Bryan O’Gorman

2.1k total citations · 2 hit papers
23 papers, 1.2k citations indexed

About

Bryan O’Gorman is a scholar working on Artificial Intelligence, Computer Networks and Communications and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Bryan O’Gorman has authored 23 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 5 papers in Computer Networks and Communications and 5 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Bryan O’Gorman's work include Quantum Computing Algorithms and Architecture (17 papers), Quantum Information and Cryptography (6 papers) and Quantum many-body systems (4 papers). Bryan O’Gorman is often cited by papers focused on Quantum Computing Algorithms and Architecture (17 papers), Quantum Information and Cryptography (6 papers) and Quantum many-body systems (4 papers). Bryan O’Gorman collaborates with scholars based in United States, Canada and Germany. Bryan O’Gorman's co-authors include Davide Venturelli, Eleanor Rieffel, Rupak Biswas, Stuart Hadfield, Zhihui Wang, Vadim Smelyanskiy, Ryan Babbush, Salvatore Mandrà, Joonho Lee and Sergey Knysh and has published in prestigious journals such as Nature, Scientific Reports and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Bryan O’Gorman

23 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

2019 431 citations Stuart Hadfield, Zhihui Wang et al. Algorithms profile →
Unbiasing fermionic quantum Monte Carlo with a quantum computer

2022 142 citations William J. Huggins, Bryan O’Gorman et al. Nature profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Bryan O’Gorman	1.0k	339	315	121	72	23	1.2k
Davide Venturelli	1.2k 1.2×	309 0.9×	390 1.2×	193 1.6×	79 1.1×	43	1.4k
Vojtěch Havlíček	1.2k 1.1×	403 1.2×	240 0.8×	143 1.2×	35 0.5×	17	1.4k
Josh Izaac	1.4k 1.3×	534 1.6×	218 0.7×	200 1.7×	37 0.5×	20	1.5k
Kosuke Mitarai	1.6k 1.5×	682 2.0×	307 1.0×	187 1.5×	38 0.5×	43	1.7k
Stuart Hadfield	871 0.8×	257 0.8×	330 1.0×	91 0.8×	32 0.4×	25	940
Hayato Goto	1.0k 1.0×	647 1.9×	158 0.5×	221 1.8×	22 0.3×	69	1.4k
Leonard Wossnig	1.0k 1.0×	459 1.4×	245 0.8×	93 0.8×	22 0.3×	15	1.2k
Martin Roetteler	1.1k 1.1×	508 1.5×	392 1.2×	197 1.6×	60 0.8×	49	1.3k
Alex Bocharov	815 0.8×	241 0.7×	209 0.7×	129 1.1×	79 1.1×	15	964
Salvatore Mandrà	414 0.4×	159 0.5×	90 0.3×	64 0.5×	45 0.6×	23	601

Countries citing papers authored by Bryan O’Gorman

Since Specialization

Citations

This map shows the geographic impact of Bryan O’Gorman'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 Bryan O’Gorman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bryan O’Gorman more than expected).

Fields of papers citing papers by Bryan O’Gorman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryan O’Gorman. 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 Bryan O’Gorman. The network helps show where Bryan O’Gorman may publish in the future.

Co-authorship network of co-authors of Bryan O’Gorman

This figure shows the co-authorship network connecting the top 25 collaborators of Bryan O’Gorman. A scholar is included among the top collaborators of Bryan O’Gorman 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 Bryan O’Gorman. Bryan O’Gorman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jiang, Tong, et al.. (2025). Unbiasing fermionic auxiliary-field quantum Monte Carlo with matrix product state trial wavefunctions. Physical Review Research. 7(1). 9 indexed citations

Huggins, William J., Bryan O’Gorman, Nicholas C. Rubin, et al.. (2022). Unbiasing fermionic quantum Monte Carlo with a quantum computer. Nature. 603(7901). 416–420. 142 indexed citations breakdown →

O’Gorman, Bryan, Sandy Irani, James Whitfield, & Bill Fefferman. (2022). Intractability of Electronic Structure in a Fixed Basis. PRX Quantum. 3(2). 16 indexed citations

Tran, Tony, N. Minh, Eleanor Rieffel, et al.. (2021). A Hybrid Quantum-Classical Approach to Solving Scheduling Problems. Proceedings of the International Symposium on Combinatorial Search. 7(1). 98–106. 31 indexed citations

O’Gorman, Bryan, et al.. (2021). Quantum-accelerated constraint programming. Quantum. 5. 550–550. 8 indexed citations

Stollenwerk, Tobias, Bryan O’Gorman, Davide Venturelli, et al.. (2019). Quantum Annealing Applied to De-Conflicting Optimal Trajectories for Air Traffic Management. IEEE Transactions on Intelligent Transportation Systems. 21(1). 285–297. 74 indexed citations

O’Gorman, Bryan. (2019). Parameterization of Tensor Network Contraction. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 19. 1 indexed citations

Hadfield, Stuart, Zhihui Wang, Bryan O’Gorman, et al.. (2019). From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz. Algorithms. 12(2). 34–34. 431 indexed citations breakdown →

Grabbe, Shon, Eleanor Rieffel, Stuart Hadfield, et al.. (2019). Overview of NASA QuAIL Team Research. NASA Technical Reports Server (NASA). 1 indexed citations

10.

Hadfield, Stuart, Zhihui Wang, Eleanor Rieffel, et al.. (2017). Quantum Approximate Optimization with Hard and Soft Constraints. 15–21. 24 indexed citations

11.

O’Gorman, Bryan, et al.. (2017). An Investigation of Phase Transitions in Single-Machine Scheduling Problems. Proceedings of the International Conference on Automated Planning and Scheduling. 27. 325–329. 2 indexed citations

12.

Tran, Tony, Zhihui Wang, N. Minh, et al.. (2016). Explorations of Quantum-Classical Approaches to Scheduling a Mars Lander Activity Problem. National Conference on Artificial Intelligence. 4 indexed citations

13.

Perdomo‐Ortiz, Alejandro, et al.. (2016). Determination and correction of persistent biases in quantum annealers. Scientific Reports. 6(1). 18628–18628. 29 indexed citations

14.

O’Gorman, Bryan, Eleanor Rieffel, N. Minh, Davide Venturelli, & Jeremy Frank. (2016). Comparing planning problem compilation approaches for quantum annealing. The Knowledge Engineering Review. 31(5). 465–474. 2 indexed citations

15.

Biswas, Rupak, Jiang Zhang, Sergey Knysh, et al.. (2016). A NASA perspective on quantum computing: Opportunities and challenges. Parallel Computing. 64. 81–98. 57 indexed citations

16.

Perdomo‐Ortiz, Alejandro, et al.. (2015). Programming and Tuning a Quantum Annealing Device to Solve Real World Problems. Bulletin of the American Physical Society. 2015. 1 indexed citations

17.

O’Gorman, Bryan, Eleanor Rieffel, N. Minh, Davide Venturelli, & Jeremy Frank. (2015). Compiling Planning into Quantum Optimization Problems: A Comparative Study. 3 indexed citations

18.

O’Gorman, Bryan, Ryan Babbush, Alejandro Perdomo‐Ortiz, Alán Aspuru‐Guzik, & Vadim Smelyanskiy. (2015). Bayesian network structure learning using quantum annealing. The European Physical Journal Special Topics. 224(1). 163–188. 54 indexed citations

19.

Rieffel, Eleanor, et al.. (2014). A case study in programming a quantum annealer for hard operational planning problems. Quantum Information Processing. 14(1). 1–36. 131 indexed citations

20.

Babbush, Ryan, Alejandro Perdomo‐Ortiz, Bryan O’Gorman, William G. Macready, & Alán Aspuru‐Guzik. (2012). Construction of Energy Functions for Lattice Heteropolymer Models: Efficient Encodings for Constraint Satisfaction Programming and Quantum Annealing. arXiv (Cornell University). 2 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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