---
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