A. Mott
Impact in
- Artificial Intelligence top 10%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
- Computational Physics and Python Applications
- Neural Networks and Applications
-
- Particle physics theoretical and experimental studies
Papers in
-
- Quantum Computing Algorithms and Architecture 2
- Computational Physics and Python Applications 2
- Quantum Information and Cryptography 1
-
- Particle physics theoretical and experimental studies 2
- Particle Detector Development and Performance 1
- High-Energy Particle Collisions Research 1
- Co-authors
- Daniel A. Lidar (2 shared papers)M. Spiropulu (3 shared papers)Joshua Job (2 shared papers)Jean-Roch Vlimant (2 shared papers)Alexander Zlokapa (1 shared paper)A. Bornheim (1 shared paper)H. B. Newman (1 shared paper)Y. G. (1 shared paper)
- Journals
- Physical review. A (1 paper)Nature (1 paper)LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
A. Mott
4 papers receiving 154 citations
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 126
- Nuclear and High Energy Physics 26
- Hardware and Architecture 9
- Computational Theory and Mathematics 20
- Atomic and Molecular Physics, and Optics 33
Countries citing papers authored by A. Mott
This map shows the geographic impact of A. Mott'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 A. Mott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Mott more than expected).
Fields of papers citing papers by A. Mott
This network shows the impact of papers produced by A. Mott. 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 A. Mott. The network helps show where A. Mott may publish in the future.
Co-authors
The 25 scholars most cited alongside A. Mott, 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 | 2017 | 135 | |
| 2 | 2020 | 17 | |
| 3 | Search for Supersymmetry in pp Collisions at √s = 7 Te V in Events with Two Photons and Missing Transverse Energy | 2011 | 3 |
| 4 | S3TA: A Soft, Spatial, Sequential, Top-Down Attention Model | 2018 | 2 |
About A. Mott
A. Mott is a scholar working on Artificial Intelligence, Nuclear and High Energy Physics, Cognitive Neuroscience, Infectious Diseases and Organic Chemistry, having authored 4 papers that have together received 157 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (2 papers), Particle physics theoretical and experimental studies (2 papers), Computational Physics and Python Applications (2 papers), EEG and Brain-Computer Interfaces (1 paper), Particle Detector Development and Performance (1 paper), Quantum Information and Cryptography (1 paper), Functional Brain Connectivity Studies (1 paper) and High-Energy Particle Collisions Research (1 paper). The work is most often cited by research in Artificial Intelligence (126 citations), Nuclear and High Energy Physics (26 citations), Hardware and Architecture (9 citations), Computational Theory and Mathematics (20 citations) and Atomic and Molecular Physics, and Optics (33 citations). A. Mott has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Daniel A. Lidar, M. Spiropulu, Joshua Job, Jean-Roch Vlimant, Alexander Zlokapa, A. Bornheim, H. B. Newman, Y. G., Danilo Jimenez Rezende and S. Chatrchyan. Their work appears in journals such as Physical review. A, Nature and LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas).
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.