John Preskill

36.2k total citations · 16 hit papers
142 papers, 21.7k citations indexed

About

John Preskill is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Nuclear and High Energy Physics. According to data from OpenAlex, John Preskill has authored 142 papers receiving a total of 21.7k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Atomic and Molecular Physics, and Optics, 83 papers in Artificial Intelligence and 33 papers in Nuclear and High Energy Physics. Recurrent topics in John Preskill's work include Quantum Computing Algorithms and Architecture (76 papers), Quantum Information and Cryptography (68 papers) and Quantum Mechanics and Applications (39 papers). John Preskill is often cited by papers focused on Quantum Computing Algorithms and Architecture (76 papers), Quantum Information and Cryptography (68 papers) and Quantum Mechanics and Applications (39 papers). John Preskill collaborates with scholars based in United States, Canada and Austria. John Preskill's co-authors include Alexei Kitaev, Peter W. Shor, Frank Wilczek, Mark B. Wise, Daniel Gottesman, Patrick Hayden, Hsin-Yuan Huang, Richard Kueng, Panos Aliferis and Andrew M. Childs and has published in prestigious journals such as Nature, Science and Physical Review Letters.

In The Last Decade

John Preskill

139 papers receiving 20.9k citations

Hit Papers

Quantum Comput... 1983 2026 1997 2011 2018 1983 2000 2006 2001 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John Preskill United States 55 13.2k 12.1k 5.4k 3.6k 1.8k 142 21.7k
Wojciech H. Zurek United States 66 15.7k 1.2× 21.2k 1.8× 1.1k 0.2× 2.0k 0.6× 1.0k 0.6× 184 25.8k
Yakir Aharonov United States 51 7.4k 0.6× 16.2k 1.3× 1.3k 0.2× 1.1k 0.3× 644 0.3× 229 19.0k
Raymond Laflamme Canada 50 13.4k 1.0× 12.1k 1.0× 1.2k 0.2× 1.2k 0.3× 1.7k 0.9× 179 17.4k
Guifré Vidal Australia 62 12.1k 0.9× 21.0k 1.7× 1.7k 0.3× 699 0.2× 438 0.2× 137 23.0k
Asher Peres Israel 47 18.8k 1.4× 20.2k 1.7× 790 0.1× 1.2k 0.3× 1.0k 0.6× 212 23.4k
Edward Farhi United States 40 3.8k 0.3× 2.9k 0.2× 3.9k 0.7× 3.4k 0.9× 1.3k 0.7× 83 9.4k
Michael A. Nielsen Australia 42 22.3k 1.7× 18.8k 1.6× 596 0.1× 462 0.1× 3.2k 1.7× 70 26.4k
Jens Eisert Germany 68 13.1k 1.0× 17.5k 1.4× 751 0.1× 391 0.1× 650 0.4× 336 20.9k
Alexei Kitaev United States 30 7.0k 0.5× 14.5k 1.2× 939 0.2× 350 0.1× 1.1k 0.6× 47 18.4k
Stephen M. Barnett United Kingdom 77 10.2k 0.8× 19.9k 1.6× 387 0.1× 682 0.2× 1.4k 0.7× 489 26.4k

Countries citing papers authored by John Preskill

Since Specialization
Citations

This map shows the geographic impact of John Preskill's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John Preskill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Preskill more than expected).

Fields of papers citing papers by John Preskill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Preskill. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John Preskill. The network helps show where John Preskill may publish in the future.

Co-authorship network of co-authors of John Preskill

This figure shows the co-authorship network connecting the top 25 collaborators of John Preskill. A scholar is included among the top collaborators of John Preskill based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John Preskill. John Preskill is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huang, Hsin-Yuan, et al.. (2025). Certifying almost all quantum states with few single-qubit measurements. Nature Physics. 21(11). 1834–1841. 1 indexed citations
2.
Gharibyan, Hrant, et al.. (2025). Quantum chaos in the sparse SYK model. Journal of High Energy Physics. 2025(2). 9 indexed citations
3.
Mok, Wai‐Keong, Tobias Haug, Adam L. Shaw, Manuel Endres, & John Preskill. (2025). Optimal Conversion from Classical to Quantum Randomness via Quantum Chaos. Physical Review Letters. 134(18). 180403–180403. 1 indexed citations
4.
Liu, Zhenghao, E Østergaard, Senrui Chen, et al.. (2025). Quantum learning advantage on a scalable photonic platform. Science. 389(6767). 1332–1335.
5.
Lewis, L. H., et al.. (2024). Improved machine learning algorithm for predicting ground state properties. Nature Communications. 15(1). 895–895. 24 indexed citations
6.
Kim, Isaac H. & John Preskill. (2023). Complementarity and the unitarity of the black hole S-matrix. Journal of High Energy Physics. 2023(2). 11 indexed citations
7.
Lee, Seunghoon, Joonho Lee, Huanchen Zhai, et al.. (2023). Evaluating the evidence for exponential quantum advantage in ground-state quantum chemistry. Nature Communications. 14(1). 1952–1952. 143 indexed citations breakdown →
8.
Huang, Hsin-Yuan, Michael Broughton, Jordan Cotler, et al.. (2022). Quantum advantage in learning from experiments. Science. 376(6598). 1182–1186. 298 indexed citations breakdown →
9.
Huang, Hsin-Yuan, Richard Kueng, Giacomo Torlai, Victor V. Albert, & John Preskill. (2022). Provably efficient machine learning for quantum many-body problems. Science. 377(6613). eabk3333–eabk3333. 150 indexed citations breakdown →
10.
Elben, Andreas, Steven T. Flammia, Hsin-Yuan Huang, et al.. (2022). The randomized measurement toolbox. Nature Reviews Physics. 5(1). 9–24. 208 indexed citations breakdown →
11.
Chamberland, Christopher, Kyungjoo Noh, Patricio Arrangoiz-Arriola, et al.. (2022). Building a Fault-Tolerant Quantum Computer Using Concatenated Cat Codes. PRX Quantum. 3(1). 172 indexed citations breakdown →
12.
Brandão, Fernando G. S. L., Wissam Chemissany, Nicholas Hunter-Jones, Richard Kueng, & John Preskill. (2021). Models of Quantum Complexity Growth. PRX Quantum. 2(3). 75 indexed citations
13.
Huang, Hsin-Yuan, Richard Kueng, & John Preskill. (2021). Information-Theoretic Bounds on Quantum Advantage in Machine Learning. Physical Review Letters. 126(19). 190505–190505. 150 indexed citations
14.
Preskill, John. (2016). Stability, topology, holography: The many facets of quantum error correction. Bulletin of the American Physical Society. 2016. 2 indexed citations
15.
Beverland, Michael E., et al.. (2016). Protected gates for topological quantum field theories. Journal of Mathematical Physics. 57(2). 25 indexed citations
16.
Jiang, Liang, et al.. (2012). Generalized Uhrig Dynamical Decoupling for Multi-Level Quantum Systems. Bulletin of the American Physical Society. 2012. 2 indexed citations
17.
Preskill, John. (2003). Topologically protected quantum computation. APS. 2003. 1 indexed citations
18.
Preskill, John. (1984). Magnetic monopoles in particle physics and cosmology.. Presented at. 373–389. 1 indexed citations
19.
Preskill, John, Mark B. Wise, & Frank Wilczek. (1983). Cosmology of the invisible axion. Physics Letters B. 120(1-3). 127–132. 2151 indexed citations breakdown →
20.
Preskill, John. (1982). MONOPOLES IN THE VERY EARLY UNIVERSE. Presented at. 119–146. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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