Random Graphs and the Parity Quantifier

TL;DR

This paper investigates the behavior of properties expressible in first-order logic with the parity quantifier over random graphs, establishing a modular convergence law that describes their limiting probabilities.

Contribution

It introduces a modular convergence law for FO[parity] over G(n, p), extending to Mod-q quantifiers, and develops new algebraic tools based on Gowers norms.

Findings

Establishes the modular convergence law for FO[parity]

Extends results to Mod-q quantifiers for prime q

Uses multivariate polynomials and Gowers norms in proofs

Abstract

The classical zero-one law for first-order logic on random graphs says that for any first-order sentence $\phi$ in the theory of graphs, as n approaches infinity, the probability that the random graph G(n, p) satisfies $\phi$ approaches either 0 or 1. It is well known that this law fails to hold for any formalism that can express the parity quantifier: for certain properties, the probability that G(n, p) satisfies the property need not converge, and for others the limit may be strictly between 0 and 1. In this paper, we capture the limiting behavior of properties definable in first order logic augmented with the parity quantier, FO[parity], over G(n, p), thus eluding the above hurdles. Specifically, we establish the following "modular convergence law": For every FO[parity] sentence $\phi$, there are two rational numbers a_0, a_1, such that for i in {0,1}, as n approaches infinity, the probability that the random graph G(2n+i, p) satisfies $\phi$ approaches a_i. Our results also extend appropriately to first order logic equipped with Mod-q quantiers for prime q. Our approach is based on multivariate polynomials over finite fields, in particular, on a new generalization of the Gowers norm. The proof generalizes the original quantifier elimination approach to the zero-one law, and has analogies with the Razborov-Smolensky method for lower bounds for AC0 with parity gates.