metadata
language:
- en
license: mit
pretty_name: EUV Illumination Pupil Coherence Drift Detection v0.1
dataset_name: euv-illumination-pupil-coherence-drift-detection-v0.1
tags:
- clarusc64
- euv
- lithography
- optics
- drift-detection
task_categories:
- tabular-classification
- tabular-regression
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: data/train.csv
- split: test
path: data/test.csv
Purpose
Detect when illumination-pupil coupling begins to drift toward loss of critical dimension control.
This dataset maps coherence decay between:
pupil geometry
dose distribution
printed wafer metrics
The goal is to identify drift before feature collapse.
Task
Input system metrics.
Predict:
drift_score
drift_flag
Format: float,int
Example: 0.42,1
Why this matters
Lithography systems rarely fail instantly.
They drift.
Early detection prevents yield loss and tool downtime.
Evaluation
Absolute error on drift_score
Classification bonus for drift_flag
Format validity scored when ground truth absent.
Version
v0.1