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Choosing a quantum control strategy

Watch this webinar and gain expert insights that empower you to apply quantum control to automate and improve the performance of your hardware, even in the presence of large uncertainties, noise, and decoherence. We’ll help you navigate through the confusing landscape of jargon to confidently choose the best approach for your needs. What you will learn 1. How to select the right control-design approach for your needs, subject to the constraints you face in your experiment. We will explain the decision process you should apply to choose between optimal control, robust control or learning control. 2. How reinforcement learning can automate the optimization of a quantum system when it is subject to many unknown parameters. 3. How stochastic optimization can be used in regimes with large uncertainty and noise that have traditionally been out of reach for other control-design strategies.