Benjamin Jauregui

Benjamin Jauregui, Pedro Montealegre, Ivan Rapaport

One of the most basic techniques in algorithm design consists of breaking a problem into subproblems and then proceeding recursively. In the case of graph algorithms, one way to implement this approach is through separator sets. Given a graph $G=(V,E)$, a subset of nodes $S \subseteq V$ is called a separator set of $G$ if the size of each connected component of $G-S$ is at most $2/3 \cdot |V|$. The most useful separator sets are those that satisfy certain restrictions of cardinality or structure. For over 40 years, various efficient algorithms have been developed for computing separators of different kinds, particularly in planar graphs. Separator sets, combined with a divide and conquer approach, have been fundamental in the design of efficient algorithms in various settings. In this work, we present the first deterministic algorithm in the distributed CONGEST model that recursively computes a cycle separator in planar graphs in $\tilde{\mathcal{O}}(D)$ rounds. This result, as in the centralized setting, has significant implications for distributed planar algorithms. In fact, from this result, we can construct a deterministic algorithm that computes a DFS tree in $\tilde{\mathcal{O}}(D)$ rounds. This matches both the best-known randomized algorithm of Ghaffari and Parter (DISC'17) and, up to polylogarithmic factors, the trivial lower bound of $Ω(D)$ rounds. Besides DFS, our deterministic cycle separator algorithm can be used to derandomize several planar-graph algorithms whose only randomized ingredient is the computation of a cycle separator, such as maximum flow (Abd-Elhaleem, Dory, Parter and Weimann, PODC'25), single-source shortest path (Li and Parter, STOC'19), and reachability (Parter, DISC'20).

Benjamin Jauregui, Masayuki Miyamoto

We study distributed zero-knowledge proofs, introduced by Bick, Kol, and Oshman (SODA 2022). While distributed interactive proofs have advanced rapidly, general-purpose techniques for distributed zero-knowledge remain limited and mostly problem-specific. We address this gap by introducing distributed statistical zero-knowledge, requiring that each node's view be simulatable within negligible statistical distance, and by lifting the classical Sumcheck protocol (Lund, Fortnow, Karloff, and Nisan, FOCS 1990) into a modular primitive for distributed zero-knowledge proofs. Our main contribution is a distributed zero-knowledge implementation of Sumcheck. Given oracle access to a polynomial F over a finite field $\mathbb{F}$ with N variables, we design a protocol verifying claims of the form $\sum_{x\in\mathbb{F}} F(x)=a$ using $O(N)$ rounds of $O(\log |\mathbb{F}|)$-bit messages, while achieving statistical zero-knowledge and small soundness error. We apply this primitive to two problems. For non-k-colorability, we obtain an $O(n)$-round distributed statistical zero-knowledge proof deciding whether a graph is not k-colorable, for any constant k, using $O(log^{1+o(1)} n)$-bit messages. This is the first nontrivial distributed interactive proof for this problem, even without zero-knowledge guarantees. For Subgraph Counting, we obtain an $O(k \log n)$-round, $O(k \log n)$-bit distributed statistical zero-knowledge proof for counting copies of a given k-node pattern, improving previous distributed interactive proofs while additionally providing statistical zero-knowledge. Finally, we show that additional round compression of Sumcheck is problem-dependent: for non-3-colorability on constant-degree graphs, we prove a lower bound excluding $o(n/\log n)$ rounds under polynomial-time local computation.