March 2025 arXiv papers — page 191

Miftahul Jannat Mokarrama, Hamed Alhoori

In recent years, there has been a growing concern and emphasis on conducting research beyond academic or scientific research communities, benefiting society at large. A well-known approach to measuring the impact of research on society is enumerating its policy citation(s). Despite the importance of research in informing policy, there is no concrete evidence

Gabriele Bizzarri, Miranda Parisi, Mylenne Manrique, Ilaria Gianani

The description of complex systems requires a progressively larger number of parameters. However, in practice, it often happens that a small subset of parameters suffices to describe the dynamics of the system itself: these combinations are usually referred to as \textit{stiff} combinations. In turn, the remaining combinations, called \textit{sloppy}, only p

Shiyuan Zhang, Weitong Zhang, Quanquan Gu

This paper investigates energy guidance in generative modeling, where the target distribution is defined as $q(\mathbf x) \propto p(\mathbf x)\exp(-\beta \mathcal E(\mathbf x))$, with $p(\mathbf x)$ being the data distribution and $\mathcal E(\mathcal x)$ as the energy function. To comply with energy guidance, existing methods often require auxiliary procedu

Yutian Pang, Andrew Paul Kendall, Alex Porcayo, Mariah Barsotti

This work provides a feasible solution to the existing airport surface safety monitoring capabilities (i.e., Airport Surface Surveillance Capability (ASSC)), namely language AI-based voice communication understanding for collision risk assessment. The proposed framework consists of two major parts, (a) rule-enhanced Named Entity Recognition (NER); (b) surfac

Giulio Corallo, Orion Weller, Fabio Petroni, Paolo Papotti

Incorporating external knowledge in large language models (LLMs) enhances their utility across diverse applications, but existing methods have trade-offs. Retrieval-Augmented Generation (RAG) fetches evidence via similarity search, but key information may fall outside top ranked results. Long-context models can process multiple documents but are computationa

Mehmet Kardan, Bhawna Piryani, Adam Jatowt

Despite advancements in state-of-the-art models and information retrieval techniques, current systems still struggle to handle temporal information and to correctly answer detailed questions about past events. In this paper, we investigate the impact of temporal characteristics of answers in Question Answering (QA) by exploring several simple answer selectio

Songyuan Li, Jia Hu, Geyong Min, Haojun Huang

Foundation models (FMs) such as GPT-4 exhibit exceptional generative capabilities across diverse downstream tasks through fine-tuning. Split Federated Learning (SFL) facilitates privacy-preserving FM fine-tuning on resource-constrained local devices by offloading partial FM computations to edge servers, enabling device-edge synergistic fine-tuning. Practical

Joana A Kramer, Hendrik Müller, Jan Röder, Eduardo Ros

The magnetic field morphology of relativistic jets can be studied with circular polarization (CP). Recent 3D relativistic magnetohydrodynamic (RMHD) simulations coupled with radiative transfer calculations make strong predictions about the level (and morphology) of the jet's CP emission. These simulations show that the sign of CP and the electric vector posi

Zhenghao Peng, Zhizheng Liu, Bolei Zhou

Mobile robots are essential in applications such as autonomous delivery and hospitality services. Applying learning-based methods to address mobile robot tasks has gained popularity due to its robustness and generalizability. Traditional methods such as Imitation Learning (IL) and Reinforcement Learning (RL) offer adaptability but require large datasets, car

V. Ossenkopf-Okada, A. Karska, M. Benedettini, D. Colombo

Models predict that atomic carbon occurs at the surface and in the process of the formation of molecular clouds, making its fine structure transitions a diagnostic of cloud formation. We study the distribution of atomic carbon in a small inconspicuous region towards the outer Galaxy that might be representative for a large fraction of the molecular gas of th

Siyeop Yoon, Yujin Oh, Matthew Tivnan, Sifan Song

This study presents a 3D flow-matching model designed to predict the progression of the frozen region (iceball) during kidney cryoablation. Precise intraoperative guidance is critical in cryoablation to ensure complete tumor eradication while preserving adjacent healthy tissue. However, conventional methods, typically based on physics driven or diffusion bas

E. S. Costello, R. R. Ghent, A. Romero-Wolf, P. W. Gorham

We present the first full-wavelength numerical simulations of the electric field generated by cosmic ray impacts into the Moon. Billions of cosmic rays fall onto the Moon every year. Ultra-high energy cosmic ray impacts produce secondary particle cascades within the regolith and subsequent coherent, widebandwidth, linearly-polarized radio pulses by the Askar

Jacek Dziubański, Agnieszka Hejna

We extend the classical theorem of Uchiyama about constructive Fefferman-Stein decompositions of ${\rm BMO}$ functions by systems of singular integrals to the rational Dunkl setting. On $\mathbb{R}^N$ equipped with a root system $R$ and a multiplicity function $k \geq 0$, let \[ dw(\mathbf{x}) = \prod_{\alpha \in R} |\langle \alpha, \mathbf{x} \rangle|^{k(\a

Hanene F. Z. Brachemi Meftah, Wassim Hamidouche, Sid Ahmed Fezza, Olivier Deforges

The growing computational demand for deep neural networks ( DNNs) has raised concerns about their energy consumption and carbon footprint, particularly as the size and complexity of the models continue to increase. To address these challenges, energy-efficient hardware and custom accelerators have become essential. Additionally, adaptable DNN s are being dev

Sharadh Jois, Gregory M. Stephen, Nick Blumenschein, Patrick J. Taylor

Topological insulators (TIs) are intriguing materials for advanced computing applications based on spintronics because they can host robust spin effects. For instance, TIs have intrinsically large spin generation enabled by their large spin-orbit coupling. Furthermore, topological surface states (TSS) with spin-momentum locking and Dirac dispersion lead to l

João Pedro Mendonça, Krzysztof Jachymski, Yao Wang

The superradiant phenomenon, usually described by the Dicke model, is a hallmark of strong light-matter interaction. We explore how matter-matter interactions influence this phenomenon by performing ground-state simulations of Dicke-like models with both isotropic and anisotropic spin couplings. We find that Ising-type interactions produce two qualitatively

Marc Miranda, Sebastian Semper, Christian Schneider, Reiner Thomä

The use of future communication systems for sensing offers the potential for a number of new applications. In this paper, we show that leveraging user data payloads in multi-node Orthogonal Frequency Division Multiple Access (OFDMA) networks for estimating target delay and Doppler-shift parameters can yield a significant advantage in SNR and addressable band

Haoyuan Ma, Yongliang Shen, Hengwei Liu, Wenqi Zhang

Recent text-to-SQL systems powered by large language models (LLMs) have demonstrated remarkable performance in translating natural language queries into SQL. However, these systems often struggle with complex database structures and domain-specific queries, as they primarily focus on enhancing logical reasoning and SQL syntax while overlooking the critical n

Onno van Gaans, Jochen Glück, Anke Kalauch

For ordered normed vector spaces $X, Y$, we consider the space $\mathcal{L}(X,Y)$ of bounded linear operators and characterize when its cone of positive operators has non-empty interior. When this is satisfied, we give a functional representation of the closure $\mathcal{C}(X,Y)$ of the finite rank operators in $\mathcal{L}(X,Y)$. This space is particularly

Ada Defne Tur, Nicholas Meade, Xing Han Lù, Alejandra Zambrano

LLM-based agents are becoming increasingly proficient at solving web-based tasks. With this capability comes a greater risk of misuse for malicious purposes, such as posting misinformation in an online forum or selling illicit substances on a website. To evaluate these risks, we propose SafeArena, the first benchmark to focus on the deliberate misuse of web

Daniel Andrew Coulson, Martin T. Wells

Time series forecasts are widely used to inform decisions. Human decision-makers interpret these forecasts, incorporate prior experience and uncertainty about future outcomes, and then make a decision. In this paper, we propose a new machine learning problem, which we call Foreclassing, which addresses settings in which the aim is to automate human involveme

Júlia C. Anjos, Hércules S. Santana, E. V. L. de Mello

Measurements of the Hall coefficient in La$_{2-x}$Sr$_x$CuO$_4$, ranging from the undoped ($x = p = 0$) Mott insulator to overdoped compounds, exhibit a temperature dependence that offers insights into their electronic structure. We interpret these results using a model based on the theory of phase-separation (PS) dynamics, which begins at half-filled ($n =

R. Spencer Hallyburton, Miroslav Pajic

Lacking security awareness, sensor fusion in systems with multi-agent networks such as smart cities is vulnerable to attacks. To guard against recent threats, we design security-aware sensor fusion that is based on the estimates of distributions over trust. Trust estimation can be cast as a hidden Markov model, and we solve it by mapping sensor data to trust

Ali Bahri, Moslem Yazdanpanah, Mehrdad Noori, Sahar Dastani

State space models have shown significant promise in Natural Language Processing (NLP) and, more recently, computer vision. This paper introduces a new methodology leveraging Mamba and Masked Autoencoder networks for point cloud data in both supervised and self-supervised learning. We propose three key contributions to enhance Mamba's capability in processin

Yihong Tang, Wei Ma

Accurate trajectory prediction of road agents (e.g., pedestrians, vehicles) is an essential prerequisite for various intelligent systems applications, such as autonomous driving and robotic navigation. Recent research highlights the importance of environmental contexts (e.g., maps) and the "multi-modality" of trajectories, leading to increasingly complex mod

Wenchen Liu, Chang Liu, Dehui Wang, Yiyuan She

The COVID-19 pandemic has significantly challenged traditional epidemiological models due to factors such as delayed diagnosis, asymptomatic transmission, isolation-induced contact changes, and underreported mortality. In response to these complexities, this paper introduces a novel CURNDS model prioritizing compartments and transmissions based on contact le

Nikita Borisov

We study representation stability in the sense of Church, Ellenberg, and Farb \cite{FI-module} through the lens of symmetric function theory and the different symmetric function bases. We show that a sequence, $(F_n)_n$, where $F_n$ is a homogeneous symmetric function of degree $n$, has stabilizing Schur coefficients if and only if it has stabilizing monomia

Yechan Kim, Hye-Sung Lee

We propose a novel mechanism in which an external oscillatory wave modulates the mass-squared term of a scalar potential, periodically switching its sign. As a result of this "potential oscillation," the vacuum transitions between symmetry-broken and symmetry-restored phases. This repeated toggling leads to a time-varying vacuum state with rich phenomenologi

Aashaq Shah

The Phase II upgrade of the ATLAS Muon Spectrometer will involve the installation of approximately 1000 next-generation Resistive Plate Chamber (RPC) singlets. This upgrade aims to enhance detector coverage, increase hit efficiency, and improve timing precision, ultimately strengthening the precision and robustness of the muon trigger system. The upgrade is

Zuojian Pan, Zhizhong Chen, Haodong Zhang, Chuhan Deng

High-In-content InGaN quantum wells (QWs) in red light-emitting diodes (LEDs) are typically grown at low temperatures to ensure effective In incorporation. In this study, red LEDs based on bulk InGaN active region were demonstrated. The growth temperature of bulk InGaN was ~800C, which is over 100C higher than the typical growth temperature of red QWs. By in

Changchang Yin, Hong-You Chen, Wei-Lun Chao, Ping Zhang

Individual treatment effect (ITE) estimation is to evaluate the causal effects of treatment strategies on some important outcomes, which is a crucial problem in healthcare. Most existing ITE estimation methods are designed for centralized settings. However, in real-world clinical scenarios, the raw data are usually not shareable among hospitals due to the po

Jooyoung Lee, Xiaochen Zhu, Georgi Karadzhov, Tom Stafford

The proliferation of generative models has presented significant challenges in distinguishing authentic human-authored content from deepfake content. Collaborative human efforts, augmented by AI tools, present a promising solution. In this study, we explore the potential of DeepFakeDeLiBot, a deliberation-enhancing chatbot, to support groups in detecting dee

Anja Sheppard, Katherine A. Skinner

In this work, we propose the use of Ground Penetrating Radar (GPR) for rover localization on Mars. Precise pose estimation is an important task for mobile robots exploring planetary surfaces, as they operate in GPS-denied environments. Although visual odometry provides accurate localization, it is computationally expensive and can fail in dim or high-contras

Yiyang Jiang, Tobias Holder, Binghai Yan

Berry curvature-related topological phenomena have been a central topic in condensed matter physics. Yet, until recently other quantum geometric quantities such as the metric and connection received only little attention due to the relatively few effects which have been documented for them. This review gives a modern perspective how quantum geometric quantit

Kartik A. Pant, Li-Yu Lin, Worawis Sribunma, Sabine Brunswicker

We present a hierarchical safe auto-taxiing framework to enhance the automated ground operations of multiple unmanned aircraft systems (multi-UAS). The auto-taxiing problem becomes particularly challenging due to (i) unknown disturbances, such as crosswind affecting the aircraft dynamics, (ii) taxiway incursions due to unplanned obstacles, and (iii) spatiote

Ege Erdil, Andrei Potlogea, Tamay Besiroglu, Edu Roldan

Assessing the economic impacts of artificial intelligence requires integrating insights from both computer science and economics. We present the Growth and AI Transition Endogenous model (GATE), a dynamic integrated assessment model that simulates the economic effects of AI automation. GATE combines three key ingredients that have not been brought together i

Sharadh Jois, Erica Lee, Philip Li, Tsegereda Esatu

Advancements in fabrication methods have shaped new computing device technologies. Among these methods, depositing electrical contacts to the channel material is fundamental to device characterization. Novel layered and two-dimensional (2D) materials are promising for next-generation computing electronic channel materials. Direct-write printing of conductive

Mohammad Mahdi Samiei Paqaleh, Mehdi Jamalkhah, Mahdieh Soleymani Baghshah

Emergent Language (EL) focuses on the emergence of communication among artificial agents. Although symbolic communication channels more closely mirror the discrete nature of human language, learning such protocols remains fundamentally difficult due to the non-differentiability of symbol sampling. Existing approaches typically rely on high-variance gradient

Guillermo Fernandez Moroni, Fernando Chierchie, Lucas Giardino, Javier Tiffenberg

This work introduces an advanced technique optimized for detecting photons generated by charged particles, leveraging Skipper-CCD sensors. By analyzing background sources and detection efficiencies, the technique achieves strong agreement between experimental results and Cherenkov-based simulations. It also provides a robust framework for investigating secon

Giuseppe De Nittis, Santiago G. Rendel

In this work we study the topology of certain families of states of the Weyl $C^*$-algebra with finite degrees of freedom. We focus on families of pure states characterized by symmetries and a (semi-)regularity condition, and obtain precise topological descriptions through homeomorphisms with other explicit spaces. Of special importance are the families of p

Jack Hopkins, Mart Bakler, Akbir Khan

Large Language Models (LLMs) are rapidly saturating existing benchmarks, necessitating new open-ended evaluations. We introduce the Factorio Learning Environment (FLE), based on the game of Factorio, that tests agents in long-term planning, program synthesis, and resource optimization. FLE provides exponentially scaling challenges -- from basic automation to

J. P. Uchima-Tamayo, R. Angeloni, M. Jaque Arancibia, C. Goez Theran

Light pollution, a rapidly escalating anthropogenic phenomenon driven by the excessive and often inefficient use of artificial lighting, has profound implications for astronomy, ecology, and human health. This study presents the first comprehensive characterization of night sky quality in Colombia, focusing on sites of astronomical and ecological significanc

Manuel Pichardo Marcano, Anjali B. Yelikar, Karan Jani

We explore the potential of lunar-based gravitational-wave detectors to broaden the multi-messenger astrophysics landscape by detecting mergers of massive ($M_1,M_2 >1 M_\odot$) double white dwarf (WD) binaries. These systems are potential progenitors of Type Ia supernovae and could serve as independent probes of cosmic expansion. We examine two proposed lun

Marx M. M. Freitas, Stefano Buzzi, Giovanni Interdonato

This paper proposes two approaches for overcoming access points' phase misalignment effects in the downlink of cell-free massive MIMO (CF-mMIMO) systems. The first approach is based on the differential space-time block coding technique, while the second one is based on the use of differential modulation schemes. Both approaches are shown to perform exception

Stuart Benjamin, Nikolas Logan, Christopher Hansen

Integrals to calculate generalised magnetic coordinates from an input magnetic flux function asymptotically close to the separatrix are presented, and implemented in the GPEC/DCON code suite. These integrals allow characterisation of the magnetic equilibrium of a diverted tokamak, in magnetic coordinates, arbitrarily close to the last closed flux surface, av

Haoming Zhang

This short paper presents research findings on two learning-based methods for quantifying measurement uncertainties in global navigation satellite systems (GNSS). We investigate two learning strategies: offline learning for outlier prediction and online learning for noise distribution approximation, specifically applied to GNSS pseudorange observations. To d

Joseph Nakao, Gianluca Ceruti, Lukas Einkemmer

This paper presents a rank-adaptive implicit-explicit integrator for the tensor approximation of three-dimensional convection-diffusion equations. In particular, the recently developed Reduced Augmentation Implicit Low-rank (RAIL) integrator is extended from the two-dimensional matrix case to the three-dimensional tensor case. The solutions are approximated

Pierrick Lorang, Hong Lu, Matthias Scheutz

Adapting quickly to dynamic, uncertain environments-often called "open worlds"-remains a major challenge in robotics. Traditional Task and Motion Planning (TAMP) approaches struggle to cope with unforeseen changes, are data-inefficient when adapting, and do not leverage world models during learning. We address this issue with a hybrid planning and learning s

Yao Ge, Yuting Guo, Sudeshna Das, Swati Rajwal

We present HILGEN, a Hierarchically-Informed Data Generation approach that combines domain knowledge from the Unified Medical Language System (UMLS) with synthetic data generated by large language models (LLMs), specifically GPT-3.5. Our approach leverages UMLS's hierarchical structure to expand training data with related concepts, while incorporating contex

Sven Kirchner, Nils Purschke, Chengdong Wu, Muhammed Aqib Khan

The evolution of automotive technologies towards more integrated and sophisticated systems requires a shift from traditional distributed architectures to centralized vehicle architectures. This work presents a novel framework that addresses the increasing complexity of Software Defined Vehicles (SDV) through a centralized approach that optimizes software and

Adam Bredvik, Scott Richardson, Daniel Crispell

Heterogeneous collections of ground and airborne imagery can readily be used to create high-quality 3D models and novel viewpoint renderings of the observed scene. Standard photogrammetry pipelines generate models in arbitrary coordinate systems, which is problematic for applications that require georegistered models. Even for applications that do not requir

A. R. da Silva, R. Smiljanic

R-process enhanced metal-poor stars (\EuFe$\geq+0.3$ and \FeH$\leq-1.0$) are rare objects whose study can provide clues to the astrophysical sites of the rapid neutron capture process. In this study, we investigate the detailed chemical abundance patterns of two of these anomalous stars, originally identified among stars observed by the GALAH survey. Our aim

M. Bellazzini, T. Muraveva, A. Garofalo

The mass-metallicity relation (MZR) is a fundamental scale law of galaxies. It is observed to evolve with redshift in unresolved galaxies up to z>6. However, observational constraints limits our view at such early epochs to galaxies with M_* >= 10^7 M_Sun. On the other hand, in the local Universe the MZR can be traced down to the faintest end of the galaxy l

Jonathan Auerbach, Theresa M. Crimmins, David Kepplinger, Ruishan Lin

We propose a new method to adjust for the bias that occurs when an individual monitors a location and reports the status of an event. For example, a monitor may visit a plant each week and report whether the plant is in flower or not. The goal is to estimate the time the event occurred at that location. The problem is that popular estimators often incur bias

Eugene Gorsky, Soyeon Kim, Tonie Scroggin, José Simental

Skew shaped positroids (or skew shaped positroid varieties) are certain Richardson varieties in the flag variety that admit a realization as explicit subvarieties of the Grassmannian $\mathrm{Gr}(k,n)$. They are parametrized by a pair of Young diagrams $\mu \subseteq \lambda$ fitting inside a $k \times (n-k)$-rectangle. For every $a = 1, \dots, n-k$, we defi

Clément Pellet-Mary, Debarghya Dutta, Märta A. Tschudin, Patrick Siegwolf

Atomically thin van der Waals (vdW) magnets have emerged as a fascinating platform for the exploration of novel physical phenomena arising from their reduced dimensionality and exceptional material properties. Their single-crystalline nature and ultimate miniaturization position them as leading candidates for next-generation spintronic applications. Antiferr

Armin Ariamajd, Raquel López-Ríos de Castro, Andrea Volkamer

The increasing importance of Computational Science and Engineering has highlighted the need for high-quality scientific software. However, research software development is often hindered by limited funding, time, staffing, and technical resources. To address these challenges, we introduce PyPackIT, a cloud-based automation tool designed to streamline researc

Adam Brandenburger, Pierfrancesco La Mura

Any quasi-probability representation of a no-signaling system -- including quantum systems -- can be simulated via a purely classical scheme by allowing signed events and a cancellation procedure. This raises a fundamental question: What properties of the non-classical system does such a classical simulation fail to replicate? We answer by using large deviat

Ian Huang, Yanan Bao, Karen Truong, Howard Zhou

Scene generation with 3D assets presents a complex challenge, requiring both high-level semantic understanding and low-level geometric reasoning. While Multimodal Large Language Models (MLLMs) excel at semantic tasks, their application to 3D scene generation is hindered by their limited grounding on 3D geometry. In this paper, we investigate how to best work

Aysegul Ucar, Soumyadeep Ro, Sanapala Satwika, Pamarthi Yasoda Gayathri

Vision-Language Models (VLMs) have emerged as powerful tools in artificial intelli-gence, capable of integrating textual and visual data for a unified understanding of complex scenes. While models such as Florence2, built on transformer architectures, have shown promise across general tasks, their performance in object detection within unstructured or clutte

Hans Christianson, Emmanuel Schenck, Michael Taylor

We consider the stabilization problem on a manifold with boundary for a wave equation with measure-valued linear damping. For a wide class of measures, containing Dirac masses on hypersurfaces as well as measures with fractal support, we establish an abstract energy decay result.

Caroline B. Owen, Alexandria Tucker, Yonatan Kahn, Nicolás Yunes

Gravitational wave observations are a powerful tool to constrain fundamental physics. This work considers dark matter that carries charge under a dark abelian massive vector field. If such dark matter is bound inside coalescing neutron stars, the presence of the new force will modify the total energy of the binary, and the emission of dark radiation modes wi

M. Wirth, J. Hagedorn, B. Weigand, S. Kabelac

Geothermal phase change probes operate on the principle of falling film evaporation, enabling the efficient use of geothermal heat for space heating applications. Despite successful applications in research, their commercial use is limited. One of the primary reasons for this is the absence of validated models capable of accurately representing the falling f

Federico Lot, Christian Rieger

The kernel-based multi-scale method has been proven to be a powerful approximation method for scattered data approximation problems which is computationally superior to conventional kernel-based interpolation techniques. The multi-scale method is based of an hierarchy of point clouds and compactly supported radial basis functions, typically Wendland function

F. Giddings, B. C. Lemaux, B. Forrest, L. Shen

We present a study of the galaxy merger and interaction activity within the Hyperion Proto-supercluster at z~2.5 in an effort to assess the occurrence of galaxy mergers and interactions in contrast to the coeval field and their impact on the build up of stellar mass in high density environments at higher-z. For this work, we utilize data from the Charting Cl

Joseph Helfer, Eric Jovinelly, Eric Larson, Anda Tenie

This paper computes the integral Chow ring of the moduli space $M_2^{ct}$ of stable genus 2 curves of compact type. This is done by excising boundary strata from $\bar M_2$ one-by-one. During this process, we determine the Chow rings of all other open strata in $\bar M_2$ with $Z[1/2]$-coefficients.

Kelsey Kraus, Margaret Kroll

The emergence of powerful LLMs has led to a paradigm shift in Natural Language Understanding and Natural Language Generation. The properties that make LLMs so valuable for these tasks -- creativity, ability to produce fluent speech, and ability to quickly and effectively abstract information from large corpora -- also present new challenges to evaluating the

Mehdi Davoudi, Mingyu Chen, Junjie Qin

This paper studies the scheduling of a large population of non-preemptive flexible electric loads, each of which has a flexible starting time but once started will follow a fixed load shape until completion. We first formulate the scheduling problem as a mixed-integer convex program (MICP), then propose an efficient polynomial time relaxation-adjustment-roun

Mohammad Javad Najafirad, Shirantha Welikala

This paper presents a novel dissipativity-based distributed droop-free control approach for voltage regulation and current sharing in DC microgrids (MGs) comprised of an interconnected set of distributed generators (DGs), loads, and power lines. First, we describe the closed-loop DC MG as a networked system where the DGs and lines (i.e., subsystems) are inte

Marco Cirelli, Arpan Kar

Galactic weak-scale Dark Matter (DM) particles annihilating into lepton-rich channels not only produce gamma-rays via prompt radiation but also generate abundant energetic electrons and positrons, which subsequently emit through bremsstrahlung or inverse Compton scattering (collectively called `secondary-radiation photons'). While the prompt gamma-rays conce

J. Duarte, S. González-Gaitán, A. Mourão, J. Rino-Silvestre

Dust attenuation in galaxies has often been used as a proxy for the extinction of point sources, such as supernovae, even though this approach ignores fundamental differences between the two cases. We present an analysis of the impact of geometric effects and scattering within dusty media on recovered galaxy dust properties. We use SKIRT, a radiative transfe

Jeanette Miriam Lorenz, Thomas Monz, Jens Eisert, Daniel Reitzner

Architectures for quantum computing can only be scaled up when they are accompanied by suitable benchmarking techniques. The document provides a comprehensive overview of the state and recommendations for systematic benchmarking of quantum computers. Benchmarking is crucial for assessing the performance of quantum computers, including the hardware, software,

Daryl Swartzentruber, Eloise Kaizar

Regression discontinuity (RD) designs are a popular approach to estimating a treatment effect of cutoff-based interventions. Two current estimation approaches dominate the literature. One fits separate regressions on either side of the cutoff, and the other performs finite sample inference based on a local randomization assumption. Recent developments of the

Maximilian Häberle, Nadine Neumayer, Callie Clontz, Anil Seth

Omega Centauri ($\omega$ Cen) is the Milky Way's most massive globular cluster and is likely the stripped nucleus of an accreted dwarf galaxy. In this paper, we analyze $\omega$ Cen's kinematics using data from oMEGACat, a comprehensive catalog of $\omega$ Cen's central regions, including 1.4 million proper motion measurements and 300,000 spectroscopic radia

Lorenzo De Lillo, Marialuisa Frau, Alessandro Pini

We consider two four-dimensional SCFTs with gauge group $Sp(N)$: the $\mathcal{N}=4$ SYM theory and the $\mathcal{N}=2$ theory with four hypermultiplets in the fundamental representation and one hypermultiplet in the rank-2 antisymmetric representation of the gauge group. Using supersymmetric localization and by exploiting a Toda equation, we compute the int

Ehsan Ghane, Marina A. Maia, Iuri B. C. M. Rocha, Martin Fagerström

Multiscale homogenization of woven composites requires detailed micromechanical evaluations, leading to high computational costs. Data-driven surrogate models based on neural networks address this challenge but often suffer from big data requirements, limited interpretability, and poor extrapolation capabilities. This study introduces a Hierarchical Physical

Victor Sebastian Martinez Pozos, Ivan Vladimir Meza Ruiz

This paper explores the potential of abstracting complex visual information into discrete, structured symbolic sequences using self-supervised learning (SSL). Inspired by how language abstracts and organizes information to enable better reasoning and generalization, we propose a novel approach for generating symbolic representations from visual data. To lear

Wenwen Zheng, Xiaoting Fu, Yang Chen, Xuefei Chen

Individual stars located near the caustics of galaxy clusters can undergo extreme magnification when crossing micro-caustics, rendering them observable even at cosmological distances. Though most massive stars are likely reside in binary systems rather than as single star, the influence of binary star system on magnification events is severely under-explored

Hsu-Wen Chiang, Carlos G. Boiza, Mariam Bouhmadi-López

Axions have emerged as compelling candidates for describing the dark sector of the Universe. In this work, we explore quintessence models inspired by axion-like potentials as a dynamical alternative to the cosmological constant. These models naturally exhibit a tracking behaviour, reducing the need for fine-tuned initial conditions. We perform a Markov chain

Teena Gerhardt, Maximilien Péroux, W. Hermann B. Soré

We establish comparison maps between the classical algebraic $K$-theory of algebras over a field and its analogue $K^c$, an algebraic $K$-theory for coalgebras over a field. The comparison maps are compatible with the Hattori--Stallings (co)traces. We identify conditions on the algebras or coalgebras under which the comparison maps are equivalences. Notably,

Tianshu Wang, Adam Burrows

Merging our supernova code F{\sc{ornax}} with the Box3D fast-flavor neutrino oscillation formalism, we explore the effects of fast-flavor conversion (FFC) in state-of-the-art 1D and 2D core-collapse supernova simulations. We find that after a few tens of milliseconds after bounce the FFC emerges just interior to and exterior to the stalled shock wave. It doe

Davis Thuillier, Sayak Ghosh, B. J. Ramshaw, Thomas Scaffidi

Recent developments in electron hydrodynamics have demonstrated the importance of considering the full structure of the electron-electron scattering operator, which encodes a sequence of lifetimes, one for each component of the Fermi surface deformation in a multipolar expansion. In this context, the dipolar lifetime is measured by resistivity, whereas the q

William McClymont, Sandro Tacchella, Aaron Smith, Rahul Kannan

We explore the evolution of galaxy sizes at high redshift ($3 < z < 13$) using the high-resolution THESAN-ZOOM radiation-hydrodynamics simulations, focusing on the mass range of $10^6\,\mathrm{M}_{\odot} < \mathrm{M}_{\ast} < 10^{10}\,\mathrm{M}_{\odot}$. Our analysis reveals that galaxy size growth is tightly coupled to bursty star formation. Galaxies above

Prakash Gaikwad, Frederick B. Davies, Martin G. Haehnelt

We present measurements of the spatially averaged HeII photo-ionization rate ($\langle \Gamma_{\rm HeII} \rangle$), mean free path of HeII ionizing photons ($\lambda_{\rm mfp, HeII}$), and HeII fraction ($f_{\rm HeII}$) across seven redshift bins within the redshift range $2<z<4$. The measurements are obtained by comparing the observed effective optical dept

Hugo Calvo, Francesco Mignosa, Diego Rodriguez-Gomez

We explicitly compute correlation functions with the insertion of a continuous symmetry defect in bosonic field theories. To recover the expected action, the definition of the defect must be modified to include a specific contact term. This can be regarded as a singular background gauge field for the global symmetry. It can be traced to the definition of the

Tomohiro Hashizume, Felix Herbort, Joseph Tindall, Dieter Jaksch

We investigate two types of dynamical quantum phase transitions (DQPTs) in the transverse field Ising model on ensembles of Erd\H{o}s-R\'enyi networks of size $N$. These networks consist of vertices connected randomly with probability $p$ ($0<p\leq 1$). Using analytical derivations and numerical techniques, we compare the characteristics of the transitions f

Paolo Molignini

Rotating dipolar Bose-Einstein condensates exhibit rich physics due to the interplay of long-range interactions and rotation, leading to unconventional vortex structures and strongly correlated phases. While most studies rely on mean-field approaches, these fail to capture quantum correlations that become significant at high rotation speeds and strong intera

J. Lukas K. König, Kang Yang, André Grossi Fonseca, Sachin Vaidya

We classify gapped phases and characteristic nodal points of non-Hermitian band structures on two-dimensional nonorientable parameter spaces. Such spaces arise in a wide range of physical systems in the presence of nonsymmorphic parameter space symmetries. For gapped phases, we find that nonorientable spaces provide a natural setting for exploring fundamenta

Arushi Bodas, Raymond T. Co, Akshay Ghalsasi, Keisuke Harigaya

A rotation in the field space of a complex scalar field corresponds to a Bose-Einstein condensation of $U(1)$ charges. We point out that fluctuations in this rotating condensate exhibit sound-wave modes, which can be excited by cosmic perturbations and identified with axion fluctuations once the $U(1)$ charge condensate has been sufficiently diluted by cosmi

Peter J. Barnes, Dylan G. H. Barnes, Audra K. Hernandez, Sebastian Lopez

We present Data Release 6 of ThrUMMS, consisting of complete data cubes and various moments of line emission ($^{12}$CO, $^{13}$CO, C$^{18}$O) from molecular clouds, across 60$^{\circ}$$\times$2$^{\circ}$ of the Fourth Quadrant (4Q) of the Milky Way at a resolution of 72$''$ in (l,b) and 0.09 kms$^{-1}$ in V$_{LSR}$. From LTE radiative transfer analysis of t

Lars Aalsma, Sang-Eon Bak

Verlinde and Zurek (VZ) have proposed that quantum gravity fluctuations in causal diamonds lead to observable effects. In particular, they argued that in quantum gravity causal diamonds have an uncertainty in their size that scales as $\delta L \sim \sqrt{\ell_p L}$, i.e. fluctuations are enhanced from the Planck scale. In this work, we explore the origin of

Ethan O. Nadler

We study the impact of molecular (${\rm H_2}$) and atomic (HI) hydrogen cooling on the galaxy formation threshold. We calculate the fraction of dark matter (DM) halos that exceeds a critical mass required for star formation, $M_{\mathrm{crit}}(z)$, as a function of their peak mass. By convolving analytic halo mass accretion histories (MAHs) with models for $

Ben Forrest, Lu Shen, Brian C. Lemaux, Ekta Shah

We present first results and catalogs from the HST-Hyperion survey. This survey has collected 50 orbits of WFC3/F160W imaging and WFC3/G141 grism spectroscopy in the most overdense regions of the Hyperion proto-supercluster at $z\sim2.45$, which are analyzed in conjunction with the adjacent 56 orbits of WFC3/F140W imaging and WFC3/G141 grism spectroscopy fro

Martin Hoferichter, Jan Lüdtke, Luca Naterop, Massimiliano Procura

A precise evaluation of the electroweak contribution to the anomalous magnetic moment of the muon requires control over all aspects of the Standard Model, ranging from Higgs physics, over multi-loop computations for bosonic and (heavy-)fermion diagrams, to non-perturbative effects in the presence of light quarks. Currently, the dominant uncertainties arise f

Xiaoqing Sun, Stephanie O'Neil, Xuejian Shen, Mark Vogelsberger

The splashback radius $R_{\rm sp}$ is a boundary of a halo that separates infalling and accreted matter. This results in a steep drop in the density profile at $R_{\rm st}$, which is a commonly adopted proxy for $R_{\rm sp}$. Observationally, $R_{\rm st}$ can be measured through fitting the projected galaxy number density profile of the halo, but there has b

Zachary Gelles, Frans Pretorius

We numerically analyze the behavior of a charged scalar field on a fixed extremal Reissner-Nordstr\"om background. We find an extension of the Aretakis instability characterized by an accumulation of charge on the extremal event horizon. In particular, when the charge coupling to the scalar field is sufficiently large, the charge density on the horizon asymp

Cem Eröncel, Yann Gouttenoire, Ryosuke Sato, Géraldine Servant

We discuss a novel mechanism for generating dark matter from a fast-rolling scalar field, relevant for both inflation and rotating axion models, and apply it specifically to the (QCD) axion. Dark matter comes from scalar field fluctuations generated by the product of the curvature perturbation and the fast-rolling background field. These fluctuations can exp

Y. Li, S. B. Zhang, Y. P. Yang, C. W. Tsai

Fast radio bursts (FRBs) are millisecond-duration radio bursts with unidentified extra-galactic origin. Some FRBs exhibit mild magneto-ionic environmental variations, possibly attributed to plasma turbulence or binary configuration. We report an abrupt magneto-ionic variation of FRB 20220529, a repeating FRB from a disk galaxy at redshift $0.1839 \pm 0.0001$

Wen Yin, Yutaka Fujita, Yuichiro Ezoe, Yoshitaka Ishisaki

We investigate the indirect detection search of the two-body decay of dark matter particles into final states containing a photon, a process predicted in various promising dark matter models such as axion-like particles and sterile neutrinos. Recent and near-future photon detectors with a resolution $ R \equiv \lambda/\Delta\lambda = O(1000) $ are primarily

Zhuo Chen, Oriol Mayné i Comas, Zhuotao Jin, Di Luo

We present a universal theoretical framework for understanding long-context language modeling based on a bipartite mutual information scaling law that we rigorously verify in natural language. We demonstrate that bipartite mutual information captures multi-token interactions distinct from and scaling independently of conventional two-point mutual information