Arnaud Münch

1.1k citations
71 papers · 659 indexed · h-index 16

Impact in

Papers in

Arnaud Münch

64 papers receiving 620 citations

Peers

Arnaud Münch
Comparison fields: 5 of 46
  • Mathematical Physics 285
  • Computational Theory and Mathematics 453
  • Control and Systems Engineering 437
  • Numerical Analysis 71
  • Computational Mechanics 146
Replace Maria Grazia Naso with:
Maria Grazia Naso Italy
Cheng-Zhong Xu France
Françis Conrad France
Francisco Periago Spain
J. Nečas Czechia
Ana L. Silvestre Portugal
Feng‐Fei Jin China
Caroline Fabre France
Baowei Feng China
Arnaud Münch relative to Maria Grazia Naso Italy Maria Grazia Naso's profile →
Citations per field
00.5×4.6×
Maria Grazia Naso · 1×
Citations per year

Countries citing papers authored by Arnaud Münch

Since Specialization
Citations

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

Fields of papers citing papers by Arnaud Münch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Arnaud Münch, 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 Arnaud Münch Line = papers co-authored together Arnaud Münch links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201046
2 200532
3 200729
4 200628
5 201227
6 200727
7 201424
8 201323
9 201322
10 201419
11 200719
12 201917
13 201416
14 201016
15 201015
16 200715
17 201414
18 201614
19 200813
20 201513

About Arnaud Münch

Arnaud Münch is a scholar working on Computational Theory and Mathematics, Control and Systems Engineering, Mathematical Physics, Computational Mechanics and Mechanics of Materials, having authored 71 papers that have together received 659 indexed citations. Recurring topics across this work include Stability and Controllability of Differential Equations (45 papers), Advanced Mathematical Modeling in Engineering (44 papers), Numerical methods in inverse problems (21 papers), Advanced Numerical Methods in Computational Mathematics (14 papers), Advanced Mathematical Physics Problems (10 papers), Composite Material Mechanics (6 papers), Numerical methods for differential equations (6 papers) and Contact Mechanics and Variational Inequalities (6 papers). The work is most often cited by research in Mathematical Physics (285 citations), Computational Theory and Mathematics (453 citations), Control and Systems Engineering (437 citations), Numerical Analysis (71 citations) and Computational Mechanics (146 citations). Arnaud Münch has collaborated with scholars based in France, Spain and United Kingdom. Frequent co-authors include Pablo Pedregal, Enrique Fernández‐Cara, Francisco Periago, Enrique Zuazua, Y. Ousset, Carlos Castro, Ademir F. Pazoto, Sorin Micu, Françoise Krasucki and Patrick Hild. Their work appears in journals such as ESAIM Control Optimisation and Calculus of Variations, Comptes Rendus Mathématique, SIAM Journal on Control and Optimization, Asymptotic Analysis and Inverse Problems.

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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