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Mathematics & Statistics
New mathematics and statistics is posted on arXiv, often long before it appears in a journal. This page shows the newest papers ReadSearch has read, from algebra and geometry to analysis, probability and applied mathematics.
The newest 1,000 papers, from 13 October 2026 to 5 November 2026: 968 arXiv preprints and 32 OpenAlex records.
Newest papers, page 45
Graph-Regularized Synthetic Control for Stable Counterfactual Estimation under Donor Redundancy
Synthetic control methods estimate counterfactual outcomes by weighting untreated donor units to match a treated unit before treatment.lepidoptera: A Domain-Agnostic Engine for Causal Simulation with Mixed Variable Types, Vine Copula Dependence, and Individual-Level Counterfactual Propagation
lepidoptera is an open-source R and Python package for simulation from structural causal models with heterogeneous variable types.Translation-Invariant Pure States with Exotic Half-Chain Factors
We construct translation-invariant pure quasifree fermionic states on the one-dimensional lattice whose half-chain von Neumann algebras are hyperfinite factors of type $\mathrm{II}_\infty$ or…Reusable QUBO-Derived Block-Schur Inverse Factors for Fixed-Operator Finite-Difference PDE Solvers
Many simulations of partial differential equations require the repeated solution of linear systems whose matrix remains fixed while the righthand side changes.Margin Certificates for Voting Classifiers under Mixing Dependence
Margin bounds explain why weighted votes generalize after training error vanishes, but dependent observations require concentration arguments that keep the dependence model and failure budget…A Pricing and Hedging Framework for Infinite-Dimensional Financial Markets
In this paper, we provide a comprehensive study of how the classical Black--Scholes-type market framework behaves in an infinite-dimensional setting.Certifiably Correct Fréchet Means in Orbit Spaces
We study Fréchet means in orbit spaces of finite orthogonal group actions.Certified neural approximations for parabolic obstacle problems
Residual-trained neural surrogates carry no error guarantee, a limitation for free-boundary problems such as phase change and contact.Censored Flow Matching for Synthetic Time-to-Event Generation
Generating time-to-event data is increasingly important in survival analysis, but it remains statistically challenging because event times are often censored and thus prevent flexible generative…Constructive Universal Approximation by Infinite-Dimensional Neural Networks via Gaussian-Weighted Ridgelet Transform
Neural networks whose inputs are functions, as in operator learning, are usually shown to be universal by existence arguments, either by reduction to finite-dimensional networks or by…Near optimal gap in the Lonely Runner Conjecture
For a set $V$ of $n$ distinct positive integers, let $\mathrm{ML}(V)=\max_{t\in\mathbb{R}/\mathbb{Z}}\min_{v\in V}\|vt\|$, where $\|x\|$ is the distance from $x$ to the nearest integer.The maximum number of Hamiltonian cycles in tournaments
Let $C(n)$ denote the maximum number of directed Hamiltonian cycles in a tournament on $n$ vertices.New lower bounds for binary constant-weight codes from prescribed-automorphism search, and two quantum codes meeting their upper bounds
We give explicit binary constant-weight codes that raise the lower bounds on $A(n,6,w)$ in eight cells of Brouwer's table, all now listed there.Strong $\mathfrak{sl}_2$ Actions and Symmetric Chain Decompositions
We introduce a notion of a strong $\mathfrak{sl}_2$-action on a poset, and conjecture the existence of such an action is equivalent to the existence of a symmetric chain decomposition of that poset.Singular wave functions and quantum collapse in inverse-power potentials
Quantum collapse (QC) occurs under the action of the inverse-power potential U(r)=-U_{0}/(2r^{n}) in the framework of the Schroedinger equation.SALTO: Solver-Anchored Lifted Transfer Operators for Nonlinear Event Inference
Learned dynamical models can accurately predict trajectories while producing unreliable sensitivities when differentiated or transposed, limiting their use in inverse problems and scientific…Adaptive Randomized Neural Networks for PDEs: Structure-Aware Feature Redistribution and Residual-Driven Block Enrichment
Randomized neural networks retain an output-linear least-squares solve, but globally sampled random features may fail to capture the spatial and scale structure of PDE solutions.A One-Sided McDiarmid-Type Inequality for Heavy Tails via Reverse KL Tensorization
We revisit McDiarmid's inequality, a central tool in statistical learning theory and algorithm analysis.Pathwise Shrinkage and Probabilistic Calibration of the Multiplicative Half-Cauchy Process
We characterize the multiplicative half-Cauchy process through its log-scale random-walk representation, establishing shrinkage, expansion, and critical regimes, almost-sure summability, local…When is a better LLM worth paying for? Stochastic Optimization with Switching Mixed-Fidelity Oracles
Large language models (LLMs) are increasingly used upstream of decision-making to clean data, detect label errors, and reconstruct missing values.
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