Development of a Fourier Transform Spectrometer to Assess Performance of an Analogue of the SPICA SAFARI Instrument
Bibliographic record
Abstract
The sensitivity of state-of-the-art superconducting far-infrared (FIR) detectors is such that wideband spectroscopic observations, particularly those employing Fourier transform spectrometers (FTS), will require techniques to reduce the spectral bandwidth of a detector to limit the photon noise from an astronomical source. The proposed SPICA SAFARI instrument employs grating spectrometers to post-disperse the light that has been modulated by a polarizing FTS onto a detector array, thereby reducing the photon noise on each detector. While the principles of this method are understood, to date an integrated system has not been realized in the laboratory. We present the development of a FIR post-dispersed polarizing FTS (PDPFTS) consisting of a warm FTS and a 4 K grating spectrometer as a first step to a fully cryogenic PDPFTS demonstrator. Realistic astronomical spectra are generated by combining line emission from a tunable THz photomixer source with continuum emission from a variable blackbody 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".