A note on the Landauer principle in quantum statistical mechanics
Bibliographic record
Abstract
The Landauer principle asserts that the energy cost of erasure of one bit of information by the action of a thermal reservoir in equilibrium at temperature T is never less than kBT log 2. We discuss Landauer's principle for quantum statistical models describing a finite level quantum system \documentclass[12pt]{minimal}\begin{document}${\cal S}$\end{document}S coupled to an infinitely extended thermal reservoir \documentclass[12pt]{minimal}\begin{document}${\cal R}$\end{document}R. Using Araki's perturbation theory of KMS states and the Avron-Elgart adiabatic theorem we prove, under a natural ergodicity assumption on the joint system \documentclass[12pt]{minimal}\begin{document}${\cal S}+{\cal R}$\end{document}S+R, that Landauer's bound saturates for adiabatically switched interactions. The recent work [Reeb, D. and Wolf M. M., “(Im-)proving Landauer's principle,” preprint arXiv:1306.4352v2 (2013)] on the subject is discussed and compared.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".