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license: mit
task_categories:
- image-to-image
tags:
- lithography
- physics-simulation
- semiconductor
- chemistry
size_categories:
- n<1K
---
# vFab-1.0-Photolithography-ML-surrogate-Tensor-Dataset
This dataset contains generated physics simulations for semiconductor photolithography, formatted as Native NCHW `.npy` arrays for direct ingestion into PyTorch models.
## Dataset Structure
The data is split into two simulation phases:
**1. Aerial Image Dataset (`aerial_image_dataset/`)**
* **Inputs (`X_input/`):** Shape `[4, 512, 512]`. Contains:
* Channel 0: Binary Layout Mask (Vertical/Horizontal Gratings, Contact Arrays, etc.)
* Channel 1: Normalized Dose (mJ)
* Channel 2: Normalized Defocus (nm)
* Channel 3: Normalized Numerical Aperture (NA)
* **Targets (`Y_normalized_aerial/`):** Shape `[1, 512, 512]`. Hopkins-Abbe optical intensity simulation.
**2. Post-Exposure Bake (PEB) Dataset (`peb_dataset/`)**
* **Targets (`Y_target_M/`):** Shape `[1, 512, 512]`. Chemical reaction matrices (M-matrix) simulating the acid-base diffusion and polymer deprotection during the PEB step.
## Usage
Data can be loaded directly using NumPy and PyTorch:
```python
import numpy as np
import torch
x_input = np.load('X_input/sample_0.npy')
tensor_x = torch.tensor(x_input, dtype=torch.float32)
```
> **Note:** The Hugging Face Dataset Viewer will show an error for this repository because it cannot natively render `.npy` tensor arrays in the browser. The dataset is fully functional and can be downloaded using the `huggingface_hub` library. |