Metadata-Version: 2.4
Name: GokuNEmu
Version: 0.1.10
Summary: 10D emulator for the nonlinear matter power spectrum built on Goku simulations
Author-email: Yanhui Yang <yyang440@ucr.edu>
License-Expression: MIT
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch
Requires-Dist: scikit-learn
Requires-Dist: numpy
Requires-Dist: scipy
Dynamic: license-file

# GokuNEmu: A Neural Network Emulator Based on the Goku Simulation Suite

**GokuNEmu** is a neural network (NN) emulator for the nonlinear matter power spectrum, trained on simulations from the **Goku** suite using the [T2N-MusE](https://github.com/astro-YYH/T2N-MusE) emulation technique.

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## Installation

We recommend installing GokuNEmu via `pip`:

```bash
pip install gokunemu
```

> **Note for Intel Mac users:**  
> You may need to install (if not yet) `pytorch` via `conda` before installing GokuNEmu due to potential compatibility issues with `pip` wheels:
> ```bash
> conda install -c conda-forge pytorch
> ```

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## Usage

Example notebooks are provided in the `examples/` directory:

- `example.ipynb`: Demonstrates how to use GokuNEmu for predicting the nonlinear matter power spectrum.
- `speed_benchmark.ipynb`: Benchmarks the runtime performance.

## Training data
The data used as the training set for the emulator are available at https://github.com/astro-YYH/T2N-MusE.

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## Citation

If you use **GokuNEmu**, please cite:

- The main GokuNEmu paper: https://arxiv.org/abs/2507.07177  
- The Goku simulations: https://arxiv.org/abs/2501.06296  
- The T2N-MusE emulation method: https://arxiv.org/abs/2507.07184

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## License

This project is licensed under the **MIT License**.
