Daniel Vert, PhD

Daniel Vert, PhD

Coordinateur du Hub Advanced Engineering & Computing

Paris, Île-de-France, France
5 k abonnés + de 500 relations

À propos

PhD in Quantum Computing on "Benchmarking different quantum computer technologies". The aim of my research was to evaluate the performance of the new generation of quantum computers.

Today, I'm part of an ecosystem focused on quantum and augmented computing (simulation, HPC, systems engineering).
My role is to lead and support these structures throughout their growth:
Accompanying and accrediting R&D projects, promoting technologies and companies, networking and setting up projects, organizing thematic events...

If you want to be part of this ecosystem, contact me!

My publications: https://www.researchgate.net/profile/Daniel_Vert

Articles de Daniel

Activité

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Expérience

  • Graphique Systematic Paris-Region

    Coordinateur du Hub Advanced Engineering & Computing

    Systematic Paris-Region

    - aujourd’hui 1 an 7 mois

    Palaiseau, Île-de-France, France

    - Connecting stakeholders from software, digital and industry, and boosts digital projects through collaborative innovation, SME development (careers, fundings, R&D), networking and business sourcing
    - Mentoring (Hackathon)
    - Speaker on technical events
    - Promoting its members and their innovation projects
    - Enhancing the attractiveness of the geographical territory and ecosystem
    - Interfacing regional authorities, national incubators, technology centers, national associations…

    - Connecting stakeholders from software, digital and industry, and boosts digital projects through collaborative innovation, SME development (careers, fundings, R&D), networking and business sourcing
    - Mentoring (Hackathon)
    - Speaker on technical events
    - Promoting its members and their innovation projects
    - Enhancing the attractiveness of the geographical territory and ecosystem
    - Interfacing regional authorities, national incubators, technology centers, national associations and EU platforms
    - Systematic ambassador for technological conferences and universities (Assises du quantique, VIVATECH, FDDay, forum TERATEC, ...)

  • Graphique CEA Tech

    Ingénieur recherche

    CEA Tech

    - 1 an 6 mois

    Saclay, Île-de-France, France

    Développement de l’architecture matérielle de l’ordinateur quantique et études de l’avantage du quantique pour les domaines de l’optimisation et de l’apprentissage machine.

  • Graphique CEA Tech

    Doctorat

    CEA Tech

    - 2 ans 7 mois

    Région de Paris, France

    Analyse des transformations polynomiales en vue de l’exploitation de calculateurs quantiques analogiques.

  • Graphique CEA

    Stage de Recherche

    CEA

    - 6 mois

    Région de Bordeaux, France

    Simulation et étude numérique du centrage d’un faisceau d’électrons dans un accélérateur de particules linéaire.

  • Graphique LPC CNRS CLERMONT FERRAND

    Stage de Recherche

    LPC CNRS CLERMONT FERRAND

    - 5 mois

    Région de Clermont-Ferrand, France

    Simulation et analyse Monte Carlo pour la mise en évidence de nouvelles désintégrations radiatives de mésons Beaux avec le détecteur LHCb.

  • Graphique IRAP - Institut de Recherche en Astrophysique et Planétologie

    Stage de Recherche

    IRAP - Institut de Recherche en Astrophysique et Planétologie

    - 3 mois

    Région de Toulouse, France

    Calibration expérimentale des unités de détection du plan focal des télescopes pour l’observatoire CTA.

  • Stage de Recherche

    Laboratoire de Physique Théorique

    - 4 mois

    Région de Toulouse, France

    Etude numérique du chaos quantique et de la sismologie dans les étoiles en rotation rapide.

  • Graphique CEA Cadarache

    Stagiaire en ingénierie industrielle

    CEA Cadarache

    - 3 mois

    Cadarache

    Analyse expérimentale de la métrologie de surface sous sodium pour l’inspection d’un réacteur nucléaire refroidi par du sodium liquide

Formation

Publications

  • Benchmarking quantum annealing against "hard" instances of the bipartite matching problem

    SN Computer Science

    This paper experimentally investigates the behavior of analog quantum computers as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem which is specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest…

    This paper experimentally investigates the behavior of analog quantum computers as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem which is specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest that quantum annealing, at least as implemented in a D-Wave device, falls in the same pitfalls as simulated annealing and hence provides additional evidences suggesting that there exist polynomial-time problems that such a machine cannot solve efficiently to optimality. Additionally, we investigate the extent to which the qubits interconnection topologies explains these latter experimental results. In particular, we provide evidences that the sparsity of these topologies which, as such, lead to QUBO problems of artificially inflated sizes can partly explain the aforementioned disappointing observations. Therefore, this paper hints that denser interconnection topologies are necessary to unleash the potential of the quantum annealing approach.

    See publication
  • Operational Quantum Annealers are Cursed by their Qubits Interconnection Topologies

    2020 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)

    Recent experimental works have studied how the quantum annealing approach, as implemented in D-Wave devices, deals with pathological instances of the (polynomial) bipartite matching problem known to be hard for classical simulated annealing algorithms and shown that the quantum approach also performed rather poorly on such instances. In this paper, we investigate the extent to which the qubits interconnection topologies explains these latter experimental results. In particular, we provide…

    Recent experimental works have studied how the quantum annealing approach, as implemented in D-Wave devices, deals with pathological instances of the (polynomial) bipartite matching problem known to be hard for classical simulated annealing algorithms and shown that the quantum approach also performed rather poorly on such instances. In this paper, we investigate the extent to which the qubits interconnection topologies explains these latter experimental results. In particular, we provide evidences that the sparsity of these topologies which, as such, lead to QUBO problems of artificially inflated sizes can partly explain the aforementioned disappointing observations. Therefore, this paper hints that denser interconnection topologies are necessary to unleash the potential of the quantum annealing approach.

    See publication
  • Revisiting Old Combinatorial Beasts in the Quantum Age: Quantum Annealing Versus Maximal Matching

    International Conference on Computational Science ICCS 2020

    This paper experimentally investigates the behavior of analog quantum computers such as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest that…

    This paper experimentally investigates the behavior of analog quantum computers such as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest that quantum annealing, at least as implemented in a D-Wave device, falls in the same pitfalls as simulated annealing and therefore provides additional evidences suggesting that there exist polynomial-time problems that such a machine cannot solve efficiently to optimality.

    See publication
  • Revisiting old combinatorial beasts in the quantum age: quantum annealing versus maximal matching

    preprint

    This paper experimentally investigates the behavior of analog quantum computers such as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggests…

    This paper experimentally investigates the behavior of analog quantum computers such as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggests that quantum annealing, at least as implemented in a D-Wave device, falls in the same pitfalls as simulated annealing and therefore suggest that there exist polynomial-time problems that such a machine cannot solve efficiently to optimality.

    See publication
  • On the limitations of the chimera graph topology in using analog quantum computers

    16th ACM International Conference

    This paper investigates the possibility of using an analog quantum computer as commercialized by D-Wave to solve large QUBO problems by means of a single invocation of the quantum annealer. Indeed this machine solves a spin glass problem with programmable coefficients but subject to quite strong topology restrictions on the set of non-zero coefficients. Rather than mapping problem variables onto multiple qbits, an approach which requires many invocations of the annealer to solve small size…

    This paper investigates the possibility of using an analog quantum computer as commercialized by D-Wave to solve large QUBO problems by means of a single invocation of the quantum annealer. Indeed this machine solves a spin glass problem with programmable coefficients but subject to quite strong topology restrictions on the set of non-zero coefficients. Rather than mapping problem variables onto multiple qbits, an approach which requires many invocations of the annealer to solve small size problems, it is tempting to investigate the existence of sparse relaxations compliant with the qbits interconnection topology of the machine, hence solvable in one invocation of the annealing oracle, but still providing good-quality solutions to the original problem. This paper provides an experimental setup which aims to determine whether or not such convenient relaxations do exist or, rather, are easy to find. Our experiments suggest that it is not the case and, therefore, that solving even moderate size arbitrary problems with a single call to a quantum annealer is not possible at least within the constraints of the so-called Chimera topology. We conclude the paper with a number of perspectives that this results imply on the design of heuristics taking profit of a quantum annealing oracle to solve large scale problems.

    See publication
  • Vers l'exploitation de calculateurs quantiques analogiques pour l'optimisation

    ROADEF

    Sur le plan pratique, l’émergence à moyen terme d’ordinateurs quantiques capables de rivaliser, pour la résolution de certains problèmes, avec les performances des calculateurs classiques les plus puissants reste hautement spéculative. En effet, et bien qu’il soit tout à fait pertinent d’investiguer les conséquences de l’existence de telles machines dans différents domaines applicatifs, les réalisations actuelles que l’on peut apparenter à des ordinateurs quantiques, bien qu’impressionnantes…

    Sur le plan pratique, l’émergence à moyen terme d’ordinateurs quantiques capables de rivaliser, pour la résolution de certains problèmes, avec les performances des calculateurs classiques les plus puissants reste hautement spéculative. En effet, et bien qu’il soit tout à fait pertinent d’investiguer les conséquences de l’existence de telles machines dans différents domaines applicatifs, les réalisations actuelles que l’on peut apparenter à des ordinateurs quantiques, bien qu’impressionnantes sur le plan de la physique, restent très modestes sur le plan informatique. Ces remarques concernent néanmoins ce qu’il convient d’appeler aujourd’hui l’ordinateur quantique numérique, c’est-à-dire composé de portes logiques quantiques s’appliquant sur des qbits. Cette voie n’est néanmoins pas la seule, afin de mettre à profit les propriétés quantiques de la nature pour le traitement de l’information. Ces dernières années, sont apparues des machines quantiques dites analogiques, dont les calculateurs actuellement commercialisés par la société canadienne D-Wave sont les premiers représentants, fonctionnant selon un principe de recuit à accélération quantique.. Ces machines ont l’avantage d’exister à une échelle non triviale et le chemin technologique en vue de leur passage à l’échelle est beaucoup moins flou que celui de leurs cousins numériques. Dans ce contexte, nous cherchons des chemins de transformations polynomiales permettant aussi efficacement que possible de ramener des problèmes d’optimisation vers le type de problème traité par ces machines.

    See publication

Langues

  • Anglais

    Capacité professionnelle générale

  • Français

    Bilingue ou langue natale

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