Explore the optimization of Dicke quantum batteries through reinforcement learning in this one-hour lecture by Gian Marcello Andolina from PCS Institute for Basic Science. Delve into the world of quantum batteries, energy-storing devices governed by quantum mechanics that offer enhanced charging performance due to collective effects. Learn about the Dicke battery design, comprising N two-level systems coupled to a common photon mode, and its experimental feasibility. Discover how reinforcement learning techniques can be applied to optimize the charging process of a Dicke battery, resulting in significant improvements in both extractable energy (ergotropy) and quantum mechanical energy fluctuations (charging precision) compared to standard charging strategies.
Reinforcement Learning Optimization of Charging a Dicke Quantum Battery
PCS Institute for Basic Science via YouTube
Overview
Syllabus
Gian Marcello Andolina: Reinforcement learning optimization of charging of a Dicke quantum battery
Taught by
PCS Institute for Basic Science
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