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Inverse design of an optical power splitter using a global optimization method

Inria -
Sophia Antipolis (06)

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Détails de l'emploi

Avantages

Qualifications

Anglais
Fortran
Master
C
Développement logiciel
Python

Description complète du poste

Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : Convention de stage

Niveau de diplôme exigé : Bac + 5 ou équivalent

Autre diplôme apprécié : Master in applied mathematics or scientific computing

Fonction : Stagiaire de la recherche

A propos du centre ou de la direction fonctionnelle

The Inria center at Université Côte d'Azur includes 42 research teams and 9 support services. The center’s staff (about 500 people) is made up of scientists of diﬀerent nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM ...), but also with the regional economic players.

With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.

Contexte et atouts du poste

This internship project is part of a collaborative project between the Atlantis project-team from Inria Research Center at Université Côte d’Azur, Sophia Antipolis and Ansys Lumerical R&D, La Farlède.

Atlantis is a team from Inria Research Center at Université Côte d’Azur located in Sophia Antipolis. It gathers researchers in numerical mathematics and computational physics, with an interdisciplinariy focus. The team has developed a specific expertise in the efficient numerical modeling of propagation of electromagnetic wave in complex media with a strong emphasis on nanoscale light-matter interactions. Through the years, the Atlantis team has developed a strong expertise in the design, analysis and development of dedicated efficient numerical methods (based on high order accurate Discontinuous Galerkin finite elements methods). More recently, the team has also acquired a know-how of numerical optimization using various techniques, and a solid experience on high performance computing practices (parallel numerical algorithms and parallelization strategies for large-scale problems). This materializes concretely through the DIOGENeS software suite [1] that has already proven its crucial efficiency in nanophotonics. DIOGENeS will be the corner stone to numerically address the various complex scenarios in this internship project.

Mission confiée

Photonic Integrated Circuits (PICs) are considered among the most promising approaches to ensure progress in computer technology. Their possible applications range from improving the performance and efficiency of modern AI accelerators to realizing solid state LIDAR detectors for autonomous driving. However, the design of large-scale PICs still lags the design process of electronic circuits and presents unique challenges.

The goal of our research is to improve photonic components by reducing their footprint, enhancing their performance, and improving their robustness against manufacturing variations. To do so, we develop and employ advanced simulation and optimization methods, such as inverse design and topology optimization.

Principales activités

This internship project aims at realizing a preliminary (and preparatory) study prior to a more ambitious project that will be undertaken in the context of a Cifre PhD thesis between Ansys R&D and Inria. The internship will take place in the Atlantis project-team from Inria Center at Université Côte d’Azur in Sophia Antipolis. The overall objective will be to develop and assess an inverse design strategy leveraging a modern global optimization algorithm. Specifically, we want to implement the global optimization of a PIC device by combining the following approaches:

A DGTD (Discontinuous Galerkin Time-Domain) Maxwell solver [1] to simulate a device and compute a specified figure-of-merit (FoM) for a given design;
The EGO (Efficient Global Optimization) method, which is a statistical learning-based global optimization algorithm [2] belonging to the family of Bayesian optimization methods [3];
A shape parameterization technique, which is compliant with the fact that the DGTD method makes use of an unstructured tetrahedral mesh for the simulations.

As an initial use case, we will optimize a symmetric Y-branch (50:50 optical splitter). This basic and well-studied device [4] requires a relatively low number of parameters (< 20) and is therefore well-suited for global optimization.

The individual software components mentioned above are already available in the DIOGENeS software suite developed by the Atlantis project-team. The internship focusses on the geometrical modeling and parametrization of the PIC device as well as the integration of the individual components. The results of the internship will be integrated in DIOGENeS.

[1] 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)

[2] D. Jones. Efficient global optimization of expensive black-box functions. Journal of Global Optimization, Vol. 13, No. 4, pp. 455-492 (1998)

[3] R. Garnett. Bayesian Optimization. Cambridge University Press (2023)

[4] https://optics.ansys.com/hc/en-us/articles/360042305274-Inverse-design-of-y-branch

Compétences

Technical skills and level required :

Master or engineering degree in numerical mathematics or scientific computing
Sound knowledge of numerical analysis for PDEs
Basic knowledge of physiscs of electromagnetic wave propagation

Software development skills : Python and Fortran 2003

Relational skills : team worker (verbal communication, active listening, motivation and commitment)

Other valued appreciated : good level of spoken and written english

Avantages

Subsidized meals
Partial reimbursement of public transport costs
Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
Possibility of teleworking and flexible organization of working hours
Professional equipment available (videoconferencing, loan of computer equipment, etc.)
Social, cultural and sports events and activities
Access to vocational training
Contribution to mutual insurance (subject to conditions)

Rémunération

Traineeship grant depending on attendance hours

Informations générales

Thème/Domaine : Schémas et simulations numériques
Calcul Scientifique (BAP E)
Ville : Sophia Antipolis
Centre Inria : Centre Inria d'Université Côte d'Azur
Date de prise de fonction souhaitée : 2025-02-01
Durée de contrat : 6 mois
Date limite pour postuler : 2026-06-30

Attention: Les candidatures doivent être déposées en ligne sur le site Inria. Le traitement des candidatures adressées par d'autres canaux n'est pas garanti.

Consignes pour postuler

Sécurité défense :
Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie dans le décret n°2011-1425 relatif à la protection du potentiel scientifique et technique de la nation (PPST). L’autorisation d’accès à une zone est délivrée par le chef d’établissement, après avis ministériel favorable, tel que défini dans l’arrêté du 03 juillet 2012, relatif à la PPST. Un avis ministériel défavorable pour un poste affecté dans une ZRR aurait pour conséquence l’annulation du recrutement.

Politique de recrutement :
Dans le cadre de sa politique diversité, tous les postes Inria sont accessibles aux personnes en situation de handicap.

Contacts

Équipe Inria : ATLANTIS
Recruteur :
Lanteri Stéphane / [email protected]

A propos d'Inria

Inria est l’institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l’interface d’autres disciplines. L’institut fait appel à de nombreux talents dans plus d’une quarantaine de métiers différents. 900 personnels d’appui à la recherche et à l’innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eﬀorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.

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Inverse design of an optical power splitter using a global optimization method

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