Michael Hecht
Impact in
-
- Black Holes and Theoretical Physics
- Geometry and Topology top 10%
- Algebraic Geometry and Number Theory
Papers in
-
- Scientific Research and Discoveries 2
- Nonlinear Waves and Solitons 2
- Model Reduction and Neural Networks 2
- Co-authors
- Peter Mayr (2 shared papers)Hans Jockers (2 shared papers)Masoud Soroush (2 shared papers)M. A. Alim (1 shared paper)Antje Mertens (1 shared paper)Murad Alim (2 shared papers)M. Schwartz (1 shared paper)Albrecht Klemm (1 shared paper)
- Journals
- Nuclear Physics B (1 paper)Journal of Fixed Point Theory and Applications (1 paper)Theory of Computing Systems (1 paper)SIAM Journal on Numerical Analysis (1 paper)Machine Learning Science and Technology (1 paper)
- Partner nations
- GermanyUnited StatesPoland
In The Last Decade
Michael Hecht
19 papers receiving 204 citations
Peers
Comparison fields: 5 of 49
- Nuclear and High Energy Physics 69
- Geometry and Topology 34
- Statistical and Nonlinear Physics 35
- Mathematical Physics 20
- Astronomy and Astrophysics 33
Countries citing papers authored by Michael Hecht
This map shows the geographic impact of Michael Hecht'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 Michael Hecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Hecht more than expected).
Fields of papers citing papers by Michael Hecht
This network shows the impact of papers produced by Michael Hecht. 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 Michael Hecht. The network helps show where Michael Hecht may publish in the future.
Co-authors
The 18 scholars most cited alongside Michael Hecht, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1974 | 51 | |
| 2 | 2010 | 44 | |
| 3 | Delay modulation | 1969 | 41 |
| 4 | 2023 | 21 | |
| 5 | 2015 | 19 | |
| 6 | 2011 | 15 | |
| 7 | 1968 | 9 | |
| 8 | 2017 | 4 | |
| 9 | 2025 | 2 | |
| 10 | 2024 | 2 | |
| 11 | 2023 | 2 | |
| 12 | 2016 | 2 | |
| 13 | Switch matrix for TWTA redundancy on communication satellites | 1978 | 2 |
| 14 | 2023 | 1 | |
| 15 | 2025 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2009 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2013 | 1 | |
| 20 | 2025 | 0 |
About Michael Hecht
Michael Hecht is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computational Theory and Mathematics, Nuclear and High Energy Physics and Electrical and Electronic Engineering, having authored 21 papers that have together received 220 indexed citations. Recurring topics across this work include Black Holes and Theoretical Physics (3 papers), Quantum, superfluid, helium dynamics (2 papers), Scientific Research and Discoveries (2 papers), Probabilistic and Robust Engineering Design (2 papers), Advanced Numerical Analysis Techniques (2 papers), Nonlinear Waves and Solitons (2 papers), Algebraic Geometry and Number Theory (2 papers) and Model Reduction and Neural Networks (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (69 citations), Geometry and Topology (34 citations), Statistical and Nonlinear Physics (35 citations), Mathematical Physics (20 citations) and Astronomy and Astrophysics (33 citations). Michael Hecht has collaborated with scholars based in Germany, United States and Poland. Frequent co-authors include Peter Mayr, Hans Jockers, Masoud Soroush, M. A. Alim, Antje Mertens, Murad Alim, M. Schwartz, Albrecht Klemm, Tobias Dornheim and Maximilian Böhme. Their work appears in journals such as Nuclear Physics B, Journal of Fixed Point Theory and Applications, Theory of Computing Systems, SIAM Journal on Numerical Analysis and Machine Learning Science and Technology.
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.