Machine learning, specifically reinforcement learning (RL), is being used to control quantum systems, according to researchers from the University of Patras, Greece. The team developed an RL agent to control the dynamics of a single quantum bit, or qubit, by formulating the problem as a Markov decision process. The use of deep learning and deep neural networks allowed for continuous action and state spaces. The methodologies achieved high fidelity in controlling the qubit, showing promise for quantum computing applications. The techniques could also be extended to control collections of qubits, improving quantum sensing applications.
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