Sarah Sheldon

3.1k total citations · 4 hit papers
23 papers, 1.8k citations indexed

About

Sarah Sheldon is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Spectroscopy. According to data from OpenAlex, Sarah Sheldon has authored 23 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Atomic and Molecular Physics, and Optics, 17 papers in Artificial Intelligence and 3 papers in Spectroscopy. Recurrent topics in Sarah Sheldon's work include Quantum Computing Algorithms and Architecture (17 papers), Quantum Information and Cryptography (14 papers) and Quantum and electron transport phenomena (13 papers). Sarah Sheldon is often cited by papers focused on Quantum Computing Algorithms and Architecture (17 papers), Quantum Information and Cryptography (14 papers) and Quantum and electron transport phenomena (13 papers). Sarah Sheldon collaborates with scholars based in United States, Switzerland and Germany. Sarah Sheldon's co-authors include Jay Gambetta, Jerry M. Chow, David McKay, Lev S. Bishop, Easwar Magesan, Andrew W. Cross, Paul D. Nation, Christopher J. Wood, Sergey Bravyi and Abhinav Kandala and has published in prestigious journals such as Nature, Physical Review Letters and Nature Physics.

In The Last Decade

Sarah Sheldon

22 papers receiving 1.7k citations

Hit Papers

Validating quantum computers using randomized model circuits 2016 2026 2019 2022 2019 2017 2016 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
Sarah Sheldon United States 11 1.6k 1.2k 222 210 51 23 1.8k
Shantanu Debnath United States 11 1.3k 0.8× 1.1k 1.0× 152 0.7× 170 0.8× 23 0.5× 17 1.6k
Nathan Wiebe United States 15 1.4k 0.8× 826 0.7× 117 0.5× 312 1.5× 40 0.8× 26 1.6k
He-Liang Huang China 17 1.7k 1.0× 1.3k 1.1× 367 1.7× 141 0.7× 24 0.5× 48 2.1k
Dave Wecker United States 10 1.5k 0.9× 1.1k 0.9× 109 0.5× 255 1.2× 45 0.9× 14 1.7k
Kosuke Mitarai Japan 16 1.6k 0.9× 682 0.6× 187 0.8× 307 1.5× 50 1.0× 43 1.7k
Craig Gidney United States 12 1.3k 0.8× 782 0.7× 119 0.5× 321 1.5× 41 0.8× 19 1.4k
Suguru Endo Japan 14 2.1k 1.3× 1.4k 1.2× 173 0.8× 323 1.5× 44 0.9× 32 2.4k
K. A. Landsman United States 15 1.5k 0.9× 1.3k 1.1× 139 0.6× 195 0.9× 30 0.6× 19 1.8k
Caroline Figgatt United States 13 1.3k 0.8× 1.2k 1.1× 135 0.6× 172 0.8× 27 0.5× 18 1.7k
Josh Izaac Australia 14 1.4k 0.8× 534 0.5× 200 0.9× 218 1.0× 25 0.5× 20 1.5k

Countries citing papers authored by Sarah Sheldon

Since Specialization
Citations

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

Fields of papers citing papers by Sarah Sheldon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sarah Sheldon

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Sheldon. A scholar is included among the top collaborators of Sarah Sheldon 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 Sarah Sheldon. Sarah Sheldon 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.
Chen, Edward H., Guoyi Zhu, Ruben Verresen, et al.. (2024). Nishimori transition across the error threshold for constant-depth quantum circuits. Nature Physics. 21(1). 161–167. 11 indexed citations
2.
Layden, David, Guglielmo Mazzola, Ryan V. Mishmash, et al.. (2023). Quantum-enhanced Markov chain Monte Carlo. Nature. 619(7969). 282–287. 39 indexed citations
3.
Pednault, Edwin, Chai Wah Wu, Sarah Sheldon, et al.. (2023). Active learning of quantum system Hamiltonians yields query advantage. Physical Review Research. 5(3). 8 indexed citations
4.
Eddins, Andrew, Mário Motta, Tanvi P. Gujarati, et al.. (2022). Doubling the Size of Quantum Simulators by Entanglement Forging. PRX Quantum. 3(1). 116 indexed citations
5.
Eddins, Andrew, Tanvi P. Gujarati, Sergey Bravyi, et al.. (2021). Reducing circuit size in the variational quantum eigensolver -- Part 2: Experiment. Bulletin of the American Physical Society. 1 indexed citations
6.
Gujarati, Tanvi P., Andrew Eddins, Sergey Bravyi, et al.. (2021). Reducing circuit size in the variational quantum eigensolver -- Part 1: Theory. Bulletin of the American Physical Society. 1 indexed citations
7.
Bishop, Lev S., et al.. (2021). Hardware-efficient random circuits to classify noise in a multi-qubit system. arXiv (Cornell University). 5 indexed citations
8.
Kanazawa, Naoki, Haggai Landa, David McKay, et al.. (2020). Experimental implementation of non-Clifford interleaved randomized benchmarking with a controlled-S gate. arXiv (Cornell University). 1 indexed citations
9.
Wei, Ken Xuan, Isaac Lauer, Srikanth Srinivasan, et al.. (2020). Verifying multipartite entangled Greenberger-Horne-Zeilinger states via multiple quantum coherences. Physical review. A. 101(3). 88 indexed citations
10.
Ollitrault, Pauline J., Abhinav Kandala, Chun-Fu Chen, et al.. (2020). Quantum equation of motion for computing molecular excitation energies on a noisy quantum processor. Repository for Publications and Research Data (ETH Zurich). 142 indexed citations
11.
Maslov, Dmitri, et al.. (2020). Quantum advantage for computations with limited space. arXiv (Cornell University).
12.
McKay, David, Sarah Sheldon, John A. Smolin, Jerry M. Chow, & Jay Gambetta. (2019). Three-Qubit Randomized Benchmarking. Physical Review Letters. 122(20). 200502–200502. 90 indexed citations
13.
Cross, Andrew W., Lev S. Bishop, Sarah Sheldon, Paul D. Nation, & Jay Gambetta. (2019). Validating quantum computers using randomized model circuits. Physical review. A. 100(3). 371 indexed citations breakdown →
14.
Haas, H., Sarah Sheldon, R. Deshpande, et al.. (2018). NMR study of optically hyperpolarized phosphorus donor nuclei in silicon. Physical review. B.. 98(18). 1 indexed citations
15.
McKay, David, Christopher J. Wood, Sarah Sheldon, Jerry M. Chow, & Jay Gambetta. (2017). Efficient Z gates for quantum computing. Physical review. A. 96(2). 333 indexed citations breakdown →
16.
Sheldon, Sarah, Lev S. Bishop, Easwar Magesan, et al.. (2016). Characterizing errors on qubit operations via iterative randomized benchmarking. Physical review. A. 93(1). 85 indexed citations
17.
Sheldon, Sarah & David G. Cory. (2015). Demonstration of open-quantum-system optimal control in dynamic nuclear polarization. Physical Review A. 92(4). 1 indexed citations
18.
Sheldon, Sarah, et al.. (2007). ISPO consensus conference on wheelchairs for developing countries. Prosthetics and Orthotics International. 31(2). 217–223. 9 indexed citations
19.
Shirron, Peter, et al.. (2006). An adiabatic demagnetization refrigerator capable of continuous cooling at 10 mK and below. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 559(2). 651–653. 7 indexed citations
20.
Sheldon, Sarah, et al.. (2000). Fast wire per wire X-ray data acquisition system for time-resolved small angle scattering experiments. IEEE Transactions on Nuclear Science. 47(2). 70–74. 3 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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