Philippe Faist

1.1k citations
22 papers · 672 · h-index 12

Impact in

Papers in

Philippe Faist

22 papers receiving 668 citations

Peers

Philippe Faist
Comparison fields: 5 of 51
  • Statistical and Nonlinear Physics 342
  • Atomic and Molecular Physics, and Optics 451
  • Artificial Intelligence 441
  • Computational Mathematics 2
  • Nuclear and High Energy Physics 32
Replace Carlo Cafaro with:
Carlo Cafaro United States
Zhiming Huang China
Łukasz Rudnicki Poland
Gabriel G. Carlo Argentina
Milán Mosonyi Hungary
S. Salimi Iran
D�nes Petz Hungary
Alan R. Derk United States
Salman Beigi Iran
Roope Uola Switzerland
Philippe Faist relative to Carlo Cafaro United States Carlo Cafaro's profile →
Citations per field
00.5×2×2.7×
Carlo Cafaro · 1×
Citations per year

Countries citing papers authored by Philippe Faist

Since Specialization
Citations

This map shows the geographic impact of Philippe Faist'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 Philippe Faist with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Faist more than expected).

Fields of papers citing papers by Philippe Faist

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philippe Faist. 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 Philippe Faist. The network helps show where Philippe Faist may publish in the future.

Co-authors

The 25 scholars most cited alongside Philippe Faist, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Philippe Faist Line = papers co-authored together Philippe Faist links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022105
2 2015104
3 2016102
4 201645
5 201642
6 201839
7 201538
8 201337
9 201934
10 202030
11 202221
12 201912
13 202011
14 201911
15 20239
16 20188
17 20217
18 20255
19 20255
20 20213

About Philippe Faist

Philippe Faist is a scholar working on Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics, Artificial Intelligence, Computational Theory and Mathematics and Numerical Analysis, having authored 22 papers that have together received 672 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (14 papers), Quantum Mechanics and Applications (12 papers), Advanced Thermodynamics and Statistical Mechanics (11 papers), Quantum Computing Algorithms and Architecture (10 papers), Quantum many-body systems (7 papers), Statistical Mechanics and Entropy (2 papers), Spectroscopy and Quantum Chemical Studies (2 papers) and Computability, Logic, AI Algorithms (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (342 citations), Atomic and Molecular Physics, and Optics (451 citations), Artificial Intelligence (441 citations), Computational Mathematics (2 citations) and Nuclear and High Energy Physics (32 citations). Philippe Faist has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Renato Renner, Jonathan Oppenheim, Nicole Yunger Halpern, Frédéric Dupuis, Jens Eisert, Andreas J. Winter, Jonas Haferkamp, Fernando G. S. L. Brandão, Mario Berta and Mirjam Weilenmann. Their work appears in journals such as Physical Review Letters, PRX Quantum, Nature Communications, Physical Review A and Journal of Physics A Mathematical and Theoretical.

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.

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