Efficient quantum-enhanced classical simulation for patches of quantum landscapes
This work addresses the need to optimize quantum resource usage by enabling classical simulation of specific quantum circuit patches, which is incremental but practical for quantum computing applications.
The authors tackled the problem of identifying when classical simulation can replace quantum computation by showing that any sub-region of a quantum expectation landscape can be classically simulated after simple quantum measurements, with time and sample complexity guarantees for various circuit families. They demonstrated this on a 127-qubit simulation, achieving efficient quantum-enhanced classical simulation.
Understanding the capabilities of classical simulation methods is key to identifying where quantum computers are advantageous. Not only does this ensure that quantum computers are used only where necessary, but also one can potentially identify subroutines that can be offloaded onto a classical device. In this work, we show that it is always possible to generate a classical surrogate of a sub-region (dubbed a "patch") of an expectation landscape produced by a parameterized quantum circuit. That is, we provide a quantum-enhanced classical algorithm which, after simple measurements on a quantum device, allows one to classically simulate approximate expectation values of a subregion of a landscape. We provide time and sample complexity guarantees for a range of families of circuits of interest, and further numerically demonstrate our simulation algorithms on an exactly verifiable simulation of a Hamiltonian variational ansatz and long-time dynamics simulation on a 127-qubit heavy-hex topology.