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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 15
Robust distortion riskmetrics under symmetry, unimodality, and Wasserstein constraints
We study worst-case distortion riskmetrics over symmetric distributions with prescribed mean and variance in a Wasserstein ball around a reference distribution.Entropy-Regularized Reinforcement Learning for the Regime-Switching Consumption-Investment Problem
This paper establishes an entropy-regularized reinforcement learning (ERRL) framework for the continuous-time consumption-investment problem under a regime-switching market model with general…Maximal input entropy for binary two-deletion and two-insertion channels
Under uniform transmission, we determine the received binary words that maximize input entropy for two-deletion and two-insertion channels.On Sparse Graph Limits for Neural Combinatorial Optimization
Graph neural networks are often trained on small graphs and deployed on larger ones, raising the question of which graph information must be preserved for combinatorial optimization values to…Minimum-Norm Interpolation in Weighted Variation Spaces: Direct and Inverse Problems
We study minimum-norm interpolation in weighted variation spaces generated by ReLU$^s$ ridge functions on the unit ball, where $s$ is a positive integer.The Value of Steiner Hubs in Two-Hop Distance Labeling
Two-hop distance labelings were introduced in 2002 by Cohen, Halperin, Kaplan, and Zwick with hubs of two kinds: vertices of the graph, or, in their Steiner variant, arbitrary objects carrying…Selective inference for pruned interaction trees with known unequal variances in randomized trials
Interaction trees reuse outcomes to discover treatment-effect heterogeneity, complicating inference after growth and pruning.Lower Bounds on Inference Complexity for Polyak-Ruppert Averaged Stochastic Gradient Descent
In this paper, we establish sharp lower bounds for Gaussian approximation of Polyak-Ruppert averaged stochastic gradient descent with polynomially decreasing step sizes.Nonlinear Dynamics in Periodically Distributed Fibre Amplification Systems
We investigate effects of longitudinally varying nonlinearity on periodically distributed amplification systems in optical fibres.Fluid Limits and Upper Bounds for Randomized Greedy Matching
The Modified Randomized Greedy (MRG) algorithm [Tinhofer (1984), Aronson-Dyer-Frieze-Suen (1995)] is a classical greedy algorithm for finding approximate maximum matchings.Online Autotuning of Algebraic Multigrid via Contextual Bandits and Reinforcement Learning
Algebraic multigrid (AMG) methods are widely used for solving large sparse linear systems, but their efficiency depends strongly on interacting setup and solve parameters.Density functionals for the Pauli-Fierz Hamiltonian
We develop a density-functional theory for the Pauli-Fierz Hamiltonian of nonrelativistic quantum electrodynamics in the spirit of the convex-analytic formulation of Lieb.Adaptive Optimizers Can Get a Policy Ranking Wrong: Momentum, Dependent Data, and a Two-Run Remedy
Operators choosing among decision rules, such as when a battery charges or where an idle taxi goes, rank them by estimated long-run value.How Much Can Approximate Equilibria Change the Social Cost of Selfish Routing?
We study approximate Nash equilibria in nonatomic congestion games, with the goal of understanding how much the social cost can change when the equilibrium condition is relaxed.Exponential suppression of bit-flip errors in dissipative cat qubits
We study the infinite-dimensional Lindblad generator $L_ε=D[a^2-α^2]+εD[a]$, describing a dissipative cat qubit subject to single-photon loss.Accelerating posterior sampling in Bayesian inverse problems with diffusion models: an online-offline perspective
Bayesian inverse problems require both informative prior models and computationally feasible posterior inference.Maximum purity of absolutely separable and absolutely PPT states in qutrit--qudit systems
A bipartite state is absolutely positive partial transpose (APPT) if it remains PPT under every global unitary transformation, and absolutely separable if it remains separable.Accuracy Is Not Risk: Why Medical AI Should Not Report Only Its Most Likely Label
Many medical AI models are trained to reproduce a single reference label and hand the most likely label to the next step in a clinical workflow.Sentiment sensing: comparative analysis of multilingual sentiment dynamics
Cross-country sentiment analysis faces three fundamental challenges: language-specific biases distort comparisons, compositional data constraints invalidate standard statistics and temporal dynamics…An Introduction to Financial Derivatives: Open Lecture Notes
These lecture notes give a broad introduction to financial derivatives at the level of a Masters program in quantitative finance.
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