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Theoretical computer science

Almost-linear-time exact matching and prescribed-degree factors in general graphs

OpenAI research collection · 1 manuscript · Source checked 2026-10-19

OpenAI's result summary

Gives a randomized algorithm finding an exact maximum-cardinality matching in any simple undirected graph in (n+m)^{1+o(1)} word time, with success probability at least 2/3. The time bound holds on every computation path. The same guarantees apply to finding a spanning subgraph with prescribed admissible vertex degrees, or deciding that none exists.

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Short excerpts below come from OpenAI's abstracts. The full abstract and original PDF preserve the paper's precise scope.

MANUSCRIPT 01

Almost-Linear-Time Maximum-Cardinality Matching in General Graphs

We prove that maximum-cardinality matching in a simple undirected graph with n vertices and m edges can be found by one uniform randomized algorithm in (n+m)^{1+o(1)} time. The bound holds on every computation path in a logarithmic-word model, and the algorithm returns an explicit maximum matching with probability at least 2/3.…

Full source abstract

We prove that maximum-cardinality matching in a simple undirected graph with n vertices and m edges can be found by one uniform randomized algorithm in (n+m)^{1+o(1)} time. The bound holds on every computation path in a logarithmic-word model, and the algorithm returns an explicit maximum matching with probability at least 2/3. An explicit reduction gives the same time and probability guarantees for deciding whether a simple host graph has a spanning subgraph with prescribed valid vertex degrees, and for finding one when it exists.

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