Preparing Schrödinger cat states in a microwave cavity using a neural network

• URL: http://arxiv.org/abs/2409.05557v1
• Date: Mon, 9 Sep 2024 12:28:02 GMT
• Title: Preparing Schrödinger cat states in a microwave cavity using a neural network
• Authors: Hector Hutin, Pavlo Bilous, Chengzhi Ye, Sepideh Abdollahi, Loris Cros, Tom Dvir, Tirth Shah, Yonatan Cohen, Audrey Bienfait, Florian Marquardt, Benjamin Huard,
• Abstract summary: We show that it is possible to teach a neural network to output optimized control pulses for a whole family of quantum states. Results demonstrate how deep neural networks and transfer learning can produce efficient simultaneous solutions to a range of quantum control tasks.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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 Schr\"odinger 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.

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