Mio Murao
- Artificial Intelligence top 0.5%
- Atomic and Molecular Physics, and Optics top 1%
- Statistical and Nonlinear Physics top 5%
- Computational Theory and Mathematics top 10%
- Electrical and Electronic Engineering
- Co-authors
- Vlatko VedralMartin B. PlenioDaniel JonathanDamian MarkhamAkihito SoedaP. L. KnightMasaki OwariS. Virmani
- Topics
- Quantum Information and Cryptography (67 papers)Quantum Computing Algorithms and Architecture (56 papers)Quantum Mechanics and Applications (42 papers)
- Partner nations
- JapanUnited KingdomSingapore
In The Last Decade
Mio Murao
72 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 1.6k
- Atomic and Molecular Physics, and Optics 1.6k
- Statistical and Nonlinear Physics 129
- Computational Theory and Mathematics 58
- Electrical and Electronic Engineering 55
Countries citing papers authored by Mio Murao
This map shows the geographic impact of Mio Murao'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 Mio Murao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mio Murao more than expected).
Fields of papers citing papers by Mio Murao
This network shows the impact of papers produced by Mio Murao. 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 Mio Murao. The network helps show where Mio Murao may publish in the future.
Co-authorship network of co-authors of Mio Murao
This figure shows the co-authorship network connecting the top 25 collaborators of Mio Murao. A scholar is included among the top collaborators of Mio Murao 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 Mio Murao. Mio Murao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 5 | |
| 4 | 4 | |
| 5 | 15 | |
| 6 | 12 | |
| 7 | 31 | |
| 8 | 49 | |
| 9 | 10 | |
| 10 | Reversing unknown quantum transformations: A universal protocol for inverting general unitary operations | 1 |
| 11 | 10 | |
| 12 | 26 | |
| 13 | 38 | |
| 14 | Translating measurement-based quantum computation with gflow into quantum circuit | 0 |
| 15 | Diagonal-unitary t-designs and their constructions | 1 |
| 16 | 6 | |
| 17 | 5 | |
| 18 | 125 | |
| 19 | 83 | |
| 20 | Generalisation of purification to multi-particle entanglement | 0 |
About Mio Murao
Mio Murao is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics, having authored 75 papers that have together received 1.8k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (67 papers), Quantum Computing Algorithms and Architecture (56 papers) and Quantum Mechanics and Applications (42 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Atomic and Molecular Physics, and Optics (1.6k citations) and Computational Mathematics (22 citations). Mio Murao has collaborated with scholars based in Japan, United Kingdom and Singapore. Frequent co-authors include Vlatko Vedral, Martin B. Plenio, Daniel Jonathan, Damian Markham, Akihito Soeda, P. L. Knight, Masaki Owari, S. Virmani, Ştefan Popescu and Peter S. Turner. Their work appears in journals such as Physical Review Letters, Nature Communications and IEEE Transactions on Information Theory.
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.