1. Exponential improvement for quantum cooling through finite-memory effects
- Author
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Faraj Bakhshinezhad, Fabien Clivaz, Marcus Huber, Philipp Schüttelkopf, and Philip Taranto
- Subjects
Quantum Physics ,education.field_of_study ,Computer science ,Population ,General Physics and Astronomy ,Markov process ,FOS: Physical sciences ,02 engineering and technology ,021001 nanoscience & nanotechnology ,01 natural sciences ,Exponential function ,Quantum technology ,symbols.namesake ,Qubit ,0103 physical sciences ,symbols ,Applied mathematics ,Embedding ,010306 general physics ,0210 nano-technology ,education ,Quantum Physics (quant-ph) ,Quantum ,Third law of thermodynamics - Abstract
Practical implementations of quantum technologies require preparation of states with a high degree of purity---or, in thermodynamic terms, very low temperatures. Given finite resources, the Third Law of thermodynamics prohibits perfect cooling; nonetheless, attainable upper bounds for the asymptotic ground state population of a system repeatedly interacting with quantum thermal machines have been derived. These bounds apply within a memoryless (Markovian) setting, in which each refrigeration step proceeds independently of those previous. Here, we expand this framework to study the effects of memory on quantum cooling. By introducing a memory mechanism through a generalized collision model that permits a Markovian embedding, we derive achievable bounds that provide an exponential advantage over the memoryless case. For qubits, our bound coincides with that of heat-bath algorithmic cooling, which our framework generalizes to arbitrary dimensions. We lastly describe the adaptive step-wise optimal protocol that outperforms all standard procedures., Comment: 4.5+13 pages, 9 figures. Close to published version
- Published
- 2020
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