The Real-Time controller (RTC) for the Narrow Field Infrared Adaptive Optics System (NFIRAOS) for TMT final design
Bibliographic record
Abstract
The Real-Time Controller (RTC) for the Thirty Meter Telescope (TMT) Narrow Field Infrared Adaptive Optics System (NFIRAOS) is the software and server hardware that converts wavefront error measurements into wavefront corrector demands, at the heart of the laser guide star multi-conjugate adaptive optics (MCAO) or natural guide star adaptive optics (NGS AO). The RTC takes input from up to six Shack-Hartmann Laser Guide Star wavefront sensors (LGS WFS), one high-order Natural Guide Star Pyramid Wavefront Sensor (PWFS), up to three Shack-Hartmann On-Instrument wavefront sensors (OIWFS) that are located in the client science instruments, and up to 4 on-detector guide windows (ODGW) also in the client instruments. The RTC controls two deformable mirrors conjugated to 0km (DM0) and 11.8km (DM11). DM0 is mounted on a tip/tilt stage (TTS). During the final design phase we performed prototyping to verify that off-the-shelf servers using general purpose CPUs are able to support the maximum 800 Hz frequency at which the RTC is required to operate. We also considered methods to provide live data streams to a graphical user interface without impacting the AO system performance. This paper will discusses the outcome of the impact of jitter and latency on loop speed in our prototype and an overview of the RTC pipeline, including the many “knobs” that can be turned to fine-tune the behavior of NFIRAOS in different observing modes, and under different observing conditions.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.016 |
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".