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Quantum Computing for Drug Discovery Challenge at ICCAD 2023

License: MIT License

Python 83.91% Batchfile 5.34% Makefile 0.13% Jupyter Notebook 10.62%
contest-solution quantum-computing vqe

iccad-2023-vqe's Introduction

ICCAD-2023-VQE

Quantum Computing for Drug Discovery Challenge at ICCAD 2023

Contest page: https://qccontest.github.io/QC-Contest/

How to run?

⚪ install

  • better prepare a working Linux system, since PySCF CANNOT run on Windows!! :(
    • it's also ok to run on Windows, but must use a pre-calculated ham file like OHhamiltonian.txt
    • and few features are unavailable, no big matter
  • create venv (optional)
    • install Miniconda latest
    • conda create -n qs
    • conda activate qs
  • install dependencies pip install -r requirements.txt
    • if you have CUDA on Linux, one more cmdline: pip install qiskit-aer-gpu
  • test qiskit installation
    • python _tutorial_qiskit_vqe.py
  • clone the code & data base git clone https://github.com/qccontest/QC-Contest-Demo
  • test demo code runnable
    • python _test_examplecode.py -T 2; this might be very slow, just be patient :(
    • python _test_NoiseModel_and_SystemModel.py

⚪ run the results for submission

  • run jupyter notebook run_submission.ipynb

⚪ run development

⚠ for Windows where PySCF is not available, you could only run with a pre-calculated ham file

  • python run.py, the ham will be computed by Qiskit-PySCF (Linux only!)
  • python run.py -H ham_file to specify an arbitary pre-calculated ham file
    • run the contest ham: python run.py -H txt or python run.py -H QC-Contest-Demo\Hamiltonian\OHhamiltonian.txt
    • run the ChemiQ pre-computed ham: python run.py -H playground\run_chq.ham
      • this ham seems to be inconsist with the Qiskit-PySCF analyzed one, with energy-diff approximately right the value of nuclear_repulsion_energy
      • have no idea about know whether it is a bug or feature :(

references


by Armit 2023/09/05

iccad-2023-vqe's People

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