arXiv preprints from January 1, 2026 through September 23, 2026 — 17:28:36 EST
Geometric scaling was conjectured and observed at the ISR more than 50 years ago. We argue that it still holds at the LHC. We show that the dip-bump structures of the differential elastic cross-sections exhibit a remarkable regularity, namely that the ratio of the bump to dip positions is constant from 23 GeV to 13 TeV. Using crossing...
To address the escalating energy and latency demands of machine-learning workloads, we introduce a blueprint for an energy-efficient and fast thermodynamic computing stack that leverages stochastic analog processes in physical hardware. In this work, we focus on energy-based thermodynamic computing where the stochastic process is well...
This study introduces a vision-language pipeline that detects risky driving behaviors and generates emotionally expressive responses to support driver awareness and comfort. Although vision-language models have advanced perception and reasoning in autonomous driving, existing systems rarely consider the emotional dimension or...
Ferroelectric materials are promising platforms for controllable photonic devices because of the strong coupling between their spontaneous polarization and optical properties. Yet, these materials remain challenging to design because of the close connection between the ferroelectric domain structure and optical response, which no...
Inspired by Wigner's classification of elementary particles as irreducible unitary representations of a spacetime symmetry group, we ask what group can give rise in this way to the quantum states of a particle dressed with clouds of infrared gauge bosons. We show that the answer is given by standard asymptotic symmetries (such as BMS...
In many applications of matching, the point clouds to be matched are not merely unstructured sets of points but rather samples from distributions with an intrinsic cluster structure. In such cases, as individual points are often interchangeable within a coherent region, finding a robust region-to-region alignment is more desirable...
Reinforcement learning (RL) has recently emerged as a promising feedback control strategy for nonlinear and complex dynamical systems. However, RL algorithms are sample inefficient and require a large number of interaction with the environment to synthesize optimal control strategies. Consequently, applications of RL are typically...
Synthetic optical holography (SOH) introduced holographic reconstruction into scanning optical microscopy, enabling quantitative phase imaging with sequential acquisition and point detection. Here, we extend this concept to the quantum regime by implementing SOH within quantum imaging with undetected light (QIUL). By integrating a...
Connected and Autonomous Vehicles (CAVs) rely on interconnected software and hardware components, including sensors, Electronic Control Units, in-vehicle infotainment systems, and telematics units, where vulnerabilities can compromise assets, users, and vehicle operations. These vulnerabilities are commonly documented as plain text in...
Neutron-rich Si isotopes represent a unique case of shell evolution, exhibiting a robust shell closure at $N=20$ and pronounced quadrupole collectivity at $N = 28$. We report lifetime measurements of excited states in $^{40}$Si and the first simultaneous lifetime and heavy-ion inelastic-scattering measurements in $^{41}$Si. In...
Open-vocabulary 3D maps let robots answer language queries about what and where, but they assume a static world and cannot answer queries about how scene elements behave. We introduce Vision-Language-Motion Maps (VLMM), an open-vocabulary, natural-language-queryable 3D map in which each element carries a fused motion attribute: a...
The modern manufacturing industry is investing in new technologies such as the Internet of Things (IoT), big data analytics, cloud computing and cybersecurity to cope with system complexity, increase information visibility, improve production performance, and gain competitive advantages in the global market. These advances are rapidly...
We disprove the conjecture that every globally asymptotically stable homogeneous polynomial vector field admits a homogeneous polynomial Lyapunov function. The counterexample is a planar homogeneous cubic polynomial vector field with integer coefficients. It admits no positive definite homogeneous polynomial with nonpositive Lie...
The optical morphologies of low-mass galaxies can be used to directly trace their assembly and constrain models of galaxy evolution. We select a sample of 6211 low-mass ($7\lesssim {\rm log}(M_{\ast}/M_{\odot})\lesssim 10$) star-forming galaxies from the SAGAbg catalog that has high-completeness at low-redshifts ($z<0.1$). We obtain...
Muon is competitive with AdamW in large-scale pre-training, but its value for reinforcement-learning (RL) post-training remains unclear. We study vanilla Muon in sparse-reward agentic RL through matched single-seed comparisons with AdamW on ALFWorld using Qwen2.5-0.5B-Instruct. Under Group-in-Group Policy Optimization (GiGPO),...
Production LLM-agent frameworks ship control primitives -- human-in-the-loop approval gates, run cancellation, and execution timeouts -- whose names and documentation imply barrier semantics: while a run is paused, cancelled, or timed out, no gated side effect executes. This contract holds on none of six widely used open-source...
The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatial Foundation Models (GeoFMs), which are artificial intelligence/machine learning (AI/ML) models pre-trained on massive geospatial datasets through varied methodologies. We first...
Unequal availability of human preference data across languages poses a significant challenge for aligning large language models in multilingual settings. To address the lack of sufficient data in low-resource language alignment, we propose a meta-learning framework for Reinforcement Learning from Human Feedback and Direct Preference...
The covariant density functional theory in a three-dimensional lattice space is extended to the PCF-PK1 functional with localized exchange terms and is employed to study the nuclear shape evolution of even-even Ra isotopes. Well-developed axial octupole deformations are found for the ground states of $^{222-228}$Ra with no evidence of...
Long-term persona agents must remain identifiable while adapting to new events, relationships, evidence, and social conditions. We identify self-locking as a runtime failure mode in continuing persona-life loops: locally plausible events keep appearing while the generated life collapses toward familiar environments, weak...
In this paper, we establish an analogue of the Kővari-Sós-Turán Theorem for $\operatorname{GF}(q)$-representable matroids. For $2\leq s\leq t$, we show that if $M$ is a rank-$n$ simple $\operatorname{GF}(q)$-representable matroid having no $M(K_{s,t})$-restriction, then \[ |E(M)|=O_{q,s,t}\bigl(q^{(1-1/s)n}\bigr). \] In particular,...
An LLM-as-judge score can move even when the candidate responses stay fixed, simply because the evaluator has changed. We treat this evaluator-replacement ambiguity as a measurement-validity problem. Across four judgment datasets, we compare two upgrade paths available in practice: scaling Qwen3 dense judges from 1.7B to 32B...
This paper introduces Actor as Its Own Critic, a unified reinforcement learning framework, Cycle Group Relative Policy Optimization (CycleGRPO), that jointly optimizes region understanding and localization for Multimodal Large Language Models (MLLMs). Unlike existing separate pipelines, we leverage the inherent duality between the two...
Few-shot spheroid segmentation must adapt to new cell lines, microscopes, and illumination conditions from only a small set of annotated images. While foundation few-shot segmenters can be accurate, their large opaque backbones make it difficult to understand which visual cues drive success or failure. We study this question with...
The minimum spanning tree (MST) problem is one of the most basic optimization problems on metric spaces and graphs. We study the problem of computing a $(1+ε)$-approximation to the MST of an $n$-point metric space $(X, \mathbf{d})$ of doubling dimension $\mathrm{ddim}$. In doubling metrics, previous deterministic algorithms incur a...