March 2025 arXiv papers — page 98

Aneesh Ramaswamy, Dmitry Budker, Simon Rochester, Aram Papoyan

Theoretical predictions were made for the steady-state gain of an orthogonally polarized probe field in a degenerate two-level alkali atom system driven by a linearly polarized continuous-wave pump field in [Opt. Mem. Neural Networks 32 (Suppl 3), S443-S446 (2023)]. Employing linear response theory, we computed the probe absorption spectrum under conditions

Robert Bernson, Alex Witte, Genevieve Clark, Kamil Gradkowski

Optically linked solid-state quantum memories such as color centers in diamond are a promising platform for distributed quantum information processing and networking. Photonic integrated circuits (PICs) have emerged as a crucial enabling technology for these systems, integrating quantum memories with efficient electrical and optical interfaces in a compact a

Junehyoung Jeon, Boyuan Liu, Anthony J. Taylor, Vasily Kokorev

Observations with the James Webb Space Telescope (JWST) have identified an abundant population of supermassive black holes (SMBHs) already in place during the first few hundred million years of cosmic history. Most of them appear overmassive relative to the stellar mass in their host systems, challenging models of early black hole seeding and growth. Multipl

Xiaoyuan Cheng, Yi He, Yiming Yang, Xiao Xue

Learning long-term behaviors in chaotic dynamical systems, such as turbulent flows and climate modelling, is challenging due to their inherent instability and unpredictability. These systems exhibit positive Lyapunov exponents, which significantly hinder accurate long-term forecasting. As a result, understanding long-term statistical behavior is far more val

M. J. Nadjafi Arani, S. Sorgun, M. Mirzargar

This study conducts a Quantitative Structure Property Relationship (QSPR) analysis to explore the correlation between the physical properties of drug molecules and their topological indices using machine learning techniques. While prior studies in drug design have focused on degree-based topological indices, this work analyzes a dataset of 166 drug molecules

Podshara Chanrungmaneekul, Yiting Chen, Joshua T. Grace, Aaron M. Dollar

Camera-to-robot (also known as eye-to-hand) calibration is a critical component of vision-based robot manipulation. Traditional marker-based methods often require human intervention for system setup. Furthermore, existing autonomous markerless calibration methods typically rely on pre-trained robot tracking models that impede their application on edge device

Moo K. Chung, Anass B. El-Yaagoubi, Anqi Qiu, Hernando Ombao

In brain network analysis using resting-state fMRI, there is growing interest in modeling higher-order interactions beyond simple pairwise connectivity via persistent homology. Despite the promise of these advanced topological tools, robust and consistently observed higher-order interactions over time remain elusive. In this study, we investigate why convent

Matei P. Coiculescu, Stan Palasek

We consider the Cauchy problem for the incompressible Navier-Stokes equations in dimension three and construct initial data in the critical space $BMO^{-1}$ from which there exist two distinct global solutions, both smooth for all $t>0$. One consequence of this construction is the sharpness of the celebrated small data global well-posedness result of Koch an

Yiming Wang, Lucy Chai, Xuan Luo, Michael Niemeyer

Recent advances in feed-forward 3D Gaussian Splatting have led to rapid improvements in efficient scene reconstruction from sparse views. However, most existing approaches construct Gaussian primitives directly aligned with the pixels in one or more of the input images. This leads to redundancies in the representation when input views overlap and constrains

Juan Sosa, Carlo Martínez

Bayesian sociality models provide a scalable and flexible alternative for network analysis, capturing degree heterogeneity through actor-specific parameters while mitigating the identifiability challenges of latent space models. This paper develops a comprehensive Bayesian inference framework, leveraging Markov chain Monte Carlo and variational inference to

Adelina Bärligea, Benedikt Poggel, Jeanette Miriam Lorenz

With rapid advances in quantum hardware, a central question is whether quantum devices with or without full error correction can outperform classical computers on practically relevant problems. Variational Quantum Algorithms (VQAs) have gained significant attention as promising candidates in this pursuit, particularly for combinatorial optimization problems.

Hyangdong Park

We are concerned with the unique existence of an axisymmetric supersonic solution with nonzero vorticity and nonzero angular momentum density for the steady Euler-Poisson system in three-dimensional divergent nozzles when prescribing the velocity, strength of electric field, and the entropy at the entrance. We first reformulate the problem via the method of

Jakub Šebesta, Karol Synoradzki, Michal Vališka, Tetiana Haidamak

Magnetic materials represent an essential ingredient for the contemporary industry. Apart from common material parameters such as magnetocrystalline anisotropy, coercivity, or saturation magnetization, magnetoelastic behavior is vital for applications serving in various devices, e.g., in acoustic actuators, transducers, or sensors providing a desirable fast

Ronghai Wu, Michael Zaiser

In recent years, the behavior of dislocations in random solid solutions has received renewed interest, and several models have been discussed where random alloys are treated as effective media containing random distributions of dilatation and compression centers. More generally speaking, the arrangement of defects in metals and alloys is always characterized

Kyle Van Gorkom, Ramya M. Anche, Christopher B. Mendillo, Jessica Gersh-Range

NASA's Habitable Worlds Observatory (HWO) concept and the 2020 Decadal Survey's recommendation to develop a large space telescope to "detect and characterize Earth-like extrasolar planets" requires new starlight suppression technologies to probe a variety of biomarkers across multiple wavelengths. Broadband absorption due to ozone dominates Earth's spectrum

Mauro Bisson, Alexandros Vasilopoulos, Massimo Bernaschi, Massimiliano Fatica

We explicitly demonstrate the universality of critical dynamics through unprecedented large-scale GPU-based simulations of two out-of-equilibrium processes, comparing the behavior of spin-$1/2$ Ising and spin-$1$ Blume-Capel models on a square lattice. In the first protocol, a completely disordered system is instantaneously brought into contact with a therma

Peter Frinchaboy, Andy Sheinis, Sam Barden, Viraja Khatu

The Maunakea Spectroscopic Explorer (MSE) ia a massively multiplexed spectroscopic survey facility that is proposed to replace the Canada-France-Hawai'i-Telescope in the 2040s. Since 2019, due to the uncertainty for new facilities on Maunakea, the project has been focused on new technology enabling greater capabilities beyond the concept design reviewed faci

Sarah A. Brands, Frank Backs, Alex de Koter, Joachim Puls

Mass loss governs the evolution of massive stars and shapes the stellar surroundings. To quantify the impact of the stellar winds we need to know the exact mass-loss rates; however, empirical constraints on the rates are hampered by limited knowledge of their small-scale wind structure or 'wind clumping'. We aim to improve empirical constraints on the mass l

S. Ferraiuolo, S. Mastrogiovanni, S. Escoffier, E. Kajfasz

Gravitational waves (GWs) from compact binary coalescences (CBCs) provide a new avenue to probe the cosmic expansion, in particular the Hubble constant $H_0$. The spectral sirens method is one of the most used techniques for GW cosmology. It consists of obtaining cosmological information from the GW luminosity distance, directly inferred from data, and the r

Anna Biggs, Aidan Herderschee

We investigate higher-point correlators in the BFSS matrix model, a non-conformal theory dual to type IIA string theory, using Witten diagrams and techniques from the amplitudes program. While the Witten diagrams are more complex than those relevant for conformal holographic theories, we find that the added complexity is minimal. As an illustration, we compu

Mojtaba Esfandiari, Pengyuan Du, Haochen Wei, Peter Gehlbach

Modeling and controlling cable-driven snake robots is a challenging problem due to nonlinear mechanical properties such as hysteresis, variable stiffness, and unknown friction between the actuation cables and the robot body. This challenge is more significant for snake robots in ophthalmic surgery applications, such as the Improved Integrated Robotic Intraoc

A. Jaradat, G. Molera Calvés, J. Edwards, S. Ellingsen

Advancements in VLBI instrumentation, driven by the geodetic community's goal of achieving positioning accuracy of 1 mm and stability of 0.1 mm/y, have led to the development of new broadband systems. Here, we assess the potential of these new capabilities for space weather monitoring. These enhanced VLBI capabilities were used to investigate interplanetary

Remi A. Chou

Information-theoretically secure Symmetric Private Information Retrieval (SPIR) is known to be infeasible over noiseless channels with a single server. Known solutions to overcome this infeasibility involve additional resources such as database replication, shared randomness, or noisy channels. In this paper, we propose an alternative approach for achieving

Chen Gong, Kecen Li, Zinan Lin, Tianhao Wang

Differentially private (DP) image synthesis aims to generate artificial images that retain the properties of sensitive images while protecting the privacy of individual images within the dataset. Despite recent advancements, we find that inconsistent--and sometimes flawed--evaluation protocols have been applied across studies. This not only impedes the under

Zijie Zhou

We prove an asymptotic for the moment of derivatives of quadratic twists of two distinct modular $L$-functions. This was previously known conditionally on GRH by the work of Ian Petrow.

Alex Foutch, Kazuma Kobayashi, Ayodeji Alajo, Dinesh Kumar

The pursuit of enhanced nuclear safety has spurred the development of accident-tolerant cladding (ATC) materials for light water reactors (LWRs). This study investigates the potential of repurposing these ATCs in advanced reactor designs, aiming to expedite material development and reduce costs. The research employs a multi-physics approach, encompassing neu

F. Javier García de Abajo, Albert Polman, Cruz I. Velasco, Mathieu Kociak

Over the past century, continuous advancements in electron microscopy have enabled the synthesis, control, and characterization of high-quality free-electron beams. These probes carry an evanescent electromagnetic field that can drive localized excitations and provide high-resolution information on material structures and their optical responses, currently r

Samah Kansab, Matthieu Hanania, Francis Bordeleau, Ali Tizghadam

DevOps integrates collaboration, automation, and continuous improvement, enhancing agility, reducing time to market, and ensuring consistent software releases. A key component of this process is GitLab's Merge Request (MR) mechanism, which streamlines code submission and review. Studies have extensively analyzed MR data and similar mechanisms like GitHub pul

Teemu Saksala, Andrew Shedlock

We show that a complete Riemannian manifold, as well as time independent smooth lower order terms appearing in a first order symmetric perturbation of a Riemannian wave operator can be uniquely recovered, up to the natural obstructions, from a local source to solution map of the respective hyperbolic initial value problem. Our proofs are based on an adaptati

Guilherme B. Xavier, Jan-Åke Larsson, Paolo Villoresi, Giuseppe Vallone

Entanglement is a key resource in many quantum information tasks. From a fundamental perspective entanglement is at the forefront of major philosophical discussions advancing our understanding of nature. An experimental scheme was proposed in 1989 by Franson that exploited the unpredictability in the generation time of a photon pair in order to produce a the

Liu Jing, Amirul Rahman

Large Vision-Language Models (LVLMs) have shown remarkable progress in various multimodal tasks, yet they often struggle with complex visual reasoning that requires multi-step inference. To address this limitation, we propose MF-SQ-LLaVA, a novel approach that enhances LVLMs by enabling implicit self-questioning through end-to-end training. Our method involv

Carlo Iazeolla, Per Sundell, Brenno Carlini Vallilo

We derive a manifestly superconformally covariant unfolded formulation of the free (2,0) tensor multiplet in six spacetime dimensions. The unfolded system consists of an abelian two-form and an infinite-dimensional chiral zero-form containing the system's curvature, matter fields, and their derivatives on-shell, realized using superoscillators. The construct

Panu Jalas

We investigate a possible category theoretical description for agent based modeling by outlining justifications for two main principles to describe the valuations in a realistic way in microeconomics: 1) It is assumed that the valuations can be expressed as a subcategory of the category of metric space so that value differences between various objects, that

Xiangyong Chen, Xiaochuan Lin

Early detection of depression from social media data offers a valuable opportunity for timely intervention. However, this task poses significant challenges, requiring both professional medical knowledge and the development of accurate and explainable models. In this paper, we propose LLM-MTD (Large Language Model for Multi-Task Depression Detection), a novel

M. Kilin, O. Tanriverdi, B. Karahan, F. Yasar

This study presents a comprehensive simulation-based optimization of gallium nitride (GaN)-based metal-semiconductor-metal (MSM) photodetectors designed for ultraviolet (UV) applications. The proposed device architecture incorporates a novel indium nitride/gallium nitride/aluminum nitride (InN/GaN/AlN) heterostructure integrated on a sapphire substrate, comb

Hamed Rahimi Nohooji, Abolfazl Zaraki, Holger Voos

This paper presents a reinforcement learning-based neuroadaptive control framework for robotic manipulators operating under deferred constraints. The proposed approach improves traditional barrier Lyapunov functions by introducing a smooth constraint enforcement mechanism that offers two key advantages: (i) it minimizes control effort in unconstrained region

Mykhaylo Khoma

The elastic scattering and resonant charge transfer integral cross sections in $\rm{H}(1s) + \rm{H^+}$ collisions are computed for the center-of-mass energy range of $10^{-10}-10$ eV. Fully quantal and semiclassical approaches are utilized in these calculations. The reliability of the semiclassical approximation for very low collision energies is discussed.

Pablo Ochoa

In this paper, we show the existence of non-trivial solutions to very general elliptic systems with critical non-linearities in the sense of embeddings in Orlicz-Sobolev spaces. This allows to consider non-linearities which do not have polynomial growth. To achieve the existence, we combine a Mountain Pass Theorem without the Palais-Smale condition with the

Tharindu Kumarage, Cameron Johnson, Jadie Adams, Lin Ai

The rapid advancement of conversational agents, particularly chatbots powered by Large Language Models (LLMs), poses a significant risk of social engineering (SE) attacks on social media platforms. SE detection in multi-turn, chat-based interactions is considerably more complex than single-instance detection due to the dynamic nature of these conversations.

Maria Teresa Chiri, Roberto Guglielmi, Gennaro Notomista

In this letter we propose an optimization-based boundary controller for traffic flow dynamics capable of achieving both stability and invariance conditions. The approach is based on the definition of Boundary Control Barrier Functionals, from which sets of invariance-preserving boundary controllers are derived. In combination with sets of stabilizing control

Parker Ewen, Hao Chen, Seth Isaacson, Joey Wilson

This paper introduces a novel approach to uncertainty quantification for radiance fields by leveraging higher-order moments of the rendering equation. Uncertainty quantification is crucial for downstream tasks including view planning and scene understanding, where safety and robustness are paramount. However, the high dimensionality and complexity of radianc

Maria Bras-Amorós

We present a new algorithm to explore or count the numerical semigroups of a given genus which uses the unleaved version of the tree of numerical semigroups. In the unleaved tree there are no leaves rather than the ones at depth equal to the genus in consideration. For exploring the unleaved tree we present a new encoding system of a numerical semigroup give

Anni Zhou, Beyah Raheem, Rishikesan Kamaleswaran, Yao Xie

Sepsis is a life-threatening syndrome with high morbidity and mortality in hospitals. Early prediction of sepsis plays a crucial role in facilitating early interventions for septic patients. However, early sepsis prediction systems with uncertainty quantification and adaptive learning are scarce. This paper proposes Sepsyn-OLCP, a novel online learning algor

Yicheng Fu, Zikui Wang, Liuxin Yang, Meiqing Huo

Quizzes play a crucial role in education by reinforcing students' understanding of key concepts and encouraging self-directed exploration. However, compiling high-quality quizzes can be challenging and require deep expertise and insight into specific subject matter. Although LLMs have greatly enhanced the efficiency of quiz generation, concerns remain regard

Metin Arik, Tarik Tok

We consider a model where the Standard Model is added to the Einstein Lagrangian together with a Jordan-Brans-Dicke(JBD) coupling. The time-dependent Higgs field has an important role in interpreting the effective gravitational constant, $G_{eff}$. This may lead to two Big Bangs, the first Big Bang characterizes the size of the universe being zero. At this B

Mark Webster, Stergios Koutsioumpas, Dan E Browne

Efficiently implementing Clifford circuits is crucial for quantum error correction and quantum algorithms. Linear reversible circuits, equivalent to circuits composed of CNOT gates, have important applications in classical computing. In this work we present methods for CNOT and general Clifford circuit synthesis which can be used to minimise either the entan

Mehmet Kirtisoglu, Ergun Yalcin

Given a functor $\varphi : \mathcal{C} \to \mathcal{D}$ between two small categories, there is a homotopy equivalence $\kappa: hocolim _{\mathcal{D}} N(\varphi /-) \to N\mathcal{C}$ where $N(\varphi/-)$ is the functor which sends every object $d$ in $\mathcal{D}$ to the nerve of the comma category $\varphi/d$. We prove that the homotopy equivalence $\kappa$

Grigorii Khvatskii, Yong Suk Lee, Corey Angst, Maria Gibbs

This paper examines the performance of Multimodal LLMs (MLLMs) in skilled production work, with a focus on welding. Using a novel data set of real-world and online weld images, annotated by a domain expert, we evaluate the performance of two state-of-the-art MLLMs in assessing weld acceptability across three contexts: RV \& Marine, Aeronautical, and Farming.

Antonio Agresti

We show that the Lagrangian flow associated with the stochastic 3D primitive equations (PEs) with non-degenerate noise is chaotic, i.e., the corresponding top Lyapunov exponent is strictly positive almost surely. This result builds on the landmark work by Bedrossian, Blumenthal, and Punshon-Smith on Lagrangian chaos in stochastic fluid mechanics. Our primary

Davide Massari

In this research note I update the associations between globular clusters and their putative galaxy progenitors determined in Massari et al. (2019), based on the kinematic measurements from the Gaia early data release 3 (eDR3, Gaia Collaboration et al. 2021). The table with the associations is available at https://www.oas.inaf.it/en/research/m2-en/carma-en/,

Basit Muhammad Imran, Jeeseop Kim, Taizoon Chunawala, Alexander Leonessa

This paper presents a novel hierarchical, safety-critical control framework that integrates distributed nonlinear model predictive controllers (DNMPCs) with control barrier functions (CBFs) to enable cooperative locomotion of multi-agent quadrupedal robots in complex environments. While NMPC-based methods are widely adopted for enforcing safety constraints a

Minheng Chen, Xiaowei Yu, Jing Zhang, Tong Chen

Understanding the organization of human brain networks has become a central focus in neuroscience, particularly in the study of functional connectivity, which plays a crucial role in diagnosing neurological disorders. Advances in functional magnetic resonance imaging and machine learning techniques have significantly improved brain network analysis. However,

Jonas Dornbusch, Emanuel Pfarr, Florin-Alexandru Vasluianu, Frank Werner

Diffusion models have garnered considerable interest in computer vision, owing both to their capacity to synthesize photorealistic images and to their proven effectiveness in image reconstruction tasks. However, existing approaches fail to efficiently balance the high visual quality of diffusion models with the low distortion achieved by previous image recon

Patricio Escalona, João Paulo Pinheiro, A. Doff, C. A. de S. Pires

We perform a systematic study of flavor-changing neutral currents (FCNCs) in the 331 model with right-handed neutrinos (331RHNs), analyzing constraints on the $Z^\prime$ boson mass from $K$-, $D$-, $B_d$-, and $B_s$-meson oscillations. By explicitly incorporating scalar sector dynamics and quark rotation ambiguities ($V_L^{u,d}$), we demonstrate that $Z^\pri

Duarte Feiteira, Oleg Lebedev

We study production of free and feebly interacting scalars during inflation using the Bogolyubov coefficient and Starobinsky stochastic approaches. While the two methods agree in the limit of infinitely long inflation, the Starobinsky approach is more suitable for studying realistic situations, where the duration of inflation is finite and the scalar field h

Antonio Ambrosone, Carmelo Evoli, Benedikt Schroer, Pasquale Blasi

The secondary/primary cosmic-ray ratios and the diffuse backgrounds of gamma rays and neutrinos provide us with complementary information about the transport of Galactic cosmic rays~(CRs). We used the recent measurement of the diffuse gamma ray background in the $\sim \rm TeV -\rm PeV$ range by LHAASO and of the very high-energy diffuse neutrino background f

Priyantha Wijayatunga

Jeffreys-Lindley paradox is a case where frequentist and Bayesian hypothesis testing methodologies contradict with each other. This has caused confusion among data analysts for selecting a methodology for their statistical inference tasks. Though the paradox goes back to mid 1930's so far there hasn't been a satisfactory resolution given for it. In this pape

Wenqi Jiang, Suvinay Subramanian, Cat Graves, Gustavo Alonso

Retrieval-augmented generation (RAG), which combines large language models (LLMs) with retrievals from external knowledge databases, is emerging as a popular approach for reliable LLM serving. However, efficient RAG serving remains an open challenge due to the rapid emergence of many RAG variants and the substantial differences in workload characteristics ac

Maham Kamran, Amirhossein Fardi, Chengyu Li, Muhammad Saif Ullah Khalid

Understanding the interplay between hydrodynamics and chemical sensing in aquatic environments is crucial for unraveling biological swimmers' navigation, foraging, and communication strategies. This study investigates the role of kinematics and morphologies of fish in dispersion and suppression of odor cues in their wake. We employ high-fidelity three-dimens

Hanchen Li, Yuhan Liu, Yihua Cheng, Kuntai Du

Across large language model (LLM) applications, we observe an emerging trend for reusing KV caches to save the prefill delays of processing repeated input texts in different LLM inputs. This has led to a broad design space, including colocating stored KV caches with (or close to) GPUs to various KV cache compression. However, a key question remains unanswere

Henryk Gzyl, Silvia Mayoral

To quantify the changes in the credit rating of a bond is an important mathematical problem for the credit rating industry. To think of the credit rating as the state a Markov chain is an interesting proposal leading to challenges in mathematical modeling. Since cumulative default rates are more readily measurable than credit migrations, a natural question i

Zhi-Yuan Wei, Daniel Malz

We introduce parallel-sequential (PS) circuits, a family of quantum circuit layouts that interpolate between brickwall and sequential circuits, which introduces control parameters governing a trade-off between the amount of entanglement and the maximum correlation range they can express. We provide numerical evidence that PS circuits can efficiently prepare

Jaroslaw Wojtun, Cezary Ziolkowski, Jan M. Kelner, Tomas Mikulasek

Millimeter wave (mmWave) technology offers high throughput but has a limited radio range, necessitating the use of directional antennas or beamforming systems such as massive MIMO. Path loss (PL) models using narrow-beam antennas are known as directional models, while those using omnidirectional antennas are referred to as omnidirectional models. To standard

N. E. Shaik, E. Fogh, B. Dalla Piazza, B. Normand

Fractionalization remains one of the most fascinating manifestations of strong interactions in quantum many-body systems. In quantum magnetism, the existence of spinons -- collective magnetic excitations that behave as quasiparticles with fractional quantum numbers -- is proven in spin chains, but the criteria for their appearance in higher dimensions remain

F. R. Ferraro, L. Chiappino, A. Bartolomei, L. Origlia

We present the scientific goals and the very first results of the Bulge Cluster Origin (BulCO) survey. This survey has been specifically designed to perform an unprecedented chemical screening of stellar systems orbiting the Milky Way bulge, with the aim to unveil their true origin. It takes advantage of the improved performances of the spectrograph CRIRES+

Muhammad Kazim, Harun Pirim, Chau Le, Trung Le

In modern energy networks, where operational efficiency and resilience are critical, this study introduces an in-depth analysis from a multiplex network perspective - defined as a network where multiple types of connections exist between the same set of nodes. Utilizing Belgium's electricity and gas networks, we construct a five-layer multiplex network to si

Yi Liao, Yongsheng Gao, Weichuan Zhang

Various Vision Transformer (ViT) models have been widely used for image recognition tasks. However, existing visual explanation methods can not display the attention flow hidden inside the inner structure of ViT models, which explains how the final attention regions are formed inside a ViT for its decision-making. In this paper, a novel visual explanation ap

Gustavo J. Turiaci, Chih-Hung Wu

We study quantum gravity corrections to the no-boundary wavefunction describing a universe with spatial topology $S^1\times S^2$. It has been suggested that quantum effects become increasingly important when the size of the circle is large relative to the sphere. In this paper, we confirm this claim by an explicit four-dimensional one-loop calculation of the

Shuo Huang, Muhammad Umair Nasir, Steven James, Julian Togelius

We present Word2Minecraft, a system that leverages large language models to generate playable game levels in Minecraft based on structured stories. The system transforms narrative elements-such as protagonist goals, antagonist challenges, and environmental settings-into game levels with both spatial and gameplay constraints. We introduce a flexible framework

Tamás Kátay

We establish a connection between two well-studied spaces of countable groups: the space of group operations and the space of marked groups. This connection shows that the two spaces are equivalent in terms of generic properties in the sense of Baire category, which allows us to translate several results from the former setting to the latter. As an applicati

Merkourios Simos, Alberto Silvio Chiappa, Alexander Mathis

How do humans move? Advances in reinforcement learning (RL) have produced impressive results in capturing human motion using physics-based humanoid control. However, torque-controlled humanoids fail to model key aspects of human motor control such as biomechanical joint constraints & non-linear and overactuated musculotendon control. We present KINESIS, a mo

Floris B. Roodenburg

We characterise the complex interpolation spaces of weighted vector-valued Sobolev spaces with and without boundary conditions on the half-space and on smooth bounded domains. The weights we consider are power weights that measure the distance to the boundary and do not necessarily belong to the class of Muckenhoupt $A_p$ weights. First, we determine the hig

Jianghao Zhang

We establish $L^p$ estimates for multilinear multipliers acting on $(n-1)$-tuples of functions on $\mathbb{R}^d$. We assume that the multiplier satisfies symbol estimates outside a linear subspace of dimension $m$. The difficulty of proving $L^p$ bounds increases with the rank $\frac{m}{d}$, and our focus is on the fractional rank case $\frac{m}{d}<\frac{n}{

Xanda C Kolesnikow, Thomas B Smith, Felix Thomsen, Abhijeet Alase

Protected superconducting qubits such as the $0$-$\pi$ qubit promise to substantially reduce physical error rates. However, a key challenge in the field is designing gates for these qubits that do not compromise their protection, or become infeasibly slow as the protection of the qubit is improved. In this work we propose a protected phase gate that is compa

Shahabedin Sagheb, Sagar Parekh, Ravi Pandya, Ye-Ji Mun

Robot actions influence the decisions of nearby humans. Here influence refers to intentional change: robots influence humans when they shift the human's behavior in a way that helps the robot complete its task. Imagine an autonomous car trying to merge; by proactively nudging into the human's lane, the robot causes human drivers to yield and provide space. I

Martin Matys, James P. Thistlewood, Mariana Kecová, Petr Valenta

We present the Virtual Beamline (VBL) application, an interactive web-based platform for visualizing high-intensity laser-matter interactions using particle-in-cell (PIC) simulations, with future potential for experimental data visualization. These interactions include ion acceleration, electron acceleration, $\gamma$-flash generation, electron-positron pair

Matt Stephenson

We show that a replicated state machine (such as a blockchain protocol) can retain liveness in a strategic setting even while facing substantial ambiguity over certain events. This is implemented by a complementary protocol called "Machine II", which generates a non-ergodic value within chosen intervals such that no limiting frequency can be observed. We sho

Priscylla Silva, Evandro Costa

Providing effective feedback is important for student learning in programming problem-solving. In this sense, Large Language Models (LLMs) have emerged as potential tools to automate feedback generation. However, their reliability and ability to identify reasoning errors in student code remain not well understood. This study evaluates the performance of four

Gloria Bertolotti, Giovanni Limatola, Paolo Torrielli, Sandro Uccirati

In this article we present a number of developments within the scheme of Local Analytic Sector Subtraction for infrared divergences in QCD. First, we extend the scheme to deal with next-to-leading-order (NLO) singularities related to massive QCD particles in the final state. Then, we document a new implementation of the NLO subtraction scheme in the MADNKLO

Sanchita Ghosh, Tanushree Roy

A Connected Autonomous Vehicle (CAV) platoon in an evolving real-world driving environment relies strongly on accurate vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication for its safe and efficient operation. However, a cyberattack on this communication network can corrupt the appropriate control actions, tamper with system measurement

Stefan Kuntz, Gerald Gerlach, Sina Fella

Rotor position feedback is required in many industrial and automotive applications, e.g. for field-oriented control of brushless motors. Traditionally, magnetic sensors, resolvers or optical encoders are used to measure the rotor position. However, advances in inductive sensing concepts enable a low-cost, high-precision position measurement principle which i

Ramon Ruiz-Dolz, John Lawrence

Natural language misinformation detection approaches have been, to date, largely dependent on sequence classification methods, producing opaque systems in which the reasons behind classification as misinformation are unclear. While an effort has been made in the area of automated fact-checking to propose explainable approaches to the problem, this is not the

Peyman Fahimi, Andrew J. Irwin, Michael Lynch

The motility skills of phytoplankton have evolved and persisted over millions of years, primarily in response to factors such as nutrient and light availability, temperature and viscosity gradients, turbulence, and predation pressure. Phytoplankton motility is broadly categorized into swimming and buoyancy regulation. Despite studies in the literature explor

Isaiah I. Tristan, Rachel A. Osten, Yuta Notsu, Adam F. Kowalski

M dwarfs are the most common type of star in the solar neighborhood, and many exhibit frequent and highly energetic flares. To better understand these events across the electromagnetic spectrum, a campaign observed AU Mic (dM1e) over 7 days from the X-ray to radio regimes. Here, we present high-time-resolution light curves from the Karl G. Jansky Very Large

Matthew J. Blacker, Alejandra Castro, Watse Sybesma, Chiara Toldo

We study quantum corrections to the Euclidean path integral of charged and static four-dimensional de Sitter (dS$_4$) black holes near extremality. These black holes admit three different extremal limits (Cold, Nariai and Ultracold) which exhibit AdS$_2 \times S^2 $, dS$_2 \times S^2 $ and $\text{Mink}_2 \times S^2$ near horizon geometries, respectively. The

Jiajun Huang, Sean Preins, Ryan Tsiao, Miguel Rodriguez

Silicon photomultipliers (SiPMs) will be used to read out all calorimeters in the ePIC experiment at the Electron-Ion Collider (EIC). A thorough characterization of the radiation damage expected for SiPMs under anticipated EIC fluences is essential for accurate simulations, detector design, and effective operational strategies. In this study, we evaluate rad

Grace Funmilayo Farayola, Akinyemi Sadeeq Akintola, Oluwole Fagbohun, Chukwuka Michael Oforgu

False arrhythmia alarms in intensive care units (ICUs) are a significant challenge, contributing to alarm fatigue and potentially compromising patient safety. Ventricular tachycardia (VT) alarms are particularly difficult to detect accurately due to their complex nature. This paper presents a machine learning approach to reduce false VT alarms using the VTaC

Hikaru Shimadzu, Takehito Utsuro, Daisuke Kitayama

In the 2023 edition of the White Paper on Information and Communications, it is estimated that the population of social networking services in Japan will exceed 100 million by 2022, and the influence of social networking services in Japan is growing significantly. In addition, marketing using SNS and research on the propagation of emotions and information on

Leonardo Henrique de Melo, Gustavo de Carvalho Bertoli, Michele Nogueira, Aldri Luiz dos Santos

Distributed denial-of-service (DDoS) attacks remain a critical threat to Internet services, causing costly disruptions. While machine learning (ML) has shown promise in DDoS detection, current solutions struggle with multi-domain environments where attacks must be detected across heterogeneous networks and organizational boundaries. This limitation severely

M Collaboration, K. Aggarwal, I. Arnquist, N. Avalos

We report on a search for sub-GeV dark matter (DM) particles interacting with electrons using the DAMIC-M prototype detector at the Modane Underground Laboratory. The data feature a significantly lower detector single $e^-$ rate (factor 50) compared to our previous search, while also accumulating a ten times larger exposure of $\sim$1.3 kg-day. DM interactio

D. Bafia, B. Abdisatarov, R. Pilipenko, Y. Lu

Trapped magnetic vortices in niobium introduce microwave losses that degrade the performance of superconducting resonators. While such losses have been extensively studied above 1~K, we report here their direct quantification in the millikelvin and low-photon regime relevant to quantum devices. Using a high-quality factor 3-D niobium cavity cooled through it

Selim Jerad, Anej Svete, Jiaoda Li, Ryan Cotterell

Understanding the expressive power of transformers has recently attracted attention, as it offers insights into their abilities and limitations. Many studies analyze unique hard attention transformers, where attention selects a single position that maximizes the attention scores. When multiple positions achieve the maximum score, either the rightmost or the

A. Ravlić, P. Schwerdtfeger, W. Nazarewicz

The superheavy nuclei push the periodic table of the elements and the chart of the nuclides to their limits, providing a unique laboratory for studies of the electron-nucleus interactions. The most important weak decay mode in known superheavy nuclei is electron capture (EC). In the standard calculations of EC, the lepton wave functions are usually considere

Amirhossein Fardi, Hamayun Farooq, Imran Akhtar, Arman Hemmati

In this paper, we investigate the hydrodynamic characteristics of harbor seal locomotion, focusing on the role of hind flippers in thrust generation and wake dynamics. Through three-dimensional numerical simulations using an immersed boundary method at Reynolds number of 3000, we analyze the impact of varying Strouhal number (St = 0.2-0.35) and propulsive wa

Antoine Delignat-Lavaud, Cédric Fournet, Kapil Vaswani, Manuel Costa

Confidential services running in hardware-protected Trusted Execution Environments (TEEs) can provide higher security assurance, but this requires custom clients and protocols to distribute, update, and verify their attestation evidence. Compared with classic Internet security, built upon universal abstractions such as domain names, origins, and certificates

A. E. Cárcamo Hernández, Ivo de Medeiros Varzielas, S. F. King, Vishnudath K. N

We present a unified model of quarks and leptons with modular $S_3$ flavour symmetry, where the two lightest family masses are naturally suppressed via a Pati-Salam version of the type I seesaw mechanism, mediated through heavier vector-like fermions. Majorana neutrino masses are further suppressed through a double seesaw mechanism. The viable parameter spac

Santiago Estupiñán-Salamanca, Oliver Pechenik

We give a new Littlewood-Richardson rule for the Schubert structure coefficients of isotropic Grassmannians, equivalently for the multiplication of $P$-Schur functions. Serrano (2010) previously gave a formula in terms of classes in his shifted plactic monoid. However, this formula is challenging to use because of the difficulty of characterizing shifted pla

Yahui Li, Pablo Sala, Frank Pollmann, Sanjay Moudgalya

Continuous symmetries lead to universal slow relaxation of correlation functions in quantum many-body systems. In this work, we study how local symmetry-breaking impurities affect the dynamics of these correlation functions using Brownian quantum circuits, which we expect to apply to generic non-integrable systems with the same symmetries. While explicitly b

Shuo Xing, Zezhou Sun, Shuangyu Xie, Kaiyuan Chen

In this paper, we introduce MapBench-the first dataset specifically designed for human-readable, pixel-based map-based outdoor navigation, curated from complex path finding scenarios. MapBench comprises over 1600 pixel space map path finding problems from 100 diverse maps. In MapBench, LVLMs generate language-based navigation instructions given a map image a

Jinchang Zhang, Guoyu Lu

Depth estimation is a core problem in robotic perception and vision tasks, but 3D reconstruction from a single image presents inherent uncertainties. Current depth estimation models primarily rely on inter-image relationships for supervised training, often overlooking the intrinsic information provided by the camera itself. We propose a method that embodies