AppQSim: Application-oriented benchmarks for Hamiltonian simulation on a quantum computer

Abstract

We introduce AppQSim, a benchmarking suite for quantum computers focused on applications of Hamiltonian simulation. We consider five different settings for which we define a precise task and score: condensed matter and material simulation (dynamic and static properties), nuclear magnetic resonance simulation, chemistry ground state preparation, and classical optimization. These five different benchmark tasks display different resource requirements and scalability properties. We introduce a metric to evaluate the quality of the output of a tested quantum hardware, called distinguishability cost, defined as the minimal number of gates that a perfect quantum computer would have to run to certify that the output of the benchmarked hardware is incorrect.

24 pages. v2: minor modifications and references added

References in corpus (6)

• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Randomized Benchmarking of Quantum Gates
• The computational power of random quantum circuits in arbitrary geometries
• Practicality of quantum adiabatic algorithm for chemistry applications
• Dilution of error in digital Hamiltonian simulation
• Analog simulation of noisy quantum circuits

Cited by in corpus (2)

• Quantum Optimization Benchmarking Library - The Intractable Decathlon
• Simulating sparse SYK model with a randomized algorithm on a trapped-ion quantum computer