Denis Boyda

900 total citations
30 papers, 486 citations indexed

About

Denis Boyda is a scholar working on Nuclear and High Energy Physics, Condensed Matter Physics and Mathematical Physics. According to data from OpenAlex, Denis Boyda has authored 30 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Nuclear and High Energy Physics, 8 papers in Condensed Matter Physics and 4 papers in Mathematical Physics. Recurrent topics in Denis Boyda's work include Quantum Chromodynamics and Particle Interactions (15 papers), High-Energy Particle Collisions Research (12 papers) and Particle physics theoretical and experimental studies (11 papers). Denis Boyda is often cited by papers focused on Quantum Chromodynamics and Particle Interactions (15 papers), High-Energy Particle Collisions Research (12 papers) and Particle physics theoretical and experimental studies (11 papers). Denis Boyda collaborates with scholars based in Russia, United States and United Kingdom. Denis Boyda's co-authors include Phiala E. Shanahan, Michael S. Albergo, Daniel C. Hackett, K. Cranmer, Danilo Jimenez Rezende, Sébastien Racanière, Gurtej Kanwar, Maksim Ulybyshev, A. V. Molochkov and Atsushi Nakamura and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Physical Review B.

In The Last Decade

Denis Boyda

26 papers receiving 482 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Denis Boyda Russia 12 204 137 122 95 83 30 486
Michael S. Albergo United States 8 158 0.8× 103 0.8× 139 1.1× 134 1.4× 36 0.4× 14 449
Sebastian J. Wetzel Canada 7 43 0.2× 209 1.5× 136 1.1× 117 1.2× 130 1.6× 9 495
Akio Tomiya China 13 401 2.0× 157 1.1× 84 0.7× 81 0.9× 38 0.5× 39 602
Klas Markström Sweden 14 25 0.1× 72 0.5× 163 1.3× 57 0.6× 19 0.2× 69 585
Ramamurti Shankar United States 4 34 0.2× 183 1.3× 68 0.6× 66 0.7× 33 0.4× 6 342
G. R. Katz United States 7 287 1.4× 112 0.8× 154 1.3× 12 0.1× 20 0.2× 9 550
P. Białas Poland 13 257 1.3× 78 0.6× 141 1.2× 49 0.5× 23 0.3× 47 531
Cody P. Nave United States 7 121 0.6× 701 5.1× 302 2.5× 251 2.6× 104 1.3× 7 879
Vieri Mastropietro Italy 18 103 0.5× 595 4.3× 371 3.0× 33 0.3× 110 1.3× 94 996
J. Stephany Venezuela 9 76 0.4× 91 0.7× 223 1.8× 60 0.6× 27 0.3× 43 430

Countries citing papers authored by Denis Boyda

Since Specialization
Citations

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

Fields of papers citing papers by Denis Boyda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Denis Boyda

This figure shows the co-authorship network connecting the top 25 collaborators of Denis Boyda. A scholar is included among the top collaborators of Denis Boyda 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 Denis Boyda. Denis Boyda 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.
Boyda, Denis, Gurtej Kanwar, Fernando Romero-López, et al.. (2025). Progress in Normalizing Flows for 4d Gauge Theories. Proceedings Of Science. 66–66.
2.
Hackett, Daniel C., Denis Boyda, Gurtej Kanwar, et al.. (2024). Practical applications of machine-learned flows on gauge fields. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 11–11. 6 indexed citations
3.
Abbott, Ryan, Michael S. Albergo, Denis Boyda, et al.. (2024). Multiscale Normalizing Flows for Gauge Theories. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 35–35. 3 indexed citations
4.
Shanahan, Phiala E., Ryan Abbott, Michael S. Albergo, et al.. (2023). Sampling QCD field configurations with gauge-equivariant flow models. Proceedings of The 39th International Symposium on Lattice Field Theory — PoS(LATTICE2022). 10 indexed citations
5.
Abbott, Ryan, Michael S. Albergo, Aleksandar Botev, et al.. (2023). Aspects of scaling and scalability for flow-based sampling of lattice QCD. The European Physical Journal A. 59(11). 19 indexed citations
6.
Chernodub, M. N., et al.. (2022). Applying machine learning methods to prediction problems of lattice observables. SHILAP Revista de lepidopterología. 1 indexed citations
7.
Albergo, Michael S., Denis Boyda, K. Cranmer, et al.. (2022). Flow-based sampling in the lattice Schwinger model at criticality. Physical review. D. 106(1). 24 indexed citations
8.
Albergo, Michael S., Denis Boyda, K. Cranmer, et al.. (2022). Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions. Physical review. D. 106(7). 33 indexed citations
9.
10.
Kanwar, Gurtej, Michael S. Albergo, Denis Boyda, et al.. (2020). Equivariant Flow-Based Sampling for Lattice Gauge Theory. Physical Review Letters. 125(12). 121601–121601. 114 indexed citations
11.
Nakamura, Atsushi, V. G. Bornyakov, Denis Boyda, V. A. Goy, & A. V. Molochkov. (2020). Canonical partition functions in lattice QCD at finite density and temperature. 271–271.
12.
Bornyakov, V. G., Denis Boyda, V. A. Goy, et al.. (2019). Lee-Yang zeros in lattice QCD for searching phase transition points. Physics Letters B. 793. 227–233. 15 indexed citations
13.
Bornyakov, V. G., Denis Boyda, V. A. Goy, et al.. (2018). Lattice QCD at finite baryon density using analytic continuation. Springer Link (Chiba Institute of Technology). 4 indexed citations
14.
Bornyakov, V. G., Denis Boyda, V. A. Goy, et al.. (2018). Restoring canonical partition functions from imaginary chemical potential. SHILAP Revista de lepidopterología. 175. 7027–7027. 2 indexed citations
15.
Boyda, Denis, V. V. Braguta, M. I. Katsnelson, & A. Yu. Kotov. (2018). Phase diagram and Chiral Magnetic Effect in Dirac Semimetals from Lattice Simulation. SHILAP Revista de lepidopterología. 175. 3001–3001. 2 indexed citations
16.
Boyda, Denis, V. G. Bornyakov, V. A. Goy, et al.. (2017). Lattice Study of QCD Phase Structure by Canonical Approach - Towards determining the phase transition line. arXiv (Cornell University). 2 indexed citations
17.
Stauber, Tobias, Prakash Parida, Maxim Trushin, et al.. (2017). Interacting Electrons in Graphene: Fermi Velocity Renormalization and Optical Response. Physical Review Letters. 118(26). 266801–266801. 53 indexed citations
18.
Boyda, Denis, V. G. Bornyakov, V. A. Goy, et al.. (2016). Novel approach to deriving the canonical generating functional in lattice QCD at a finite chemical potential. Journal of Experimental and Theoretical Physics Letters. 104(10). 657–661. 8 indexed citations
19.
Belov, Oleg, et al.. (2015). Simulation of the charge migration in DNA under irradiation with heavy ions. Bio-Medical Materials and Engineering. 26(1_suppl). S1937–44. 9 indexed citations
20.
Boyda, Denis, et al.. (2013). Study of DNA conducting properties: Reversible and irreversible evolution. Biophysical Chemistry. 180-181. 95–101. 9 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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