Evaluating a quantum-classical quantum Monte Carlo algorithm with Matchgate shadows

Physical Review Research (2024)

 

A research team addresses the challenge of accurately calculating the electronic structure of molecules and solids using quantum computers. Quantum computers show promise for providing solutions with high accuracy, but the scaling of algorithms running on noisy devices requires improvements.
This study builds on a proposed hybrid quantum-classical algorithm using quantum Monte Carlo that could, in principle, be more accurate than methods adopted on classical computers. However, the quantum-classical algorithm has a major drawback — it requires substantial computational resources for postprocessing.

The team improved the approach by using a protocol called Matchgate shadows. This improvement reduces the postprocessing requirements, making the algorithm more efficient without affecting its noise resilience.

The new approach still demands extensive computational resources. But it is an important step in the realization of practical calculations on quantum computers.

The paper’s authors are Benchen Huang, Yi-Ting (Tim) Chen, Brajesh Gupt, Martin Suchara, Anh Tran, Sam McArdle and Giulia Galli, who conducted their work at the University of Chicago, Amazon Web Services and Argonne National Laboratory.