Complex lens design: searching for a needle in a haystack
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Optical design of complex (multi-element) lenses is traditionally considered to be part science and part art, primarily because of the enormous complexity of the problem. Recent advances in high performance computing (HPC) made it feasible to adopt a purely scientific approach in discovering new lens designs. In this paper, I formulate the task of finding a new lens design that satisfies a given set of constraints as a search for the global minimum of a function of unknown and very large (∼ 30 – 100) number of dimensions. I address the significant complication that only a tiny fraction of the volume of the free parameters space is physically accessible. I propose a smart lens drafting algorithm which circumvents this difficulty. I present my numerical code which can be used to discover novel complex lens designs in a fully automatic fashion. I discuss the HPC aspects of the problem of searching for minima of high dimensionality functions.
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.
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 | 0.001 | 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 | 0.004 |
| 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 it