The SAFARI far-infrared instrument for the SPICA space telescope
Bibliographic record
Abstract
The far-infrared spectrometer SAFARI is one of the three scientific instruments on the SPICA mission, a joint European-Japanese project, which was recently selected as one of the three mission candidates for further study in ESA’s M5 call. SPICA employs a 2.5m large telescope deeply cooled to below 8K, improving sensitivities by more than two orders of magnitude with respect to Herschel and Spitzer, filling in the spectral gap between JWST, ELT and ALMA. SAFARI will provide unprecedented spectroscopic observing capabilities in the far-infrared targeting the physical processes governing the formation and evolution of galaxies over cosmic time, and of planetary systems.SAFARI will provide limiting line sensitivities of order of a few times 10–20 W/m2 (5σ-10hr) instantaneously covering the 34-230 µm wavelength range. The extremely high sensitivity of the instrument is realized by utilization of TES detector arrays distributed over four grating modules, offering a native spectral resolving power of 300. The high-resolution spectroscopy mode of the instrument is carefully designed around a post-dispersed Martin-Puplett polarizing interferometer yielding R up to 11000 at the short wavelength limit. The cryogenic translation mechanism in the heart of the FTS spectrometer layout, presents challenging development goals within the context of SAFARI, and is provided by a Canadian consortium sponsored by the CSA.In this paper we provide a comprehensive overview of the instrument architecture and key technologies currently baselined for the subsystems, units and components of SAFARI. We will present the rationale of the FTS architecture employing a MP interferometer as the best way to meet the high-resolution spectroscopic and sensitivity requirements of SAFARI, and we will discuss the different spectroscopic modes in which the instrument can be configured. We conclude the paper by discussing the projected instrument performance and spectroscopic characteristics in view of the scientific goals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".