Integrating MATLAB and IDL: adding adaptive optics to the TMT/VLOT integrated model
Bibliographic record
Abstract
The next generation of ground-based telescopes will have apertures of 20 meters or more and will be increasingly dependent on active and adaptive optics (AO) to deliver good image quality. A numerical model of the complete telescope system, including optical, mechanical, and atmospheric seeing effects, will be a vital tool during the design process. The Thirty Meter Telescope (TMT) / Very Large Optical Telescope (VLOT) Integrated Model (IM) is written in MATLAB and runs on a Windows PC. One goal of the IM is to study the interaction of various AO designs with several telescope configurations. This requires the inclusion of an AO simulation engine; the IDL-based CAOS code was chosen as a starting point. Socket based software was developed to allow MATLAB MEX functions called from the IM to control the CAOS code running on a Linux PC. Software was also developed to allow MATLAB MEX functions to interact with IDL on the same Windows computer using callable IDL.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".