Danylo Lykov
Impact in
- Computational Mathematics top 10%
- Tensor decomposition and applications
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Papers in
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- Quantum Computing Algorithms and Architecture 10
- Quantum Information and Cryptography 7
- Stochastic Gradient Optimization Techniques 1
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- Parallel Computing and Optimization Techniques 5
- Co-authors
- Jonathan Wurtz (2 shared papers)Yuri Alexeev (8 shared papers)Ivan Oseledets (1 shared paper)Alexey Galda (2 shared papers)C. Poole (1 shared paper)M. Saffman (1 shared paper)Thomas Noël (1 shared paper)Yue Sun (1 shared paper)
- Journals
- Physical review. A (2 papers)npj Quantum Information (1 paper)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- United StatesRussia
In The Last Decade
Danylo Lykov
10 papers receiving 131 citations
Peers
Comparison fields: 5 of 21
- Computational Mathematics 11
- Hardware and Architecture 31
- Artificial Intelligence 124
- Computational Theory and Mathematics 36
- Atomic and Molecular Physics, and Optics 32
Countries citing papers authored by Danylo Lykov
This map shows the geographic impact of Danylo Lykov'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 Danylo Lykov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danylo Lykov more than expected).
Fields of papers citing papers by Danylo Lykov
This network shows the impact of papers produced by Danylo Lykov. 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 Danylo Lykov. The network helps show where Danylo Lykov may publish in the future.
Co-authors
The 22 scholars most cited alongside Danylo Lykov, 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 | 2021 | 40 | |
| 2 | 2023 | 22 | |
| 3 | 2022 | 15 | |
| 4 | 2020 | 14 | |
| 5 | 2023 | 13 | |
| 6 | 2023 | 12 | |
| 7 | 2021 | 9 | |
| 8 | 2022 | 5 | |
| 9 | 2022 | 5 | |
| 10 | 2023 | 2 |
About Danylo Lykov
Danylo Lykov is a scholar working on Artificial Intelligence, Hardware and Architecture, Computational Mathematics, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics, having authored 10 papers that have together received 137 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (10 papers), Quantum Information and Cryptography (7 papers), Parallel Computing and Optimization Techniques (5 papers), Quantum and electron transport phenomena (2 papers), Tensor decomposition and applications (2 papers), Quantum-Dot Cellular Automata (1 paper), Low-power high-performance VLSI design (1 paper) and Stochastic Gradient Optimization Techniques (1 paper). The work is most often cited by research in Computational Mathematics (11 citations), Hardware and Architecture (31 citations), Artificial Intelligence (124 citations), Computational Theory and Mathematics (36 citations) and Atomic and Molecular Physics, and Optics (32 citations). Danylo Lykov has collaborated with scholars based in United States and Russia. Frequent co-authors include Jonathan Wurtz, Yuri Alexeev, Ivan Oseledets, Alexey Galda, C. Poole, M. Saffman, Thomas Noël, Yue Sun, Marco Pistoia and Ruslan Shaydulin. Their work appears in journals such as Physical review. A, npj Quantum Information and SHILAP Revista de lepidopterología.
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.