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Calculating the thermal rate constant with exponential speedup on a quantum computer
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It is shown how to formulate the ubiquitous quantum chemistry problem of calculating the thermal rate constant on a quantum computer. The resulting exact algorithm scales exponentially faster with the dimensionality of the system than all known ``classical'' algorithms for this problem.
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“The first quantum algorithms suited particularly for quantum chemistry appeared as early as the late 1990s. These include, for instance, simulating fermionic Hamiltonians 43 and the quantum algorithm for calculating thermal rate constant efficiently 44 .”
From Quantum Chemistry in the Age of Quantum Computing (2019) · cites this paper as [43]
In the citing paper
“It has been shown that quantum computers avoid the dynamical sign problem 43 providing a more effective alternative to classical methods for quantum simulation.”
From Quantum Chemistry in the Age of Quantum Computing (2019) · cites this paper as [43]
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“Quantum computation circumvents the main issues encountered in classical methods by maintaining a highly entangled quantum state which may not admit efficient classical description, enabling a fundamentally different approach to realizing the unitary evolution and in doing so avoids the dynamical sign problem 43 .”
From Quantum Chemistry in the Age of Quantum Computing (2019) · cites this paper as [43]
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Cites
GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems
Saad, Y., & Schultz, M. H. (1986) · SIAM Journal on Scientific and Statistical Computing · doi:10.1137/0907058 · Cited by 11,280
Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer
Shor, P. W. (1997) · SIAM Journal on Computing · doi:10.1137/s0097539795293172 · Cited by 8,472
Simulating physics with computers
Feynman, R. P. (1982) · International Journal of Theoretical Physics · doi:10.1007/bf02650179 · Cited by 7,691
Mathematical Foundations of Quantum Mechanics
von Neumann, J. (2018) · Princeton University Press eBooks · doi:10.1515/9781400889921 · Cited by 5,072
Quantum theory, the Church–Turing principle and the universal quantum computer
Deutsch, D. (1985) · Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences · doi:10.1098/rspa.1985.0070 · Cited by 4,597
Lanczos, C. (1950) · Journal of research of the National Bureau of Standards · doi:10.6028/jres.045.026 · Cited by 4,356
Quantum Mechanics Helps in Searching for a Needle in a Haystack
Grover, L. K. (1997) · Physical Review Letters · doi:10.1103/physrevlett.79.325 · Cited by 4,306
Quantum Computations with Cold Trapped Ions
Cirac, J. I., & Zoller, P. (1995) · Physical Review Letters · doi:10.1103/physrevlett.74.4091 · Cited by 3,733
Solution of the Schrödinger equation by a spectral method
Feit, M. D., Fleck, J. A., & Steiger, A. (1982) · Journal of Computational Physics · doi:10.1016/0021-9991(82)90091-2 · Cited by 3,375
Mathematical foundations of quantum mechanics
Offenbacher, E. L. (1955) · Journal of the Franklin Institute · doi:10.1016/0016-0032(55)90752-3 · Cited by 3,129
Flagged first, then by citations
Research works printed but not linked: 5
- W. H. Miller, 1998, J. Phys. Chem., 102, 793, 10.1021/jp973208o · DOI
- F. Matzkies, 1997, J. Chem. Phys., 2647
- C. Scheurer, 1995, J. Chem. Phys., 2869
- R. Kosloff, 1988, J. Phys. C, 92, 2087
- A. Ekert, 1998, Philos. Trans. R. Soc. London Ser. A, 356, 1765
Cited by
Sorted by citations
Georgescu, I. M., Ashhab, S., & Nori, F. (2014) · Reviews of Modern Physics · doi:10.1103/revmodphys.86.153 · Cited by 2,932
“For example, an efficient algorithm for calculating the thermal rate constant was given in (Lidar and Wang, 1999).”
MethodQuantum computational chemistry
McArdle, S., Endo, S., Aspuru-Guzik, A., Benjamin, S. C., & Yuan, X. (2020) · Reviews of Modern Physics · doi:10.1103/revmodphys.92.015003 · Cited by 1,621
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Cao, Y., Romero, J., Olson, J. P., Degroote, M., Johnson, P. D., Kieferová, M., Kivlichan, I. D., Menke, T., Peropadre, B., Sawaya, N. P. D., et al. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00803 · Cited by 1,560
Quantum Chemistry in the Age of Quantum Computing
Cao, Y., Romero, J., Olson, J., Degroote, M., Johnson, P., Kieferová, M., Kivlichan, I., Menke, T., Peropadre, B., Sawaya, N., et al. (n.d.) · OPUS - Open Publications of UTS Scholars (University of Technology Sydney) · Cited by 1,265
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Tilly, J., Chen, H., Cao, S., Picozzi, D., Setia, K., Li, Y., Grant, E., Wossnig, L., Rungger, I., Booth, G. H., et al. (2022) · Physics Reports · doi:10.1016/j.physrep.2022.08.003 · Cited by 1,031
Towards quantum chemistry on a quantum computer
Lanyon, B. P., Whitfield, J. D., Gillett, G. G., Goggin, M. E., Almeida, M. P., Kassal, I., Biamonte, J. D., Mohseni, M., Powell, B. J., Barbieri, M., et al. (2010) · Nature Chemistry · doi:10.1038/nchem.483 · Cited by 796
Elucidating reaction mechanisms on quantum computers
Reiher, M., Wiebe, N., Svore, K. M., Wecker, D., & Troyer, M. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1619152114 · Cited by 745
The Bravyi-Kitaev transformation for quantum computation of electronic structure
Seeley, J. T., Richard, M. J., & Love, P. J. (2012) · The Journal of Chemical Physics · doi:10.1063/1.4768229 · Cited by 585
Simulation of electronic structure Hamiltonians using quantum computers
Whitfield, J. D., Biamonte, J., & Aspuru-Guzik, A. (2011) · Molecular Physics · doi:10.1080/00268976.2011.552441 · Cited by 472
Polynomial-time quantum algorithm for the simulation of chemical dynamics
Kassal, I., Jordan, S. P., Love, P. J., Mohseni, M., & Aspuru-Guzik, A. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0808245105 · Cited by 385
Simulating Chemistry Using Quantum Computers
Kassal, I., Whitfield, J. D., Perdomo-Ortiz, A., Yung, M.-H., & Aspuru-Guzik, A. (2011) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-032210-103512 · Cited by 352
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Cao, Y., Romero, J., & Aspuru-Guzik, A. (2018) · IBM Journal of Research and Development · doi:10.1147/jrd.2018.2888987 · Cited by 357
Gate-count estimates for performing quantum chemistry on small quantum computers
Wecker, D., Bauer, B., Clark, B. K., Hastings, M. B., & Troyer, M. (2014) · Physical Review A · doi:10.1103/physreva.90.022305 · Cited by 296
NMR implementation of a molecular hydrogen quantum simulation with adiabatic state preparation.
Du, J., Xu, N., Peng, X., Wang, P.-F., Wu, S., & Lu, D.-W. (2010) · Physical Review Letters · doi:10.1103/physrevlett.104.030502 · Cited by 205
Simulating the vibrational quantum dynamics of molecules using photonics
Sparrow, C., Martín-López, E., Maraviglia, N., Neville, A., Harrold, C., Carolan, J., Joglekar, Y. N., Hashimoto, T., Matsuda, N., O’Brien, J. L., et al. (2018) · Nature · doi:10.1038/s41586-018-0152-9 · Cited by 230
From transistor to trapped-ion computers for quantum chemistry
Yung, M.-H., Casanova, J., Mezzacapo, A., McClean, J., Lamata, L., Aspuru-Guzik, A., & Solano, E. (2014) · Scientific Reports · doi:10.1038/srep03589 · Cited by 221
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Cao, Y., Papageorgiou, A., Petras, I., Traub, J., & Kais, S. (2013) · New Journal of Physics · doi:10.1088/1367-2630/15/1/013021 · Cited by 204
Jones, J. A. (2010) · Progress in Nuclear Magnetic Resonance Spectroscopy · doi:10.1016/j.pnmrs.2010.11.001 · Cited by 195
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Terhal, B. M., & Divincenzo, D. P. (2000) · Physical Review A · doi:10.1103/physreva.61.022301 · Cited by 204
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Yung, M., & Aspuru‐Guzik, A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1111758109 · Cited by 168
Ajagekar, A., & You, F. (2022) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2022.112493 · Cited by 164
Improving quantum algorithms for quantum chemistry
Hastings, M., Wecker, D., Bauer, B., & Troyer, M. (2014) · Quantum information & computation · doi:10.26421/qic15.1-2-1 · Cited by 208
Johnson, T. H., Clark, S. R., & Jaksch, D. (2014) · EPJ Quantum Technology · doi:10.1140/epjqt10 · Cited by 127
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Head-Marsden, K., Flick, J., Ciccarino, C. J., & Narang, P. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00620 · Cited by 133
Tranter, A., Love, P. J., Mintert, F., & Coveney, P. V. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00450 · Cited by 138
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Paudel, H. P., Syamlal, M., Crawford, S. E., Lee, Y., Shugayev, R., Lu, P., Ohodnicki, P. R., Mollot, D., & Duan, Y. (2022) · ACS Engineering Au · doi:10.1021/acsengineeringau.1c00033 · Cited by 153
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Wang, H., Kais, S., Aspuru-Guzik, A., & Hoffmann, M. R. (2008) · Physical Chemistry Chemical Physics · doi:10.1039/b804804e · Cited by 109
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Javadi-Abhari, A., Gokhale, P., Holmes, A. A., Franklin, D. M., Brown, K. R., Martonosi, M., & Chong, F. T. (2017) · IEEE/ACM International Symposium on Microarchitecture (MICRO) · doi:10.1145/3123939.3123949 · Cited by 69
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Veis, L., Višňák, J., Fleig, T., Knecht, S., Saue, T., Visscher, L., & Pittner, J. (2012) · Physical Review A · doi:10.1103/physreva.85.030304 · Cited by 36
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Babbush, R., Huggins, W. J., Berry, D. W., Ung, S. F., Zhao, A., Reichman, D. R., Neven, H., Baczewski, A. D., & Lee, J. (2023) · Nature Communications · doi:10.1038/s41467-023-39024-0 · Cited by 32
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Eshaghian‐Wilner, M. M., & service), W. I. (. (2009) · Wiley eBooks · doi:10.1002/9780470429983 · Cited by 34
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Peng, X., & Suter, D. (2009) · 物理学前沿：英文版 · doi:10.1007/s11467-009-0067-x · Cited by 33
Geller, M. R., Martinis, J. M., Sornborger, A. T., Stancil, P. C., Pritchett, E., You, H., & Galiautdinov, A. (2015) · Physical Review A · doi:10.1103/physreva.91.062309 · Cited by 31
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Self-citationA universal quantum circuit scheme for finding complex eigenvalues
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Shokri, S., Rafibakhsh, S., Pooshgan, R., & Faeghi, R. (2021) · The European Physical Journal Plus · doi:10.1140/epjp/s13360-021-01743-y · Cited by 8
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Lu, D., Xu, N., Xu, B., Li, Z., Chen, H., Peng, X., Xu, R., & Du, J. (2012) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2011.0360 · Cited by 6
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Veis, L., & Pittner, J. (2014) · Advances in Chemical Physics · doi:10.1002/9781118742631.ch04 · Cited by 3
Bidart, A., Vaish, P., Kabengele, T., Pang, Y., Liu, Y., & Rubenstein, B. M. (2026) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-082624-084635 · Cited by 6
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Poirier, B., & Jerke, J. (2022) · Physical Chemistry Chemical Physics · doi:10.1039/d1cp02036f · Cited by 4
Ohtsuki, Y., Mikami, S., Ajiki, T., & Tannor, D. J. (2023) · Journal of the Chinese Chemical Society · doi:10.1002/jccs.202200451 · Cited by 4
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Jákli, I., Perczel, A., Viskolcz, B., & Csizmadia, I. G. (2014) · Springer eBooks · doi:10.1007/978-3-319-09976-7_2 · Cited by 2
A bird's eye view of quantum computersPreprint
Benenti, G., & Strini, G. (2007) · arXiv (Cornell University) · doi:10.48550/arxiv.quant-ph/0703105 · Cited by 2
A Quantum Algorithm for Molecular Dynamics SimulationPreprint
Fan, Y. (2009) · arXiv (Cornell University) · Cited by 2
Shiba, K., Sugiyama, R., Yamaguchi, K., & Sogabe, T. (2022) · Advances in Condensed Matter Physics · doi:10.1155/2022/9711407 · Cited by 1
Metadata
- Authors
- Lidar, D. A., & Wang, H.
- Affiliations
- University of California, Berkeley (US)
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 1999-02-01
- Volume
- 59
- Issue
- 2
- Pages
- 2429-2438
- ISSN
- 1063-651X (ISSN-L)
- 1095-3787
- OpenAlex
- W1997740743
- Cited by
- 115
- References
- 115
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 1 · 2023: 3 · 2022: 6 · 2021: 9 · 2020: 4 · 2019: 5 · 2018: 7 · 2017: 3 · 2016: 2 · 2015: 3 · 2014: 15 · 2013: 4 · 2012: 6
- FWCI
- 0.83
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- 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 › Advanced Chemical Physics Studies
- Keywords
- thermal rate constants, quantum computing, quantum algorithms, exponential speedup, reaction rate, quantum chemistry, algorithmic complexity
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