March 2026 arXiv papers — page 14

Lawrence Lee, John Lawless, Caroline Riggall

We demonstrate that a future precision $ee$ Higgs factory would be able to perform a spacetime-resolved test of quantum nonlocality in Higgs boson decays. In simulated $ee\rightarrow ZH \rightarrow (\mu\mu)(\tau\tau)$ events at $\sqrt{s}=240$ GeV, we reconstruct $\tau$ lepton decay vertices and measure spin correlations as a function of the spacetime interva

Álvaro Ribas, Thomas Lack, Francesco Zagaria, Enrique Macías

HD 98800 is a nearby hierarchical quadruple system comprising two binaries orbiting each other. Surprisingly, despite its $\sim$ 10 Myr age and dynamic environment, the Ba-Bb component is surrounded by a compact gas-rich disc in a polar configuration. Previous millimetre continuum observations of this disc found a low millimetre spectral index ($\alpha \sim$

Charlie Sharpe, Yonadav Barry Ginat, Thomas F. M. Spieksma, Bence Kocsis

Dense concentrations of dark matter (DM) surrounding black holes provide a compelling opportunity to probe the nature of DM. In the classic Gondolo-Silk model, the adiabatic growth of a massive black hole (MBH) in a DM cusp produces a steep density spike ($\rho \propto r^{-7/3}$), potentially inducing measurable gravitational-wave dephasings in intermediate

Francesco Ubertosi, Ewan O'Sullivan, Gerrit Schellenberger, William Forman

The role of cooling gas in triggering active galactic nucleus (AGN) feedback in the centers of galaxy groups and clusters remains a key open question. NGC 5044, the X-ray brightest galaxy group, hosts the largest known reservoir of molecular gas among cool-core groups and exhibits multiple AGN outbursts, making it an ideal system to study AGN feeding. We pre

Mingyu Li

For decades, astronomers have been searching for bright radio sources deep into the epoch of reionization (EoR). The most distant, powerful radio sources are expected to reside in heavily dust-obscured galaxies, exceedingly faint at optical and infrared wavelengths. Motivated by this, I systematically cross-match radio and JWST source catalogs in the COSMOS

Maolan Yang, Suoqing Ji, Robert Feldmann, Feng Yuan

We investigate the impact of galaxy mergers on the circumgalactic medium (CGM) using the FIREbox cosmological hydrodynamic simulation. By comparing matched samples of merging and isolated galaxies with stellar masses $M_\star \sim 10^{10}$--$10^{11} M_{\odot}$ at $z=0$ and mass ratio of merging galaxies larger than $1:10$, we find that mergers significantly

Dejan Gajic

This is the second part of a series of papers deriving the precise, late-time behaviour and (in)stability properties of charged scalar fields on near-extremal Reissner--Nordstr\"om spacetimes via energy estimates. In this paper, we use purely physical-space based methods to establish the precise late-time behaviour of solutions to the charged scalar field eq

James M. Cline, Gonzalo Herrera, Jean-Samuel Roux

Active neutrinos in standard cosmology were ruled out as a dark matter candidate in the 1980's. The reason is twofold: they are too light to account for the observed energy density of dark matter in the Universe, and their relativistic nature would spoil structure formation. In this note we suggest that an enhanced density of cold Standard Model active neutr

Haiyue Song, Masao Utiyama

Continual pre-training is widely used to adapt LLMs to target languages and domains, yet the mixture ratio of training data remains a sensitive hyperparameter that is expensive to tune: they must be fixed before training begins, and a suboptimal choice can waste weeks of compute. In this work, we propose OptiMer, which decouples ratio selection from training

T. J. Hutchins, D. I. Jones

Gravitational waves may set the spin frequencies of neutron stars in low-mass X-ray binaries (LMXBs). One mechanism for facilitating such emission is the formation of a mass asymmetry - or 'mountain' - supported by elastic strains driven by thermal gradients. Most studies have focused either on the origin of the elastic strains or the temperature asymmetry i

Alexandre Jeanneau, Johan Richard, Nicolas F. Bouché, Davor Krajnović

In a series of papers on lensed kinematics, we seek to combine the sensitivity of 3D forward modelling to low signal-to-noise ratio outskirts with the enhanced spatial resolution of cluster lensing. In this first paper, we (i) present and validate our methodology, which directly constrains the source parameters by incorporating lensing deflections into the $

Damiano F. G. Fiorillo, Georg G. Raffelt

Dense neutrino plasmas can develop instabilities that drive collisionless flavor exchange, equivalent to the emission of flavomons, the quanta of flavor waves. We treat these waves, for the first time, as independent linear degrees of freedom and develop a quasi-linear theory (QLT), including backreaction on the neutrino distribution and nonresonant neutrino

David Poland, Gordon Rogelberg

Correlation functions of CFT operators with infinite scaling dimension are rich, multifaceted objects that describe physics ranging across classical holography, black hole dynamics, and flat-space scattering amplitudes. In this work, we provide a rigorous framework for characterizing the space of four-point functions of identical operators with infinite dime

Gilad Kishony, Austin Fowler

Syndrome extraction in the planar color code is complicated by high weight stabilizers and hook errors that can reduce the circuit-level distance. With a single auxiliary qubit per plaquette, any spatially uniform circuit halves the circuit-level distance. We propose a single-auxiliary syndrome extraction circuit with color-dependent gate schedules that avoi

Walter Arata, Stefano Liberati, Giulio Neri

Black hole thermodynamics in Lorentz-violating gravity is subtle because different excitations propagate at different speeds and hence identify different causal horizons. We revisit Einstein--AEther gravity using the covariant phase space formalism with boundaries and derive a consistent first law for stationary black holes. For a mode of propagation speed $

Kevin K. Hardegree-Ullman, Melanie Swain, Jessie L. Christiansen, Emily A. Gilbert

The TESS Input Catalog (TIC) was built on Gaia Data Release 2 (DR2). To date, there has not been an update to the TIC to incorporate Gaia Data Release 3 (DR3) IDs. In this Research Note, we outline how we cross-matched the TIC with Gaia DR3 IDs, its immediate applications to exoplanet research, and lessons learned when dealing with such large data sets. A fu

Christopher Ekman, Emil J. Bergholtz, Paolo Molignini

In one dimension, strongly correlated gapless systems are highly constrained due to conformal invariance, leading to the decoupling of low energy degrees of freedom corresponding to different symmetry sectors. The most familiar example of this is spin-charge separation. Here, we extend this mechanism to the non-Hermitian realm by demonstrating that skin effe

DBM Collaboration, David Komanek, Vaclav Pavlík, Santiago Jimenez

Modern numerical models are increasingly complex, opaque, and computationally expensive, yet frequently fail to predict even qualitative features of observed phenomena. We propose a new paradigm, Declarative Bespoke Modelling, in which the modeller explicitly declares the relationship between model inputs and outputs. We demonstrate that this approach achiev

Zimu Zhang, Yucheng Zhang, Xiyan Xu, Ziyin Wang

Synthesizing human motion has advanced rapidly, yet realistic hand motion and bimanual interaction remain underexplored. Whole-body models often miss the fine-grained cues that drive dexterous behavior, finger articulation, contact timing, and inter-hand coordination, and existing resources lack high-fidelity bimanual sequences that capture nuanced finger dy

Jack Cook, Hyemin S. Lee, Kathryn Le, Junxian Guo

NVFP4 has grown increasingly popular as a 4-bit format for quantizing large language models due to its hardware support and its ability to retain useful information with relatively few bits per parameter. However, the format is not without limitations: recent work has shown that NVFP4 suffers from its error distribution, resulting in large amounts of quantiz

Ryan Babbush, Adam Zalcman, Craig Gidney, Michael Broughton

This whitepaper seeks to elucidate implications that the capabilities of developing quantum architectures have on blockchain vulnerabilities and mitigation strategies. First, we provide new resource estimates for breaking the 256-bit Elliptic Curve Discrete Logarithm Problem, the core of modern blockchain cryptography. We demonstrate that Shor's algorithm fo

N Alex Cayco-Gajic, Arthur Pellegrino

Similarity measures are widely used to interpret the representational geometries used by neural networks to solve tasks. Yet, because existing methods compare the extrinsic geometry of representations in state space, rather than their intrinsic geometry, they may fail to capture subtle yet crucial distinctions between fundamentally different neural network s

Lorenza Prospero, Orest Kupyn, Ostap Viniavskyi, João F. Henriques

Acquiring labeled datasets for 3D human mesh estimation is challenging due to depth ambiguities and the inherent difficulty of annotating 3D geometry from monocular images. Existing datasets are either real, with manually annotated 3D geometry and limited scale, or synthetic, rendered from 3D engines that provide precise labels but suffer from limited photor

Yuqi Zhou, Sunhao Dai, Changle Qu, Liang Pang

Information retrieval (IR) systems have traditionally been designed and trained for human users, with learning-to-rank methods relying heavily on large-scale human interaction logs such as clicks and dwell time. With the rapid emergence of large language model (LLM) powered search agents, however, retrieval is increasingly consumed by agents rather than huma

Shi-Fan Chen, Joseph DeRose, Mikhail M. Ivanov, Oliver H. E. Philcox

Cosmic shear is a powerful probe of cosmological distances, matter abundance and clustering in the low-redshift Universe. Cosmological parameter extraction from cosmic shear data is limited by our understanding of baryonic astrophysics, which severely restricts the range of scales used in such analyses. We show that the remaining scales are largely perturbat

Patrick Rim, Kevin Harris, Braden Copple, Shangchen Han

Accurate 3D understanding of human hands and objects during manipulation remains a significant challenge for egocentric computer vision. Existing hand-object interaction datasets are predominantly captured in controlled studio settings, which limits both environmental diversity and the ability of models trained on such data to generalize to real-world scenar

Astghik Hakobyan, Amaras Nazarians, Aditya Gahlawat, Naira Hovakimyan

Safe operation of autonomous systems requires robustness to both model uncertainty and uncertainty in the environment. We propose DRP-$\mathcal{L}_1$AC, a hierarchical framework for stochastic nonlinear systems that integrates distributionally robust model predictive control (DR-MPC) with $\mathcal{L}_1$-adaptive control. The key idea is to use the $\mathcal

Derong Jin, Xiyi Chen, Ming C. Lin, Ruohan Gao

Tremendous progress in visual scene generation now turns a single image into an explorable 3D world, yet immersion remains incomplete without sound. We introduce Image2AVScene, the task of generating a 3D audio-visual scene from a single image, and present SonoWorld, the first framework to tackle this challenge. From one image, our pipeline outpaints a 360{\

Dinesh Kumar, Jeffrey Donatelli

Model-Based Iterative Reconstruction (MBIR) is important because direct methods, such as Filtered Back-Projection (FBP) can introduce significant noise and artifacts in sparse-angle tomography, especially for time-evolving samples. Although MBIR produces high-quality reconstructions through prior-informed optimization, its computational cost has traditionall

Minh-Thu Do, Quynh-Chau Le-Tran, Duc-Duy Nguyen-Mai, Thien-Trang Nguyen

The Four Books have shaped East Asian intellectual traditions, yet their multi-layered interpretive complexity limits their accessibility in the digital age. While traditional bilingual commentaries provide a vital pedagogical bridge, computational frameworks are needed to preserve and explore this wisdom. This paper bridges AI and classical philosophy by in

Yaozhi Du, Jing Shuang Li

This paper provides a novel approach for finding sparse state-space realizations of linear systems (e.g., controllers). Sparse controllers are commonly used in distributed control, where a controller is synthesized with some sparsity penalty. Here, motivated by a modeling problem in sensorimotor neuroscience, we study a complementary question: given a linear

Giuseppe Aceto, Valerio Persico, Antonio Pescapè

This paper analyzes the Internet shutdown that occurred in Iran in January 2026 in the context of protests, focusing on its impact on the country's digital communication infrastructure and on information access and control dynamics. The scale, complexity, and nation-state nature of the event motivate a comprehensive investigation that goes beyond isolated re

Wojciech J. Jankowski, Giandomenico Palumbo, Robert-Jan Slager

We report on a universal topological dichroism of chiral three-dimensional systems in response to the chirality of light. We show that chiral topological invariants result in integer-quantized dichroic excitation rate differences. Moreover, we demonstrate that such topological effects arise more generally from coupling optical chirality to higher tensor Berr

Aur Shalev Merin

For three decades online recurrent learning has been assumed to require propagating a Jacobian tensor through the network's dynamics at $O(n^4)$ per step. We show it doesn't. Dropping the propagation entirely ($d=0$, $O(n^2)$ memory) matches full RTRL within CI on held-out BCI cross-session drift (TOST equivalent within $\pm 3$ pp at $n=20$, Adam, float64),

Mats Gustafsson, Yaniv Brick

The number of spatial degrees of freedom (NDoF) and channel strength in antenna systems are examined within a geometric framework. Starting from a correlation-operator representation of the channel between transmitter and receiver regions, we analyze the associated eigenspectrum and relate the NDoF to its spectral transition (corner). We compare the spectrum

Carmen Embil Villagra, Fiona McCarthy, Antón Baleato Lizancos, Blake D. Sherwin

The kSZ effect has recently emerged as a powerful probe for precision cosmology through its ability to reconstruct the large-scale velocity field. In particular, the kSZ-reconstructed velocity-galaxy cross-correlation is sensitive to signatures of primordial non-Gaussianity through its imprint on the galaxy bias. The kSZ velocity reconstruction is performed

Finn Bartsch, Ariyan Javanpeykar

We construct the first weakly special surfaces that are not Campana-special, including the complement of the plane curve $x^2y^3 = 1$ in $\mathbb{A}^2$. We prove that the set of $\mathcal{O}_{K,S}$-integral points on this surface is non-dense for every number field $K$ and finite set $S$ of finite places of $K$ if and only if Campana's Orbifold Mordell conje

Vitória Barin Pacela, Shruti Joshi, Isabela Camacho, Simon Lacoste-Julien

The linear representation hypothesis states that neural network activations encode high-level concepts as linear mixtures. However, under superposition, this encoding is a projection from a higher-dimensional concept space into a lower-dimensional activation space, and a linear decision boundary in the concept space need not remain linear after projection. I

Liliang Ren, Yang Liu, Yelong Shen, Weizhu Chen

Scaling laws for large language models depend critically on the optimizer and parameterization. Existing hyperparameter transfer laws are mainly developed for first-order optimizers, and they do not structurally prevent training instability at scale. Recent hypersphere optimization methods constrain weight matrices to a fixed-norm hypersphere, offering a pro

Vipul Bairathi, Kishora Nayak

The directed flow ($v_1$) of identified hadrons ($\pi^{\pm}, K^{\pm}, p, \bar{p}, \phi, \Lambda$, and $\bar{\Lambda}$) is studied in symmetric nuclear collisions (O+O, Cu+Cu, Ru+Ru, Au+Au, and U+U) at $\sqrt{s_{NN}} = 200$ GeV using the string-melting version of a multiphase transport model with improved quark coalescence. The mid-rapidity $v_1$-slope ($dv_1

Fiorenzo Stoppa, Stephen J. Smartt

We present SNID-SAGE (SuperNova IDentification-Spectral Analysis and Guided Exploration), a framework for supernova spectral classification with both a fully interactive graphical interface and a scriptable command-line pipeline for large-scale processing. The pipeline combines deterministic spectral preprocessing, FFT-based cross-correlation against a curat

Yichi Zhang, Weihao Yuan, Yizhuo Zhang, Xidong Zhang

Vision-Language-Action (VLA) models improve action generation by conditioning policies on rich vision-language information. However, current auto-regressive policies are constrained by three bottlenecks: (1) architectural bias drives models to overlook visual details, (2) an excessive number of visual tokens makes attention difficult to focus on the correct

Meitong Liu, Christopher Jung, Rui Li, Xue Feng

In transfer learning, the learner leverages auxiliary data to improve generalization on a main task. However, the precise theoretical understanding of when and how auxiliary data help remains incomplete. We provide new insights on this issue in two canonical linear settings: ordinary least squares regression and under-parameterized linear neural networks. Fo

Varun Sivashankar

We prove a general upper bound on the $k$-th adjacency eigenvalue of a graph. For $k\ge 2$, we show that \[ \lambda_k(G)\le \frac{(k-2)\sqrt{k+1}+2}{2k(k-1)}\,n-1 \] for every graph $G$ on $n$ vertices. We build on a recent approach that addresses the case $k=3$ and generalize the upper bound for all $k \geq 3$ by using the positivity of Gegenbauer polynomia

Cesar Montaner, Saúl Fenollosa, Andres Ortega, Hugo Beltrán

This paper introduces a methodology to calibrate Radio-Frequency Digital Twins (RF-DTs) for Integrated Sensing and Communication (ISAC) in dynamic wireless environments. The approach leverages high-resolution ray tracing in combination with wideband channel sounding to ensure consistency between simulated and measured propagation. The methodology is validate

Oliver Aleksander Larsen, Mahyar T. Moghaddam

AI-augmented ecosystems (interconnected systems where multiple AI components interact through shared data and infrastructure) are becoming the architectural norm for smart cities, autonomous fleets, and intelligent platforms. Yet the architecture documentation frameworks practitioners rely on, arc42 and the C4 model, were designed for deterministic software

Lucas D'Alimonte, Piet Lammers

We consider three models of statistical mechanics: the classical XY model in arbitrary dimension, the lattice Coulomb gas in dimension two, and the square well model in arbitrary dimension. For each of these three models, we prove that the free energy is analytic in the disordered regime (the square well model is disordered at any positive temperature). In o

Ikechukwu Uchendu, Swati Goel, Karly Hou, Ebrahim Songhori

We propose using Vision-Language Models (VLMs) for macro placement in chip floorplanning, a complex optimization task that has recently shown promising advancements through machine learning methods. Because human designers rely heavily on spatial reasoning to arrange components on the chip canvas, we hypothesize that VLMs with strong visual reasoning abiliti

Alan Yu, Yun Chang, Christopher Xie, Luca Carlone

Robotic mapping systems typically approach building metric-semantic scene representations from the robot's own sensors and cameras. However, these "first person" maps inherit the robot's own limitations due to its embodiment or skillset, which may leave many aspects of the environment unexplored. For example, the robot might not be able to open drawers or ac

Oliver Aleksander Larsen, Mahyar T. Moghaddam

Modern distributed systems integrate heterogeneous services, REST APIs with different schema versions, GraphQL endpoints, and IoT devices with proprietary payloads that suffer from persistent schema mismatches. Traditional static adapters require manual coding for every schema pair and cannot handle novel combinations at runtime. We present SAGAI-MID, a Fast

Alexander Kaltashov, Safa Jamali

Multicomponent gel systems have garnered much interest due to their compelling mechanical properties in the past decade. Yet, some mechanisms associated with multicomponent gels, such as sequential gelation, have been explored primarily in the context of chemical nonreversible polymeric and protein gels than in physical reversible colloidal ones. In this stu

Tushin Mallick, Ashish Kundu, Ramana Kompella

The advent of quantum computing poses significant threats to classical public-key cryptographic primitives such as RSA and elliptic-curve cryptography. As many critical network and security protocols depend on these primitives for key exchange and authentication, there is an urgent need to understand their quantum vulnerability and assess the progress made t

Oliver Aleksander Larsen, Rasmus Thorsen Larsen, Mahyar T. Moghaddam

Today's internet concentrates identity, payments, communication, and content hosting under a small number of corporate intermediaries, creating single points of failure, enabling censorship, and extracting economic rent from participants. We present BitSov, an architectural framework for sovereign internet infrastructure that composes existing decentralized

Yuma Ichikawa, Keiji Kimura, Akihiro Yoshida, Yudai Fujimoto

Deploying foundation models is increasingly constrained by memory footprint, latency, and hardware costs. Post-training compression can mitigate these bottlenecks by reducing the precision of model parameters without significantly degrading performance; however, its practical implementation remains challenging as practitioners navigate a fragmented landscape

Crescenza Calculli, Serena Arima, Alessio Pollice, Nunziata Ribecco

Violence Against Women (VAW) is a widespread issue deeply rooted in social and cultural structures. Affecting women of all ages and backgrounds, VAW is often underreported due to stigma and victim-blaming. This study explores young people's perceptions of VAW in the Apulia region (Southern Italy), using a local survey inspired by a National framework on gend

Bartłomiej Dudek, Nick Fischer, Geri Gokaj, Ce Jin

We revisit the complexity of verifying basic identities, such as associativity and distributivity, on a given finite algebraic structure. In particular, while Rajagopalan and Schulman (FOCS'96, SICOMP'00) gave a surprising randomized algorithm to verify associativity of an operation $\odot: S\times S\to S$ in optimal time $O(|S|^2)$, they left the open probl

Fei Wang, Xuanxi Cai, Xiao Tang, Jinxi Lu

Floquet engineering provides a powerful pathway for creating non-equilibrium phases of matter with tailored electronic structures and properties through time-periodic driving. As the original theoretical prototype, graphene established the framework in which the Floquet topological insulator with light-induced anomalous Hall effect was proposed. However, the

Fei Wang, Xuanxi Cai, Wanying Chen, Jinxi Lu

Floquet engineering provides an emerging pathway for tailoring the electronic states of quantum materials through time-periodic drive. A critical step along this direction is achieving light-induced modifications of the dynamical electronic structure, such as avoided-crossing gap at the Floquet Brillouin zone boundary, via efficient coupling of electrons wit

Cullen Gantenberg, David B. Kaplan

While chiral perturbation theory for mesons is characterized by a momentum expansion in $Q/\Lambda_\chi$ with $\Lambda_\chi \sim 1$ GeV, existing formulations of effective theory for nucleon-nucleon scattering deviate from data at $Q\sim 300$ MeV or lower. We offer heuristic evidence that unsuspected nonanalytic structure exists in the complex momentum plane

Sofiane Azzouz, Pierre-André Vuissoz, Yves Laprie

Articulatory-to-acoustic inversion strongly depends on the type of data used. While most previous studies rely on EMA, which is limited by the number of sensors and restricted to accessible articulators, we propose an approach aiming at a complete inversion of the vocal tract, from the glottis to the lips. To this end, we used approximately 3.5 hours of RT-M

Rui Wen, Sakura Schafer-Nameki

The classification of phases using categorical symmetries has greatly expanded the landscape of gapped and gapless phases. So far, however, these developments have largely been restricted to phases with unitary (higher-)categorical symmetries over $\mathbb{C}$. In this work, we incorporate anti-unitary symmetries, such as time-reversal symmetry $\mathbb{Z}_2

Zidi Tao, A. Agung Julius, John T Wen

Sleep is vital for maintaining cognitive function, facilitating metabolic waste removal, and supporting memory consolidation. However, modern societal demands, particularly shift work, often disrupt natural sleep patterns. This can induce excessive sleepiness among shift workers in critical sectors such as healthcare and transportation and increase the risk

Yash Savani, Branislav Kveton, Yuchen Liu, Yilin Wang

Flow-GRPO successfully applies reinforcement learning to flow models, but uses uniform credit assignment across all steps. This ignores the temporal structure of diffusion generation: early steps determine composition and content (low-frequency structure), while late steps resolve details and textures (high-frequency details). Moreover, assigning uniform cre

Ashwini Dasare, Nirmesh Shah, Ashishkumar Gudmalwar, Pankaj Wasnik

Evaluating AI generated dubbed content is inherently multi-dimensional, shaped by synchronization, intelligibility, speaker consistency, emotional alignment, and semantic context. Human Mean Opinion Scores (MOS) remain the gold standard but are costly and impractical at scale. We present a hierarchical multimodal architecture for perceptually meaningful dubb

Anthony Bloch, Amir Sagiv, Stefan Steinerberger

We study dispersive decay for non-autonomous Hamiltonian systems. While the general theory for dispersion in such non-autonomous systems is largely open, it was shown \cite{kraisler2025time} that there exists a time-periodically forced one-dimensional Dirac equation with unusually slow dispersive decay rate of $t^{-1/5}$. It is to be expected that such behav

Kailai Feng, Yuxiang Wei, Bo Chen, Yang Pan

Diffusion models have made significant progress in both text-to-image (T2I) generation and text-guided image editing. However, these models are typically built with billions of parameters, leading to high latency and increased deployment challenges. While on-device diffusion models improve efficiency, they largely focus on T2I generation and lack support for

Xiangyu Chen, Qiang Lei

Quantum coherence, as a direct manifestation of the quantum superposition principle, is a crucial resource in quantum information processing. Block coherence resource theory generalizes the traditional coherence framework by defining coherence via a set of orthogonal projectors. Within this framework, we investigates the construction and comparison of block

Qiang Ma, Qingjie Meng, Yicheng Wu, Shuo Wang

The human heart is a sophisticated system composed of four cardiac chambers with distinct shapes, which function in a coordinated manner. Existing shape models of the heart mainly focus on the ventricular chambers and they are derived from relatively small datasets. Here, we present a spatio-temporal (3D+t) statistical shape model of all four cardiac chamber

Shubham Kumar Goswami, Dapse Vidyesh, Konduri Aditya

The scalability of time-dependent partial differential equation (PDE) solvers based on the discontinuous Galerkin (DG) method is increasingly limited by data communication and synchronization requirements across processing elements (PEs) at extreme scales. To address these challenges, asynchronous computing approaches that relax communication and synchroniza

Abdullah Azhar, Uneeb Kamal, Wajid Ali, Saad Gillani

This paper presents the design and physical implementation of UET-RVMCU, a lightweight RISC-V microcontroller derived from the UETRV-PCore. Aimed at creating an accessible and flexible open-source RISC-V-based microcontroller, UET-RVMCU simplifies the application-class UETRV-PCore by reducing pipeline stages, removing MMU functionality, and integrating GPIO

Soutrik Mukherjee, Sangwhan Cha

This paper presents the design and evaluation of a GPU-accelerated inference pipeline for transformer models using NVIDIA TensorRT with mixed-precision optimization. We evaluate BERT-base (110M parameters) and GPT-2 (124M parameters) across batch sizes from 1 to 32 and sequence lengths from 32 to 512. The system achieves up to 64.4x speedup over CPU baseline

Nils Margenberg, Carolin Mehlmann

Fully implicit tensor-product space-time discretizations of time-dependent $(p,\delta)$-Navier-Stokes models yield, on each time step, large nonlinear monolithic saddle-point systems. In the shear-thinning regime $1<p<2$, especially as $p\downarrow 1$ and $\delta\downarrow 0$, the decisive difficulty is the constitutive tangent: its ill-conditioning impairs

Nuno Braz, Miguel Correia, Diogo Poças

Decentralized Autonomous Organizations (DAOs) increasingly delegate decisions to small committees whose members hold two independent kinds of private information: idiosyncratic preferences over alternatives (what they want) and beliefs about which alternative best serves the organization (what they know). Members have no reason to reveal what they know unles

Thomas D. MacDonald, Hannah S. Parrilla, Jayson R. Vavrek

Recent work by Vavrek et al. (2025) showed that machine learning methods can be used to exploit spatial patterns of performance variations within the highly-segmented H3D M400 gamma spectrometer to improve an overall spectroscopic performance metric. That work also introduced the spectre-ml software, which tests various greedy, heuristic, random, and machine

Kyprianos-Iason Prodromidis, Allan Sly

In this paper, we consider the Ising model on random $d$-regular graphs (with $d\ge3$) and Erd\"os-R\'enyi graphs $G(n,d/n)$ (with $d>1$) at the critical temperature. We prove that the \textit{magnetization}, i.e.\ the sum of the spins of a configuration, is typically of order $n^{3/4}$ and when multiplied by $n^{-3/4}$ converges in distribution to a non-tri

Joshua Brakensiek, Neng Huang, Aaron Potechin, Uri Zwick

The input to the Multiway Cut problem is a weighted undirected graph, with nonnegative edge weights, and $k$ designated terminals. The goal is to partition the vertices of the graph into $k$ parts, each containing exactly one of the terminals, such that the sum of weights of the edges connecting vertices in different parts of the partition is minimized. The

Liang Li, Yu Wang, Bing Zhang, Ye Li

Gamma-ray bursts (GRBs), the most energetic transients in the Universe, are traditionally classified into long-duration ($T_{90}>2$ s) and short-duration ($T_{90}<2$ s) events, associated with the core collapse of massive stars (Type II) and the merger of compact binary systems (Type I), respectively. The two classes exhibit distinct observational properties

Shuang Zhou, Kai Yu, Zaifu Zhan, Huixue Zhou

Epilepsy and psychogenic non-epileptic seizures often present with similar seizure-like manifestations but require fundamentally different management strategies. Misdiagnosis is common and can lead to prolonged diagnostic delays, unnecessary treatments, and substantial patient morbidity. Although prolonged video-electroencephalography is the diagnostic gold

Sam C. Collingbourne, Marius A. Oancea, Jan Sbierski

We study Gaussian wave packet solutions for Maxwell's equations in an isotropic, inhomogeneous medium and derive a system of ordinary differential equations that captures the leading-order correction to geodesic motion. The dynamical quantities in this system are the energy centroid, the linear and angular momentum, and the quadrupole moment. Furthermore, th

Zaifu Zhan, Yu Hou, Kai Yu, Min Zeng

Rare diseases affect over 300 million people worldwide and are characterized by complex care pathways, limited clinical expertise, and substantial unmet communication needs throughout the long patient journey. Recent advances in large language models (LLMs) offer new opportunities to support patient education and communication, yet their application in rare

Haozhe Qi, Kevin Qu, Mahdi Rad, Rui Wang

Long video understanding remains challenging for Multi-modal Large Language Models (MLLMs) due to high memory costs and context-length limits. Prior approaches mitigate this by scoring and selecting frames/tokens within short clips, but they lack a principled mechanism to (i) compare relevance across distant video clips and (ii) stop processing once sufficie

Dongryul M. Kim, Andrew Zimmer

In this paper we develop a theory for Patterson--Sullivan measures for non-Borel Anosov groups on the Furstenberg boundary. Previously, such a theory has been successfully developed for measures supported on the partial flag manifold associated to the Anosov condition, which coincides with the Furstenberg boundary only under the strongest Anosov condition, B

Dongryul M. Kim, Andrew Zimmer

In higher rank, there is a well-studied theory of Patterson--Sullivan measures supported on partial flag manifolds. However, establishing the existence and uniqueness of such measures is a difficult question. In this paper, we develop a theory for Patterson--Sullivan measures supported on certain vector-valued horofunction boundaries of the associated symmet

Ian Hedgepeth, Youqiu Zhan, Vitaly Fedoseev, Dirk Bouwmeester

Quantum optomechanical STIRAP (Stimulated Raman Adiabatic Passage) is investigated for a system of two mechanical modes coupled to an optical mode. We show analytically that in a system without loss, fractional STIRAP can generate a mechanical Bell state from a single phonon Fock state of one of the mechanical modes with the other mechanical mode in the vacu

Federico Zocco, Maria Pozzi, Monica Malvezzi

Stable and reliable supplies of rare-Earth minerals and critical raw materials (CRMs) are essential for the development of the European Union. Since a large share of these materials enters the Union from outside, a valid option for CRMs supply resilience and security is to recover them from end-of-use products. Hence, in this paper we present the preliminary

Bipin Singh Koranga, Baktiar Wasir Farooq

We investigate the joint influence of CPT violation and quantum-gravity-induced Planck-scale corrections on the entanglement entropy of two-flavor neutrino oscillations. Building on the CPT-violating neutrino mass matrix arising from flavour-blind Planck-scale physics, we compute the von Neumann entanglement entropy separately for neutrinos and anti-neutrino

Yan Cao, Yong-Liang Ma, Yong Tang

Gravitational-wave displacement memory is a remarkable and ubiquitous phenomenon predicted by general relativity, which has not yet been detected. Unlike the oscillatory components of gravitational waveforms, displacement memory is associated with soft gravitons, making it the only observable signal of its parent event at sufficiently low frequencies. Simila

Christian Sattler, David Wärn

We give a model-independent construction of directed univalent cocartesian fibrations of $(\infty,1)$-categories, and prove a straightening equivalence against such fibrations. The key step is showing that cocartesian fibrations descend along localisations, which we accomplish by analysing mapping spaces of localisations. Along the way we introduce a directe

Ahmed Shokry, Movahhed Sadeghi, Mahmut Kandemir

Quantum metric learning enhances machine learning by mapping classical data to a quantum Hilbert space with maximal separation between classes. However, on current NISQ hardware, this mapping process itself is prone to errors and could be fundamentally incorrect. Verifying that a quantum embedding model successfully achieves its promised separation is essent

Yanyan Yan, Yang Feng, Jiangshan Liu, Di Liu

The growing adoption of Rust for its memory safety and performance has increased the demand for effective migration of legacy C codebases. However, existing rule-based translators (e.g., \ctorust) often generate verbose, non-idiomatic code that preserves unsafe C semantics, limiting readability, maintainability, and practical adoption. Moreover, manual post-

Kalina Dimitrova

The PADME Experiment at Laboratori Nationali di Frascati is designed to search for the Dark Photon, a hypothetical gauge boson responsible for the interaction between the visible and the hidden sector. PADME explores the process of annihilation of beam positrons with the electrons in a fixed target, employing the missing mass technique: in case the annihilat

R. Salinas, V. Kalari, G. Hajdu, Z. Prudil

Despite their key role in astrophysics, the binary properties of RR Lyrae stars (RRL) remain almost completely unknown since only a single RRL is confirmed as belonging to a binary system. Finding companions to RRL is difficult since most of them will be at wider orbits, given that close orbits will likely ensue mass transfer disrupting the conditions to dev

Klara Suchan, Shaswat Mohanty, Hanfeng Zhai, Wei Cai

We present a fully automated framework for extracting interatomic force constants (IFCs) directly from X-ray thermal diffuse scattering (TDS) data. By formulating scattering intensity as a differentiable function of a symmetry-reduced IFC parameterization, we enable gradient-based optimization via direct, Cholesky-based sampling of correlated atomic displace

Muhammad A. Latif, Daniel J. Whalen, Sadegh Khochfar, Fergus Cullen

Overmassive black hole galaxies (OBGs) at redshifts $z \sim$ 10, or 450 Myr after the Big Bang, are one of the most puzzling discoveries by the James Webb Space Telescope to date because they formed by such early epochs and their black-hole to stellar mass ratios are a hundred times higher than those in galaxies today. Here we show that OBGs are simply the r

Aurelien Bibaut, Houssam Zenati, Thibaud Rahier, Nathan Kallus

We propose a cross-fitted debiasing device for policy learning from offline data. A key consequence of the resulting learning principle is $\sqrt N$ regret even for policy classes with complexity greater than Donsker, provided a product-of-errors nuisance remainder is $O(N^{-1/2})$. The regret bound factors into a plug-in policy error factor governed by poli

Damian Sójka, Sebastian Cygert, Marc Masana

We introduce PACE, a backpropagation-free continual test-time adaptation system that directly optimizes the affine parameters of normalization layers. Existing derivative-free approaches struggle to balance runtime efficiency with learning capacity, as they either restrict updates to input prompts or require continuous, resource-intensive adaptation regardle

Yue Hu, Zhenyuan Shang, Chenxi Zhang, Yuanjie Ning

Dispersion engineering via geometric confinement is essential to integrated photonics, enabling phenomena such as soliton microcombs, supercontinua, parametric oscillators, and entangled photons. However, prevailing methodologies rely on semi-empirical Sellmeier models that assume idealized material purity, neglecting the pronounced dispersion shifts induced

Yulie Arad, Stav Ashur, Marta Markowicz, James D. Motes

Motion planning in dynamic environments, such as robotic warehouses, requires fast adaptation to frequent changes in obstacle poses. Traditional roadmap-based methods struggle in such settings, relying on inefficient reconstruction of a roadmap or expensive collision detection to update the existing roadmap. To address these challenges we introduce the Red-G

Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab, Azzam Mourad

Backdoor attacks pose a significant threat to the integrity and reliability of Artificial Intelligence (AI) models, enabling adversaries to manipulate model behavior by injecting poisoned data with hidden triggers. These attacks can lead to severe consequences, especially in critical applications such as autonomous driving, healthcare, and finance. Detecting

Oscar Adamuz-Hinojosa, Jonathan Prados-Garzon, Sara Vaquero-Gil, Juan M. Lopez-Soler

Quantum networks (QNs) enable qubit transfer between distant nodes through quantum teleportation, which reconstructs a quantum state at a remote node by consuming a shared Bell pair. In multi-qubit quantum applications (QApps), the teleported qubits may need to remain stored in quantum memories until execution can start, while decoherence progressively reduc