# neuroptica

**Repository Path**: m3reference/neuroptica

## Basic Information

- **Project Name**: neuroptica
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-10-01
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# neuroptica [![Documentation Status](https://readthedocs.org/projects/neuroptica/badge/?version=latest)](https://neuroptica.readthedocs.io/en/latest/?badge=latest) [![Build Status](https://travis-ci.com/fancompute/neuroptica.svg?token=CSoUuvqmixfJpdwkLqet&branch=master)](https://travis-ci.com/fancompute/neuroptica)

`neuroptica` is a flexible chip-level simulation platform for [nanophotonic neural networks](https://arxiv.org/abs/1903.04579) written in Python/NumPy. It provides a wide range of abstracton levels for simulating optical NN's: the lowest-level functionality allows you to manipulate the arrangement and properties of individual phase shifters on a simulated chip, and the highest-level features provide a Keras-like API for designing optical NN by stacking network layers.


## Installation

The easiest way to get started with `neuroptica` is to install directly from the Python package manager:

```
pip install neuroptica
```

Alternately, you can clone the repository source code and edit it as needed with:

```
git clone https://github.com/fancompute/neuroptica.git
pip install -e neuroptica
```

To run unit tests, use `- python -m unittest discover -v` from the root package directory.

## Getting started

For an overview of `neuroptica`, read the [documentation](https://neuroptica.readthedocs.io). Example notebooks are included in the [`neuroptica-notebooks`](https://github.com/fancompute/neuroptica-notebooks) repository:

- [Planar data classification using electro-optic activation functions](https://github.com/fancompute/neuroptica-notebooks/blob/master/neuroptica_demo.ipynb)

![neuroptica training demo](https://raw.githubusercontent.com/fancompute/neuroptica/master/img/neuroptica_demo.gif)


## Citing

`neuroptica` was written by [Ben Bartlett](https://github.com/bencbartlett), [Momchil Minkov](https://github.com/momchilmm), [Tyler Hughes](https://github.com/twhughes), and  [Ian Williamson](https://github.com/ianwilliamson). If you find this useful for your research, please cite the GitHub repository and/or the JSQTE paper:

```
@misc{Bartlett2019Neuroptica,
  author = {Ben Bartlett and Momchil Minkov and Tyler Hughes and Ian A. D. Williamson},
  title = {Neuroptica: Flexible simulation package for optical neural networks},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/fancompute/neuroptica}},
  commit = {06484f698ee038eeb128cdfbd4c59a7e96185bb4}
}
```


```
@article{Williamson2019Reprogrammable, 
  author={I. A. D. Williamson and T. W. Hughes and M. Minkov and B. Bartlett and S. Pai and S. Fan}, 
  journal={IEEE Journal of Selected Topics in Quantum Electronics}, 
  title={Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks},
  year={2020}, 
  volume={26}, 
  number={1}, 
  pages={1-12}
}
```