Stefano Paesani

2.9k citations
44 papers · 1.5k indexed · 1 hit paper · h-index 14
Topics
Quantum Information and Cryptography (35 papers)Neural Networks and Reservoir Computing (26 papers)Quantum Computing Algorithms and Architecture (18 papers)

In The Last Decade

Stefano Paesani

40 papers receiving 1.4k citations

Hit Papers

An optical neural chip for implementing complex-valued ne...20212026202220242021100200300400

Peers

Stefano Paesani
Comparison fields: 5 of 57
  • Artificial Intelligence 1.2k
  • Electrical and Electronic Engineering 781
  • Atomic and Molecular Physics, and Optics 638
  • Materials Chemistry 56
  • Biomedical Engineering 54
Replace M. Menotti with:
M. Menotti Italy
Chris Sparrow United Kingdom
Nicolás Quesada Canada
Enrique Martín-López United Kingdom
Z. Vernon Canada
Davide Bacco Denmark
Sheng‐Kai Liao China
Guilherme B. Xavier Chile
Anthony Martin Switzerland
Stefano Paesani relative to M. Menotti Italy M. Menotti's profile →
Citations per field
00.5×5.7×
M. Menotti · 1×
Citations per year

Countries citing papers authored by Stefano Paesani

Since Specialization
Citations

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

Fields of papers citing papers by Stefano Paesani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefano Paesani

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 3
4 0
5 9
6 5
7 41
8 16
9 19
10 6
11 26
12 38
13 12
14 121
15 3
16 0
17 135
18 124
19
Quantum simulation of Hamiltonian spectra on a silicon chip
4
20 66

About Stefano Paesani

Stefano Paesani is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Electrical and Electronic Engineering, having authored 44 papers that have together received 1.5k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (35 papers), Neural Networks and Reservoir Computing (26 papers) and Quantum Computing Algorithms and Architecture (18 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Atomic and Molecular Physics, and Optics (638 citations) and Acoustics and Ultrasonics (17 citations). Stefano Paesani has collaborated with scholars based in United Kingdom, Denmark and China. Frequent co-authors include Anthony Laing, Raffaele Santagati, Mark G. Thompson, Jianwei Wang, Nathan Wiebe, Antonio A. Gentile, Jeremy L. O’Brien, A. Q. Liu, L. C. Kwek and Hong Cai. Their work appears in journals such as Physical Review Letters, Nature Communications and Nature Physics.

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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