Search Results - "Réglade, Ulysse"

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  1. 1

    Irreversible Qubit-Photon Coupling for the Detection of Itinerant Microwave Photons by Lescanne, Raphaël, Deléglise, Samuel, Albertinale, Emanuele, Réglade, Ulysse, Capelle, Thibault, Ivanov, Edouard, Jacqmin, Thibaut, Leghtas, Zaki, Flurin, Emmanuel

    Published in Physical review. X (01-05-2020)
    “…Single photon detection is a key resource for sensing at the quantum limit and the enabling technology for measurement-based quantum computing. Photon…”
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    Journal Article
  2. 2

    Exploiting locality and translational invariance to design effective deep reinforcement learning control of the 1-dimensional unstable falling liquid film by Belus, Vincent, Rabault, Jean, Viquerat, Jonathan, Che, Zhizhao, Hachem, Elie, Reglade, Ulysse

    Published in AIP advances (01-12-2019)
    “…Instabilities arise in a number of flow configurations. One such manifestation is the development of interfacial waves in multiphase flows, such as those…”
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  3. 3

    Harnessing two-photon dissipation for enhanced quantum measurement and control by Marquet, Antoine, Dupouy, Simon, Réglade, Ulysse, Essig, Antoine, Cohen, Joachim, Albertinale, Emanuele, Bienfait, Audrey, Peronnin, Théau, Jezouin, Sébastien, Lescanne, Raphaël, Huard, Benjamin

    Published 24-09-2024
    “…Phys. Rev. Applied 22, 034053 (2024) Dissipation engineering offers a powerful tool for quantum technologies. Recently, new superconducting devices have…”
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  4. 4
  5. 5

    Detecting itinerant microwave photons with engineered non-linear dissipation by Lescanne, Raphaël, Deléglise, Samuel, Albertinale, Emanuele, Réglade, Ulysse, Capelle, Thibault, Ivanov, Edouard, Jacqmin, Thibaut, Leghtas, Zaki, Flurin, Emmanuel

    Published 13-02-2019
    “…Phys. Rev. X 10, 021038 (2020) Single photon detection is a key resource for sensing at the quantum limit and the enabling technology for measurement based…”
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    Journal Article
  6. 6

    Artificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control by Rabault, Jean, Kuchta, Miroslav, Jensen, Atle, Reglade, Ulysse, Cerardi, Nicolas

    Published 18-12-2018
    “…We present the first application of an Artificial Neural Network trained through a Deep Reinforcement Learning agent to perform active flow control. It is…”
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  7. 7

    Quantum control of a cat qubit with bit-flip times exceeding ten seconds by Réglade, U., Bocquet, A., Gautier, R., Cohen, J., Marquet, A., Albertinale, E., Pankratova, N., Hallén, M., Rautschke, F., Sellem, L.-A., Rouchon, P., Sarlette, A., Mirrahimi, M., Campagne-Ibarcq, P., Lescanne, R., Jezouin, S., Leghtas, Z.

    Published in Nature (London) (23-05-2024)
    “…Quantum bits (qubits) are prone to several types of error as the result of uncontrolled interactions with their environment. Common strategies to correct these…”
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  8. 8

    One Hundred Second Bit-Flip Time in a Two-Photon Dissipative Oscillator by Berdou, C., Murani, A., Réglade, U., Smith, W.C., Villiers, M., Palomo, J., Rosticher, M., Denis, A., Morfin, P., Delbecq, M., Kontos, T., Pankratova, N., Rautschke, F., Peronnin, T., Sellem, L.-A., Rouchon, P., Sarlette, A., Mirrahimi, M., Campagne-Ibarcq, P., Jezouin, S., Lescanne, R., Leghtas, Z.

    Published in PRX quantum (01-06-2023)
    “…Current implementations of quantum bits (qubits) continue to undergo too many errors to be scaled into useful quantum machines. An emerging strategy is to…”
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  9. 9

    A geometrical summation method for the Riemann z\^eta function by Reglade, Ulysse

    Published 23-03-2019
    “…In this paper, we introduce a geometrical summation method that makes the original Riemann series converge over the critical strip. This method gives an…”
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  10. 10

    Deep Reinforcement Learning achieves flow control of the 2D Karman Vortex Street by Rabault, Jean, Reglade, Ulysse, Cerardi, Nicolas, Kuchta, Miroslav, Jensen, Atle

    Published 31-08-2018
    “…The Karman Vortex Street has been investigated for over a century and offers a reference case for investigation of flow stability and control of high…”
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  11. 11

    Exploiting locality and physical invariants to design effective Deep Reinforcement Learning control of the unstable falling liquid film by Belus, Vincent, Rabault, Jean, Viquerat, Jonathan, Che, Zhizhao, Hachem, Elie, Reglade, Ulysse

    Published 17-10-2019
    “…Instabilities arise in a number of flow configurations. One such manifestation is the development of interfacial waves in multiphase flows, such as those…”
    Get full text
    Journal Article