A Jacobian Gram matrix framework quantifies how seven density-matrix parameterizations affect diffusion-based quantum state tomography, showing isometry and constraint satisfaction are competing and that conditioning alone does not predict end-to-end performance.
Elucidating the design space of diffusion-based generative models (EDM).Advances in Neural Information Processing Systems (NeurIPS), 35, 2022
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A Design Space Study of Density Matrix Parameterizations for Diffusion-Based Quantum State Tomography
A Jacobian Gram matrix framework quantifies how seven density-matrix parameterizations affect diffusion-based quantum state tomography, showing isometry and constraint satisfaction are competing and that conditioning alone does not predict end-to-end performance.