October 2022 arXiv papers — page 130

Carl Perreault-Lafleur, Margarida Carvalho, Guy Desaulniers

Nowadays, reaching a high level of employee satisfaction in efficient schedules is an important and difficult task faced by companies. We tackle a new variant of the personnel scheduling problem under unknown demand by considering employee satisfaction via endogenous uncertainty depending on the combination of their preferred and received schedules. We addre

Hussein Nassar, Andrew N. Norris, Guoliang Huang

This chapter presents a selection of theoretical and numerical tools suitable for the study of wave propagation in time-dependent media. The focus is on one-dimensional spring-mass chains whose properties are modulated in space and time in a periodic progressive fashion. The chapter is written for the uninitiated newcomer as well as for the theoretically inc

Nir Ailon, Supratim Shit

Recently, neural tangent kernel (NTK) has been used to explain the dynamics of learning parameters of neural networks, at the large width limit. Quantitative analyses of NTK give rise to network widths that are often impractical and incur high costs in time and energy in both training and deployment. Using a matrix factorization technique, we show how to obt

Sofia Nikiforova, Tejaswini Deoskar, Denis Paperno, Yoad Winter

Accurately reporting what objects are depicted in an image is largely a solved problem in automatic caption generation. The next big challenge on the way to truly humanlike captioning is being able to incorporate the context of the image and related real world knowledge. We tackle this challenge by creating an end-to-end caption generation system that makes

Kevin J Painter, Michael Winkler

We consider a phenotype-switching chemotaxis model for aggregation, in which a chemotactic population is capable of switching back and forth between a chemotaxing state (performing chemotactic movement) and a secreting state (producing the attractant). We show that the switching rate provides a powerful mechanism for controlling the densities of spontaneousl

Lucas Backes, Davor Dragicevic, Wenmeng Zhang

The main purpose of this paper is to formulate new conditions for smooth linearization of nonautonomous systems with discrete and continuous time. Our results assume that the linear part admits a nonuniform polynomial dichotomy and that the associated polynomial dichotomy spectrum exhibits appropriate spectral gap and spectral band conditions. This is in sha

Sean Grullon, Vaughn Spurrier, Jiayi Zhao, Corey Chivers

Although melanoma occurs more rarely than several other skin cancers, patients' long term survival rate is extremely low if the diagnosis is missed. Diagnosis is complicated by a high discordance rate among pathologists when distinguishing between melanoma and benign melanocytic lesions. A tool that provides potential concordance information to healthcare pr

Hossein Hajipour, Ning Yu, Cristian-Alexandru Staicu, Mario Fritz

Large code datasets have become increasingly accessible for pre-training source code models. However, for the fine-tuning phase, obtaining representative training data that fully covers the code distribution for specific downstream tasks remains challenging due to the task-specific nature and limited labeling resources. Moreover, fine-tuning pretrained model

Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang

Object discovery is a core task in computer vision. While fast progresses have been made in supervised object detection, its unsupervised counterpart remains largely unexplored. With the growth of data volume, the expensive cost of annotations is the major limitation hindering further study. Therefore, discovering objects without annotations has great signif

Linda Blot, Pier Stefano Corasaniti, Fabian Schmidt

Upcoming large-scale-structure surveys can shed new light on the properties of dark energy. In particular, if dark energy is a dynamical component, it must have spatial perturbations. Their behaviour is regulated by the speed of sound parameter, which is currently unconstrained. In this work we present the numerical methods that will allow to perform cosmolo

Ants Remm, Sebastian Krinner, Nathan Lacroix, Christoph Hellings

Josephson traveling wave parametric amplifiers enable the amplification of weak microwave signals close to the quantum limit with large bandwidth, which has a broad range of applications in superconducting quantum computing and in the operation of single-photon detectors. While the large bandwidth allows for their use in frequency-multiplexed detection archi

Benjamin Hennion, Valerio Melani, Gabriele Vezzosi

In this paper we define and study a generalization of the Belinson-Drinfeld Grassmannian to the case where the curve is replaced by a smooth projective surface $X$, and the trivialization data are given on loci suitably associated to a nonlinear flag of closed subschemes. In order to do this, we first establish some general formal gluing results for moduli o

Maxime Martinez, Gabriel Lemarié, Bertrand Georgeot, Christian Miniatura

We study coherent forward scattering (CFS) in critical disordered systems, whose eigenstates are multifractals. We give general and simple arguments that make it possible to fully characterize the dynamics of the shape and height of the CFS peak. We show that the dynamics is governed by multifractal dimensions $D_1$ and $D_2$, which suggests that CFS could b

R. Dassonneville, T. Ramos, V. Milchakov, C. Mori

We demonstrate a transmon qubit readout based on the nonlinear response to a drive of polaritonic meters in-situ coupled to the qubit. Inside a 3D readout cavity, we place a transmon molecule consisting of a transmon qubit and an ancilla mode interacting via non-perturbative cross-Kerr coupling. The cavity couples strongly only to the ancilla mode, leading t

Dan Wilson

Koopman analysis provides a general framework from which to analyze a nonlinear dynamical system in terms of a linear operator acting on an infinite-dimensional observable space. This theoretical framework provides a rigorous underpinning for widely used dynamic mode decomposition algorithms. While such methods have proven to be remarkably useful in the anal

Alex Davidson, Matthias Frei, Marten Gartner, Hamed Haddadi

The question at which layer network functionality is presented or abstracted remains a research challenge. Traditionally, network functionality was either placed into the core network, middleboxes, or into the operating system -- but recent developments have expanded the design space to directly introduce functionality into the application (and in particular

Simon Hands, Johann Ostmeyer

We employ the domain wall fermion (DWF) formulation of the Thirring model on a lattice in 2+1+1 dimensions and perform $N=1$ flavor Monte Carlo simulations. At a critical interaction strength the model features a spontaneous $\mathrm{U}(2)\rightarrow\mathrm{U}(1)\otimes \mathrm{U}(1)$ symmetry breaking; we analyse the induced spin-0 mesons, both Goldstone an

Giulio Bresciani, Angelo Vistoli

Given a perfect field $k$ with algebraic closure $\overline{k}$ and a variety $X$ over $\overline{k}$, the field of moduli of $X$ is the subfield of $\overline{k}$ of elements fixed by field automorphisms $\gamma\in\operatorname{Gal}(\overline{k}/k)$ such that the twist $X_{\gamma}$ is isomorphic to $X$. The field of moduli is contained in all subextensions

K. Gallmeister, U. Mosel, L. von Smekal

The HADES collaboration has extracted dilepton mass spectra for $\pi^-$ induced reactions on the proton from a comparison of data taken on C and CH$_2$ targets. The spectra were interpreted in terms of different versions of vector meson dominance. Here we present results obtained from the theory and generator GiBUU. We first check the subtraction procedure u

Junhong Lin, Nanfeng Jiang, Zhentao Zhang, Weiling Chen

Snow removal aims to locate snow areas and recover clean images without repairing traces. Unlike the regularity and semitransparency of rain, snow with various patterns and degradations seriously occludes the background. As a result, the state-of-the-art snow removal methods usually retains a large parameter size. In this paper, we propose a lightweight but

Genoveva Micheva, Martin M. Roth, Peter M. Weilbacher, Christophe Morisset

There are known differences between the physical properties of HII and diffuse ionized gas (DIG), but most of the studied regions in the literature are relatively bright. We compiled a faint sample of 390 HII regions with median $\log_{10}H\alpha$=34.7 in the spiral galaxy NGC300, derived their physical properties in terms of metallicity, density, extinction

E. Carli, L. Levin, B. W. Stappers, E. D. Barr

The TRAPUM collaboration has used the MeerKAT telescope to conduct a search for pulsed radio emission from the young Small Magellanic Cloud pulsar J0058-7218 located in the supernova remnant IKT 16, following its discovery in X-rays with XMM-Newton. We report no significant detection of dispersed, pulsed radio emission from this source in three 2-hour L-band

Vitalii Vertogradov

In this paper, we consider the analogy of the Penrose process in Charged Vaidya spacetime. We calculate the border of the generalized ergosphere, in which the charged particles with negative energy might exist, and show that it is temporary. We show that there are no closed orbits for particles with negative energy inside the generalized ergosphere. We inves

Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han

State-of-the-art (SOTA) semi-supervised learning (SSL) methods have been highly successful in leveraging a mix of labeled and unlabeled data by combining techniques of consistency regularization and pseudo-labeling. During pseudo-labeling, the model's predictions on unlabeled data are used for training and thus, model calibration is important in mitigating c

Kyung Ho Park, Hyunhee Chung, Soonwoo Kwon

Upon the significant performance of the supervised deep neural networks, conventional procedures of developing ML system are \textit{task-centric}, which aims to maximize the task accuracy. However, we scrutinized this \textit{task-centric} ML system lacks in engineering efficiency when the ML practitioners solve multiple tasks in their domain. To resolve th

Asa Cooper Stickland, Sailik Sengupta, Jason Krone, Saab Mansour

Advances in neural modeling have achieved state-of-the-art (SOTA) results on public natural language processing (NLP) benchmarks, at times surpassing human performance. However, there is a gap between public benchmarks and real-world applications where noise, such as typographical or grammatical mistakes, is abundant and can result in degraded performance. U

Vipin Agrawal, Dhrubaditya Mitra

We study a single, freely--floating, inextensible, elastic filament in a linear shear flow: $\mathbf{U}_{0}(x,y) = \dot{\gamma} y \hat{x}$. In our model: the elastic energy depends only on bending; the rate-of-strain, $\dot{\gamma} = S \sin(\omega t)$ is a periodic function of time, $t$; and the interaction between the filament and the flow is approximated b

Ted Thorbeck, Andrew Eddins, Isaac Lauer, Douglas T. McClure

Superconducting qubit lifetimes must be both long and stable to provide an adequate foundation for quantum computing. This stability is imperiled by two-level systems (TLSs), currently a dominant loss mechanism, which exhibit slow spectral dynamics that destabilize qubit lifetimes on hour timescales. Stability is also threatened at millisecond timescales, wh

Amine Asselah, Nicolas Forien, Alexandre Gaudillière

Activated Random Walks, on $\mathbb{Z}^d$ for any $d\geqslant 1$, is an interacting particle system, where particles can be in either of two states: active or frozen. Each active particle performs a continuous-time simple random walk during an exponential time of parameter $\lambda$, after which it stays still in the frozen state, until another active partic

Pavel Galashin, Thomas Lam, Melissa Sherman-Bennett, David Speyer

We introduce $3$-dimensional generalizations of Postnikov's plabic graphs and use them to establish cluster structures for type $A$ braid varieties. Our results include known cluster structures on open positroid varieties and double Bruhat cells, and establish new cluster structures for type $A$ open Richardson varieties.

Kewen Li, Wenlong Liu, Yimin Dou, Zhifeng Xu

Recently, seismic facies classification based on convolutional neural networks (CNN) has garnered significant research interest. However, existing CNN-based supervised learning approaches necessitate massive labeled data. Labeling is laborious and time-consuming, particularly for 3D seismic data volumes. To overcome this challenge, we propose a semi-supervis

Cecilia Herrero, Camille Scalliet, M. D. Ediger, Ludovic Berthier

The discovery of ultrastable glasses has raised novel challenges about glassy systems. Recent experiments studied the macroscopic devitrification of ultrastable glasses into liquids upon heating but lacked microscopic resolution. We use molecular dynamics simulations to analyse the kinetics of this transformation. In the most stable systems, devitrification

Negin Gorlezaei, Patrick Jaillet, Zijie Zhou

We study an online resource allocation problem under uncertainty about demand and about the reward of each type of demand (agents) for the resource. Even though dealing with demand uncertainty in resource allocation problems has been the topic of many papers in the literature, the challenge of not knowing rewards has been barely explored. The lack of knowled

Henry Liu

We define a multiplicative version of vertex coalgebras and show that various equivariant K-theoretic constructions of Hall algebras (KHAs) also admit a compatible multiplicative vertex coalgebra structure. In particular, this is true of the preprojective KHA of Varagnolo--Vasserot, which is (conjecturally) isomorphic to certain quantum loop algebras.

Benjamin J. Walker, Kenta Ishimoto, Eamonn A. Gaffney

Simple models are used throughout the physical sciences as a means of developing intuition, capturing phenomenology, and qualitatively reproducing observations. In studies of microswimming, simple force-dipole models are commonplace, arising generically as the leading-order, far-field descriptions of a range of complex biological and artificial swimmers. Tho

Joice Mathew, James Gilbert, Robert Sharp, Alexey Grigoriev

For a remote sensing optical payload to achieve a Ground Sampling Distance of ~ 10-30 m, a critical problem is platform-induced motion blur. While forward motion compensation can reduce this transit speed, it comes at the expense of a more challenging satellite attitude control system and induces a variable observation/illumination angle. This relative motio

Qian Hu, John Veitch

Observations of gravitational waves (GWs) from compact binary coalescences provide powerful tests of general relativity (GR), but systematic errors in data analysis could lead to incorrect scientific conclusions. This issue is especially serious in the third-generation GW detectors in which the signal-to-noise ratio (SNR) is high and the number of detections

Michael Adam

This paper is the documentation of a pre-study performed by AXA Konzern AG in collaboration with Fraunhofer ITWM to assess the relevance of quantum computing for the insurance industry. Beside a general overview of the status quo of quantum computing technologies, we investigate its applicability for the valuation of insurance contracts as a concrete use cas

Joshua A. Rackers, Pranav Rao

Equivariant machine learning methods have shown wide success at 3D learning applications in recent years. These models explicitly build in the reflection, translation and rotation symmetries of Euclidean space and have facilitated large advances in accuracy and data efficiency for a range of applications in the physical sciences. An outstanding question for

Marina Artuso, Robert H. Bernstein, Alexey A. Petrov

This is the Snowmass 2021 Rare and Precision Frontier Report. The Rare Processes and Precision Measurements Frontier, referred to as the ``Rare and Precision Frontier", or RPF, encompasses searches for extremely rare processes or tiny deviations from the Standard Model (SM) that can be studied with intense sources and high-precision detectors. Our community

Hina Binte Haq, Syed Taha Ali, Ronan McDermott

In recent years end-to-end verifiable voting (E2EVV) has emerged as a promising new paradigm to conduct evidence-based elections. However, E2EVV systems thus far have primarily been designed for the developed world and the fundamental assumptions underlying the design of these systems do not readily translate to the developing world, and may even act as pote

Wei Xiao, Tsun-Hsuan Wang, Ramin Hasani, Mathias Lechner

We propose a new method to ensure neural ordinary differential equations (ODEs) satisfy output specifications by using invariance set propagation. Our approach uses a class of control barrier functions to transform output specifications into constraints on the parameters and inputs of the learning system. This setup allows us to achieve output specification

Xin Ren, Kohji Yanagawa

For a partition $\lambda$ of $n$, the _Specht ideal_ $I_\lambda \subset K[x_1, \ldots, x_n]$ is the ideal generated by all Specht polynomials of shape $\lambda$. In their unpublished manuscript, Haiman and Woo showed that $I_\lambda$ is a radical ideal, and gave its universal Gr\"obner bases (recently, Murai et al. published a quick proof of this result). On

George M. French, Marc Sher

Weakly interacting massive particles (WIMPs) can be captured by the Sun and annihilate in the core, which may result in production of kaons that can decay at rest into monoenergetic 236 MeV neutrinos. Several studies of detection of these neutrinos at DUNE have been carried out. It has been shown that if the WIMP mass is below 4 GeV, then they will evaporate

Tien-Cuong Dinh, Cécile Gachet, Hsueh-Yung Lin, Keiji Oguiso

The aim of this paper is twofold. First of all, we confirm a few basic criteria of the finiteness of real forms of a given smooth complex projective variety, in terms of the Galois cohomology set of the discrete part of the automorphism group, the cone conjecture and the topological entropy. We then apply them to show that a smooth complex projective surface

Kunal Pal, Kuntal Pal, Tapobrata Sarkar

We consider torsion in parameter manifolds that arises via conformal transformations of the Fisher information metric, and define it for information geometry of a wide class of physical systems. The torsion can be used to differentiate between probability distribution functions that otherwise have the same scalar curvature and hence define similar geometries

Maohua Le, Anitha Srinivasan

A conjecture of N. Terai states that for any integer $k>1$, the equation $x^2+(2k-1)^y =k^z$ has only one solution, namely, $(x, y, z) = (k-1, 1, 2).$ Using the structure of class groups of binary quadratic forms, we prove the conjecture when $4\Vert k$, with $2k-1$ a prime power and $4\le k\le 1000$.

Edward Duc Hien Nguyen, Sulaiman A. Alghunaim, Kun Yuan, César A. Uribe

We study the decentralized optimization problem where a network of $n$ agents seeks to minimize the average of a set of heterogeneous non-convex cost functions distributedly. State-of-the-art decentralized algorithms like Exact Diffusion~(ED) and Gradient Tracking~(GT) involve communicating every iteration. However, communication is expensive, resource inten

Giorgio Ottolina, John Pavlopoulos

This study presents a new approach to metaphorical paraphrase generation by masking literal tokens of literal sentences and unmasking them with metaphorical language models. Unlike similar studies, the proposed algorithm does not only focus on verbs but also on nouns and adjectives. Despite the fact that the transfer rate for the former is the highest (56%),

Ansgar Wehrhahn, Nikolai Piskunov, Tanja Ryabchikova

The characterization of exoplanet requires reliable determination of the fundamental parameters of their host stars. Spectral fitting plays an important role in this process. For the majority of stellar parameters matching synthetic spectra to the observations provides a robust and unique solution for fundamental parameters, such as effective temperature, su

Yan Gong, Georgina Cosma

Visual Semantic Embedding (VSE) aims to extract the semantics of images and their descriptions, and embed them into the same latent space for cross-modal information retrieval. Most existing VSE networks are trained by adopting a hard negatives loss function which learns an objective margin between the similarity of relevant and irrelevant image-description

Youngjun Lee, Seungjun Lee, Jaewu Choi, Chinkyo Kim

Thru-hole epitaxy has recently been reported to be able to grow readily detachable domains crystallographically aligned with the underlying substrate over 2D mask material transferred onto a substrate. [Jang \textit{et al.}, \textit{Adv. Mater. Interfaces}, \textbf{2023} \textit{10}, 4 2201406] While the experimental demonstration of thru-hole epitaxy of GaN

Noe Angelo Caruso

We analyse the Krylov solvability of inverse linear problems on Hilbert space $\mathcal{H}$ where the underlying operator is compact and normal. Krylov solvability is an important feature of inverse linear problems that has profound implications in theoretical and applied numerical analysis as it is critical to understand the utility of Krylov based methods

Xue-Feng Pan, Xin-Lei Hei, Xing-Liang Dong, Jia-Qiang Chen

Spin-mechanical hybrid systems have been widely used in quantum information processing. However, the spin-mechanical interaction is generally weak, making it a critical challenge to enhance the spin-mechanical interaction into the strong coupling or even ultra-strong coupling regime. Here, we propose a protocol that can significantly enhance the spin-mechani

Dmitry Ponomarev

In this short paper, we consider a sliding punch problem under recently proposed model of wear which is based on the Riemann-Liouville fractional integral relation between pressure and worn volume, and incorporates another additional effect pertinent to relaxation. A particular case of oscillatory (time-harmonic) load is studied. The time-dependent stationar

R. Aguilar-Sanchez, I. F. Herrera-Gonzalez, J. A. Mendez-Bermudez, Jose M. Sigarreta

Given a simple connected non-directed graph $G=(V(G),E(G))$, we consider two families of graph invariants: $RX_\Sigma(G) = \sum_{uv \in E(G)} F(r_u,r_v)$ (which has gained interest recently) and $RX_\Pi(G) = \prod_{uv \in E(G)} F(r_u,r_v)$ (that we introduce in this work); where $uv$ denotes the edge of $G$ connecting the vertices $u$ and $v$, $r_u$ is the R

Shuang Chen, Jinqiao Duan

We study the spectra for a class of differential operators with asymptotically constant coefficients.These operators widely arise as the linearizations of nonlinear partial differential equations about patterns or nonlinear waves. We present a unified framework to prove the perturbation results on the related spectra. The proof is based on exponential dichot

Shiwen He, Kangli Cai, Shiyue Huang, Zhenyu Anz

The millimeter-wave (mmWave)-based Wi-Fi sensing technology has recently attracted extensive attention since it provides a possibility to realize higher sensing accuracy. However, current works mainly concentrate on sensing scenarios where the line-of-sight (LoS) path exists, which significantly limits their applications. To address the problem, we propose a

Marcel Maier

In the main part of this PhD thesis, we consider a periodically realized microscopic superconductor described by BCS theory, which is subject to external electromagnetic fields. We show that the superconductor is properly described by Ginzburg--Landau theory in the macroscopic and weak magnetic field limit. The main novelty of our results is to allow for a n

Daniele Ancora, Matteo Negri, Antonio Gianfrate, Dimitris Trypogeorgos

In the domain of disordered photonics, the characterization of optically opaque materials for light manipulation and imaging is a primary aim. Among various complex devices, multi-mode optical fibers stand out as cost-effective and easy-to-handle tools, making them attractive for several tasks. In this context, we cast these fibers into random hardware proje

Paul Minter

For each positive integer $Q\in\mathbb{Z}_{\geq 2}$, we prove a multi-valued $C^{1,\alpha}$ regularity theorem for varifolds in the class $\mathcal{S}_Q$, i.e., stable codimension one stationary integral $n$-varifolds which have no classical singularities of vertex density $<Q$, which are sufficiently close to a stationary integral cone comprised of $2Q+1$ h

Tobias Mai

The so-called density of states is a Borel probability measure on the real line associated with the solution of the Dyson equation which we set up, on any fixed $C^\ast$-probability space, for a selfadjoint offset and a $2$-positive linear map. Using techniques from free noncommutative function theory, we prove explicit H\"older bounds for the L\'evy distanc

J. L. Rodríguez-Sánchez, A. Graña-González, J. Benlliure, A. Chatillon

In the last decades, measurements of spallation, fragmentation and Coulex induced fission reactions in inverse kinematics have provided valuable data to accurately investigate the fission dynamics and nuclear structure at large deformations of a large variety of stable and non-stable heavy nuclei. To go a step further, we propose now to induce fission by the

Dimitrios Ntalampekos

We present sufficient conditions so that a conformal map between planar domains whose boundary components are Jordan curves or points has a continuous or homeomorphic extension to the closures of the domains. Our conditions involve the notions of cofat domains and CNED sets, i.e., countably negligible for extremal distance, recently introduced by the author.

Paolo Leonetti

Let $\succsim$ be a binary relation on the set of simple lotteries over a countable outcome set $Z$. We provide necessary and sufficient conditions on $\succsim$ to guarantee the existence of a set $U$ of von Neumann--Morgenstern utility functions $u: Z\to \mathbf{R}$ such that $$ p\succsim q \,\,\,\Longleftrightarrow\,\,\, \mathbf{E}_p[u] \ge \mathbf{E}_q[u

Caio Corro

Span-based nested named-entity recognition (NER) has a cubic-time complexity using a variant of the CYK algorithm. We show that by adding a supplementary structural constraint on the search space, nested NER has a quadratic-time complexity, that is the same asymptotic complexity than the non-nested case. The proposed algorithm covers a large part of three st

Piotr Kubala, Michał Cieśla, Lech Longa

We studied equilibrium systems composed of wedge-shaped monodisperse molecules using hard-particle Monte Carlo simulations. Each model molecule was made up of six colinear tangent spheres with linearly decreasing diameters. Thus, the shape was unequivocally described by a single parameter $d$: the ratio of the smallest and largest diameters of the spheres. T

Ph. André, P. Palmeirim, D. Arzoumanian

Herschel studies suggest that nearby (d < 500 pc) molecular filaments have a typical half-power width ~0.1pc, but this finding has been questioned on the ground that the measured widths tend to increase with distance. Here we revisit the dependence of measured filament widths on distance or equivalently spatial resolution, in an effort to determine whether n

Shokhrukh Miraliev, Shakhboz Abdigapporov, Jumabek Alikhanov, Vijay Kakani

A safe and robust autonomous driving system relies on accurate perception of the environment for application-oriented scenarios. This paper proposes deployment of the three most crucial tasks (i.e., object detection, drivable area segmentation and lane detection tasks) on embedded system for self-driving operations. To achieve this research objective, multi-

A. P. Dimmock, E. Yordanova, D. B. Graham, Yu. V. Khotyaintsev

Mirror modes are ubiquitous in space plasma and grow from pressure anisotropy. Together with other instabilities, they play a fundamental role in constraining the free energy contained in the plasma. This study focuses on mirror modes observed in the solar wind by Solar Orbiter for heliocentric distances between 0.5 and 1 AU. Typically, mirror modes have tim

Hadi Farahani, Hamid Reza Shahriari

In recent years, the volume of data generated by IoT devices has increased dramatically. Using this data can improve decision-making in the public and private sectors and increase productivity. Many attempts have been made to enhance and adapt businesses to exploit this IoT data. Among these, IoT data trading is the most popular approach. To this end, ongoin

Tongzhu Li, Xiang Ma, Changping Wang, Peng Wang

Let $\mathbb{M}(\mathbb{S}^{n+1})$ denote the M\"{o}bius transformation group of the $(n+1)$-dimensional sphere $\mathbb{S}^{n+1}$. A hypersurface $x:M^n\to \mathbb{S}^{n+1}$ is called a M\"{o}bius homogeneous hypersurface if there exists a subgroup $G$ of $\mathbb{M}(\mathbb{S}^{n+1})$ such that the orbit $G\cdot p=x(M^n), p\in x(M^n)$. In this paper, the M

Andrei Kulikovsky

Transient Navies--Stokes equations for laminar flow of incompressible fluid in a channel with permeable wall are reduced to a single equation for the transversal profile of longitudinal flow velocity. Small--amplitude harmonic perturbation of injection velocity induces oscillations of longitudinal velocity with the peak at the walls. The oscillations amplitu

Riccardo Caniato, Filippo Gaia

For every given $p\in [1,+\infty)$ and $n\in\mathbb{N}$ with $n\ge 1$, the authors identify the strong $L^p$-closure $L_{\mathbb{Z}}^p(D)$ of the class of vector fields having finitely many integer topological singularities on a domain $D$ which is either bi-Lipschitz equivalent to the open unit $n$-dimensional cube or to the boundary of the unit $(n+1)$-dim

Dougal Maclaurin, Alexey Radul, Adam Paszke

Correctly manipulating program terms in a compiler is surprisingly difficult because of the need to avoid name capture. The rapier from "Secrets of the Glasgow Haskell Compiler inliner" is a cutting-edge technique for fast, stateless capture-avoiding substitution for expressions represented with explicit names. It is, however, a sharp tool: its invariants ar

Mathias Lechner, Ramin Hasani, Philipp Neubauer, Sophie Neubauer

Hyperparameter tuning is a fundamental aspect of machine learning research. Setting up the infrastructure for systematic optimization of hyperparameters can take a significant amount of time. Here, we present PyHopper, a black-box optimization platform designed to streamline the hyperparameter tuning workflow of machine learning researchers. PyHopper's goal

Donald M. Davis, W. Stephen Wilson

We compute ku^*(K(Z/p,2)) and ku_*(K(Z/p,2)), the connective KU-cohomology and connective KU-homology groups of the mod-p Eilenberg-MacLane space K(Z/p,2), using the Adams spectral sequence. We obtain a striking interaction between h_0-extensions and exotic extensions. The mod-p connective KU-cohomology groups, computed elsewhere, are needed in order to esta

Cicero Nogueira dos Santos, Zhe Dong, Daniel Cer, John Nham

Soft prompts have been recently proposed as a tool for adapting large frozen language models (LMs) to new tasks. In this work, we repurpose soft prompts to the task of injecting world knowledge into LMs. We introduce a method to train soft prompts via self-supervised learning on data from knowledge bases. The resulting soft knowledge prompts (KPs) are task i

Chi-Ming Chang, Wei Cui, Wen-Jie Ma, Hongfei Shu

We study scattering amplitudes in the shadow conformal primary basis, which satisfies the same defining properties as the original conformal primary basis and has many advantages over it. The shadow celestial amplitudes exhibit locality manifestly on the celestial sphere, and behave like correlation functions in conformal field theory under the operator prod

Mohammad Afzal Shadab, Marc Andre Hesse

Richards equation is often used to represent two-phase fluid flow in an unsaturated porous medium when one phase is much heavier and more viscous than the other. However, it cannot describe the fully saturated flow for some capillary functions without specialized treatment due to degeneracy in the capillary pressure term. Mathematically, gravity-dominated va

Amal Alabdulkarim, Madhuri Singh, Gennie Mansi, Kaely Hall

Reinforcement learning (RL) systems can be complex and non-interpretable, making it challenging for non-AI experts to understand or intervene in their decisions. This is due in part to the sequential nature of RL in which actions are chosen because of their likelihood of obtaining future rewards. However, RL agents discard the qualitative features of their t

Franziska Dettner, Simon Hilpert

A high temporal and spatial resolution emission inventory for the North Sea and Baltic Sea for the year 2015 was compiled using current emission factors and ship activity data. The inventory includes seagoing vessels over 100 GT registered with the International Maritime Organisation traversing in the North and Baltic Seas. A bottom-up approach was chosen fo

Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Franck Dernoncourt

Multimedia summarization with multimodal output (MSMO) is a recently explored application in language grounding. It plays an essential role in real-world applications, i.e., automatically generating cover images and titles for news articles or providing introductions to online videos. However, existing methods extract features from the whole video and articl

E. Franciosini, S. Randich, P. de Laverny, K. Biazzo

The Gaia-ESO Survey (GES) is a large public spectroscopic survey that was carried out using the multi-object FLAMES spectrograph at the Very Large Telescope. The survey provides accurate radial velocities, stellar parameters, and elemental abundances for ~115,000 stars in all Milky Way components. In this paper we describe the method adopted in the final dat

Huaying Wei, Katsuhiko Matsuzaki

We verify that the $p$-integrable Teichm\"uller space $T_p$ admits the canonical complex Banach manifold structure for any $p \geq 1$. Moreover, we characterize a quasisymmetric homeomorphism corresponding to an element of $T_p$ in terms of the $p$-Besov space for any $p>1$.

Bojun Zhao

Let $M$ be a connected, closed, orientable, irreducible $3$-manifold. We show that: if $M$ admits a co-orientable taut foliation $\mathcal{F}$ with orderable cataclysm, then $\pi_1(M)$ is left orderable. This provides an elementary proof that $\pi_1(M)$ is left orderable if $M$ admits an Anosov flow with a co-orientable stable foliation without using Thursto

Lisi Li, Huili Liu, Maxim Avdeev, Dehong Yu

We present studies on crystal structure and ionic diffusion behaviors of superionic Cu$_{2-\delta}$Se ($\delta$=0, 0.04, and 0.2) by utilizing neutron powder diffraction and quasi-elastic neutron scattering. In the superionic phase, the structural model with Cu ions occupying the Wyckoff sites of 8$c$ and 32$f$ provides the best description of the structure.

Ming-Chien Hsu, En-Jui Kuo, Wei-Hsuan Yu, Jian-Feng Cai

The recovery of an unknown density matrix of large size requires huge computational resources. The recent Factored Gradient Descent (FGD) algorithm and its variants achieved state-of-the-art performance since they could mitigate the dimensionality barrier by utilizing some of the underlying structures of the density matrix. Despite their theoretical guarante

Thomas Saout, Frédéric Lardeux, Frédéric Saubion

The automated analysis of administrative documents is an important field in document recognition that is studied for decades. Invoices are key documents among these huge amounts of documents available in companies and public services. Invoices contain most of the time data that are presented in tables that should be clearly identified to extract suitable inf

Chen Ding, Chao Dang, Marcos A. Valdebenito, Matthias G. R. Faes

First-passage probability estimation of high-dimensional nonlinear stochastic systems is a significant task to be solved in many science and engineering fields, but remains still an open challenge. The present paper develops a novel approach, termed 'fractional moments-based mixture distribution', to address such challenge. This approach is implemented by ca

Yuxin Xiao, Paul Pu Liang, Umang Bhatt, Willie Neiswanger

Pre-trained language models (PLMs) have gained increasing popularity due to their compelling prediction performance in diverse natural language processing (NLP) tasks. When formulating a PLM-based prediction pipeline for NLP tasks, it is also crucial for the pipeline to minimize the calibration error, especially in safety-critical applications. That is, the

Justin Kin Jun Hew, Rod W. Boswell, Christoph Federrath, Rajesh Gopalapillai

A combined analytical and numerical study is conducted to investigate the asymmetric cap-shock non-uniform Mach Reflection (csMR) phenomenon outside of an over-expanded supersonic jet. Prior analytical works have only considered the wedge-induced steady symmetric and asymmetric Mach reflection (MR) configurations, as well as symmetric MR in an open jet. Howe

Dániel Gerbner, Balázs Keszegh, Dániel Lenger, Dániel T. Nagy

We study $\mathrm{exa}_k(n,F)$, the largest number of edges in an $n$-vertex graph $G$ that contains exactly $k$ copies of a given subgraph $F$. The case $k=0$ is the Tur\'an number $\mathrm{ex}(n,F)$ that is among the most studied parameters in extremal graph theory. We show that for any $F$ and $k$, $\mathrm{exa}_k(n,F)=(1+o(1))\mathrm{ex}(n,F))$ and deter

M. Diomede, V. Ayvazyan, J. Branlard, M. Grecki

The European XFEL (EuXFEL) is a free-electron laser in the X-ray range for users. Its high availability is one of the key aspects of the machine. In 2022, it entered in the sixth year of operation. The EuXFEL linac is based on the TESLA superconducting RF technology, operating at 1.3 GHz with an RF pulse length of 650 $\mu$s and a repetition rate of 10 Hz. T

Megha Sundriyal, Atharva Kulkarni, Vaibhav Pulastya, Md Shad Akhtar

The widespread diffusion of medical and political claims in the wake of COVID-19 has led to a voluminous rise in misinformation and fake news. The current vogue is to employ manual fact-checkers to efficiently classify and verify such data to combat this avalanche of claim-ridden misinformation. However, the rate of information dissemination is such that it

Panagiotis Chatzipantelidis, Christos Pervolianakis

For a Keller-Segel model for chemotaxis in two spatial dimensions we consider a modification of a positivity preserving fully discrete scheme using a local extremum diminishing flux limiter. We discretize space using piecewise linear finite elements on an quasiuniform triangulation of acute type and time by the backward Euler method. We assume that initial d

Fan Zhang, Shaodi You, Yu Li, Ying Fu

Rain is transparent, which reflects and refracts light in the scene to the camera. In outdoor vision, rain, especially rain streaks degrade visibility and therefore need to be removed. In existing rain streak removal datasets, although density, scale, direction and intensity have been considered, transparency is not fully taken into account. This problem is

Dominic Anstey, Eloy de Lera Acedo, Will Handley

Global 21cm cosmology aims to investigate the cosmic dawn and epoch of reionisation by measuring the sky averaged HI absorption signal, which requires, accurate modelling of, or correction for, the bright radio foregrounds and distortions arising from chromaticity of the antenna beam. We investigate the effect of improving foreground modelling by fitting dat

David Müller-Bender, Günter Radons

A new type of chaos called laminar chaos was found in singularly perturbed dynamical systems with periodic time-varying delay [Phys. Rev. Lett. 120, 084102 (2018)]. It is characterized by nearly constant laminar phases, which are periodically interrupted by irregular bursts, where the intensity levels of the laminar phases vary chaotically from phase to phas

Zheheng Luo, Qianqian Xie, Sophia Ananiadou

Different from general documents, it is recognised that the ease with which people can understand a biomedical text is eminently varied, owing to the highly technical nature of biomedical documents and the variance of readers' domain knowledge. However, existing biomedical document summarization systems have paid little attention to readability control, leav