Daniel D. Scherer

837 total citations
30 papers, 543 citations indexed

About

Daniel D. Scherer is a scholar working on Condensed Matter Physics, Artificial Intelligence and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Daniel D. Scherer has authored 30 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Condensed Matter Physics, 10 papers in Artificial Intelligence and 9 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Daniel D. Scherer's work include Quantum Computing Algorithms and Architecture (9 papers), Physics of Superconductivity and Magnetism (9 papers) and Iron-based superconductors research (7 papers). Daniel D. Scherer is often cited by papers focused on Quantum Computing Algorithms and Architecture (9 papers), Physics of Superconductivity and Magnetism (9 papers) and Iron-based superconductors research (7 papers). Daniel D. Scherer collaborates with scholars based in Germany, Denmark and United States. Daniel D. Scherer's co-authors include Holger Gies, Jens Braun, Michael M. Scherer, Brian M. Andersen, Carsten Honerkamp, Ilya Eremin, Astrid T. Rømer, P. J. Hirschfeld, Christopher Mutschler and Axel Plinge and has published in prestigious journals such as Physical Review Letters, Physical Review B and Journal of the Franklin Institute.

In The Last Decade

Daniel D. Scherer

28 papers receiving 526 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel D. Scherer Germany 14 290 191 177 126 62 30 543
Tom Heitmann United States 8 213 0.7× 120 0.6× 120 0.7× 7 0.1× 20 0.3× 20 314
Bin-Bin Chen China 17 359 1.2× 410 2.1× 91 0.5× 13 0.1× 76 1.2× 28 579
Ryan V. Mishmash United States 15 313 1.1× 488 2.6× 50 0.3× 13 0.1× 107 1.7× 22 604
Richard J. Creswick United States 10 188 0.6× 104 0.5× 28 0.2× 16 0.1× 10 0.2× 19 270
E. Lahoud Israel 10 374 1.3× 864 4.5× 144 0.8× 4 0.0× 114 1.8× 12 991
Eli Levenson-Falk United States 12 169 0.6× 490 2.6× 34 0.2× 13 0.1× 191 3.1× 23 587
E. Boaknin Canada 8 243 0.8× 264 1.4× 157 0.9× 4 0.0× 186 3.0× 12 463
Daniel Bothner Germany 13 205 0.7× 404 2.1× 37 0.2× 5 0.0× 147 2.4× 31 509
Alban L. Fauchère Switzerland 9 413 1.4× 502 2.6× 122 0.7× 7 0.1× 118 1.9× 12 589
Ofer Naaman United States 13 179 0.6× 452 2.4× 37 0.2× 8 0.1× 197 3.2× 25 552

Countries citing papers authored by Daniel D. Scherer

Since Specialization
Citations

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

Fields of papers citing papers by Daniel D. Scherer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel D. Scherer. 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 Daniel D. Scherer. The network helps show where Daniel D. Scherer may publish in the future.

Co-authorship network of co-authors of Daniel D. Scherer

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel D. Scherer. A scholar is included among the top collaborators of Daniel D. Scherer 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 Daniel D. Scherer. Daniel D. Scherer 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
1.
Scherer, Daniel D., et al.. (2025). Fourier Analysis of Variational Quantum Circuits for Supervised Learning. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1785–1795.
2.
Scherer, Daniel D., et al.. (2024). BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1–9. 2 indexed citations
3.
Plinge, Axel, et al.. (2024). Comprehensive Library of Variational LSE Solvers. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1–4. 1 indexed citations
4.
Geiger, M., Christian Ufrecht, Axel Plinge, et al.. (2024). SCIM MILQ: An HPC Quantum Scheduler. mediaTUM (Technical University of Munich). 292–298. 2 indexed citations
5.
Plinge, Axel, et al.. (2024). Guided-SPSA: Simultaneous Perturbation Stochastic Approximation Assisted by the Parameter Shift Rule. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1504–1515. 4 indexed citations
6.
Ufrecht, Christian, et al.. (2024). Optimal joint cutting of two-qubit rotation gates. Physical review. A. 109(5). 6 indexed citations
7.
Plinge, Axel, et al.. (2024). Unitary Synthesis of Clifford+T Circuits with Reinforcement Learning. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 824–835. 2 indexed citations
8.
Popov, Alexander I., et al.. (2024). Warm-Start Variational Quantum Policy Iteration. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1458–1466.
9.
Ufrecht, Christian, et al.. (2023). An Empirical Comparison of Optimizers for Quantum Machine Learning with SPSA-Based Gradients. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 450–456. 13 indexed citations
10.
Ufrecht, Christian, et al.. (2023). Cutting multi-control quantum gates with ZX calculus. Quantum. 7. 1147–1147. 13 indexed citations
11.
Scherer, Daniel D., et al.. (2023). Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 36–41. 6 indexed citations
12.
Zhou, Rui, Daniel D. Scherer, H. Mayaffre, et al.. (2020). Singular magnetic anisotropy in the nematic phase of FeSe. npj Quantum Materials. 5(1). 15 indexed citations
13.
Rømer, Astrid T., Daniel D. Scherer, Ilya Eremin, P. J. Hirschfeld, & Brian M. Andersen. (2019). Knight Shift and Leading Superconducting Instability from Spin Fluctuations in Sr2RuO4. Physical Review Letters. 123(24). 247001–247001. 74 indexed citations
14.
Andersen, Brian M. & Daniel D. Scherer. (2018). Spin-Orbit Coupling and Magnetic Anisotropy in Iron-Based Superconductors. Bulletin of the American Physical Society. 2018. 1 indexed citations
15.
Lu, Xingye, Daniel D. Scherer, Wenliang Zhang, et al.. (2018). Spin Waves in Detwinned BaFe2As2. Physical Review Letters. 121(6). 67002–67002. 23 indexed citations
16.
Scherer, Daniel D. & Brian M. Andersen. (2018). Spin-Orbit Coupling and Magnetic Anisotropy in Iron-Based Superconductors. Physical Review Letters. 121(3). 37205–37205. 11 indexed citations
17.
Scherer, Daniel D., et al.. (2018). Topological superconductivity in the extended Kitaev-Heisenberg model. Physical review. B.. 97(1). 11 indexed citations
18.
Scherer, Daniel D., et al.. (2016). Electronic instabilities of the extended Hubbard model on the honeycomb lattice from functional renormalization. Physical review. B.. 94(16). 16 indexed citations
19.
Scherer, Daniel D., Michael M. Scherer, & Carsten Honerkamp. (2015). Correlated spinless fermions on the honeycomb lattice revisited. Physical Review B. 92(15). 39 indexed citations
20.
Scherer, Daniel D. & Holger Gies. (2012). Renormalization group study of magnetic catalysis in the3dGross-Neveu model. Physical Review B. 85(19). 33 indexed citations

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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