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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 22
Self-regularization and structural adaptation of NPMLE for Gaussian mixture models in all dimensions
We establish structural properties of the nonparametric maximum likelihood estimator (NPMLE) for $d$-dimensional Gaussian mixtures whose means lie in a hypercube.On the Quantum Chromatic Gap II
We confirm a conjecture of the first author [SODA'26] on a strong form of pseudo-telepathy for Khot's $d$-to-$1$ games: for every $d\geq 4$, every $ε>0$, and every $k\in\mathbb N$, there is a…Classical communication over quantum channels: does entanglement help in nature?
Can entangling codewords across independent uses of a quantum channel improve the rate of classical communication?Algebraic theory of abelian fractons and beyond
We develop an algebraic theory of fusion, mobility, and statistics in abelian gapped fracton orders and topological phases.On Zeros and Algorithms for Disordered Systems II: The Antiferromagnetic Ising Model up to Kesten-Stigum
We give the first polynomial-time algorithm to estimate the partition function of the antiferromagnetic Ising model on the uniformly random $d$-regular graph to arbitrarily high accuracy for all…Exceptional Points as Witnesses of Non-Gaussian Noise
Efficient control of quantum devices requires the knowledge of their environmental noise, yet the commonly measured power spectrum does not fully characterize non-Gaussian fluctuations of realistic…The Geometry of Multitask Learning: Sharp Rates for Shared Subspace Estimation
Learning a shared subspace in multitask learning is an important statistical problem, yet exact rates remain poorly understood in many of the formal settings considered in the literature.Model-Agnostic Search for New Physics in the Presence of Imperfect Background by Smearing the Data
In the search for new particles in high-energy physics, it is necessary to first define the signal region (SR) enriched in signal events, and then compare events in this region with the expected…Learning Finite-Memory Binary Sources
Estimating biased finite-memory sources from a single trajectory is a fundamental problem with practical impact, for example in estimating entropy for cryptography.Analysis of Triggered Packet Streams: Stochastic Bounds on System Time under General Triggering Delays
Many emerging communication systems increasingly involve devices that transmit packets in multiple causally dependent stages as part of an internal workflow, rather than waiting for receiver feedback.Proof of the entropic $c$-theorem
We prove an entropic $c$-theorem in two dimensions by constructing a $c$-function from the mutual information between spacelike separated wedges, defined through the relative entropy.Learning Stabilizing Latent Feedback Controllers via Multi-Step Backward Losses
Can learned latent dynamics models support the design of feedback controllers that provably stabilize the original system?Hypergraph cycle enumeration for efficient inference of planted k-XOR with smooth trade-off
We introduce hypergraph cycle enumeration (HCE), a simple spectral framework for detecting and recovering planted signals in noisy hypergraph inference problems.Immersed Boundary Electrodiffusion in the Wasserstein Gradient Flow Formalism: Global Well-Posedness, Non-Equilibrium Thermodynamics, and Singular Asymptotics
We introduce a unified optimal transport framework for the Immersed Boundary (IB) electrodiffusion active pump model.Kernel-based Interpolatory Methods for Context Compression of Attention Mechanisms
The bottleneck of attention mechanisms, which are the fundamental building block of modern language models, is their quadratic complexity in terms of context size.RC Prediction: A Python Package for Parameter-Aware Reservoir Computing
A nonlinear dynamical system can be characterized by the autonomous evolution of its state in time and its dependence on system parameters.Neural Network Methods in the 2BSDE Formalism for Solving the High-Dimensional Black--Scholes Equation with Transaction Costs
A 2BSDE system is written down for a $(D+1)$-dimensional Black--Scholes partial differential equation (PDE) with the Leland transaction cost model which incorporates the sign of the curvature.CuPIQP: A Batched and Differentiable QP Solver on GPUs for Robot Learning and Control
Quadratic programs (QPs) are fundamental building blocks of many robotic tasks such as inverse kinematics, whole-body control, and model predictive control.Quantum amplification of improbable futures
Some consequential futures consist of entirely plausible steps arranged into an unlikely sequence, such as ordinary weather anomalies combining into an extreme event or local equipment failures…When can Optimally Trained Transformers Achieve Near-Lossless Token Prediction for non-Markovian Data?
There exists little mathematical theory explaining why Transformer architectures are empirically successful even for non-Markovian data.
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