Interferometric measurement of ultra-smooth vacuum chucks for high-precision optical manufacturing
Bibliographic record
Abstract
The precise measurement of discontinuous precise surfaces with numerous isolated features, such as the array of planar pads on a vacuum chuck for wafer handling, remains a significant challenge in optical metrology. Traditional phase-shifting interferometry (PSI) fails due to the phase unwrapping dilemma at the numerous discontinuous boundaries surrounding each protrusion, while other methods suffer from limited resolution, environmental sensitivity, or low efficiency. This paper presents a novel Dual-State Interferometric Profilometry (DSIP) method to overcome these limitations. The core of DSIP involves the acquisition of two interferograms: an in-focus state for capturing high-resolution XY coordinate information of the protruding pad array, and a deliberately defocused state for robust retrieval of Z-height information, bypassing the need for global phase unwrapping. Preliminary experiments on a vacuum chuck sample with an array of raised circular pads demonstrated that the DSIP method successfully reconstructed the three-dimensional topography with enhanced edge resolution and environmental robustness. This approach therefore offers an efficient and practical solution for quality control in precision manufacturing.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".