arXiv preprints from January 1, 2026 through September 23, 2026 — 17:05:16 EST
This paper describes how the discrete Askey scheme independently arose in Russia and how Askey learned about this. In particular, Askey met main characters in this story, namely Gel'fand and Suslov as well as Nikiforov and Uvarov, during his trip to U.S.S.R, in September 1987. The paper describes this trip in some detail, in...
In this contribution, we summarize our results on the complete NLO predictions for the production of off-shell top quark pairs in the $\ell+j$ channel at the LHC. All NLO QCD and electroweak corrections are consistently included across the full set of LO contributions and partonic subprocesses, while retaining finite-width effects of...
Let $K$ be an algebraically closed field of characteristic $0$ and $G$ a finite abelian group. For a $G$-graded $K$-algebra $A$, we define the primeness property for graded central polynomials: for any graded polynomials $f$ and $g$ in disjoint sets of variables, if $fg$ is graded central, then both $f$ and $g$ are graded central. Let...
A key challenge in network science is the detection of communities, which are sets of nodes in a network that are densely connected internally but sparsely connected to the rest of the network. A fundamental result in community detection is the existence of a nontrivial threshold for community detectability on sparse graphs that are...
Flat bands underlie a diverse range of quantum phenomena, from strongly correlated phases to superconductivity. We theoretically establish that a two-dimensional electron gas under a linear magnetic-field gradient and a transverse electric field exhibits electrically tunable flat bands. At specific field values, these bands become...
Magnetic resonance imaging (MRI) is a cornerstone of clinical neuroimaging, yet conventional MRIs provide qualitative information heavily dependent on scanner hardware and acquisition settings. While quantitative MRI (qMRI) offers intrinsic tissue parameters, the requirement for specialized acquisition protocols and reconstruction...
Deploying LLMs in real-world applications requires controllable output that satisfies multiple desiderata at the same time. While existing work extensively addresses LLM steering for a single behavior, \textit{compositional steering} -- i.e., steering LLMs simultaneously towards multiple behaviors -- remains an underexplored problem....
Manganese-doped tin telluride, Sn(1-x)Mn(x)Te, initially investigated as diluted magnetic semiconductor, has recently attracted considerable attention as a prospective thermoelectric material. The introduction of Mn was found to modify the valence band electronic structure, resulting in an improvement in the Seebeck coefficient and...
Context. Ionisation controls the chemistry, thermal balance, and magnetic coupling in protoplanetary discs. However, standard ionisation vectors such as stellar UV, X-rays, Galactic cosmic rays (GCRs) might not be efficient enough, as UV/X-rays are attenuated rapidly with depth, while GCRs are modulated. Turbulence-induced magnetic...
Vision Language Models (VLMs) are poised to revolutionize the digital transformation of pharmacyceutical industry by enabling intelligent, scalable, and automated multi-modality content processing. Traditional manual annotation of heterogeneous data modalities (text, images, video, audio, and web links), is prone to inconsistencies,...
In this work, we aim to achieve a minimal extension of the quantum-number projected generator coordinate method (PGCM) to describe Gamow-Teller (GT) transition strengths in even-even nuclei and to compute the NME of $2νββ$ decay. Within the PGCM framework, the wave functions of odd-odd nuclei are constructed as superpositions of...
There has been a plethora of microarchitectural-level attacks leading to many proposed countermeasures. This has created an unexpected and unaddressed security issue where naive integration of those defenses can potentially lead to security vulnerabilities. This occurs when one defense changes an aspect of a microarchitecture that is...
This paper investigates zeroth-order (ZO) finite-sum composite optimization. Recently, variance reduction techniques have been applied to ZO methods to mitigate the non-vanishing variance of 2-point estimators in constrained/composite optimization, yielding improved convergence rates. However, existing ZO variance reduction methods...
Light bosonic fields may suffer an instability around a rotating compact object. This process, known as superradiance, leads to the exponential amplification of the field around a black hole or neutron star, while the spin of the central object is correspondingly depleted. The discovery of a highly spinning black hole could therefore...
We study a spatial predator-prey model in which prey can enter a protection zone (refuge) inaccessible to predators, while predators exhibit directed movement toward prey-rich regions. The directed movement is modeled by a far-sighted population flux motivated by classical movement rules, in contrast to the more commonly analyzed...
Reinforcement learning with verifiable rewards (RLVR) has proven effective in enhancing the reasoning of large language models (LLMs). Monte Carlo Tree Search (MCTS)-based extensions improve upon vanilla RLVR (e.g., GRPO) by providing tree-based reasoning rollouts that enable fine-grained and segment-level credit assignment. However,...
Building efficient and effective generative models for neural network weights has been a research focus of significant interest that faces challenges posed by the high-dimensional weight spaces of modern neural networks and their symmetries. Several prior generative models are limited to generating partial neural network weights,...
Scientific reviews are central to knowledge integration in materials science, yet their key insights remain locked in narrative text and static PDF tables, limiting reuse by humans and machines alike. This article presents a case study in atomic layer deposition and etching (ALD/E) where we publish review tables as FAIR,...
Large language models (LLMs) have been shown to be persuasive across a variety of contexts. But it remains unclear whether this persuasive power advantages accuracy, or if bad actors can just as easily use LLMs to promote misbeliefs. Here, we investigate this question across four experiments in which participants (N = 3996 Americans)...
Optimal configuration of the learning rate (LR) is a fundamental yet formidable challenge in large-scale pre-training. Given the stringent trade-off between training costs and model performance, the pivotal question is whether the optimal LR can be accurately extrapolated from low-cost experiments. In this paper, we formalize this...
The launch of relativistic jets of plasma on astrophysical to cosmological scales is observed in a variety of astrophysical sources, from active galactic nuclei to X-ray binaries. While these jets can be reproduced by general relativistic magneto-hydrodynamics (GRMHD) and particle-in-cells (GRPIC) simulations of the dynamical Kerr...
Large Language Model (LLM) inference is hard. The autoregressive Decode phase of the underlying Transformer model makes LLM inference fundamentally different from training. Exacerbated by recent AI trends, the primary challenges are memory and interconnect rather than compute. To address these challenges, we highlight four...
Quantum thermometry provides a key capability for nanoscale devices and quantum technologies, but most existing strategies rely on probes initialized near equilibrium. This equilibrium paradigm imposes intrinsic limitations: sensitivity is tied to long-time thermalization and often cannot be improved in fast, noisy, or nonstationary...
Inverse optimization (IO) algorithms are used in GYN HDR brachytherapy planning, with user parameter settings embedded in commercial TPS. To examine the dosimetric influence of hidden input parameters in three IO algorithms-IPSA, HIPO, and MCO-for GYN HDR brachytherapy across two applicator types. In-house implementations of IPSA,...
Assuming that P is not equal to NP, the worst-case run time of any algorithm solving an NP-complete problem must be super-polynomial. But what is the fastest run time we can get? Before one can even hope to approach this question, a more provocative question presents itself: Since for many problems the naive brute-force baseline...