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

奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
爱范儿
爱范儿
博客园 - 三生石上(FineUI控件)
Vercel News
Vercel News
M
MIT News - Artificial intelligence
L
LangChain Blog
大猫的无限游戏
大猫的无限游戏
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Microsoft Azure Blog
Microsoft Azure Blog
J
Java Code Geeks
Recent Announcements
Recent Announcements
Stack Overflow Blog
Stack Overflow Blog
人人都是产品经理
人人都是产品经理
IT之家
IT之家
F
Fortinet All Blogs
博客园 - 聂微东
U
Unit 42
Martin Fowler
Martin Fowler
腾讯CDC
博客园_首页
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
量子位
阮一峰的网络日志
阮一峰的网络日志
博客园 - Franky

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
Maximum packings in graphs forbidding given rainbow cycles
Ping Li, Yang Yang · 2026-03-22 · via math updates on arXiv.org

For graphs $F$ and $G$, $F$-multicolor Turán number of $G$, denoted by $\mathrm{ex}_F(n,G)$, is the maximum number of edge-disjoint copies of $F$ in an $n$-vertex graph such that there is no copy of $G$ whose edges come from distinct copies of $F$. We study this parameter mainly for cycle pairs and determine, up to asymptotic order, when $\mathrm{ex}_{C_k}(n,C_\ell)$ attains the three natural thresholds: the upper bound, the lower bound, and the $n^{2-o(1)}$ regime. In particular, for every odd $k\ge 5$ and every $t\ge 1$, where $C_k(t)$ denotes the $t$-blow-up of $C_k$, we prove $\mathrm{ex}_{C_k(t)}(n,C_{k-2})=n^2/(kt)^2+o(n^2),$ and establish a corresponding stability theorem. We further show that if $F$ and $G$ have the same odd girth $k$ and there exist homomorphisms from both $F$ and $G$ to $C_k$, then $\mathrm{ex}_F(n,G)=n^{2-o(1)}$; in particular, $\mathrm{ex}_{C_k}(n,C_k)=n^{2-o(1)}$ for odd $k$. In addition, we prove $\mathrm{ex}_{C_{2k+1}}(n,C_{2\ell+1})=O\!\left(n^{1+1/\lceil \ell/k\rceil}\right)$ for $\ell>k$ and $\mathrm{ex}_F(n,G)=O(\mathrm{ex}(n,G))$ for bipartite $G$. We particularly establish $\mathrm{ex}_{C_4}(n,C_4)=\frac{\sqrt{2}}{8}n^{3/2}+O(n)$, and give a sufficient condition under which the lower bound cannot be attained.