May 2023 arXiv papers — page 116

Robert Graubohm, Nayel Fabian Salem, Marcus Nolte, Markus Maurer

Automated driving systems are subject to various kinds of uncertainty during design, development, and operation. These kinds of uncertainty lead to an inherent risk of the technology that can be mitigated, but never fully eliminated. Situations involving obscured traffic participants have become popular examples in the field to illustrate a subset of these u

Bohan Li, Dan Xie, WenBin Yan

Gaiotto and Witten found that one can construct 3d $\mathcal{N}=4$ Chern-Simons matter theories by using $\mathcal{N}=4$ SCFT whose momentum map of global symmetries satisfy special condition. Usually, one uses free hypermultiplet and twisted hypermultiplet, and more recently it was found that strongly coupled theory such as 3d version of $T_N$ theory and Ar

Zihao Wu, Janko Boehm, Rourou Ma, Hefeng Xu

In this work, we present the package {\sc NeatIBP}, which automatically generates small-size integration-by-parts (IBP) identities for Feynman integrals. Based on the syzygy and module intersection techniques, the generated IBP identities' propagator degree is controlled and thus the size of the system of IBP identities is shorter than that generated by the

Hsin-Wei Hung, Ardalan Amiri Sani

The eBPF technology in the Linux kernel has been widely adopted for different applications, such as networking, tracing, and security, thanks to the programmability it provides. By allowing user-supplied eBPF programs to be executed directly in the kernel, it greatly increases the flexibility and efficiency of deploying customized logic. However, eBPF also i

Vidya Sagar, Ritumoni Sarma

In this article, we construct linear codes over the commutative non-unital ring $I$ of size four. We obtain their Lee-weight distributions and study their binary Gray images. Under certain mild conditions, these classes of binary codes are minimal and self-orthogonal. All codes in this article are few-weight codes. Besides, an infinite class of these binary

Andras Szenes, Olga Trapeznikova

Type-A toric varieties may be obtained as GIT quotients with respect to a torus action with weights corresponding to roots of the group $SL(k)$ for some $k>1$. These varieties appear in various important applications, in particular, as normal cones to strata in moduli spaces of vector bundles. In this paper, we describe the intersection Betti numbers of thes

Oscar Morris

Neural networks and in particular the attention mechanism have brought significant advances to the field of Automated Essay Scoring. Many of these systems use a regression-based model which may be prone to underfitting when the model only predicts the mean of the training data. In this paper, we present a dynamic loss function that creates an incentive for t

Matthew Korban, Peter Young, Scott T. Acton

This paper proposes a novel age estimation algorithm, the Temporally-Aware Adaptive Graph Convolutional Network (TAA-GCN). Using a new representation based on graphs, the TAA-GCN utilizes skeletal, posture, clothing, and facial information to enrich the feature set associated with various ages. Such a novel graph representation has several advantages: First,

Maria Mahbub, Ian Goethert, Ioana Danciu, Kathryn Knight

Background: Injection drug use (IDU) is a dangerous health behavior that increases mortality and morbidity. Identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients' electronic health records (EHR) is difficult because there is no International Classification of Disease

Zhimin Chen, Longlong Jing, Yingwei Li, Bing Li

Foundation models have achieved remarkable results in 2D and language tasks like image segmentation, object detection, and visual-language understanding. However, their potential to enrich 3D scene representation learning is largely untapped due to the existence of the domain gap. In this work, we propose an innovative methodology called Bridge3D to address

Seray Şahin, Patrick Antolin, Clara Froment, Thomas A. Schad

The solar corona produces coronal rain, hundreds of times colder and denser material than the surroundings. Coronal rain is known to be deeply linked to coronal heating, but its origin, dynamics, and morphology are still not well understood. The leading theory for its origin is thermal instability (TI) occurring in coronal loops in a state of thermal non-equ

Leonardo Zambrano, Luciano Pereira, Aldo Delgado

We present an analytical method to estimate pure quantum states using a minimum of three measurement bases in any finite-dimensional Hilbert space. This is optimal as two bases are insufficient to construct an informationally complete positive operator-valued measurement (IC-POVM) for pure states. We demonstrate our method using a binary tree structure, prov

Giulio Binosi

We extend some definitions and give new results about the theory of slice analysis in several quaternionic variables. The sets of slice functions which are respectively slice, slice regular and circular w.r.t. given variables are characterized. We introduce new notions of partial spherical value and derivative for functions of several variables that extend t

Prabhat kumar

Permitting multiple materials within a topology optimization setting increases the search space of the technique, which facilitates obtaining high-performing and efficient optimized designs. Structures with multiple materials involving fluidic pressure loads find various applications. However, dealing with the design-dependent nature of the pressure loads is

Supawit Chockchowwat, Zhaoheng Li, Yongjoo Park

In machine learning (ML), Python serves as a convenient abstraction for working with key libraries such as PyTorch, scikit-learn, and others. Unlike DBMS, however, Python applications may lose important data, such as trained models and extracted features, due to machine failures or human errors, leading to a waste of time and resources. Specifically, they la

Axel Brandenburg, Gustav Larsson

Magnetic helicity plays a tremendously important role when it is different from zero on average. Most notably, it leads to the phenomenon of an inverse cascade. Here, we consider decaying magnetohydrodynamic (MHD) turbulence as well as some less common examples of magnetic evolution under the Hall effect and ambipolar diffusion, as well as cases in which the

Robin Piedeleu, Fabio Zanasi

This document is an elementary introduction to string diagrams. It takes a computer science perspective: rather than using category theory as a starting point, we build on intuitions from formal language theory, treating string diagrams as a syntax with its semantics. After the basic theory, pointers are provided to contemporary applications of string diagra

Firas Bayram, Phil Aupke, Bestoun S. Ahmed, Andreas Kassler

Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role in optimizing energy scheduling and enabling more flexible and intelligent power grid systems. As a result, these systems allow power utility companies to respond promptly to demands in the electricity market. Deep learning (DL) models have been commonly employed in

A. Chomez, A. -M. Lagrange, P. Delorme, M. Langlois

We aim at searching for exoplanets on the whole ESO/VLT-SPHERE archive with improved and unsupervised data analysis algorithm that could allow to detect massive giant planets at 5 au. To prepare, test and optimize our approach, we gathered a sample of twenty four solar-type stars observed with SPHERE using angular and spectral differential imaging modes. We

Hong-peng Lu, Hui Tian, He-chao Chen, Yu Xu

Coronal mass ejections (CMEs) are violent ejections of magnetized plasma from the Sun, which can trigger geomagnetic storms, endanger satellite operations and destroy electrical infrastructures on the Earth. After systematically searching Sun-as-a-star spectra observed by the Extreme-ultraviolet Variability Experiment (EVE) onboard the Solar Dynamics Observa

Tomasz Cieślak, Piotr Kokocki, Wojciech S. Ożański

We consider Alexander spirals with $M\geq 3$ branches, that is symmetric logarithmic spiral vortex sheets. We show that such vortex sheets are linearly unstable in the $L^\infty$ (Kelvin-Helmholtz) sense, as solutions to the Birkhoff-Rott equation. To this end we consider Fourier modes in a logarithmic variable to identify unstable solutions with polynomial

Marcin Copik, Roman Böhringer, Alexandru Calotoiu, Torsten Hoefler

Serverless functions provide elastic scaling and a fine-grained billing model, making Function-as-a-Service (FaaS) an attractive programming model. However, for distributed jobs that benefit from large-scale and dynamic parallelism, the lack of fast and cheap communication is a major limitation. We overcome this limitation and present the FaaS Message Interf

Babak Sadigh, Daniel Aberg, John Pask

We introduce a general, variational scheme applied to Kohn-Sham density functional theory that allows for partitioning of the ground-state density matrix into distinct spectral domains, each of which spanned by an independent diagonal representation without requirement of mutual orthogonality. It is shown that by generalizing the entropic contribution to the

Lucio Galeati, Dejun Luo

A fundamental open problem in fluid dynamics is whether solutions to $2$D Euler equations with $(L^1_x\cap L^p_x)$-valued vorticity are unique, for some $p\in [1,\infty)$. A related question, more probabilistic in flavour, is whether one can find a physically relevant noise regularizing the PDE. We present some substantial advances towards a resolution of th

Ioana Lal, Constantin Morarescu, Jamal Daafouz, Lucian Busoniu

We propose two new optimistic planning algorithms for nonlinear hybrid-input systems, in which the input has both a continuous and a discrete component, and the discrete component must respect a dwell-time constraint. Both algorithms select sets of input sequences for refinement at each step, along with a continuous or discrete step to refine (split). The dw

Enide Andrade, Dante Carrasco-Olivera, Cristina Manzaneda

In this paper, closed formulas for the eigenvectors of a particular class of matrices generated by generalized permutation matrices, named generalized circulant matrices, are presented.

Akun Liang, Robin Turnbull, Catalin Popescu, Ismael Fernandez-Guillen

The crystal structure of CH3NH3PbBr3 perovskite has been investigated under high-pressure by synchrotron-based powder X-ray diffraction. We found that after the previously reported phase transitions in CH3NH3PbBr3 (Pm-3m->Im-3->Pmn21), which occur below 2 GPa, there is a third transition to a crystalline phase at 4.6 GPa. This transition is reported here for

Cooper Lorsung, Zijie Li, Amir Barati Farimani

Solving Partial Differential Equations (PDEs) is the core of many fields of science and engineering. While classical approaches are often prohibitively slow, machine learning models often fail to incorporate complete system information. Over the past few years, transformers have had a significant impact on the field of Artificial Intelligence and have seen i

Bernardo Araneda

We give a simple prescription for relating different solutions to the zero-rest-mass field equations in conformally flat space-time via complex conformal transformations and changes in reality conditions. We give several examples including linearized black holes. In particular, we show that the linearized Plebanski-Demianski and Schwarzschild fields are rela

Zhichao Wang, Xin Zhou

We prove that in the three dimensional sphere with a bumpy metric or a metric with positive Ricci curvature, there exist at least four distinct embedded minimal two-spheres. This confirms a conjecture of S. T. Yau in 1982 for bumpy metrics and metrics with positive Ricci curvature. The proof relies on a multiplicity one theorem for the Simon-Smith min-max th

Dang Qua Nguyen, Taejoon Kim

Approximate message passing (AMP) is a scalable, iterative approach to signal recovery. For structured random measurement ensembles, including independent and identically distributed (i.i.d.) Gaussian and rotationally-invariant matrices, the performance of AMP can be characterized by a scalar recursion called state evolution (SE). The pseudo-Lipschitz (polyn

Samuel Lanthaler, T. Konstantin Rusch, Siddhartha Mishra

Coupled oscillators are being increasingly used as the basis of machine learning (ML) architectures, for instance in sequence modeling, graph representation learning and in physical neural networks that are used in analog ML devices. We introduce an abstract class of neural oscillators that encompasses these architectures and prove that neural oscillators ar

Alexander Hoelzemann, Kristof Van Laerhoven

Research into the detection of human activities from wearable sensors is a highly active field, benefiting numerous applications, from ambulatory monitoring of healthcare patients via fitness coaching to streamlining manual work processes. We present an empirical study that evaluates and contrasts four commonly employed annotation methods in user studies foc

Nikolay Borozenets

In this paper, we build on recent results of Frank Garvan and Rishabh Sarma as well as classical results of Bruce Berndt in order to establish the 11-dissection of the deviations of the rank and crank modulo 11. Using our new dissections we re-derive results of Garvan, Atkin, Swinnerton-Dyer, Hussain and Ekin. By developing and exploiting positivity conditio

Shenyang Huang, Jacob Danovitch, Guillaume Rabusseau, Reihaneh Rabbany

How can we detect traffic disturbances from international flight transportation logs or changes to collaboration dynamics in academic networks? These problems can be formulated as detecting anomalous change points in a dynamic graph. Current solutions do not scale well to large real-world graphs, lack robustness to large amounts of node additions/deletions,

R. E. Arias

Magnonics, an emerging field of Magnetism, studies spin waves (SWs) in nano-structures, with an aim towards possible applications. As information may be eventually transmitted with efficiency stored in the phase and amplitude of spin waves, a topic of interest within Magnonics is the propagation of SW modes. Thus, understanding mechanisms that may influence

Francesco Tropeano

We determine the relative monodromy group of abelian logarithms with respect to periods in the cases of fibered products of elliptic schemes. This gives rise to a result stronger than a theorem due to Y. Andr\'e and implies in particular the algebraic independence of the logarithm of any non-torsion section and the periods. We then conjecture an analogous re

Victor Morel, Simone Fischer-Hübner

Users are often overwhelmed by privacy decisions to manage their personal data, which can happen on the web, in mobile, and in IoT environments. These decisions can take various forms -- such as decisions for setting privacy permissions or privacy preferences, decisions responding to consent requests, or to intervene and ``reject'' processing of one's person

Christopher E. Overton, Rachel Abbey, Tarrion Baird, Rachel Christie

Objectives: To identify and quantify risk factors that contribute to clusters of COVID-19 in the workplace. Methods: We identified clusters of COVID-19 cases in the workplace and investigated the characteristics of the individuals, the workplaces, the areas they work, and the methods of commute to work, through data linkages based on Middle Layer Super Outpu

Huajian Fang, Dennis Becker, Stefan Wermter, Timo Gerkmann

Supervised masking approaches in the time-frequency domain aim to employ deep neural networks to estimate a multiplicative mask to extract clean speech. This leads to a single estimate for each input without any guarantees or measures of reliability. In this paper, we study the benefits of modeling uncertainty in clean speech estimation. Prediction uncertain

Z. Hawkhead, T. J. Hicken, N. P. Bentley, B. M. Huddart

We present a first-principles study of the effect of 3$d$ transition metal intercalation on the magnetic properties of the 2H-NbS$_2$ system, using spin-resolved density functional theory calculations to investigate the electronic structure of $N_{1/3}$NbS$_2$ ($N$ = Ti, V, Cr, Mn, Fe, Co, Ni). We are able to accurately determine the magnetic moments and cry

Nick Tsipinakis, Panagiotis Tigkas, Panos Parpas

Newton's method may exhibit slower convergence than vanilla Gradient Descent in its initial phase on strongly convex problems. Classical Newton-type multilevel methods mitigate this but, like Gradient Descent, achieve only linear convergence near the minimizer. We introduce an adaptive multilevel Newton-type method with a principled automatic switch to full

Brit Youngmann, Michael Cafarella, Babak Salimi, Anna Zeng

Causal inference is fundamental to empirical scientific discoveries in natural and social sciences; however, in the process of conducting causal inference, data management problems can lead to false discoveries. Two such problems are (i) not having all attributes required for analysis, and (ii) misidentifying which attributes are to be included in the analys

Dan Li, Chunmei Wang, Junping Wang, Xiu Ye

This article proposes and analyzes the generalized weak Galerkin ({\rm g}WG) finite element method for the second order elliptic problem. A generalized discrete weak gradient operator is introduced in the weak Galerkin framework so that the {\rm g}WG methods would not only allow arbitrary combinations of piecewise polynomials defined in the interior and on t

T. J. Meijer, T. Holicki, S. J. A. M. van den Eijnden, C. W. Scherer

The projection lemma (often also referred to as the elimination lemma) is one of the most powerful and useful tools in the context of linear matrix inequalities for system analysis and control. In its traditional formulation, the projection lemma only applies to strict inequalities, however, in many applications we naturally encounter non-strict inequalities

Kevin J. Parker

In the approaches to elastography, two mathematical operations have been frequently applied to improve the final estimate of shear wave speed and shear modulus of tissues. The vector curl operator can separate out the transverse component of a complicated displacement field, and directional filters can separate distinct orientations of wave propagation. Howe

Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann

We present an iterative framework to improve the amortized approximations of posterior distributions in the context of Bayesian inverse problems, which is inspired by loop-unrolled gradient descent methods and is theoretically grounded in maximally informative summary statistics. Amortized variational inference is restricted by the expressive power of the ch

Yunzhi Yao, Peng Wang, Shengyu Mao, Chuanqi Tan

Previous studies have revealed that vanilla pre-trained language models (PLMs) lack the capacity to handle knowledge-intensive NLP tasks alone; thus, several works have attempted to integrate external knowledge into PLMs. However, despite the promising outcome, we empirically observe that PLMs may have already encoded rich knowledge in their pre-trained para

Thiago Carvalho Corso

In this article, we analyze the Dyson equation for the density-density response function (DDRF) that plays a central role in linear response time-dependent density functional theory (LR-TDDFT). First, we present a functional analytic setting that allows for a unified treatment of the Dyson equation with general adiabatic approximations for discrete (finite a

Ciro Ciliberto, Claudio Fontanari

In this paper, inspired by work of Fano, Morin and Campana--Flenner, we give a full projective classification of (however singular) varieties of dimension 3 whose general hyperplane sections have negative Kodaira dimension, and we partly extend such a classification to varieties of dimension $n\geq 4$ whose general surface sections have negative Kodaira dime

Wentao Ye, Mingfeng Ou, Tianyi Li, Yipeng chen

The recent popularity of large language models (LLMs) has brought a significant impact to boundless fields, particularly through their open-ended ecosystem such as the APIs, open-sourced models, and plugins. However, with their widespread deployment, there is a general lack of research that thoroughly discusses and analyzes the potential risks concealed. In

Michele Crescenzi

We study distributed knowledge, which is what privately informed agents come to know by communicating freely with one another and sharing everything they know. Knowledge is not necessarily partitional: agents may be boundedly rational and differ in the ability to form higher-order knowledge. We model the inference making process that leads to distributed kno

Ankit Shukla, Siyuan Qian, Shaloo Rakheja

We numerically investigate and develop analytic models for both the DC and pulsed spin-orbit-torque (SOT)-driven response of order parameter in single-domain Mn$_3$Sn, which is a metallic antiferromagnet with an anti-chiral 120$^\circ$ spin structure. We show that DC currents above a critical threshold can excite oscillatory dynamics of the order parameter i

Pablo Barceló, Diego Figueira, Rémi Morvan

We study the separability problem for automatic relations (i.e., relations on finite words definable by synchronous automata) in terms of recognizable relations (i.e., finite unions of products of regular languages). This problem takes as input two automatic relations $R$ and $R'$, and asks if there exists a recognizable relation $S$ that contains $R$ and do

Shilin Yang

The aim of this paper is to introduce the concept of $q$-Coxeter transformation and $q$-Coxeter matrix for a connected acyclic bound quiver $(Q, I)$ with a homogeneous relations $I$, then to establish the relationship between $q$-Coxeter matrix and $q$-Cartan matrix of $(Q, I)$.

Sebastian Schuster

Physicality has the bad habit of sneaking up on unsuspecting physicists. Unfortunately, it comes in multitudinous incarnations, which will not always make sense in a given situation. Breaching a warp drive metric with physical arguments is all good, but often what counts as physicality here is but a mere mask for something else. In times of analogue space-ti

Olaitan Akintunde, Trichina Tucker, Valerie J. Carabetta

The genetic information that dictates the structure and function of all life forms is encoded in the DNA. In 1953, Watson and Crick first presented the double helical structure of a DNA molecule. Their findings unearthed the desire to elucidate the exact composition and sequence of DNA molecules. Discoveries and the subsequent development and optimization of

Lukas Kesper, Sebastian Trimpe, Dominik Baumann

Event-triggered communication and control provide high control performance in networked control systems without overloading the communication network. However, most approaches require precise mathematical models of the system dynamics, which may not always be available. Model-free learning of communication and control policies provides an alternative. Nevert

Peng Hu

Recently advanced non-geostationary (NGSO) satellite networks represented by large constellations and advanced payloads provide great promises for enabling high-quality Internet connectivity to any place on Earth. However, the traditional approach to satellite operations cannot address the new challenges in the NGSO satellite networks imposed by the signific

Qijun Song, Siyun Zhou, Liwei Xu

Few-shot learning for image classification comes up as a hot topic in computer vision, which aims at fast learning from a limited number of labeled images and generalize over the new tasks. In this paper, motivated by the idea of Fisher Score, we propose a Discriminative Local Descriptors Attention (DLDA) model that adaptively selects the representative loca

Maria Gerasimova, Konstantin Shchepin

We study stability of amalgamated free products and HNN extensions of stable groups over finite groups. We focus on operator norm stability, Hilbert-Schmidt stability and stability in permutations. We provide many new examples of stable (or flexibly stable) non-amenable groups.

Hiuyi Cheng, Peirong Zhang, Sihang Wu, Jiaxin Zhang

Document layout analysis is a crucial prerequisite for document understanding, including document retrieval and conversion. Most public datasets currently contain only PDF documents and lack realistic documents. Models trained on these datasets may not generalize well to real-world scenarios. Therefore, this paper introduces a large and diverse document layo

Massimo Blasone, Petr Jizba, Gaetano Lambiase, Luciano Petruzziello

We investigate the non-relativistic limit of the Klein--Gordon equation for mixed scalar particles and show that, in this regime, one unavoidably arrives at redefining the particle's inertial mass. This happens because, in contrast to the case when mixing is absent, the antiparticle sector contribution cannot be neglected for particles with definite flavor.

Victoria A. Vasileva, Daria A. Mazur, Yury A. Budkov

In this paper, we present a continuation of our research on modeling electrolyte solutions within charged slit pores. We make use of the model developed by Blossey et al., which takes into account the structural interactions between ions through a bilinear form over the gradients of local ionic concentrations in the grand thermodynamic potential, as well as

Minho Cho, Jinha Kim

A stacked $d$-sphere $S$ is the boundary complex of a stacked $(d+1)$-ball, which is obtained by taking cone over a free $d$-face repeatedly from a $(d+1)$-simplex. A stacked sphere $S$ is called linear if every cone is taken over a face added in the previous step. In this paper, we study the transversal number of facets of stacked $d$-spheres, denoted by $\

Bing Duan, Ralf Schiffler

Let $\mathscr{C}$ be the category of finite-dimensional modules over a simply-laced quantum affine algebra $U_q(\widehat{\mathfrak{g}})$. For any height function $\xi$ and $\ell\in \mathbb{Z}_{\geq 1}$, we introduce certain subcategories $\mathscr{C}^{\leq \xi}_\ell$ of $\mathscr{C}$, and prove that the quantum Grothendieck ring $K_t(\mathscr{C}^{\leq \xi}_\

Chengguang Gan, Tatsunori Mori

Prompt engineering relevance research has seen a notable surge in recent years, primarily driven by advancements in pre-trained language models and large language models. However, a critical issue has been identified within this domain: the inadequate of sensitivity and robustness of these models towards Prompt Templates, particularly in lesser-studied langu

Louis Soares

We consider sequences $(X_n)_{n\in \mathbb{N}}$ of coverings of convex cocompact hyperbolic surfaces $X$ with Euler characterictic $\chi(X_n)$ tending to $-\infty$ as $n\to \infty.$ We prove that for $n$ large enough, each $X_n$ has an abundance of "low-lying" resonances, provided the length of the shortest closed geodesic on $X_n$ grows sufficiently fast. W

Dejin Ren, Wanli Lu, Jidong Lv, Lijun Zhang

In this paper we investigate the optimal controller synthesis problem, so that the system under the controller can reach a specified target set while satisfying given constraints. Existing model predictive control (MPC) methods learn from a set of discrete states visited by previous (sub-)optimized trajectories and thus result in computationally expensive mi

Lars Hillebrand, Maren Pielka, David Leonhard, Tobias Deußer

We present sustainAI, an intelligent, context-aware recommender system that assists auditors and financial investors as well as the general public to efficiently analyze companies' sustainability reports. The tool leverages an end-to-end trainable architecture that couples a BERT-based encoding module with a multi-label classification head to match relevant

Ali Baktash, Dieter Horns

The detailed simulation of extended air showers (EAS) and their emission of Cherenkov and fluorescence light requires increasing computation time and storage volume with increasing energy of the primary particle. Given these limitations, it is currently challenging to optimize configurations of imaging air Cherenkov telescopes at photon energies beyond appro

Qingkai Fang, Yang Feng

The success of end-to-end speech-to-text translation (ST) is often achieved by utilizing source transcripts, e.g., by pre-training with automatic speech recognition (ASR) and machine translation (MT) tasks, or by introducing additional ASR and MT data. Unfortunately, transcripts are only sometimes available since numerous unwritten languages exist worldwide.

Jessie Mosso, Dunja Simicic, Bernard Lanz, Rolf Gruetter

A new sequence for single-voxel diffusion-weighted 1H MRS (DWS), named DW-SPECIAL, is proposed to improve the detection and subsequent estimation of the diffusion properties of strongly J-coupled metabolites. It combines the semi-adiabatic SPECIAL sequence with a stimulated echo (STE) diffusion block. Acquisitions with DW-SPECIAL and STE-LASER, the current g

Peter K Elgee, Joshua C Hill, Kermit-James E Leblanc, Gabriel D Ko

Rydberg electric field sensors exploit the large number of Rydberg resonances to provide sensitivity over a broad range of the electromagnetic spectrum. However, due to the difficulty of accessing resonant Rydberg states at ultra-high frequency (UHF) and below, ubiquitous bands in the world's current wireless communications infrastructure, they currently fal

Qingkai Fang, Yang Feng

How to achieve better end-to-end speech translation (ST) by leveraging (text) machine translation (MT) data? Among various existing techniques, multi-task learning is one of the effective ways to share knowledge between ST and MT in which additional MT data can help to learn source-to-target mapping. However, due to the differences between speech and text, t

The STAR Collaboration

In relativistic heavy-ion collisions, a global spin polarization, $P_\mathrm{H}$, of $\Lambda$ and $\bar{\Lambda}$ hyperons along the direction of the system angular momentum was discovered and measured across a broad range of collision energies and demonstrated a trend of increasing $P_\mathrm{H}$ with decreasing $\sqrt{s_{\rm NN}}$. A splitting between $\L

Aun Zaidi, Noah A. Rubin, Maryna L. Meretska, Lisa Li

When light scatters off an object its polarization, in general, changes - a transformation described by the object's Mueller matrix. Mueller matrix imaging polarimetry is an important technique in science and technology to image the spatially varying polarization response of an object of interest, to reveal rich information otherwise invisible to traditional

Hongbin Ye, Honghao Gui, Xin Xu, Xi Chen

Conventional Knowledge Graph Construction (KGC) approaches typically follow the static information extraction paradigm with a closed set of pre-defined schema. As a result, such approaches fall short when applied to dynamic scenarios or domains, whereas a new type of knowledge emerges. This necessitates a system that can handle evolving schema automatically

Yujia Qin, Cheng Qian, Xu Han, Yankai Lin

Continual pre-training is the paradigm where pre-trained language models (PLMs) continually acquire fresh knowledge from growing data and gradually get upgraded. Before an upgraded PLM is released, we may have tuned the original PLM for various tasks and stored the adapted weights. However, when tuning the upgraded PLM, these outdated adapted weights will ty

Yuval Scher, Shlomi Reuveni, Denis S. Grebenkov

Adsorption to a surface, reversible-binding, and trapping are all prevalent scenarios where particles exhibit "stickiness". Escape and first-passage times are known to be drastically affected, but detailed understanding of this phenomenon remains illusive. To tackle this problem, we develop an analytical approach to the escape of a diffusing particle from a

O. Băzăvan, S. Saner, E. Tirrito, G. Araneda

We present a detailed scheme for the analog quantum simulation of $\mathbb{Z}_2$ gauge theories in crystals of trapped ions, which exploits a more efficient hybrid encoding of the gauge and matter fields using the native internal and motional degrees of freedom. We introduce a versatile toolbox based on parametric excitations corresponding to different spin-

Cristian D. Gonzalez-Aviles

If k is an arbitrary field, we construct a category of k-1-motives in which every commutative algebraic k-group G has a dual object $G^{\vee}$. When k is a local field of arbitrary characteristic, we establish Pontryagin duality theorems that relate the fppf cohomology groups of G to the hypercohomology groups of the k-1-motive $G^{\vee}$. We also obtain a d

Xiang Chen, Jintian Zhang, Xiaohan Wang, Ningyu Zhang

Current Multimodal Knowledge Graph Construction (MKGC) models struggle with the real-world dynamism of continuously emerging entities and relations, often succumbing to catastrophic forgetting-loss of previously acquired knowledge. This study introduces benchmarks aimed at fostering the development of the continual MKGC domain. We further introduce MSPT fram

William Bernardoni

We introduce a generalization of the universal valuation semiring defined by Jeffrey and Noah Giansiracusa. We then explicitly characterize the additive structure of this semiring and show that, when applied to $\mathbb Q$, this characterization gives the Non-Archimedean case of Ostrowski's theorem. We conclude with examples of non-commutative valuations and

Mahdi Chehimi, Shahrooz Pouryousef, Nitish K. Panigrahy, Don Towsley

Quantum networks (QNs) are a promising platform for secure communications, enhanced sensing, and efficient distributed quantum computing. However, due to the fragile nature of quantum states, these networks face significant challenges in terms of scalability. In this paper, the scaling limits of quantum repeater networks (QRNs) are analyzed. The goal of this

Katsuya Yonehara, Sudeshna Ganguly, Don Athula Wickremasinghe, Pavel Snopok

Neutrinos at the Main Injector (NuMI) is a project at Fermilab that provides an intense beam of neutrinos used by a number of experiments. NuMI creates a beam of pions that decay into neutrinos, muons, and other particles. Muons are registered by the muon monitors. Magnetic horns are the key elements of the NuMI beam line. This paper uses the muon beam profi

Ryan Webster

Recently, Carlini et al. demonstrated the widely used model Stable Diffusion can regurgitate real training samples, which is troublesome from a copyright perspective. In this work, we provide an efficient extraction attack on par with the recent attack, with several order of magnitudes less network evaluations. In the process, we expose a new phenomena, whic

Alessandro Lupo, Enrico Picco, Marina Zajnulina, Serge Massar

Reservoir computers (RC) are randomized recurrent neural networks well adapted to process time series, performing tasks such as nonlinear distortion compensation or prediction of chaotic dynamics. Deep reservoir computers (deep-RC), in which the output of one reservoir is used as the input for another one, can lead to improved performance because, as in othe

Thomas Führer, Norbert Heuer

We present a mixed finite element method with triangular and parallelogram meshes for the Kirchhoff-Love plate bending model. Critical ingredient is the construction of low-dimensional local spaces and appropriate degrees of freedom that provide conformity in terms of a sufficiently large tensor space and that allow for any kind of physically relevant Dirich

Jukka P. Pekola, Bayan Karimi, Marco Cattaneo, Sabrina Maniscalco

We discuss the long-time relaxation of a qubit linearly coupled to a finite bath of $N$ spins (two-level systems, TLSs), with the interaction Hamiltonian in rotating wave approximation. We focus on the regime $N\gg 1$, assuming that the qubit-bath coupling is weak, that the range of spin frequencies is sufficiently broad, and that all the spins are initializ

Yuntao Wang, Zhou Su, Tom H. Luan, Jiliang Li

Due to the limited battery and computing resource, offloading unmanned aerial vehicles (UAVs)' computation tasks to ground infrastructure, e.g., vehicles, is a fundamental framework. Under such an open and untrusted environment, vehicles are reluctant to share their computing resource unless provisioning strong incentives, privacy protection, and fairness gu

Hiroyuki Tajima, Hiroshi Funaki, Yuta Sekino, Nobutoshi Yasutake

We explore the theoretical possibility of $^3P_0$ neutron superfluid in dilute spin-polarized neutron matter, which may be relevant to the crust region of a magnetized neutron star. In such a dilute regime where the neutron Fermi energy is less than 1 MeV, the $^1S_0$ neutron superfluid can be suppressed by a strong magnetic field of the compact star. In the

Yukako Kezuka, Yong-Xiong Li

We prove non-vanishing theorems for the central values of $L$-series of quadratic twists of the Gross elliptic curve with complex multiplication by the imaginary quadratic field $\mathbb{Q}(\sqrt{-q})$, where $q$ is any prime congruent to $7$ modulo $8$. This completes the non-vanishing theorems proven by Coates and the second author in which the primes $q$

Florian Hörsch

For a given digraph $D$ and distinct $u,v \in V(D)$, we denote by $\lambda_D(u,v)$ the local arc-connectivity from $u$ to $v$. Further, we define the total arc-connectivity $tac(D)$ of $D$ to be $\sum_{\{u,v\}\subseteq V(D)}\lambda_D(u,v)+\lambda_D(v,u)$. We show that, given a graph $G$ and an integer $k$, it is NP-complete to decide whether $G$ has an orien

Giovanni Seraghiti, Atharva Awari, Arnaud Vandaele, Margherita Porcelli

In this paper, we study the following nonlinear matrix decomposition (NMD) problem: given a sparse nonnegative matrix $X$, find a low-rank matrix $\Theta$ such that $X \approx f(\Theta)$, where $f$ is an element-wise nonlinear function. We focus on the case where $f(\cdot) = \max(0, \cdot)$, the rectified unit (ReLU) non-linear activation. We refer to the co

Guillaume O. Berger, Sriram Sankaranarayanan

We investigate the problem of fitting piecewise affine functions (PWA) to data. Our algorithm divides the input domain into finitely many polyhedral regions whose shapes are specified using a user-defined template such that the data points in each region are fit by an affine function within a desired error bound. We first prove that this problem is NP-hard.

Linhui Xiao, Xiaoshan Yang, Fang Peng, Ming Yan

Visual Grounding (VG) is a crucial topic in the field of vision and language, which involves locating a specific region described by expressions within an image. To reduce the reliance on manually labeled data, unsupervised visual grounding have been developed to locate regions using pseudo-labels. However, the performance of existing unsupervised methods is

Susanna Bertelli, Fabio Bossi, Riccardo De Sangro, Claudio Di Giulio

The Positron Annihilation to Dark Matter Experiment (PADME) was designed and constructed to search for dark photons ($A'$) in the process $e^+e^-\rightarrow\gamma A'$, using the positron beam at the Beam Test Facility (BTF) at the National Laboratories of Frascati (LNF). Since the observation of an anomalous spectra in internal pair creation decays of nuclei

I. T. Drummond

We study two (massless free field) models, a photon/photino model with a vector gauge field and a Majorana spinor field, and a Wess-Zumino model. They each exhibit Lorentz symmetry violation but retain, in an appropriate way, the supersymmetry correspondance between the particles of the two fields. In relation to the photon field the Lorentz symmetry violati

Stefan Hetzl, Jannik Vierling

We investigate quantifier-free induction for Lisp-like lists constructed inductively from the empty list $\mathit{nil}$ and the operation $\mathit{cons}$, that adds an element to the front of a list. First we show that, for $m \geq 1$, quantifier-free $m$-step induction does not simulate quantifier-free $(m + 1)$-step induction. Secondly, we show that for al