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Analogs Of Event Horizon

2009· book-chapter· en· W2499376471 on OpenAlexaboutno aff
VOLOVIK GRIGORY E.

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldPhysics and Astronomy
TopicQuantum, superfluid, helium dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEvent horizonPhysicsBlack hole (networking)QuasiparticleMembrane paradigmHorizonBlack hole complementarityHawking radiationBlack hole thermodynamicsFuzzballClassical mechanicsQuantum mechanicsEvent (particle physics)Micro black holeExtremal black holeCharged black holeAstronomyComputer science

Abstract

fetched live from OpenAlex

Abstract A black hole is the region from which the observer who is outside the hole cannot obtain any information. The event horizon represents the boundary of the black hole region. Analogs of the black hole horizon can be realised in such condensed matter where the effective metric arises for quasiparticles. The simplest way to do this is to exploit the liquids moving with velocities exceeding the local maximum attainable speed of quasiparticles. Then, an inner observer who uses only quasiparticles as a means of transferring the information, finds that some regions of space are not accessible for observation. For this observer, who lives in the quantum liquid, these regions are black holes. This chapter discusses different arrangement in superfluids, which may simulate the event horizons; the moving vierbein wall; Laval nozzle; and horizon emerging for ripplons at the interface between 3He-A and 3He-B. The effective Painlevé–Gullstrand metric, which naturally arises in moving superfluids, leads to the simple description of Hawking radiation in terms of quantum tunnelling of quasiparticles across the event horizon. This consideration is extended to the astronomical black holes. Black hole instability beyond the horizon and modified Dirac equation for fermions in the black hole environment are considered.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.363
Threshold uncertainty score1.000

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)0.0040.000

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

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