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Record W2228026312 · doi:10.1103/physreve.79.031105

Generalizing Landauer’s principle

2009· article· en· W2228026312 on OpenAlexaff
O. J. E. Maroney

Bibliographic record

VenuePhysical Review E · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsPerimeter Institute
Fundersnot available
KeywordsUniversality (dynamical systems)Mathematical proofStatement (logic)ComputationMathematicsMathematical economicsWork (physics)Calculus (dental)Logical conjunctionTheoretical physicsComputer scienceStatistical physicsEpistemologyPhysicsQuantum mechanicsPhilosophyAlgorithm

Abstract

fetched live from OpenAlex

In a recent paper [Stud. Hist. Philos. Mod. Phys. 36, 355 (2005)] it is argued that to properly understand the thermodynamics of Landauer's principle it is necessary to extend the concept of logical operations to include indeterministic operations. Here we examine the thermodynamics of such operations in more detail, extending the work of Landauer to include indeterministic operations and to include logical states with variable entropies, temperatures, and mean energies. We derive the most general statement of Landauer's principle and prove its universality, extending considerably the validity of previous proofs. This confirms conjectures made that all logical operations may, in principle, be performed in a thermodynamically reversible fashion, although logically irreversible operations would require special, practically rather difficult, conditions to do so. We demonstrate a physical process that can perform any computation without work requirements or heat exchange with the environment. Many widespread statements of Landauer's principle are shown to be special cases of our generalized principle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.019
Scholarly communication0.0030.009
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.016
GPT teacher head0.345
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations97
Published2009
Admission routes1
Has abstractyes

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