Patrick Rebentrost

13.0k total citations · 5 hit papers
45 papers, 7.5k citations indexed

About

Patrick Rebentrost is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Molecular Biology. According to data from OpenAlex, Patrick Rebentrost has authored 45 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 22 papers in Atomic and Molecular Physics, and Optics and 8 papers in Molecular Biology. Recurrent topics in Patrick Rebentrost's work include Quantum Computing Algorithms and Architecture (30 papers), Quantum Information and Cryptography (29 papers) and Spectroscopy and Quantum Chemical Studies (13 papers). Patrick Rebentrost is often cited by papers focused on Quantum Computing Algorithms and Architecture (30 papers), Quantum Information and Cryptography (29 papers) and Spectroscopy and Quantum Chemical Studies (13 papers). Patrick Rebentrost collaborates with scholars based in United States, Singapore and Germany. Patrick Rebentrost's co-authors include Seth Lloyd, Masoud Mohseni, Nathan Wiebe, Jacob Biamonte, Péter Wittek, Nicola Pancotti, Alán Aspuru‐Guzik, Frank K. Wilhelm, Felix Motzoi and Jay Gambetta and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Patrick Rebentrost

43 papers receiving 7.2k citations

Hit Papers

Quantum machine learning 2008 2026 2014 2020 2017 2014 2008 2014 2009 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Patrick Rebentrost United States 23 5.6k 3.3k 1.2k 712 703 45 7.5k
Masoud Mohseni United States 27 4.6k 0.8× 3.2k 1.0× 867 0.7× 607 0.9× 534 0.8× 65 6.1k
Francesco Petruccione South Africa 35 6.4k 1.1× 6.6k 2.0× 577 0.5× 312 0.4× 605 0.9× 248 9.5k
Simon C. Benjamin United Kingdom 40 5.1k 0.9× 4.2k 1.3× 759 0.6× 156 0.2× 686 1.0× 121 6.8k
Maria Schuld South Africa 20 4.3k 0.8× 1.5k 0.5× 866 0.7× 212 0.3× 700 1.0× 38 6.0k
Mario Krenn Austria 32 2.3k 0.4× 2.7k 0.8× 588 0.5× 384 0.5× 783 1.1× 83 4.7k
Serge Massar Belgium 39 7.8k 1.4× 6.7k 2.1× 408 0.3× 230 0.3× 2.7k 3.8× 158 10.1k
Horst D. Simon United States 39 1.8k 0.3× 605 0.2× 1.6k 1.3× 393 0.6× 1.4k 1.9× 142 7.7k
Keisuke Fujii Japan 34 2.5k 0.4× 1.4k 0.4× 405 0.3× 186 0.3× 653 0.9× 234 4.9k
John E. Stone United States 32 639 0.1× 522 0.2× 433 0.4× 1.8k 2.5× 709 1.0× 64 6.4k

Countries citing papers authored by Patrick Rebentrost

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Rebentrost

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Rebentrost

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Rebentrost. A scholar is included among the top collaborators of Patrick Rebentrost 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 Patrick Rebentrost. Patrick Rebentrost 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.
Ban, Yue, et al.. (2025). Quantum approximated cloning-assisted density matrix exponentiation. Physical Review Research. 7(1). 1 indexed citations
2.
Pun, Chi Seng, et al.. (2025). Quantum Algorithms for the Pathwise Lasso. Quantum. 9. 1674–1674. 1 indexed citations
3.
Rebentrost, Patrick, et al.. (2024). Quantum computational finance for martingale asset pricing in incomplete markets. Scientific Reports. 14(1). 18941–18941. 2 indexed citations
4.
Zi, Wei, et al.. (2024). Efficient quantum circuits for machine learning activation functions including constant T-depth ReLU. Physical Review Research. 6(4). 5 indexed citations
5.
Liu, Y. Y., Zhen Chen, C. Shu, et al.. (2023). A variational quantum algorithm-based numerical method for solving potential and Stokes flows. Ocean Engineering. 292. 116494–116494. 11 indexed citations
6.
Rebentrost, Patrick & Seth Lloyd. (2019). Quantum gradient descent and Newton’s method for constrained polynomial optimization. DSpace@MIT (Massachusetts Institute of Technology). 70 indexed citations
7.
Rebentrost, Patrick, et al.. (2019). Quantum and classical algorithms for approximate submodular function minimization. Quantum Information and Computation. 19(15&16). 1325–1349. 6 indexed citations
8.
Rebentrost, Patrick, Thomas R. Bromley, Christian Weedbrook, & Seth Lloyd. (2017). A Quantum Recurrent Neural Network. arXiv (Cornell University). 1 indexed citations
9.
Biamonte, Jacob, Péter Wittek, Nicola Pancotti, et al.. (2017). Quantum machine learning. Nature. 549(7671). 195–202. 2441 indexed citations breakdown →
10.
Park, Heechul, Nimrod Heldman, Patrick Rebentrost, et al.. (2015). Enhanced energy transport in genetically engineered excitonic networks. Nature Materials. 15(2). 211–216. 78 indexed citations
11.
Rebentrost, Patrick, Masoud Mohseni, & Seth Lloyd. (2014). Quantum Support Vector Machine for Big Data Classification. Physical Review Letters. 113(13). 130503–130503. 1149 indexed citations breakdown →
12.
Eisele, Dörthe M., Dylan H. Arias, Xiaofeng Fu, et al.. (2014). Robust excitons inhabit soft supramolecular nanotubes. Proceedings of the National Academy of Sciences. 111(33). E3367–75. 96 indexed citations
13.
Lloyd, Seth, Masoud Mohseni, & Patrick Rebentrost. (2013). Quantum self analysis. arXiv (Cornell University). 2 indexed citations
14.
Rebentrost, Patrick, Masoud Mohseni, & Seth Lloyd. (2013). Quantum support vector machine for big feature and big data classification.. arXiv (Cornell University). 23 indexed citations
15.
Rebentrost, Patrick, et al.. (2012). Atomistic Study of the Long-Lived Quantum Coherences in the Fenna-Matthews-Olson Complex. Biophysical Journal. 102(3). 649–660. 167 indexed citations
16.
Mostame, Sarah, Patrick Rebentrost, Alexander Eisfeld, et al.. (2012). Quantum simulator of an open quantum system using superconducting qubits: exciton transport in photosynthetic complexes. New Journal of Physics. 14(10). 105013–105013. 79 indexed citations
17.
Rebentrost, Patrick, et al.. (2011). Microscopic origin of the long-lived quantum coherences in the Fenna-Matthew-Olson complex. arXiv (Cornell University). 3 indexed citations
18.
Rebentrost, Patrick, M. Stopa, & Alán Aspuru‐Guzik. (2010). Förster Coupling in Nanoparticle Excitonic Circuits. Nano Letters. 10(8). 2849–2856. 11 indexed citations
19.
Rebentrost, Patrick, et al.. (2009). Optimal Control of a Qubit Coupled to a Non-Markovian Environment. Physical Review Letters. 102(9). 90401–90401. 105 indexed citations
20.
Mohseni, Masoud, Patrick Rebentrost, Seth Lloyd, & Alán Aspuru‐Guzik. (2008). Environment-assisted quantum walks in photosynthetic energy transfer. The Journal of Chemical Physics. 129(17). 174106–174106. 802 indexed citations breakdown →

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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