README.md

neurarpes

Neural networks applied to ARPES data

Installation

To install the package in an existing environment, clone the repository and run the following command in the root directory:

Virtual Environment

In order to properly install this package, it is recommended to use a virtual environment. This can be done using conda by running the following commands:

conda create -n arpesnet python=3.11

This will create a new empty environment called arpesnet

Activate this environment

conda activate arpesnet

Package Installation

To start, we install PyTorch, the main dependency of the package. How to correctly install pytorch depends on the system and the desired settings. We recomend to follow the instructions on the pytorch website, however here are a few common case examples:

CPU only

To install pytorch with CPU only, run the following command:

conda install pytorch torchvision torchaudio cpuonly -c pytorch

CUDA 12.1

To install pytorch with CUDA 11.1, run the following command:

conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia

Apple MX processor

To install pytorch with the Apple MX processor, run the following command:

conda install pytorch torchvision torchaudio -c pytorch-nightly

Package Installation

After installing pytorch, we can install arpesnet as described above, running:

pip install -e .

Notebooks

A few additional packages are required to run the notebooks available in the notebooks folder. To install these, install the package with the following command:

pip install -e .[notebooks]

Citation and Acknowledgements

If you use this package in your work, please cite the following paper:

@article{arpesnet,
  title={Neural networks applied to ARPES data},
  author={Steinn  Ýmir Ágústsson, Mohammad Ahsanul Haque, Thi Tam Truong, Marco Bianchi, Nikita Klyuchnikov, Davide Mottin, Panagiotis Karras and Philip Hofmann},
  status={In Preparation}
}