Deterministic Girth Approximation in Weighted Undirected Graphs

We give deterministic algorithms for approximating the girth~$g$ of an undirected graph with $n$ vertices, $m$ edges, and nonnegative real edge lengths. For every integer $k\ge 2$, our algorithm returns a cycle of length at most $\frac{2k}{3}g$ in $O((m+n^{1+2\mathrm{/}k})k\log n)$ worst-case time. For every constant~$k$, this matches the stretch and the expected running time of the randomized algorithms of Kadria, Roditty, Sidford, Vassilevska Williams, and Zwick [SODA’23, SICOMP’26] and Kadria, Roditty, and Vassilevska Williams [ESA’26]. In general, it loses only a factor of $O(\min \{k,\log n\})$ in the term that depends on~$m$. The best previous deterministic trade-off, of Kadria, Roditty, Sidford, Vassilevska Williams, and Zwick [SODA’22], has stretch~$k$ instead of $\frac{2k}{3}$ at the same exponent (for even~$k$) and requires integer edge lengths. In particular, for $k=3$ we obtain a deterministic $2$-approximation in $O((m+n^{5\mathrm{/}3})\log n)$ time for real edge lengths, whereas the deterministic algorithm of Ducoffe [SIDMA’21] for real lengths has stretch $2+\epsilon$. Our main technical idea is that a deterministic construction of the Thorup–Zwick hierarchy used by these algorithms may stop exploring as soon as it finds a cycle: the approximation analysis only needs clusters truncated at half the best cycle certificate found, so balls stopped in this way need not be hit. Together with a degree-weighted selection rule, this bounds the work of each level by its number of edges and stored ball entries. More generally, a ball need not be hit whenever the analysis only uses clusters up to a radius bounded by a certificate that the algorithm has already found.