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Record W2073390666 · doi:10.1109/cleoe.2011.5942681

Chirped-pulse interferometry for dispersion-cancelled OCT

2011· article· en· W2073390666 on OpenAlexaff
Robert Prevedel, K. M. Schreiter, Rainer Kaltenbaek, Jonathan Lavoie, D. N. Biggerstaff, Kevin J. Resch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInterferometryPhysicsAstronomical interferometerPhotonOpticsQuantum imagingLaserQuantumQuantum opticsChirpDispersion (optics)Bandwidth (computing)Quantum mechanicsQuantum technologyComputer scienceOpen quantum systemTelecommunications

Abstract

fetched live from OpenAlex

Here we report on a completely classical technique based on the time-reversal symmetry of quantum mechanics that achieves all the advantages of HOM interferometry by using oppositely-chirped laser pulses. Since our technique relies on classical lasers instead of entangled photons, it achieves these features with millions of times larger signal making it an attractive candidate for dispersion-free OCT. In particular, the visibility and width of the CPI interferogram is insensitive to dispersion and photon loss, and inherently robust against phase-fluctuations. Further, we achieve higher resolution than classical interferometers using the same bandwidth. On a fundamental level, our work emphasizes the importance of delineating truly quantum effects from those with classical analogues, and shows how insights gained from quantum mechanics can inspire novel classical technologies.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.225
Teacher spread0.195 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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