Kanav Setia
Impact in
- Artificial Intelligence top 2%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
-
- Quantum and electron transport phenomena
- Quantum many-body systems
- Quantum Mechanics and Applications
Papers in
-
- Quantum Computing Algorithms and Architecture 7
- Quantum Information and Cryptography 4
- Neural Networks and Reservoir Computing 1
-
- Quantum and electron transport phenomena 2
- Co-authors
- Dario Picozzi (2 shared papers)Jonathan Tennyson (2 shared papers)Ying Li (2 shared papers)Ivan Rungger (2 shared papers)George H. Booth (2 shared papers)Jules Tilly (2 shared papers)Hongxiang Chen (2 shared papers)Shuxiang Cao (2 shared papers)
- Journals
- Journal of Chemical Theory and Computation (1 paper)Physics Reports (1 paper)Quantum Machine Intelligence (1 paper)Physical review. A (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Kanav Setia
7 papers receiving 709 citations
Kanav Setia's Hit Papers
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 615
- Atomic and Molecular Physics, and Optics 370
- Computational Theory and Mathematics 119
- Statistical and Nonlinear Physics 22
- Computational Mathematics 1
Countries citing papers authored by Kanav Setia
This map shows the geographic impact of Kanav Setia'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 Kanav Setia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanav Setia more than expected).
Fields of papers citing papers by Kanav Setia
This network shows the impact of papers produced by Kanav Setia. 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 Kanav Setia. The network helps show where Kanav Setia may publish in the future.
Co-authors
The 25 scholars most cited alongside Kanav Setia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The Variational Quantum Eigensolver: A review of methods and best practices Hit paper breakdown → | 2022 | 616 |
| 2 | 2020 | 81 | |
| 3 | 2019 | 7 | |
| 4 | 2021 | 6 | |
| 5 | 2023 | 6 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 1 |
About Kanav Setia
Kanav Setia is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Materials Chemistry, Molecular Biology and Computational Theory and Mathematics, having authored 7 papers that have together received 721 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (7 papers), Quantum Information and Cryptography (4 papers), Quantum and electron transport phenomena (2 papers), Machine Learning in Materials Science (2 papers), Fractal and DNA sequence analysis (1 paper), Neural Networks and Reservoir Computing (1 paper), Radiation Effects in Electronics (1 paper) and Quantum-Dot Cellular Automata (1 paper). The work is most often cited by research in Artificial Intelligence (615 citations), Atomic and Molecular Physics, and Optics (370 citations), Computational Theory and Mathematics (119 citations), Statistical and Nonlinear Physics (22 citations) and Computational Mathematics (1 citation). Kanav Setia has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Dario Picozzi, Jonathan Tennyson, Ying Li, Ivan Rungger, George H. Booth, Jules Tilly, Hongxiang Chen, Shuxiang Cao, Leonard Wossnig and Edward Grant. Their work appears in journals such as Journal of Chemical Theory and Computation, Physics Reports, Quantum Machine Intelligence, Physical review. A and arXiv (Cornell University).
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.