April 2026 arXiv papers — page 88

Francisco Prada, Peter Behroozi, Tomoaki Ishiyama, Enrique Pérez

We show that the rest-frame UV statistics and global properties of galaxies at 7 <= z <= 14 are naturally reproduced within the standard {\Lambda}CDM framework when galaxy formation is modeled with UniverseMachine applied to the high-resolution Uchuu N-body simulation. Our model matches the UV luminosity functions over five magnitudes and reproduces the evol

Mahesh Herath, Nicolas B. Cowan, Charles-Édouard Boukaré, Mathieu Dumberry

Lava planets likely did not form in their current orbits, instead migrating inward via orbital decay, which influenced the evolution of their magma oceans. We introduce a coupled thermal-orbital evolution model to explore how rocky planets migrate from the inner edge of the protoplanetary disk, with periods of 1-10 days, to orbital periods of less than a day

Daniel Gavilan-Martin, Grzegorz Łukasiewicz, Vincent Schäfer, Mikhail Padniuk

We demonstrate dynamical control of the effective spin-spin interaction, dominated by Fermi-contact interaction, in a hybrid spin system via parametric modulation. We show that, in an alkali-noble-gas comagnetometer, periodic modulation of the direction of the electron spin polarization with respect to the nuclear polarization leads to a Floquet-induced reno

Georgios Karikos, Jayana A. Saes, Pratik Wagle, Nicolás Yunes

Black-hole ringdown offers a clean probe of strong gravity, but one of its most accurate tools--Leaver's continued-fraction method--requires a three-term recurrence relation. Beyond general relativity, and more generally in non-Kerr spacetimes, Frobenius expansions of the perturbation equations generically produce higher-order recurrence relations and, often

P. V. Athira, Ashik H, Priyadarshi Paul

On an unstable D-brane, the rolling of the tachyon away from the maximum of its potential is described by time-dependent solutions in string theory. Subsequent analysis leads to an understanding of physics around the tachyon vacuum in terms of an effective field theory. The classical solutions of this effective field theory in the late time limit are in one-

Robert V. Harlander, Yannick Kluth, Jonas T. Kohnen, Henry Werthenbach

We develop a perturbative formulation of the Ricci flow in gravity. Following steps analogous to the gradient flow in QCD, we supplement the usual Feynman rules for perturbative gravity by flowed propagators and vertices as well as graviton flow lines which describe the evolution of gravity along the Ricci flow. By calculating vacuum expectation values of a

Nicolas Grimbaum Yamamoto, Thomas Hambye

High energy neutrinos can be injected in the early Universe from the decay or annihilation of long lived primordial relics. We analyse the possibility that the ultrahigh energy neutrino event recently observed by the KM3NeT neutrino telescope could have such an origin. This possibility has the advantage of leading to a sharp spectral feature in a way that th

Aleksandra Olejak

The recent O4a release from the LIGO-Virgo-KAGRA collaboration, which significantly increased the number of gravitational-wave (GW) detections, reveals features with potentially important astrophysical implications. One notable example is a hint of the so-called pair-instability mass gap. In particular, the observed decline in the number of black holes (BHs)

Marta Bucca, Akash Jain, Márk Mezei, Alexey Milekhin

The SYK model has played an important role in recent developments in many-body quantum chaos. We study a spatially local generalisation of it: the SYK lattice. Starting from the nonlinear action of pseudo-Goldstone bosons that dominate its dynamics at low temperatures, in the long wavelength limit we reorganise this action as the effective field theory for f

Shivam Gola, Akash Kumar Saha, Manibrata Sen

We investigate the sensitivities of upcoming MeV gamma-ray telescopes to sterile neutrino dark matter in the mass range $(0.2-100)\,{\rm MeV}$. Sterile neutrinos in this regime can produce observable photon signals through radiative two-body decays and three-body decays with final-state radiation. We perform a Fisher forecasting analysis incorporating realis

Jacob L. Bourjaily, Michael Plesser, Philip Velie

We describe the implementation and usage of `fermionic_amplitudes.m', a Mathematica package for the computation of tree amplitudes involving arbitrary numbers of gauge bosons and arbitrarily-charged massless fermions of (possibly) distinct flavours in pure (non-supersymmetric) gauge theory. These are given in terms of a basis of partial amplitudes involving

D. Kakkad, Y. Song, T. S. -Y. Lai, L. Armus

Studying the content and distribution of molecular gas provides key insights into how feedback from Active Galactic Nuclei (AGN) and star formation influences galaxy evolution, since molecular gas is the primary fuel for star formation. Ultra-Luminous Infrared Galaxies (ULIRGs) are ideal candidates to study how AGN and/or starbursts affect the interstellar m

Luiz H. Santos

Hybrid systems where a quantum material strongly couples to a nonlocal cavity photon mode have emerged as a new frontier for controlling and probing quantum correlations, yet the structure and scaling of light-matter entanglement produced by the nonlocal coupling remains poorly understood. We address this problem through an exactly solvable framework based o

Heming Zhu, Guoxing Sun, Marc Habermann

Building photorealistic, animatable full-body digital humans remains a longstanding challenge in computer graphics and vision. Recent advances in animatable avatar modeling have largely progressed along two directions: improving the fidelity of dynamic geometry and appearance, or reducing computational complexity to enable deployment on resource-constrained

S. L. Skornyakov, V. I. Anisimov, A. A. Katanin

By employing a combined method of density functional theory and dynamical mean field theory (DFT+DMFT) we investigate the effect of electronic correlations on the magnetic and superconducting properties of the iron-based parent compound LaFeAsO. We find that the static non-local susceptibility $\chi({\bf q})$ exhibits a peak at the in-plane wave vector ${\ma

Samuel Goldstein, Kendrick M. Smith, Utkarsh Giri, Moritz Münchmeyer

We present a method to estimate non-Gaussian power spectrum covariance matrices by directly measuring the response of the small-scale power spectrum to long-wavelength perturbations via bispectrum and trispectrum estimators. Specifically, we derive estimators for the complete non-Gaussian matter power spectrum covariance, including the super-sample contribut

Liubomyr Horbatko

Modern sequence modeling is dominated by two families: Transformers, whose self-attention can access arbitrary elements of the visible sequence, and structured state-space models, which propagate information through an explicit recurrent state. These mechanisms face different limitations on long contexts: when attention is diffuse, the influence of individua

Joshua T. Roth, Joel D. Hartman, Gáspár Á. Bakos, Samuel W. Yee

The T16 project has produced a uniformly detrended and systematics-corrected set of 83,717,159 TESS Cycle 1 full-frame image light curves for stars observed by TESS in its primary mission down to T=16 mag, enabling sensitive transit searches beyond the official TESS pipelines. While most existing TESS planet searches focus on relatively bright targets, plane

Yunke Ao, Le Chen, Bruce D. Lee, Assefa S. Wahd

Proximal Policy Optimization (PPO) has become the predominant algorithm for on-policy reinforcement learning due to its scalability and empirical robustness across domains. However, there is a significant disconnect between the underlying foundations of trust region methods and the heuristic clipped objective used in PPO. In this paper, we bridge this gap by

Arindam Biswas

We study a chromatic theory of asymptotic approximate groups for tuples of subsets of abelian groups, combining Nathanson's chromatic sumset formalism with asymptotic covering ideas from approximate group theory. This framework encodes simultaneous additive growth across several color classes. We show some general lifting and invariance principles, establish

Aditya Arora, Akshita Gupta, Pau Rodriguez, Marcus Rohrbach

Story Visualization aims to generate a sequence of images that faithfully depicts a textual narrative that preserve character identity, spatial configuration, and stylistic coherence as the narratives unfold. Maintaining such cross-frame consistency has traditionally relied on explicit memory banks, architectural expansion, or auxiliary language models, resu

Salman Rahman, Jingyan Shen, Anna Mordvina, Hamid Palangi

Large language models have achieved significant reasoning improvements through reinforcement learning with verifiable rewards (RLVR). Yet as model capabilities grow, constructing high-quality reward signals becomes increasingly difficult, making it essential to understand when RLVR can succeed under weaker forms of supervision. We conduct a systematic empiri

Savya Khosla, Sethuraman T, Aryan Chadha, Alex Schwing

Despite recent progress, vision-language encoders struggle with two core limitations: (1) weak alignment between language and dense vision features, which hurts tasks like open-vocabulary semantic segmentation; and (2) high token counts for fine-grained visual representations, which limits scalability to long videos. This work addresses both limitations. We

Florian Grube

We provide a simple and direct proof of a strong-type unique continuation principle for the fractional $p$-Laplacian $(-\Delta_p)^s$ for a range of $s$ and $p$. The result extends to strong solutions of the fractional nonlinear Schr\"odinger equation. We adapt the recent proofs of the weak UCP by Berger, Schilling and Prasad.

Andrew Zhang, Tong Ding, Sophia J. Wagner, Caiwei Tian

Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clinical record into a unified patient representation. We introduce Apollo, a multimodal temporal foundation model trained and evaluated on over three decades of longitudinal hospital records from a major US hospit

Maria-Eleni Sfyraki, Jun-Kun Wang

In this work, we revisit the problem of active sequential prediction-powered mean estimation, where at each round one must decide the query probability of the ground-truth label upon observing the covariates of a sample. Furthermore, if the label is not queried, the prediction from a machine learning model is used instead. Prior work proposed an elegant sche

Javier Carvajal-Rojas, Axel Stäbler

We introduce a framework for pulling back Cartier modules and their associated invariants along regular $F$-finite morphisms. To achieve this, we construct a relative Cartier isomorphism and operator for an arbitrary regular $F$-finite map of locally noetherian schemes. As an application, we obtain new results on the constancy regions of mixed test ideals, b

Manan Gupta, Dhruv Kumar

Large language models frequently commit unrecoverable reasoning errors mid-generation: once a wrong step is taken, subsequent tokens compound the mistake rather than correct it. We introduce $\textbf{Latent Phase-Shift Rollback}$ (LPSR): at each generation step, we monitor the residual stream at a critical layer lcrit, detect abrupt directional reversals (ph

Terry Leitch

We present a systematic evaluation of large language model families -- spanning both proprietary cloud APIs and locally-hosted open-source models -- on two purpose-built benchmarks for System Dynamics AI assistance: the \textbf{CLD Leaderboard} (53 tests, structured causal loop diagram extraction) and the \textbf{Discussion Leaderboard} (interactive model di

Jiaze Li, Leto Peel

Community structure is prevalent in real-world networks, with empirical studies revealing heterogeneous distributions where a few dominant majority communities coexist with many smaller groups. These small-scale groups, which we term minority communities, are critical for understanding network organization but pose significant challenges for detection. Here,

Haoyu Wu, Jiwen Yu, Yingtian Zou, Xihui Liu

Video world models have achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled as action-conditioned video generation models that take historical frames and current actions as input to predict future frames. Yet, most existing approaches are limited to single-agent scenarios and fail to ca

Tatsuki Kuribayashi, Alex Warstadt, Yohei Oseki, Ethan Gotlieb Wilcox

A recent study (Kuribayashi et al., 2025) has shown that human sentence processing behavior, typically measured on syntactically unchallenging constructions, can be effectively modeled using surprisal from early layers of large language models (LLMs). This raises the question of whether such advantages of internal layers extend to more syntactically challeng

Rui Qian, Chuanhang Deng, Qiang Huang, Jian Xiong

Reasoning segmentation requires models to ground complex, implicit textual queries into precise pixel-level masks. Existing approaches rely on a single segmentation token $\texttt{<SEG>}$, whose hidden state implicitly encodes both semantic reasoning and spatial localization, limiting the model's ability to explicitly disentangle what to segment from where t

S. Brendle, Y. Wang

We describe how the spacetime positive energy theorem in dimension $n \geq 4$ follows from our recent work on the Riemannian version of the positive mass theorem. Our proof builds on the fundamental work of Schoen and Yau and the remarkable work of Eichmair, and uses the Jang equation with a capillary term. We also use the shielding principle from the work o

Minji Lee, Colin Kalicki, Minkyu Jeon, Aymen Qabel

Models from the AlphaFold (AF) family reliably predict one dominant conformation for most well-ordered proteins but struggle to capture biologically relevant alternate states. Several efforts have focused on eliciting greater conformational variability through ad hoc inference-time perturbations of AF models or their inputs. Despite their progress, these app

Lucas D'Alimonte, Loïc Gassmann

We prove that, in the FK-percolation model, the probabilities of local events are uniformly analytic in the percolation parameter $p$ under suitable mixing assumptions on the measure, and satisfy a uniform exponential growth bound. This result allows us to prove that the magnetisation of the Potts model is analytic in a suitable range of parameters, includin

Ran Ben-Basat, Yaniv Ben-Itzhak, Gal Mendelson, Michael Mitzenmacher

This note clarifies the relationship between the recent TurboQuant work and the earlier DRIVE (NeurIPS 2021) and EDEN (ICML 2022) schemes. DRIVE is a 1-bit quantizer that EDEN extended to any $b>0$ bits per coordinate; we refer to them collectively as EDEN. First, TurboQuant$_{\text{mse}}$ is a special case of EDEN obtained by fixing EDEN's scalar scale para

Amanda Maria Petcu

A conjecture of Simon Donaldson is that on a compact $4$-manifold $X^4$ one can flow from a hypersymplectic structure to a hyperk\"ahler structure while remaining in the same cohomology class. To this end the hypersymplectic flow was introduced by Fine-Yao. In this paper the notion of a positive triple on $X^4$ is used to describe a hypersymplectic and hyper

R Gajewski, RT Desai, B Hnat, D Lin

Measuring field-aligned currents (FACs) using magnetic field observations provides a powerful means to probe the multi-scale interactions between the magnetosphere, ionosphere and thermosphere. In this study, we apply the curlometer technique to Swarm spacecraft observations and to simulations of the coupled magnetosphere-ionosphere system. We begin by corre

Zhiyuan Chen, Love Jayesh Ahir, Ahmad Suleiman, Kundi Yao

Privacy policies are intended to inform users about how software systems collect and handle data, yet they often remain vague or incomplete. This paper presents an empirical study of patterns in log-related statements within privacy policies and their alignment with privacy disclosures observed in Android application logs. We analyzed 1,000 Android apps acro

Charles Igel, Jeremy Mancinas, Juan Villarreal

This work is motivated by recent developments in celestial holography. In \cite{CP}, the authors interpreted QCD collinear singularities in terms of operator product expansions in a two-dimensional CFT. We reformulate the algebraic structures arising in their work using the formalism of non-linear Lie conformal algebras developed in \cite{SK}.

Anders Rantzer

An explicit solution is derived for the Bellman inequality corresponding to minimax optimal dual control. The minimizing player determines control action as a function of past state measurements and inputs. The maximizing player selects disturbances and model parameters for the underlying linear time-invariant dynamics. The optimal minimizing policy is a dua

Qihang Fan, Huaibo Huang, Mingrui Chen, Hongmin Liu

In recent years, the Vision Transformer (ViT) has garnered significant attention within the computer vision community. However, the core component of ViT, Self-Attention, lacks explicit spatial priors and suffers from quadratic computational complexity, limiting its applicability. To address these issues, we have proposed RMT, a robust vision backbone with e

William Lavery, Jodie A. Cochrane, Christian Olesen, Dagim S. Tadele

Physics-informed neural networks (PINNs) provide a powerful framework for learning governing equations of dynamical systems from data. Biologically-informed neural networks (BINNs) are a variant of PINNs that preserve the known differential operator structure (e.g., reaction-diffusion) while learning constitutive terms via trainable neural subnetworks, enfor

Joonhyuk Lee, Virginia Ma, Sarah Zhao, Yash Nair

Verification of model outputs is rapidly emerging as a key primitive for both training and real-world deployment of large language models (LLMs). In practice, this often involves using imperfect LLM judges and reward models since ground truth acquisition can be time-consuming and expensive. We introduce Fully Unsupervised Score Ensembling (FUSE), a method fo

Gergely Ambrus, Dorottya Dancsó

We call a cell $C \subset \mathbb{R}^d$ soft if every point of its boundary lies on a smooth curve contained in $\partial C$. A tiling of the space is called completely soft if all of its cells are soft. In their 2024 article, Domokos, Goriely, G. Horváth and Regős conjectured that every polyhedral tiling of $\mathbb{R}^3$ satisfying mild regularity assumpti

Vjekoslav Kovač, Adian Anibal Santos Sepčić

We study density thresholds that force a measurable set $E\subseteq\mathbb{R}^d$ to contain all sufficiently large similar copies of every $n$-point configuration. We prove a lower bound of the form $1-O((\log n)/n)$, which matches the known upper bound up to the logarithmic factor, thus essentially resolving a problem posed by Falconer, Yavicoli, and the fi

Mingsheng Tian, Zhen Bi, Thomas Iadecola, Bryce Gadway

Preparing correlated quantum states is essential for emerging technologies, but remains challenging in many-body systems. Here we propose a dissipative protocol that engineers nonreciprocal, energy-selective transitions to steer dipolar quantum systems toward desired many-body states. This is realized by introducing two types of controllable dissipative auxi

Andre Mas, Fatma Terzioglu, Ilse C. F. Ipsen

We highlight the important role of the Fourier transform in deriving inversion formulas for the integral transforms of tomographic imaging. We demonstrate this principle by deriving inversion formulas for the divergent beam transform and the V-line transform, the latter arising in contemporary models of single-scattering optical tomography.

Leon Bungert, Lucas Schmitt

Adversarial training of binary classifiers can be reformulated as regularized risk minimization involving a nonlocal total variation. Building on this perspective, we establish a characterization of the subdifferential of this total variation using duality techniques. To achieve this, we derive a dual representation of the nonlocal total variation and a rela

Eric Rudolph, Philipp Steigerwald, Jens Albrecht

This paper studies how empirical dialogue-flow statistics can be incorporated into Next Dialogue Act Prediction (NDAP). A KL regularization term is proposed that aligns predicted act distributions with corpus-derived transition patterns. Evaluated on a 60-class German counselling taxonomy using 5-fold cross-validation, this improves macro-F1 by 9--42% relati

Nicholas Gardella, James Prather, Juho Leinonen, Paul Denny

Code-generating Artificial Intelligence has gained popularity within both professional and educational programming settings over the past several years. While research and pedagogy are beginning to cope with this change, computing students are left to bear the unforeseen consequences of AI amidst a dearth of empirical evidence about its effects. Though pair

Tanjim Rahaman Fardin, S M Zunaid Alam, Mahadi Hasan Fahim, Md Faysal Mahfuz

The rapid progress of subject-driven text-to-image synthesis, and in particular DreamBooth, has enabled a consent-free deepfake pipeline: an adversary needs only 4-8 publicly available face images to fine-tune a personalized diffusion model and produce photorealistic harmful content. Current adversarial face-protection systems -- PhotoGuard, Anti-DreamBooth,

Syver Døving Agdestein, Benjamin Sanderse

We present IncompressibleNavierStokes.jl, an open-source Julia package for solving the incompressible Navier--Stokes equations on staggered Cartesian grids. The package features matrix-free, hardware-agnostic kernels that are compiled from a single source for multi-threaded CPU or GPU execution, and hand-written adjoint kernels for all discrete operators, en

Boon Suan Ho

We construct dyadic lacunary counterexamples for two problems of Erd\H{o}s on pointwise behavior of dilates on the circle. The main device is a dyadic spike block: rare positive spikes create long positive runs in the lacunary averages, while a deterministic lower floor prevents cancellation from the remaining stages. The endpoint construction gives a mean-z

Vladimir Kadets, Geivison Ribeiro

For an operator T from X to Y denote m(T) the infimum of $||Tx||$ on the unit sphere $S_X$ of X. A sequence $(x_n)$ in $S_X$ is said to be minimizing for T if $||Tx_n||$ tends to m(T). In 2020 U. S. Chakraborty introduced and studied the following weak minimizing property (WmP): a pair (X,Y) of Banach spaces is said to have the WmP if, for every bounded line

A. Durán

The numerical approximation of some Boussinesq systems in two spatial dimensions is here considered. The differential systems under study are proposed as asymptotic models for the propagation of waves along the interface of two layers of fluids with different densities and subjected to a Boussinesq physical regime in each layer. Well-posedness of the periodi

Zhong-Xia Shang, Daniel Stilck França

The fundamental difference between closed and open quantum dynamics lies in their environmental interaction: closed systems are perfectly isolated and evolve reversibly under unitary Hamiltonian dynamics, whereas open systems continuously couple to an external bath, resulting in irreversible dissipation and information loss. In this work, we show internal Ha

Giuseppe De Giacomo, Christian Hagemeier, Daniel Hausmann, Nir Piterman

We study synthesis for obligation properties expressed in LTLfp, the extension of LTLf to infinite traces. Obligation properties are positive Boolean combinations of safety and guarantee (co-safety) properties and form the second level of the temporal hierarchy of Manna and Pnueli. Although obligation properties are expressed over infinite traces, they retai

Mao Lin, Xi Wang, Guilherme Cox, Dong Li

As modern LLMs support thousands to millions of tokens, KV caches grow to hundreds of gigabytes, stressing memory capacity and bandwidth. Existing solutions, such as KV cache pruning and offloading, alleviate these but underutilize hardware by relying solely on either GPU or CPU for attention computing, and considering yet limited CPU local memory for KV cac

Daniel Evans, Yizhi Shen, Ahmad K. Omar

Nonreciprocity, a hallmark of nonequilibrium systems, can generate dynamics not possible near thermodynamic equilibrium, including oscillatory and rotating patterns. The onset of temporal oscillations is often evident in linearized dynamics, where nonreciprocity appears as complex eigenvalues of an asymmetric Jacobian. Here, we show that the topology of open

Yun Jeong Kang, Sung Kyu Seo, Kyungsik Kim

We analytically investigate the diffusive motion inferred from experimental observations of active particles driven by quantum vortices on the surface of superfluid helium. We first study the dynamical behavior of an active particle subject to a viscoelastic memory effect characterized by a power-law kernel. We then analyze the dynamics of an active particle

Abilio Rodrigues, Marcelo E. Coniglio

In this paper we present the first-order logic QLETF+, a quantified version of the logic LETF+, introduced in Coniglio and Rodrigues (Studia Logica 112:561-606, 2024). QLETF+ exhibits several properties that are not always enjoyed by logics equipped with classicality operators. We show that it satisfies the replacement property and admits conjunctive, disjun

Tamás Aladics, Norbert Vándor, Rudolf Ferenc, Péter Hegedűs

Static code analysis (SCA) tools are widely used as effective ways to detect bugs and vulnerabilities in software systems. However, the reports generated by these tools often contain a large number of non-actionable findings, which can overwhelm developers to the point of ignoring them altogether -- this phenomenon is known as "alert fatigue". In this paper,

Sangeeta Rajpurohit, Sheikh Rubaiat Ul Haque, Aaron M. Lindenberg, Peter E. Blöchl

The orbital degree of freedom in rare-earth nickelates is typically inactive across the temperature-driven metal-insulator transition, where the system develops two inequivalent Ni sites associated with Ni-O bond disproportionation and breathing-mode distortions of NiO$_6$ octahedra. Here, we show that orbital polarization can be induced by optical excitatio

Yang Sun, Zhiyuan Ji, Francesco D'Eugenio, Yongda Zhu

We present a statistical census of the Na D-traced neutral interstellar medium (ISM) and outflows in 309 galaxies at $0.6<z<4$ using JWST/NIRSpec medium-resolution grating spectroscopy from the SMILES, JADES, Blue Jay, and Aurora surveys. After subtracting the stellar continuum, we model the Na D $\lambda\lambda 5890, 5896$ \AA and detect neutral ISM absorpt

Aniruddha Adiga, Jingyuan Chou, Anshul Chiranth, Bryan Lewis

Epidemic forecasting has become an integral part of real-time infectious disease outbreak response. While collaborative ensembles composed of statistical and machine learning models have become the norm for real-time forecasting, standardized benchmark datasets for evaluating such methods are lacking. Further, there is limited understanding on performance of

Yanan Du, Sai Xu, Kezhi Wang, Yansha Deng

This paper studies end-to-end latency minimization for a multi-band radar sensing and deep neural network (DNN) inference pipeline. Unlike conventional stage-wise designs that treat radar sensing and DNN inference as two sequential stages, the proposed framework exploits cross-stage parallelism by allowing the inference branch associated with a sensed band t

Difan Jiao, Yilun Liu, Ye Yuan, Zhenwei Tang

Guard models are widely used to detect harmful content in user prompts and LLM responses. However, state-of-the-art guard models rely solely on terminal-layer representations and overlook the rich safety-relevant features distributed across internal layers. We present SIREN, a lightweight guard model that harnesses these internal features. By identifying saf

Tigran Zalinyan, Giovanni Nastasi

We investigate Pauli-consistent ensemble Monte Carlo simulations of graphene with explicit intraband electron-electron scattering. To reduce the cost of electron-electron proposal-rate evaluation, we introduce a sampled-partner approximation that replaces the full partner-cell sum by uniform sampling from the instantaneous ensemble, while leaving the event-l

Tanmoy Pati, Narayan Rana, Alessandro Vicini

We reevaluate the vacuum polarization functions for electroweak gauge bosons at three loops in QCD, employing state-of-the-art perturbative techniques. We apply these results to determine the ${\mathcal{O}}(\alpha \alpha_s^2)$ corrections to the electroweak radiative parameters $\Delta\rho$, $\Delta r$ and $\Delta \kappa$. We improve the accuracy of the calc

Mihai Turinici

The 2015 fixed point result on rs-relational metric spaces due to Alam and Imdad [J. Fixed Point Th. Appl., 17 (2015), 693-702] is equivalent with the classical Banach Contraction Principle [Fund. Math., 3 (1922), 133-181]. This is also valid for the 1961 statement in metric spaces due to Edelstein [Proc. Amer. Math. Soc., 12 (1961), 7-10], or the 2005 fixed

Sauvik Roy, Ram Nandan Kumar, Biswajit Das, Nirmalya Ghosh

A linearly polarized Gaussian beam, carrying zero net spin angular momentum, is conventionally not expected to exert optical torque or induce rotational motion in birefringent microparticles. When such a beam is tightly focused, the constituent left- and right-circular polarization components separate spatially due to spin-orbit interaction, commonly known a

J. G. A. Caribé, M. S. Guimaraes, I. Roditi, S. P. Sorella

It is pointed out that the vertex operators of a chiral boson in 1+1 dimensions provide an explicit realization of dichotomic, bounded, Hermitian operators that saturate the Tsirelson bound of the Bell-CHSH inequality in the vacuum state.

Nitish Shukla, Surgan Jandial, Arun Ross

Vision-Language Models (VLMs) have demonstrated remarkable progress in single-image understanding, yet effective reasoning across multiple images remains challenging. We identify a critical capability gap in existing multi-image alignment approaches: current methods focus primarily on localized reasoning with pre-specified image indices (``Look at Image 3 an

Jochen Schmid, Philipp Seufert, Jan Schwientek, Tobias Seidel

We develop a novel iterative algorithm for locally optimal experimental design under constraints, like budget or performance constraints. It is an adaptive discretization algorithm. In every iteration, a discretized version of the constrained-design problem is solved and then the discretization is adaptively refined by adding an approximate violator of a sui

Md Rysul Kabir, Zoran Tiganj

Open-weight language models can be rendered unsafe through several distinct interventions, but the resulting models may differ substantially in capabilities, behavioral profile, and internal failure mode. We study behavioral and mechanistic properties of jailbroken models across three unsafe routes: harmful supervised fine-tuning (SFT), harmful reinforcement

Xingchen Xiao, Heyan Huang, Runheng Liu, Jincheng Xie

Large language models (LLMs) are widely used in retrieval-augmented generation (RAG) to incorporate external knowledge at inference time. However, when retrieved contexts are noisy, incomplete, or heterogeneous, a single generation process often struggles to reconcile evidence effectively. We propose \textbf{MASS-RAG}, a multi-agent synthesis approach to ret

Ghazal Khalighinejad, Raghuveer Thirukovalluru, Alexander H. Oh, Bhuwan Dhingra

Many recent document embedding models are trained on document-as-image representations, embedding rendered pages as images rather than the underlying source. Meanwhile, existing benchmarks for scientific document retrieval, such as ArXivQA and ViDoRe, treat documents as images of pages, implicitly favoring such representations. In this work, we argue that th

Jun Chen, Umberto Biccari, Junmin Wang

We propose a computational framework for replacing the repeated numerical solution of differential Riccati equations in finite-horizon Linear Quadratic Regulator (LQR) problems by a learned operator surrogate. Instead of solving a nonlinear matrix-valued differential equation for each new system instance, we construct offline an approximation of the associat

Antonio Ferrer-Sánchez, Yolanda Vives-Gilabert, Yue Ban, Xi Chen

Quantum Fisher Information (QFI) sets the ultimate precision limit for parameter estimation and is therefore a central quantity in quantum metrology. In time-dependent many-body systems, however, maximizing QFI is a highly non-trivial task due to the combined effects of non-commutativity, control complexity, and the exponential growth of the Hilbert space. I

Huchen Yang, Xinghao Dong, Jinlong Wu

Bayesian experimental design (BED) for complex physical systems is often limited by the nested inference required to estimate the expected information gain (EIG) or its gradients. Each outer sample induces a different posterior, creating a large and heterogeneous set of inference targets. Existing methods have to sacrifice either accuracy or efficiency: they

Jean-Baptiste Jolly, Linda J. Tacconi, Reinhard Genzel, Roberto Neri

We present NOEMA3D, a unique high-resolution study of purely molecular gas kinematics at $z \sim 1.1$ to 1.6, providing a dedicated view of cold gas dynamics at the late stages of the peak epoch of cosmic star formation. Using deep ($> 20$ hr on source per target) IRAM-NOEMA CO observations of 10 massive ($10.45 < \log(M^*/M_\odot) < 11.43$)) main-sequence g

Christoph Burtscher, Mateusz Dolata

Because artificial intelligence (AI) increasingly mediates organizational work, fairness has become a critical governance challenge. Existing frameworks often prioritize abstract ethical principles rather than fairness-specific ones and lack actionable guidance across the entire AI lifecycle. This study addresses the principles-to-practice gap in AI fairness

Zetian Chen, Noa Mazurski, Uriel Levy

Nonlinear metasurfaces provide a route to compact frequency conversion by replacing phase matching and long interaction lengths with resonantly enhanced light matter interaction in subwavelength structures. Extending this capability to continuous wave (CW) operation is particularly important for applications requiring narrow linewidth, stable frequency, and

Terence Lim, Kumar Muthuraman, Michael Sury

We introduce a multi-agent framework intended to emulate parts of a quantitative research team and support equity factor research on large financial panel datasets. QRAFTI integrates a research toolkit for panel data with MCP servers that expose data access, factor construction, and custom coding operations as callable tools. It can help replicate establishe

Abhijit Banerjee, Trevor J. Hall

Injection locking of optoelectronic oscillators (OEOs) with large delay gives rise to phase dynamics that lie beyond the scope of classical single mode locking theory, including the spontaneous formation of persistent $2\pi$ phase kinks. In this work, a multiscale theoretical framework is developed that explains the origin, structure, and stability of these

Anuj Jakhar, Mahesh Kumar Ram

We develop an algebraic framework over arbitrary quadratic fields $L = \mathbb{Q}(\sqrt{D})$ to generalize the Miller-Rabin primality test. Consequently, we present a deterministic primality test for integers of the form $N = K p^{\ell} - 1$ that requires only a single modular exponentiation and achieves a computational complexity of $\tilde{\mathcal{O}}(\lo

Ping Zeng, Yicheng Zeng, Lixing Zhu

Determining the number of factors in high-dimensional factor models remains a fundamental challenge, particularly when data are incomplete. This paper introduces the concept of identifiable factors, those that can be reliably recovered despite missing observations, and proposes the Missingness-Adaptive Thresholding Estimator (MATE). To our knowledge, MATE is

Lian Zhou, Kaiwen Xue, Yun-Jhu Lee, Chun-Ho Lee

High-performance computing underpins modern artificial intelligence (AI), enabling foundation models, real-time inference and perception in autonomous systems, and data-intensive scientific simulations. Recent advances in quantization techniques utilizing low-precision computation without degrading model accuracy, create new opportunities for analog photonic

Tanya Keshari, Debasis Sadhukhan

We simulate a long-range extended Ising model in one dimension using a hybrid quantum algorithm, namely Variational Quantum Eigensolver (VQE). In this quantum simulation, we investigate how quantum resources scale with system size and interaction strength. Three structure-aware ansatze incorporating nearest-neighbor (NN), next-nearest-neighbor (NNN), and nex

Y. T. Feng

The control of energy dissipation in non-spherical particle contact remains an unresolved problem. Unlike spherical contact, where the interaction reduces to a one-dimensional normal oscillator, both the effective inertia and the effective stiffness depend on the evolving contact geometry, and the impact dynamics are intrinsically coupled across translationa

Zhenwen Liang, Yujun Zhou, Sidi Lu, Xiangliang Zhang

Reinforcement Learning (RL) enhances LLM reasoning, yet a paradox emerges as models scale: strong base models saturate standard benchmarks (e.g., MATH), yielding correct but homogeneous solutions. In such environments, the lack of failure cases causes the advantage signal in group-relative algorithms (e.g., GRPO) to vanish, driving policies into mode collaps

Worachit Amnuaypongsa, Yotsapat Suparanonrat, Pana Wanitchollakit, Jitkomut Songsiri

This paper proposes a multi-step probabilistic forecasting framework using a single neural-network based model to generate simultaneous point and interval forecasts. Our approach ensures non-crossing prediction intervals (PIs) through a model structure design that strictly satisfy a target coverage probability (PICP) while maximizing sharpness. Unlike existi

Nicholas Thumiger, Andrea Bartezzaghi, Mattia Rigotti, Cezary Skura

Computational Fluid Dynamics (CFD) is central to race-car aerodynamic development, yet its cost -- tens of thousands of core-hours per high-fidelity evaluation -- severely limits the design space exploration feasible within realistic budgets. AI-based surrogate models promise to alleviate this bottleneck, but progress has been constrained by the limited comp

Samar M. Magdy, Fakhraddin Alwajih, Abdellah El Mekki, Wesam El-Sayed

Existing MT evaluation frameworks, including automatic metrics and human evaluation schemes such as Multidimensional Quality Metrics (MQM), are largely language-agnostic. However, they often fail to capture dialect- and culture-specific errors in diglossic languages (e.g., Arabic), where translation failures stem from mismatches in language variety, content

Hao Meng, Siyuan Zheng, Shuran Zhou, Qiangqiang Wang

Large Language Models (LLMs) show promise in lyric-to-melody generation, but models trained with Supervised Fine-Tuning (SFT) often produce musically implausible melodies with issues like poor rhythm and unsuitable vocal ranges, a phenomenon we term "constraint violation". To address this, we propose a novel alignment framework that instills musical knowledg

Edvard T. Musaev

In this review branes of string theory are described from three different perspectives: as endpoints of open string, as supergravity backgrounds with BPS properties, as dynamical objects with gauge invariant actions. Based on these descriptions various effects of brane interactions are reviewed: brane bound states, Hanany--Witten and Myers effects, supertube

Marcello Galisai, Susanna Cifani, Francesco Giarrusso, Piercosma Bisconti

The Adversarial Humanities Benchmark (AHB) evaluates whether model safety refusals survive a shift away from familiar harmful prompt forms. Starting from harmful tasks drawn from MLCommons AILuminate, the benchmark rewrites the same objectives through humanities-style transformations while preserving intent. This extends literature on Adversarial Poetry and

Jinghui Lu, Jiayi Guan, Zhijian Huang, Jinlong Li

Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature imposes a latency cost that is prohibitive for real-time deployment. Latent CoT methods attempt to close this gap by compressing reasoning into continuous hidden states, but consistently fall short of their exp