March 2024 arXiv papers — page 129

Robert Lakatos, Peter Pollner, Andras Hajdu, Tamas Joo

The development of generative large language models (G-LLM) opened up new opportunities for the development of new types of knowledge-based systems similar to ChatGPT, Bing, or Gemini. Fine-tuning (FN) and Retrieval-Augmented Generation (RAG) are the techniques that can be used to implement domain adaptation for the development of G-LLM-based knowledge syste

Morteza Bodaghi, Majid Hosseini, Raju Gottumukkala

Multimodal deep learning methods capture synergistic features from multiple modalities and have the potential to improve accuracy for stress detection compared to unimodal methods. However, this accuracy gain typically comes from high computational cost due to the high-dimensional feature spaces, especially for intermediate fusion. Dimensionality reduction i

Xuan Fan, Ya Xiao, Yongjian Gu

In the past decades, researches on parity-time (PT) and anti-parity-time(APT) systems have garnered unprecedented attention, showcasing their various intriguing characteristics and promising potentiality in extending canonical Hermitian quantum mechanics. However, despite significant endeavors devoted to this new field of physics, non-Hermitian dynamics of c

Ruifeng Chen, Jing Mao

In this paper, by mainly using the rearrangement technique and suitably constructing trial functions, under the constraint of fixed weighted volume, we can successfully obtain several isoperimetric inequalities for the first and the second Dirichlet eigenvalues, the first nonzero Neumann eigenvalue of the Witten-Laplacian on bounded domains in space forms. T

Philipp del Hougne

We estimate the scattering matrix of an arbitrarily complex linear, passive, time-invariant system with $N$ monomodal lumped ports by inputting and outputting waves only via a fixed set of $N_\mathrm{A}<N$ ports while terminating the remaining $N_\mathrm{S}=N-N_\mathrm{A}$ "not-directly-accessible" (NDA) ports with tunable individual loads. First, we present

Xuan Fan, Ya Xiao, Yongjian Gu

Contextuality is well known as a vital resource for locating the boundary between classical and quantum theories, as well as identifying tasks showing quantum advantage. In a surge of recent works [Schmid and Spekkens, Phys.Rev.X 8, 011015 (2018); Mukherjee, Naonit and Pan, Phys.Rev.A 106, 012216 (2022); Flatt, Lee, Carceller, Brask and Bae, PRX QUANTUM 3, 0

David Gao, Srivatsav Kunnawalkam Elayavalli, Gregory Patchell, Hui Tan

We study conjugacy orbits of certain types of subalgebras in tracial von Neumann algebras. For any separable II$_1$ factor $N_0$ we construct a highly indecomposable non Gamma II$_1$ factor $N$ such that $N_0 \subset N$ and moreover every von Neumann subalgebra of $N$ with Haagerup's property admits a unique embedding up to unitary conjugation. Such a factor

Maciej Beręsewicz, Marcin Szymkowiak, Piotr Chlebicki

The use of non-probability data sources for statistical purposes and for official statistics has become increasingly popular in recent years. However, statistical inference based on non-probability samples is made more difficult by nature of their biasedness and lack of representativity. In this paper we propose quantile balancing inverse probability weighti

Rocco Chirivì, Xin Fang, Peter Littelmann

The goal of the paper is twofold: on one side it provides an order structure on the set of all maximal chains in the Bruhat poset of Schubert varieties in a Grassmann variety; on the other hand, using this order structure, it works out explicit formulae for the valuation and the Newton-Okounkov body associated to each maximal chain appearing in the framework

Ruifeng Chen, Jing Mao

An isoperimetric inequality for lower order nonzero Neumann eigenvalues of the Witten-Laplacian on bounded domains in a Euclidean space or a hyperbolic space has been proven in this paper. About this conclusion, we would like to point out two things: It strengthens the well-known Szeg\H{o}-Weinberger inequality for nonzero Neumann eigenvalues of the classica

Xudong Huai, Emmanuel Acheampong, Erich Delles, Michał J. Winiarski

Noncentrosymmetric triangular magnets offer a unique platform for realizing strong quantum fluctuations. However, designing these quantum materials remains an open challenge attributable to a knowledge gap in the tunability of competing exchange interactions at the atomic level. Here, we create a new noncentrosymmetric triangular S = 3/2 magnet CaMnTeO$_6$ b

Mehrzad Mohammadi, Reza Javan, Mohammad Beheshti-Atashgah, Mohammad Reza Aref

Internet of Things (IoT) devices are capable of allowing for far-reaching access to and evaluation of patient data to monitor health and diagnose from a distance. An electronic healthcare system that checks patient data, prepares medicines and provides financial assistance is necessary. Providing safe data transmission, monitoring, decentralization, preservi

Tawny Sit, David H. Weinberg, Adam Wheeler, Christian R. Hayes

Stellar abundance measurements are subject to systematic errors that induce extra scatter and artificial correlations in elemental abundance patterns. We derive empirical calibration offsets to remove systematic trends with surface gravity $\log(g)$ in 17 elemental abundances of 288,789 evolved stars from the SDSS APOGEE survey. We fit these corrected abunda

Gabriel Karl Gegenhuber, Wilfried Mayer, Edgar Weippl

Zero-rating, the practice of not billing data traffic that belongs to certain applications, has become popular within the mobile ecosystem around the globe. There is an ongoing debate whether mobile operators should be allowed to differentiate traffic or whether net neutrality regulations should prevent this. Despite the importance of this issue, we know lit

Raman Goyal, Dhrubajit Chowdhury, Shantanu Rane

This paper introduces a novel approach to concurrently design dynamic controllers and correlated differential privacy noise in dynamic control systems. An increase in privacy noise increases the system's privacy but adversely affects the system's performance. Our approach optimizes the noise distribution while shaping closed-loop system dynamics such that th

Sławomir Rams, Matthias Schütt

We prove that there are at most $(24-r_0)$ low-degree rational curves on high-degree models of K3 surfaces with at most Du Val singularities, where $r_0$ is the number of exceptional divisors on the minimal resolution. We also provide several existence results in the above setting (i.e. for rational curves on quasi-polarized K3 surfaces), which imply that fo

Richard Angersbach, Sebastian Kuckuck, Harald Köstler

This paper presents a novel method designed to generate multigrid solvers optimized for octree-based software frameworks. Our approach focuses on accurately capturing local features within a domain while leveraging the efficiency inherent in multigrid techniques. We outline the essential steps involved in generating specialized kernels for local refinement a

Ziheng Wang, Alex Aiken

Modern distributed pipelined query engines either do not support intra-query fault tolerance or employ high-overhead approaches such as persisting intermediate outputs or checkpointing state. In this work, we present write-ahead lineage, a novel fault recovery technique that combines Spark's lineage-based replay and write-ahead logging. Unlike Spark, where t

Sunwoong Choi, Zaid Abbas Al-Sabbag, Sriram Narasimhan, Chul Min Yeum

Routine inspections for critical infrastructures such as bridges are required in most jurisdictions worldwide. Such routine inspections are largely visual in nature, which are qualitative, subjective, and not repeatable. Although robotic infrastructure inspections address such limitations, they cannot replace the superior ability of experts to make decisions

Saleh Afroogh, Ali Akbari, Evan Malone, Mohammadali Kargar

The increasing use of artificial intelligence (AI) systems in our daily life through various applications, services, and products explains the significance of trust/distrust in AI from a user perspective. AI-driven systems (as opposed to other technologies) have ubiquitously diffused in our life not only as some beneficial tools to be used by human agents bu

Benjamin H. Feintzeig, Jer Steeger

Hilbert bimodules are morphisms between C*-algebraic models of quantum systems, while symplectic dual pairs are morphisms between Poisson geometric models of classical systems. Both of these morphisms preserve representation-theoretic structures of the relevant types of models. Previously, it has been shown that one can functorially associate certain symplec

Benjamin D. Killeen, Liam J. Wang, Blanca Inigo, Han Zhang

Language promptable X-ray image segmentation would enable greater flexibility for human-in-the-loop workflows in diagnostic and interventional precision medicine. Prior efforts have contributed task-specific models capable of solving problems within a narrow scope, but expanding to broader use requires additional data, annotations, and training time. Recentl

Saurabh Agarwal, Bilge Acun, Basil Hosmer, Mostafa Elhoushi

Large Language Models (LLMs) with hundreds of billions of parameters have transformed the field of machine learning. However, serving these models at inference time is both compute and memory intensive, where a single request can require multiple GPUs and tens of Gigabytes of memory. Multi-Head Attention is one of the key components of LLMs, which can accoun

Ademola Isaac Adebimpe, Sajjad Foroughi, Branko Bijeljic, Martin J. Blunt

Conventional measurements of two-phase flow in porous media often use completely immiscible fluids, or are performed over time-scales of days to weeks. If applied to the study of gas storage and recovery, these measurements do not properly account for Ostwald ripening, significantly over-estimating the amount of trapping and hysteresis. When there is transpo

Hyunsung Cho, Yukang Yan, Kashyap Todi, Mark Parent

Extended Reality (XR) interfaces offer engaging user experiences, but their effective design requires a nuanced understanding of user behavior and preferences. This knowledge is challenging to obtain without the widespread adoption of XR devices. We introduce MineXR, a design mining workflow and data analysis platform for collecting and analyzing personalize

Luke Panayi, Rohan Gandhi, Jim Whittaker, Vassilios Chouliaras

This paper explores the potential of communicating information gained by static analysis from compilers to Out-of-Order (OoO) machines, focusing on the memory dependence predictor (MDP). The MDP enables loads to issue without all in-flight store addresses being known, with minimal memory order violations. We use LLVM to find loads with no dependencies and la

Mohamed Elrefaie, Angela Dai, Faez Ahmed

This study introduces DrivAerNet, a large-scale high-fidelity CFD dataset of 3D industry-standard car shapes, and RegDGCNN, a dynamic graph convolutional neural network model, both aimed at aerodynamic car design through machine learning. DrivAerNet, with its 4000 detailed 3D car meshes using 0.5 million surface mesh faces and comprehensive aerodynamic perfo

Tzu-Yuan Huang, Sihua Zhang, Xiaobing Dai, Alexandre Capone

In many control system applications, state constraint satisfaction needs to be guaranteed within a prescribed time. While this issue has been partially addressed for systems with known dynamics, it remains largely unaddressed for systems with unknown dynamics. In this paper, we propose a Gaussian process-based time-varying control method that leverages backs

Anmol Singhal, Chirag Jain, Preethu Rose Anish, Arkajyoti Chakraborty

Enterprises frequently enter into commercial contracts that can serve as vital sources of project-specific requirements. Contractual clauses are obligatory, and the requirements derived from contracts can detail the downstream implementation activities that non-legal stakeholders, including requirement analysts, engineers, and delivery personnel, need to con

Sachin Shivakumar, Matthew Peet

In this paper, we present solvable, convex formulations of $H_2$-optimal state estimation and state-feedback control problems for a general class of linear Partial Differential Equations (PDEs) with one spatial dimension. These convex formulations are derived by using an analysis and control framework called the `Partial Integral Equation' (PIE) framework, w

Cristian Cioflan, Lukas Cavigelli, Manuele Rusci, Miguel de Prado

Keyword spotting accuracy degrades when neural networks are exposed to noisy environments. On-site adaptation to previously unseen noise is crucial to recovering accuracy loss, and on-device learning is required to ensure that the adaptation process happens entirely on the edge device. In this work, we propose a fully on-device domain adaptation system achie

Ariel D. Procaccia, Benjamin Schiffer, Shirley Zhang

Rent division is the well-studied problem of fairly assigning rooms and dividing rent among a set of roommates within a single apartment. A shortcoming of existing solutions is that renters are assumed to be considering apartments in isolation, whereas in reality, renters can choose among multiple apartments. In this paper, we generalize the rent division pr

Raphael A Abrahao, Henri P N Morin, Jordan T R Page, Akbar Safari

Light, being massless, casts no shadow; under ordinary circumstances, photons pass right through each other unimpeded. Here, we demonstrate a laser beam acting like an object - the beam casts a shadow upon a surface when the beam is illuminated by another light source. We observe a regular shadow in the sense it can be seen by the naked eye, it follows the c

Yuexi Chen, Vlad I. Morariu, Anh Truong, Zhicheng Liu

Mixed-media tutorials, which integrate videos, images, text, and diagrams to teach procedural skills, offer more browsable alternatives than timeline-based videos. However, manually creating such tutorials is tedious, and existing automated solutions are often restricted to a particular domain. While AI models hold promise, it is unclear how to effectively h

Kaitlyn M. Chen, Trevor Z. Dorn-Wallenstein

Yellow supergiants (YSGs) are rare and poorly understood, and studying them is critical to constraining massive star evolution. We obtained flux-calibrated Magellan Inamori Kyocera Echelle (MIKE) high-resolution spectra of 40 YSGs in the Large Magellanic Cloud (LMC); this sample likely contains post-red supergiants (RSGs). Fitting these data with ATLAS9 mode

K. Mursula, A. A. Pevtsov, T. Asikainen, I. Tähtinen

The Sun experienced a period of unprecedented activity during the 20th century, now called the Modern Maximum (MM). The decay of the MM after cycle 19 has changed the Sun, the heliosphere, and the planetary environments in many ways. However, studies disagree on whether this decay has proceeded synchronously in different solar parameters or not. One key issu

Charlie Campanella, Rob van der Goot

Large language models (LLMs) have emerged as a useful technology for job matching, for both candidates and employers. Job matching is often based on a particular geographic location, such as a city or region. However, LLMs have known biases, commonly derived from their training data. In this work, we aim to quantify the metropolitan size bias encoded within

Damiano Aliverti-Piuri, Kaustav Chatterjee, Lexin Ding, Ke Liao

It is the ultimate goal of this work to foster synergy between quantum chemistry and the flourishing field of quantum information theory. For this, we first translate quantum information concepts such as entanglement and correlation into the context of quantum chemical systems. In particular, we establish two conceptually distinct perspectives on `electron c

Tiash Rana Mukherjee, Oshin Tyagi, Jingkun Wang, John Kang

Passive shoulder exoskeletons have been widely introduced in the industry to aid upper extremity movements during repetitive overhead work. As an ergonomic intervention, it is important to understand how users adapt to these devices over time and if these induce external stress while working. The study evaluated the use of an exoskeleton over a period of 3 d

Shuai Liu, Shantanu Agarwal, Jonathan May

Authorship style transfer aims to rewrite a given text into a specified target while preserving the original meaning in the source. Existing approaches rely on the availability of a large number of target style exemplars for model training. However, these overlook cases where a limited number of target style examples are available. The development of paramet

Amel Imene Hadj Bouzid, Baudouin Denis de Senneville, Fabien Baldacci, Pascal Desbarats

This research embarked on a comparative exploration of the holistic segmentation capabilities of Convolutional Neural Networks (CNNs) in both 2D and 3D formats, focusing on cystic fibrosis (CF) lesions. The study utilized data from two CF reference centers, covering five major CF structural changes. Initially, it compared the 2D and 3D models, highlighting t

Ying Liu, Liucheng Guo, Valeri A. Makarovc, Alexander Gorbana

Automated hand gesture recognition has long been a focal point in the AI community. Traditionally, research in this field has predominantly focused on scenarios with access to a continuous flow of hand's images. This focus has been driven by the widespread use of cameras and the abundant availability of image data. However, there is an increasing demand for

Kostas Karpouzis

Gamification, the integration of game mechanics in non-game settings, has become increasingly prevalent in various digital platforms; however, its ethical and societal impacts are often overlooked. This paper delves into how Platonic and Aristotelian philosophies can provide a critical framework for understanding and evaluating the ethical dimensions of gami

Yushan Huang, Ranya Aloufi, Xavier Cadet, Yuchen Zhao

Microcontroller Units (MCUs) are ideal platforms for edge applications due to their low cost and energy consumption, and are widely used in various applications, including personalized machine learning tasks, where customized models can enhance the task adaptation. However, existing approaches for local on-device personalization mostly support simple ML arch

Krzysztof Jan Nowak

The main purpose is to establish two theorems about closed 0-definable subsets $A$ of an affine space $K^{n}$ over a Hensel minimal field $K$. The first, being a non-Archimedean counterpart of one from o-minimal geometry, states that every such subset $A$ is the zero locus of a continuous 0-definable function on $K^{n}$. The second is a definable, non-Archim

Egor Klimov, Muhammad Umair Ahmed, Nikolai Sviridov, Pouria Derakhshanfar

Bus factor (BF) is a metric that tracks knowledge distribution in a project. It is the minimal number of engineers that have to leave for a project to stall. Despite the fact that there are several algorithms for calculating the bus factor, only a few tools allow easy calculation of bus factor and convenient analysis of results for projects hosted on Git-bas

M. Simonte, H. Andernach, M. Brueggen, G. K. Miley

In this study, we compare the radio, optical and environmental properties of GRGs with those of a control sample of smaller RGs we found in the three LOw-Frequency ARray (LOFAR) deep fields, namely the Bootes, ELAIS-N1, Lockman Hole, for a total area of about 95 deg^2. We inspected the LOFAR deep fields and created a catalogue of 1609 extended radio galaxies

Ajay Kulkarni, Yingjie Wang, Munisamy Gopinath, Dan Sobien

The increasing utilization of emerging technologies in the Food & Agriculture (FA) sector has heightened the need for security to minimize cyber risks. Considering this aspect, this manuscript reviews disclosed and documented cybersecurity incidents in the FA sector. For this purpose, thirty cybersecurity incidents were identified, which took place between J

Tharindu Kumarage, Amrita Bhattacharjee, Joshua Garland

Large language models (LLMs) excel in many diverse applications beyond language generation, e.g., translation, summarization, and sentiment analysis. One intriguing application is in text classification. This becomes pertinent in the realm of identifying hateful or toxic speech -- a domain fraught with challenges and ethical dilemmas. In our study, we have t

Marie Labeye, Camille Lévêque, François Risoud, Alfred Maquet

We investigate ultrafast vibronic dynamics triggered by intense femtosecond infrared pulses in small molecules. Our study is based on numerical simulations performed with 2D model molecules, and analyzed in the perspective of the renown Lochfrass and Bond-Softening models. We give a new interpretation of the observed nuclear wave packet dynamics, with a focu

A. Ayda Gercek, Zeki C. Seskir

This article explores the potential divides from emerging quantum technologies (QT) on society, covering impacts on science, technology, geopolitics, and societal structures. We aim to challenge the concept of a single "quantum divide" by offering a comprehensive view. We propose four divides: in science, technologies, between countries, and within societies

Pranav Singh Chib, Pravendra Singh

Accurate pedestrian trajectory prediction is crucial for various applications, and it requires a deep understanding of pedestrian motion patterns in dynamic environments. However, existing pedestrian trajectory prediction methods still need more exploration to fully leverage these motion patterns. This paper investigates the possibilities of using Large Lang

Eduardo Perez-Richet, Vasiliki Skreta

We propose a mechanism design framework that incorporates both soft information, which can be freely manipulated, and semi-hard information, which entails a cost for falsification. The framework captures various contexts such as school choice, public housing, organ transplant and manipulations of classification algorithms. We first provide a canonical class

Elena Caviglia

We generalize the concept of stack one dimension higher, introducing a notion of 2-stack suitable for a trihomomorphism from a 2-category equipped with a bitopology into the tricategory of bicategories. Moreover, we give a characterization of 2-stacks in terms of explicit conditions, that are easier to use in practice. These explicit conditions are effective

S. Huber, S. H. Suyu

Strongly lensed Type Ia supernovae (LSNe Ia) are a promising probe to measure the Hubble constant ($H_0$) directly. To use LSNe Ia for cosmography, a time-delay measurement between the multiple images, a lens-mass model, and a mass reconstruction along the line of sight are required. In this work, we present the machine learning network LSTM-FCNN which is a

Didier Ndengeyintwali, Shiva Heidari, Cody Youmans, Pavan Hosur

We study the Yu-Shiba-Rusinov states in materials with bulk band inversion such as iron-based topological superconductors or doped topological insulators. We show that the structure of the YSR state spectrum depends on the doping level relative to the chemical potential at which the band-inversion occurs. Moreover, we demonstrate that the transition from fer

Braulio V. Sánchez Vinces, Robson L. F. Cordeiro, Christos Faloutsos

How could we have an outlier detector that works even with nondimensional data, and ranks together both singleton microclusters ('one-off' outliers) and nonsingleton microclusters by their anomaly scores? How to obtain scores that are principled in one scalable and 'hands-off' manner? Microclusters of outliers indicate coalition or repetition in fraud activi

Pranta Rahman Sarkar, Hossein Ebrahimi, Md Shahjahan Hossain, Ranajay Ghosh

We develop the fundamentals of nonlinear and anisotropic bending behavior of biomimetic scale plates using a combination of analytical modeling, finite element (FE) computations, and motivational experiments. The analytical architecture-property relationships are derived for both synclastic and anticlastic curvatures. The results show that, as the scales eng

Niladri Ghosh, Amiya Das, Debraj Nath

This paper explores the analytical approach for obtaining the multiple solutions of three-wave interacting system in (1+1) dimensions. We present a novel approach by expressing the wave solutions in terms of Jacobi elliptic functions and delve into specific cases involving hyperbolic functions. Additionally, the paper focuses on analysing the linear stabilit

Jiajie Li, Jinjun Xiong

Private Inference (PI) enables deep neural networks (DNNs) to work on private data without leaking sensitive information by exploiting cryptographic primitives such as multi-party computation (MPC) and homomorphic encryption (HE). However, the use of non-linear activations such as ReLU in DNNs can lead to impractically high PI latency in existing PI systems,

Bolton Bailey, Or Sattath

We present a strategy for a single quantum miner with relatively low hashing power, with the same ramifications as a 51% attack. Bitcoin nodes consider the chain with the highest cumulative proof-of-work to be the valid chain. A quantum miner can manipulate the block timestamps to multiply the difficulty by $c$. The fork-choice rule counts every block with i

Nikita Nikulsin, Wrick Sengupta, Rogerio Jorge, Amitava Bhattacharjee

A first-order model is derived for quasisymmetric stellarators where the vacuum field due to coils is dominant, but plasma-current-induced terms are not negligible and can contribute to magnetic differential equations, with $\beta$ of the order of the ratio of induced to vacuum fields. Under these assumptions, it is proven that the aspect ratio must be large

T. Cisneros-Pérez, A. Ramirez-Morales, J. Montaño-Domínguez, A. Gutiérrez-Rodríguez

We review the anomalous Chromomagnetic Dipole Moment (CMDM) of the top quark in a Two Higgs Doublet Model (2HDM). We include interactions with the involvement of the extended CKM matrix in this model, we obtain new bonds for the future experimental measurements and theoretical considerations.

Esra Adiyeke, Yuanfang Ren, Shmuel Fogel, Parisa Rashidi

Background: Acute kidney injury (AKI) is a clinical syndrome affecting almost one fifth of hospitalized patients, as well as more than half of the patients who are admitted to the intensive care unit (ICU). Stratifying AKI patients into groups based on severity and duration would facilitate more targeted efforts for treating AKI. Methods: In a retrospective,

Yuelong Li, Yafei Mao, Raja Bala, Sunil Hadap

We propose a single-shot approach to determining 6-DoF pose of an object with available 3D computer-aided design (CAD) model from a single RGB image. Our method, dubbed MRC-Net, comprises two stages. The first performs pose classification and renders the 3D object in the classified pose. The second stage performs regression to predict fine-grained residual p

Mehdi Miah, Guillaume-Alexandre Bilodeau, Nicolas Saunier

We propose a novel Transformer-based module to address the data association problem for multi-object tracking. From detections obtained by a pretrained detector, this module uses only coordinates from bounding boxes to estimate an affinity score between pairs of tracks extracted from two distinct temporal windows. This module, named TWiX, is trained on sets

Vladimir Zaigrajew, Hubert Baniecki, Lukasz Tulczyjew, Agata M. Wijata

Remote sensing (RS) applications in the space domain demand machine learning (ML) models that are reliable, robust, and quality-assured, making red teaming a vital approach for identifying and exposing potential flaws and biases. Since both fields advance independently, there is a notable gap in integrating red teaming strategies into RS. This paper introduc

Micheli Nayara de Oliveira Vicente, Gabriel Toshio Hirokawa Higa, João Vitor de Andrade Porto, Higor Henrique

Aedes aegypti is still one of the main concerns when it comes to disease vectors. Among the many ways to deal with it, there are important protocols that make use of egg numbers in ovitraps to calculate indices, such as the LIRAa and the Breteau Index, which can provide information on predictable outbursts and epidemics. Also, there are many research lines t

Shuhua Chang, Tiefeng Jiang, Yongcheng Qi

Consider two types of products of independent random matrices, including products of Ginibre matrices and inverse Ginibre matrices and products of truncated Haar unitary matrices and inverse truncated Haar matrices. Each product matrix has $m$ multiplicands of $n$ by $n$ square matrices, and the empirical distribution based on the $n$ eigenvalues of the prod

Jared Bryan, Julien de Wit, Meng Sun, Zoë L. de Beurs

Hot Jupiters are expected to form far from their host star and move toward close-in, circular orbits via a smooth, monotonic decay due to mild and constant tidal dissipation. Yet, three systems have recently been found exhibiting planet-induced stellar pulsations suggesting unexpectedly strong tidal interactions. Here we combine stellar evolution and tide mo

Ergys Çokaj, Halvor Snersrud Gustad, Andrea Leone, Per Thomas Moe

Time series classification is of significant importance in monitoring structural systems. In this work, we investigate the use of supervised machine learning classification algorithms on simulated data based on a physical system with two states: Intact and Broken. We provide a comprehensive discussion of the preprocessing of temporal data, using measures of

Seán R. Kavanagh, Alexander G. Squires, Adair Nicolson, Irea Mosquera-Lois

Defects are a universal feature of crystalline solids, dictating the key properties and performance of many functional materials. Given their crucial importance yet inherent difficulty in measuring experimentally, computational methods (such as DFT and ML/classical force-fields) are widely used to predict defect behaviour at the atomic level and the resultan

Yash Sharma, Basil Abraham, Preethi Jyothi

An important and difficult task in code-switched speech recognition is to recognize the language, as lots of words in two languages can sound similar, especially in some accents. We focus on improving performance of end-to-end Automatic Speech Recognition models by conditioning transformer layers on language ID of words and character in the output in an per

Jingcong Liang, Rong Ye, Meng Han, Ruofei Lai

How can we construct an automated debate judge to evaluate an extensive, vibrant, multi-turn debate? This task is challenging, as judging a debate involves grappling with lengthy texts, intricate argument relationships, and multi-dimensional assessments. At the same time, current research mainly focuses on short dialogues, rarely touching upon the evaluation

Giacomo Brunello, Stefano De Angelis

We combine the observable-based formalism (KMOC), the analytic properties of the scattering amplitude, generalised unitarity and the heavy-mass expansion with a newly introduced IBP reduction for Fourier integrals, to provide an efficient framework for computing scattering waveforms. We apply this framework to the scattering of two charged massive bodies in

Zi Zhuang, Yang Su, Shiyu Zhang, Xuepeng Chen

We perform a comprehensive CO study toward the Monoceros OB1 (Mon OB1) region based on the MWISP survey at an angular resolution of about $50''$. The high-sensitivity data, together with the high dynamic range, shows that molecular gas in the $\rm 8^{\circ}\times4^{\circ}$ region displays complicated hierarchical structures and various morphology (e.g., fila

Harsh Lunia, Ajoy Mondal, C V Jawahar

The importance of Scene Text Recognition (STR) in today's increasingly digital world cannot be overstated. Given the significance of STR, data intensive deep learning approaches that auto-learn feature mappings have primarily driven the development of STR solutions. Several benchmark datasets and substantial work on deep learning models are available for Lat

Thomas Greber

Anisotropic open shell 4f ions have magnetic moments that can be read and written as atomic bits. If it comes to qbits where the phase of the wave function has to be written, controlled and read, it is of advantage to rely on more than one atom that carries the quantum information of the system because states with different susceptibilities may be addressed.

Zetian Yan

We prove that a stable $C^{1,1}$-to-edge properly embedded free boundary minimal hypersurface $\Sigma^3$ of a $4$-dimensional wedge domain $\Omega^4_{\theta}$ with angle $\theta\in (0,\pi]$ is flat.

Rodrigo Santos, João Silva, António Branco

The combination of language processing and image processing keeps attracting increased interest given recent impressive advances that leverage the combined strengths of both domains of research. Among these advances, the task of editing an image on the basis solely of a natural language instruction stands out as a most challenging endeavour. While recent app

Zijian Wu, Adam Schmidt, Peter Kazanzides, Septimiu E. Salcudean

The Segment Anything Model (SAM) is a powerful vision foundation model that is revolutionizing the traditional paradigm of segmentation. Despite this, a reliance on prompting each frame and large computational cost limit its usage in robotically assisted surgery. Applications, such as augmented reality guidance, require little user intervention along with ef

Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu

The scaling laws and extraordinary performance of large foundation models motivate the development and utilization of such models in biomedicine. However, despite early promising results on some biomedical benchmarks, there are still major challenges that need to be addressed before these models can be used in real-world clinics. Frontier general-domain mode

Kiril Hristov, Minwoo Suh

We construct solutions in the form of $AdS_2\times\Sigma$, where $\Sigma$ denotes a spindle geometry, within a particular 4d $\mathcal{N}=2$ gauged supergravity with vector multiplets and a charged hypermultiplet stemming from a consistent truncation of 6d matter coupled $F(4)$ gauged supergravity on a Riemann surface. We also compute the Bekenstein-Hawking

Ankit Kumar, Hermenegildo Borges de Oliveira, Manil T. Mohan

In this work, we consider the incompressible generalized Navier-Stokes-Voigt equations in a bounded domain $\mathcal{O}\subset\mathbb{R}^d$, $d\geq 2$, driven by a multiplicative Gaussian noise. The considered momentum equation is given by: \begin{align*} \mathrm{d}\left(\boldsymbol{u} - \kappa \Delta \boldsymbol{u}\right) = \left[\boldsymbol{f} +\operatorna

Do Duy Hieu, Phan Thi Ha Duong

The issue of network community detection has been extensively studied across many fields. Most community detection methods assume that nodes belong to only one community. However, in many cases, nodes can belong to multiple communities simultaneously.This paper presents two overlapping network community detection algorithms that build on the two-step approac

Nick Bultinck

We consider electron pairing in a two-dimensional thermally disordered itinerant anti-ferromagnet. It is shown that transverse spin fluctuations in such a state can give rise to superconductivity with a sizeable critical temperature $T_c$. Below $T_c$ there is quasi-long-range spin-singlet and $d_{x^2-y^2}$ superconducting order, together with fluctuating tr

Khizar Qureshi, Tauhid Zaman

Pairs trading, a strategy that capitalizes on price movements of asset pairs driven by similar factors, has gained significant popularity among traders. Common practice involves selecting highly cointegrated pairs to form a portfolio, which often leads to the inclusion of multiple pairs sharing common assets. This approach, while intuitive, inadvertently ele

Xun Qian, Tianyi Wang, Xuhai Xu, Tanya R Jonker

Advances in ubiquitous computing have enabled end-user authoring of context-aware policies (CAPs) that control smart devices based on specific contexts of the user and environment. However, authoring CAPs accurately and avoiding run-time errors is challenging for end-users as it is difficult to foresee CAP behaviors under complex real-world conditions. We pr

Jacob Pilawa, Emily R. Liepold, Chung-Pei Ma

Evidence for the majority of the supermassive black holes in the local universe has been obtained dynamically from stellar motions with the Schwarzschild orbit superposition method. However, there have been only a handful of studies using simulated data to examine the ability of this method to reliably recover known input black hole masses $M_{BH}$ and other

Keshav Bhandari, Simon Colton

Modelling musical structure is vital yet challenging for artificial intelligence systems that generate symbolic music compositions. This literature review dissects the evolution of techniques for incorporating coherent structure, from symbolic approaches to foundational and transformative deep learning methods that harness the power of computation and data a

D. G. Bussandri, G. M. Bosyk, F. Toscano

The conventional certification method for quantum teleportation protocols relies on surpassing the highest achievable classical average fidelity between target and teleported states. Our investigation highlights the limitations of this approach: inconsistent conclusions can be obtained when it is considered different distance measures in the quantum state sp

Ishaq Aden-Ali, Mikael Møller Høgsgaard, Kasper Green Larsen, Nikita Zhivotovskiy

Developing an optimal PAC learning algorithm in the realizable setting, where empirical risk minimization (ERM) is suboptimal, was a major open problem in learning theory for decades. The problem was finally resolved by Hanneke a few years ago. Unfortunately, Hanneke's algorithm is quite complex as it returns the majority vote of many ERM classifiers that ar

Bhishan Jacelon

We provide some background on the category of classifiable $\mathrm{C}^*$-algebras, whose objects are infinite-dimensional, simple, separable, unital $\mathrm{C}^*$-algebras that have finite nuclear dimension and satisfy the universal coefficient theorem, and describe some applications of the classification of objects in, and morphisms into, this category.

Daniel Zielasko, Alexander Meißner, Sebastian Freitag, Benjamin Weyers

Various factors influence the degree of cybersickness a user can suffer in an immersive virtual environment, some of which can be controlled without adapting the virtual environment itself. When using HMDs, one example is the size of the field of view. However, the degree to which factors like this can be manipulated without affecting the user negatively in

Florian Koch, Jan Carl Budich

A topological frequency converter represents a dynamical counterpart of the integer quantum Hall effect, where a two-level system enacts a quantized time-averaged power transfer between two driving modes of incommensurate frequency. Here, we investigate as to what extent temporal coherence in the quantum dynamics of the two-level system is important for the

Aravind P. Ravi, Sangwook Park, Svetozar A. Zhekov, Salvatore Orlando

Based on our Chandra imaging-spectroscopic observations, we present the latest evolution of the X-ray remnant of SN 1987A. Recent changes in the electron temperatures and volume emission measures suggest that the blast wave in SN 1987A is moving out of the dense inner ring structure, also called the equatorial ring (ER). The 0.5-2.0 keV X-ray light curve sho

Ben Adenbaum, Jennifer Elder, Pamela E. Harris, J. Carlos Martínez Mori

Given a Coxeter group $W$ with Coxeter system $(W,S)$, where $S$ is finite. We provide a complete characterization of Boolean intervals in the weak order of $W$ uniformly for all Coxeter groups in terms of independent sets of the Coxeter graph. Moreover, we establish that the number of Boolean intervals of rank $k$ in the weak order of $W$ is ${i_k(\Gamma_W)

Buxin She, Hisham Mahmood, Marcelo Elizondo, Veronica Adetola

As offshore wind farms (OWFs) become increasingly prevalent in Northern California and Southern Oregon, they introduce faster dynamics into the Western Electricity Coordinating Council (WECC) system, reshaping its dynamic behavior. Accordingly, electromagnetic transient (EMT) simulation is essential to assess high frequency dynamics of the WECC system with i

Joonas Hirvonen

We study real-time nucleation in perturbative high-temperature quantum field theories. Specifically, we incorporate the evolution of thermally fluctuating plasma driven out of equilibrium by nucleation. This plasma forms the thermal bath for the nucleating bubbles, and its off-equilibrium dynamics backreact on the bubbles, modifying the nucleation rate. Util

Anna-Christina Eilers, Ruari Mackenzie, Elia Pizzati, Jorryt Matthee

We expect luminous ($M_{1450}\lesssim-26.5$) high-redshift quasars to trace the highest density peaks in the early universe. Here, we present observations of four $z\gtrsim6$ quasar fields using JWST/NIRCam in imaging and widefield slitless spectroscopy mode and report a wide range in the number of detected [OIII]-emitting galaxies in the quasars' environmen