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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: 968 arXiv preprints and 32 OpenAlex records.
Newest papers, page 43
Topological Quantum Gates on FCIs with Bounded Quantum Geometry
Two-band 2D fractional Chern insulators (FCIs) have recently been shown, in principle, to admit unusual anyonic order, associated with Bloch Hopfions localized in momentum space.Degree Stability of Parallel Greedy Matching in Random Graphs
We study a natural synchronous greedy matching process in Erdős-Rényi random graphs $\mathbb{G}(n,p)$ and give a rigorous analysis of this parallel stochastic dynamics.Upper bounds on the number of images produced by point-mass lenses at different distances
If a light source is sequentially lensed by $n$ intervening point-mass lenses at distinct distances, the number of isolated images for a generic source position cannot be greater than $2\cdot…When Weak Submodularity Meets Matroids: How Does Standard Greedy Behave?
Weakly submodular maximization finds numerous applications in machine learning, data mining and statistics.A Two-Stage Hybrid Framework for Inferring Air Trips from Mobile Location-based Service (LBS) Data under Incomplete Airport Sightings
Mobile device location-based service (LBS) data provide large-scale spatiotemporal observations that can help airport planners understand air travelers' mobility patterns.Tactix: Towards a Programmable Strategy Interface for Flexible SAT Solving
Modern SAT solvers combine a rich repertoire of proof rules with sophisticated strategies that determine when and how to apply them.Adding Heavy-Ball Momentum to Distributed Constrained Optimization for Energy Resource Management Subject to Time-Delays and Quantization
This paper studies a hybrid discrete-time signed gradient-consensus method with heavy-ball momentum, paired communication delays, and fixed logarithmic quantization.Low-Bit Distributed Constrained Optimization with Application to Optimal Scheduling and Allocation
This paper proposes a distributed resource allocation algorithm in which each agent communicates only the sign of its local cost gradient, a single bit per directed link per iteration.Dynamic Programming for Value-at-Risk Markov Decision Processes in Continuous Spaces
Value-at-Risk (VaR) is a widely adopted quantile-based risk measure in practice, yet incorporating VaR objectives into Markov decision processes (VaR MDPs) remains a longstanding challenge.Transformers as Adaptive Kernel Learners across Tasks for In-Context Learning
Transformers have emerged as a dominant architecture in modern machine learning, with in-context learning (ICL) enabling models to adapt to new tasks by conditioning on prompts, without any…Accelerating Finite-Sum Bilevel Optimization with Fully First-Order Oracles
We study nonconvex--strongly-convex bilevel optimization with finite-sum objectives and fully first-order oracles.Comment on "The polarization hierarchy for polynomial optimization over convex bodies, with applications to nonnegative matrix rank"
We revisit the feasibility and convergence claims for the polarization hierarchy of Plávala, Ligthart and Gross [Linear Algebra Appl.\ 723 (2025) 15--32].Optimal Trading Filters and the Value of Predictive Signals
The value of a forecast depends on its accuracy, but also on its actionability.Conditional Weight of Evidence for Gradient-Boosted Credit Models: Estimation, Additivity and Its Relation to Adverse Action Reasons
Traditional weight of evidence assigns a credit characteristic a value based on its association with default across a population.Native Probability Outputs for Clinical Triage: An Evaluation of Calibration and Decision Accuracy
Patient-facing triage requires an appropriate care recommendation and recognition of when information is insufficient.Gaussian Process Bandits with Paired Auxiliary Observations
Bayesian optimization (BO) is widely used for expensive black-box optimization, yet observation noise makes each evaluation less informative and slows posterior learning.Martingale Posterior Cox Processes
Cox processes provide a principled Bayesian nonparametric framework for modeling event-based data through an underlying intensity function.Where should we look for the deviation from quantum mechanics?
We argue that the experimental measurement of the lifetime and decay law of metastable helium is a promising way to find a deviation from quantum mechanics.An example of a non-sofic hyperbolic group
We construct a torsion-free, two-dimensional, word-hyperbolic group which is not sofic.On the relationship between the POVM framework and the no-signaling hypothesis
The quantum foundations literature contains dozens of "no-signaling" arguments that rely on the Born rule or, more generally, the positive operator-valued measure (POVM) framework to show that the…
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