Metadata-Version: 2.1
Name: ga_vqc
Version: 0.5.0
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
License: UNKNOWN
Description: # 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
        
        vqc_main = 'Function that handles running your VQC optimization'
        
        gates_dict = {"I": (1, 0), "RX": (1, 1), "CNOT": (2, 0)}
        gates_probs = [0.175, 0.175, 0.175, 0.175, 0.3]
        genepool = gav.Genepool(gates_dict, gates_probs)
        
        vqc_config = {
            'num_qubits': 3,
            'etc': 'whatever config params your VQC model requires'
        }
        
        ga_output_path = FILEPATH_FOR_GA_OUTPUT
        
        config = gav.Config(vqc_main, vqc_config, genepool, ga_output_path)
        
        # Create the GA with the given hyperparameters
        ga = gav.setup(config)
        
        # Evolve the GA and search for the best ansatz
        ga.evolve()
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Provides-Extra: dev
