Mladen Pavičić
- Atomic and Molecular Physics, and Optics top 5%
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Statistical and Nonlinear Physics top 10%
- Electrical and Electronic Engineering
- Co-authors
- Harry PaulJohann SummhammerJean‐Pierre MerletP. K. AravindMordecai WaegellJarosław Pykacz
- Topics
- Quantum Mechanics and Applications (32 papers)Quantum Information and Cryptography (26 papers)Quantum Computing Algorithms and Architecture (15 papers)
- Cited by
- Atomic and Molecular Physics, and OpticsArtificial IntelligenceComputational Theory and Mathematics
- Partner nations
- CroatiaGermanyUnited States
In The Last Decade
Mladen Pavičić
54 papers receiving 440 citations
Peers
Comparison fields: 5 of 32
- Atomic and Molecular Physics, and Optics 381
- Artificial Intelligence 358
- Computational Theory and Mathematics 95
- Statistical and Nonlinear Physics 46
- Electrical and Electronic Engineering 21
Countries citing papers authored by Mladen Pavičić
This map shows the geographic impact of Mladen Pavičić'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 Mladen Pavičić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mladen Pavičić more than expected).
Fields of papers citing papers by Mladen Pavičić
This network shows the impact of papers produced by Mladen Pavičić. 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 Mladen Pavičić. The network helps show where Mladen Pavičić may publish in the future.
Co-authorship network of co-authors of Mladen Pavičić
This figure shows the co-authorship network connecting the top 25 collaborators of Mladen Pavičić. A scholar is included among the top collaborators of Mladen Pavičić 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 Mladen Pavičić. Mladen Pavičić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | Superdense Coding with Linear Optics | 1 |
| 6 | 3 | |
| 7 | 127 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | Quantum Computers, Discrete Space, and Entanglement | 2 |
| 11 | 13 | |
| 12 | Equations and State and Lattice Properties That Hold in Infinite Dimensional Hilbert Space | 1 |
| 13 | 2 | |
| 14 | 18 | |
| 15 | 18 | |
| 16 | 17 | |
| 17 | 4 | |
| 18 | 4 | |
| 19 | 1 | |
| 20 | 6 |
About Mladen Pavičić
Mladen Pavičić is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics, having authored 57 papers that have together received 478 indexed citations. Recurring topics across this work include Quantum Mechanics and Applications (32 papers), Quantum Information and Cryptography (26 papers) and Quantum Computing Algorithms and Architecture (15 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (381 citations), Artificial Intelligence (358 citations) and Computational Theory and Mathematics (95 citations). Mladen Pavičić has collaborated with scholars based in Croatia, Germany and United States. Frequent co-authors include Harry Paul, Johann Summhammer, Jean‐Pierre Merlet, P. K. Aravind, Mordecai Waegell and Jarosław Pykacz. Their work appears in journals such as Physical Review Letters, Physical Review A and Physics Letters A.
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.