Ye-Hua Liu

1.5k total citations · 1 hit paper
18 papers, 1.0k citations indexed

About

Ye-Hua Liu is a scholar working on Condensed Matter Physics, Atomic and Molecular Physics, and Optics and Artificial Intelligence. According to data from OpenAlex, Ye-Hua Liu has authored 18 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Condensed Matter Physics, 11 papers in Atomic and Molecular Physics, and Optics and 4 papers in Artificial Intelligence. Recurrent topics in Ye-Hua Liu's work include Physics of Superconductivity and Magnetism (8 papers), Magnetic properties of thin films (6 papers) and Quantum many-body systems (5 papers). Ye-Hua Liu is often cited by papers focused on Physics of Superconductivity and Magnetism (8 papers), Magnetic properties of thin films (6 papers) and Quantum many-body systems (5 papers). Ye-Hua Liu collaborates with scholars based in Switzerland, China and United States. Ye-Hua Liu's co-authors include Evert van Nieuwenburg, Sebastian D. Huber, You‐Quan Li, Matthias Troyer, David Poulin, Jung Hoon Han, Lei Wang, Lei Wang, Gergely Harcos and Eunseok Lee and has published in prestigious journals such as Physical Review Letters, Nature Communications and Journal of Applied Physics.

In The Last Decade

Ye-Hua Liu

18 papers receiving 990 citations

Hit Papers

Learning phase transitions by confusion 2017 2026 2020 2023 2017 100 200 300 400

Peers

Ye-Hua Liu
Comparison fields: 5 of 74
  • Atomic and Molecular Physics, and Optics 682
  • Condensed Matter Physics 423
  • Artificial Intelligence 275
  • Materials Chemistry 188
  • Statistical and Nonlinear Physics 153
Replace Andreas Alvermann with:
Andreas Alvermann Germany
Zohar Ringel Israel
Alexandre Dauphin Spain
Mor Verbin Israel
Sriram Ganeshan United States
Marin Bukov United States
Stefan Imhof Germany
Evert van Nieuwenburg Netherlands
Yaacov E. Kraus Israel
Jürgen Lisenfeld Germany
Andreas Alvermann Germany View profile →
Citations per field, relative to Ye-Hua Liu
Ye-Hua Liu · 1×
Citations per year, relative to Ye-Hua Liu
Ye-Hua Liu · 1×

Countries citing papers authored by Ye-Hua Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ye-Hua Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ye-Hua Liu. 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 Ye-Hua Liu. The network helps show where Ye-Hua Liu may publish in the future.

Co-authorship network of co-authors of Ye-Hua Liu

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

All Works

18 of 18 papers shown
# Work Indexed citations
1 59
2 53
3 69
4
Learning phase transitions by confusion breakdown →
473
5
Self-Learning Phase Boundaries by Active Contours
2
6 3
7 12
8 18
9 19
10 55
11 18
12 59
13 17
14 8
15 27
16 56
17 50
18 16

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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