Scaling advantage in quantum simulation of geometrically frustrated magnets

TL;DR

This paper demonstrates that quantum simulation of geometrically frustrated magnets on up to 1440 qubits shows a significant scaling advantage over classical methods, highlighting the potential of near-term quantum devices for practical computational tasks.

Contribution

The study provides experimental evidence of a quantum advantage in simulating frustrated magnets, surpassing classical Monte Carlo methods in speed and scalability.

Findings

Quantum annealing relaxation times exceed one microsecond.

Quantum simulation outperforms classical path-integral Monte Carlo.

Speedup exceeds a million-fold over CPU.

Abstract

The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter systems. One important task is the simulation of geometrically frustrated magnets in which topological phenomena can emerge from competition between quantum and thermal fluctuations. Here we report on experimental observations of relaxation in such simulations, measured on up to 1440 qubits with microsecond resolution. By initializing the system in a state with topological obstruction, we observe quantum annealing (QA) relaxation timescales in excess of one microsecond. Measurements indicate a dynamical advantage in the quantum simulation over the classical approach of path-integral Monte Carlo (PIMC) fixed-Hamiltonian relaxation with multiqubit cluster updates. The advantage increases with both system size and inverse temperature, exceeding a million-fold speedup over a CPU. This is an important piece of experimental evidence that in general, PIMC does not mimic QA dynamics for stoquastic Hamiltonians. The observed scaling advantage, for simulation of frustrated magnetism in quantum condensed matter, demonstrates that near-term quantum devices can be used to accelerate computational tasks of practical relevance.