https://github.com/dpbm/qcop
An AI model to predict the output of a quantum cirucit
https://github.com/dpbm/qcop
airflow apache-airflow compose dags docker docker-compose make pillow python pytorch qiskit qiskit-aer quantum-computing
Last synced: 4 months ago
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An AI model to predict the output of a quantum cirucit
- Host: GitHub
- URL: https://github.com/dpbm/qcop
- Owner: Dpbm
- License: apache-2.0
- Created: 2025-04-16T18:47:47.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-08-10T13:38:11.000Z (5 months ago)
- Last Synced: 2025-08-19T03:35:57.902Z (5 months ago)
- Topics: airflow, apache-airflow, compose, dags, docker, docker-compose, make, pillow, python, pytorch, qiskit, qiskit-aer, quantum-computing
- Language: Python
- Homepage: https://dpbm.github.io/qcop/
- Size: 830 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
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Metadata Files:
- Readme: readme.md
- License: LICENSE
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README
# QCOP
## In progress 🚧
[](https://github.com/Dpbm/qcop/actions/workflows/dockerhub.yml)
[](https://github.com/Dpbm/qcop/actions/workflows/ghcr.yml)
[](https://github.com/Dpbm/qcop/actions/workflows/tox-tests.yml)
This project, is a computer vision model based on RestNet trained to be able to predict the output of a quantum circuit.
To do this, Two Airflow pipelines were built. One to construct the dataset using Qiskit and then upload it to kaggle and huggingface, and the other one to get the dataset and train/evaluate the model.
The whole project was built in python with some helpers in bash and docker containers to pack the airflow instance as well as the postgres database used by it.
