October 2024 arXiv papers — page 72

Isamu Isozaki, Manil Shrestha, Rick Console, Edward Kim

Hacking poses a significant threat to cybersecurity, inflicting billions of dollars in damages annually. To mitigate these risks, ethical hacking, or penetration testing, is employed to identify vulnerabilities in systems and networks. Recent advancements in large language models (LLMs) have shown potential across various domains, including cybersecurity. Ho

Timur Aslyamov, Krzysztof Ptaszyński, Massimiliano Esposito

In nonequilibrium steady states of Markov jump processes, we derive exact Fluctuation-Response Relations (FRRs) that express the covariance between any pair of currents in terms of static responses in a notably simple form, thus generalizing the fluctuation-dissipation theorem far from equilibrium. We begin by considering perturbations in the symmetric part

Rossana Bettoni, Geneviéve Dupont, Aleksandra M. Walczak, Sophie de Buyl

The onset of neural induction in the anterior ectoderm of ascidian embryos is regulated at the extracellular level by FGF signaling molecules, which control the acquisition of neural fate through the activation of the ERK pathway. Among the anterior ectoderm cells exposed to FGF, only a fraction will acquire neural fate. The selection of neural precursors de

MD Abdullah Al Nasim, A. S. M Anas Ferdous, Abdur Rashid, Fatema Tuj Johura Soshi

Artificial Intelligence (AI) is an important part of our everyday lives. We use it in self-driving cars and smartphone assistants. People often call it a "black box" because its complex systems, especially deep neural networks, are hard to understand. This complexity raises concerns about accountability, bias, and fairness, even though AI can be quite accura

Mateusz Piorkowski

We compute the algebraic equation for arctic curves of the Aztec diamond with a doubly (quasi-)periodic weight structure and obtain similar results for certain models of the hexagon. In particular, we determine the algebraic degree of such curves as a function of the number of frozen and smooth (or gaseous) regions. The key to our result is the construction

XLZD Collaboration, J. Aalbers, K. Abe, M. Adrover

This report describes the experimental strategy and technologies for XLZD, the next-generation xenon observatory sensitive to dark matter and neutrino physics. In the baseline design, the detector will have an active liquid xenon target of 60 tonnes, which could be increased to 80 tonnes if the market conditions for xenon are favorable. It is based on the ma

Xiaoxuan Ma, Yutang Lin, Yuan Xu, Stephan P. Kaufhold

Understanding non-human primate behavior is crucial for improving animal welfare, modeling social behavior, and gaining insights into both distinctly human and shared behaviors. Despite recent advances in computer vision, automated analysis of primate behavior remains challenging due to the complexity of their social interactions and the lack of specialized

Brian M. Kirk, Urvashi Rau, Ramyaa Ramyaa

Radio interferometry is an observational technique used to study astrophysical phenomena. Data gathered by an interferometer requires substantial processing before astronomers can extract the scientific information from it. Data processing consists of a sequence of calibration and analysis procedures where choices must be made about the sequence of procedure

Yan Huang

Cohort discovery is a crucial step in clinical research on Electronic Health Record (EHR) data. Temporal queries, which are common in cohort discovery, can be time-consuming and prone to errors when processed on large EHR datasets. In this work, we introduce TELII, a temporal event level inverted indexing method designed for cohort discovery on large EHR dat

Emil Rinatovich Gallyamov, Guillaume Anciaux, Nicolas Richart, Jean-François Molinari

We present a fully implicit formulation of coupled fluid flow and geomechanics for fluid injection/withdrawal in fractured reservoirs in the context of CO2storage. Utilizing a Galerkin finite-element approach, both flow and poroelasticity equations are discretized on a shared three-dimensional mesh. The fluid flow is assumed to be single-phase. The hydraulic

Giacomo Franchini, Brenno Tuberga, Marcello Chiaberge

In an era marked by renewed interest in lunar exploration and the prospect of establishing a sustainable human presence on the Moon, innovative approaches supporting mission preparation and astronaut training are imperative. To this end, the advancements in Virtual Reality (VR) technology offer a promising avenue to simulate and optimize future human mission

Hao Xiang, Bowen Yu, Hongyu Lin, Keming Lu

The key to effective alignment lies in high-quality preference data. Recent research has focused on automated alignment, which involves developing alignment systems with minimal human intervention. However, prior research has predominantly focused on developing data generation methods, while insufficient attention has been paid to quality control mechanisms,

Dan Wang

Let $(X, \omega, J)$ be a toric variety of dimension $2n$ determined by a Delzant polytope $P$. As indicated in [40], $X$ admits a natural mixed polarization $\mathcal{P}_{k}$, induced by the action of a subtorus $T^{k}$. In this paper, we first establish the quantum space $\mathcal{H}_{k}$ for $\mathcal{P}_{k}$, identifying a basis parameterized by the inte

Oli Jones

Given a connected large-type Artin group $A_\Gamma$, we introduce a deformation space $\mathcal{D}$. If $\Gamma$ is triangle-free, or has all labels at least 6, we show that this space is canonical, in that it depends only on the isomorphism type of $A_\Gamma$, and admits an $\Out(A_\Gamma)$-action. Using this action we conclude that $\Out(A_\Gamma)$ is of t

Gholamali Aminian, Łukasz Szpruch, Samuel N. Cohen

We propose a novel framework for exploring generalization errors of transfer learning through the lens of differential calculus on the space of probability measures. In particular, we consider two main transfer learning scenarios, $\alpha$-ERM and fine-tuning with the KL-regularized empirical risk minimization and establish generic conditions under which the

Bo-Shun Yang, Susanne M Hoffmann

In recent astronomical discussions, attempts have been made to link the known dwarf nova Z Cam to historical celestial events, particularly the "guest star" phenomenon reported in China in 77 BCE. Despite other suggestions and the problems with regard to the location of the event in 77 BCE, its identification with Z Cam is used in the Variable Star IndeX (VS

Li Siyan, Vethavikashini Chithrra Raghuram, Omar Khattab, Julia Hirschberg

Users can divulge sensitive information to proprietary LLM providers, raising significant privacy concerns. While open-source models, hosted locally on the user's machine, alleviate some concerns, models that users can host locally are often less capable than proprietary frontier models. Toward preserving user privacy while retaining the best quality, we pro

Leonardo Muller-Rodriguez, Owen O'Daly

The growing use of naturalistic stimuli, such as feature films, brings research on emotions closer to ecologically valid settings within brain scanners, such as functional magnetic resonance imaging (fMRI). Music is another cultural artifact known to evoke emotions, and film soundtracks are often designed to enhance the emotional impact of the narrative. How

Alexander G. Padula, Dennis J. N. J. Soemers

Proximal Policy Optimization (PPO) is commonly used in Reinforcement Learning from Human Feedback to align large language models (LLMs) with downstream tasks. This paper investigates the feasibility of using PPO for direct reinforcement learning (RL) from explicitly programmed reward signals, as opposed to indirect learning from human feedback via an interme

Masatoshi Kitagawa

In this paper, we study the irreducibility of $\mathcal{U}(\mathfrak{g})^{G'}$-modules on the spaces of intertwining operators in the branching problem of reductive Lie algebras, and construct a family of finite-dimensional irreducible $\mathcal{U}(\mathfrak{g})^{G'}$-modules using the Zuckerman derived functors. We provide criteria for the irreducibility of

Grigoriy Blekherman, Alex Dunbar, Rainer Sinn

We study the Pythagoras numbers $py(3,2d)$ of real ternary forms, defined for each degree $2d$ as the minimal number $r$ such that every degree $2d$ ternary form which is a sum of squares can be written as the sum of at most $r$ squares of degree $d$ forms. Scheiderer showed that $d+1\leq py(3,2d)\leq d+2$. We show that $py(3,2d) = d+1$ for $2d = 8,10,12$. T

Mattia Bruno, Niccolò Forzano, Marco Panero, Antonio Smecca

The hypothesis that dark matter could be a bound state of a strongly coupled non-Abelian gauge theory is theoretically appealing and has a variety of interesting phenomenological implications. In particular, an interpretation of dark matter as the lightest glueball state in the spectrum of a dark Yang-Mills theory, possibly coupled to the visible sector only

Marcos Faundez-Zanuy, Josep Lopez-Xarbau, Moises Diaz, Manuel Garnacho-Castaño

This paper examines the saturation of pressure signals during various handwriting tasks, including drawings, cursive text, capital words text, and signature, under different levels of fatigue. Experimental results demonstrate a significant rise in the proportion of saturated samples following strenuous exercise in tasks performed without resting wrist. The a

Benjamin Brück, Kevin Ivan Piterman

We show that the complex of partial bases of the free group of rank $n$, where vertices are seen up to conjugation, is Cohen--Macaulay of dimension $n-1$. This positively answers a conjecture raised by Day and Putman. We prove our results in the more general context of freely decomposable groups.

Dan Noelck

This work focuses on the well-posedness of McKean-Vlasov stochastic differential delay equations. Under suitable lipschitz conditions on the drift and diffusion terms, along with a distribution dependent Lyapunov condition, this paper shows the existence of a unique solution to the distribution dependent stochastic differential delay equation.

Linda Knutsson, Nirbhay N. Yadav, Sajad Mohammed Ali, David Olayinka Kamson

Purpose: Dynamic glucose enhanced (DGE) MRI studies employ chemical exchange saturation transfer (CEST) or spin lock (CESL) to study glucose uptake. Currently, these methods are hampered by low effect size and sensitivity to motion. To overcome this, we propose to utilize exchange-based linewidth (LW) broadening of the direct water saturation (DS) curve of t

Han Ji, Xiping Wu, Zhihong Zeng, Chen Chen

Hybrid light fidelity (LiFi) and wireless fidelity (WiFi) networks are a promising paradigm of heterogeneous network (HetNet), attributed to the complementary physical properties of optical spectra and radio frequency. However, the current development of such HetNets is mostly bottlenecked by the existing transmission control protocol (TCP), which restricts

A. Y. Yang, M. A. Thompson, J. S. Urquhart, A. Brunthaler

Context: Theoretical models of early accretion during the formation process of massive stars have predicted that HII regions exhibit radio variability on timescales of decades. However, large-scale searches for such temporal variations with sufficient sensitivity have not yet been carried out. Aims: We aim to identify HII regions with variable radio waveleng

Martí Alonso, David Andreu, Ramon Canal, Stefano Di Carlo

Security and RAS are two non-functional requirements under focus for current systems developed for the computing continuum. Due to the increased number of interconnected computer systems across the continuum, security becomes especially pervasive at all levels, from the smallest edge device to the high-performance cloud at the other end. Similarly, RAS (Reli

Aseel AlNajjar, Stefano Spirito, Athanasios E. Tzavaras

We consider the system of viscoelasticity with higher-order gradients and nonconvex energy in several space dimensions. We establish the asymptotic limits when the viscosity $\nu\rightarrow 0$ or when the dispersion coefficient $\delta \rightarrow 0$. For the latter problem, it is worth noting that, for the case of two space dimensions, we also establish a r

Anthony Sfeir, Asya Petkova, Sabine Chaaya, Karina Chichova

As humans venture deeper into space, the need for a lunar settlement, housing the first group of settlers, grows steadily. By means of new technologies such as in situ resource utilisation (ISRU) as well as computational design, this goal can be implemented in present years. Providing the first arrivals with an immediate underground habitat safe from radiati

Jianan Bai, Erik G. Larsson

The wireless channel changes continuously with time and frequency and the block-fading assumption, which is popular in many theoretical analyses, never holds true in practical scenarios. This discrepancy is critical for user activity detection in grant-free random access, where joint processing across multiple coherence blocks is undesirable, especially when

Juraj Vladika, Luca Mülln, Florian Matthes

The increasing popularity of Large Language Models (LLMs) in recent years has changed the way users interact with and pose questions to AI-based conversational systems. An essential aspect for increasing the trustworthiness of generated LLM answers is the ability to trace the individual claims from responses back to relevant sources that support them, the pr

Yimeng Min

This paper proposes a framework that formulates a wide range of graph combinatorial optimization problems using permutation-based representations. These problems include the travelling salesman problem, maximum independent set, maximum cut, and various other related problems. This work potentially opens up new avenues for algorithm design in neural combinato

Nayandeep Deka Baruah, Pranjal Talukdar

We prove some new modular identities for the Rogers\textendash Ramanujan continued fraction. For example, if $R(q)$ denotes the Rogers\textendash Ramanujan continued fraction, then \begin{align*}&R(q)R(q^4)=\dfrac{R(q^5)+R(q^{20})-R(q^5)R(q^{20})}{1+R(q^{5})+R(q^{20})},\\ &\dfrac{1}{R(q^{2})R(q^{3})}+R(q^{2})R(q^{3})= 1+\dfrac{R(q)}{R(q^{6})}+\dfrac{R(q^{6})

Matthieu Schaller, Joop Schaye, Roi Kugel, Jeger C. Broxterman

The effect of baryon physics associated with galaxy formation onto the large-scale matter distribution of the Universe is a key uncertainty in the theoretical modelling required for the interpretation of Stage IV surveys. We use the FLAMINGO simulations to study the baryon response due to galaxy formation of the total matter power spectrum. We find that it i

Alec Farid, Peter Schleede, Aaron Huang, Christoffer Heckman

We are motivated by the problem of autonomous vehicle performance validation. A key challenge is that an autonomous vehicle requires testing in every kind of driving scenario it could encounter, including rare events, to provide a strong case for safety and show there is no edge-case pathological behavior. Autonomous vehicle companies rely on potentially mil

Vik Shirvaikar, Stephen G. Walker, Chris Holmes

Existing approaches to model uncertainty typically either compare models using a quantitative model selection criterion or evaluate posterior model probabilities having set a prior. In this paper, we propose an alternative strategy which views missing observations as the source of model uncertainty, where the true model would be identified with the complete

Joachim Schwermer

Using the quaternionic formalism for the description of the group of isometries of hyperbolic $5$-space we consider arithmetically defined $5$-dimensional hyperbolic manifolds which are non-compact but of finite volume. They arise from maximal orders $\Lambda$ in the central simple algebra $M_2(D)$ of degree $4$ where $D$ denotes a definite quaternion $\math

Huang Neng

Privacy computing involves the extensive exchange and processing of encrypted data. For the parties involved in these interactions, how to determine the consistency of exchanged data without accessing the original data, ensuring tamper resistance, non-repudiation, quality traceability, indexing, and retrieval during the use of encrypted data, which is a key

Richard Sharp

We give two short proofs of the abelian Livsi\v{c} theorem of Gogolev and Rodriguez Hertz. We show that these proofs may be extended to give new abelian Livsic theorems for positive density sets of null-homologous orbits and for amenable covers.

Aayushya Agarwal, Yihan Ruan, Larry Pileggi

Simulation is vital for engineering disciplines, as it enables the prediction and design of physical systems. However, the computational challenges inherent to large-scale simulations often arise from complex device models featuring high degrees of nonlinearities or hidden physical behaviors not captured by first principles. Gray-box models combine deep neur

Klaus Mattis, Timo Weiß

For an endofunctor $F\colon\mathcal{C}\to\mathcal{C}$ on an ($\infty$-)category $\mathcal{C}$ we define the $\infty$-category $\operatorname{Cart}(\mathcal{C},F)$ of generalized Cartier modules as the lax equalizer of $F$ and the identity. This generalizes the notion of Cartier modules on $\mathbb{F}_p$-schemes considered in the literature. We show that in f

Yongqing Liang, Huijun Han, Xin Li

Solving point-wise feature correspondence in visual data is a fundamental problem in computer vision. A powerful model that addresses this challenge is to formulate it as graph matching, which entails solving a Quadratic Assignment Problem (QAP) with node-wise and edge-wise constraints. However, solving such a QAP can be both expensive and difficult due to n

Leo de Waal, Matthaios Chouzouris, Marcelo A. Dias

Architecting mechanisms of damage in metamaterials by leveraging lattice topology and geometry poses a vital yet complex challenge, essential for engineering desirable mechanical responses. Of these metamaterials, Maxwell lattices, which are on the verge of mechanical stability, offer significant potential for advanced functionality. By leveraging their robu

Jiyi Li

The quality is a crucial issue for crowd annotations. Answer aggregation is an important type of solution. The aggregated answers estimated from multiple crowd answers to the same instance are the eventually collected annotations, rather than the individual crowd answers themselves. Recently, the capability of Large Language Models (LLMs) on data annotation

David Schneider, Sina Sajadmanesh, Vikash Sehwag, Saquib Sarfraz

Privacy-preserving computer vision is an important emerging problem in machine learning and artificial intelligence. Prevalent methods tackling this problem use differential privacy (DP) or obfuscation techniques to protect the privacy of individuals. In both cases, the utility of the trained model is sacrificed heavily in this process. In this work, we pres

Maja Rønne, Allan Larsen, Jens H. Walther, Søren V. Larsen

The present paper reports on wind tunnel tests and analyses carried out to investigate the effect of the static angle of attack on the aerodynamic stability of a twin-box bridge deck section. It is found that the critical wind speed for onset of flutter increases with increasing positive static angles (nose-up) and that this effect relates mainly to a decrea

Aurélien Alfonsi, Vlad Bally, Lucia Caramellino

The stochastic sewing lemma recently introduced by Le~(2020) allows to construct a unique limit process from a doubly indexed stochastic process that satisfies some regularity. This lemma is stated in a given probability space on which these processes are defined. The present paper develops a version of this lemma for probability measures: from a doubly inde

Shuaiqi Wang, Shuran Zheng, Zinan Lin, Giulia Fanti

Information disclosure can compromise privacy when revealed information is correlated with private information. We consider the notion of inferential privacy, which measures privacy leakage by bounding the inferential power a Bayesian adversary can gain by observing a released signal. Our goal is to devise an inferentially-private private information structu

Dripto Biswas, Raffaele Marotta, Igor Pesando

We provide a compact expression for the generating function of correlators involving an arbitrary number of bosonic open string DDF states. The explicit correlators for $M$ DDF states can then be obtained by differentiating this generating function with respect to the DDF polarization tensors. The generating function depends on single and double complex inte

Christian Zimmermann, Antoine Gérardin

Hadronic contributions dominate the uncertainty of the Standard Model prediction for the anomalous magnetic moment of the muon. In this work, we present results on the hadronic light-by-light contribution obtained from the evaluation of the hadronic four-point function of electromagnetic currents using the position-space formalism developed by the Mainz grou

Benjamin Carrel

We introduce novel dynamical low-rank methods for solving large-scale matrix differential equations, motivated by algorithms from randomized numerical linear algebra. In terms of performance (cost and accuracy), our methods overperform existing dynamical low-rank techniques. Several applications to stiff differential equations demonstrate the robustness, acc

Cristina Bertone, Francesca Cioffi, Matthias Orth, Werner M. Seiler

Using techniques coming from the theory of marked bases, we develop new computational methods for detection and construction of Cohen-Macaulay, Gorenstein and complete intersection homogeneous polynomial ideals. Thanks to the functorial properties of marked bases, an elementary and effective proof of the openness of arithmetically Cohen-Macaulay, arithmetica

Haining Wang, Jason Clark, Hannah McKelvey, Leila Sterman

A vast amount of scholarly work is published daily, yet much of it remains inaccessible to the general public due to dense jargon and complex language. To address this challenge in science communication, we introduce a reinforcement learning framework that fine-tunes a language model to rewrite scholarly abstracts into more comprehensible versions. Guided by

Andrew Mummery, Sjoert van Velzen

We reproduce the luminosity functions of the early-time peak optical luminosity, the late-time UV plateau luminosity, and the peak X-ray luminosity of tidal disruption events, using an entirely first-principles theoretical approach. We do this by first fitting three free parameters of the tidal disruption event black hole mass distribution using the observed

Aleksandrs Slivkins

How to incentivize self-interested agents to explore when they prefer to exploit? Consider a population of self-interested agents that make decisions under uncertainty. They "explore" to acquire new information and "exploit" this information to make good decisions. Collectively they need to balance these two objectives, but their incentives are skewed toward

Huihui Cheng, Minjie Song

Let $X$ be a $p\times n$ independent identically distributed real Gaussian matrix with positive mean $\mu $ and variance $\sigma^2$ entries. The goal of this paper is to investigate the largest eigenvalue of the noncentral sample covariance matrix $W=XX^{T}/n$, when the dimension $p$ and the sample size $n$ both grow to infinity with the limit $p/n=c\,(0<c<\

Abhirup Banerjee, Armin Koehl, Frank Lunkeit, Detlef Stammer

Continental heatwaves can dramatically impact ecosystems and societies, e.g., by leading to excess mortality, wildfires, and harvest failures. With a warming climate, their impacts potentially intensify globally, but the Indian subcontinent appears to be particularly vulnerable to such extreme events. In this study, we use reanalysis and the adjoint of the a

Franko Šikić, Donik Vršnak, Sven Lončarić

In this paper, we present a survey of deep learning-based methods for the regression of gaze direction vector from head and eye images. We describe in detail numerous published methods with a focus on the input data, architecture of the model, and loss function used to supervise the model. Additionally, we present a list of datasets that can be used to train

Luis Guillermo Venegas-Pineda, Hildeberto Jardón-Kojakhmetov, Ming Cao

Oscillatory behavior is ubiquitous in many natural and engineered systems, often emerging through self-regulating mechanisms. In this paper, we address the challenge of stabilizing a desired oscillatory pattern in a networked system where neither the internal dynamics nor the interconnections can be changed. To achieve this, we propose two distinct control s

Yixing Li, Ruobing Xie, Xingwu Sun, Yu Cheng

The fusion of speech and language in the era of large language models has garnered significant attention. Discrete speech token is often utilized in text-to-speech tasks for speech compression and portability, which is convenient for joint training with text and have good compression efficiency. However, we found that the discrete speech tokenizer still suff

S. Ahmadi, E. Yusofi, M. A. Ramzanpour

Numerous studies have shown that generalized uncertainty principle (GUP) removes the Chandrasekhar limit, which can be restored using a negative GUP parameter. This study indicates that observational phantom dark energy also requires an extended uncertainty principle (EUP) parameter with the opposite sign. Altering the signs of the GUP and EUP parameters wit

Ernesto Garcia-Alfonso, Francesco Ancilotto, Manuel Barranco, Fausto Cargnoni

We study superfluid helium droplets multiply charged with ions. When stable, the charges are found to reside in equilibrium close to the droplet surface, thus representing a physical realization of Thomson's model. We find the minimum radius of the helium droplet that can host a given number of ions using a model whose physical ingredients are the solvation

Hasibul Jamil, Abdul Alim, Laurent Schares, Pavlos Maniotis

The increasing complexity of AI workloads, especially distributed Large Language Model (LLM) training, places significant strain on the networking infrastructure of parallel data centers and supercomputing systems. While Equal-Cost Multi- Path (ECMP) routing distributes traffic over parallel paths, hash collisions often lead to imbalanced network resource ut

Xinyuan Zhang, Shiqi Hu, Mengxue Guan, Sheng Meng

A practical approach is proposed for efficiently generating ultrashort attosecond pulses (APs) from realistic solid-state materials, aiming to optimize pulse width effectively. By adjusting the photon energy while maintaining a constant peak electric field, this strategy modulates the peak vector potential and laser field period, thereby controlling the high

V. A. Zakharov, I. C. Fulga, G. Lemut, J. Tworzydlo

Most superconductors are thermal insulators. A disordered chiral $\textit{p}$-wave superconductor, however, can make a transition to a thermal metal phase. Because heat is then transported by Majorana fermions, this phase is referred to as a Majorana metal. Here we present numerical evidence that the mechanism for the phase transition with increasing electro

Xutong Liu, Xiangxiang Dai, Xuchuang Wang, Mohammad Hajiesmaili

We introduce a novel framework called combinatorial logistic bandits (CLogB), where in each round, a subset of base arms (called the super arm) is selected, with the outcome of each base arm being binary and its expectation following a logistic parametric model. The feedback is governed by a general arm triggering process. Our study covers CLogB with reward

Neil Lambert, Joseph Smith

It has recently been realised that there are supersymmetry-preserving non-relativistic decoupling limits associated with each half-BPS object in String Theory and M-Theory. We argue that, given a $p$-brane and a $q$-brane for which there is a quarter-BPS intersecting configuration, the $p$-brane decoupling limit of the $q$-brane's worldvolume QFT is necessar

Weihui Deng, Zhiwei Fan, Deliang Fu, Yun Gong

Short-form video content has become increasingly popular and influential in recent years. Its concise yet engaging format aligns well with todays' fast-paced and on-the-go lifestyles, making it a dominating trend in the digital world. As one of the front runners in the short video platform space, ByteDance has been highly successful in delivering a one-of-a-

Cameron Vo, Owen Anderson, Anna Wirth-Singh, Rose Johnson

Long-range imaging in the thermal infrared band is critical for applications such as environmental monitoring, industrial inspections, and surveillance. To achieve high quality imaging, these systems typically require large apertures and many elements with complex shapes to correct aberrations, adding significant weight and cost. Large-area metasurface optic

Duarte Rocha, Philip L. Lederer, Pim J. Dekker, Alvaro Marin

When an evaporating water droplet is deposited on a thermally conductive substrate, the minimum temperature will be at the apex due to evaporative cooling. Consequently, density and surface tension gradients emerge within the droplet and at the droplet-gas interface, giving rise to competing flows from, respectively, the apex towards the contact line (therma

Yasuyuki Hamura

In this short note, we consider posterior simulation for a linear regression model when the error distribution is given by a scale mixture of multivariate normals. We first show that the sampler of Backlund and Hobert (2020) for the case of the conditionally conjugate normal-inverse Wishart prior continues to be geometrically ergodic even when the error dens

Lingzhen Guo, Tangyou Huang, Lei Du

Bosonic codes offer a hardware-efficient approach to encoding and protecting quantum information with a single continuous-variable bosonic system. In this paper, we introduce a new universal quantum gate set composed of only one type of gate element, which we call the quantum lattice gate, to engineer bosonic code states for fault-tolerant quantum computing.

Jianan Bai, Zheng Chen, Erik. G. Larsson

We study a delay-constrained grant-free random access system with a multi-antenna base station. The users randomly generate data packets with expiration deadlines, which are then transmitted from data queues on a first-in first-out basis. To deliver a packet, a user needs to succeed in both random access phase (sending a pilot without collision) and data tra

Walter H. Baron, Carmen A. Nunez, Jesus A. Rodriguez

The low energy effective action describing the Kaluza-Klein reduction of string theory on a $d$-torus possesses a continuous O($d, d$) global symmetry. The non-geometric piece of this symmetry, parameterized by a bi-vector $\beta$, was recently shown to effectively act as a hidden symmetry on the massless RR and universal NSNS fields of the ten dimensional p

Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco

Spike Timing-Dependent Plasticity (STDP) is a promising substitute to backpropagation for local training of Spiking Neural Networks (SNNs) on neuromorphic hardware. STDP allows SNNs to address classification tasks by combining unsupervised STDP for feature extraction and supervised STDP for classification. Unsupervised STDP is usually employed with Winner-Ta

Sarga P K, Karthik H J, Swastibrata Bhattacharyya

Building two-dimensional (2D) van der Waals (vdW) heterostructures and enhancing their properties through strain engineering unlocks new applications for their constituent materials. In this study, we present a comprehensive first-principles investigation of oxygen-functionalized MXene-based heterostructures (M$_2$CO$_2$ (M=Sc,Zr,Hf)/blue phosphorene), empha

Haim Goldfisher, Asaf Yekutiel

This paper presents a novel approach for multi-kernel estimation by enhancing the KernelGAN algorithm, which traditionally estimates a single kernel for the entire image. We introduce Multi-KernelGAN, which extends KernelGAN's capabilities by estimating two distinct kernels based on object segmentation masks. Our approach is validated through three distinct

Rômulo Damasclin Chaves dos Santos, Jorge Henrique de Oliveira Sales

This research explores the development and application of the High-Order Dynamic Integration Method for solving integro-differential equations, with a specific focus on turbulent fluid dynamics. Traditional numerical methods, such as the Finite Difference Method and the Finite Volume Method, have been widely employed in fluid dynamics but struggle to accurat

Felix Fischer, Moonkwang Jeong, Tian Qiu

Magneto-oscillatory devices have been recently developed as very potent wireless miniature position trackers and sensors with an exceptional accuracy and sensing distance for surgical and robotic applications. However, it is still unclear to which extend a mechanically resonating sub-millimeter magnet interacts with external magnetic fields or gradients, whi

Laboni Manna, Anton Safronov, Carlo Flore, Daniel Kikola

The upcoming Electron-Ion Collider (EIC), with its high luminosity, will offer an unprecedented opportunity to explore the internal structure of atomic nucleus over an extended energy range from $\sqrt{s_{ep}} =$ 45 GeV to $\sqrt{s_{ep}} =$ 140 GeV. A particularly promising aspect of this collider is the study of the partonic structure with quasi-real photon

Alexander Hofmann, Albin Cakaj, Lea Kolb, Yutaka Noguchi

The alignment of permanent dipole moments and the resulting spontaneous orientation polarization (SOP) is commonly observed in evaporated neat films of polar organic molecules and leads to a so-called giant surface potential. In case of mixed films, often enhanced molecular orientation is observed, i.e.\ a higher degree of alignment, in comparison to neat la

Fan Xu, Lei Zhang, Bin Liu

In this work, we consider the 3D Cauchy problem for a coupled system arising in biomathematics, consisting of a chemotaxis model with a cubic logistic source and the stochastic tamed Navier-Stokes equations (STCNS, for short). Our main goal is to establish the existence and uniqueness of a global strong solution (strong in both the probabilistic and PDE sens

Yenan Shen, Naomi Ehrich Leonard, Bassam Bamieh, Juncal Arbelaiz

Soft robots offer a frontier in robotics with enormous potential for safe human-robot interaction and agility in uncertain environments. A stepping stone towards unlocking their potential is a control theory tailored to soft robotics, including a principled framework for gait design. We analyze the problem of optimal gait design for a soft crawling body - th

Jam Sadiq, Kallol Dey, Thomas Dent, Enrico Barausse

Reconstructing the properties of the astrophysical population of binary compact objects in the universe is a key science goal of gravitational wave detectors. This goal is hindered by the finite strain, frequency sensitivity and observing time of current and future detectors. This implies that we can in general observe only a selected subset of the underlyin

Antoine Scheid, Etienne Boursier, Alain Durmus, Michael I. Jordan

Reinforcement Learning from Human Feedback (RLHF) has become a popular approach to align language models (LMs) with human preferences. This method involves collecting a large dataset of human pairwise preferences across various text generations and using it to infer (implicitly or explicitly) a reward model. Numerous methods have been proposed to learn the r

David Cruz-Uribe

It is well known that non-negative solutions to the Dirichlet problem $\Delta u =f$ in a bounded domain $\Omega$, where $f\in L^q(\Omega)$, $q>\frac{n}2$, satisfy $\|u\|_{L^\infty(\Omega)} \leq C\|f\|_{L^q(\Omega)}$. We generalize this result by replacing the Laplacian with a degenerate elliptic operator, and we show that we can take the data $f$ in an Orlic

Sebastian Spiegel, Christoph Lehner

The separation of the hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment into Euclidean windows allows for a tailored approach to address the different dominant challenges at short, intermediate, and long distances. We present a novel approach to compute the short-distance window without the need for using perturbative QCD.

Meng Tong, Kejiang Chen, Xiaojian Yuan, Jiayang Liu

Text sanitization, which employs differential privacy to replace sensitive tokens with new ones, represents a significant technique for privacy protection. Typically, its performance in preserving privacy is evaluated by measuring the attack success rate (ASR) of reconstruction attacks, where attackers attempt to recover the original tokens from the sanitize

Shir Ashury-Tahan, Amir David Nissan Cohen, Nadav Cohen, Yoram Louzoun

While coreference resolution is traditionally used as a component in individual document understanding, in this work we take a more global view and explore what can we learn about a domain from the set of all document-level coreference relations that are present in a large corpus. We derive coreference chains from a corpus of 30 million biomedical abstracts

Yash Sinha, Murari Mandal, Mohan Kankanhalli

The key components of machine learning are data samples for training, model for learning patterns, and loss function for optimizing accuracy. Analogously, unlearning can potentially be achieved through anti-data samples (or anti-samples), unlearning method, and reversed loss function. While prior research has explored unlearning methods and reversed loss fun

Hadeel Aboueidah, Abdulrahman Altahhan

Accurately predicting the state of charge of Lithium-ion batteries is essential to the performance of battery management systems of electric vehicles. One of the main reasons for the slow global adoption of electric cars is driving range anxiety. The ability of a battery management system to accurately estimate the state of charge can help alleviate this pro

Yixiao Zhang, Wei Liang, Lixin Li, Wensheng Lin

This paper investigates a transmission scheme for enhancing quantum communication security, aimed at improving the security of space-air-ground integrated networks (SAGIN). Quantum teleportation achieves the transmission of quantum states through quantum channels. In simple terms, an unknown quantum state at one location can be reconstructed on a particle at

Arsenii Kasianchuk, Volodymyr Reshetnyk

In this work, we analyzed the orbits of more than 35,000 (for 2024) near-Earth objects (NEOs) for the possibility of successive approaches to all pairs of planets: Earth, Venus, and Mars in the time range from 2020 to 2120. We have selected 120 candidates for Earth-Mars, Earth-Venus, Mars-Earth, Mars-Venus, Venus-Earth, and Venus-Mars fast transfers (within

Peter W. MacDonald, Elizaveta Levina, Ji Zhu

Networks arise naturally in many scientific fields as a representation of pairwise connections. Statistical network analysis has most often considered a single large network, but it is common in a number of applications to observe multiple networks on a shared node set. When these networks are grouped by case-control status or another categorical covariate,

Sergey Goncharov, Stelios Tsampas, Henning Urbat

Levy's call-by-push-value is a comprehensive programming paradigm that combines elements from functional and imperative programming, supports computational effects and subsumes both call-by-value and call-by-name evaluation strategies. In the present work, we develop modular methods to reason about program equivalence in call-by-push-value, and in fine-grain

Danté M. Hewitt, Mohit Bhardwaj, Alexa C. Gordon, Aida Kirichenko

We present the localization and host galaxy of FRB 20190208A, a repeating source of fast radio bursts (FRBs) discovered using CHIME/FRB. As part of the PRECISE repeater localization program on the EVN, we monitored FRB 20190208A for 65.6 hours at $\sim1.4$ GHz and detected a single burst, which led to its VLBI localization with 260 mas uncertainty (2$\sigma$

Jialong Li, Shreyansh Tripathi, Lakshay Rastogi, Yiming Lei

As machine learning models scale in size and complexity, their computational requirements become a significant barrier. Mixture-of-Experts (MoE) models alleviate this issue by selectively activating relevant experts. Despite this, MoE models are hindered by high communication overhead from all-to-all operations, low GPU utilization due to the synchronous com

Anushka Narayanan, Karianne J. Bergen

Prototype-based methods are intrinsically interpretable XAI methods that produce predictions and explanations by comparing input data with a set of learned prototypical examples that are representative of the training data. In this work, we discuss a series of developments in the field of prototype-based XAI that show potential for scientific learning tasks,