Research PaperResearchia:202603.10067[Data Science > Machine Learning]
Quantum Diffusion Models: Score Reversal Is Not Free in Gaussian Dynamics
Ammar Fayad
Abstract
Diffusion-based generative modeling suggests reversing a noising semigroup by adding a score drift. For continuous-variable Gaussian Markov dynamics, complete positivity couples drift and diffusion at the generator level. For a quantum-limited attenuator with thermal parameter and squeezing , the fixed-diffusion Wigner-score (Bayes) reverse drift violates CP iff . Any Gaussian CP repair must inject extra diffusion, implying .
Source: arXiv:2603.06488v1 - http://arxiv.org/abs/2603.06488v1 PDF: https://arxiv.org/pdf/2603.06488v1 Original Link: http://arxiv.org/abs/2603.06488v1
Submission:3/10/2026
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Subjects:Machine Learning; Data Science
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Researchia:202603.10067https://www.researchia.net/explorer/369bb08c-41cb-4b74-8d86-f9135b066d2b
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arXiv: This paper is hosted on arXiv, an open-access repository
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