---
title: "Quantum algorithms — paper by Dalzell et al. (2023)"
description: "Promised quantum advantages in chemistry, optimization, finance, and machine learning are hard to… 375 references, cited by 7 papers here."
authors: ["Alexander M. Dalzell", "Sam McArdle", "Mario Berta", "Przemyslaw Bienias", "Chi-Fang Chen", "Andras Gilyen", "Connor T. Hann", "Michael J. Kastoryano", "Emil T. Khabiboulline", "Aleksander Kubica", "Grant Salton", "Samson Wang", "Fernando G. S. L. Brandao"]
year: 2023
venue: "arXiv:2310.03011"
source: "https://arxiv.org/abs/2310.03011"
doi: "10.1017/9781009639651"
arxiv: "2310.03011"
licence: "CC BY-SA 4.0 (arXiv)"
licence_url: "http://creativecommons.org/licenses/by-sa/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/dalzell-2023-quantum-algorithms-survey-applications-end/"
---
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# Quantum algorithms: A survey of applications and end-to-end complexities

**Authors:** Alexander M. Dalzell, Sam McArdle, Mario Berta, Przemyslaw Bienias, Chi-Fang Chen, Andras Gilyen, Connor T. Hann, Michael J. Kastoryano, Emil T. Khabiboulline, Aleksander Kubica, Grant Salton, Samson Wang and Fernando G. S. L. Brandao · **Year:** 2023 · **Venue:** arXiv:2310.03011 · **Licence:** [CC BY-SA 4.0 (arXiv)](http://creativecommons.org/licenses/by-sa/4.0/)

**Links:** [Publisher's page](https://doi.org/10.1017/9781009639651) · [PDF](https://arxiv.org/pdf/2310.03011) · [DOI 10.1017/9781009639651](https://doi.org/10.1017/9781009639651) · [arXiv 2310.03011](https://arxiv.org/abs/2310.03011) · [OpenAlex](https://openalex.org/W4410021745)

**Citations:** 49 citations (OpenAlex, 2026-10-14) · 7 in our library, of the 149,439 papers whose bibliographies we read

## Summary
Promised quantum advantages in chemistry, optimization, finance, and machine learning are hard to judge. Practical algorithms chain many subroutines, depend on data-loading oracles, and must run on error-corrected hardware, so hidden costs can erase an apparent speedup. This survey from the AWS Center for Quantum Computing and collaborators examines each major application area from the input to the user-relevant answer. It specifies the exact problem and input/output model, makes all oracles concrete, counts classical pre- and post-processing, and includes fault-tolerance overhead. Each quantum approach is then compared with the best classical methods and with known complexity-theoretic limits.

The survey's main conclusion is that complete end-to-end analyses are rare in the current literature. Several areas still lack a convincing cost accounting. Shor's factoring algorithm remains the clearest case of a large speedup with few caveats. The modular, wiki-style organization lets readers trace how swapping one subroutine changes the total cost, which makes the survey a practical reference for spotting realistic uses of fault-tolerant machines.

## Key points
- The survey covers nine application families: condensed matter (Fermi–Hubbard, spin, and SYK models), quantum chemistry, nuclear and particle physics, combinatorial optimization, continuous optimization, cryptanalysis, differential equations, finance, and machine learning with classical data.
- Fifteen primitive sections cover block-encodings, QSVT, qubitization, Hamiltonian simulation (product formulas, qDRIFT, Taylor/Dyson series), phase estimation, amplitude estimation, Gibbs sampling, QRAM, linear system solvers, and variational algorithms, among others.
- Three chapters address fault tolerance with the surface code, and an appendix provides background on notation and complexity theory.
- Every section has its own bibliography. Quantum sensing, annealing, and dequantization are mentioned only in passing.
- The first version appeared in October 2023, followed by an open, non-anonymous peer review. The current version reflects the field as of mid-2024 and was published in April 2025 as an open-access Cambridge University Press book.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [University of California, Berkeley](https://md.research.elamur.ai/free/en/universities/university-of-california-berkeley/) — University, Berkeley, United States · 243 works · 251,774 citations
- [University of Copenhagen](https://md.research.elamur.ai/free/en/universities/university-of-copenhagen/) — University, Copenhagen, Denmark · 117 works · 15,348 citations
- [Amazon](https://md.research.elamur.ai/free/en/companies/amazon/) — Company, Seattle, United States · 131 works · 41,785 citations
- [Yale University](https://md.research.elamur.ai/free/en/universities/yale-university/) — University, New Haven, United States · 112 works · 14,009 citations
- [RWTH Aachen University](https://md.research.elamur.ai/free/en/universities/rwth-aachen-university/) — University, Aachen, Germany · 25 works · 5,119 citations
- [California Institute of Technology](https://md.research.elamur.ai/free/en/universities/california-institute-of-technology/) — University, Pasadena, United States · 16 works · 1,291 citations
- [National Institute of Standards and Technology](https://md.research.elamur.ai/free/en/labs/national-institute-of-standards-and-technology/) — Research institute, Gaithersburg, United States · 5 works · 492 citations
- [HUN-REN Alfréd Rényi Institute of Mathematics](https://md.research.elamur.ai/free/en/labs/hun-ren-alfred-renyi-institute-of-mathematics/) — Research institute, Budapest, Hungary · 2 works · 77 citations

Also on the byline: [Hungarian Research Network](https://ror.org/04w6pnc49).

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## Cite

Cite as: Alexander M. Dalzell, Sam McArdle, Mario Berta, Przemyslaw Bienias, Chi-Fang Chen, Andras Gilyen, Connor T. Hann, Michael J. Kastoryano, Emil T. Khabiboulline, Aleksander Kubica, Grant Salton, Samson Wang and Fernando G. S. L. Brandao. 2023. Quantum algorithms: A survey of applications and end-to-end complexities. arXiv:2310.03011.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@misc{dalzell2023quantum,
  title = {{Quantum algorithms: A survey of applications and end-to-end complexities}},
  author = {Alexander M. Dalzell, Sam McArdle, Mario Berta, Przemyslaw Bienias, Chi-Fang Chen, Andras Gilyen, Connor T. Hann, Michael J. Kastoryano, Emil T. Khabiboulline, Aleksander Kubica, Grant Salton, Samson Wang and Fernando G. S. L. Brandao},
  year = {2023},
  doi = {10.1017/9781009639651},
  eprint = {2310.03011},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.1017/9781009639651}
}
```

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## References

375 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 3 November 2026*