Reinforcement learning approach to non-equilibrium quantum thermodynamics
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2020
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| _version_ | 1866914686435328000 |
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| author | Sgroi, Sofia Palma, G. Massimo Paternostro, Mauro |
| author_facet | Sgroi, Sofia Palma, G. Massimo Paternostro, Mauro |
| contents | We use a reinforcement learning approach to reduce entropy production in a closed quantum system brought out of equilibrium. Our strategy makes use of an external control Hamiltonian and a policy gradient technique. Our approach bears no dependence on the quantitative tool chosen to characterize the degree of thermodynamic irreversibility induced by the dynamical process being considered, require little knowledge of the dynamics itself and does not need the tracking of the quantum state of the system during the evolution, thus embodying an experimentally non-demanding approach to the control of non-equilibrium quantum thermodynamics. We successfully apply our methods to the case of single- and two-particle systems subjected to time-dependent driving potentials. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2004_07770 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | Reinforcement learning approach to non-equilibrium quantum thermodynamics Sgroi, Sofia Palma, G. Massimo Paternostro, Mauro Quantum Physics Statistical Mechanics We use a reinforcement learning approach to reduce entropy production in a closed quantum system brought out of equilibrium. Our strategy makes use of an external control Hamiltonian and a policy gradient technique. Our approach bears no dependence on the quantitative tool chosen to characterize the degree of thermodynamic irreversibility induced by the dynamical process being considered, require little knowledge of the dynamics itself and does not need the tracking of the quantum state of the system during the evolution, thus embodying an experimentally non-demanding approach to the control of non-equilibrium quantum thermodynamics. We successfully apply our methods to the case of single- and two-particle systems subjected to time-dependent driving potentials. |
| title | Reinforcement learning approach to non-equilibrium quantum thermodynamics |
| topic | Quantum Physics Statistical Mechanics |
| url | https://arxiv.org/abs/2004.07770 |