Nathan Wiebe

2.8k total citations · 2 hit papers
26 papers, 1.6k citations indexed

About

Nathan Wiebe is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics. According to data from OpenAlex, Nathan Wiebe has authored 26 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 18 papers in Atomic and Molecular Physics, and Optics and 4 papers in Computational Theory and Mathematics. Recurrent topics in Nathan Wiebe's work include Quantum Computing Algorithms and Architecture (20 papers), Quantum Information and Cryptography (17 papers) and Quantum and electron transport phenomena (12 papers). Nathan Wiebe is often cited by papers focused on Quantum Computing Algorithms and Architecture (20 papers), Quantum Information and Cryptography (17 papers) and Quantum and electron transport phenomena (12 papers). Nathan Wiebe collaborates with scholars based in United States, Canada and Australia. Nathan Wiebe's co-authors include Andrew M. Childs, Daniel Braun, Seth Lloyd, Ryan Babbush, Jarrod R. McClean, Dominic W. Berry, Craig Gidney, William J. Huggins, Hartmut Neven and Austin G. Fowler and has published in prestigious journals such as Physical Review Letters, New Journal of Physics and Journal of Mathematical Physics.

In The Last Decade

Nathan Wiebe

25 papers receiving 1.5k citations

Hit Papers

Quantum Algorithm for Data Fitting 2012 2026 2016 2021 2012 2021 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nathan Wiebe United States 15 1.4k 826 312 117 56 26 1.6k
Guang Hao Low United States 17 1.2k 0.8× 675 0.8× 267 0.9× 73 0.6× 57 1.0× 35 1.3k
Craig Gidney United States 12 1.3k 0.9× 782 0.9× 321 1.0× 119 1.0× 25 0.4× 19 1.4k
Matthias Degroote United States 12 1.1k 0.8× 726 0.9× 208 0.7× 117 1.0× 40 0.7× 26 1.4k
Dave Wecker United States 10 1.5k 1.0× 1.1k 1.3× 255 0.8× 109 0.9× 33 0.6× 14 1.7k
Suguru Endo Japan 14 2.1k 1.5× 1.4k 1.6× 323 1.0× 173 1.5× 90 1.6× 32 2.4k
Josh Izaac Australia 14 1.4k 1.0× 534 0.6× 218 0.7× 200 1.7× 65 1.2× 20 1.5k
Earl T. Campbell United Kingdom 18 1.3k 0.9× 818 1.0× 338 1.1× 168 1.4× 88 1.6× 25 1.4k
David Gosset United States 17 1.1k 0.8× 704 0.9× 286 0.9× 104 0.9× 71 1.3× 39 1.3k
Leonard Wossnig United Kingdom 9 1.0k 0.7× 459 0.6× 245 0.8× 93 0.8× 38 0.7× 15 1.2k
Sarah Sheldon United States 11 1.6k 1.2× 1.2k 1.4× 210 0.7× 222 1.9× 43 0.8× 23 1.8k

Countries citing papers authored by Nathan Wiebe

Since Specialization
Citations

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

Fields of papers citing papers by Nathan Wiebe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan Wiebe. 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 Nathan Wiebe. The network helps show where Nathan Wiebe may publish in the future.

Co-authorship network of co-authors of Nathan Wiebe

This figure shows the co-authorship network connecting the top 25 collaborators of Nathan Wiebe. A scholar is included among the top collaborators of Nathan Wiebe 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 Nathan Wiebe. Nathan Wiebe 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.
Segal, Dvira, et al.. (2025). Quantum simulation of Lindbladian dynamics via repeated interactions. Journal of Physics A Mathematical and Theoretical. 58(30). 305302–305302. 5 indexed citations
2.
Li, Xiangyu, Xiaolong Yin, Nathan Wiebe, et al.. (2025). Potential quantum advantage for simulation of fluid dynamics. Physical Review Research. 7(1). 9 indexed citations
3.
Girvin, S. M., et al.. (2025). Leveraging Hamiltonian simulation techniques to compile operations on bosonic devices. Journal of Physics A Mathematical and Theoretical. 58(17). 175301–175301. 2 indexed citations
4.
Mukhopadhyay, Priyanka, Torin F. Stetina, & Nathan Wiebe. (2024). Quantum Simulation of the First-Quantized Pauli-Fierz Hamiltonian. PRX Quantum. 5(1). 2 indexed citations
5.
Berry, Dominic W., et al.. (2024). Doubling the efficiency of Hamiltonian simulation via generalized quantum signal processing. Physical review. A. 110(1). 9 indexed citations
6.
Berry, Dominic W., Yuan Su, Robbie King, et al.. (2024). Analyzing Prospects for Quantum Advantage in Topological Data Analysis. PRX Quantum. 5(1). 13 indexed citations
7.
Wiebe, Nathan, et al.. (2024). Generalized Quantum Signal Processing. PRX Quantum. 5(2). 29 indexed citations
8.
Babbush, Ryan, Dominic W. Berry, Robin Kothari, Rolando D. Somma, & Nathan Wiebe. (2023). Exponential Quantum Speedup in Simulating Coupled Classical Oscillators. Physical Review X. 13(4). 24 indexed citations
9.
Hadfield, Stuart, et al.. (2023). Two-Unitary Decomposition Algorithm and Open Quantum System Simulation. Quantum. 7. 1002–1002. 23 indexed citations
10.
Tong, Yu, et al.. (2023). Entanglement area law for one-dimensional gauge theories and bosonic systems. Physical review. A. 108(4). 2 indexed citations
11.
Roggero, Alessandro, et al.. (2022). Hybridized Methods for Quantum Simulation in the Interaction Picture. Quantum. 6. 780–780. 30 indexed citations
12.
Lee, Joonho, Dominic W. Berry, Craig Gidney, et al.. (2021). Even More Efficient Quantum Computations of Chemistry Through Tensor Hypercontraction. PRX Quantum. 2(3). 189 indexed citations breakdown →
13.
Tong, Yu, Dong An, Nathan Wiebe, & Lin Lin. (2021). Fast inversion, preconditioned quantum linear system solvers, fast Green's-function computation, and fast evaluation of matrix functions. Physical review. A. 104(3). 54 indexed citations
14.
Lee, Joonho, Dominic W. Berry, Craig Gidney, et al.. (2020). Even more efficient quantum computations of chemistry through tensor hypercontraction. Zenodo (CERN European Organization for Nuclear Research). 4 indexed citations
15.
Kivlichan, Ian, Craig Gidney, Dominic W. Berry, et al.. (2020). Improved Fault-Tolerant Quantum Simulation of Condensed-Phase Correlated Electrons via Trotterization. Quantum. 4. 296–296. 104 indexed citations
16.
Babbush, Ryan, Craig Gidney, Dominic W. Berry, et al.. (2018). Encoding Electronic Spectra in Quantum Circuits with Linear T Complexity. Physical Review X. 8(4). 226 indexed citations
17.
Berry, Dominic W., Mária Kieferová, Artur Scherer, et al.. (2018). Improved techniques for preparing eigenstates of fermionic Hamiltonians. npj Quantum Information. 4(1). 90 indexed citations
18.
Childs, Andrew M. & Nathan Wiebe. (2013). Product formulas for exponentials of commutators. Journal of Mathematical Physics. 54(6). 12 indexed citations
19.
Wiebe, Nathan, Daniel Braun, & Seth Lloyd. (2012). Quantum Algorithm for Data Fitting. Physical Review Letters. 109(5). 50505–50505. 320 indexed citations breakdown →
20.
Wiebe, Nathan, Dominic W. Berry, Peter Høyer, & Barry C. Sanders. (2010). Simulating Quantum Dynamics On A Quantum Computer. arXiv (Cornell University). 2011.

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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