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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: 971 arXiv preprints and 29 OpenAlex records.
Newest papers, page 12
From Ghost SICs to SIC-POVMs: A Galois Reduction of Zauner's Conjecture
Symmetric informationally complete positive operator-valued measures (SIC-POVMs, or SICs) are optimal minimal measurements for quantum state tomography.Learning Gradients of Homogeneous Functions
Homogeneous gradient functions have widespread significance, including applications in maximum energy subspace selection and retrieval problems.MDS Algebraic Geometry Codes of Square-Root Length on Hyperelliptic Curves
For every fixed genus $g\geq2$ and every $0<ρ<1$, we construct maximum distance separable (MDS) algebraic geometry codes over $\F_q$ for all sufficiently large odd squares $q$.Principled Human-AI Collaboration in Agentic Workflows
Organizations adopting AI face the challenge of deciding which outputs can be released without human review while meeting the quality standards of human experts.Smoothed analysis of stability radii for the assignment problem
Every linear program can tolerate small changes to its costs and still yield a solution of the original problem.Stand-In Effects and Pooling Amplification: Design-Based Tests of Whether Biological World Models Use Actions
Action-conditioned world models are increasingly trained on data from randomized experiments, and whether their predictions respond to actions is usually checked by replacing or removing the actions…Convex Regression at Scale: Geometry-Preserving Constraint Sparsification
Convex regression provides a flexible nonparametric estimation framework while incorporating appropriate shape information.An Observable-Algebra Approach to Quantum Coherence in Anyonic Systems
Physical restrictions on operations can make quantum coherence inaccessible.Optimization Frameworks & Learning Algorithms for Discrete-Time Mean Field Games
This monograph introduces discrete-time mean field games with finite state and action spaces, emphasizing optimization formulations and learning algorithms.IncVNM: An Interactive Recommender System with Incremental von Neumann-Morgenstern Utility Learning
In modern recommender systems, users are often presented with products whose outcomes are random.Instance-Specific Sharp Convergence Rate of the Add-$λ$ Estimator via Feature Space Decomposition
Using the Feature Space Decomposition framework, we establish non-asymptotic matching upper and lower bounds for the expected Kullback-Leibler estimation error of the Add-$λ$ estimator of a discrete…Approximation Algorithms for Maximum-Weight Degree-Bounded Forests
In the maximum-weight degree-bounded forest problem, we are given a graph with nonnegative edge weights and a degree upper bound on each vertex.The Laplace transform of the time of ruin in the Cramér--Lundberg model with Erlang $E_2(μ)$ claims: spectrum, exact moments and matrix reduction
We study the Laplace transform of the time of ruin in the classical Cramér--Lundberg model with claims having an Erlang distribution of shape parameter 2.Tensor Contraction with ZX Calculus, a Graph-Theoretic Approach
Tensors are higher dimensional generalisations of vectors and matrices.Reduction of the integro-differential equation to an ordinary differential equation in ruin models with investment in a risky asset
We study ruin models with the surplus invested in a risky asset and Erlang-distributed claims: non-life insurance, annuity payments and the mixed model.Federated Estimation of Loading Spaces in Tensor Factor Models under Differential Privacy
Tensor factor models provide low-dimensional representations of tensor-valued observations while preserving their multiway structure.Improved lower bounds for the kissing number in dimensions 49 to 61
We give explicit kissing configurations in R^d for every d = 49, ..., 61.OC-OPD: Observation-coordinated Supervision for On-Policy Distillation
Reverse and forward Kullback--Leibler (KL) divergences provide complementary supervision in on-policy distillation: reverse KL refines the student's active token rankings, and forward KL allocates…Rare Event Constrained Reinforcement Learning with Large Deviations
We study finite-horizon reinforcement learning with a safety constraint on the probability of reaching a failure set.Classical and Quantum Logics with Multiple Non-Equivalent and Non-Isomorphic Models
Both quantum and classical logics have several mutually non-equivalent and non-isomorphic models as has repeatedly been proved in the literature.
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