Giacomo Guarnieri
- Atomic and Molecular Physics, and Optics top 5%
- Statistical and Nonlinear Physics top 1%
- Artificial Intelligence top 2%
- Civil and Structural Engineering top 10%
- Electrical and Electronic Engineering
- Co-authors
- John GooldGabriel T. LandiMark T. MitchisonBassano VacchiniSteve CampbellAndré M. TimpanaroHarry J. D. MillerStephen R. L. Clark
- Topics
- Advanced Thermodynamics and Statistical Mechanics (25 papers)Quantum Information and Cryptography (22 papers)Quantum Mechanics and Applications (11 papers)
- Cited by
- Statistical and Nonlinear PhysicsAtomic and Molecular Physics, and OpticsArtificial Intelligence
In The Last Decade
Giacomo Guarnieri
49 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 47
- Atomic and Molecular Physics, and Optics 827
- Statistical and Nonlinear Physics 720
- Artificial Intelligence 582
- Civil and Structural Engineering 136
- Electrical and Electronic Engineering 131
Countries citing papers authored by Giacomo Guarnieri
This map shows the geographic impact of Giacomo Guarnieri'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 Giacomo Guarnieri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giacomo Guarnieri more than expected).
Fields of papers citing papers by Giacomo Guarnieri
This network shows the impact of papers produced by Giacomo Guarnieri. 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 Giacomo Guarnieri. The network helps show where Giacomo Guarnieri may publish in the future.
Co-authorship network of co-authors of Giacomo Guarnieri
This figure shows the co-authorship network connecting the top 25 collaborators of Giacomo Guarnieri. A scholar is included among the top collaborators of Giacomo Guarnieri 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 Giacomo Guarnieri. Giacomo Guarnieri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 6 | |
| 7 | 6 | |
| 8 | 21 | |
| 9 | 8 | |
| 10 | 69 | |
| 11 | 34 | |
| 12 | 18 | |
| 13 | 40 | |
| 14 | Quantum many-body attractor with strictly local dynamical symmetries | 2 |
| 15 | 127 | |
| 16 | 76 | |
| 17 | 130 | |
| 18 | 17 | |
| 19 | 69 | |
| 20 | 1 |
About Giacomo Guarnieri
Giacomo Guarnieri is a scholar working on Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics and Artificial Intelligence, having authored 50 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Thermodynamics and Statistical Mechanics (25 papers), Quantum Information and Cryptography (22 papers) and Quantum Mechanics and Applications (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (720 citations), Atomic and Molecular Physics, and Optics (827 citations) and Artificial Intelligence (582 citations). Giacomo Guarnieri has collaborated with scholars based in Italy, Ireland and Germany. Frequent co-authors include John Goold, Gabriel T. Landi, Mark T. Mitchison, Bassano Vacchini, Steve Campbell, André M. Timpanaro, Harry J. D. Miller, Stephen R. L. Clark, Gianluca Francica and Francesco Plastina. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.
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.