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Record W2281863659 · doi:10.1103/physreva.92.033846

Cascading quantum light-matter interfaces with minimal interconnection losses

2015· article· en· W2281863659 on OpenAlexfundno aff
Mehdi Namazi, Thomas Mittiga, Connor Kupchak, Eden Figueroa

Bibliographic record

VenuePhysical Review A · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsnot available
FundersOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsInterconnectionPhotonKey (lock)Computer scienceMilestoneQuantumInterface (matter)OptoelectronicsQuantum networkField (mathematics)PhysicsQuantum informationOpticsQuantum mechanicsMoleculeTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

The ability to interface multiple optical quantum devices is a key milestone towards the development of future quantum information processors and networks. One of the requirements for any of their constituent elements will be cascadability, i.e., the ability to drive the input of a device using the output of another one. Here, we report the cascading of quantum light-matter interfaces by storing few-photon level pulses of light in warm vapor followed by the subsequent storage of the retrieved field onto a second ensemble. We demonstrate that by using built-in purification mechanisms in the sequential storage, the final signal-to-background ratio can remain greater than one for weak pulses containing eight input photons on average.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
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)0.0000.001

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 head0.023
GPT teacher head0.312
Teacher spread0.290 · 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 designNot applicable
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

Citations3
Published2015
Admission routes1
Has abstractyes

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