On-sky demonstration of astrophotonic fiber Fabry-Pérot correlation spectroscopy
Bibliographic record
Abstract
High sensitivity spectroscopy of astronomical targets is used for determining stellar radial velocities, exoplanet detection, and even exoplanet atmosphere sensing. However, high resolution spectrographs are bulky, highly complex and expensive instruments. While this bulk optical approach is versatile, fiber optic photonic instruments can be lower cost, more compact, and simpler to parallelize for multiple targets. Here we present a low-cost fiber-based correlation spectroscopy technique which can be used for simultaneously measuring radial velocity and molecular/atomic composition of astronomical targets. The correlation is achieved using a commercial, piezoelectrically tunable fiber Fabry-Pérot (FFP) filter that can be tuned from 1520 to 1620 nm. The output of the filter is measured using a single channel photodetector and processed using a lock-in amplifier. By adjusting the bias and modulation amplitude of the transmission spectrum of the FFP filter, the device can be optimized for maximum sensitivity to a certain absorption/emission line. We perform an on-sky demonstration using a 4.25 cm telescope to detect telluric CO2 with the sun as a background light source.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".