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 $ν$ and squeezing $r$, the fixed-diffusion Wigner-score (Bayes) reverse drift violates CP iff $\cosh(2r)>ν$. Any Gaussian CP repair must inject extra diffusion, implying $-2\ln F\ge c_{\text{geom}}(ν_{\min})I_{\mathrm{dec}}^{\mathrm{wc}}$.

翻译：基于扩散的生成建模建议通过添加得分漂移来反转噪声半群。对于连续变量高斯马尔可夫动力学，完全正性在生成元层面耦合了漂移与扩散。对于热参数为$ν$、压缩参数为$r$的量子极限衰减器，固定扩散的维格纳-得分（贝叶斯）反向漂移违反完全正性当且仅当$\cosh(2r)>ν$。任何高斯完全正性修正都必须注入额外扩散，这意味着$-2\ln F\ge c_{\text{geom}}(ν_{\min})I_{\mathrm{dec}}^{\mathrm{wc}}$。