Treffer: sakidja/quantum_bath: Quantum Bath Simulation (v1.0.1)

This release accompanies the forthcoming arXiv submission: "Structured Quantum Baths with Memory: A QuTiP Framework for Spectral Diagnostics and Machine Learning Inference." (ArXiv link will be added after announcement.) What's inside Jupyter notebook: QuTiP_Quantum_Bath.ipynb Structured multi-qubit bath models with thermal Lindblad dissipators Diagnostics: entropy, fidelity, populations, entanglement, trace-distance backflow FFT-based spectral analysis and optional ML inference (PCA + XGBoost) Automatic archival of each run into timestamped ZIPs (single & multi-run modes) Why it matters This workflow offers a hands-on, transparent way to probe memory flow and non-Markovianity for quantum control, dissipation engineering, and error mitigation—using lightweight, reproducible tools. Getting started Environment # Conda (recommended) conda env create -f environment.yml conda activate qbath # or pip python -m venv .venv source .venv/bin/activate # Windows: .venv\Scripts\activate pip install -r requirements.txt