micrOMEGAs 6.0: N-component dark matter
Impact in
Classified as
- Journal
- Computer Physics Communications
In The Last Decade
doi.org/10.1016/j.cpc.2024.109133 →Countries where authors are citing micrOMEGAs 6.0: N-component dark matter
This map shows the geographic impact of micrOMEGAs 6.0: N-component dark matter. 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 micrOMEGAs 6.0: N-component dark matter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites micrOMEGAs 6.0: N-component dark matter more than expected).
Fields of papers citing micrOMEGAs 6.0: N-component dark matter
This network shows the impact of micrOMEGAs 6.0: N-component dark matter. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the micrOMEGAs 6.0: N-component dark matter.
About micrOMEGAs 6.0: N-component dark matter
This paper, published in 2024, received 64 indexed citations . Written by G. Bélanger, F. Boudjema, Andreas Goudelis, Sabine Kraml and A. Pukhov covering the research area of Nuclear and High Energy Physics and Astronomy and Astrophysics. It is primarily cited by scholars working on Nuclear and High Energy Physics (58 citations), Astronomy and Astrophysics (43 citations), Atomic and Molecular Physics, and Optics (3 citations), Statistical and Nonlinear Physics (2 citations) and Artificial Intelligence (2 citations). Published in Computer Physics Communications.
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.
This paper is also available at doi.org/10.1016/j.cpc.2024.109133.