arXiv preprints from January 1, 2026 through September 23, 2026 — 07:18:55 EST
Determining the biological sex of the individuals who created Upper Paleolithic hand stencils remains a challenging problem due to the absence of ground truth, population differences between contemporary and prehistoric groups, and the uncertainty introduced by image degradation. Traditional morphometric methods suffer from high...
We compute the one-loop effects of vector-like fermions (VLFs) on the Higgs-strahlung cross-section, the flagship precision observable of future $e^+e^-$ Higgs factories such as FCC-ee. We consider four benchmark extensions of the Standard Model (SM): two in which a VL quark (VLQ) or VL lepton (VLL) doublet, together with its singlet...
A mixed identity of a group is a nontrivial word with constants that vanishes under every substitution of its variables. We derive lower bounds for the length of mixed identities in finite simple groups of Lie type, and characterise exactly those families of such groups of bounded rank which satisfy mixed identities of bounded length....
Network datasets in modern applications often involve multiple types of interactions occurring over a shared set of individuals. Characterizing the generating mechanisms of these interactions can be enhanced by joint modelling, as shared vertices allow layers to help explain the structure of other layers. We model multiplex...
We propose an unconventional microscopic origin for the fractional quantum anomalous Hall (FQAH) effect in rhombohedral graphene moiré superlattices: skyrmion fractionalization. We view the state at filling $ν<1$ as a metal of skyrmion vacancies, charge $+e$ objects formed by removing layer-pseudospin skyrmions from the...
We present an initial demographic study of Ly$α$ profiles in little red dots (LRDs) at $z=3$--9 using $R\sim1000$--4000 spectroscopy. Our sample consists of 8 LRDs observed in the VLT/MUSE Deep and Wide surveys and 23 LRDs observed with JWST/NIRSpec grating spectroscopy from JADES, CANUCS, and GO programs including SPURS. We identify...
Vulnerability detection via static analysis traditionally relies on security experts encoding insecure coding patterns into algorithmic rules. However, this approach often focuses on syntactic patterns and overlooks deeper semantic information in the code, such as the meanings of variable and function names. As software systems grow...
As spacecraft become more software-driven and interconnected, onboard flight software is an increasingly important security boundary. Popular flight software architectures often treat onboard components as trusted peers, simplifying integration while limiting internal isolation and access control. We analyze NASA's Core Flight...
Articulated vehicles are the workhorses of freight transportation, and their autonomous navigation is challenging. Their physical characteristics and motion constraints pose significant challenges in manoeuvring these vehicles on narrow routes. This paper presents a spatiotemporal tube-based approach to plan autonomous navigation of...
Interactive game world models typically autoregress visual observations directly in pixel or latent space, forcing structured properties such as pose, geometry, and occlusion to be implicitly maintained by the same generative sequence. Over long horizons, errors in these latent world properties accumulate, making consistency and...
For every constant $2<p<\infty$ and every constant \[ 0<\varepsilon< \min\left\{\frac{p-2}{4p},\frac18\right\}, \] we give a deterministic polynomial-time reduction from 3SAT to $M^\varepsilon$-GapSVP$_p$, where $M$ is the lattice rank. For $p=\infty$, the same holds for every constant $0<\varepsilon<1/8$. The reduction builds on...
This study investigates the methodological and theoretical properties of session handover in applications that use large language models. A task may continue in a new session when the context reaches the model's input limit, when the application restarts, or when another agent is asked to finish the task. The application must then...
Large language model (LLM) agents are increasingly used to modernize the legacy Fortran underlying production scientific software, but validation of these transformations emphasizes nominal executions and may not test whether a modernization preserves the original code's response to faults, perturbations, and reduced precision. We...
We study a general class of gradient interface models with Hamiltonian $H=β\sum V(\nablaφ)$, $β>0$, assuming essentially that the potential $V$ is even, $V'(s)\ge αs$ on $[0,\infty)$ for some $α>0$, and $-M\leq V''\le C$. We establish a Helffer-Sjöstrand representation for these models, and use it to prove that their scaling limits...
In this paper, a quantitative condition for optimality for distributed optimal control problems with box-constraints that are subject to a semilinear elliptic equation is considered. An important property of the investigated optimal control problems is the absence of a Tikhonov regularization. It is well known that at a given control,...
We develop bootstrap-assisted robust binary segmentation (BARBS), a recursive binary segmentation method for multiple change point detection under general nonstationary temporal dynamics. A novel Gaussian multiplier bootstrap for the CUSUM statistics is proposed, offering robustness to complex dependence structures. Through meticulous...
We propose a distributed selective inference framework tailored for high-dimensional quantile regression. To enable valid post-selection inference in this context, we address the computational challenge posed by the non-smooth quantile loss via a response-surrogation strategy. This strategy transforms the problem into a penalized...
Estimating the distribution of relaxation times (DRT) fromelectrochemical impedance spectroscopy (EIS) is an ill-posed inverse problem that is highly sensitive to regularisation choices. We propose a physics-informed convolutional autoencoder that estimates DRT directly from EIS data without spectrum-specific tuning. A discretised...
Causal mediation analysis is typically formulated under no interference, an assumption often violated in networked populations. We develop a nonparametric framework for a single large observed network that allows simultaneous treatment and mediator spillovers and high-dimensional network confounding. Exposure and mediator mappings...
We present the mathematical foundations of linear independent component analysis (ICA) models based on standard literature in a self-contained note. It is aimed at readers with a background in measure-theoretic probability theory. We first develop the theory of the characteristic functions of probability measures on $\mathbb{R}^d$,...
Many operational decisions are sequences of interventions under a cumulative resource limit, such as a maintenance schedule within a crew-hour budget. Choosing among them calls for the outcome and the cumulative cost each would produce, counterfactual quantities identified from observational data. Two strategies with the same expected...
We develop the statistical and algorithmic theory of inverse optimal transport (IOT) under the feature-parameterized cost C_theta(i,j) = -theta^T phi(i,j). The core technical contribution is the Sinkhorn linearization -- the implicit-function sensitivity of the entropic OT plan to the cost -- together with its spectral proxy, a...
Socioeconomic indicators in England exhibit complex spatial patterns that are not well captured by standard approaches based on averages or broad geographic classifications. We propose a method for comparing areas based on their internal spatial structure, using a multiresolution representation derived from the discrete wavelet...
To avoid missing important variables and their connections in networks, more and more variables are included in network analysis. Here we show that in a setting with many more parameters than observations (high-dimensional) it is possible to get a conservative (i.e., low false positive rate) estimate of the neighbourhood for each node...
In the linear regression model, we construct a nonparametric estimate of the regression parameter vector $\boldgreekβ$ that is insensitive to a possible nuisance autoregression in the model errors. The main tool for estimating $\boldgreekβ$ is based on the autoregression rank scores of the model. The resulting estimator is invariant...