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Record W1660590624 · doi:10.48550/arxiv.gr-qc/0404022

Simulation of gravitational objects in Bose-Einstein condensates

2004· preprint· en· W1660590624 on OpenAlexaboutno aff
Silke Weinfurtner

Bibliographic record

VenuearXiv (Cornell University) · 2004
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsnot available
Fundersnot available
KeywordsBose–Einstein condensatePhysicsGravitationEinsteinClassical mechanicsTheoretical physicsQuantum mechanics

Abstract

fetched live from OpenAlex

In this diplom-arbeit I consider a specific class of "analogue models" of curved spacetime that are specifically based on the use of Bose-Einstein condensates. As is usual in "analogue models", we are primarily interested in the kinematics of fields and quanta immersed in a curved-space background. We are not directly concerned with the Einstein equations of general relativity. Over the last few years numerous papers concerning "analogue models" have been published, the key result being that in many dynamical systems the perturbations have equations of motion that are governed by an "effective metric" that can often be interpreted in terms of an equivalent gravitational field. After a brief introduction concerning Bose-Einstein condensates and general relativity, I explain the connection between these two fields. Several specific examples are then explored in a little more detail: 1) Sinks and acoustic black holes [dumb holes]. 2) Ring-shaped Laval nozzles and acoustic horizons. 3) the de Sitter universe. In particular, the de Sitter universe is modelled by a freely expanding condensate obtained by suddenly switching off the trap that normally holds the condensate in place.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.046
GPT teacher head0.206
Teacher spread0.160 · 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 designSimulation or modeling
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

Citations8
Published2004
Admission routes1
Has abstractyes

Explore more

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