Evaluating analytic gradients of pulse programs on quantum computers

TL;DR

This paper introduces ODEgen, an analytic method for computing gradients of pulse programs on quantum computers, improving accuracy and resource efficiency over stochastic parameter-shift methods, demonstrated through VQE simulations and hardware experiments.

Contribution

The paper presents ODEgen, a novel analytic gradient computation method for pulse programs using differentiable ODE solvers, surpassing stochastic methods in accuracy and efficiency.

Findings

ODEgen achieves lower energies in VQE simulations with fewer resources.

ODEgen provides accurate gradients evaluated directly on quantum hardware.

Simulated and real hardware experiments validate ODEgen's effectiveness.

Abstract

Parametrized pulse programs running on quantum hardware can be differentiated via the stochastic parameter-shift (SPS) rule. We overcome the intrinsically approximate nature of SPS by introducing a new analytic method for computing gradients of pulse programs, that we coin ODEgen. In this new method, we find effective generators of pulse gates using a differentiable ordinary differential equation (ODE) solver. These effective generators inform parameter-shift rules that can be evaluated on quantum hardware. We showcase simulated VQE examples with realistic superconducting transmon systems, for which we obtain lower energies with fewer quantum resources using ODEgen over SPS. We further demonstrate a pulse VQE run with gradients computed via ODEgen entirely on quantum hardware.