惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

M
MIT News - Artificial intelligence
WordPress大学
WordPress大学
GbyAI
GbyAI
S
SegmentFault 最新的问题
量子位
爱范儿
爱范儿
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
MyScale Blog
MyScale Blog
人人都是产品经理
人人都是产品经理
博客园 - 叶小钗
aimingoo的专栏
aimingoo的专栏
V
Visual Studio Blog
U
Unit 42
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
The Cloudflare Blog
Stack Overflow Blog
Stack Overflow Blog
博客园 - 聂微东
J
Java Code Geeks
The GitHub Blog
The GitHub Blog
Y
Y Combinator Blog
IT之家
IT之家
Martin Fowler
Martin Fowler
宝玉的分享
宝玉的分享
雷峰网
雷峰网

math updates on arXiv.org

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization Non-normal spectral signatures of instability in neural network training dynamics Optimization of randomized neural networks for transfer operator approximation Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy Training-Free Looped Transformers Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries Asymmetric Scaling Laws from Sparse Features Is Dimensionality a Barrier for Retrieval Models? RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs Commutator-Induced Uncertainty in VAEs Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating Instance-Optimal Estimation with Multiple LLM Judges on a Budget Entropy Equivalence Testing Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation Any-Dimensional Invariant Universality Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models Anytime Training with Schedule-Free Spectral Optimization Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology The General Theory of Localization Methods Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Proximal basin hopping: global optimization with guarantees
Critical Sets in Latin Squares and Associated Structures
Richard Winston Bean · 2026-06-11 · via math updates on arXiv.org

A critical set in a Latin square of order $n$ is a set of entries in an $n\times n$ array which can be embedded in precisely one Latin square of order $n$, with the property that if any entry of the critical set is deleted, the remaining set can be embedded in more than one Latin square of order $n$. The cardinality of the largest critical set in any Latin square of order $n$ is denoted by $lcs(n)$. In 1978 Curran and van Rees proved that $lcs(n)\leq n^2-n$. In Chapter 4, it is shown that $lcs(n)\leq n^2-3n+3$. Chapter 5 provides new bounds on the maximum number of intercalates in Latin squares of orders $2^αm$ and $2^αm+1$, and a new lower bound on $lcs(4m)$. In Chapter 6 a construction is given which verifies the existence of a critical set of size $\displaystyle{\frac{n^2}{4}} + 1$ when $n$ is even and $n\geq 6$. In Chapter 7 the representation of Steiner trades of volume less than or equal to nine is examined. Computational results are used to identify those trades for which the associated partial Latin square can be decomposed into six disjoint Latin interchanges. Chapter 8 focusses on critical sets in Latin squares of order at most six and extensive computational routines are used to identify all the critical sets of different sizes in these Latin squares.