REVOLT: an on-sky adaptive optics technology research platform on a 1.2m telescope
Bibliographic record
Abstract
The Research, Experiment and Validation of adaptive Optics on a Legacy Telescope (REVOLT) project is an on-sky AO technology research platform which was commissioned at the Dominion Astrophysical Observatory’s (DAO) 1.2m telescope in Victoria, Canada in June 2022. The goal of the project is to provide a flexible and expandable AO system to test a wide variety of technologies and control strategies with rapid deployment to sky. To date, REVOLT has enabled the first on-sky use of the Herzberg Extensible Adaptive Realtime Toolkit (HEART), a realtime controller software package developed at the National Research Council of Canada’s Herzberg Astronomy and Astrophysics (NRC-HAA) research centre, slated to be deployed on multiple future AO instruments. REVOLT has provided the first on-sky demonstration of First Light Imaging’s C-Blue-One CMOS camera as a Shack-Hartmann Wavefront Sensor (SH-WFS), and demonstrated injection of the science PSF into a single mode fiber to feed experimental Spectral Correlation Sensor technology being developed to detect gas signatures in planetary atmospheres. Since its initial commissioning as a Single Conjugate AO (SCAO) system, an open loop arm, the GIRMOS Open Loop Demonstration (GOLD) arm, has been added to test OL calibration and control, and a Pyramid WFS (PWFS) arm has been added with the goal first of testing the Gemini Planet Imager 2 (GPI-2) HEART pipeline, as well as provide an on going test platform for PWFS research. This paper provides a full description of the current REVOLT system, summarizes the performance of each experiment conducted to date, highlights future plans and openly invites proposals for collaboration from the AO community.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".