A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations
Avimita Chatterjee, Sonny Rappaport, Anish Giri, Sonika Johri, Timothy, Proctor, David E. Bernal Neira, Pratik Sathe, Thomas Lubinski

TL;DR
This paper introduces a comprehensive framework for benchmarking quantum Hamiltonian simulations across different hardware and models, providing detailed performance insights and identifying quantum advantage crossover points.
Contribution
It presents a novel, extendable benchmarking methodology and software framework for evaluating quantum Hamiltonian simulations on various hardware and models.
Findings
Quantum hardware outperforms classical simulators beyond certain problem sizes.
The framework reveals hardware limitations and fidelity metrics.
Performance profiles vary across different Hamiltonian models.
Abstract
Quantum Hamiltonian simulation is one of the most promising applications of quantum computing and forms the basis for many quantum algorithms. Benchmarking them is an important gauge of progress in quantum computing technology. We present a methodology and software framework to evaluate various facets of the performance of gate-based quantum computers on Trotterized quantum Hamiltonian evolution. We propose three distinct modes for benchmarking: (i) comparing simulation on a real device to that on a noiseless classical simulator, (ii) comparing simulation on a real device with exact diagonalization results, and (iii) using scalable mirror circuit techniques to assess hardware performance in scenarios beyond classical simulation methods. We demonstrate this framework on five Hamiltonian models from the HamLib library: the Fermi and Bose-Hubbard models, the transverse field Ising model,…
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Taxonomy
TopicsQuantum, superfluid, helium dynamics · Gaussian Processes and Bayesian Inference · Advanced Thermodynamics and Statistical Mechanics
