Quantum-GAN-implementation (Classical data and discriminator, Quantum Generator)

This work uses Pytorch, PennyLane and Qiskit to generate new molecules

Reference paper: https://arxiv.org/abs/1805.11973

Reference paper: https://arxiv.org/abs/1805.11973

Refer DeCao's repo: https://github.com/nicola-decao/MolGAN for baseline

this repo was created to fix some code issues and implement statitical analysis for circuit design and energy consumption.

installations

!pip install frechetdist

!pip install kora

import kora.install.rdkit

!pip install rdkit-pypi

!pip -q install Pillow

!pip install torch torchvision

#Bash commands to download the QM9 dataset through the '.sh' file

import os

os.chdir("/home/vikram/Quantum-GAN-implementation-using-PennyLane-and-IBMQ/data/")

%%bash

chmod u+x download_dataset.sh

./download_dataset.sh

!python sparse_molecular_dataset.py

import os

os.getcwd()

os.chdir("/home/vikram/Quantum-GAN-implementation-using-PennyLane-and-IBMQ/")

!python main.py --quantum True --layer 2 --qubits 8 --complexity 'nr'