A field on ReadSearch
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 17
Underdamped Stochastic Optimal Transport with Landauer boundary conditions: machine learning and analytical solution
Finding optimal transport protocols for underdamped stochastic processes is a difficult yet important problem in control theory.Quantum Bernstein--Kolmogorov--Arnold approximation
This paper addresses the expressivity and representation gap in Quantum Neural Networks by establishing a quantum analogue of the classical Kolmogorov--Arnold representation theorem.List 3-Coloring in tame classes of graphs in quasipolynomial time
A class of graphs $\mathcal{G}$ is tame if there is a constant c such that every $n$-vertex graph in $\mathcal{G}$ has at most $n^c$ minimal separators.Chance-Constrained Inspection Viewpoint Sequencing for On-Orbit Servicing via Safe Reinforcement Learning
Autonomous inspection of a target spacecraft is typically the initial step in on-orbit servicing.Risk-Sensitive Mission Planning for Multi-Target On-Orbit Inspection via Distributional Reinforcement Learning
Multi-target on-orbit servicing missions require planning tools that can adapt to evolving operational conditions while accounting for the outcome variability inherent to safety-critical spaceflight.Mathematical foundations of second quantization: an introduction through spin-boson models
These lecture notes originate from a one-semester course on the mathematical foundations of second quantization, first given at the Department of Physics of the Friedrich-Alexander-Universität…From fleet trajectories to single-cell promises: hierarchically weighted conformal prediction for battery SOH monitoring
Interval predictions from conformal prediction are usually read as "90% coverage", but on nested battery data that number promises the fleet average, not the individual cell.Extending Sample-based Quantum Diagonalization to Systems of Linear Equations
Solving systems of linear equations, $Ax=b$, is a ubiquitous task in computational science.High-fidelity simulation and reduced-order modeling of optical pumping in quantum devices
Spatially resolved modeling of optically pumped alkali-metal vapors requires the solution of a high-dimensional nonlinear diffusive quantum master equation (DQME) coupled to state-dependent light…Bethe Hessian Recovery through the Kesten-Stigum Regime
We show that outlier eigenvectors of the Bethe Hessian achieve weak recovery in the stochastic block model down to the Kesten-Stigum threshold, for every fixed common expected degree $d>1$.Overcoming the Representational Limitations of Amplitude Encoding for Quantum Neural Networks
Quantum Neural Networks (QNNs) offer a framework for learning functions from classical data, but their expressive power depends critically on how inputs are encoded into quantum states.Integrating Low-Thrust Transfer Dynamics into POMDP Planning for On-Orbit Servicing
Recent developments in both high-thrust (HT) and low-thrust (LT) propulsion technologies broaden design options for on-orbit servicing (OOS) missions.Revisiting the directed pathwidth of h-semicomplete digraphs
A digraph is $h$-semicomplete if every vertex has at most $h$ non-neighbors.On approximate support versions of Donoho--Stark uncertainty principles for $k$-Hadamard operators
In this paper we present results related to Donoho--Stark type uncertainty principles that were proved in the article "The uncertainty principle: variations on a theme" by Wigderson and Wigderson…Variance Reduction for Decentralized Stochastic Optimization with Multiple Local Updates
Multiple local updates are widely used in decentralized optimization to enhance communication efficiency, often in conjunction with stochastic gradients when exact gradient computation is costly.Optimal Average Distortion for Non-Expansive Embeddings of Euclidean Metrics into the Line: With applications to cut-matching games and vertex expansion
We show that any $n$-point Euclidean metric admits a non-expansive embedding into the line with average distortion at most $O\left(\sqrt{\frac{\log n}{\log\log n}}\right)$, matching a known lower…When is the deepest drawdown also the longest?
Does the deepest drawdown take the longest to recover?On Statistical-Computational Gaps in Graph Combinatorial Testing Problems
We study high-dimensional graph combinatorial hypothesis testing problems in which a signal is supported on the edge set of an unknown subgraph drawn from a class invariant under vertex relabeling.Extremal character spectra of finite projective systems
Let $\mathcal M$ be a finite spanning multiset of points in ${\rm PG}(k-1,q)$, and let ${\rm Char}_{\mathcal M}$ be its character function.Near-Optimal Second-Order Convex Finite-Sum Optimization under Individual Smoothness
We study the stochastic second-order oracle complexity of solving smooth convex finite-sum optimization with $n$ components.
Get the few papers worth your time in Mathematics & Statistics every morning.
Choose your topics and ReadSearch reads the new papers in them each day, then brings you the few worth reading, each with its key finding in a sentence.