William J. Huggins

5.7k total citations · 4 hit papers
19 papers, 1.3k citations indexed

About

William J. Huggins is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Electrical and Electronic Engineering. According to data from OpenAlex, William J. Huggins has authored 19 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 12 papers in Atomic and Molecular Physics, and Optics and 2 papers in Electrical and Electronic Engineering. Recurrent topics in William J. Huggins's work include Quantum Computing Algorithms and Architecture (17 papers), Quantum and electron transport phenomena (8 papers) and Quantum Information and Cryptography (7 papers). William J. Huggins is often cited by papers focused on Quantum Computing Algorithms and Architecture (17 papers), Quantum and electron transport phenomena (8 papers) and Quantum Information and Cryptography (7 papers). William J. Huggins collaborates with scholars based in United States, Australia and United Kingdom. William J. Huggins's co-authors include Joonho Lee, Ryan Babbush, K. Birgitta Whaley, Jarrod R. McClean, Martin Head‐Gordon, Nicholas C. Rubin, Nathan Wiebe, Thomas E. O’Brien, Ying Li and Simon C. Benjamin and has published in prestigious journals such as Nature, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

William J. Huggins

17 papers receiving 1.2k citations

Hit Papers

align trajectories

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.

Generalized Unitary Coupled Cluster Wave functions for Quantum Computation

2018 293 citations Joonho Lee, William J. Huggins et al. Journal of Chemical Theory and Computation profile →
Quantum error mitigation

2023 260 citations Zhenyu Cai, Ryan Babbush et al. Reviews of Modern Physics profile →
Even More Efficient Quantum Computations of Chemistry Through Tensor Hypercontraction

2021 189 citations Joonho Lee, Dominic W. Berry et al. PRX Quantum profile →
Unbiasing fermionic quantum Monte Carlo with a quantum computer

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

Peers

Countries citing papers authored by William J. Huggins

Since Specialization

Citations

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

Fields of papers citing papers by William J. Huggins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William J. Huggins. 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 William J. Huggins. The network helps show where William J. Huggins may publish in the future.

Co-authorship network of co-authors of William J. Huggins

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

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

#	Work	Indexed citations
1	Error Mitigation and Circuit Division for Early Fault-Tolerant Quantum Phase Estimation 2025 ·PRX Quantum ·(unknown), (unknown), Maximilian Scheurer, Christian Gogolin, William J. Huggins, Thomas E. O’Brien	0
2	Unit cell manufacture by blown powder directed energy deposition 2025 ·Manufacturing Letters ·(unknown), William J. Huggins, (unknown), Andrés Díaz Lantada, J.M. Molina-Aldareguía, Christopher Saldaña, Kyle Saleeby	1
3	Efficient State Preparation for the Quantum Simulation of Molecules in First Quantization 2025 ·PRX Quantum ·William J. Huggins, (unknown), Torin F. Stetina, (unknown)	0
4	Accelerating Quantum Algorithms with Precomputation 2024 ·Quantum ·William J. Huggins, Jarrod R. McClean	5
5	Matchgate Shadows for Fermionic Quantum Simulation 2023 ·Communications in Mathematical Physics ·(unknown), William J. Huggins, Joonho Lee, Ryan Babbush	58
6	Say NO to Optimization: A Nonorthogonal Quantum Eigensolver 2023 ·PRX Quantum ·(unknown), Diptarka Hait, James Shee, (unknown), William J. Huggins, Torin F. Stetina, Martin Head‐Gordon, K. Birgitta Whaley	25
7	Quantum error mitigation breakdown → 2023 ·Reviews of Modern Physics ·Zhenyu Cai, Ryan Babbush, Simon C. Benjamin, Suguru Endo, William J. Huggins, Ying Li, Jarrod R. McClean, Thomas E. O’Brien	260
8	Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods 2023 ·Nature Communications ·Ryan Babbush, William J. Huggins, Dominic W. Berry, (unknown), (unknown), David R. Reichman, Hartmut Neven, Andrew Baczewski, Joonho Lee	16
9	Unbiasing fermionic quantum Monte Carlo with a quantum computer breakdown → 2022 ·Nature ·William J. Huggins, Bryan O’Gorman, Nicholas C. Rubin, David R. Reichman, Ryan Babbush, Joonho Lee	142
10	Efficient quantum computation of molecular forces and other energy gradients 2022 ·Physical Review Research ·Thomas E. O’Brien, Michael Streif, Nicholas C. Rubin, Raffaele Santagati, Yuan Su, William J. Huggins, Joshua J. Goings, Nikolaj Moll, Elica Kyoseva, Matthias Degroote, Christofer S. Tautermann, Joonho Lee, Dominic W. Berry, Nathan Wiebe, Ryan Babbush	37
11	Robust in practice: Adversarial attacks on quantum machine learning 2021 ·Physical review. A ·Haoran Liao, (unknown), William J. Huggins, K. Birgitta Whaley	22
12	Mutual information scaling for tensor network machine learning 2021 ·Machine Learning Science and Technology ·(unknown), William J. Huggins, Haoran Liao, K. Birgitta Whaley	14
13	Even More Efficient Quantum Computations of Chemistry Through Tensor Hypercontraction breakdown → 2021 ·PRX Quantum ·Joonho Lee, Dominic W. Berry, Craig Gidney, William J. Huggins, Jarrod R. McClean, Nathan Wiebe, Ryan Babbush	189
14	What the foundations of quantum computer science teach us about chemistry 2021 ·The Journal of Chemical Physics ·Jarrod R. McClean, Nicholas C. Rubin, Joonho Lee, Matthew P. Harrigan, Thomas E. O’Brien, Ryan Babbush, William J. Huggins, Hsin-Yuan Huang	11
15	Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers 2021 ·npj Quantum Information ·William J. Huggins, Jarrod R. McClean, Nicholas C. Rubin, Jiang Zhang, Nathan Wiebe, K. Birgitta Whaley, Ryan Babbush	158
16	Even more efficient quantum computations of chemistry through tensor hypercontraction 2020 ·Zenodo (CERN European Organization for Nuclear Research) ·Joonho Lee, Dominic W. Berry, Craig Gidney, William J. Huggins, Jarrod R. McClean, Nathan Wiebe, Ryan Babbush	4
17	Generalized Unitary Coupled Cluster Wave functions for Quantum Computation breakdown → 2018 ·Journal of Chemical Theory and Computation ·Joonho Lee, William J. Huggins, Martin Head‐Gordon, K. Birgitta Whaley	293
18	Postponing the orthogonality catastrophe: efficient state preparation for electronic structure simulations on quantum devices 2018 ·arXiv (Cornell University) ·(unknown), (unknown), Jeffrey M. Epstein, Diptarka Hait, Daniel S. Levine, William J. Huggins, Jiang Zhang, Jarrod R. McClean, Ryan Babbush, Martin Head‐Gordon, K. Birgitta Whaley	6
19	Optimizing Instructional Policies 2013 ·Neural Information Processing Systems ·Robert Lindsey, Michael C. Mozer, William J. Huggins, Harold Pashler	19

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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