Embedding quantum circuit in classical variational methods

This repository contains the code to reproduce the results of the paper "Embedding Classical Variational Methods in Quantum Circuits".

Download the code

You can download all the code present in this repository by going to the directory in which you want to save it and execute

git clone https://github.com/StefanoBarison/hybrid_ansatz.git

Libraries installation

The simulations are performed in Python using Netket library to create the classical model (might it be a simple mean field ansatz or a Neural Quantum State) and Pennylane for the quantum circuits. Once you are in the downloaded directory you can install all the required packages by executing

pip install -r requirements.txt

Repository content

• code: contains the code to perform quantum-classical embedded calculations

  • hamiltonian.py: functions to create the Hamiltonians in Netket and Pennylane, loading terms from a file or from a list
  • quantum_circuits.py: variational circuits used in the experiments, see the manuscript for more details
  • classic_models.py: code for the classic models used, from the mean field approximations to RBMs
  • utils.py: contains all the functions to compute the quantum overlaps and the Monte-Carlo expectation values, see the manuscript for more details
  • truncated_spin.py: a custom Netket Hilbert space that samples configurations only in a given range of particles
  • cx.py: a custom Pennylane gate to initialise the particle-preserving quantum circuit and perform Hadamard tests if required

  Moreover, two Jupyter notebooks are included, containing example calculations on the Ising model and on the ammonia molecule.

• data: contains the results of the calculations on the Ising model and on the ammonia molecule, used to produce the plot in the paper

• plots: the plots presented in the main text of the paper and in the supplementary material