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Note on the trace of random walks on pseudorandom graphs

Yaobin Chen,Yiting Wang

2026 · ArXiv: 2602.10970
0 Citations

TLDR

It is proved that with high probability, all vertices are covered after (1+ε)nlog⁡n(1+\varepsilon)n\log n steps, regardless of the starting vertex, and the spectral properties of the adjacency matrix and the graph expansion are relied on.

Abstract

We study the graph-theoretic properties of the trace of random walks on pseudorandom graphs. We show that for any ε>0\varepsilon>0, there exists a constant CC such that the cover time of an (n,d,λ)(n,d,\lambda)-graph GG with d/λ≥Cd/\lambda\ge C is at most (1+ε)nlog⁡n(1+\varepsilon)n\log n, meaning the expected number of steps needed to reach all vertices at least once is at most (1+ε)nlog⁡n(1+\varepsilon)n\log n regardless of the starting vertex. Furthermore, we prove that with high probability, the trace of a random walk of length (1+ε)nlog⁡n(1+\varepsilon)n\log n on GG is Hamiltonian, regardless of the starting vertex. These results also hold for random dd-regular graphs with sufficiently large dd. These findings answer two questions proposed by Frieze, Krivelevich, Michaeli, and Peled [PLMS, 2018]. Notably, our results imply a bound on a stronger version of the cover time: with high probability, all vertices are covered after (1+ε)nlog⁡n(1+\varepsilon)n\log n steps, regardless of the starting vertex. Our proofs rely on the spectral properties of the adjacency matrix and the graph expansion. All results are asymptotically optimal.