https://github.com/aishwaryahastak/qvisiongan

Quantum GAN Model to generate images with limited qubits
https://github.com/aishwaryahastak/qvisiongan

generative-adversarial-network image-generation mnist-dataset qiskit quantum-machine-learning

Last synced: about 1 month ago
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Quantum GAN Model to generate images with limited qubits

• Host: GitHub
• URL: https://github.com/aishwaryahastak/qvisiongan
• Owner: AishwaryaHastak
• Created: 2024-05-20T15:21:37.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-06-03T16:11:44.000Z (8 months ago)
• Last Synced: 2024-11-08T23:52:02.503Z (3 months ago)
• Topics: generative-adversarial-network, image-generation, mnist-dataset, qiskit, quantum-machine-learning
• Language: Python
• Homepage:
• Size: 21.8 MB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

        
# Quantum Vision GAN: Quantum GAN for generating MNIST digits

# Motivation

SOTA Quantum Generative Adversarial Networks have trouble generating high-quality images and usually tend to use lower-resolution images. A lot of the recent QGANs use a smaller version (usually 8x8 or 16x16) version of the MNIST dataset. 

We need the ability for GANs to be able to produce higher-quality images as well. 

Additionally, we want the ability to generate images even when we have a limited number of available qubits to work with. In this project we try to adapt the PatchGAN [1] model to a larger dataset. 

# Methodology

We follow the same Quantum ansatz as proposed in the original PatchGAN paper, but we adapt it for a larger dataset using the number of qubits in a range from 5 to 9. 

We start with a random noise vector and iteratively train the Generator and Discriminator to produce better-quality images.

# Results

**Generating the Digit 0 using 5 qubits**

![Digit0_5qb](https://github.com/AishwaryaHastak/QGAN/assets/31357026/1e28c4fc-e3b7-438c-b81e-8971d3c8778f)

**Generating the Digit 3 using 5 qubits**

![Digit3_5qb](https://github.com/AishwaryaHastak/QGAN/assets/31357026/d009c89d-1f21-4671-8847-abba40cbca3a)

**Generating the Digit 9 using 6 qubits**

![Digit9_6qb](https://github.com/AishwaryaHastak/QGAN/assets/31357026/03c54562-0b46-4a6e-89ef-a53b9445890b)

# Ongiong/Future Work

The images are not clear and still have some noise in the background. Additionally, the images are very similar and we would like the generator to produce different-looking images. The next steps could be to experiment with the architecture (changing gate types and adding more layers). We could also try using a quantum discriminator instead of a classical discriminator, to fully realize the quantum advantage.  

# References

[1] Huang, He-Liang, et al. "Experimental quantum generative adversarial networks for image generation." Physical Review Applied 16.2 (2021): 024051.