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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 13
Black Hole Love Numbers with Physics-Informed Neural Networks
We develop and validate a physics-informed neural network (PINN) framework for computing the tidal Love numbers of black holes directly from their perturbation equations.Optimal spectral shrinkage via Krylov approximation
Spectral shrinkage encompasses a broad family of estimators for high-dimensional linear regression that regularize estimation and prediction by applying spectral filters to the sample covariance…Beyond least-favorable distribution pairs: asymptotically instance-optimal robust hypothesis testing
When testing a composite null $\mathcal{P}$ against a composite alternative $\mathcal{Q}$, it has been known since Huber and Strassen (1973) that if a least favorable distribution (LFD) pair exists…Detection times are not local observables in quantum field theory
Detection times are routinely recorded in quantum experiments.Classical and Quantum Dynamics in State Space: Projective Hilbert Space, Measurement, and Classical Emergence
We develop a geometric formulation of classical and quantum dynamics in which projective Hilbert space is taken as the primary state space and classical configuration and phase spaces arise as…Nonreciprocal Spherical Attention and Retrieval: Sharp Coarsening Clocks and Certified Score Correction
We develop nonreciprocal spherical attention as a mathematical framework for coarsening and compressed nearest-neighbor retrieval.Partial Invariance for Classification under Structural Causal Models
Making predictions in an unseen environment from data collected across multiple training environments is challenging.Multiclass Classification with Rare Useful Features: Fundamental Limits and the Optimality of Diversity Pursuit Higher Criticism Thresholding
We consider classification in high-dimensional feature spaces where only a vanishing fraction of features are useful and the number of classes may be large.Lieb-Robinson bounds for Bose-Hubbard Hamiltonians via path expansions
We study the transport properties of Bose-Hubbard-type Hamiltonians.Overcoming Demand Censoring through Randomization for Risk-Sensitive Newsvendor Learning
We study online newsvendor learning with bounded demand, censored observations, and convex nonlinear shortage costs.Near-Quadratic Error-Free Graph Matching above Otter's Threshold via Approximate Local Tree Correlation Testing
This paper presents a near-quadratic-time algorithm that correctly matches almost all nodes of two correlated Erdős-Rényi graphs without any incorrect matches.RATSIFT: Resolution-Adaptive Transformer for Solar Irradiance Forecasting and Temporal Downscaling
Accurate forecasting and temporal downscaling of solar irradiance is critical for reliable renewable energy integration and grid management.Power-Optimal Risk Control via Standardized Margin Calibration
Machine learning can screen far more candidates than can be experimentally validated, creating a need for selection procedures that identify promising candidates while controlling risk before costly…The Continuum Limit of the Deep Linear Network
The Deep Linear Network (DLN) is a simple version of a Multilayer Perceptron (MLP) in which the activation function is the identity and the bias vector is the zero vector.Limits and Constants of OpenAI's Claimed ETH Refutation
A recent OpenAI preprint claims a deterministic algorithm that counts the satisfying assignments of a $k$-CNF formula in time $2^{O_k(n\log\log n/\sqrt{\log n})}$, and $2^{O(n/\sqrt{\log n})}$ at…Non-asymptotic analysis of SGLD with discontinuous stochastic gradients: a new route to portfolio CVaR minimization
Conditional-Value-at-Risk (CVaR) optimization is a fundamental tool in portfolio selection, yet its nonsmooth loss structure poses a challenge for the existing theory of stochastic gradient methods…Conic Certification of Transformer Attention
Attention is the computational core of large language models, yet the verifiers that bound how far an attention head's output can move under input perturbations give no guarantee on how loose their…Log-Driven Semantic Tuning for Mixed Integer Programming Solvers
Automated configuration of mixed-integer programming (MIP) solvers largely relies on black-box optimization.Cyclotomic polynomials with trinomial irreducible factors over finite fields
We classify the pairs $(q,n)$, where $q$ is a prime power, $n>1$, and $\gcd(n,q)=1$, for which every irreducible factor of $Φ_n(x)$ over $\F_q$ has exactly three nonzero terms.The Statistical Geometry of Latent Recovery in Hidden Markov Models
Hidden Markov models (HMMs) offer an important capability to interpret fitted latent states and transitions.
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