Next Tuesday, 16.11 at 15.00,  Dr. Ilia Khait from the University of Toronto will give a talk titled "Optimal control of quantum thermal machines using Machine Learning". See the details in the file attached.

We develop a deep learning (DL) framework assisted by differentiable programming for
discovery of optimal quantum control protocols under hard constraints. To that end, we use
neural network representations to our protocols, whose learning process is done with exact
gradients. We find high quality solutions to the optimization problem of finite-time
thermodynamical process in a quantum thermal machine. Using this DL algorithm, we show
that a previously employed, intuitive energetic cost of the thermal machine driving suffers
from a fundamental flaw, which we resolve with an alternative construction for the cost
function. I will describe the algorithm and will advocate how this DL-quantum control
framework can be utilized to solve other quantum dynamics and thermodynamics problems.