DESCRIPTION :
Atlantis is a joint project-team between Inria and the Jean-Alexandre Dieudonné Mathematics Laboratory at Université Côte d'Azur. The team gathers applied mathematicians and computational scientists who are collaboratively undertaking research activities aiming at the design, analysis, development and application of advanced numerical methods for solving systems of partial differential equations (PDEs) modelling nanoscale light-matter interaction problems. In this context, the team is developing the DIOGENeS [https://diogenes.inria.fr/] software suite, which implements several Discontinuous Galerkin (DG) type methods tailored to the systems of time- and frequency-domain Maxwell equations possibly coupled to differential equations modeling the behaviour of propagation media at optical frequencies. DIOGENeS also includes a component dedicated to the optimization of geometrical characteristics of nanostructures driven by some performance objective in the contex of inverse design
strategies of nanophotonic setups. DIOGENeS is a unique numerical framework leveraging the capabilities of DG techniques for the simulation of multiscale problems relevant to nanophotonics and nanoplasmonics.
One important line of research of the team during the last years has been dedicated to improve the capabilities of these numerical tools to produce novel inverse design methodologies for optical metasurfcaes. In the last decade metasurfaces, i.e. 2D arrays of optical nanoantennas with subwavelength size and separation [1] have revolutionized the field of linear optics with the promise to replace bulky and difficult-to-align optical components with ultrathin and flat devices like metagratings, metalenses and metaholograms, which can also implement new functionalities in terms of aberrations correction and arbitrary wavefront shaping. In the recent years, by combining a high-fidelity DG-based fullwave solver in the time-domain [2] with a statistical learning-based global optimization method [3], we have introduced innovative inverse design methodologies for mono-objective optimization of metadeflectors [4], multi-objective optimization of RGB metalenses [5] and robust
optimization of metadeflectors [6].
[1] W. Chen, A.Y. Zhu and F. Capasso. Flat optics with dispersion-engineered metasurfaces. Nature Review Material, vol. 5, 604 (2020)
[2] S. Lanteri, C. Scheid and J. Viquerat. Analysis of a generalized dispersive model coupled to a DGTD method with application to nanophotonics. SIAM Journal on Scientific Computing, Vol. 39, No. 3, pp. A831-A859 (2017)
[3] D. Jones. Efficient global optimization of expensive black-box functions. Journal of Global Optimization, Vol. 13, No. 4, pp. 455-492 (1998)
[4] M. Elsawy, S. Lanteri, R. Duvigneau, G. Brière, M.S. Mohamed and P. Genevet, Global optimization of metasurface designs using statistical learning methods, Scientific Reports, Vol. 9, No. 17918, (2019)
[5] M. Elsawy, A. Gourdin, M. Binois, R. Duvigneau, D. Felbacq, S. Khadir, P. Genevet an S. Lanteri, Multiobjective statistical learning optimization of RGB metalens, ACS Photonics, Vol. 8, No. 8, pp. 2498-2508 (2021)
[6] M. Elsawy, M. Binois, R. Duvigneau, S. Lanteri, and P. Genevet, Optimization of metasurfaces under geometrical uncertainty using statistical learning, Optics Express 29(19), 29887-29898 (2021)
Mission confiée
Our achievements in [4]-[5]-[6] are concerned with linear and passive metasurfaces. A more recent work has been dedicated to active, i.e., tunable, metasurfaces [7]. A first goal of this postodoctoral project will be to delve into novel modeling techniques for the design of next-generation metasurfaces. We will consider two modern topics in metasurface design:
1. Active and dynamically tunable metasurfaces. The objective will be to explore novel active metasurface designs enabled by advanced materials such as liquid crystals and phase-change materials. Special attention will be given to the dynamic modeling of such systems, including thermal effects, liquid crystal dynamical behavior, and their integration into tunable and reconfigurable devices.
2. Nonlinear metasurfaces. The goal will be to exploit the latest breakthroughs in the modeling and design of nonlinear metasurfaces, focusing on second-harmonic generation, wave mixing, and other nonlinear effects. Different modeling approaches ranging from the state-of-the art linear approximation to advanced nonlinear modelling techniques to achieve superior accuracy and performance.
[7] M.M.R. Elsawy, C. Kyrou, H. Mikheeva, R. Colom, J.Y. Duboz, K.Z. Kamali, S. Lanteri, D. Neshev and P. Genevet.
Universal active metasurfaces for ultimate wavefront molding by manipulating the reflection singularities.
Laser & Photonics Review, Vol. 17, No. 7, pp. 200880 (2023)
Principales activités
Dealing with the above physical contexts regarding dynamicity / tunability and nonlinearity, well require investigating advanced material models and adapt numerical methods currently implemented in teh DIOGENeS software suite.
The second important objective of this postodoctoral project will be to setup inverse design workflows based on the EGO optimization algorithm for unveiling novel metasurface designs with ultimate properties allowing effective operation of active and dynamically tunable metasurfaces on one hand, and nonlinear metasurfaces on the other hand.
The Atlantis team is currently involved in collaborations with several groups of physicisits who are actively working on the fabrication and characterizartion of such metasurfaces. Therefore, the third goal of this project will be to foster these collaborations through experimental demonstrations of the capabilities of the proposed virtual metasurface designs thanks to our adavanced cinoutational modeling, and copublication in high rank journals.
Code d'emploi : Ingénieur (autre) (h/f)
Domaine professionnel actuel : Ingénierie (autre)
Niveau de formation : Bac+8
Temps partiel / Temps plein : Plein temps
Type de contrat : Contrat à durée indéterminée (CDI)
Compétences : Suite Logicielle, Programmation Informatique, Fortran (Programming Language), Python (Langage de Programmation), OpenMP, Informatique Scientifique, Conception et Développement de Logiciel, Optimization Algorithms, Anglais, Sens de la Communication, Esprit d'Équipe, Motivation Personnelle, Recherche, Écoute Active, Génie Electrique, Physique Appliquée, Optique et Lunetterie, Stratégies de Conception, Équations Différentielles, Électromagnétisme, Méthodes par Éléments Finis, Domaine Fréquentiel, Revue (Publication Périodique), Travaux d'Usinage Laser, Fabrication, Mathématiques, Optimisation Mathématique, Analyse Numérique, Équation Différentielle Partielle, Photonique, Recherche Post-Doctorale, Simulations, Etudes et Statistiques, Workflows, Compétences de Modélisation
Courriel :
Stephane.Lanteri@inria.fr
Téléphone :
0139635511
Type d'annonceur : Employeur direct