Ish Dhand
Impact in
- Artificial Intelligence top 2%
- Quantum Information and Cryptography
- Quantum Computing Algorithms and Architecture
- Neural Networks and Reservoir Computing
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- Quantum Mechanics and Applications
- Quantum many-body systems
- Quantum and electron transport phenomena
Papers in
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- Quantum Information and Cryptography 14
- Quantum Computing Algorithms and Architecture 11
- Neural Networks and Reservoir Computing 8
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- Quantum many-body systems 6
- Quantum Mechanics and Applications 3
- Atomic and Subatomic Physics Research 2
- Co-authors
- Martin Bodo Plenio (9 shared papers)Trevor J. Vincent (3 shared papers)Nicolás Quesada (3 shared papers)Lars S. Madsen (2 shared papers)Jonathan Lavoie (2 shared papers)Z. Vernon (2 shared papers)L. G. Helt (2 shared papers)Jacob F. F. Bulmer (1 shared paper)
In The Last Decade
Ish Dhand
22 papers receiving 1.3k citations
Ish Dhand's Hit Papers
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 1.0k
- Atomic and Molecular Physics, and Optics 793
- Acoustics and Ultrasonics 15
- Computational Mathematics 7
- Instrumentation 20
Countries citing papers authored by Ish Dhand
This map shows the geographic impact of Ish Dhand'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 Ish Dhand with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ish Dhand more than expected).
Fields of papers citing papers by Ish Dhand
This network shows the impact of papers produced by Ish Dhand. 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 Ish Dhand. The network helps show where Ish Dhand may publish in the future.
Co-authors
The 25 scholars most cited alongside Ish Dhand, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Quantum computational advantage with a programmable photonic processor Hit paper breakdown → | 2022 | 701 |
| 2 | 2017 | 174 | |
| 3 | 2018 | 97 | |
| 4 | 2022 | 81 | |
| 5 | 2021 | 54 | |
| 6 | 2022 | 42 | |
| 7 | 2020 | 38 | |
| 8 | 2017 | 36 | |
| 9 | 2022 | 33 | |
| 10 | 2018 | 32 | |
| 11 | 2015 | 22 | |
| 12 | 2016 | 18 | |
| 13 | 2019 | 13 | |
| 14 | 2014 | 13 | |
| 15 | 2022 | 11 | |
| 16 | 2020 | 10 | |
| 17 | 2020 | 7 | |
| 18 | 2025 | 7 | |
| 19 | 2020 | 6 | |
| 20 | 2016 | 6 |
About Ish Dhand
Ish Dhand is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Biophysics and Hardware and Architecture, having authored 22 papers that have together received 1.4k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (14 papers), Quantum Computing Algorithms and Architecture (11 papers), Neural Networks and Reservoir Computing (8 papers), Quantum many-body systems (6 papers), Photonic and Optical Devices (6 papers), Quantum Mechanics and Applications (3 papers), Atomic and Subatomic Physics Research (2 papers) and Optical Network Technologies (2 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Atomic and Molecular Physics, and Optics (793 citations), Acoustics and Ultrasonics (15 citations), Computational Mathematics (7 citations) and Instrumentation (20 citations). Ish Dhand has collaborated with scholars based in Germany, Canada and Australia. Frequent co-authors include Martin Bodo Plenio, Trevor J. Vincent, Nicolás Quesada, Lars S. Madsen, Jonathan Lavoie, Z. Vernon, L. G. Helt, Jacob F. F. Bulmer, Filippo M. Miatto and Thomas Gerrits. Their work appears in journals such as Physical Review A, Journal of Physics A Mathematical and Theoretical, Physical Review Letters, Physical review. B. and Science Advances.
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.