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Optimal control of quantum thermal machines using machine learning

Ilia Khait ¹, Juan Carrasquilla^2,3, and Dvira Segal^1,4,*

¹Department of Physics, University of Toronto, 60 Saint George St., Toronto, Ontario M5S 1A7, Canada
²Vector Institute, MaRS Centre, Toronto, Ontario M5G 1M1, Canada
³Department of Physics & Astronomy, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
⁴Department of Chemistry and Centre for Quantum Information and Quantum Control, University of Toronto, 80 Saint George St., Toronto, Ontario M5S 3H6, Canada

^*dvira.segal@utoronto.ca

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Articles Citing

Optimal control of quantum thermal machines using machine learning

Quantum-enhanced thermal metamaterials with topological phase transitions

Controlling fluctuations in quantum Otto engines via spin-echo techniques

Machine learning delta-T noise for temperature bias estimation

Model-free distortion canceling and control of quantum devices

Solving the quantum many-body Hamiltonian learning problem with neural differential equations

Detecting Markovianity of quantum processes via recurrent neural networks

Floquet engineering of quantum thermal machines: A gradient-based spectral method to optimize their performance

Non-Markovianity and a generalized Landauer bound for a minimal quantum autonomous thermal machine with a work qubit

Parametrized multiqubit gates for neutral-atom quantum platforms

Optimal thermometers with spin networks

Stochastic Thermodynamics at the Quantum-Classical Boundary: A Self-Consistent Framework Based on Adiabatic-Response Theory

Quantum engines and refrigerators

Differentiable master equation solver for quantum device characterization

Exploring the optimal cycle for a quantum heat engine using reinforcement learning

Experimental graybox quantum system identification and control

Counterdiabatic optimized driving in quantum phase sensitive models

Entanglement Generation of Polar Molecules via Deep Reinforcement Learning

Dissipation-induced collective advantage of a quantum thermal machine

Multi-axis control of a qubit in the presence of unknown non-Markovian quantum noise

Counterdiabatic Optimized Local Driving

Recommender system expedited quantum control optimization

Quantum compiling with a variational instruction set for accurate and fast quantum computing

Pareto-optimal cycles for power, efficiency and fluctuations of quantum heat engines using reinforcement learning

Nonideal measurement heat engines

Quadratic enhancement in the reliability of collective quantum engines

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