Convergence of Digitized-Counterdiabatic QAOA: circuit depth versus free parameters

Abstract

Recently, Digitized-Counterdiabatic (CD) Quantum Approximate Optimization Algorithm (QAOA) has been proposed to make QAOA converge to the solution of an optimization problem in fewer steps, inspired by Trotterized counterdiabatic driving in continuous-time quantum annealing. In this paper, we critically revisit this approach by focusing on the paradigmatic weighted and unweighted one-dimensional MaxCut problem. We study two variants of QAOA with first and second-order CD corrections. Our results show that, indeed, higher order CD corrections allow for a quicker convergence to the exact solution of the problem at hand by increasing the complexity of the variational cost function. Remarkably, however, the total number of free parameters needed to achieve this result is independent of the particular QAOA variant analyzed.

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Cited by in corpus (6)

• Barren Plateaus in Variational Quantum Computing
• Shortcuts to adiabaticity: theoretical framework, relations between different methods, and versatile approximations
• Counterdiabatic optimized driving in quantum phase sensitive models
• Efficient DCQO Algorithm within the Impulse Regime for Portfolio Optimization
• Noise Effects on Diabatic Quantum Annealing Protocols
• Nonadiabatic Self-Healing of Trotter Errors in Digitized Counterdiabatic Dynamics