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Ising Optimisation

An experimental library for using annealing algorithms on toy Ising model (and other!) optimisation problems.

Contributors

@dickonfell, @JamieLNorth, @harveynw and @Joannazzh. Developed during a project for the Edinburgh CAM MSc Program - supervised by Dr Matias Ruiz.

Structure

  • /sim_anneal - Code for performing Simulated Annealing (SA), this is the popular classical algorithm.
  • /sim_quantum_anneal - Code for performing Simulated Quantum Annealing (SQA), attempting to sample from the ground state of our problem hamiltonian using Trotter slices.
  • /experiment - A sub-library for executing experiments over multiple CPU cores

Setup

  • Create a virtual environment
  • pip install -r requirements.txt

References

A crucial source in understanding and implementing Path-integral Monte Carlo for SQA:

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An optimisation library for solving Ising problems

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