HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware
In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem instances would allow for benchmarking studies that in turn he...
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| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
2024-12-01
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| Series: | Quantum |
| Online Access: | https://quantum-journal.org/papers/q-2024-12-11-1559/pdf/ |
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| _version_ | 1850062071512694784 |
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| author | Nicolas PD Sawaya Daniel Marti-Dafcik Yang Ho Daniel P Tabor David E Bernal Neira Alicia B Magann Shavindra Premaratne Pradeep Dubey Anne Matsuura Nathan Bishop Wibe A de Jong Simon Benjamin Ojas Parekh Norm Tubman Katherine Klymko Daan Camps |
| author_facet | Nicolas PD Sawaya Daniel Marti-Dafcik Yang Ho Daniel P Tabor David E Bernal Neira Alicia B Magann Shavindra Premaratne Pradeep Dubey Anne Matsuura Nathan Bishop Wibe A de Jong Simon Benjamin Ojas Parekh Norm Tubman Katherine Klymko Daan Camps |
| author_sort | Nicolas PD Sawaya |
| collection | DOAJ |
| description | In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem instances would allow for benchmarking studies that in turn help to improve both algorithms and hardware designs. To this end, here we present a large dataset of qubit-based quantum Hamiltonians. The dataset, called HamLib (for Hamiltonian Library), is freely available online and contains problem sizes ranging from 2 to 1000 qubits. HamLib includes problem instances of the Heisenberg model, Fermi-Hubbard model, Bose-Hubbard model, molecular electronic structure, molecular vibrational structure, MaxCut, Max-$k$-SAT, Max-$k$-Cut, QMaxCut, and the traveling salesperson problem. The goals of this effort are (a) to save researchers time by eliminating the need to prepare problem instances and map them to qubit representations, (b) to allow for more thorough tests of new algorithms and hardware, and (c) to allow for reproducibility and standardization across research studies. |
| format | Article |
| id | doaj-art-dbe3d84bf91d40afb9d56847aa3646a3 |
| institution | DOAJ |
| issn | 2521-327X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften |
| record_format | Article |
| series | Quantum |
| spelling | doaj-art-dbe3d84bf91d40afb9d56847aa3646a32025-08-20T02:50:00ZengVerein zur Förderung des Open Access Publizierens in den QuantenwissenschaftenQuantum2521-327X2024-12-018155910.22331/q-2024-12-11-155910.22331/q-2024-12-11-1559HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardwareNicolas PD SawayaDaniel Marti-DafcikYang HoDaniel P TaborDavid E Bernal NeiraAlicia B MagannShavindra PremaratnePradeep DubeyAnne MatsuuraNathan BishopWibe A de JongSimon BenjaminOjas ParekhNorm TubmanKatherine KlymkoDaan CampsIn order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem instances would allow for benchmarking studies that in turn help to improve both algorithms and hardware designs. To this end, here we present a large dataset of qubit-based quantum Hamiltonians. The dataset, called HamLib (for Hamiltonian Library), is freely available online and contains problem sizes ranging from 2 to 1000 qubits. HamLib includes problem instances of the Heisenberg model, Fermi-Hubbard model, Bose-Hubbard model, molecular electronic structure, molecular vibrational structure, MaxCut, Max-$k$-SAT, Max-$k$-Cut, QMaxCut, and the traveling salesperson problem. The goals of this effort are (a) to save researchers time by eliminating the need to prepare problem instances and map them to qubit representations, (b) to allow for more thorough tests of new algorithms and hardware, and (c) to allow for reproducibility and standardization across research studies.https://quantum-journal.org/papers/q-2024-12-11-1559/pdf/ |
| spellingShingle | Nicolas PD Sawaya Daniel Marti-Dafcik Yang Ho Daniel P Tabor David E Bernal Neira Alicia B Magann Shavindra Premaratne Pradeep Dubey Anne Matsuura Nathan Bishop Wibe A de Jong Simon Benjamin Ojas Parekh Norm Tubman Katherine Klymko Daan Camps HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware Quantum |
| title | HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware |
| title_full | HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware |
| title_fullStr | HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware |
| title_full_unstemmed | HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware |
| title_short | HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware |
| title_sort | hamlib a library of hamiltonians for benchmarking quantum algorithms and hardware |
| url | https://quantum-journal.org/papers/q-2024-12-11-1559/pdf/ |
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