David Sutter

64 papers receiving 793 citations

Peers

David Sutter
Comparison fields: 5 of 65
  • Artificial Intelligence 449
  • Nuclear and High Energy Physics 148
  • Atomic and Molecular Physics, and Optics 354
  • Statistical and Nonlinear Physics 110
  • Mathematical Physics 36
Replace T. Hashimoto with:
T. Hashimoto Japan
J. C. A. Barata Brazil
Sébastien Racanière United States
Jayne Thompson Singapore
Sayak Ray United States
Hongyi Zhou China
Bernard Bonnard France
Thierry Paul France
Victor Adamchik United States
Garret Sobczyk Mexico
David Sutter relative to T. Hashimoto Japan T. Hashimoto's profile →
Citations per field
00.5×7.7×
T. Hashimoto · 1×
Citations per year

Countries citing papers authored by David Sutter

Since Specialization
Citations

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

Fields of papers citing papers by David Sutter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Sutter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Sutter Line = papers co-authored together David Sutter links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199594
2 201872
3 202356
4 201748
5 201644
6 201741
7 201641
8 202238
9 202030
10 202429
11 200524
12 197523
13 201921
14 202220
15 202219
16 201518
17 201817
18 201611
19 20239
20 20059

About David Sutter

David Sutter is a scholar working on Nuclear and High Energy Physics, Aerospace Engineering, Artificial Intelligence, Statistics and Probability and Electrical and Electronic Engineering, having authored 73 papers that have together received 822 indexed citations. Recurring topics across this work include Particle accelerators and beam dynamics (26 papers), Particle Accelerators and Free-Electron Lasers (22 papers), Quantum Computing Algorithms and Architecture (20 papers), Quantum Information and Cryptography (20 papers), Magnetic confinement fusion research (12 papers), Quantum Mechanics and Applications (9 papers), Superconducting Materials and Applications (7 papers) and Statistical Mechanics and Entropy (4 papers). The work is most often cited by research in Artificial Intelligence (449 citations), Nuclear and High Energy Physics (148 citations), Atomic and Molecular Physics, and Optics (354 citations), Statistical and Nonlinear Physics (110 citations) and Mathematical Physics (36 citations). David Sutter has collaborated with scholars based in United States, Switzerland and Spain. Frequent co-authors include Renato Renner, Savas Dimopoulos, Christophe Piveteau, Marco Tomamichel, Omar Fawzi, Stefan Woerner, Andreas Winter, Mario Berta, Aram W. Harrow and Mark M. Wilde. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Nuclear Science, Quantum, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and IEEE Transactions on Applied Superconductivity.

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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