P. Gras

93.7k citations
11 papers · 138 · h-index 5

Impact in

    • Particle physics theoretical and experimental studies
    • High-Energy Particle Collisions Research
    • Particle Detector Development and Performance
    • Quantum Chromodynamics and Particle Interactions
    • Dark Matter and Cosmic Phenomena
    • Black Holes and Theoretical Physics

Papers in

P. Gras

9 papers receiving 130 citations

Peers

P. Gras
Comparison fields: 5 of 43
  • Nuclear and High Energy Physics 98
  • Oral Surgery 5
  • Orthodontics 3
  • Hardware and Architecture 5
  • Radiation 5
Replace P. Golonka with:
P. Golonka Switzerland
T. Schlüter Germany
M. Jonker Switzerland
J. How France
S.R. In South Korea
T. M. Hong United States
T. Ngo Germany
S. Huber Germany
R. Lombroni Italy
Andrea Apollonio Switzerland
P. Gras relative to P. Golonka Switzerland P. Golonka's profile →
Citations per field
00.5×10×16×
P. Golonka · 1×
Citations per year

Countries citing papers authored by P. Gras

Since Specialization
Citations

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

Fields of papers citing papers by P. Gras

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside P. Gras, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with P. Gras Line = papers co-authored together P. Gras links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 201787
2 201926
3 20238
4 20085
5 20024
6
Results of the OPC Evaluation Done within JCOP for the Control of the LHC Experiments
19994
7
FRONT-END ELECTRONICS CONFIGURATION SYSTEM FOR CMS
20011
8 20241
9 20151
10 20251
11 20070

About P. Gras

P. Gras is a scholar working on Nuclear and High Energy Physics, Computer Networks and Communications, Biomedical Engineering, Hardware and Architecture and Artificial Intelligence, having authored 11 papers that have together received 138 indexed citations. Recurring topics across this work include Particle Detector Development and Performance (7 papers), Particle physics theoretical and experimental studies (4 papers), Distributed and Parallel Computing Systems (4 papers), Advanced Data Storage Technologies (3 papers), Superconducting Materials and Applications (2 papers), Parallel Computing and Optimization Techniques (2 papers), Computational Physics and Python Applications (2 papers) and Atomic and Subatomic Physics Research (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (98 citations), Oral Surgery (5 citations), Orthodontics (3 citations), Hardware and Architecture (5 citations) and Radiation (5 citations). P. Gras has collaborated with scholars based in France, Switzerland and United Kingdom. Frequent co-authors include Andrzej Siódmok, Stefan Höche, Andrew J. Larkoski, Peter Skands, Simon Plätzer, Grégory Soyez, Jesse Thaler, D. Kar, Leif Lönnblad and David Grossin. Their work appears in journals such as Powder Technology, IEEE Transactions on Nuclear Science, Journal of High Energy Physics, Journal of Instrumentation and Journal of Physics Conference Series.

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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