused by two reasons. Firstly, the high flexibility of rule-based XAI methods leads to num

Gil R. Cavalcanti, Aldo Witte

We extend the notion of T-duality to manifolds endowed with non-principal torus actions. The singularities of the torus action are controlled by a certain Lie algebroid, called the elliptic tangent bundle. Using this Lie algebroid, we explain how certain invariant generalized complex structures can be transported via T-duality. Along the way, we use the elli

Chih-Wei Chang

In this paper, we investigate the Seshadri constant $\varepsilon(X,T_X;p)$ of the tangent sheaf $T_X$ on a complete $\mathbb Q$-factorial toric variety $X$. We show that $\varepsilon(X,T_X;1)>0$ if and only if the following statement holds true: if $a_1v_1+\cdots +a_kv_k=0$ where $a_i$'s are positive real numbers and $v_i$'s are primitive generators of some

Jing Yao, Zheng Liu, Junhan Yang, Zhicheng Dou

Deep semantic matching aims to discriminate the relationship between documents based on deep neural networks. In recent years, it becomes increasingly popular to organize documents with a graph structure, then leverage both the intrinsic document features and the extrinsic neighbor features to derive discrimination. Most of the existing works mainly care abo

Galina Zalesskaya, Bogna Bylicka, Eugene Liu

The rapidly evolving industry demands high accuracy of the models without the need for time-consuming and computationally expensive experiments required for fine-tuning. Moreover, a model and training pipeline, which was once carefully optimized for a specific dataset, rarely generalizes well to training on a different dataset. This makes it unrealistic to h

Niclas Boehmer, Martin Bullinger, Anna Maria Kerkmann

We study the formation of stable outcomes via simple dynamics in cardinal hedonic games, where the utilities of agents change over time depending on the history of the coalition formation process. Specifically, we analyze situations where members of a coalition decrease their utility for a leaving agent (resent) or increase their utility for a joining agent

Chunyu Ma, Zhihan Zhou, Han Liu, David Koslicki

Background: Computational drug repurposing is a cost- and time-efficient approach that aims to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It is especially critical for emerging and/or orphan diseases due to its cheaper investment and shorter research cycle compared with traditional wet-lab drug discovery approache

Martin Gärttner, Tobias Haas, Johannes Noll

We explore the advantages of a class of entanglement criteria for continuous variable systems based on the Husimi $Q$-distribution in scenarios with sparse experimental data. The generality of these criteria allows optimizing them for a given entangled state and experimental setting. We consider the scenario of coarse grained measurements, or finite detector

Miriam Oliva, Timur Flissikowski, Michał Góra, Jonas Lähnemann

GaAs-based nanowires are among the most promising candidates for realizing a monolithical integration of III-V optoelectronics on the Si platform. To realize their full potential for applications as light absorbers and emitters, it is crucial to understand their interaction with light governing the absorption and extraction efficiency, as well as the carrier

Paolo Felli, Marco Montali, Fabio Patrizi, Sarah Winkler

We study monitoring of linear-time arithmetic properties against finite traces generated by an unknown dynamic system. The monitoring state is determined by considering at once the trace prefix seen so far, and all its possible finite-length, future continuations. This makes monitoring at least as hard as satisfiability and validity. Traces consist of finite

Martin Gärttner, Tobias Haas, Johannes Noll

We prove a general class of continuous variable entanglement criteria based on the Husimi $Q$-distribution, which represents a quantum state in canonical phase space, by employing a theorem by Lieb and Solovej. We discuss their generality, which roots in the possibility to optimize over the set of concave functions, from the perspective of continuous majoriz

Zheng Ma, Zhenglu Yu, Yuntao Pan, Yishan Wu

A journal's impact and similarity with rivals is closely related to its competitive intensity. A subject area can be considered as an ecological system of journals, and can then be measured using the competitive intensity concept from plant systems. Based on Journal Citation Reports data from 1997, 2000, 2005, 2010, and 2013, we calculated the mutual citatio

Johann Petrak, Brigitte Krenn

This paper presents work on detecting misogyny in the comments of a large Austrian German language newspaper forum. We describe the creation of a corpus of 6600 comments which were annotated with 5 levels of misogyny. The forum moderators were involved as experts in the creation of the annotation guidelines and the annotation of the comments. We also describ

Alek Bedroya

We give a short review of high energy scattering in string theory, thermal properties of strings, explain the connection between the two and how they all tie together with the string/black hole transition.

Jijie Wu, Dongliang Chang, Aneeshan Sain, Xiaoxu Li

The main challenge for fine-grained few-shot image classification is to learn feature representations with higher inter-class and lower intra-class variations, with a mere few labelled samples. Conventional few-shot learning methods however cannot be naively adopted for this fine-grained setting -- a quick pilot study reveals that they in fact push for the o

Martin Gärttner, Tobias Haas, Johannes Noll

We present a general class of entanglement criteria for continuous variable systems. Our criteria are based on the Husimi $Q$-distribution and allow for optimization over the set of all concave functions rendering them extremely general and versatile. We show that several entropic criteria and second moment criteria are obtained as special cases. Our criteri

Nisarg Desai, Praneet Bala, Rebecca Richardson, Jessica Raper

Because of their close relationship with humans, non-human apes (chimpanzees, bonobos, gorillas, orangutans, and gibbons, including siamangs) are of great scientific interest. The goal of understanding their complex behavior would be greatly advanced by the ability to perform video-based pose tracking. Tracking, however, requires high-quality annotated datas

Miriam Di Ianni

The influence of the social relationships of an individual on the individual's opinions (about a topic, a product, or whatever else) is a well known phenomenon and it has been widely studied. This paper considers a network of positive (i.e. trusting) or negative (distrusting) social relationships where every individual has an initial positive or negative opi

Johannes Hertrich

Normalizing flows are a powerful tool for generative modelling, density estimation and posterior reconstruction in Bayesian inverse problems. In this paper, we introduce proximal residual flows, a new architecture of normalizing flows. Based on the fact, that proximal neural networks are by definition averaged operators, we ensure invertibility of certain re

Jingcheng Lu, Eitan Tadmor, Anil Zenginoglu

We introduce a new Swarm-Based Gradient Descent (SBGD) method for non-convex optimization. The swarm consists of agents, each is identified with a position, ${\mathbf x}$, and mass, $m$. The key to their dynamics is communication: masses are being transferred from agents at high ground to low(-est) ground. At the same time, agents change positions with step

S. Joseph Lippert

Given a row-finite, source-free, graph of rank k, we extend the definition of reduction introduced by Eckhardt et al. This constitutes a large step forward in the extension of the geometric classification of finite directed graph $C^*$-algebras presented by Eilers et al. to higher-rank graph $C^*$-algebras. This new move acts as an inverse to delay, directly

Ho Yun, Byeong U. Park

In Euclidean spaces, the empirical mean vector as an estimator of the population mean is known to have polynomial concentration unless a strong tail assumption is imposed on the underlying probability measure. The idea of median-of-means tournament has been considered as a way of overcoming the sub-optimality of the empirical mean vector. In this paper, to a

Jialin Yi, Milan Vojnović

We consider the nonstochastic multi-agent multi-armed bandit problem with agents collaborating via a communication network with delays. We show a lower bound for individual regret of all agents. We show that with suitable regularizers and communication protocols, a collaborative multi-agent \emph{follow-the-regularized-leader} (FTRL) algorithm has an individ

Luiz L. Lopes, Kauan D. Marquez, Débora P. Menezes

We calculate the baryon-meson coupling constants for the spin-1/2 baryonic octet and spin-3/2 decuplet in a unified approach relying on symmetry arguments such as the fact that the Yukawa couplings, present in the Lagrangian density of the Walecka-type models, must be an invariant under SU(3) and SU(6) group transformations. The coupling constants of the bar

Lukas Herron, Pablo Sartori, BingKan Xue

Many biological systems dynamically rearrange their components through a sequence of configurations in order to perform their functions. Such dynamic processes have been studied using network models that sequentially retrieve a set of stored patterns. Previous models of sequential retrieval belong to a general class in which the components of the system are

Yoshiaki Yasuno

Jones-matrix optical coherence tomography (JM-OCT) is an extension of OCT that provides multiple types of optical contrasts of biological and clinical samples. JM-OCT measures the spatial distribution of the Jones matrix of the sample and also its time sequence. All contrasts (i.e., multi-contrast OCT images) are then computed from the Jones matrix. The cont

Andrey Kupavskii, Arsenii Sagdeev, Dmitrii Zakharov

We say that a subset $M$ of $\mathbb R^n$ is exponentially Ramsey if there are $\epsilon>0$ and $n_0$ such that $\chi(\mathbb R^n,M)\ge(1+\epsilon)^n$ for any $n>n_0$, where $\chi(\mathbb R^n,M)$ stands for the minimum number of colors in a coloring of $\mathbb R^n$ such that no copy of $M$ is monochromatic. One important result in Euclidean Ramsey theory is

Sebastian Wenderoth, Heinz-Peter Breuer, Michael Thoss

A small system in contact with a macroscopic environment usually approaches an asymptotic state, determined only by some macroscopic properties of the environment such as the temperature or the chemical potential. In the long-time limit, the state of the small system is thus expected to be independent of its initial state. In some situations, however, the as

Qi Zhu, Christian Geishauser, Hsien-chin Lin, Carel van Niekerk

Task-oriented dialogue (TOD) systems function as digital assistants, guiding users through various tasks such as booking flights or finding restaurants. Existing toolkits for building TOD systems often fall short of in delivering comprehensive arrays of data, models, and experimental environments with a user-friendly experience. We introduce ConvLab-3: a mul

Theo Torres, Mohamed Ould El Hadj, Shi-Qian Hu, Ruth Gregory

We study the problem of plane monochromatic scalar waves impinging upon a Schwarzschild dirty black hole -- a Schwarzschild black hole surrounded by a thin spherical shell of matter -- using the complex angular momentum approach. We first recall general results concerning the differential scattering cross section in the classical limit through a null geodesi

A. A. Poblaguev, A. Zelenski, E. Aschenauer, G. Atoian

At RHIC, the hydrogen jet target polarimeter (HJET) is used to measure proton beam polarization with accuracy $\sigma_P^\text{syst}/P\lesssim0.5\%$ by counting low energy (1--10 MeV) recoil protons in left-right symmetric detectors. The HJET performance also allowed us to precisely measure $pp$ and $p$A (where A is any ion stored at RHIC) analyzing powers in

Kaustav Roy, Arijit Paramanik, Souradip Paul, Akshay Kalyan

Photoacoustic image (PAI) quality improvement using a low frequency piezoelectric micromachined ultrasound transducer (PMUT) having the fundamental resonant frequency 1 MHz is being reported. Specifically, three different methods are implemented such as the frame averaging, mathematically improved algorithms, and a hardware position accurate arrangement in o

Robin Y. Engel, Markus Scholz, Jan O. Schunck, Martin Beye

Absorbing a focused, femtosecond X-ray pulse from a Free-Electron Laser (FEL) can lead to extreme electronic excitations in solids. This excitation drives changes of the electronic system over the course of the pulse duration and the overall absorption of the pulse becomes fluence-dependent. Thus, fluence-dependent non-linear X-ray Absorption Near Edge Spect

E. J. Kolmes, I. E. Ochs, N. J. Fisch

The possibility of fusion ignition in proton-Boron$^{11}$ plasma is strongly enhanced if the energy from the fusion-produced $\alpha$ particles is channeled to fast protons, but in an environment in which most of the protons are thermally distributed. This hybrid of thermonuclear fusion and beam-plasma fusion offers surprisingly large advantages to either pu

Hailin Chen, Amrita Saha, Shafiq Joty, Steven C. H. Hoi

Machine learning models usually assume i.i.d data during training and testing, but data and tasks in real world often change over time. To emulate the transient nature of real world, we propose a challenging but practical task: text classification in-the-wild, which introduces different non-stationary training/testing stages. Decomposing a complex task into

Yang Long, Chenwen Yang, Hong Chen, Jie Ren

Acoustic spin, radiation torque, energy flow, and reactive power are of significant importance from both fundamental and practical aspects, responsible for flexible tweezer manipulations and near-field sound directionality. Nevertheless, the intrinsic relations among these physical quantities are far from clear. Here, we prove the universal geometric relatio

Valerian H. Hall-Chen, Felix I. Parra, Jon C. Hillesheim, Juan Ruiz Ruiz

The Doppler backscattering (DBS) diagnostic, also referred to as Doppler reflectometry, measures turbulent density fluctuations of intermediate length scales. However, when the beam's wavevector is not properly aligned perpendicular to the magnetic field, the backscattered power is attenuated. In previous work, we used beam tracing and reciprocity to derive

R. S. Khmyrov, P. A. Podrabinnik, T. V. Tarasova, M. A. Gridnev

Metals in amorphous state are promising for the use as structural materials due to their superior properties related to the absence of grain boundaries and dislocations.Obtaining the amorphous state requires quenching with a high cooling rate.In conventional technologies,this is the reason for a considerable size limitation hindering application of amorphous

Julie Payette, Sylvain G. Cloutier, Fabrice Vaussenat

In the upcoming years, artificial intelligence (AI) is going to transform the practice of medicine in most of its specialties. Deep learning can help achieve better and earlier problem detection, while reducing errors on diagnosis. By feeding a deep neural network (DNN) with the data from a low-cost and low-accuracy sensor array, we demonstrate that it becom

Helena Gerdener, Jürgen Kusche, Kerstin Schulze, Petra Döll

We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5{\deg}, covering the time frame 2003 to 2019 without gaps, and including uncertainty quantification. GLWS2.0 was derived by assimilating monthly GRACE/-FO

Jean Carlo Guella

In this paper we show that the strictly positive definite matrix valued isotropic kernels in the circle and the real dot product kernels in Euclidean spaces are not well behaved with respect to its scalar valued projections. We generalize the counterexamples that we obtained to an abstract setting by using the concepts of unitarily invariant kernels and adjo

Jose M. Munoz, Serkan Akkoyun, Zayda P. Reyes, Leonardo A. Pachon

$Q_\beta$ represents one of the most important factors characterizing unstable nuclei, as it can lead to a better understanding of nuclei behavior and the origin of heavy atoms. Recently, machine learning methods have been shown to be a powerful tool to increase accuracy in the prediction of diverse atomic properties such as energies, atomic charges, volumes

Joel Niklaus, Daniele Giofré

Pretrained transformer models have achieved state-of-the-art results in many tasks and benchmarks recently. Many state-of-the-art Language Models (LMs), however, do not scale well above the threshold of 512 input tokens. In specialized domains though (such as legal, scientific or biomedical), models often need to process very long text (sometimes well above

Michael Dine

We review arguments that supersymmetric QCD with $N$ colors and $N_f \ge 0$ massive quarks confines. We explain that this remains the case for small soft breakings and small supersymmetric masses for any quarks. These results continue to hold at large $N$. We then consider these theories with large soft breakings -- real QCD -- describing the problem in term

Inwon Kim, Jona Lelmi

In this paper, we study a tumor growth model with nutrients. The contact inhibition for the tumor cells, presented in the model, results in the evolution of a congested tumor patch. We study the regularity of the tumor patch as the nutrients' diffusion strength $D$ diminishes. In particular, we show that for small $D>0$ the boundary of the tumor patch stays

Saptarashmi Bandyopadhyay, Chenqi Zhu, Philip Daniel, Joshua Morrison

Reinforcement Learning (RL) algorithms have been successfully applied to real world situations like illegal smuggling, poaching, deforestation, climate change, airport security, etc. These scenarios can be framed as Stackelberg security games (SSGs) where defenders and attackers compete to control target resources. The algorithm's competency is assessed by w

Haotian Zhang, Rao Li, Zewei Wu, Guodong Sun

In machine learning and big data, the optimization objectives based on set-cover, entropy, diversity, influence, feature selection, etc. are commonly modeled as submodular functions. Submodular (function) maximization is generally NP-hard, even in the absence of constraints. Recently, submodular maximization has been successfully investigated for the setting

Guido D'Amico, Yaniv Donath, Matthew Lewandowski, Leonardo Senatore

We derive the kernels and the Effective Field Theory of Large-Scale Structure counterterms for the one-loop bispectrum of dark matter and of biased tracers in real and redshift space. This requires the expansion of biased tracers up to fourth order in fluctuations. In the process, we encounter several subtleties related to renormalization. One is the fact th

Benjamin Braun, McCabe Olsen

We introduce the definition of an Ehrhart limit, that is, a formal power series with integer coefficients that is the limit in the ring of formal power series of a sequence of Ehrhart $h^*$-polynomials. We identify a variety of examples of sequences of polytopes that yield Ehrhart limits, with a focus on reflexive polytopes and simplices.

Esther Orisakwe, Conrad Johnston, Ruchita Jani, Xiaoli Liu

Buildings are responsible for a considerable fraction of the energy wasted globally every year, and as a result, excess carbon emissions. While heat is lost directly in colder months and climates, resulting in increased heating loads, in hot climates cooling and ventilation is required. One avenue towards improving the energy efficiency of buildings is to in

Mark Story

By a symmetry argument, a synethic aperture radar collection along a linear path does not collect three-dimensional information about the scene. However, it is known that vertical curvature can be used to derive some vertical position information. This paper approaches the problem from a monopulse perspective, resulting in a non-iterative computation that co

Jiaming Liu, Rongyu Zhang, Xiaoqi Li, Xiaowei Chi

Vision-centric bird-eye-view (BEV) perception has shown promising potential in autonomous driving. Recent works mainly focus on improving efficiency or accuracy but neglect the challenges when facing environment changing, resulting in severe degradation of transfer performance. For BEV perception, we figure out the significant domain gaps existing in typical

Petra Berenbrink, Colin Cooper, Cristina Gava, David Kohan Marzagão

We consider two simple asynchronous opinion dynamics on arbitrary graphs where every node $u$ has an initial value $\xi_u(0)$. In the first process, the NodeModel, at each time step $t\ge 0$, a random node $u$ and a random sample of $k$ of its neighbours $v_1,v_2,\cdots,v_k$ are selected. Then, $u$ updates its current value $\xi_u(t)$ to $\xi_u(t+1) = \alpha

Tim Adamo, Wei Bu, Eduardo Casali, Atul Sharma

On-shell kinematics for gluon scattering can be parametrized with points on the celestial sphere; in the limit where these points collide, it is known that tree-level gluon scattering amplitudes exhibit an operator product expansion (OPE)-like structure. While it is possible to obtain singular contributions to this celestial OPE, getting regular contribution

Mark Harfouche, Kanghyun Kim, Kevin C. Zhou, Pavan Chandra Konda

This article experimentally examines different configurations of a novel multi-camera array microscope (MCAM) imaging technology. The MCAM is based upon a densely packed array of "micro-cameras" to jointly image across a large field-of-view at high resolution. Each micro-camera within the array images a unique area of a sample of interest, and then all acqui

Jérémy Blanc, Julia Schneider, Egor Yasinsky

We prove that any group of cardinality at most the one of $\mathbb{C}$ is a quotient of any Cremona group of rank at least $4$. This provides a definitive answer to the question of what the quotients of Cremona groups can be. As a consequence, this gives a negative answer to the question of I. Dolgachev of whether Cremona groups of all ranks are generated by

D. Gazda, A. Pérez-Obiol, A. Gal, E. Friedman

Conflicting values of the hypertriton lifetime $\tau({}_\Lambda^3\mathrm{H})$ were derived in relativistic heavy ion (RHI) collision experiments over the last decade. A very recent ALICE Collaboration measurement is the only experiment where the reported $\tau({}_\Lambda^3\mathrm{H})$ comes sufficiently close to the free-$\Lambda$ lifetime $\tau_\Lambda$,as

Anna Munoz-Farre, Harry Rose, Sera Aylin Cakiroglu

Electronic health records (EHR) offer unprecedented opportunities for in-depth clinical phenotyping and prediction of clinical outcomes. Combining multiple data sources is crucial to generate a complete picture of disease prevalence, incidence and trajectories. The standard approach to combining clinical data involves collating clinical terms across differen

J. Aalbers, D. S. Akerib, A. K. Al Musalhi, F. Alder

The LUX-ZEPLIN experiment recently reported limits on WIMP-nucleus interactions from its initial science run, down to $9.2\times10^{-48}$ cm$^2$ for the spin-independent interaction of a 36 GeV/c$^2$ WIMP at 90% confidence level. In this paper, we present a comprehensive analysis of the backgrounds important for this result and for other upcoming physics ana

Jeremy P Parker, Claire Valva

The eigenspectrum of the Koopman operator enables the decomposition of nonlinear dynamics into a sum of nonlinear functions of the state space with purely exponential and sinusoidal time dependence. For a limited number of dynamical systems, it is possible to find these Koopman eigenfunctions exactly and analytically. Here, this is done for the Korteweg-de V

Dipramit Majumdar, Pratiksha Shingavekar

Given an integer n>1, it is a classical Diophantine problem that whether n can be written as a sum of two rational cubes. The study of this problem, considering several special cases of n, has a copious history that can be traced back to the works of Sylvester, Satg\'e, Selmer etc. and up to the recent works of Alp\"oge-Bhargava-Shnidman. In this article, we

J. T. Mäkinen, K. Zhang, V. B. Eltsov

The different superfluid phases of $^3$He are described by $p$-wave order parameters that include anisotropy axes both in the orbital and spin spaces. The anisotropy axes characterize the broken symmetries in these macroscopically coherent quantum many-body systems. The systems' free energy has several degenerate minima for certain orientations of the anisot

Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin

We study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of their entropy-regularized long-term rewards. To overcome the curse of dimensionality and to reduce communication, we propose a Localized Policy Iteration (LPI) algorithm that provably

Giannis Daras, Alexandros G. Dimakis

We extend Textual Inversion to learn pseudo-words that represent a concept at different resolutions. This allows us to generate images that use the concept with different levels of detail and also to manipulate different resolutions using language. Once learned, the user can generate images at different levels of agreement to the original concept; "A photo o

M. Menichelli, M. Bizzarri, L. Calcagnile, M. Caprai

The HASPIDE (Hydrogenated Amorphous Silicon PIxels DEtectors) project aims at the development of thin hydrogenated amorphous silicon (a-Si:H) detectors on flexible substrates (mostly Polyimide) for beam monitoring, neutron detection and space applications. Since a-Si:H is a material with superior radiation hardness, the benefit for the above-mentioned applic