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Record W4319339209 · doi:10.21203/rs.3.rs-2501000/v1

A mode-locked random laser generating transform-limited optical pulses

2023· preprint· en· W4319339209 on OpenAlexaff
Jean Pierre von der Weid, Marlon M. Correia, Pedro Tovar, Anderson S. L. Gomes, Walter Margulis

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLaserOpticsUltrashort pulseNanosecondRandom laserCoherence (philosophical gambling strategy)Mode-lockingPulse durationPhysicsRayleigh scatteringFiber laserMaterials scienceOptoelectronicsLasing threshold

Abstract

fetched live from OpenAlex

Abstract Ever since the mid-1960’s, locking the phases of modes enabled the generation of laser pulses of duration limited only by the uncertainty principle, opening the field of ultrafast science. In contrast to conventional lasers, random lasers usually lack at least a mirror and generally emit broadband low-coherence light. They have, nevertheless, cavity modes that distinguish them from amplifiers and superluminescent light sources. Mode spacing in random lasers is ill-defined because optical feedback comes from scattering centres at random positions. Although progress has been made towards locking spatial and longitudinal modes in random lasers, the literature lacks reports on transform-limited pulse generation despite the many decades of the field. Here the generation of sub-nanosecond transform-limited pulses from a mode-locked random fibre laser is described. Exceedingly weak (<-73 dB) Rayleigh backscattering from decimetre-long sections of telecom fibre serves as laser feedback, providing narrow spectral selectivity to the Fourier limit. This unique laser is adjustable in pulse duration (0.34-20 ns), repetition rate (0.714-1.05 MHz) and can be temperature tuned. The high spectral-efficiency pulses are applied in distributed temperature sensing with 9.0 cm and 3.3x10 -3 K resolution, exemplifying how the results can drive advances in the fields of spectroscopy, telecommunications, and sensing.

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.076
GPT teacher head0.397
Teacher spread0.321 · 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 designOther design
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

Citations2
Published2023
Admission routes1
Has abstractyes

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