Shuxiang Cao

1.4k citations
13 papers · 629 indexed · 1 hit paper · h-index 5

Shuxiang Cao

13 papers receiving 611 citations

Hit Papers

The Variational Quantum Eigensolver: A review of methods ...5522022202620232024100200300400500

Peers

Shuxiang Cao
Comparison fields: 5 of 46
  • Artificial Intelligence 535
  • Atomic and Molecular Physics, and Optics 325
  • Computational Theory and Mathematics 107
  • Statistical and Nonlinear Physics 22
  • Computational Mathematics 1
Replace Kanav Setia with:
Kanav Setia United States
Hongxiang Chen China
Jules Tilly United Kingdom
Peter Groszkowski United States
Oscar Higgott United Kingdom
Dar Dahlen United States
Harper R. Grimsley United States
Panagiotis Kl. Barkoutsos Switzerland
Russell Stutz United States
Aleksander Kubica United States
Shuxiang Cao relative to Kanav Setia United States Kanav Setia's profile →
Citations per field
00.5×1.5×
Kanav Setia · 1×
Citations per year

Countries citing papers authored by Shuxiang Cao

Since Specialization
Citations

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

Fields of papers citing papers by Shuxiang Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 21 scholars most cited alongside Shuxiang Cao, 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 Shuxiang Cao Line = papers co-authored together Shuxiang Cao links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20251
2 20251
3 20251
4 20244
5 20244
6 202415
7 20231
8
The Variational Quantum Eigensolver: A review of methods and best practicesbreakdown →
2022552
9 202223
10 20221
11 20216
12 202019
13 20191

About Shuxiang Cao

Shuxiang Cao is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Condensed Matter Physics, having authored 13 papers that have together received 629 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (12 papers), Quantum Information and Cryptography (11 papers), Quantum and electron transport phenomena (5 papers), Neural Networks and Reservoir Computing (3 papers), Quantum Mechanics and Applications (2 papers), Physics of Superconductivity and Magnetism (1 paper), Advancements in Semiconductor Devices and Circuit Design (1 paper) and Superconductivity in MgB2 and Alloys (1 paper). The work is most often cited by research in Artificial Intelligence (535 citations), Atomic and Molecular Physics, and Optics (325 citations) and Computational Theory and Mathematics (107 citations). Shuxiang Cao has collaborated with scholars based in United Kingdom, China and Canada. Frequent co-authors include Leonard Wossnig, Edward Grant, Ivan Rungger, Jules Tilly, Hongxiang Chen, Kanav Setia, Ying Li, George H. Booth, Jonathan Tennyson and Peter Leek. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Physics Reports.

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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