The DOI matches its Crossref record; 40 of the 42 references it cites were found in a registry or an index.
Resource-efficient digital quantum simulation of d-level systems for photonic, vibrational, and spin-s Hamiltonians
Open accessAbstract
Simulation of quantum systems is expected to be one of the most important applications of quantum computing, with much of the theoretical work so far having focused on fermionic and spin- $$\frac{1}{2}$$ 1 2 systems. Here, we instead consider encodings of d -level (i.e., qudit) quantum operators into multi-qubit operators, studying resource requirements for approximating operator exponentials by Trotterization. We primarily focus on spin- s and truncated bosonic operators in second quantization, observing desirable properties for approaches based on the Gray code, which to our knowledge has not been used in this context previously. After outlining a methodology for implementing an arbitrary encoding, we investigate the interplay between Hamming distances, sparsity patterns, bosonic truncation, and other properties of local operators. Finally, we obtain resource counts for five common Hamiltonian classes used in physics and chemistry, while modeling the possibility of converting between encodings within a Trotter step. The most efficient encoding choice is heavily dependent on the application and highly sensitive to d , although clear trends are present. These operation count reductions are relevant for running algorithms on near-term quantum hardware because the savings effectively decrease the required circuit depth. Results and procedures outlined in this work may be useful for simulating a broad class of Hamiltonians on qubit-based digital quantum computers.
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“Gray code in particular is found to be resource efficient (in terms of number of qubits and two-qubit entangling gates) in simulating some specific bosonic and spin Hamiltonians (Sawaya et al. , 2020).”
From Noisy intermediate-scale quantum algorithms (2022) · cites this paper as Sawaya et al. , 2020
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Noisy intermediate-scale quantum algorithms
Bharti, K., Cervera-Lierta, A., Kyaw, T. H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J. S., Menke, T., et al. (2022) · Reviews of Modern Physics · doi:10.1103/revmodphys.94.015004 · Cited by 2,231
Self-citationEmerging quantum computing algorithms for quantum chemistry
Motta, M., & Rice, J. E. (2021) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.1580 · Cited by 201
A perspective on scaling up quantum computation with molecular spins
Carretta, S., Zueco, D., Chiesa, A., Gómez-León, Á., & Luis, F. (2021) · Applied Physics Letters · doi:10.1063/5.0053378 · Cited by 99
Biology and medicine in the landscape of quantum advantages
Cordier, B. A., Sawaya, N. P. D., Guerreschi, G. G., & McWeeney, S. K. (2022) · Journal of The Royal Society Interface · doi:10.1098/rsif.2022.0541 · Cited by 87
Self-citationHardware efficient quantum algorithms for vibrational structure calculations
Ollitrault, P. J., Baiardi, A., Reiher, M., & Tavernelli, I. (2020) · Chemical Science · doi:10.1039/d0sc01908a · Cited by 97
Metadata
- Authors
- Sawaya, N. P. D., Menke, T., Kyaw, T. H., Johri, S., Aspuru-Guzik, A., & Guerreschi, G. G.
- Affiliations
- Intel (United States) (US)
- Harvard University (US)
- University of Toronto (CA)
- Corresponding author
- Sawaya, Nicolas P. D.
- Guerreschi, Gian Giacomo
- Venue
- npj Quantum Information
- Published
- 2020-06-02
- Volume
- 6
- Issue
- 1
- ISSN
- 2056-6387 (ISSN-L)
- OpenAlex
- W2976208308
- Cited by
- 163
- References
- 42
- Citations by year
- 2026: 18 · 2025: 41 · 2024: 29 · 2023: 19 · 2022: 27 · 2021: 25 · 2020: 4
- FWCI
- 7.37
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- npj Quantum Information (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Intel Research
- Vannevar Bush Faculty Fellowship and the Canada 150 Research Chairs Program.
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Keywords
- digital quantum simulation, qudits, d-level systems, Trotterization, Gray code, second quantization, Hamming distance, sparsity pattern, circuit depth, vibrational Hamiltonian, spin Hamiltonian
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