April 2026 arXiv papers — page 144

Wenqing Li, Xu Feng, Peixue Jiang, Yinhai Zhu

Thermodynamic cycles are pivotal in determining the efficacy of energy conversion systems. Traditional design methodologies, which rely on expert knowledge or exhaustive enumeration, are inefficient and lack scalability, thereby constraining the discovery of high-performance cycles. In this study, we introduce a graph-based hierarchical reinforcement learnin

Koichiro Takahashi, Shuichiro Ebata, Naotaka Yoshinaga, Shintaro Hoshino

We investigate the localized-electron character of the Mott-insulating phase in A$_3$C$_{60}$ using a single-site multiorbital electron model coupled to anisotropic molecular vibrations (Jahn--Teller phonons). We apply the spherical-tensor formalism, a framework originally developed in nuclear physics, to analyze the electron--phonon-coupled ground-state mul

Z. Fan, B. P. Y. Loo, F. Duarte, C. Ratti

This study leverages large-scale travel surveys for over 200,000 residents across Boston, Chicago, Hong Kong, London, and Sao Paulo. With rich individual-level data, we make systematic comparisons and reveal patterns in social mixing, which cannot be identified by analyzing high-resolution mobility data alone. Using the same set of data, inferring socioecono

Hongru Song, Yu-An Liu, Ruqing Zhang, Jiafeng Guo

Retrieval-augmented generation (RAG) enhances large language model (LLM) reasoning by retrieving external documents, but also opens up new attack surfaces. We study knowledge-base poisoning attacks in RAG, where an attacker injects malicious content into the retrieval corpus, which is then naturally surfaced by the retriever and consumed by the LLM during re

Ning Yang, Jinliang Gao, Haijun Zhang

Efficient spectrum management in massive-scale wireless networks is increasingly challenged by explosive action spaces and the computational intractability of traditional optimization. This study proposes a LLM-Driven Large-Scale Spectrum Access (LSA) framework rooted in Group Relative Policy Optimization (GRPO). To overcome the computational intractability

Guangzhi He, Shifan Zuo, Jixia Li, Yichao Li

The Tianlai Dish Pathfinder Array (TDPA) is a radio interferometer designed to test techniques for 21 cm intensity mapping in the post-reionization universe as a means of measuring large-scale cosmic structure. Using 9 nights of observations targeting the North Celestial Pole (NCP) field, totaling approximately 107 hours of integration time, we analyze data

Jon Kim

The moduli space of cubic surfaces and its compactifications are classical and date back to the mid-nineteenth century. Recently, Schock described compactifications of moduli spaces of fully marked cubic surfaces with their 27 lines via Koll\'ar--Shepherd-Barron--Alexeev (KSBA) weighted stable pairs where the 27 lines are uniformly weighted. Furthermore, he

Jose Negrete, Jaime Joel Ramos

Factor models characterize the joint behavior of large sets of financial assets through a smaller number of underlying drivers. We develop a network-based framework in which factors emerge naturally from the structure of interactions among assets rather than being imposed statistically. The market is modeled as a system of coupled iterated maps, where assets

Manh Nguyen, Sunil Gupta, Hung Le

Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challenging, especially when correctness diverges from surface-level majority agreement. Existing approaches, such as self-consistency, rely on discrete voting, while probability-based methods often fail to capture rel

Dhara Yu, Karthikeya Kaushik, Bill D. Thompson

Work in cognitive science and artificial intelligence has suggested that exposing learning agents to traces of interaction between multiple individuals can improve performance in a variety of settings, yet it remains unknown which features of interactions contribute to this improvement. We examined the factors that support the effectiveness of interaction da

Barry Jay, Johannes Bader

This paper introduces a simple type system for combinatory logic in which combinators have at most one type, whose polymorphism is revealed by application. The combinatory types exactly describe the structure of their values, which may be hidden by abstract types, such as list types and function types. Even without any quantified types, it supports polymorph

Yiheng Chen, Wai-Chi Cheng, Tzung-May Fu, Wei Tao

Accurate urban surface characterization is essential for environmental modeling, risk assessment, and climate adaptation. However, existing classifications of urban surfaces lack the global consistency and physical detail to fully represent present-day urban heterogeneity. To address this need, we developed a globally unified, Data-driven Urban Environmental

Lorenzo De Gaspari, Serena Dipierro, Enrico Valdinoci

We consider a bushfire model in a gully. The biological scenario under consideration involves flammable fuel (trees, leaves, etc.) concentrated within the gully, surrounded by rocky hillslopes containing little or no burnable material. The mathematical formulation of the problem is a nonlocal evolution equation of parabolic type. The nonlocality arises from

Xu Zhang, Xudong Gong, Jiacheng Qin, Qiang Wang

Current evaluations of large language models aggregate performance across diverse tasks into single scores. This obscures fine-grained ability variation, limiting targeted model improvement and ability-guided selection for specific tasks. Motivated by this gap, we propose a cognitive diagnostic framework that estimates model abilities across multiple fine-gr

Bernardo B. P. Medeiros, Malvika Jadhav, Allison Lu, Tadayoshi Kohno

Many malicious actors responsible for disseminating synthetic non-consensual intimate imagery (SNCII) operate within internet forums to exchange resources, strategies, and generated content across multiple platforms. Technically-sophisticated actors gravitate toward certain communities (e.g., 4chan), while lower-sophistication end-users are more active on ot

Yuxuan He, Weiyang Wang, Chen Zhang, Yi-Ming Zhong

Observations of ultra-dense substructures in strong lensing systems challenge the standard cosmological model at small scales. Self-interacting dark matter (SIDM), as an alternative to the cold and collisionless dark matter (CDM) of the standard cosmological model, provides a natural mechanism for forming such structures via gravothermal core collapse. We sh

Oleg Kiriukhin

I study the cubic Fourier-Galerkin truncation of the three-dimensional (3D) incompressible Navier-Stokes equations on the periodic torus after reduction by the full octahedral symmetry group $O_h$. The nonlinear interaction is encoded by a state-dependent orbit-level transfer matrix $M_N(u)$, and the main discrete problem is to estimate orbit-triad incidence

Jorge Meza-Domínguez

We establish a rigorous bundle isomorphism between the complex velocity field $\eta_{\mu} = \pi_{\mu} - i u_{\mu}$, obtained by averaging matter dynamics over stochastic gravitational fluctuations, and the symmetric logarithmic derivative (SLD) operator $L_{\mu}$ of quantum estimation theory. The isomorphism $\widetilde{\mathcal{T}}: \Gamma(E/{\sim}) \to \Ga

Avijit Mandal, Henry D. Pfister

We develop a quantum message-passing framework for factor graphs over finite abelian groups. Our starting point is the task of discriminating between a collection of quantum states indexed by the elements of a finite abelian group $\mathcal{G}$ whose overlaps respect the structure of a group-covariant pure-state channel (PSC). For such channels, we show that

Keshu Wu, Chenchen Kuai, Zihao Li, Jiwan Jiang

Retrieval-augmented generation (RAG) enhances large language models by grounding outputs in retrieved knowledge. However, existing RAG methods including graph- and hypergraph-based approaches treat retrieved evidence as an unordered set, implicitly assuming permutation invariance. This assumption is misaligned with many real-world reasoning tasks, where outc

Gautama Shastry Bulusu Venkata, Santhosh Kakarla, Maheedhar Omtri Mohan, Aishwarya Gaddam

TRUST Agents is a collaborative multi-agent framework for explainable fact verification and fake news detection. Rather than treating verification as a simple true-or-false classification task, the system identifies verifiable claims, retrieves relevant evidence, compares claims against that evidence, reasons under uncertainty, and generates explanations tha

Luyao Wang

Industrial control systems operate in dynamic environments where traffic distributions vary across scenarios, labeled samples are limited, and unknown attacks frequently emerge, posing significant challenges to cross-domain intrusion detection. To address this issue, this paper proposes a clustering-enhanced domain adaptation method for industrial control tr

Chang-Quan Zhou, Hua-Shu Dou, Lin Niu, Wen-Qian Xu

Simulations of the transitional flow in Taylor-Couette configuration are carried out to study the effect of the gap width on turbulent transition. The research results show that, under the same radius and the rotating speed of the inner cylinder, as the gap width increases, the flow becomes more stable. It is discovered that the average velocity distribution

Román Aranda, Sarah Blackwell, Geunyoung Kim, Patrick Naylor

We introduce and study bridge decompositions for 3-manifolds embedded in the 5-sphere. These generalize both the classical notion of bridge position for knots in the 3-sphere and the bridge trisections of surfaces in the 4-sphere due to Meier and Zupan. Our main technical tool is the multisections of 5-manifolds introduced by Aribi, Courte, Golla, and Moussa

Terence Highsmith

Many matching markets feature unknown, dynamic arrivals of agents that must match immediately. A caseworker must match an abused child to a foster home, a hospital must assign a patient in critical condition to a room, or a city must place a homeless individual into a shelter. We design an online matching algorithm -- the Sequential Equilibrium Mechanism (SE

Renlong Hang, Zihao Xu, Jiuwei Zhao, Runling Yu

Tropical cyclones (TCs) rank among the most destructive natural hazards, yet their forecasting faces fundamental trade-offs: numerical weather prediction (NWP) models are computationally prohibitive and struggle to leverage historical data, while existing deep learning (DL)-based intelligent models are variable-specific and deterministic, which fail to gener

Manoj Madushanka Perera, Adnan Mahmood, Kasun Eranda Wijethilake, Quan Z. Sheng

Recent advancements in Large Language Models (LLMs) have improved their ability to process extended conversational contexts, yet fine-tuning and evaluating short- and long-term memories remain difficult due to the absence of datasets that encode both short- and long-term conversational history. Existing conversational datasets lack memory grounding, overlook

Keshav Sood, Iynkaran Natgunanathan, Purathani Praitheeshan, Praitheeshan Kirupananthan

Protecting sensitive visual content from unauthorized redistribution is a growing challenge for privacy focused mobile applications, including dating platforms. Screenshot prevention mechanisms, rely on server side monitoring or are limited to digital screenshot detection, are commonly deployed to stop forwarding sensitive images. However, an adversary uses

Jie Wu, Ming Gong

LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational policy because the facts needed for correct policy judgment are hidden at decision time. We call this failure mode policy-invisible violations: cases in which compliance depends on entity attributes, contextual st

Yugang Zhang

We define a regular polynomial skew product $(p(z),q(z,w))$ of $\mathbb{C}^2$ of degree $d\geq 2$ to be special if it is triangularly conjugate to a map of the form $(p(z),q(w))$, where $p$ and $q$ are power maps or $\pm$Chebyshev maps, or of the form $(z^d,D_d(w,\zeta z^m))$, where $\zeta^{d-1}=1$, $m\in\{1,2\}$, and $D_d$ is the Dickson polynomial of degre

Dominik Blain

We present COBALT-TLA, a neuro-symbolic verification loop that pairs an LLM with TLC, the TLA+ model checker, in an automated REPL. The LLM generates bounded TLA+ specifications; TLC acts as a semantic oracle; structured error traces are parsed and injected back into the model's context to drive convergence. We evaluate the system against three cross-chain b

Xu Bai, Muhammed Tawfiqul Islam, Chen Wang, Adel N. Toosi

Pipeline parallelism (PP) is widely used to partition layers of large language models (LLMs) across GPUs, enabling scalable inference for large models. However, existing systems rely on static PP configurations that fail to adapt to dynamic settings, such as serverless platforms and heterogeneous GPU environments. Reconfiguring PP by stopping and redeploying

Yankang Liu, Ke Zhang, Maziar Raissi, Roya Zandi

We learn parameterized nonlinear elasticity on curved surfaces using a physics-informed neural network that enforces governing equations and boundary conditions directly through the loss function, enabling a single trained model to represent a continuous family of elastic equilibria across geometric and material parameters. Nonlinear elasticity on curved man

Anes Abdennebi, Nadjia Kara, Laaziz Lahlou

The applications of Generative Artificial Intelligence (GenAI) and their intersections with data-driven fields, such as healthcare, finance, transportation, and information security, have led to significant improvements in service efficiency and low latency. However, this synergy raises serious concerns regarding the security of large language models (LLMs)

William Savage

We present (Experience-Modulated Biologically-inspired Emergent Reasoning), a hybrid cognitive architecture that reorganises the relationship between large language models (LLMs) and memory: rather than augmenting an LLM with retrieval tools, we place the LLM as a replaceable reasoning engine within a persistent, biologically-grounded associative substrate.

Felipe Lara, Alberto Ramos

We develop refined Karush-Kuhn-Tucker (KKT) and Fritz-John (FJ)-type optimality conditions for nonsmooth, nonconvex mathematical pro\-gra\-mming problems. We pay special attention in the case that the functional constraint belongs to a specific class of generalized convex functions known as strongly quasiconvex functions. After analyzing a specialized sub\-d

Xi Wang, Jie Liu, Shuangyan Yang, Jongryool Kim

Memory tiering provides a cost-effective solution to increase memory capacity, utilization, and even bandwidth. Memory tiering relies on system software for memory profiling, detection of frequently accessed pages, and page migration. Such a system software often comes with system parameters. The configurations of those parameters impact application performa

P. Skums

In this study, we investigate the application of Semidefinite Programming (SDP) to phylogenetics. SDP is a powerful optimization framework that seeks to optimize a linear objective function over the cone of positive semidefinite matrices. As a convex optimization problem, SDP generalizes linear programming and provides tight relaxations for many combinatoria

Chandan Akiti, Ajay Modukuri, Murali Nandan Nagarapu, Gunavardhan Akiti

We present Nucleus-Image, a text-to-image generation model that establishes a new Pareto frontier in quality-versus-efficiency by matching or exceeding leading models on GenEval, DPG-Bench, and OneIG-Bench while activating only approximately 2B parameters per forward pass. Nucleus-Image employs a sparse mixture-of-experts (MoE) diffusion transformer architec

Pengrui Lu, Bingyu Xu, Wenjun Zhang, Shengjia Hua

The rapid deployment of AI agents in commercial settings has outpaced the development of evaluation methodologies that reflect production realities. Existing benchmarks measure agent capabilities through retrospectively curated tasks with well-specified requirements and deterministic metrics -- conditions that diverge fundamentally from production environmen

Tim Ellis-Caleo, Timothy Keyes, Nerissa Ambers, Faraah Bekheet

Tumor boards are multidisciplinary conferences dedicated to producing actionable patient care recommendations with live review of primary radiology and pathology data. Succinct patient case summaries are needed to drive efficient and accurate case discussions. We developed a manual AI-based workflow to generate patient summaries to display live at the Stanfo

Anupam Nayak, Baris Askin, Muhammed Ustaomeroglu, Carlee Joe-Wong

Reasoning post-training with reinforcement learning from verifiable rewards (RLVR) is typically studied in centralized settings, yet many realistic applications involve decentralized private data distributed across organizations. Federated training is a natural solution, but scaling RLVR in this regime is challenging: full-model synchronization is expensive,

Parth Parag Kulkarni, Rohit Gupta, Prakash Chandra Chhipa, Mubarak Shah

The task of video geolocalization aims to determine the precise GPS coordinates of a video's origin and map its trajectory; with applications in forensics, social media, and exploration. Existing classification-based approaches operate at a coarse city-level granularity and fail to capture fine-grained details, while image retrieval methods are impractical o

Abed Hammoud

We give a finite-horizon variational formulation that places Bayesian filtering and smoothing, variational data assimilation, KL-regularized control, and Kalman-type methods inside one mathematically explicit hierarchy. For a discrete-time hidden Markov model and any admissible one-step candidate law $q_t$, We prove $J_t(q_t)=\mathbb{E}_{q_t}\!\left[-\log p(

Joel Bierman, Shubdeep Mohapatra, Huiyang Zhou, Yuan Liu

Transferring the information stored in the expansion coefficients of a multi-qubit state to the coefficients of a continuous-variable state is an important protocol for communicating quantum information. It was shown in previous work how to transfer an $n$-qubit state to a single qumode in $\mathcal{O}(2^n)$ time. We show that by transferring this state to $

Shawn Knabel, Tommaso Treu, Michele Cappellari, Simon Birrer

We model the dynamical mass density profiles of 14 strong gravitational lens galaxies from the Sloan Lens ACS (SLACS) sample using spatially resolved kinematics obtained from Keck KCWI integral-field spectroscopy. We use the Jeans Anisotropic Modeling (JAM) method, combining 2D kinematic maps with joint constraints from lens models from Hubble Space Telescop

Saeid Pakravan, Imene Trigui, Wessam Ajib, Wei-Ping Zhu

This paper studies a pinching antenna system (PAS)-assisted hybrid uplink architecture that integrates over-the-air computation (AirComp) and non-orthogonal multiple access (NOMA) to simultaneously support distributed data aggregation and individual communication services. A base station with a dielectric waveguide hosting multiple pinching antennas receives

Alzayat Saleh, Mostafa Rahimi Azghadi

Satellite sea surface temperature (SST) products underpin global coral bleaching monitoring, yet they measure only the ocean skin. Corals inhabit depths from the shallows to beyond 20 metres, where temperatures can be 1-3{\deg}C cooler than the surface; applying satellite SST uniformly to all depths therefore overestimates subsurface thermal stress. We prese

Akan Selim, Siddhartha Ganguly, Ali Pakniyat, Panagiotis Tsiotras

In this paper, we develop a theoretical framework for nonlinear stochastic optimal control problems with optimal stopping by establishing a density-based deterministic representation of the underlying diffusion. For state-independent diffusion, we rewrite the controlled Fokker-Planck equation as a continuity equation driven by a score-corrected velocity fiel

Sebastian Cajas, Ashaba Judith, Rahul Gorijavolu, Sahil Kapadia

Latent diffusion models for medical image super-resolution universally inherit variational autoencoders designed for natural photographs. We show that this default choice, not the diffusion architecture, is the dominant constraint on reconstruction quality. In a controlled experiment holding all other pipeline components fixed, replacing the generic Stable D

Cole Gibson, Wenping Cui, Gautam Reddy

Modern distributed networks, notably transformers, acquire a remarkable ability (termed `in-context learning') to adapt their computation to input statistics, such that a fixed network can be applied to data from a broad range of systems. Here, we provide a complete mechanistic characterization of this behavior in transformers trained on a finite set $S$ of

Luis A. Jiménez Pérez, Antonio Rojas, Genaro Toledo

We explore the sensitivity of the $e^{+} e^{-} \to K^+ K^- 2 \pi^0$ cross section to the magnetic dipole moment (MDM) of the $K^*$ vector meson. We describe the $\gamma^* \to 2K2\pi$ vertex using a vector meson dominance model, including the intermediate resonant contributions relevant for energies below 2.4 GeV. Using BaBar data for this process, we show th

Peter David Fagan

This research note revisits Leibniz's mill, Turing's imitation game, and Searle's Chinese Room through the Conservation-Congruent Encoding (CCE) framework. It formalises a toy symbolic setting in which successful behaviour is measured by task performance ($W_{causal,T}$), while the efficiency with which preserved internal structure supports that

Xiangyu Wang

Training on synthetic data causes model collapse, but existing analyses treat this as single-chain degradation. In reality, the AI ecosystem involves cross-contamination: models ingest synthetic data from other models, produce new synthetic text, and contaminate shared corpora. We propose a bilayer coupled SIR/SIRS framework -- a phenomenological mean-field

Afshan Hashmi

Background: Alzheimer's disease (AD) affects over 55 million people worldwide. Accurate, interpretable detection of normal cognition (NC), mild cognitive impairment (MCI), and AD from routine clinical assessments remains a critical unmet need. Methods: An XGBoost classifier was developed for three-class detection using eight clinical features from the Al

Alexey Tikhonov, Alexey Ivanov

Humor generation remains difficult not only because producing fluent, novel jokes is hard, but because "funny" is audience-dependent and supervision is noisy -- preferences vary with audience, context, and culture, and annotator agreement is often low. In this paper, we describe our system for the SemEval-2026 Task-1 (MWAHAHA), which focuses on humor

Shaowen Chen, Zhicheng Liao, Hongwei Wang

Speculative Decoding (SD) accelerates Large Language Model (LLM) inference by employing a lightweight draft model to propose candidate tokens, which are verified in parallel by the target model, without compromising generation quality. While Retrieval-based Speculative Decoding (RSD) is favored for its plug-and-play versatility, its potential is impeded by r

Wei Tian, Yuhao Zhou, Man Lan

Large Language Model (LLM) based Chinese Grammatical Error Correction (CGEC) systems face two critical challenges: general-purpose models lack specialized linguistic priors for subtle grammatical distinctions, and Supervised Fine-Tuning (SFT) with Maximum Likelihood Estimation fails to optimize for precision-focused metrics, leading to systematic over-correc

Yiliang Zhou, Yawen Guo, Sairam Sutari, Jasmine Dhillon

Ambient artificial intelligence (AI) documentation tools are increasingly deployed to reduce clinician documentation burden, but their implications for biased language in clinical notes remain unclear. We conducted a large-scale comparison analysis of AI drafts and corresponding clinician finalized notes to quantify stigmatizing language changes pre- and pos

Yiliang Zhou, Yawen Guo, Di Hu, Sairam Sutari

Ambient AI documentation systems generate clinical note drafts that clinicians frequently revise before signing off into electronic health records, yet how these edits alter hedging language remains unclear. We conducted paired analysis of clinician-edited portions of ambient AI drafts and final notes to examine (1) whether these edits change the prevalence

Junsoo Park, Youssef Medhat, Htet Phyo Wai, Ploy Thajchayapong

We study how conditioning context shapes personalization behavior in a teacher-facing educational recommender system. We compare contextual conditioning based on the current student question with memory-based conditioning using persistent learner information. Using deviation correlation and paired statistical tests, we find that contextual recommendations ex

Jaeha Oh, Byungchan Kim, Ju Li, Yang Jeong Park

Modern scientific discovery is bottlenecked not by data scarcity, but by the inability to synthesize fragmented knowledge into actionable hypotheses. This challenge is especially acute in battery materials research, where electrochemical performance, interfacial behavior, and manufacturing feasibility must be optimized simultaneously. Here, we present the Mu

Gibson Nkhata, Uttamasha Anjally Oyshi, Quan Mai, Susan Gauch

Personalized Retrieval-Augmented Generation (RAG) relies on accurately selecting user-relevant documents. In practice, existing RAG approaches often suffer from high retrieval costs and overlook that collaborative signals from similar users can enhance personalized generation for the current user. We propose ClusterRAG, a Cluster-Based Collaborative Filterin

Angelo A. Salatino, Ansgar Scherp, Christin Katharina Kreutz, Sahar Vahdati

A Nature survey from 2023 involving 1,600 researchers shows that scientists are ``concerned, as well as excited, by the increasing use of artificial-intelligence tools in research.'' This tension frames our central question: Are researchers being replaced by artificial intelligence? We argue that replacement is already underway-not as disappearance,

Islem Rekik

Perceptions of intelligence shape how learners evaluate and rely on artificial intelligence (AI) systems. Despite rapid advances in AI capabilities, the impact of sustained exposure to these tools on students' valuation of human intelligence (HI) relative to AI remains underexplored. This paper presents a longitudinal analysis of classroom poll responses

Paul Anton Bachmann, Niclas Boehmer, Lukas Daniel Klausner, Martin Lackner

With the growing adoption of AI systems, reasoning about how society can exert control over AI becomes an increasingly urgent problem. Existing work on democratic control largely focuses on macro-level governance. In contrast, we propose a new approach grounded in social choice theory, which we term collective control of artificial intelligence. We argue tha

Sihang Guo, Chenlin Zhou, Jiaqi Wang, Kehai Chen

Spiking Neural Networks (SNNs) offer promising energy-efficient alternatives to large language models (LLMs) due to their event-driven nature and ultra-low power consumption. However, to preserve capacity, most existing spiking LLMs still incur intensive floating-point matrix multiplication (MatMul) and nonlinearities, or training difficulties arising from t

Wojciech Gajek, Max Benke, Andreas Wüstefeld, Andreas Köhler

Distributed Acoustic Sensing (DAS) has emerged as a promising tool for environmental and cryoseismological studies, yet its performance under the extreme conditions of the High Arctic remains poorly documented. Here we report on a multi-season DAS experiment conducted across tundra and glacier environments in Hornsund, Svalbard, using 9\,km of fiber-optic ca

Najmul Hasan

Trusted monitoring, the standard defense in AI control, is vulnerable to adaptive attacks, collusion, and strategic attack selection. All of these exploit the fact that monitoring is passive: it observes model behavior but never probes whether the model would behave differently under different perceived conditions. We introduce the honeypot protocol, which t

Zhiping He, Luigi Ranno, Padraic Burns, Fan Yang

Two-dimensional (2D) wide field-of-view (FOV) beam steering is a key enabling capability for emerging free-space optical systems, including inter-satellite optical links, airborne LiDAR, point-to-point optical wireless communications, and collaborative robotic platforms. These applications require rapid acquisition and tracking across both azimuth and elevat

D. Alfs, D. Grzonka, G. Khatri, P. Kulessa

Spin dependent phenomena in inclusive hadron production have been extensively investigated, yet their microscopic origin and universality across different hadrons are still not fully understood. In particular, it is presently unknown whether antiprotons produced in unpolarized hadronic collisions can acquire a transverse polarization as a result of spin depe

Hryhorii Ovcharenko, Jiri Podolsky

We demonstrate the uniqueness of the spacetimes recently found by us in [H. Ovcharenko and J. Podolsky, Phys. Rev. D 112 (2025) 064076]. First, we prove that the conformal-to-Carter metric ansatz we used therein is the only possible for stationary axisymmetric geometries that are of Weyl type D, with geodesic and shear-free principal null directions (PNDs) w

A. Borghese, M. Armas Padilla, T. Muñoz-Darias

Ultra-compact X-ray binaries (UCXBs) are a subclass of low-mass X-ray binaries (LMXBs) characterised by tight orbits and hydrogen-poor donor stars. We present a spectral and timing study in the hard X-ray band of 11 of the 20 confirmed UCXBs, based on 37 archival NuSTAR observations. Using both X-ray colours and fractional root mean square values, we show th

T. Mkrtchyan, C. Mazzucchelli, R. J. Assef, M. J. Temple

The identification of high-redshift quasars ($z > 4.5$) is critical for studying the early Universe, supermassive black hole growth, and cosmic reionization. Most known high-redshift quasars are located in the northern hemisphere, leaving the southern sky largely unexplored. As part of the 4-meter Multi-Object Spectroscopic Telescope (4MOST) and Chilean AGN/

Shi-Yi Zhao, Xingjiang Zhu, Jacob Cardinal Tremblay, Yiqin Chen

We perform Bayesian targeted searches for continuous gravitational waves from eccentric supermassive binary black holes (SMBBHs) using the Parkes Pulsar Timing Array third data release (PPTA DR3). Six electromagnetically motivated sky directions are analyzed, including the blazar OJ~287 and five nearby galaxy clusters (Virgo, Fornax, Norma, Hercules, and Com

Dainis Dravins, Hans-Günter Ludwig, Matthias Steffen, Carlos Allende Prieto

Finding low-mass planets around solar-type stars requires to understand the physical variability of the host star, which greatly exceeds the planet-induced radial-velocity modulation. Different solar photospheric absorption lines have slightly disparate responses to stellar activity, which should permit to disentangle wavelength shifts induced by exoplanets

M. Galbiati, A. Pensabene, S. Cantalupo, A. Travascio

The formation and evolution of galaxies is regulated by the exchange of gas with the surrounding large-scale structures on circum- and intergalactic scales. Yet, little is known about the complex processes shaping the cycle of baryons in and out of galaxies. In this work, we present a multiline study of the gas surrounding a $z\approx3.66$ quasar known to ho

Ish Kaul, S. Peng Oh

Radiative turbulent mixing layers are widely invoked to explain the survival, growth, and entrainment of cold gas in hot astrophysical flows, but quantitative dynamical tests have remained scarce. RBH-1, the first confirmed runaway supermassive black hole, offers a rare opportunity to test this framework: JWST observations show a 62 kpc tail of cold H$α$ and

Lev Steinberg

We develop a variationally consistent mesoscopic extension of Cosserat elasticity motivated by the breakdown of compatibility in classical formulations. By admitting compatibility-breaking perturbations, the classical theory ceases to remain closed under admissible variations, necessitating an enlargement of the constitutive framework. This leads naturally t

Lauren Niu, Randall D. Kamien

Inspired by the structure of $srs$ Laves networks in $\mathbb{R}^3$ that underpin the celebrated gyroid surface, we construct a Laves network of identical three-coordinated vertices on $S^3$ with double-twist. This network is a subset of the vertices and edges of the 600-cell, and can be viewed as a bipartite graph of disjoint 24-cell vertices inscribed in t

Nafis Fuad Shahid, Maroof Ahmed, Md Akib Haider, Saidur Rahman Sagor

Multimodal federated learning enables privacy-preserving collaborative model training across healthcare institutions. However, a fundamental challenge arises from modality heterogeneity: many clinical sites possess only a subset of modalities due to resource constraints or workflow variations. Existing approaches address this through feature imputation netwo

Mina Ghodsi Yengejeh, Tatiana A. Koryukova, Leonid I. Gurvits, Sándor Frey

VLBI measurements of the sizes of compact extragalactic radio sources, jetted active galactic nuclei, provide data for probing the angular size--redshift relation, offering a complementary test to other distance--redshift methods. We analyse a significantly expanded dataset to reassess the angular size--redshift relation and its potential for constraining co

Pablo Tablas de Paula, Julius O. Smith, Vesa Välimäki, Joshua D. Reiss

Digital waveguide physical modeling offers efficient simulation of acoustic wave propagation as compared to general finite-difference schemes commonly used in computational physics. This efficiency has enabled the real-time implementation of physically modeled musical instruments and sound effects, as well as real-time vocal models and artificial reverberati

D. Van De Putte, K. D. Gordon, K. Misselt, A. N. Witt

We analyze JWST spectroscopy of the northwest filament of NGC7023, where the relatively soft radiation field results in a photodissociation region with an extended atomic hydrogen region, and strongly pronounced variations of the carbonaceous emission band profiles. We focus on the 16.4 and 17.4 um bands and their relation to the main bands at 3.3, 3.4, 5.2,

G. Russano, Y. De Leo, F. Frassati, G. Jerse

Context. Studying the kinematic and dynamic evolution of fast eruptive events from the middle to high solar corona is a primary objective of the Metis coronagraph on Solar Orbiter. During perihelion, Metis acquires visible light images at a 20s cadence, reaching a spatial resolution of around 2000 km at 0.28 au. This enables capturing coronal mass ejections

Indranil Biswas, Subrata Bera, Ujjwal Sen, Indrani Chattopadhyay

The role of complex numbers in quantum theory extends beyond mathematical convenience, having recently been formalized as a resource under the framework of the resource theory of imaginarity. Operationally, imaginarity translates into using fewer resources in optical setups. In this work, we investigate the operational advantage offered by complex-valued mea

Sabyasachi Dash, John Golden, Girish Krishnan

In tendon driven continuum manipulators (TDCMs), reconfiguring the tendon routing enables tailored spatial deformation of the backbone. This work presents a design in which tendons can be rerouted either prior to or after actuation by actively rotating the individual spacer disks. Each disk rotation thus adds a degree of freedom to the actuation space, compl

Shihao Zhang

Altermagnets represent a novel category of magnetic materials characterized by zero net magnetization yet featuring spin-split band structures, and they demonstrate distinctive orbital-spin locking phenomena. Commencing from the minimal multi-orbital tight-binding Hamiltonian of d-wave altermagnets, we conduct an analysis of the general formulas for the thir

Takehito Yokoyama

We propose a mechanism of supercurrent-induced phonon angular momentum in mixed parity superconductors and s-wave superconductors with spin orbit coupling. We derive analytical expressions of phonon angular momentum induced by the supercurrent by perturbative calculation. The physical interpretation of this effect is also discussed.

Gabriel Rabelo-Soares, Gojko Vujanovic, Giorgio Torrieri

The experimental observation of collective behaviour in proton-proton and proton-nucleus collisions poses a fundamental theoretical question regarding the proper characterization of the initial state underlying hydrodynamic evolution. While relativistic hydrodynamics requires an initial condition (IC) characterized by an entropy current, corresponding to a m

Fabrizio Caragiulo, Sergio Scalabrino, Edoardo Voglino

We study the limit behavior of Cahn--Hilliard-type functionals in which the derivative is replaced by higher-order fractional derivatives and modulated by an oscillating factor. Depending on the ratio between the oscillation scale and the interface length, we identify three different regimes and prove $Γ$-convergence in each regime to a suitable sharp-interf

Satish S. Sonkamble, Dharam V. Lal, S. Ilani Loubser, Mahadev B. Pandge

We present a new metal enrichment analysis of a unique galaxy group IC 1262 using archival Chandra and GMRT observations, focusing on metal transport via radio jet, sloshing cold fronts, and shock front. This group shows two sloshing cold fronts along the east and north-west direction which is nearly orthogonal to the north - south orientated radio jet. We r

T. Boismard, M. Rieutord

Context. Be stars are presently viewed as B-type stars surrounded by a disc fueled by the star itself during episodicexcretion events. The origin of these events are poorly understood.Aims. This article aims to determine whether or not surface equatorial Kelvin waves can be unstable and therefore canplay a role in the triggering of the Be phenomenon.Methods.

Tao-Chung Ching, Zhi-Yun Li, Qizhou Zhang, Josep Miquel Girart

Magnetic fields play a fundamental role in the formation of protostellar winds. In the magneto-centrifugal models, poloidal magnetic fields launch winds from accretion disks, and fast-rotating gas twists the fields into toroidal geometry that collimates and accelerates winds through magnetic hoop stress. However, toroidal fields in protostellar winds remain

Parthib Khound

Navigating dense, lane-less traffic remains one of the most challenging scenarios for autonomous vehicles, especially in emerging regions where road structure and driver behavior are highly unpredictable. This paper presents a hybrid control framework tailored for such environments, integrating a $360^\circ$ zone-based perception module with a dual-layer con

Yu Sun, Jue Li, Wei Li, Bo Li

Chiral phonon-polaritonic states are of interest for handedness-dependent light-matter interactions, yet their realization and magnetic control remain challenging, while direct magneto-optical tunability of phonon-polaritonic media is limited. Here, we propose a hybrid platform in which an hBN phonon polariton couples to a chiral bound state in the continuum

Maël Gonin, Oleksii Ivanytskyi, David Blaschke, Günther Hasinger

We review the role of primordial black holes (PBHs) for illuminating the dark ages of the cosmological evolution and as dark matter (DM) candidates. We elucidate the role of phase transitions for primordial black hole formation in the early Universe and focus our attention on the cosmological QCD phase transition within a recent microscopical model. We explo

Riccardo Cesaroni

Variability is a well known phenomenon in low-mass young stellar objects, but in recent years the monitoring of methanol masers and infrared continuum emission has permitted the detection of both burst-like episodes and periodic variations also in high-mass (proto)stars. Multi-epoch studies on large samples of these objects have become possible thanks to the

Antonio Capanema, Pasquale Blasi, Emanuele Sobacchi

Magnetic field amplification is an integral part of the process of particle acceleration at non-relativistic shocks. It is necessary to reach the maximum energies required by observations, especially in supernova remnants, thought to be sources of the bulk of Galactic cosmic rays. Such amplification can be caused by the acoustic instability that develops whe

Sayak Chakrabarty, Souradip Pal

Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic memory and latency budgets. This work demonstrates that it is not only practical but also effective-at academic scale. We release a complete, end-to-end framework that implements industrial-style long-sequen