A Design Space Study of Density Matrix Parameterizations for Diffusion-Based Quantum State Tomography

arXiv:2608.09625 · quant-ph, math-ph, math.MP · Submitted 2026-08-10 · Read on arXiv

quant-ph, math-ph, math.MP

Submitted: 2026-08-10

Updated: 2026-09-19

Code: https://github.com/csjnb/DM-QST-EDM

Terminology

• Fidelity — 61× in this paper · explained in 2 episodes
• Trace — 59× in this paper · explained in 2 episodes
• Calibration — 43× in this paper · explained in 7 episodes
• Diffusion Model — 15× in this paper · explained in 8 episodes
• Diffusion Models — 13× in this paper · explained in 6 episodes
• Anisotropy — 8× in this paper · explained in 3 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Diagonal Anisotropy — 4× in this paper
• Generative Model — 4× in this paper · explained in 2 episodes
• Process tomography — 4× in this paper · explained in 2 episodes
• Quantum Circuits — 4× in this paper · explained in 2 episodes
• Flow Matching — 3× in this paper · explained in 7 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Physical Constraints — 3× in this paper · explained in 7 episodes
• Spectral Dynamic Range — 3× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Fisher Information — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Berry Curvature — 1× in this paper · explained in 3 episodes
• Entanglement — 1× in this paper · explained in 3 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Hamiltonian Learning — 1× in this paper · explained in 2 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 1× in this paper
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Quantum Geometric Tensor (QGT) — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• The diagonal of the multiplihedra and the tensor product of A-infinity morphisms
• Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection
• Classifier-Free Diffusion Guidance
• A joint Bayesian hierarchical model for estimating SARS-CoV-2 diagnostic and subgenomic RNA viral dynamics and seroconversion
• Learning Asymmetric Embedding for Attributed Networks via Convolutional Neural Network
• Flow Matching for Generative Modeling
• Experimental evidence for bounds on quantum correlations

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