Progress toward favorable landscapes in quantum combinatorial optimization

TL;DR

This paper investigates the structure of quantum and classical components in variational quantum algorithms for MaxCut, showing that overparameterization can lead to favorable landscapes but does not outperform classical algorithms, with noncommutativity and entanglement being key for performance.

Contribution

It analytically characterizes how quantum features influence the optimization landscape and demonstrates that overparameterization yields favorable landscapes without surpassing classical methods.

Findings

Overparameterization leads to landscapes without local optima.

Quantum ansätze do not provide superpolynomial speedups over classical MaxCut algorithms.

Noncommutativity and entanglement improve algorithm performance.

Abstract

The performance of variational quantum algorithms relies on the success of using quantum and classical computing resources in tandem. Here, we study how these quantum and classical components interrelate. In particular, we focus on algorithms for solving the combinatorial optimization problem MaxCut, and study how the structure of the classical optimization landscape relates to the quantum circuit used to evaluate the MaxCut objective function. In order to analytically characterize the impact of quantum features on the critical points of the landscape, we consider a family of quantum circuit ans\"atze composed of mutually commuting elements. We identify multiqubit operations as a key resource and show that overparameterization allows for obtaining favorable landscapes. Namely, we prove that an ansatz from this family containing exponentially many variational parameters yields a landscape free of local optima for generic graphs. However, we further prove that these ans\"atze do not offer superpolynomial advantages over purely classical MaxCut algorithms. We then present a series of numerical experiments illustrating that noncommutativity and entanglement are important features for improving algorithm performance.