Metadata-Version: 2.1
Name: ga-vqc
Version: 0.0.2
Summary: Genetic Algorithm for VQC ansatz search.
Home-page: https://github.com/tcoulvert/GA_Ansatz_Search
Author: Thomas Sievert
Author-email: 63161166+tcoulvert@users.noreply.github.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: matplotlib (>=3.7.1)
Requires-Dist: numpy (>=1.20.3)
Requires-Dist: pandas (>=1.5.3)
Requires-Dist: scikit-learn (>=1.0.1)
Provides-Extra: dev
Requires-Dist: pytest (>=3.7) ; extra == 'dev'
Requires-Dist: check-manifest (>=0.47) ; extra == 'dev'

# GA for VQC Ansatz Search
This is a module to support Variational Quantum Circuits by optimizing the ansatz. The ansatz optimization is performed using a Genetic Algorithm, which can be sped up with GPUs.


## Installation
Run the following to install:
```bash
$ pip install ga_vqc
```

## Contributors
This module was developed through the Caltech SURF program. Special thanks
to my mentor at Caltech.
- Jean-Roch (California Institute of Technology, Pasadena, CA 91125, USA)

## Usage
```python
import ga_vqc as gav

# Config (hyperparameters) for GA, see full list in example
config = {
    'backend': 'simple',
    'vqc': main,
}

# Create the GA with the given hyperparameters
ga = gav.setup(config)

# Evolve the GA and search for the best ansatz
ga.evolve()
```
