Adaptive variational quantum computing algorithm for nonequilibrium dynamics simulations

Circuit saturation and scalability of practical calculations of N-site models for fixed times.

Schematic illustration of algorithm

Scientific Achievement

A new adaptive quantum computing algorithm demonstrates high-fidelity quantum simulations, with linear system size scaling.

Significance and Impact

This scalable algorithm creates opportunities to study quantum dynamics of significantly larger systems on current and near-term quantum devices.

Research Details

Algorithm self-adaptively constructs ansatz based on McLachlan’s variational principle.
Resulting circuits are two orders of magnitude shorter than for standard first-order Trotter expansion.
Calculations for different integrable and non-integrable spin models and quench protocols.
Circuit grows linearly with time at initial simulation stage, followed by slowing down at saturation.
Linear system size scaling for fixed simulation times.

Y.-X. Yao, N. Gomes, F. Zhang, C.-Z. Wang, K.-M. Ho, T. Iadecola, and P. P. Orth, Adaptive Variational Quantum Dynamics Simulation, PRX Quantum 2, 030307 (2021).