Algorithmic meta-theorems, stating that graph properties expressible in some particular logic can be decided efficiently in graph classes having some specific structural properties, are now standard in sequential graph algorithms. One of the most classic examples is Courcelle's theorem: all properties expressible in Monadic Second-Order logic (MSO) are decidable in linear time in graphs of bounded treewidth.

We study distributed zero-knowledge proofs, introduced by Bick, Kol, and Oshman (SODA 2022). While distributed interactive proofs have advanced rapidly in recent years, general-purpose techniques for distributed zero-knowledge remain scarce and mostly problem-specific. We address this gap by introducing distributed statistical zero-knowledge, requiring that each node's view be simulatable up to negligible statistical distance, and by lifting the robust Sumcheck protocol (Lund, Fortnow, Karloff, and Nisan; FOCS 1990) into a modular primitive for distributed zero-knowledge proofs.

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 ⊆ V is called a separator set of G if the size of each connected component of G - S is at most 2/3 · |V|. The most useful separator sets are those that satisfy certain restrictions of cardinality or structure.