Maximum-Flow and Minimum-Cut Sensitivity Oracles for Directed Graphs
Mridul Ahi, Keerti Choudhary, Shlok Pande, Pushpraj, Lakshay Saggi

TL;DR
This paper develops efficient data structures called sensitivity oracles for directed graphs to quickly update maximum flow and minimum cut information after edge failures, with applications to fault-tolerant network design.
Contribution
It introduces new sensitivity oracles for max-flow and min-cut problems that are space-efficient and handle multiple failures, improving robustness and query speed.
Findings
Constructed a family of flows resilient to edge failures.
Designed space-efficient sensitivity oracles for max-flow and min-cut.
Achieved constant-time updates for small failure sets and large graphs.
Abstract
Given a digraph with a designated source , sink , and an -max-flow of value , we present constructions for max-flow and min-cut sensitivity oracles, and introduce the concept of a fault-tolerant flow family, which may be of independent interest. Our main contributions are as follows. 1. Fault-Tolerant Flow Family: For any graph with -max-flow value , we construct a family of -flows such that for every edge , contains an -max-flow of . 2. Max-Flow Sensitivity Oracle: We construct a single as well as dual-edge sensitivity oracle for -max-flow that requires only space. Given any set of up to two failing edges, the oracle reports the updated max-flow value in in time. Additionally, for the single-failure case, the oracle can determine in constant time…
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