Sensitivity Oracles for Matroid Packing, Matroid Covering, and Matching Problems with Applications

📅 2026-09-01
📈 Citations: 0
Influential: 0
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🤖 AI Summary
本文通过构建基于拟阵打包、覆盖及匹配问题的统一代数框架,设计了能处理任意数量边增删操作的灵敏度预言机,解决了多个图优化问题。
📝 Abstract
Sensitivity oracles preprocess a graph so that queries can be answered after any $f$ edge insertions and deletions, without recomputing from scratch. For structural optimization problems the known landscape is limited: for flows and cuts, all known compact oracles handle only $f\le2$ failures; existing oracles for $s$- and global min-cut apply only to undirected graphs; and for matchings, arborescence and spanning-tree packings, and arboricity, no efficient oracle is known for $f>1$. We present a unified algebraic framework based on sensitivity oracles for matroid packing, covering, and parity of sparse linear matroids, yielding the first oracles supporting an arbitrary number $f$ of updates across all of these problems (all constructions randomized Monte-Carlo). Concretely, we obtain efficient oracles for exact $(s,t)$-max-flow/min-cut, resolving an open problem of Baswana, Bhanja, and Pandey (ICALP'22) with near-optimal space; for all-pairs $k$-bounded flow, generalizing the near-optimal reachability oracle of Brand and Saranurak (FOCS'19, the case $k=1$); the first oracles for any $f$ for directed $s$- and global min-cut; oracles for $k$-disjoint arborescences, $k$-disjoint spanning trees, colorful spanning trees, and arboricity; and oracles for the existence of an $α$-factor, with perfect matching as the case $α=1$. We further introduce the \emph{subset sensitivity model}, in which updates are confined to a susceptible edge set of size $σ$ fixed during preprocessing. Here we decouple updates from the matroid representation and eliminate the dependence on $k$ and the matroid density altogether: all of the above are supported with $\widetilde O(f^ω)$ query time and $O(fσ^2)$ space. We also prove a matching $Ω(\min\{σ^2,n^2\})$-bit lower bound when $f\ge2$, establishing optimality.
Problem

Research questions and friction points this paper is trying to address.

Sensitivity Oracles
Matroid Packing
Graph Theory
Structural Optimization
Innovation

Methods, ideas, or system contributions that make the work stand out.

Sensitivity Oracles
Matroid Packing and Covering
Arbitrary Number of Updates
Subset Sensitivity Model
Efficient Oracles
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