Theoretical bound of the efficiency of learning
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
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| _version_ | 1866912322615771136 |
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| author | Su, Shanhe Pan, Ousi Xia, Shihao Chen, Jincan Uchiyama, Chikako |
| author_facet | Su, Shanhe Pan, Ousi Xia, Shihao Chen, Jincan Uchiyama, Chikako |
| contents | A unified thermodynamic formalism describing the efficiency of learning is proposed. First, we derive an inequality, which is more strength than Clausius's inequality, revealing the lower bound of the entropy-production rate of a subsystem. Second, the inequality is transformed to determine the general upper limit for the efficiency of learning. In particular, we exemplify the bound of the efficiency in nonequilibrium quantum-dot systems and networks of living cells. The framework provides a fundamental trade-off relationship between energy and information inheriting in stochastic thermodynamic processes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2209_08096 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Theoretical bound of the efficiency of learning Su, Shanhe Pan, Ousi Xia, Shihao Chen, Jincan Uchiyama, Chikako Statistical Mechanics Quantum Physics A unified thermodynamic formalism describing the efficiency of learning is proposed. First, we derive an inequality, which is more strength than Clausius's inequality, revealing the lower bound of the entropy-production rate of a subsystem. Second, the inequality is transformed to determine the general upper limit for the efficiency of learning. In particular, we exemplify the bound of the efficiency in nonequilibrium quantum-dot systems and networks of living cells. The framework provides a fundamental trade-off relationship between energy and information inheriting in stochastic thermodynamic processes. |
| title | Theoretical bound of the efficiency of learning |
| topic | Statistical Mechanics Quantum Physics |
| url | https://arxiv.org/abs/2209.08096 |