S. K. Gorman

883 total citations · 1 hit paper
29 papers, 586 citations indexed

About

S. K. Gorman is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, S. K. Gorman has authored 29 papers receiving a total of 586 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Atomic and Molecular Physics, and Optics, 13 papers in Electrical and Electronic Engineering and 12 papers in Artificial Intelligence. Recurrent topics in S. K. Gorman's work include Quantum and electron transport phenomena (24 papers), Advancements in Semiconductor Devices and Circuit Design (10 papers) and Quantum Computing Algorithms and Architecture (9 papers). S. K. Gorman is often cited by papers focused on Quantum and electron transport phenomena (24 papers), Advancements in Semiconductor Devices and Circuit Design (10 papers) and Quantum Computing Algorithms and Architecture (9 papers). S. K. Gorman collaborates with scholars based in Australia, United Kingdom and China. S. K. Gorman's co-authors include M. Y. Simmons, J. G. Keizer, Yu He, Daniel Keith, Ludwik Kranz, Matthew A. Broome, William Baker, Matthew House, Thomas F. Watson and Samuel J. Hile and has published in prestigious journals such as Nature, Physical Review Letters and Advanced Materials.

In The Last Decade

S. K. Gorman

28 papers receiving 574 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.

A two-qubit gate between phosphorus donor electrons in silicon

2019 213 citations Yu He, S. K. Gorman et al. Nature profile →

Peers

S. K. Gorman

AMPO

EEE

AI

MC

CMP

Daniel Keith Australia

Changyi Yang Australia

Pierre-André Mortemousque France

Floris Braakman Switzerland

Sebastian Pauka Australia

Ludwik Kranz Australia

Thomas Hazard United States

Hong Wen Jiang United Kingdom

Dharmraj Kotekar‐Patil Singapore

Xiao Mi United States

Daniel Keith Australia

S. K. Gorman

496 ×1.0

AMPO

306 ×1.1

EEE

205 ×1.1

AI

92 ×0.8

MC

19 ×0.6

CMP

Citations per year, relative to S. K. Gorman S. K. Gorman (= 1×) peers Daniel Keith

Countries citing papers authored by S. K. Gorman

Since Specialization

Citations

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

Fields of papers citing papers by S. K. Gorman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. K. 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 S. K. Gorman. The network helps show where S. K. Gorman may publish in the future.

Co-authorship network of co-authors of S. K. Gorman

This figure shows the co-authorship network connecting the top 25 collaborators of S. K. Gorman. A scholar is included among the top collaborators of S. K. 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 S. K. Gorman. S. K. 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

1.

Voisin, B., Michael T. Jones, Luis Fabián Peña, et al.. (2025). Grover’s algorithm in a four-qubit silicon processor above the fault-tolerant threshold. Nature Nanotechnology. 20(4). 472–477. 10 indexed citations

2.

Timofeev, Andrey, Daniel Keith, John Rowlands, et al.. (2025). High-fidelity sub-microsecond single-shot electron spin readout above 3.5 K. Nature Communications. 16(1). 3382–3382. 1 indexed citations

3.

Jones, Michael T., et al.. (2025). An 11-qubit atom processor in silicon. Nature. 648(8094). 569–575.

4.

Gorman, S. K., et al.. (2024). Impact of measurement backaction on nuclear spin qubits in silicon. Physical review. B.. 109(3). 1 indexed citations

5.

Keith, Daniel, S. K. Gorman, Ludwik Kranz, et al.. (2024). Engineering Spin‐Orbit Interactions in Silicon Qubits at the Atomic‐Scale. Advanced Materials. 36(26). e2312736–e2312736. 5 indexed citations

6.

Macha, P., Ludwik Kranz, Daniel Keith, et al.. (2024). High-fidelity initialization and control of electron and nuclear spins in a four-qubit register. Nature Nanotechnology. 19(5). 605–611. 11 indexed citations

7.

Kranz, Ludwik, et al.. (2023). Hyperfine-mediated spin relaxation in donor-atom qubits in silicon. Physical Review Research. 5(2). 6 indexed citations

8.

Gorman, S. K., et al.. (2023). Single-Shot Readout of Multiple Donor Electron Spins with a Gate-Based Sensor. PRX Quantum. 4(1). 1 indexed citations

9.

Kranz, Ludwik, et al.. (2023). High-Fidelity CNOT Gate for Donor Electron Spin Qubits in Silicon. Physical Review Applied. 19(2). 6 indexed citations

10.

Jones, Michael T., P. Macha, J. G. Keizer, et al.. (2023). Atomic Engineering of Molecular Qubits for High-Speed, High-Fidelity Single Qubit Gates. ACS Nano. 17(22). 22601–22610. 1 indexed citations

11.

Gorman, S. K., et al.. (2022). Shelving and latching spin readout in atom qubits in silicon. Physical review. B.. 106(7). 4 indexed citations

12.

Gorman, S. K., Yu He, M. T. Jones, et al.. (2022). Flopping-Mode Electric Dipole Spin Resonance in Phosphorus Donor Qubits in Silicon. Physical Review Applied. 17(5). 13 indexed citations

13.

Gorman, S. K., et al.. (2022). Engineering topological states in atom-based semiconductor quantum dots. Nature. 606(7915). 694–699. 86 indexed citations

14.

Kranz, Ludwik, S. K. Gorman, Yu He, et al.. (2022). The Use of Exchange Coupled Atom Qubits as Atomic‐Scale Magnetic Field Sensors. Advanced Materials. 35(6). e2201625–e2201625. 10 indexed citations

15.

Fricke, Lukas, Matthew House, Chin‐Yi Chen, et al.. (2018). Addressable electron spin resonance using donors and \ndonor molecules in silicos. Sussex Research Online (University of Sussex). 15 indexed citations

16.

Broome, Matthew A., S. K. Gorman, Matthew House, et al.. (2018). Two-electron spin correlations in precision placed donors in silicon. Nature Communications. 9(1). 980–980. 48 indexed citations

17.

Gorman, S. K., Matthew A. Broome, Matthew House, et al.. (2018). Singlet-triplet minus mixing and relaxation lifetimes in a double donor dot. Applied Physics Letters. 112(24). 1 indexed citations

18.

Broome, Matthew A., Thomas F. Watson, Daniel Keith, et al.. (2017). High-Fidelity Single-Shot Singlet-Triplet Readout of Precision-Placed Donors in Silicon. Physical Review Letters. 119(4). 46802–46802. 32 indexed citations

19.

Broome, Matthew A., S. K. Gorman, J. G. Keizer, et al.. (2016). Mapping the chemical potential landscape of a triple quantum dot. Physical review. B.. 94(5). 2 indexed citations

20.

Gorman, S. K., Matthew A. Broome, J. G. Keizer, et al.. (2016). Extracting inter-dot tunnel couplings between few donor quantum dots in silicon. New Journal of Physics. 18(5). 53041–53041. 4 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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