Lorenzo Leone

32 total papers · 912 total citations
20 papers, 601 citations indexed

About

Lorenzo Leone is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics. According to data from OpenAlex, Lorenzo Leone has authored 20 papers receiving a total of 601 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 15 papers in Atomic and Molecular Physics, and Optics and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Lorenzo Leone's work include Quantum Computing Algorithms and Architecture (16 papers), Quantum Information and Cryptography (15 papers) and Quantum many-body systems (14 papers). Lorenzo Leone is often cited by papers focused on Quantum Computing Algorithms and Architecture (16 papers), Quantum Information and Cryptography (15 papers) and Quantum many-body systems (14 papers). Lorenzo Leone collaborates with scholars based in United States, Italy and Germany. Lorenzo Leone's co-authors include Salvatore F. E. Oliviero, Alioscia Hamma, Seth Lloyd, Lennart Bittel, M. Cerezo, Łukasz Cincio, Francesco Caravelli, You Zhou, Sofiène Jerbi and Jens Eisert and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Nature Physics.

In The Last Decade

Lorenzo Leone

19 papers receiving 591 citations

Hit Papers

Stabilizer Rényi Entropy 2022 2026 2023 2024 2022 2024 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Lorenzo Leone 396 394 103 23 22 20 601
Salvatore F. E. Oliviero 409 1.0× 397 1.0× 106 1.0× 23 1.0× 23 1.0× 19 606
Matteo Ippoliti 556 1.4× 273 0.7× 119 1.2× 14 0.6× 29 1.3× 30 614
Johnnie Gray 404 1.0× 355 0.9× 78 0.8× 30 1.3× 10 0.5× 16 541
Joseph Tindall 486 1.2× 220 0.6× 143 1.4× 7 0.3× 12 0.5× 18 563
Hengyan Wang 443 1.1× 357 0.9× 141 1.4× 46 2.0× 24 1.1× 20 590
Tibor Rakovszky 589 1.5× 258 0.7× 173 1.7× 24 1.0× 35 1.6× 20 652
Daniel Nagaj 409 1.0× 513 1.3× 48 0.5× 123 5.3× 7 0.3× 29 649
Martin Ganahl 581 1.5× 124 0.3× 94 0.9× 23 1.0× 19 0.9× 26 640
Ion Nechita 336 0.8× 378 1.0× 75 0.7× 43 1.9× 11 0.5× 51 529
Jin-Guo Liu 285 0.7× 333 0.8× 51 0.5× 58 2.5× 13 0.6× 13 525

Countries citing papers authored by Lorenzo Leone

Since Specialization
Citations

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

Fields of papers citing papers by Lorenzo Leone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lorenzo Leone

This figure shows the co-authorship network connecting the top 25 collaborators of Lorenzo Leone. A scholar is included among the top collaborators of Lorenzo Leone 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 Lorenzo Leone. Lorenzo Leone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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