A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations
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 face...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Transactions on Quantum Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/10949677/ |
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| author | Avimita Chatterjee Sonny Rappaport Anish Giri Sonika Johri Timothy Proctor E. David Bernal Neira Pratik Sathe Thomas Lubinski |
| author_facet | Avimita Chatterjee Sonny Rappaport Anish Giri Sonika Johri Timothy Proctor E. David Bernal Neira Pratik Sathe Thomas Lubinski |
| author_sort | Avimita Chatterjee |
| collection | DOAJ |
| description | 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: 1) comparing simulation on a real device to that on a noiseless classical simulator; 2) comparing simulation on a real device with exact diagonalization results; and 3) 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–Hubbard and Bose–Hubbard models, the transverse-field Ising model, the Heisenberg model, and the Max3SAT problem. Experiments were conducted using Qiskit's Aer simulator, BlueQubit's CPU cluster and GPU simulators, and IBM's quantum hardware. Our framework, extendable to other Hamiltonians, provides comprehensive performance profiles that reveal hardware and algorithmic limitations and measure both fidelity and execution times, identifying crossover points where quantum hardware outperforms CPU/GPU simulators. |
| format | Article |
| id | doaj-art-13ee7af7116246408dffa6c9cd48b083 |
| institution | OA Journals |
| issn | 2689-1808 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Quantum Engineering |
| spelling | doaj-art-13ee7af7116246408dffa6c9cd48b0832025-08-20T01:51:49ZengIEEEIEEE Transactions on Quantum Engineering2689-18082025-01-01612610.1109/TQE.2025.355809010949677A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian SimulationsAvimita Chatterjee0https://orcid.org/0009-0001-7421-9334Sonny Rappaport1Anish Giri2Sonika Johri3Timothy Proctor4https://orcid.org/0000-0003-0219-8930E. David Bernal Neira5https://orcid.org/0000-0002-8308-5016Pratik Sathe6Thomas Lubinski7https://orcid.org/0000-0002-3749-3430Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, USAQuantum Economic Development Consortium, SRI International, Menlo park, CA, USAQuantum Economic Development Consortium, SRI International, Menlo park, CA, USACoherent Computing Inc., Cupertino, CA, USAQuantum Performance Laboratory, Sandia National Laboratories, Livermore, CA, USAResearch Institute of Advanced Computer Science, Universities Space Research Association, Mountain View, CA, USATheoretical Division (T4), Los Alamos National Laboratory, Los Alamos, NM, USAQuantum Circuits Inc, New Haven, CT, USAQuantum 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: 1) comparing simulation on a real device to that on a noiseless classical simulator; 2) comparing simulation on a real device with exact diagonalization results; and 3) 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–Hubbard and Bose–Hubbard models, the transverse-field Ising model, the Heisenberg model, and the Max3SAT problem. Experiments were conducted using Qiskit's Aer simulator, BlueQubit's CPU cluster and GPU simulators, and IBM's quantum hardware. Our framework, extendable to other Hamiltonians, provides comprehensive performance profiles that reveal hardware and algorithmic limitations and measure both fidelity and execution times, identifying crossover points where quantum hardware outperforms CPU/GPU simulators.https://ieeexplore.ieee.org/document/10949677/Algorithmsapplication benchmarksbenchmarkingbenchmarksfidelityHamiltonian |
| spellingShingle | Avimita Chatterjee Sonny Rappaport Anish Giri Sonika Johri Timothy Proctor E. David Bernal Neira Pratik Sathe Thomas Lubinski A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations IEEE Transactions on Quantum Engineering Algorithms application benchmarks benchmarking benchmarks fidelity Hamiltonian |
| title | A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations |
| title_full | A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations |
| title_fullStr | A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations |
| title_full_unstemmed | A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations |
| title_short | A Comprehensive Cross-Model Framework for Benchmarking the Performance of Quantum Hamiltonian Simulations |
| title_sort | comprehensive cross model framework for benchmarking the performance of quantum hamiltonian simulations |
| topic | Algorithms application benchmarks benchmarking benchmarks fidelity Hamiltonian |
| url | https://ieeexplore.ieee.org/document/10949677/ |
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