Preparing Schrödinger Cat States in a Microwave Cavity Using a Neural Network
Hutin H, Bilous P, Ye C, Abdollahi S, Cros L, Dvir T, Shah T, Cohen Y, Bienfait A, Marquardt F, Huard B (2025)
Publication Type: Journal article
Publication year: 2025
Journal
Book Volume: 6
Article Number: 010321
Journal Issue: 1
DOI: 10.1103/PRXQuantum.6.010321
Abstract
Scaling up quantum computing devices requires solving ever more complex quantum control tasks. Machine learning has been proposed as a promising approach to tackle the resulting challenges. However, experimental implementations are still scarce. In this work, we demonstrate experimentally a neural-network-based preparation of Schrödinger cat states in a cavity coupled dispersively to a qubit. We show that it is possible to teach a neural network to output optimized control pulses for a whole family of quantum states. After being trained in simulations, the network takes a description of the target quantum state as input and rapidly produces the pulse shape for the experiment, without any need for time-consuming additional optimization or retraining for different states. Our experimental results demonstrate more generally how deep neural networks and transfer learning can produce efficient simultaneous solutions to a range of quantum control tasks, which will benefit not only state preparation but also parametrized quantum gates.
Authors with CRIS profile
Involved external institutions
École normale supérieure de Lyon (ENS)
France (FR)
Max-Planck-Institut für die Physik des Lichts (MPL) / Max Planck Institute for the Science of Light
Germany (DE)
France (FR)
Max-Planck-Institut für die Physik des Lichts (MPL) / Max Planck Institute for the Science of Light
Germany (DE)
How to cite
APA:
Hutin, H., Bilous, P., Ye, C., Abdollahi, S., Cros, L., Dvir, T.,... Huard, B. (2025). Preparing Schrödinger Cat States in a Microwave Cavity Using a Neural Network. PRX Quantum, 6(1). https://doi.org/10.1103/PRXQuantum.6.010321
MLA:
Hutin, Hector, et al. "Preparing Schrödinger Cat States in a Microwave Cavity Using a Neural Network." PRX Quantum 6.1 (2025).
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