Allow to train for a different target Gibbs state

CQCL / qbm_benchmark_dataset

A simple python package to benchmark Quantum Boltzmann Machine models using Stochastic Gradient Descent. Based on the quantum many-body physics package `quimb`

Apache License 2.0

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Allow to train for a different target Gibbs state #17

Closed erinaldiq closed 8 months ago

erinaldiq commented 8 months ago

The current benchmark script is only targeting the TFIM Hamiltonian with fixed inverse temperature.

We would like to allow to train QBMs for different target states.

erinaldiq commented 8 months ago

This will be closed by merging #18