Universal Configuration for Optimizing Complexity in Variational Distributed Quantum Circuits

TL;DR

This paper proves the existence of a universal optimal configuration for distributing quantum gates in variational distributed quantum circuits, optimizing complexity and depth across various topologies, validated through analytical and numerical methods.

Contribution

It introduces a universal optimal configuration for distributing gates in variational distributed circuits, based on a new complexity measure and validated through numerical comparisons.

Findings

Existence of a universal optimal configuration proven analytically and numerically.

A complexity measure based on Markov matrices quantifies convergence rates.

Numerical validation aligns with the majorization criterion.

Abstract

Distributed quantum computing represents at present one of the most promising approaches to scaling quantum processors. Current implementations typically partition circuits into multiple cores, each composed of several qubits, with inter-core connectivity playing a central role in ensuring scalability. Identifying the optimal configuration -- defined as the arrangement that maximizes circuit complexity with minimal depth -- thus constitutes a fundamental design challenge. In this work, we demonstrate, both analytically and numerically, the existence of a universal optimal configuration for distributing single and two qubit gates across arbitrary intercore communication topologies in variational distributed circuits. Our proof is based on a complexity measure based on Markov matrices, which quantifies the convergence rate toward the Haar measure, as introduced by Weinstein et al. Finally, we validate our predictions through numerical comparisons with the well established majorization criterion proposed in Ref 2.