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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.18783 |
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| _version_ | 1866915356974514176 |
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| author | Bresque, Léa Das, Debraj Roldán, Édgar |
| author_facet | Bresque, Léa Das, Debraj Roldán, Édgar |
| contents | We introduce a single-qubit quantum measurement engine fuelled by backaction energy input. To reduce energetic costs associated with information processing, the measurement outcomes are only used with a prescribed laziness probability in the feedback step. As a result, we show that the work extracted over consecutive cycles is a second-order Markov process, analogous to a run-and-tumble process with transient anomalous diffusion. We derive exact analytical expressions for the work finite-time moments and first-passage-time statistics. Furthermore, we find the optimal laziness probability maximizing the mean power extracted per cycle. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_18783 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Run-and-tumble exact work statistics in a lazy quantum measurement engine: stochastic information processing Bresque, Léa Das, Debraj Roldán, Édgar Quantum Physics Statistical Mechanics We introduce a single-qubit quantum measurement engine fuelled by backaction energy input. To reduce energetic costs associated with information processing, the measurement outcomes are only used with a prescribed laziness probability in the feedback step. As a result, we show that the work extracted over consecutive cycles is a second-order Markov process, analogous to a run-and-tumble process with transient anomalous diffusion. We derive exact analytical expressions for the work finite-time moments and first-passage-time statistics. Furthermore, we find the optimal laziness probability maximizing the mean power extracted per cycle. |
| title | Run-and-tumble exact work statistics in a lazy quantum measurement engine: stochastic information processing |
| topic | Quantum Physics Statistical Mechanics |
| url | https://arxiv.org/abs/2410.18783 |