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Quintessence

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MIT IQuHack 2023 Hackathon

IonQ challenge

Landing page: https://ionq.com/

To recap, for this challenge, you must use a quantum computer to generate something new. Some ideas:

Quantum haze

We are using a number preserving quantum walk search algorithm running on IonQ (other backends can be included) to output results of a graph traversal algorithm which represents the scattered journey of our main character, Mr. Quanta, and how he tries to figure out what happened to him during his incoherent rambling through QuantaLand. This output will be fed back into a transformers AI model and then to a stable diffusion AI model to generate a exciting dynamic storyline with associated graphics. For a more in depth discussion of the applied circuit, see the following file.

Example Result

rose

Mr. Quanta awoke on the rooftop bar, feeling a bit disoriented. He had no idea how he had gotten there, but he had a vague recollection of a concert venue. He remembered the music, the lights, and the energy of the crowd. He had been having a great time, but he couldn't remember how he had ended up on the rooftop bar.

generated Image

Setup

You'll need to provide your own API keys as env variables at the beginning on main.py

  • provider = IonQProvider("tQgNZln2nI3JSOg7hZhRXjSJHYfgrS2S")
  • openai.api_key = "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"

You need to install those python packages:

  • qiskit
  • qiskit-ionq
  • flask
  • flask-cors
  • openai

Run

To run "Quantum Haze" you need to run the following command:

python main.py

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