NaturalGradientQBM

This repository contains collaborative work on using Natural Gradient methods for training Quantum Boltzmann Machines (QBMs), with the goal of estimating the ground-state energies of Hamiltonians.

📦 Structure

src/ → source code modules
examples/ → Jupyter notebooks for experiments and demos
results/ → saved plots and outputs
tests/ → optional unit tests (future)
docs/ → documentation (future)

⚙️ Environment setup

This project uses uv for Python environment management.

# 1. Install uv (if not already installed)
pip install uv

# 2. Clone the repository
git clone git@github.com:Michele-Minervini/NaturalGradientQBM.git
cd NaturalGradientQBM

# 3. Initialize environment
uv init

# 4. Create environment
uv sync

Activate the environment (VSCode usually detects it automatically).

🧠 Running examples

You can open the notebooks in examples/ using Jupyter or VSCode's notebook interface.

👥 Contributors

• Michele Minervini (Michele-Minervini)

• Lucas De Venecia (ldevenecia)

• Madison Chin (mc2933)