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Proposal for a long-lived quantum memory using matter-wave optics with Bose-Einstein condensates in microgravity

2023· article· en· W4383218594 on OpenAlexaff
Elisa Da Ros, Simon Kanthak, Erhan Sağlamyürek, Mustafa Gündoğan, Markus Krutzik

Bibliographic record

VenuePhysical Review Research · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCold Atom Physics and Bose-Einstein Condensates
Canadian institutionsUniversity of CalgaryUniversity of Alberta
FundersHorizon 2020European Commission
KeywordsPhysicsBose–Einstein condensateQuantum decoherenceQuantumQuantum sensorQuantum mechanicsMatter waveQuantum computerQuantum network

Abstract

fetched live from OpenAlex

Bose-Einstein condensates are a promising platform for optical quantum memories but suffer from several decoherence mechanisms, leading to short memory lifetimes. While some of these decoherence effects can be mitigated by conventional methods, density-dependent atom-atom collisions ultimately set the upper limit of the quantum memory lifetime to timescales of seconds in trapped Bose-Einstein condensates. We propose a quantum memory technique that utilizes microgravity as a resource to minimize such density-dependent effects. We show that by using optical atom lenses to collimate and refocus the freely expanding atomic ensembles, in a semi-ideal environment, the expected memory lifetime is only limited by the quality of the background vacuum. We anticipate that this method can be experimentally demonstrated in Earth-bound microgravity platforms or space missions, eventually leading to storage times of minutes and unprecedented time-bandwidth products of ${10}^{10}$.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.135
GPT teacher head0.422
Teacher spread0.288 · 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 designBench or experimental
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

Citations10
Published2023
Admission routes1
Has abstractyes

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