Evidence map›Paper›PMID 37029105›Full record

ArticleNature communications2023

Evaluating the evidence for exponential quantum advantage in ground-state quantum chemistry.

Seunghoon Lee, Joonho Lee, Huanchen Zhai, Yu Tong, Alexander M Dalzell, Ashutosh Kumar, Phillip Helms, Johnnie Gray, Zhi-Hao Cui, Wenyuan Liu and 8 more

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Quantum computing applications in drug discovery.Briefings in bioinformatics · 2026
    Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Implicit Solvent Sample-Based Quantum Diagonalization.The journal of physical chemistry. B · 2025
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Seunghoon LeeDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.ORCID http://orcid.org/0000-0003-3665-587X
Joonho LeeDepartment of Chemistry, Columbia University, New York, NY, 10027, USA.ORCID http://orcid.org/0000-0002-9667-1081
Huanchen ZhaiDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.
Yu TongDepartment of Mathematics, University of California, Berkeley, CA, 94720, USA.ORCID http://orcid.org/0000-0002-7555-9373
Alexander M DalzellAWS Center for Quantum Computing, Pasadena, CA, 91125, USA.
Ashutosh KumarDepartment of Chemistry, Virginia Tech, Blacksburg, VA, 24061, USA.
Phillip HelmsDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.
Johnnie GrayDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.
Zhi-Hao CuiDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.ORCID http://orcid.org/0000-0002-7389-4063
Wenyuan LiuDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.
Michael KastoryanoAWS Center for Quantum Computing, Pasadena, CA, 91125, USA.
Ryan BabbushGoogle Quantum AI, 340 Main Street, Venice, CA, 90291, USA.
John PreskillAWS Center for Quantum Computing, Pasadena, CA, 91125, USA.
David R ReichmanDepartment of Chemistry, Columbia University, New York, NY, 10027, USA.
Earl T CampbellRiverlane, Cambridge, UK.
Edward F ValeevDepartment of Chemistry, Virginia Tech, Blacksburg, VA, 24061, USA.
Lin LinDepartment of Mathematics, University of California, Berkeley, CA, 94720, USA.
Garnet Kin-Lic ChanDivision of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA. gkc1000@gmail.com.ORCID http://orcid.org/0000-0001-8009-6038

Funding

DOE | Office of Science (SC) DE-NA0003525DOE | Office of Science (SC) DE-SC0017867DOE | Office of Science (SC) DE-SC0019374DOE | Office of Science (SC) DE-SC0019390DOE | Office of Science (SC) DE-SC0020290DOE | Office of Science (SC) DOE-SC0018140National Science Foundation (NSF) CHE-2102505National Science Foundation (NSF) OAC-1550456National Science Foundation (NSF) OMA-2016245National Science Foundation (NSF) PHY-1733907National Science Foundation (NSF) PHY-1748958Simons Foundation Simons Investigator Award
6 · The paper itself

Abstract

Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem.

Identifiers

PMID37029105
PMCPMC10082187

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.