March 2026 arXiv papers — page 109

Shuyao Shi, Kang G. Shin

Recent Multimodal Large Language Models (MLLMs) have shown high potential for spatial reasoning within 3D scenes. However, they typically rely on computationally expensive 3D representations like point clouds or reconstructed Bird's-Eye View (BEV) maps, or lack physical grounding to resolve ambiguities in scale and size. This paper significantly enhances MLL

Jinho Park, Se Young Chun, Mingoo Seok

Radar is a critical perception modality in autonomous driving systems due to its all-weather characteristics and ability to measure range and Doppler velocity. However, the sheer volume of high-dimensional raw radar data saturates the communication link to the computing engine (e.g., an NPU), which is often a low-bandwidth interface with data rate provisione

Franco Golfieri Madriaga, Ariel Pacetti, Fernando Rodriguez Villegas

Hypergeometric motives are family of motives associated to hypergeometric local systems. Their special features, in particular their rigidity, makes them more tractable than general motives. In the present article we prove most of the properties that they are expected to satisfy in the rank $2$ case.

Preston Bohm, Mingjun Li, Akanksha K. Menon, Zhuomin M. Zhang

The photomolecular effect has been hypothesized to enhance evaporation of water at visible wavelengths. This study develops a measurement technique to investigate its presence and magnitude at the liquid-vapor interface of water. The experiment detects surface absorptance by comparing polarized reflectance for substrates with and without a water layer. The r

E. Cohen Arazi, M. E. Ortega, S. Paron, P. F. Velázquez

High-mass stars, with their powerful winds and intense radiation fields, are fundamental in regulating galactic dynamics and evolution; however, despite their great relevance, the mechanisms involved in their formation are still not fully understood. In this context, molecular outflows, which are essential for removing angular momentum and allowing accretion

Amine Lbath

Software vulnerabilities continue to grow in volume and remain difficult to detect in practice. Although learning-based vulnerability detection has progressed, existing benchmarks are largely function-centric and fail to capture realistic, executable, interprocedural settings. Recent repo-level security benchmarks demonstrate the importance of realistic envi

Pepe Alonso, Sergio Yovine, Victor A. Braberman

AI coding agents can resolve real-world software issues, yet they frequently introduce regressions -- breaking tests that previously passed. Current benchmarks focus almost exclusively on resolution rate, leaving regression behavior under-studied. This paper presents TDAD (Test-Driven Agentic Development), an open-source tool that performs pre-change impact

Louis Primeau, Qiong Ma, Yang Zhang

Berry curvature fundamentally dictates the topological ground state, anomalous transport and optical properties of quantum materials. However, directly mapping its momentum-space distribution in real materials remains an outstanding experimental challenge. Here, we present an inverse method for reconstructing the abelian Berry curvature of a single band usin

Omar Alsheikh, A. F. Kemper, Ermal Rrapaj, Evan J. Rule

We introduce the CaRBM algorithm for fixed-depth thermal state preparation. Our algorithm is based on thermal state purification and uses the Restricted Boltzmann Machine (RBM) block-encoding scheme to implement the imaginary-time propagator $e^{-\beta H}$, which is implemented in the quantum circuit in a fixed-depth manner via Cartan decomposition. Our algo

Ben S. Southworth, Stephen Thomas

Orthogonalized-momentum optimizers such as Muon improve transformer training by approximately whitening/orthogonalizing matrix-valued momentum updates via a short polar-decomposition iteration. However, polar-factor approximations typically require multiple large matrix multiplications, and the resulting overhead can be substantial and hardware-dependent. We

Sadık Bera Yüksel, Derya Aksaray

Robotics foundation models have demonstrated strong capabilities in executing natural language instructions across diverse tasks and environments. However, they remain largely data-driven and lack formal guarantees on safety and satisfaction of time-dependent specifications during deployment. In practice, robots often need to comply with operational constrai

Hirofumi Takesue

Myopic best-response dynamics (MBRD) capture agents' bounded rationality and can generate evolutionary outcomes that differ from those produced by widely examined imitation dynamics. In this study, we apply MBRD to a three-strategy social dilemma -- the snowdrift game with an individual solution -- in which not only defection but also an individual solution

Yoan David, Pierre-Marc Jodoin, Alzheimer's Disease Neuroimaging Initiative, The TRACK-TBI Investigators

Harmonization methods such as ComBat and its variants are widely used to mitigate diffusion MRI (dMRI) site-specific biases. However, ComBat assumes that subject distributions exhibit a Gaussian profile. In practice, patients with neurological disorders often present diffusion metrics that deviate markedly from those of healthy controls, introducing patholog

E. Iani, P. Rinaldi, A. Torralba, J. Lyu

We report the discovery and characterization of two compact galaxies, Pelias and Neleus, at z ~ 0.71 and z ~ 0.75, identified in MACS J0416.1-2403 and GOODS-North. Both exhibit unusual spectral energy distributions (SEDs), with very blue rest-frame UV-optical emission and a steep rise toward near- and mid-infrared wavelengths. JWST/NIRISS and JWST/NIRSpec sp

Vlad-Constantin Lungu-Stan, Ionut Mironica, Mariana-Iuliana Georgescu

Media design layer generation enables the creation of fully editable, layered design documents such as posters, flyers, and logos using only natural language prompts. Existing methods either restrict outputs to a fixed number of layers or require each layer to contain only spatially continuous regions, causing the layer count to scale linearly with design co

A. Armatol, C. Augier, L. Bergé, J. Billard

Solid state athermal phonon calorimeters used in the search for low mass dark matter or coherent neutrino-nucleus interactions have long observed a large excess of events below several hundred eV. The relaxation of damage created by the interaction of fast cosmic ray neutrons with the detector has been proposed as a source of these excess events. By comparin

Argentina Anna Rescigno, Eva Vanmassenhove, Johanna Monti

Handling gender across languages remains a persistent challenge for Machine Translation (MT) and Large Language Models (LLMs), especially when translating from gender-neutral languages into morphologically gendered ones, such as English to Italian. English largely omits grammatical gender, while Italian requires explicit agreement across multiple grammatical

Richard J. Anslow, Maylis Landeau, Amy Bonsor, Jonathan Itcovitz

The excess abundance of highly siderophile elements (HSEs), as inferred for the terrestrial planets and the Moon, is thought to record a `late veneer' of impacts after the giant impact phase of planet formation. Estimates for total mass accretion during this period typically assume all HSEs delivered remain entrained in the mantle. Here, we present an analyt

Tomohiro Asano, Yukihiro Okamoto

Fix a knot $K_0$ in $\mathbb{R}^3$ and consider a Lagrangian submanifold $L$ of $T^*\mathbb{R}^3$ that is isotopic to the conormal bundle of $K_0$ by a compactly supported Hamiltonian isotopy and intersects the zero section $\mathbb{R}^3$ cleanly along a knot. In this paper, using microlocal sheaf theory and some results in $3$-manifold theory, we prove that

Qing-Xing Xie, Yong-Kang Duan, Fa-Hui Liu, Yan Zhao

Extracting energy spectra from quantum Hamiltonians is a fundamental task for quantum simulation, yet remains challenging on noisy intermediate-scale quantum (NISQ) devices. We propose Measured Quantum Time Evolution (MQTE), an ancilla-free algorithm that estimates energy gaps by applying real-time evolution to a reference state and measuring time-resolved p

Leen Aburub, Gergo Gyenizse

By median we mean a scheme that inputs three element of a lattice, and outputs an element that is an average of the three inputs in a certain sense. The medians of a given finite lattice form a new lattice that is usually larger than the original, but generates a (not necessarily strictly) smaller variety. A median is called inner if it is a term function. T

Qi Xu, Beat Signer

Scholarly reading often involves engaging with various supplementary materials beyond PDFs to support understanding. In practice, scholars frequently incorporate such external materials into their reading workflow through annotation. However, most existing PDF annotation tools support only a limited range of media types for embedding annotations in PDF docum

Gilles Brassard, Xavier Coiteux-Roy, Rémi Ligez

As early as 1935, Schr\"odinger recognized entanglement as ``not one but rather the characteristic trait of quantum mechanics, the one that enforces its entire departure from classical lines of thought''. Indeed, most remarkable phenomena in quantum information science, such as quantum computing and quantum teleportation, spring from clever uses of entanglem

Mankei Tsang

I propose a physical measurement scheme on multiple independent and identically distributed quantum objects to approach the Holevo--Nagaoka bound for quantum multiparameter estimation. The scheme entails a physical interaction of the objects with bosonic ancillas, followed by a general-dyne measurement of the ancillas. The proposal offers a more concrete des

Francesca Centrone, Asmerilda Hitaj, Elisa Mastrogiacomo, Emanuela Rosazza Gianin

This paper develops a unified framework for the robustification of risk measures beyond the classical convex and cash-additive setting. We consider general risk measures on Lp spaces and construct their robust counterparts through families of uncertainty sets that capture ambiguity. Two complementary mechanisms generate robust quasi-convex measures: in the f

Arturo Tozzi

The number of stable macroscopic organizations in complex systems is often much smaller than the large number of microscopic degrees of freedom would suggest. Yet theoretical approaches rarely address whether general limits constrain the diversity of admissible macroscopic organizations. We develop a geometric framework in which interactions among system com

Qing-Xing Xie, Zidong Lin, Yun-Long Liu, Yan Zhao

This paper introduces Witnessed Quantum Time Evolution (WQTE), a novel quantum algorithm for efficiently computing the eigen-energy spectra of arbitrary quantum systems without requiring eigenstate preparation-a key limitation of conventional approaches. By leveraging a single ancillary qubit to control real-time evolution operators and employing Fourier ana

Chiara Manna, Hosein Mohebbi, Afra Alishahi, Frédéric Blain

While Large Language Models achieve state-of-the-art results across a wide range of NLP tasks, they remain prone to systematic biases. Among these, gender bias is particularly salient in MT, due to systematic differences across languages in whether and how gender is marked. As a result, translation often requires disambiguating implicit source signals into e

M. Adhikari, M. Ahn, D. Amaya Matamoros, P. S. Barbeau

The COHERENT collaboration reports the most precise measurement of the coherent elastic neutrino-nucleus scattering cross section to date. This measurement was performed with COHERENT's germanium detector array, Ge-Mini, at the Spallation Neutron Source at Oak Ridge National Laboratory. A cumulative exposure of $4.68\times10^{22}$ protons on target yielded a

Efe Ilker, Michael Hinczewski, Xingbo Yang, Frank Jülicher

Living systems continuously transform matter and energy through the chemical processes that constitute their metabolism. The overall metabolic rate of an organism correlates positively with its body mass, however both the exact scaling behavior and possible explanations for this behavior have been under intense debate for two centuries. This review synthesiz

Zhengze Xiao, Xuanzhe Ding, Yuyang Lou, Lixue Cheng

Neural Network Variational Monte Carlo (NNVMC) has emerged as a promising paradigm for solving quantum many-body problems by combining variational Monte Carlo with expressive neural-network wave-function ans\"atze. Although NNVMC can achieve competitive accuracy with favorable asymptotic scaling, practical deployment remains limited by high runtime and memor

Arist Zhenyuan Yang, Zheng-Xin Liu

Known symmetry groups are insufficient to describe the various couplings among spin, charge, and spatial degrees of freedom in fermionic systems. To address this problem, we introduce spin-charge groups (SCGs), which provide a unified framework for fermionic symmetries. SCGs incorporate spin and charge operations as `internal' symmetries, spatial and tempora

Saharon Shelah

Assume $\kappa = \kappa^{< \kappa}$ (usually $\aleph_0$ or an inaccessible). We shall deal with iterated forcings preserving ${}^{\kappa>}{\rm Ord}$ and not collapsing cardinals along a linear order $L$. A sufficient condition for this, which we will focus on, is for the forcings to have support $<\kappa$ and the $\kappa^+$-cc, and be strategically $<{\kappa

Mohamed Eltahir, Ali Habibullah, Yazan Alshoibi, Lama Ayash

Extending language models to video introduces two challenges: representation, where existing methods rely on lossy approximations, and long-context, where caption- or agent-based pipelines collapse video into text and lose visual fidelity. To overcome this, we introduce \textbf{VideoAtlas}, a task-agnostic environment to represent video as a hierarchical gri

Cristiano Capone, Luca Falorsi, Andrea Ciardiello, Luca Manneschi

Rapid adaptation in complex control systems remains a central challenge in reinforcement learning. We introduce a framework in which policy and value functions share a low-dimensional coefficient vector - a goal embedding - that captures task identity and enables immediate adaptation to novel tasks without retraining representations. During pretraining, we j

Zhongzhu Zhou, Fengxiang Bie, Ziyan Chen, Zhenyu Zhang

Converting pretrained attention modules such as grouped-query attention (GQA) into multi-head latent attention (MLA) can improve expressivity without increasing KV-cache cost, making it attractive for efficient inference. However, many practical conversion baselines rely on weight-only low-rank approximations (e.g., SVD-style initializations) and uniform ran

Chloé Greenstreet, Anastasia Vayona, Jane Henriksen-Bulmer

Despite public motivation to recycle, significant barriers hinder effective household recycling in the UK. Decentralised local authority waste management creates citizen confusion and "wishcycling" (disposing of non-recyclable items in recycling bins). The recent Simpler Recycling Policy further complicates this landscape by mandating new identification, sor

Fei Zhang, Zijian Zhou, Bohao Tang, Sen He

We introduce the first method, to the best of our knowledge, for adapting image-to-video models to layer-aware text (glyph) animation, a capability critical for practical dynamic visual design. Existing approaches predominantly handle the transparency-encoding (alpha channel) as an extra latent dimension appended to the RGB space, necessitating the reconstru

Zoltan Bajnok, Bercel Boldis, Dennis le Plat

We present the full transseries of the strong-coupling expansion of the cusp anomalous dimension in N=4 super Yang-Mills theory. This quantity admits an exact representation as a ratio of two determinants with particularly simple strong-coupling expansions. Nonperturbative contributions are classified by partitions into distinct odd integers and obey a unive

Wataru Setoyama, Keisuke Fujii

Non-Markovian dynamics is ubiquitous in both quantum and classical systems, but the numerical computation of the time-delay dynamics is demanding. In this work, we propose an efficient quantum algorithm for solving linear distributed delay differential equations and identify the condition under which it applies. Using the linear chain trick, the distributed

Md Firoz Ali, Lokenath Thakur

In this paper, we investigate three specific subclasses of Ma-Minda type convex functions: namely, convex functions of order $\alpha$, Janowski convex functions, and Robertson functions of normalized analytic functions defined in the open unit disk. For these classes, we establish logarithmic coefficient inequalities concerning both individual coefficient es

Rodolfo Aguilar, Cristhian Garay

The classical Shafarevich conjecture predicts that the universal cover of a complex smooth projective variety $X$ is holomorphically convex. In this paper, we propose a refinement of this conjecture for varieties defined over the reals. In order to do this, we introduce the notions of real holomorphic convexity and transverse holomorphic convexity to capture

J. J. M. in 't Zand, L. Kuiper, F. Ceraudo, Y. Evangelista

The concept of two perpendicular one-dimensional coded aperture cameras, necessitated by the imaging capability of the detector, finds its application in the design of the Wide Field Monitor (WFM). This instrument has the future goal to monitor the variable X-ray sky for transient activity. Characteristic of each camera is a fine angular resolution in one di

Rutvij Gholap, Alexey Ermakov, Alexander Kazantsev, Mohammad Saeed Bahramy

We identify overdamped gauge phonons as a new microscopic route to non-Fermi-liquid behaviour in Dirac materials. These phonons couple to electronic currents rather than densities, thereby realising a lattice analogue of transverse gauge-field mechanisms without requiring proximity to a quantum critical point. By computing the electronic self-energy with a p

Eugene Y. Huang, Christian Kraglund Andersen

We study the cross-resonance effect in capacitively-coupled fluxonium qubits and devise a simple formula for their maximum ZX interaction strength. By going beyond the perturbative regime, we find that a CNOT gate can generally be realized in under 200 ns with residual ZZ limited to 50 kHz, for fluxonium qubits with frequencies below 1 GHz. Our analysis reli

Taorui Wang, Xun Li, Gu Wang, Zhongqiang Zhang

Choosing how much noise to add in Langevin dynamics is essential for making these algorithms effective in challenging optimization problems. One promising approach is to determine this noise by solving Hamilton-Jacobi-Bellman (HJB) equations and their exploratory variants. Though these ideas have been demonstrated to work well in one dimension, extension to

Cyprien Tamekue, Zongxi Yu, ShiNung Ching

Fixed-horizon minimum-energy control for control-affine systems rarely admits closed-form formulas beyond the linear setting. In this article, under the assumption of unconstrained controls, we derive a fixed-horizon minimum-energy control for a broad class of control-affine systems as a fixed point of a Lagrange multiplier synthesis map. Compared with our e

Lívia Dutra, Arthur Lorenzi, Frederico Belcavello, Ely Matos

Gender-based violence (GBV) is a major public health issue, with the World Health Organization estimating that one in three women experiences physical or sexual violence by an intimate partner during her lifetime. In Brazil, although healthcare professionals are legally required to report such cases, underreporting remains significant due to difficulties in

Jingchun Yang, Jinchang Zhang

The widespread adoption of dashcams has made video evidence in traffic accidents increasingly abundant, yet transforming "what happened in the video" into "who is responsible under which legal provisions" still relies heavily on human experts. Existing ego-view traffic accident studies mainly focus on perception and semantic understanding, while LLM-based le

Ikhtiyor Eshtursunov, Sanjar Shaymatov

In this work, we investigate the magnetic reconnection (MR) process as a mechanism for energy extraction from a rapidly rotating Buchdahl star (BS), one of the most compact horizonless objects that can, in principle, possess a spin parameter exceeding the extremal limit of a black hole (BH). We explore the energetics of the BS by focusing on the newly propos

Xichen Yuan, Zhe Li, Bofan Lyu, Kuangji Zuo

While generative models have become effective at producing human-like motions from text, transferring these motions to humanoid robots for physical execution remains challenging. Existing pipelines are often limited by retargeting, where kinematic quality is undermined by physical infeasibility, contact-transition errors, and the high cost of real-world dyna

Javier Venema, Stefano De Luca, Pablo Mesejo, Óscar Ibáñez

Legal age estimation plays a critical role in forensic and medico-legal contexts, where decisions must be supported by accurate, robust, and reproducible methods with explicit uncertainty quantification. While prior artificial intelligence (AI)-based approaches have primarily focused on hand radiographs or dental imaging, clavicle computed tomography (CT) sc

Saurabhsingh Rajput, Tushar Sharma

Accurate software energy measurement is critical for optimizing energy, yet existing profilers force a trade-off between measurement accuracy and overhead due to tight coupling with supported specific hardware or languages. We present CodeGreen, a modular energy measurement platform that decouples instrumentation from measurement via an asynchronous producer

Joshua Forer

The rotational excitation of the three asymmetric-top molecular ion isotopologues H$_2$O$^+$, HDO$^+$, and D$_2$O$^+$ is studied theoretically using a combined framework of electron-molecule R-matrix scattering theory, multichannel quantum-defect theory, frame transformation theory, and the Coulomb-Born approximation. The latter two have been adapted here fo

Kathryn A. Pitton, Michiel P. Dubbelman, Trent M. Kyrk, Houssam El Mrabet Haje

Josephson junctions translate quantum phase coherence into an electrical response and underpin superconducting sensors and quantum circuits. In conventional junctions, the barrier acts primarily as a passive weak link, however, when the barrier is a quantum material with its own internal degrees of freedom like magnetism, strong correlations, or switchable p

María Teresa Valdivia-Mena, Jaime E. Pineda, Caroline Gieser, Paola Caselli

(Abridged) Recently, streamers have been observed causing shocks at the outer edge of protoplanetary disks. The study of sulfur-bearing species can help us to understand the physical and chemical changes caused by infalling streamers toward their landing positions. We study the physical properties traced by SO$_2$ and SO toward the Class I protostar Per-emb

Borja Aizpurua, Sukhbinder Singh, Román Orús

Large language models (LLMs) contain billions of parameters, yet many exact values are not essential. We show that what matters most is the relative rank of weights-whether one connection is stronger or weaker than another-rather than precise magnitudes. To reduce the number of unique weight values, we apply weight clustering to pretrained models, replacing

Michał Szyfelbein

We consider the following generalization of the classic Binary Search Problem: a searcher is required to find a hidden target vertex $x$ in a graph $G$, by iteratively performing queries about vertices. A query to $v$ incurs a cost $c(v, x)$ and responds whether $v=x$ and if not, returns the connected component in $G-v$ containing $x$. The goal is to design

Shima Yousefi, Saptarshi Debroy

Collaborative inference of object classification Deep neural Networks (DNNs) where resource-constrained end-devices offload partially processed data to remote edge servers to complete end-to-end processing, is becoming a key enabler of edge-AI. However, such edge-offloading is vulnerable to malicious data injections leading to stealthy misclassifications tha

James Kessinger, Andrei Martinez-Finkelshtein

We study the logarithmic equilibrium problem on the interval $[-1,1]$ in the presence of an external field generated by a uniform background charge supported on the same interval. For a real parameter $\tau$, the external field is taken to be $\tau$ times the logarithmic potential of the unit Lebesgue measure, and for all values of $\tau$ we determine explic

Yue Zhao, Jiatao Gu, Paloma Jeretič, Weijie Su

Understanding the distance between human languages is central to linguistics, anthropology, and tracing human evolutionary history. Yet, while linguistics has long provided rich qualitative accounts of cross-linguistic variation, a unified and scalable quantitative approach to measuring language distance remains lacking. In this paper, we introduce a method

Sebastian Gurriaran

We consider solutions of the Einstein vacuum equations which arise from smooth initial data on a hypersurface slightly inside a dynamical black hole settling down to a subextremal Kerr black hole, and satisfying a precise non-linear Price's law-type estimate (which we expect to hold generically). We prove that the corresponding maximal globally hyperbolic de

Marcos A. Ferreira, Tianao Li, John Mamish, Josiah Hester

We introduce SpiderCam, an FPGA-based snapshot depth-from-defocus camera which produces 480x400 sparse depth maps in real-time at 32.5 FPS over a working range of 52 cm while consuming 624 mW of power in total. SpiderCam comprises a custom camera that simultaneously captures two differently focused images of the same scene, processed with a SystemVerilog imp

Miles Stanley, Soumyajit Datta, Ashutosh Kumar, Ashiqur R. KhudaBukhsh

A significant gap exists in datasets regarding post-COVID-19 vaccination experiences, particularly ``vaccine buyer's remorse''. Understanding the prevalence and nature of vaccine regret, whether based on personal or vicarious experiences, is vital for addressing vaccine hesitancy and refining public health communication. In this paper, we curate a novel data

Vladyslav Mikytiv, Bernardo Toninho, Carla Ferreira

Runtime verification has gained popularity as a lightweight approach for increasing assurance in systems under scrutiny. Performing runtime checks enables dynamic monitoring and alerts for unexpected behavior, thereby improving reliability and correctness. Actor-based systems present significant challenges for runtime verification. Properties frequently span

Tobias M. Schmidt, Ewelina Obrzud, François Bouchy, Gaspare Lo Curto

Laser frequency combs (LFCs) are a promising technology for wavelength calibration of astronomical high-resolution spectrographs requiring utmost accuracy and stability, since they directly translate the fundamental SI time standard from the radio frequency regime to optical frequencies. However, they have so far seen limited use in practice, due to their co

Ya-Ting Yang, Quanyan Zhu

Actionable recourse studies whether individuals can modify feasible features to overturn unfavorable outcomes produced by AI-assisted decision-support systems. However, many such systems operate in competitive settings, such as admission or hiring, where only a fraction of candidates can succeed. A fundamental question arises: what happens when actionable re

Jinbao Cheng, Jianguo Huang, Haoqin Wang, Tao Zhou

We propose a decoupled divergence-free neural networks basis (Decoupled-DFNN) method for solving incompressible flow problems, including the Stokes and Navier-Stokes equations. To ensure the divergence free property exactly, the velocity field is represented as the curl of a stream function in two dimensions and as the curl of a vector potential in three dim

Abdul Ahad Mamun, Rokon Uddin Mahmud, Shahin Aziz, Muhammad Shahriar Bashar

Electrochemical water electrolysis, which produces clean energy carriers to mitigate carbon emissions, lacks suitable, low-cost electrodes for efficient oxygen evolution reaction (OER) in alkaline water splitting. To address this challenge, we developed Zn-Al alloy electrodes with varying Al contents up to 20 wt.% via powder metallurgy method and conducted e

Sriram Gopalakrishnan

Skele-Code is a natural-language and graph-based interface for building workflows with AI agents, designed especially for less or non-technical users. It supports incremental, interactive notebook-style development, and each step is converted to code with a required set of functions and behavior to enable incremental building of workflows. Agents are invoked

Rafael Aoude, Asaad Elkhidir, Anton Ilderton, Donal O'Connell

It is now common to describe classical backgrounds involving dynamical black holes with the production of gravitational radiation using the methods of scattering amplitudes. In that light, we revisit the standard formulation of quantum field theory on a background. We discuss the interpretation of Bogoliubov coefficients as generalised amplitudes, and explai

Ya-Ting Yang, Quanyan Zhu

Large language models (LLMs) and AI agents are increasingly integrated into enterprise systems to access internal databases and generate context-aware responses. While such integration improves productivity and decision support, the model outputs may inadvertently reveal sensitive information. Although many prior efforts focus on protecting the privacy of us

Yining Wang, Alhasan Abdellatif, Artemis Deligianni, Hannah Hok

We present the first large-scale comparative analysis of Truth Social and the most popular conservative Reddit communities, r/Conservative, r/conservatives, and r/Republican. Using topic modeling with FASTopic and LLM-assisted refinement, we analyze topic prevalence, toxicity, and temporal dynamics across these communities during the first eight months of Tr

Felix Erben, Matthew Black, Peter Boyle, Matteo Di Carlo

Rare $b\to s\ell^+\ell^-$ decays provide some of the most sensitive tests of the Standard Model and require precise and systematically improvable hadronic input from lattice QCD. For the phenomenologically important channel $B\to K^*\ell^+\ell^-$ this entails a first-principles treatment of a resonant $K\pi$ final state together with controlled heavy-quark d

Mark Mets, Peter Sheridan Dodds, Maximilian Schich

Aggression against Ukraine has drawn widespread international attention, particularly in the wake of the two Russian invasions into Ukrainian territory in 2014 and 2022. Although previous studies have examined social-media dynamics around these events, a comparative longitudinal data-driven view across languages is still missing. This article fills this gap

Jakub Growiec, Klaus Prettner, Maciej Szkróbka

We characterize the optimal tax policy in an economy with human manual and cognitive labor, physical capital, and artificial intelligence (AI). Extending the dynamic taxation setup of Slavik and Yazici (2014), we find that it is optimal to start taxing AI when cognitive workers start to consider switching to manual jobs. This threshold may be crossed once AI

Kiran R. Bhutani, Anthony Christiana, Peter Ulrickson

We study the secure domination number of the Mycielskian graph of a simple, connected, undirected graph. We give generally applicable bounds, compute secure domination numbers for Mycielskians of important families of graphs, and construct families of graphs realizing particular values of (secure) domination parameters.

Leonardo Defilippis, Florent Krzakala, Bruno Loureiro, Antoine Maillard

Understanding when learning is statistically possible yet computationally hard is a central challenge in high-dimensional statistics. In this work, we investigate this question in the context of single- and multi-index models, classes of functions widely studied as benchmarks to probe the ability of machine learning methods to discover features in high-dimen

Ruixiao Shi, Fu Feng, Yucheng Xie, Xu Yang

Text-to-image (T2I) models have substantially improved image fidelity and prompt adherence, yet their creativity remains constrained by reliance on discrete natural language prompts. When presented with fuzzy prompts such as ``a creative vinyl record-inspired skyscraper'', these models often fail to infer the underlying creative intent, leaving creative idea

Viktor Holubec, Frank Cichos

Feedback control plays a central role in active matter, yet it is inevitably accompanied by noise and finite perception--action delays. This Perspective reviews recent advances on active systems with delayed interactions, showing how time delay can induce activity, chirality, transport, and collective pattern formation, and can act as an effective control pa

Amr Eleraqi, Hager H. Mustafa, Abdul Hadi N. Ahmed

This study examines how different artificial intelligence architectures interpret sentiment in conflict-related media discourse, using the 2023 Gaza War as a case study. Drawing on a corpus of 10,990 Arabic news headlines (Eleraqi 2026), the research conducts a comparative analysis between three large language models and six fine-tuned Arabic BERT models. Ra

Tanmay Sah, Vishal Srivastava, Dolly Sah, Kayden Jordan

We study how runtime enforcement against unsafe actions affects end-to-end task performance in multi-step tool using large language model (LLM) agents. Using tau-bench across Airline and Retail domains, we compare baseline Tool-Calling, planning-integrated (TRIAD), and policy-mediated (TRIAD-SAFETY) architectures with GPT-OSS-20B and GLM-4-9B. We identify mo

Arpit Singh Gautam, Saurabh Jha

Post training quantization is essential for deploying large language models (LLMs) on resource constrained hardware, yet state of the art methods enforce uniform bit widths across layers, yielding suboptimal accuracy efficiency trade offs. We present RAMP (Reinforcement Adaptive Mixed Precision), an off policy Soft Actor Critic framework that learns per laye

Scott Neville, José Simental

The deep locus of a cluster variety is defined to be the set of its points that do not belong to any cluster torus. We show that, if the cluster variety has a seed whose mutable part is a tree without multiple edges, then the deep locus can be characterized as the set of points whose stabilizer under a certain group action is nontrivial. Deep points without

Kasra Ahmadi, Saeed Aghapour, Mehran Mozaffari Kermani, Reza Azarderakhsh

The inference phase of deep neural networks (DNNs) in embedded systems is increasingly vulnerable to fault attacks and failures, which can result in incorrect predictions. These vulnerabilities can potentially lead to catastrophic consequences, making the development of effective mitigation techniques essential. In this paper, we introduce MAED (Mathematical

A. I. Komech, E. A. Kopylova

We consider damped driven Maxwell-Bloch equations for a single-mode Maxwell field coupled to a two-level molecule. The equations are used for semiclassical description of the laser action. Our main result is the construction of solutions with single-frequency asymptotics of the Maxwell field in the case of quasiperiodic pumping. The asymptotics hold for solu

Michel Schimpf, Julian Voigt, Thomas Bohné

Helping people identify and pursue personally meaningful career goals at scale remains a key challenge in applied psychology. Career coaching can improve goal quality and attainment, but its cost and limited availability restrict access. Large language model (LLM)-based chatbots offer a scalable alternative, yet the psychological mechanisms by which they mig

Stephen DiIorio, Ricardo Fonseca, Frank Tsung, Benjamin J. Winjum

Ionization is critical in the formation and evolution of plasma dynamics; collisional ionization, in particular, is an often overlooked source of electrons when dealing with laser-plasma interactions. Ionization plays a crucial role in understanding the complex plasma kinetics, ranging from cold and sparse astrophysical settings to hot and dense fusion syste

Wenjie Jacky Mo, Qin Liu, Xiaofei Wen, Wenxuan Zhou

Large language models (LLMs) are trained through multi-stage pipelines over heterogeneous data sources, yet developers lack a principled way to pinpoint the specific data responsible for an observed behavior. This lack of observability reduces debugging to reactive patching and makes failures prone to recur under distribution shift or subsequent model update

Marcin Abram

We analyze the challenges of benchmarking scientific (multi)-agentic systems, including the difficulty of distinguishing reasoning from retrieval, the risks of data/model contamination, the lack of reliable ground truth for novel research problems, the complications introduced by tool use, and the replication challenges due to the continuously changing/updat

Zehra Karadağ, Simon Klix, René Walendy, Felix Hahn

Hardware serves as the root of trust in modern computing systems, making Hardware Reverse Engineering (HRE) essential for security assurance$-$from design verification and supply-chain integrity to vulnerability discovery. We scope HRE to netlist recovery and its subsequent analysis, spanning the three subdomains of Integrated Circuit (IC), Field-Programmabl

Savvas Raptis, Domenico Trotta, Drew L. Turner, Xóchitl Blanco-Cano

Collisionless shocks are fundamental accelerators of energetic particles; yet, the observations of nonlinear foreshock structures, which are essential in acceleration processes, differ significantly between Interplanetary (IP) shocks and planetary bow shocks. We present a direct comparison of two high-Mach-number, quasi-parallel shocks: an IP shock observed

Christian Rutzer, Dragan Filimonovic, Jeffrey T. Macher, Rolf Weder

The CD index is a widely used measure of disruptive inventions. Most studies compute it using USPTO data. This creates a puzzle because the US appears less disruptive than European and Asian countries. We show that this largely stems from missing international citations. Using a global citation network, we quantify and correct this bias. The disruptiveness a

João Paulo Esper, Yure Freitas, Pedro Souza, Bruno Silvestre

While the Open Radio Access Network Alliance (O-RAN) architecture enables third-party applications to optimize radio access networks at multiple timescales, real-time distributed applications (dApps) that demand low latency, high performance, and strong isolation remain underexplored. Existing approaches propose colocating a new RAN Intelligent Controller (R

Samantha Sbarra, Ji Zhou, Boris Zabelich, Marco Clementi

On-chip coherent visible and near-infrared (NIR) light generation has broad applications in metrology, bio-sensing, and quantum information. High-Q microresonators are ideal candidates for generating light across such broad wavelength ranges via efficient second- ($\chi^{(2)}$) and third-order ($\chi^{(3)}$) nonlinear optical processes. However, harnessing t

Alexander Vinogradov, Marian Lazar, Ioannis Zouganelis, Viviane Pierrard

Recent evidence from Parker Solar Probe on the suprathermal electrons with Kappa-type velocity distributions in the outer corona has revived interest in the kinetic-based macro-modelling of the solar (SW), aiming to explain its properties. Invoked in kinetic modelling of nonequilibrium plasmas, standard Kappa distributions (SKDs) have been adjusted to the re

Guandong Li, Zhaobin Chu

Instruction-following image editing models are expected to modify only the specified region while keeping the rest of the image unchanged. However, in practice, we observe a pervasive phenomenon -- edit spillover: models alter semantically related but unspecified content outside the edit region. This raises a fundamental question -- does spillover reflect ge

Abhishek Gupta, Aditya Mahajan

Markov decision processes (MDPs) is viewed as an optimization of an objective function over certain linear operators over general function spaces. A new existence result is established for the existence of optimal policies in general MDPs, which differs from the existence result derived previously in the literature. Using the well-established perturbation th

Johannes V. Roth, Yunxin Ye, Sören Schlichting, Lorenz von Smekal

We employ a novel real-time formulation of the functional renormalization group (FRG) to compute universal scaling functions of the thermal diffusivity and the shear viscosity in the vicinity of the liquid-gas critical point, i.e., for the dynamic universality class of Model H from the Halperin-Hohenberg classification. We map out the universal dependence of

Serge Galam

I introduce a new analytical framework for estimating critical temperatures in interacting many-body systems, focusing on the Ising model. Combining the Bethe cluster setting, the Metropolis update, and the Galam Majority Model developed in sociophysics, I build a two stroke pumping technique (TSP). Applied to the Ising model in dimensions d=2, 3, 4, TSP yie