October 2025 arXiv papers — page 148

Rita T. Sousa, Heiko Paulheim

Knowledge graphs represent information as structured triples and serve as the backbone for a wide range of applications, including question answering, link prediction, and recommendation systems. A prominent line of research for exploring knowledge graphs involves graph embedding methods, where entities and relations are represented in low-dimensional vector

Zelin Gan, Henrique Buglia, Romulo Aparecido, Mindaugas Jarmolovičius

We present a novel closed-form model for nonlinear interference (NLI) estimation in low-dispersion O-band transmission systems. The formulation incorporates the four-wave mixing (FWM) efficiency term as well as the coherent contributions of self- and cross-phase modulation (SPM/XPM) across multiple identical spans. This extension enables accurate evaluation

Michael Crystal, Guy Goren, Scott Duke Kominers

Decentralized storage is one of the most natural applications built on blockchains and a central component of the Web3 ecosystem. Yet despite a decade of active development -- from IPFS and Filecoin to more recent entrants -- most of these storage protocols have received limited formal analysis of their incentive properties. Claims of incentive compatibility

Nathan Chen, David Yang

The purpose of this note is to show that the subvarieties of small degree inside a general hypersurface of large degree come from intersecting with linear spaces or other varieties.

Izzatjon Allayarov, Andrey B. Evlyukhin, Antonio Calà Lesina

Membrane-metasurfaces, formed by periodic arrangements of holes in a dielectric layer, are gaining attention for their easier manufacturing via subtractive techniques, unnecessity of substrates, and access to resonant near-fields. Despite their practical relevance, their theoretical description remains elusive. Here, we present a semi-analytical dipole-quadr

Zhentao Liu, Arun Das, Wen Meng, Yu-Chiao Chiu

High-resolution spatial transcriptomics (HR-ST) technologies offer unprecedented insights into tissue architecture but lack standardized frameworks for histological annotation. We present ST2HE, a cross-platform generative framework that synthesizes virtual hematoxylin and eosin (H&E) images directly from HR-ST data. ST2HE integrates nuclei morphology and sp

Jiaqi Tong, Fan Li

In many causal inference problems, multiple action variables, such as factors, mediators, or network units, often share a common causal role yet lack a natural ordering. To avoid ambiguity, the scientific interpretation of a vector of estimands should remain invariant under relabeling, an implicit principle we refer to as permutation equivariance. Permutatio

Dan Ciubotaru

We classify the unitary representations with integral infinitesimal character in Lusztig's category of unipotent representations in the case when the geometric parameter space comes from the action of a Levi subgroup on the abelian nilradical of a (maximal) parabolic subalgebra. We organise the unitary representations into microlocal Arthur packets. This is

Ssohrab Borhanian, Arianna Renzini, Philippa S. Cole, Costantino Pacilio

While the Einstein Telescope and Cosmic Explorer proposals for next-generation, ground-based detectors promise vastly improved sensitivities to gravitational-wave signals, only joint observations are expected to enable the full scientific potential of these facilities, making timing and coordination between the efforts crucial to avoid missed opportunities.

Adithya Suresh, Ramon Guerrero-Suarez, Tanmay Maiti, Shuang Liang

The scaling exponent $g$ of the quasiparticle propagator for incompressible fractional quantum Hall states in the Laughlin sequence is expected to be robust against perturbations that do not close the gap. Here we probe the topological robustness of the chiral Luttinger liquid at the boundary of the $\nu=1/3$ state by measuring the tunneling conductance betw

Maximilian Luka, Yijun Wang, Denis Uhland, Ilja Gerhardt

Magnetically induced rotation of linearly polarized light near an atomic resonance, combined with Doppler-broadened absorption windows, enables narrowband transmission of optical frequencies. An ultra-narrowband lithium vapor Faraday filter at about 671 nm is investigated experimentally and theoretically. The resulting Faraday filter transmittance is demonst

Alexander Berenstein, Nicolás Cuervo Ovalle, Isaac Goldbring

We show that every general theory \`a la Keisler with the Schr\"oder-Bernstein property is stable. This generalizes the corresponding result from classical logic due to John Goodrick. Our proof uses the classical result (generalized to the case that the instability is witnessed by an infinitary formula) together with a discretization technique introduced by

Aaron Anderson, Diego Bejarano

In continuous logic, there are plenty of examples of interesting stable metric structures. However, on the other side of the SOP line, there are only a few metric structures where order is relevant, and orders often appear in different ways. We now present a unified approach to linear and cyclic orders in continuous logic. We axiomatize theories of metric li

Aurelie Leribaux, Rafael Oyamada, Johannes De Smedt, Zahra Dasht Bozorgi

Predictive Process Monitoring (PPM) is a key task in Process Mining that aims to predict future behavior, outcomes, or performance indicators. Accurate prediction of the latter is critical for proactive decision-making. Given that processes are often resource-driven, understanding and incorporating actor behavior in forecasting is crucial. Although existing

Rafael Sfair, Tiago F. L. L. Pinheiro, Giovana Ramon, Ernesto Vieira

Binary systems host complex orbital dynamics where test particles can occupy stable regions despite strong gravitational perturbations. The sailboat region, discovered in the Pluto-Charon system, allows highly eccentric S-type orbits at intermediate distances between the two massive bodies. This region challenges traditional stability concepts by supporting

Cristóbal Corral, Borja Diez, Eleftherios Papantonopoulos

In this work, we study nonconformally Ricci-flat gravitational instantons in four-dimensional Conformal Gravity, both in vacuum and in the presence of nonlinear conformal matter. First, the one-parameter extension of the Kerr-NUT-AdS metric is analyzed. We obtain their conserved charges by using the Noether-Wald formalism. It turns out that they receive corr

Anirban Chatterjee, Aaditya Ramdas

The Maximum Mean Discrepancy (MMD) is a widely used multivariate distance metric for two-sample testing. The standard MMD test statistic has an intractable null distribution typically requiring costly resampling or permutation approaches for calibration. In this work we leverage a martingale interpretation of the estimated squared MMD to propose martingale M

Saroj Basnet, Shafkat Farabi, Tharindu Ranasinghe, Diptesh Kanoji

Recent advances in open-source vision-language models (VLMs) offer new opportunities for understanding complex and subjective multimodal phenomena such as sarcasm. In this work, we evaluate seven state-of-the-art VLMs - BLIP2, InstructBLIP, OpenFlamingo, LLaVA, PaliGemma, Gemma3, and Qwen-VL - on their ability to detect multimodal sarcasm using zero-, one-,

Shuo Chen, Zonggen Li, Xingyu Jin, Zhen Han

We reveal that Deep Research (DR) agents systematically expose safety risks: simply submitting harmful queries that a standalone LLM would reject outright can elicit detailed and dangerous reports from DR agents. Empirical analysis reveals that the advantages that make DR agents powerful unintentionally make them vulnerable: both the research role assignment

Anael Ben-Asher, Antonio I. Fernandez-Dominguez, Johannes Feist

Polaritons are usually described within single-mode cavity QED models. However, nanophotonic environments typically involve several modes that spectrally overlap and interfere, giving rise to sharp dip features such as Fano profiles in the electromagnetic spectral density. Here, we identify these features as interference-induced resonances, effective electro

Efstratios Reppas, Ali Wadi, Brendan Gould, Kyriakos G. Vamvoudakis

In this paper, we develop a framework for deception in quantum games, extending the Honey-X paradigm from classical zero-sum settings into the quantum domain. Building on a view of deception in classical games as manipulation of a player's perception of the payoff matrix, we formalize quantum deception as controlled perturbations of the payoff Hamiltonian su

Yingjia Wan, Haochen Tan, Xiao Zhu, Xinyu Zhou

Evaluating the factuality of long-form generations from Large Language Models (LLMs) remains challenging due to efficiency bottlenecks and reliability concerns. Prior efforts attempt this by decomposing text into claims, searching for evidence, and verifying claims, but suffer from critical drawbacks: (1) inefficiency due to overcomplicated pipeline componen

Sam Hawke, Eric Zhang, Jiawen Chen, Didong Li

Contrastive dimension reduction (CDR) methods aim to extract signal unique to or enriched in a treatment (foreground) group relative to a control (background) group. This setting arises in many scientific domains, such as genomics, imaging, and time series analysis, where traditional dimension reduction techniques such as Principal Component Analysis (PCA) m

Samuel Alperin

We show that the Floquet Hamiltonian of a quantum particle driven by a general time-periodic imaginary potential is exactly equivalent, at stroboscopic times, to the Hamiltonian of a free particle constrained to a curved Riemannian manifold with fixed embedding. We illustrate the construction for a sinusoidal drive and for the torus of revolution, and outlin

Mingao Yuan, Feng Yu

Random geometric graphs (RGGs) offer a powerful tool for analyzing the geometric and dependence structures in real-world networks. For example, it has been observed that RGGs are a good model for protein-protein interaction networks. In RGGs, nodes are randomly distributed over an $m$-dimensional metric space, and edges connect the nodes if and only if their

Anran Hu, Zijiu Lyu

This paper introduces a framework of Constrained Mean-Field Games (CMFGs), where each agent solves a constrained Markov decision process (CMDP). This formulation captures scenarios in which agents' strategies are subject to feasibility, safety, or regulatory restrictions, thereby extending the scope of classical mean field game (MFG) models. We first establi

Urs Spiegelhalter, Jörg K. H. Franke, Frank Hutter

Adapting language models to new tasks through continued pretraining faces a fundamental trade-off: models must learn new capabilities while avoiding catastrophic forgetting of existing knowledge. While prior work has studied synthetic data generation techniques, the optimal replay ratios for balancing task performance and knowledge retention under computatio

Igor Bulyzhenkov

The metric gyro-potential of rotating distributions creates centripetal forces that can override Newtonian attraction on the inner and near-zone orbits. Einstein's geodesics in four metric potentials predict Zeeman-like shifts of Keplerian frequencies and measurable differences in the orbital speeds of direct and retrograde circulations.

Alexander Almeida, Susan Athey, Guido Imbens, Eva Lestant

There has been a recent surge in research on causal panel data models, leading to many new estimators for average causal effects. However, researchers have paid less attention to quantifying the precision of these estimators. This paper addresses that gap by studying the problem of variance estimation in causal panel settings. We develop a unified framework

Daniel Messenger, Ben Southworth, Hans Hammer, Luis Chacon

We introduce an equation learning framework to identify a closed set of equations for moment quantities in 1D thermal radiation transport (TRT) in optically thin media. While optically thick media admits a well-known diffusive closure, the utility of moment closures in providing accurate low-dimensional surrogates for TRT in optically thin media is unclear,

Yu-Hsiang Wang, Olgica Milenkovic

Time series are ubiquitous in many applications that involve forecasting, classification and causal inference tasks, such as healthcare, finance, audio signal processing and climate sciences. Still, large, high-quality time series datasets remain scarce. Synthetic generation can address this limitation; however, current models confined either to the time or

Xu Yang, Jiayuan Zhou, Michael Pacheco, Wenhan Zhu

Driven by the advancements of Large Language Models (LLMs), LLM-powered agents are making significant improvements in software engineering tasks, yet struggle with complex, repository-level issue resolution. Existing agent-based methods have two key limitations. First, they lack of procedural knowledge (i.e., how an issue is fixed step-by-step and rationales

Dominik Schwarz

The security of Large Language Model (LLM) applications is fundamentally challenged by "form-first" attacks like prompt injection and jailbreaking, where malicious instructions are embedded within user inputs. Conventional defenses, which rely on post hoc output filtering, are often brittle and fail to address the root cause: the model's inability to disting

Samuel Lippl, Thomas McGee, Kimberly Lopez, Ziwen Pan

How do inference time and latent computations enable large language models (LLMs) to solve multi-step reasoning problems? We introduce AlgoTrace, a framework for tracing and steering algorithmic operations in the model latent space for multi-step reasoning. We operationalize primitives by clustering latent activations of the model when solving four benchmark

Yiming Liu, Yuhui Zhang, Dhruba Ghosh, Ludwig Schmidt

CLIP outperforms self-supervised models like DINO as vision encoders for vision-language models (VLMs), but it remains unclear whether this advantage stems from CLIP's language supervision or its much larger training data. To disentangle these factors, we pre-train CLIP and DINO under controlled settings -- using the same architecture, dataset, and training

Narine Kokhlikyan, Kamalika Chaudhuri, Saeed Mahloujifar

A critical aspect of analyzing and improving modern machine learning systems lies in understanding how individual training examples influence a model's predictive behavior. Estimating this influence enables critical applications, including data selection and model debugging; in particular, self-influence, which quantifies the influence of a training point on

Ben T. McDonough, Marius Lemm, Andrew Lucas

Strong disorder often has drastic consequences for quantum dynamics. This is best illustrated by the phenomenon of Anderson localization in non-interacting systems, where destructive quantum wave interference leads to the complete absence of particle and information transport over macroscopic distances. In this work, we investigate the extent to which strong

Yuyang Jiang, Binzhu Xie, Lina Xu, Xiaokang Lei

Mindfulness meditation has seen increasing applications in diverse domains as an effective practice to improve mental health. However, the standardized frameworks adopted by most applications often fail to cater to users with various psychological states and health conditions. This limitation arises primarily from the lack of personalization and adaptive con

Jin Ma, Ying Tan, Renyuan Xu

Generative AI can be framed as the problem of learning a model that maps simple reference measures into complex data distributions, and it has recently found a strong connection to the classical theory of the Schr\"odinger bridge problems (SBPs) due partly to their common nature of interpolating between prescribed marginals via entropy-regularized stochastic

Debatri Chattopadhyay, Kyle A. Rocha, Seth Gossage, Vicky Kalogera

The discovery of wide, eccentric Gaia neutron stars (NSs) in binaries with still evolving (likely main sequence) companions offers a new probe of mass transfer and pulsar recycling beyond the compact-binary regime. We model their origins and fates using population synthesis with POSYDON and detailed binary evolution with MESA, contrasting two limiting prescr

Simone Mungari, Ettore Ritacco, Pietro Sabatino

Node-level anomaly detection (NAD) is challenging due to diverse structural patterns and feature distributions. As such, NAD is a critical task with several applications which range from fraud detection, cybersecurity, to recommendation systems. We introduce Janus, a framework that jointly leverages Euclidean and Hyperbolic Graph Neural Networks to capture c

Massimo A. Picardello

We outline the development of the research group of Harmonic Analysis in Italy and the personality of its founder, Alessandro Fig\`a-Talamanca.

Simin Li, Zihao Mao, Hanxiao Li, Zonglei Jing

In cooperative Multi-Agent Reinforcement Learning (MARL), it is a common practice to tune hyperparameters in ideal simulated environments to maximize cooperative performance. However, policies tuned for cooperation often fail to maintain robustness and resilience under real-world uncertainties. Building trustworthy MARL systems requires a deep understanding

Caelin Kaplan, Alexander Warnecke, Neil Archibald

AI models are being increasingly integrated into real-world systems, raising significant concerns about their safety and security. Consequently, AI red teaming has become essential for organizations to proactively identify and address vulnerabilities before they can be exploited by adversaries. While numerous AI red teaming tools currently exist, practitione

Suryaansh Jain, Umair Z. Ahmed, Shubham Sahai, Ben Leong

New Large Language Models (LLMs) become available every few weeks, and modern application developers confronted with the unenviable task of having to decide if they should switch to a new model. While human evaluation remains the gold standard, it is costly and unscalable. The state-of-the-art approach is to use LLMs as evaluators ( LLM-as-a-judge), but this

Matěj Moravík

We consider the Szeg\H{o} reproducing kernel associated with the space of $H$-harmonic functions on the unit ball in n-dimensional space, i.e. functions that are characterized by being annihilated by the hyperbolic Laplacian. This paper derives an explicit series expansion for the reproducing kernel in terms of a triple hypergeometric function introduced of

Anna R. Barth, Navneet Singh, Stephen J. Thornton, Pranav Kakhandiki

Tuning shear thickening behavior is a longstanding problem in the field of dense suspensions. Acoustic perturbations offer a convenient way to control shear thickening in real time, opening the door to a new class of smart materials. However, complete control over shear thickening requires a quantitative description for how suspension viscosity varies under

Kristina Monsch, Joshua B. Lovell, Karl R. Stapelfeldt, Sean M. Andrews

We present high-resolution ($\lesssim 0.1''$) Hubble Space Telescope (HST)/Wide Field Camera 3 (WFC3) imaging of the near edge-on ($i{\sim}80^\circ$) protoplanetary disk IRAS 23077+6707 ("Dracula's Chivito") obtained across six broadband filters spanning $0.4-1.6\,\mu$m. These observations unveil the scattered light from this unusually large disk (${\sim}14'

Zhiyuan Wang

We show that a family of secret communication challenge games naturally define a hierarchy of emergent quasiparticle statistics in three-dimensional (3D) topological phases. The winning strategies exploit a special class of the recently proposed $R$-paraparticles to allow nonlocal secret communication between the two participating players. We first give a hi

Yumi Iwashita, Haakon Moe, Yang Cheng, Adnan Ansar

As global efforts to explore the Moon intensify, the need for high-quality 3D lunar maps becomes increasingly critical-particularly for long-distance missions such as NASA's Endurance mission concept, in which a rover aims to traverse 2,000 km across the South Pole-Aitken basin. Kaguya TC (Terrain Camera) images, though globally available at 10 m/pixel, suff

Christian M. Ireland, Georg Bollen, Scott E. Campbell, Xiangcheng Chen

The favorable energy configurations of nuclei at magic numbers of ${N}$ neutrons and ${Z}$ protons are fundamental for understanding the evolution of nuclear structure. The ${Z=50}$ (tin) isotopic chain is a frontier for such studies, with particular interest at and around the doubly-magic \textsuperscript{100}Sn isotope, for which the mass is a topic of deb

Georgios Papas

This is the second paper in a series by the author, centered on the study of values of G-functions associated to a $1$-parameter family of abelian varieties $f:\CX\rightarrow S$ and a point $s_0\in S(K)$ over some number field $K$. Here we study the case where $f:\CX\rightarrow S$ is a family of elliptic curves. Extending work of Andr\'e and Beukers, we cons

Marcus Emmanuel Barnes, Taher A. Ghaleb, Safwat Hassan

Large Language Models (LLMs) are increasingly applied to data-intensive workflows, from database querying to developer observability. Yet the effectiveness of these systems is constrained by the volume, verbosity, and noise of real-world text-rich data such as logs, telemetry, and monitoring streams. Feeding such data directly into LLMs is costly, environmen

Souradeep Mukhopadhyay, Rishabh Baral, Nimeesh Mahajan, Samhitha Harish

Large language models (LLMs) such as GPT, Gemini, and Claude often appear adept at solving classic logic puzzles--but how much genuine reasoning underlies their answers? Recent evidence suggests that these models frequently rely on memorized templates rather than reasoning from first principles. When puzzles are slightly modified, their performance collapses

Matilde Gianocca

A minimal immersion from a surface to $S^3$ can be viewed both as a critical point of the area and of the energy. Although no difference appears at first order, looking at the respective second variations unveils significant differences. It is well known that whenever the first eigenvalue satisfies $\lambda_1(\Sigma)\geq2$, the index is $\mathrm{ind}_E(\Sigm

D. Vale Cofer-Shabica, Jennifer R. DeRosa, Joseph E. Subotnik

Marcus theory is the workhorse of theoretical chemistry for predicting the rates of charge and energy transfer. Marcus theory overwhelmingly agrees with experiment -- both in terms of electron transfer and triplet energy transfer -- for the famous set of naphthalene-bridge-biphenyl and naphthalene-bridge-benzophenone systems studied by Piotrowiak, Miller, an

Miguel G. Echevarria, Raj Kishore, Samuel F. Romera

The next-to-leading order hard function for quarkonium electroproduction is calculated within the framework of transverse-momentum-dependent (TMD) factorization in the low-transverse-momentum regime. The structure of the TMD shape function in quarkonium leptoproduction is analyzed through its operator-level definition. Particular attention is given to the co

Gong Chen, Abdon Moutinho

We continue our study of scattering theory and dispersive properties for one-dimensional charge transfer models, namely linear Schr\"odinger equations with multiple moving potentials. By the discovery of a refined structure of the construction of distorted Fourier transforms adapted to the multi-potential framework, we remove the large-velocity separation as

Georgios Papas

This is the first in a series of papers aimed at studying families of G-functions associated to $1$-parameter families of abelian schemes. In particular, the construction of relations, in both the archimedean and non-archimedean settings, at values of specific interest to problems of unlikely intersections. In this first text in this series, we record what w

Yuwen Cui, Guangjing Wang, Khanh Vu, Kai Wei

The Tor network provides users with strong anonymity by routing their internet traffic through multiple relays. While Tor encrypts traffic and hides IP addresses, it remains vulnerable to traffic analysis attacks such as the website fingerprinting (WF) attack, achieving increasingly high fingerprinting accuracy even under open-world conditions. In response,

A. Kostenkov, Y. Solovyeva, E. Dedov, A. Vinokurov

Luminous Blue Variables (LBVs) are massive stars with extreme luminosities, exhibiting significant irregular photometric and spectroscopic variability. This paper is dedicated to the study of dormant LBV Var$\,$2 in the galaxy M33, which has not shown significant brightness changes for almost century and currently observed as Ofpe/WN9 star. In order to obtai

T. Asano, T. Antoja

The Gaia phase spiral is considered to work as a dynamical clock for dating past perturbations, but some of the previous studies neglected the disc's self-gravity, potentially biasing estimates of the phase spiral's excitation time. We revisit the impact of self-gravitating effects on the evolution of vertical phase spirals and quantify the bias introduced i

Akaxia Cruz, Alyson Brooks, Mariangela Lisanti, Annika H. G. Peter

Observed rotation curves of dwarf galaxies exhibit significant diversity at fixed halo mass, challenging galaxy formation within the Cold Dark Matter (CDM) model. Previous cosmological galaxy formation simulations with baryonic physics fail to reproduce the full diversity of rotation curves, suggesting either that there is a flaw in baryonic feedback models,

A. Gkini, C. Fransson, R. Lunnan, S. Schulze

We present X-shooter observations of a sample of 21 hydrogen-poor superluminous supernovae (SLSNe-I), spanning a redshift range of z=0.13-0.95, aimed at searching for shells of circumstellar material (CSM). Specifically, we focus on identifying broad Mg II absorption features that are blueshifted by several thousand kilometers per second and have previously

Nisarga Paul

Variational wavefunctions offer a practical route around the exponential complexity of many-body Hilbert spaces, but their expressive power is often sharply constrained. Matrix product states, for instance, are efficient but limited to area law entangled states. Neural quantum states (NQS) are widely believed to overcome such limitations, yet little is known

Olivia Y. Long, Peter B. Catrysse, Seunghoon Han, Shanhui Fan

The original concept of left-handed material has inspired the possibility of optical antimatter, where the effect of light propagation through a medium can be completely cancelled by its complementary medium. Despite recent progress in the development of negative-index metamaterials, losses continue to be a significant barrier to realizing optical antimatter

Arushi Bodas, Sohitri Ghosh, Roni Harnik

Qubit-based sensing platforms offer promising new directions for wave-like dark matter searches. Recent proposals demonstrate that entangled qubits can achieve quadratic scaling of the signal in the number of qubits. In this work we expand on these proposals to analyze the bandwidth and scan rate performance of entangled qubit protocols across different erro

Nathan Wycoff

In Bayesian Optimization (BO), additive assumptions can mitigate the twin difficulties of modeling and searching a complex function in high dimension. However, common acquisition functions, like the Additive Lower Confidence Bound, ignore pairwise covariances between dimensions, which we'll call \textit{bilateral uncertainty} (BU), imposing a second layer of

Afif Omar, Adam Ritz

We investigate the impact of residual annihilation from sub-GeV mass thermal relic dark matter candidates during big bang nucleosynthesis (BBN). Focusing on candidates with $p$-wave annihilation channels, we show that the hadronic injection of pions and kaons beyond freeze-out, and their subsequent interaction with protons and neutrons prior to the deuterium

Aniruddha Chakraborty, Suvodip Mukherjee

Lensing of gravitational waves (GWs) due to intervening massive astrophysical systems between the source and the observer is an inevitable consequence of the general theory of relativity, which can produce multiple GW events with overlapping sky localization error. However, the confirmed detection of such a unique astrophysical phenomenon is challenging due

Shai Zucker, Xiong Wang, Fei Lu, Inbar Seroussi

We study the convergence rate of learning pairwise interactions in single-layer attention-style models, where tokens interact through a weight matrix and a nonlinear activation function. We prove that the minimax rate is $M^{-\frac{2\beta}{2\beta+1}}$, where $M$ is the sample size and $\beta$ is the H\"older smoothness of the activation function. Importantly

Hideki Umehata, Yoichi Tamura, Yoshinobu Fudamoto, Yurina Nakazato

We present a study of the metal, dust, and molecular gas content in galaxies within the A2744-z7p9OD proto-cluster at z ~ 7.88. We focus on two galaxy groups, the Quintet and the Chain, which are covered by the ELPIS survey (The Emission-Line Protocluster Imaging Survey of the furthest overdensity beyond Pandora's Cluster Abell 2744). [C II] 158 um emission

Kyle Kremer, Newlin C. Weatherford, Philip F. Hopkins, Nicholas Z. Rui

The centers of massive elliptical galaxies exhibit a wide range in density profiles, from central cusps to resolved cores with order kiloparsec sizes. The cored ellipticals have been linked to the presence of supermassive black hole binaries that excavate their hosts' central stellar populations through three-body encounters. This connection between cores an

Kiran Adhikari

We show that the minimal query complexity for preparing $f(H)\ket{\psi_0}$ is exactly the optimal polynomial approximation degree of $f$ in $L^2(\mu)$, where $\mu$ is the spectral measure of $(H,\ket{\psi_0})$. This state-aware perspective refines the worst-case bounds, unifies Krylov/Favard approximation with quantum queries, and explains how state-dependen

Dieran Wang, Jiaru Li, Dong Lai

Exoplanetary systems hosting multiple low-mass planets are thought to have experienced dynamical instability, during which planet-planet collisions and mergers occur; these collisions can impart substantial amount of angular momentum to the merger remnants, changing the obliquities of the resulting planets significantly. In this work, we carry out a series o

Michael Nee, Lisa Randall

Supersymmetric models in singular extra dimensional spaces feature prominently in many interesting phenomenological models, including those derived from string theory. In this paper we explicitly derive the low energy theory of phenomenologically viable supersymmetric theories in five dimensions, and highlight several aspects of these models that are not obv

Francesco Crescimbeni, Xisco Jimenez-Forteza, Paolo Pani

Black hole ringdowns in extensions of General Relativity (GR) generically exhibit two distinct signatures: (1) theory-dependent shifts in the standard black-hole quasinormal modes, and (2) additional modes arising from extra fundamental fields -- such as scalar, vector, or tensor degrees of freedom -- that can also contribute to the gravitational-wave signal

Rüdiger Pakmor, Ken J. Shen, Aakash Bhat, Abinaya Swaruba Rajamuthukumar

Binary systems of two carbon-oxygen white dwarfs are one of the most promising candidates for the progenitor systems of Type Ia supernovae. Violent mergers, where the primary white dwarf ignites when the secondary white dwarf smashes onto it while being disrupted on its last orbit, were the first proposed double degenerate merger scenario that ignites dynami

Rodrigo Córdova Rosado, Andy D. Goulding, Jenny E. Greene, Nickolas Kokron

Understanding the dark matter (DM) halo environment in which galaxies that host active galactic nuclei (AGN) reside is a window into the nature of supermassive black hole (SMBH) accretion. We apply halo occupation distribution (HOD) modeling tools to interpret the angular cross-correlation functions between $1.5\times10^6$ luminous red galaxies (LRGs) and ou

W. B. Hoogendam, B. J. Shappee, J. J. Wray, B. Yang

Cometary activity from interstellar objects provides a unique window into the environs of other stellar systems. We report blue-sensitive integral field unit spectroscopy of the interstellar object 3I/ATLAS from the Keck-II-mounted Keck Cosmic Web Imager on August 24, 2025 UT. We confirm previously reported CN and Ni outgassing, and present, for the first ti

A. T. Barnes, R. Chandar, K. Kreckel, F. Belfiore

We present the PHANGS-MUSE/HST-Halpha nebulae catalogue, comprising 5177 spatially resolved nebulae across 19 nearby star-forming galaxies (< 20 Mpc), based on high-resolution Halpha imaging from HST, homogenised to a fixed 10 pc resolution and sensitivity. Combined with MUSE spectroscopy, this enables robust classification of 4882 H II regions and separatio

Sergio E. Aguilar-Gutierrez

How do we describe non-trivial bulk measurements relative to an observer (i.e. relationally) when both the observer and the system it probes may/may not evolve in time? How can we interpret this holographically; particularly for zero-energy BPS states in supersymmetric theories? We address these questions, in the $\mathcal{N}=2$ double-scaled SYK model and i

Joaquín López-Suárez, Alexios P. Polychronakos, Konstantinos Sfetsos

We derive the phase structure and thermodynamics of ferromagnets consisting of elementary magnets carrying the adjoint representation of $SU(N)$ and coupled through two-body quadratic interactions. Such systems have a continuous $SU(N)$ symmetry as well as a discrete conjugation symmetry. We uncover a rich spectrum of phases and transitions, involving a para

Sirio Belli, Letizia Bugiani, Minjung Park, J. Trevor Mendel

We present the Blue Jay survey, a Cycle-1 JWST program aimed at studying the stellar and gas content of galaxies at Cosmic Noon. The survey consists of deep spectroscopy for 153 targets observed over two pointings in the COSMOS field using the NIRSpec micro-shutter assembly (MSA). We employ the three medium-resolution gratings G140M, G235M, and G395M, with e

Hridoy Debnath, Pavel Fileviez Perez

We investigate the predictions for lepton number violating processes within the minimal theory of neutrino masses based on the spontaneous breaking of local lepton number. In this framework, the symmetry is broken at the low scale, leading to the existence of a viable dark matter candidate. The new fermions required for anomaly cancellation mediate lepton nu

Matteo Robbiati, Andrea Papaluca, Andrea Pasquale, Edoardo Pedicillo

We present Qiboml, an open-source software library for orchestrating quantum and classical components in hybrid machine learning workflows. Building on Qibo's quantum computing capabilities and integrating with popular machine learning frameworks such as TensorFlow and PyTorch, Qiboml enables the construction of quantum and hybrid models that can run on a br

Andrew D. Santarelli, Claire B. Campbell, Ebraheem Farag, Earl P. Bellinger

The origin of the first supermassive black holes (SMBHs) observed at redshifts $z\geq 9$ remains one of the most challenging open questions in astrophysics. Their rapid emergence suggests that massive ``heavy seeds'' must have formed early, possibly through the direct collapse of pristine gas clouds in the first galaxies. We present MESA-QUEST, a new framewo

Severin Lüst, Michael Nee, Lisa Randall

In this paper we derive the effective theory for a stabilized five-dimensional warped geometry, addressing several outstanding issues in this derivation. These include allowing for a non-zero 4d cosmological constant, accounting for constraints from both the UV and IR branes, and determining how the stabilized theory responds to an energy perturbation on eac

Yoshinobu Fudamoto, Yurina Nakazato, Daniel Ceverino, Luis Colina

Rest-frame optical observations with the James Webb Space Telescope (JWST) have uncovered a population of massive galaxies, exceeding $10^{10}$ solar masses, present less than a billion years after the Big Bang. The large stellar masses of these galaxies require an efficient conversion of baryons into stars, which may exceed theoretical expectations. However

M. Grayling, S. Thorp, K. S. Mandel, M. Pascale

We present BayeSN-TD, an enhanced implementation of the probabilistic type Ia supernova (SN Ia) BayeSN SED model, designed for fitting multiply-imaged, gravitationally lensed type Ia supernovae (glSNe Ia). BayeSN-TD fits for magnifications and time-delays across multiple images while marginalising over an achromatic, Gaussian process-based treatment of micro

Chengqi Duan, Kaiyue Sun, Rongyao Fang, Manyuan Zhang

Recent advances in Large Language Models (LLMs) and Vision Language Models (VLMs) have shown significant progress in mathematical reasoning, yet they still face a critical bottleneck with problems requiring visual assistance, such as drawing auxiliary lines or plotting functions to solve the problems. Most LLMs and VLMs are constrained to text-only reasoning

Takuya Nakabayashi, Navami Kairanda, Hideo Saito, Vladislav Golyanik

Event cameras offer various advantages for novel view rendering compared to synchronously operating RGB cameras, and efficient event-based techniques supporting rigid scenes have been recently demonstrated in the literature. In the case of non-rigid objects, however, existing approaches additionally require sparse RGB inputs, which can be a substantial pract

Ulrich Nierste

Meson-antimeson transitions are flavor-changing neutral current processes in which the strangeness, charm, or beauty quantum number changes by two units. In the Standard Model (SM) these transitions originate from box diagrams with two W bosons. They permit the preparation of time-dependent, oscillating quantum states which are superpositions of a meson and

Ayush Shrivastava, Sanyam Mehta, Daniel Geng, Andrew Owens

Trackers and video generators solve closely related problems: the former analyze motion, while the latter synthesize it. We show that this connection enables pretrained video diffusion models to perform zero-shot point tracking by simply prompting them to visually mark points as they move over time. We place a distinctively colored marker at the query point,

Marco Pozza, Alfonso Sorrentino

This article establishes a stochastic homogenization result for the first order Hamilton-Jacobi equation on a Riemannian manifold $M$, in the context of a stationary ergodic random environment. The setting involves a finitely generated abelian group $ \mathtt{G}$ of rank $b$ acting on $M$ by isometries in a free, totally discontinuous, and co-compact manner,

Haoran Feng, Dizhe Zhang, Xiangtai Li, Bo Du

In this work, we propose DiT360, a DiT-based framework that performs hybrid training on perspective and panoramic data for panoramic image generation. For the issues of maintaining geometric fidelity and photorealism in generation quality, we attribute the main reason to the lack of large-scale, high-quality, real-world panoramic data, where such a data-cent

Pau Batlle, Pratik Patil, Michael Stanley, Javier Ruiz Lupon

Many scientific analyses require simultaneous comparison of multiple functionals of an unknown signal at once, calling for multidimensional confidence regions with guaranteed simultaneous frequentist under structural constraints (e.g., non-negativity, shape, or physics-based). This paper unifies and extends many previous optimization-based approaches to cons

Ruiqi Xu, Arnab Seth, Itamar Kimchi

We study the honeycomb lattice with a single magnetic impurity modeled by adding imaginary next-nearest-neighbor hopping ih on a single hexagon. This Haldane defect gives a topological mass term to the gapless Dirac cones and generates chirality. For a small density of defects Neehus et al [arXiv:2405.19289] found that the system's chirality reverses at a cr

Siva Darbha, Alexey Khudorozhkov, Pedro L. S. Lopes, Fangli Liu

The dynamics of isolated quantum systems following a sudden quench plays a central role in many areas of material science, high-energy physics, and quantum chemistry. Featuring complex phenomena with implications for thermalization, non-equilibrium phase transitions, and Floquet phase engineering, such far-from-equilibrium quantum dynamics is challenging to

Armengol Gasull, Paulo Santana

We give lower bounds in terms of~$n,$ for the number of limit cycles of polynomial vector fields of degree~$n,$ having any prescribed invariant algebraic curve. By applying them when the ovals of this curve are also algebraic limit cycles we obtain a new recurrent property for the Hilbert numbers. Finally, we apply our results to two important families of mo