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Record W4384008657 · doi:10.1117/12.2689277

A mature 100-W 1178-nm single-frequency linearly-polarized Raman fiber amplifier for laser guide star assisted optical ground station adaptive optics systems

2023· article· en· W4384008657 on OpenAlexaff
D.-P. Wei, Ning Guo, Wallace R. L. Clements

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsMPB Technologies & Communications (Canada)
Fundersnot available
KeywordsMaterials scienceOptical amplifierOpticsOptoelectronicsFiber laserLaserAdaptive opticsAmplifierPhysicsCMOS

Abstract

fetched live from OpenAlex

While the next generation of satellite constellations provide improved capacity through the use of optical inter-satellite links, there is still a capacity bottleneck at the RF feeder links between satellites and ground stations, which are an order of magnitude slower in moving data. In order to move to all optical feeder links, there is a challenge to overcome the distortion associated with atmospheric turbulence. Laser Guide Star (LGS) adaptive optics systems are a key enabling technology to help solve this beam wander problem for ground to space optical systems. For guide star lasers suitable for daytime LGS operation, high power is key. To respond to this need, a 100-W continuous-wave (CW) 1178-nm narrow-band polarization-maintaining (PM) Raman fiber amplifier (RFA) has been developed and fully engineered. A linearly-polarized single-frequency 1178-nm seed laser with an output power of only a few mW is amplified up to 100 W in a two-stage RFA counter-pumped by a 200-W 1120-nm PM fiber laser. Techniques for efficient suppression of stimulated Brillouin scattering (SBS) have been optimized, resulting in the RFA SBS threshold being pushed beyond the 100-W level. The narrow linewidth of the seed laser is well preserved in the RFA, without any evidence of linewidth broadening up to 100 W. The RFA is based on true single-mode PM fibers and has excellent polarization purity and output beam quality, key factors for subsequent efficient frequency doubling to the Na absorption line at 589 nm in a resonant frequency-doubling cavity. Similar to the widely-deployed MPBC/TOPTICA SodiumStar 20/2, the new 100-W RFA system is a compact, modular, reliable and ruggedized off-the-shelf system ready for integration. Compared to solid-state alternatives, a guide star laser based on an all-fiber, highly-reliable, 100-W RFA not only provides excellent overall wall-plug efficiency due to its high pump-to-Raman optical conversion efficiency, but also maximizes the important “up time” for the optical channel at ground station facilities since it is a maintenance-free and turn-key system. To confirm the stability and reliability of this next-generation guide star RFA, the system was run 24/7 at the full 100 W for a total of 1300 hours. The test results confirmed that the 100-W RFA system is extremely robust and reliable, with a sufficient built-in 1120-nm pump power margin. Re-measurements of key RFA parameters, such as polarization purity and output beam quality, also confirmed that the RFA performance remained unchanged after the 1300-hour 100-W test. Assuming a conservative conversion efficiency of ~ 80% by a resonant frequency doubler and taking into account typical passive coupling losses into the doubler cavity of < 15%, narrow-linewidth CW guide star lasers with powers < 70 W at 589 nm can confidently be expected for future optical ground station adaptive optics systems. The RFA output power was shown to be solely limited by the SBS threshold. Since all the laser components showed sufficient higher optical power handling potential, it is expected that, with further optimization of the SBS suppression, the RFA output power can be scaled significantly beyond the current 100-W level.

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)0.000
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0030.002

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 head0.035
GPT teacher head0.251
Teacher spread0.217 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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