World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
40
Citations
16904
World Ranking
1978
National Ranking
121

Eric Cancès publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Eric Cancès sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 164 publications — 46th percentile

46% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Eric Cancès D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Eric Cancès sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 40 D-Index — 45th percentile

45% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Eric Cancès is affiliated with the École des Ponts ParisTech in France. Their research spans a variety of topics within physics and materials science, with a particular focus on condensed matter physics and quantum many-body systems.

Their work covers multiple subfields including atomic and molecular physics and optics, materials chemistry, condensed matter physics, surfaces, coatings and films, and mechanical engineering.

They have contributed to several main research topics, which include:

  • Graphene research and applications
  • Advanced chemical physics studies
  • Carbon nanotubes in composites
  • Quantum and electron transport phenomena
  • Quantum many-body systems
  • Machine learning in materials science
  • Electron and X-Ray spectroscopy techniques

Eric Cancès has published research in a variety of scientific venues. Frequent publication platforms include:

  • arXiv (Cornell University)
  • JuliaCon Proceedings
  • Physical Review B
  • The Journal of Chemical Physics
  • Communications on Pure and Applied Mathematics

Among their recent papers are the following:

  • "Simple derivation of moiré-scale continuous models for twisted bilayer graphene," 2023, Physical Review B
  • "Some mathematical insights on Density Matrix Embedding Theory," 2023, arXiv (Cornell University)
  • "Analysis of density matrix embedding theory around the non-interacting limit," 2025, Communications on Pure and Applied Mathematics
  • "DFTK: A Julian approach for simulating electrons in solids," 2021, JuliaCon Proceedings (authored by Michael F. Herbst)
  • "Insights into the π - π interaction driven non-covalent functionalization of carbon nanotubes of various diameters by conjugated fluorene and carbazole copolymers," 2020, The Journal of Chemical Physics (authored by Robert Benda)

Frequent co-authors collaborating with Eric Cancès include:

  • Fabian M. Faulstich
  • Louis Garrigue
  • David Gontier
  • Alfred Kirsch
  • Eloïse Letournel

Best Publications

  • A new integral equation formalism for the polarizable continuum model: Theoretical background and applications to isotropic and anisotropic dielectrics

    E. Cancès;B. Mennucci;J. Tomasi

  • The IEF version of the PCM solvation method: an overview of a new method addressed to study molecular solutes at the QM ab initio level

    J. Tomasi;B. Mennucci;E. Cancès

  • New applications of integral equations methods for solvation continuum models: ionic solutions and liquid crystals

    Eric Cancès;Benedetta Mennucci

  • Recent Advances in the Description of Solvent Effects with the Polarizable Continuum Model

    Claudio Amovilli;Vincenzo Barone;Roberto Cammi;Eric Cancès

  • A black-box self-consistent field convergence algorithm: One step closer

    Konstantin N. Kudin;Gustavo E. Scuseria;Eric Cancès

  • Computational quantum chemistry: A primer

    Eric Cancès;Mireille Defranceschi;Werner Kutzelnigg;Claude Le Bris

  • A variational formulation of the polarizable continuum model

    Filippo Lipparini;Giovanni Scalmani;Benedetta Mennucci;Eric Cancès

  • ADAPTIVE SIMULATION OF HYBRID STOCHASTIC AND DETERMINISTIC MODELS FOR BIOCHEMICAL SYSTEMS

    Aurélien Alfonsi;Eric Cancès;Gabriel Turinici;Barbara Di Ventura

  • Analytical derivatives for geometry optimization in solvation continuum models. I. Theory

    E. Cancès;B. Mennucci

  • On the convergence of SCF algorithms for the Hartree-Fock equations

    Eric Cancès;Claude Le Bris

  • THEORETICAL AND NUMERICAL COMPARISON OF SOME SAMPLING METHODS FOR MOLECULAR DYNAMICS

    Eric Cancès;Eric Cancès;Frédéric Legoll;Frédéric Legoll;Gabriel Stoltz

  • Numerical Analysis of Nonlinear Eigenvalue Problems

    Eric Cancès;Rachida Chakir;Yvon Maday

  • Some improvements of the activation-relaxation technique method for finding transition pathways on potential energy surfaces

    E. Cancès;Frédéric Legoll;M. C. Marinica;K. Minoukadeh

  • Fast Domain Decomposition Algorithm for Continuum Solvation Models: Energy and First Derivatives

    Filippo Lipparini;Benjamin Stamm;Eric Cancès;Yvon Maday;Yvon Maday;Yvon Maday

  • Analytical derivatives for geometry optimization in solvation continuum models. II. Numerical applications

    E. Cancès;B. Mennucci;J. Tomasi

  • The Electronic Ground State Energy Problem: a New Reduced Density Matrix Approach

    Eric Cancès;Gabriel Stoltz;Mathieu Lewin

  • Domain decomposition for implicit solvation models.

    Eric Cancès;Yvon Maday;Benjamin Stamm

  • A New Approach to the Modeling of Local Defects in Crystals: The Reduced Hartree-Fock Case

    Éric Cancès;Amélie Deleurence;Mathieu Lewin

  • Self-consistent field algorithms for Kohn–Sham models with fractional occupation numbers

    Eric Cancès

  • How electrons guard the space: shape optimization with probability distribution criteria

    Eric Cancès;Renaud Keriven;François Lodier;Andreas Savin

  • Some improvements of the ART method for finding transition pathways on potential energy surfaces

    E. Cancès;F. Legoll;M.-C. Marinica;K. Minoukadeh

Frequent Co-Authors

Yvon Maday
Yvon Maday Sorbonne University
Benedetta Mennucci
Benedetta Mennucci University of Pisa
Tony Lelièvre
Tony Lelièvre École des Ponts ParisTech
Jean-Philip Piquemal
Jean-Philip Piquemal Sorbonne University
Martin Vohralík
Martin Vohralík French Institute for Research in Computer Science and Automation - INRIA
Gabriel Turinici
Gabriel Turinici Paris Dauphine University
Jacopo Tomasi
Jacopo Tomasi University of Pisa
Giovanni Scalmani
Giovanni Scalmani Gaussian Inc.
William W. Hager
William W. Hager University of Florida
Gustavo E. Scuseria
Gustavo E. Scuseria Rice University

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