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Record W3036611567 · doi:10.4006/0836-1398-33.2.143

Bekenstein‐Hawking black hole entropy, Hawking temperature, and the Unruh effect: Insight from the laws of thermodynamics

2020· article· en· W3036611567 on OpenAlexvenueno aff
Stephen J. Crothers, Pierre‐Marie Robitaille

Bibliographic record

VenuePhysics Essays · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsUnruh effectBlack hole thermodynamicsLaws of thermodynamicsEntropy (arrow of time)Black hole (networking)GravitationHawkingHawking radiationThermodynamicsSchwarzschild radiusTheoretical physicsNon-equilibrium thermodynamicsLawQuantum mechanicsQuantum

Abstract

fetched live from OpenAlex

The laws of thermodynamics play a central role in scientific inquiry, guiding physics as to the validity of hypothesized claims. It is for this reason that quantities of thermodynamic relevance must retain their character wherever they appear. Temperature, for example, must always be intensive, a requirement set by the 0th law. Otherwise, the very definition of temperature is compromised. Similarly, entropy must remain extensive, in order to conform to the second law. These rules must be observed whenever a system is large enough to be characterized by macroscopic quantities, such as volume or area. This explains why ensembles comprised of just a few atoms cannot be considered thermodynamic systems. In this regard, black holes are hypothesized to be large systems, characterized by the Schwarzschild radius ( r s = 2 GM / c 2 ) and its associated “horizon” area ( A = 4π r s 2 ), where G , M , and c represent the universal constant of gravitation, the mass of the black hole, and the speed of light in vacuum, respectively. It can be readily demonstrated that Bekenstein‐Hawking black hole entropy is nonextensive, while the Hawking and the Unruh temperatures are nonintensive. As a result, the associated equations violate the laws of thermodynamics and can hold no place in the physical sciences.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.538
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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 teacher head, 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

Citations2
Published2020
Admission routes1
Has abstractyes

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