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Record W2998823960 · doi:10.1364/josab.373100

Persistent atomic frequency comb based on Zeeman sub-levels of an erbium-doped crystal waveguide

2019· article· en· W2998823960 on OpenAlex
Mohsen Falamarzi Askarani, Thomas A. Lutz, Marcelli Grimau Puigibert, Neil Sinclair, Daniel Oblak, Wolfgang Tittel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of the Optical Society of America B · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsUniversity of Calgary
FundersAlberta InnovatesAlberta Innovates - Technology FuturesNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk OnderzoekCanadian Institute for Advanced Research
KeywordsPopulationLithium niobateZeeman effectAnalytical Chemistry (journal)Materials sciencePhysicsChemistryOptoelectronics

Abstract

fetched live from OpenAlex

Long-lived sub-levels of the electronic ground-state manifold of rare-earth ions in crystals can be used as atomic population reservoirs for photon echo-based quantum memories. We measure the dynamics of the Zeeman sub-levels of erbium ions that are doped into a lithium niobate waveguide, finding population lifetimes at cryogenic temperatures down to 0.7 K as long as seconds. Then, using these levels, we prepare and characterize atomic frequency combs (AFCs), which can serve as a memory for quantum light at 1532 nm wavelength. The results allow predicting a 0.1% memory efficiency, limited mainly by unwanted background absorption that we believe to be caused by excitation-induced erbium spin flips and frequency shifting due to two-level systems or non-equilibrium phonons. Hence, while it should be possible to create an AFC-based quantum memory in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">E</mml:mi> <mml:mi mathvariant="normal">r</mml:mi> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mn>3</mml:mn> <mml:mo>+</mml:mo> </mml:mrow> </mml:msup> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>:</mml:mo> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">T</mml:mi> <mml:mi mathvariant="normal">i</mml:mi> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mn>4</mml:mn> <mml:mo>+</mml:mo> </mml:mrow> </mml:msup> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>:</mml:mo> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:msub> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">L</mml:mi> <mml:mi mathvariant="normal">i</mml:mi> <mml:mi mathvariant="normal">N</mml:mi> <mml:mi mathvariant="normal">b</mml:mi> <mml:mi mathvariant="normal">O</mml:mi> </mml:mrow> <mml:mn>3</mml:mn> </mml:msub> </mml:mrow> </mml:math> , improved crystal growth together with optimized AFC preparation will be required to make it suitable for applications in quantum communication.

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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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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