This project implements a machine learning model capable of reconstructing a quantum density matrix ρ from measurement data (Classical Shadows). The model enforces strict physical constraints (Hermitian, Positive Semi-Definite, Unit Trace) using a Cholesky decomposition approach.
deep-learning neural-network pytorch transformer quantum-computing qiskit cholesky-decomposition quantum-state-tomography quantum-information-theory density-matrix quantum-state-reconstruction shadow-tomography classical-shadows machine-learning-physics quantum-fidelity
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Updated
Jan 15, 2026 - Jupyter Notebook