The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Solving strongly correlated electron models on a quantum computer
Open accessAbstract
One of the main applications of future quantum computers will be the simulation of quantum models. While the evolution of a quantum state under a Hamiltonian is straightforward (if sometimes expensive), using quantum computers to determine the ground state phase diagram of a quantum model and the properties of its phases is more involved. Using the Hubbard model as a prototypical example, we here show all the steps necessary to determine its phase diagram and ground state properties on a quantum computer. In particular, we discuss strategies for efficiently determining and preparing the ground state of the Hubbard model starting from various mean-field states with broken symmetry. We present an efficient procedure to prepare arbitrary Slater determinants as initial states and present the complete set of quantum circuits needed to evolve from these to the ground state of the Hubbard model. We show that, using efficient nesting of the various terms each time step in the evolution can be performed with just $\mathcal{O}(N)$ gates and $\mathcal{O}(\log N)$ circuit depth. We give explicit circuits to measure arbitrary local observables and static and dynamic correlation functions, both in the time and frequency domain. We further present efficient non-destructive approaches to measurement that avoid the need to re-prepare the ground state after each measurement and that quadratically reduce the measurement error.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In the long term, quantum simulation using quantum computers has great potential to wield a broad influence on the world [48, 49, 50].”
From Quantum Computing in the NISQ era and beyond (2018) · cites this paper as [49]
Experimental — accuracy not yet measuredIn the citing paper
“The cost of estimating the correct ground state energy depends directly on the overlap of the initial state with the ground state, and it becomes progressively more expensive as the overlap with the correct ground state decreases [20, 48–50].”
From Drug design on quantum computers (2024) · cites this paper as [48]
In the citing paper
“Even though the run-time has improved over time [48, 49], the dependence on the overlap of the initial and target states cannot be circumvented [50].”
From Drug design on quantum computers (2024) · cites this paper as [48]
In the citing paper
“Correspondingly, most of the experimental implementations so far have employed methods that better tolerate these fluctuations, such as Nelder-Mead and Particle-Swarm Optimization (PSO) 353 , which are gradient free. More recently the Simultaneous Perturbation Stochastic Approximation (SPSA) has been applied 354,355 .”
From Quantum Chemistry in the Age of Quantum Computing (2019) · cites this paper as [354]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Quantum Computation and Quantum Information
Nielsen, M. A., Chuang, I., & Grover, L. K. (2002) · American Journal of Physics · doi:10.1119/1.1463744 · Cited by 21,895
Quantum Computation and Quantum Information: 10th Anniversary Edition
Nielsen, M. A., & Chuang, I. L. (2012) · doi:10.1017/cbo9780511976667 · Cited by 8,436
Simulating physics with computers
Feynman, R. P. (1982) · International Journal of Theoretical Physics · doi:10.1007/bf02650179 · Cited by 7,691
The Resonating Valence Bond State in La 2 CuO 4 and Superconductivity
Anderson, P. W. (1987) · Science · doi:10.1126/science.235.4793.1196 · Cited by 7,666
Electron correlations in narrow energy bands
Hubbard, J. (1963) · Proceedings of the Royal Society of London A Mathematical and Physical Sciences · doi:10.1098/rspa.1963.0204 · Cited by 6,687
Resonating valence bonds: A new kind of insulator?
Anderson, P. W. (1973) · Materials Research Bulletin · doi:10.1016/0025-5408(73)90167-0 · Cited by 2,852
Sachdev, S. (2011) · doi:10.1017/cbo9780511973765 · Cited by 2,842
On the product of semi-groups of operators
Trotter, H. F. (1959) · Proceedings of the American Mathematical Society · doi:10.1090/s0002-9939-1959-0108732-6 · Cited by 2,282
A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
Farhi, E., Goldstone, J., Gutmann, S., Lapan, J., Lundgren, A., & Preda, D. (2001) · Science · doi:10.1126/science.1057726 · Cited by 2,056
Effect of Correlation on the Ferromagnetism of Transition Metals
Gutzwiller, M. C. (1963) · Physical Review Letters · doi:10.1103/physrevlett.10.159 · Cited by 1,905
Research works printed but not linked: 2
- M. B. Hastings, 2015, Quantum Inf. Comput., 15, 1
- D. Poulin, 2015, Quantum Inf. Comput., 15, 361
Cited by
Sorted by citations
Quantum Computing in the NISQ era and beyond
Preskill, J. (2018) · Quantum · doi:10.22331/q-2018-08-06-79 · Cited by 8,830
“ena where quantum computers seem to have a clear advantage over classical ones. In the long term, quantum simulation using quantum computers has great potential to wield a broad influence on the world [42, 43, 44]. Advances in quantum chemistry, facilitated by quantum computing, might precipitate the design of new phar…”
BackgroundQuantum 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
Quantum Chemistry in the Age of Quantum Computing
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
The Variational Quantum Eigensolver: A review of methods and best practices
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
Metadata
- Authors
- Wecker, D., Hastings, M. B., Wiebe, N., Clark, B. K., Nayak, C., & Troyer, M.
- Affiliations
- Microsoft (United States) (US)
- ETH Zurich (CH)
- Venue
- Physical Review A
- Publisher
- American Physical Society (APS)
- Published
- 2015-12-10
- Volume
- 92
- Issue
- 6
- ISSN
- 0556-2791 (ISSN-L)
- 1050-2947
- 1094-1622
- OpenAlex
- W2167110831
- Cited by
- 285
- References
- 52
- Citations by year
- 2026: 12 · 2025: 41 · 2024: 31 · 2023: 40 · 2022: 39 · 2021: 36 · 2020: 34 · 2019: 16 · 2018: 20 · 2017: 9 · 2016: 7
- FWCI
- 11.74
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Physical Review A (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (1066293)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- European Research Council (SIMCOFE)
- Aspen Center for Physics
- 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 › Cold Atom Physics and Bose-Einstein Condensates
- Keywords
- Hubbard model, strongly correlated electrons, quantum simulation, ground state preparation, phase diagram, Slater determinants, quantum circuits, circuit depth, correlation functions, non-destructive measurement, measurement error reduction, quantum computing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
