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Record W4283257075 · doi:10.1038/s41467-022-31246-y

A forward Brillouin fibre laser

2022· article· en· W4283257075 on OpenAlexfundno aff
Gil Bashan, Hilel Hagai Diamandi, Elad Zehavi, Kavita Sharma, Yosef London, Avi Zadok

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Academy of Sciences and Humanities
KeywordsBrillouin scatteringBrillouin zoneOpticsLasing thresholdLaserMaterials scienceOptical fiberFiber laserSingle-mode optical fiberOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

Fibre lasers based on backward stimulated Brillouin scattering provide narrow linewidths and serve in signal processing and sensing applications. Stimulated Brillouin scattering in fibres takes place in the forward direction as well, with amplification bandwidths that are narrower by two orders of magnitude. However, forward Brillouin lasers have yet to be realized in any fibre platform. In this work, we report a first forward Brillouin fibre laser, using a bare off-the-shelf, panda-type polarisation maintaining fibre. Pump light in one principal axis provides Brillouin amplification for a co-propagating lasing signal of the orthogonal polarisation. Feedback is provided by Bragg gratings at both ends of the fibre cavity. Single-mode, few-modes and multi-mode regimes of operation are observed. The lasing threshold exhibits a unique environmental sensitivity: it is elevated when the fibre is partially immersed in water due to the broadening of forward Brillouin scattering spectra. The results establish a new type of fibre laser, with potential for ultra-high coherence and precision sensing of media outside the cladding.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.635
Threshold uncertainty score0.493

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 science0.0010.000
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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations27
Published2022
Admission routes1
Has abstractyes

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