I am Lecturer in the Informatics and Interactions department of Aix-Marseille University and a researcher in the CaNa team of the LIS laboratory. I got my HDR in Computer Science at AMU and earlier on I did my Ph.D in Theoretical Quantum Physics at the Université Pierre et Marie Curie (Sorbonne). My research activities take  place in discrete mathematics and theoretical computer science and deals with quantum cellular automata, simulations, models and algorithms. Get in touch!

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Recent publications 

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March 25th, 2021 New on ArXiv

A staggered gauge-invariant quantum cellular automaton for both the Kogut-Susskind Schwinger model and the Dirac equation

 

We show that, in the continuous-time discrete-space limit, the introduced QCA converges to the Kogut-Susskind staggered version of 1 + 1 QED. We also show that, in the continuous spacetime limit and in the free one particle sector, it converges to the Dirac equation—a strong indication that the model remains accurate in the relativistic regime. 

[arXiv][Journal]

March 15th, 2021 Physical Review A 103 032224

 

One can think of some physical evolutions as being the emergent-effective result of a microscopic discrete model. Inspired by classical coarse graining procedures, we provide a simple procedure to coarse-grain color-blind quantum cellular automata that follow Goldilock rules. 

[arXiv][Journal]

Coarse-grained quantum cellular automata

February 19th, 2021 Quantum Information Processing, 20 (2), 76

Continuous time limit of the DTQW in 2D+1 and plasticity

 

A Plastic quantum walk admits both continuous time and continuous spacetime, leading to a general quantum simulation scheme for simulating fermions in the relativistic and non-relativistic regimes. Here we explore the two physical dimensions case.

[arXiv][Journal]

December 7th, 2020 Scientific reports 10 (1), 1-8

Quantum control using quantum memory

 

We propose a new quantum numerical scheme to control the dynamics of a quantum walker in a two dimensional space–time grid. More specifically, we show how, introducing a quantum memory, this result can be achieved simply by acting on the initial state of the whole system, and therefore can be exactly controlled once for all. 

[arXiv][Journal]

November, 2020 Algorithms 13 (11), 305

 

We provide numerical evidence that the nonlinear searching algorithm introduced by Wong and Meyer, rephrased in terms of quantum walks with effective nonlinear phase, can be extended to the finite 2-dimensional grid, keeping the same computational advantage with respect to the classical algorithms. 

[arXiv][Journal]

Searching via Nonlinear Quantum Walk on the 2D-Grid

Avril 16th, 2020 Physical Review Letters, 124 (18), 180501

(Editor suggestion)

 

We provide the first evidence that under certain conditions, electrons may naturally behave like a Grover search, looking for defects in a material. The theoretical framework is that of discrete-time quantum walks (QW) on triangular and rectangular grids. 

[arXiv][Journal]

April,3rd, 2020, Electronic Proceedings in Theoretical Computer Science 315, pp. 38–47

Random graphs are a central element of the study of complex dynamical networks such as the internet, the brain, or socioeconomic phenomena. New methods to generate random graphs can spawn new applications and give insights into more established techniques. We propose two variations of a model to grow random graphs and trees, based on continuous-time quantum walks on the graphs. 

[arXiv][Journal]

 

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Research projects

Quantum Information Structure of Spacetime

JTF Large grant, 2M € - PI

(2019–2023)

 

Quantum Walk and geometry

PICS CNRS France-Espagne, 12k € - PI 

(2018-2021)

Fault Invariant Distributed Quantum Algorithm /QuAlgo

INS2I 20k € - PI 

(2021)

Discrete Time Quantum Simulator

Pepiniere d’excellence AMIDEX, 25k € - PI 

(2019-2021 extended due to the Covid19 crisis)

The following is a membership:

Quantum Machine Learning

ANR JCJC at LIS, 214k €

(2019–2023)

Closed : 

Lattice Quantum Simulation Theory- / LaQuSim, PI

(2018)

 

Quantum networks and Growing- /QuNet, PI

(2017)

 

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Teaching

Tous les cours seront accessibles sur Ametice à partir de 2020

Septembre, 2016 - en cours

Une introduction à l'informatique, et les notions de base nécessaires pour écrire des programmes simples (instructions, variables et types simples, fonctions et passage de paramètres, fichiers) et notions d'algorithmique.

Septembre, 2016 - en cours

Principales techniques de conception et analyse d'algorithmes pour les problèmes polynomiaux et les problèmes NP complets. Complexité de l'approximation, du comptage. Complexité paramétrée. Classes probabilistes.

Sept, 2018 - 2019

L’objectif de ce cours est de sensibiliser aux menaces et enjeux et d’initier aux principaux concepts de cybersécurité. Il s’agit de présenter un guide de bonnes pratiques applicables à l’ensemble des professionnels de l’informatique, qu’ils soient en formation ou en activité.

January, 2017 - en cours

Modèles de calcul naturel (Master 2 - IMD)

Présentation des chaînes de Markov, leurs algorithmes et applications. Réseaux Booléenne, sand piles models. Introduction aux automates quantiques cellulaires.

January, 2019 - en cours

Fondamentaux du calcul quantique I (linéarité de la théorie, q-bit, super-position, intrication); Fondamentaux du calcul quantique II (quantum gates et circuits) Algorithme quantique de Grover; Alorithme de Shor; Elements de crypto-quantique, protocole de Cryptage RSA.

Sept, 2019 - en cours

Les étudiants étudieront des notions élémentaires telles que les variables aléatoires, les distributions de probabilités, etc. avec des exercices sous la forme de travaux dirigés. À l'issue de ce cours, les étudiants seront à même de formuler des solutions probabilistes à des problèmes concrets, ce qui leur permettra de maîtriser l'utilisation des probabilités dans des cours plus avancés (algorithmes randomisés, machine learning, etc.)