Public scientific and metrology releases can leak the hidden settings that produced them. We formalize and quantify this risk as a profiled statistical side-channel audit: a release map exposes finite-band statistics of a power spectral density (PSD), a profiled observer trains labeled template spectra under an explicit budget, and a challenge release is drawn from one of two utility-equivalent recipes separated by a protected coordinate. Averaged PSD bins follow a gamma channel, replaced by a covariance-weighted log-spectrum channel when the bins are correlated; this yields exact Kullback-Leibler divergences, Chernoff exponents, protected-bit advantage bounds, and finite-training, finite-library, finite-compute, and model-mismatch corrections. Our headline result is a finite-band transport-leakage law: after amplitude and blur are eliminated, the protected acid-transport information obeys $I_{λ|α,β}(K) = (64/1225)\, w λ^{6} K^{9} + O(w λ^{8} K^{11})$ for $Kλ\ll 1$, a ninth-order exponent with a closed-form safe band. A step-by-step protocol turns a measured release into these numbers, and a fixed-seed reproducibility package regenerates every table and figure. We instantiate the audit on screened extreme-ultraviolet (EUV) roughness spectra as a model-conditioned case study, with deployment on measured releases the next step.

翻译：公共科学和计量发布可能泄露产生它们的隐藏设置。我们将这种风险形式化并量化为一种剖析式统计侧信道审计：发布映射暴露了功率谱密度（PSD）的有限带宽统计量，剖析观测者在明确预算下训练带标签的模板谱，挑战发布则从由受保护坐标区分的两个效用等价的配方中随机抽取。平均PSD分箱遵循伽马信道，当分箱存在相关性时，该信道被协方差加权对数谱信道替代；这导出了精确的Kullback-Leibler散度、Chernoff指数、受保护比特优势界以及有限训练、有限库、有限计算和模型失配修正。我们的核心结果是有限带宽传输泄露定律：在消除幅度和模糊之后，受保护酸传输信息满足 $I_{λ|α,β}(K) = (64/1225)\, w λ^{6} K^{9} + O(w λ^{8} K^{11})$，其中 $Kλ\ll 1$，这是一个九阶指数且具有封闭形式的安全带。逐步协议可将测量发布转化为这些数值，而固定种子的可重复性包可重新生成所有表格和图表。我们将该审计实例化于筛选的极紫外（EUV）粗糙度谱上作为模型条件案例研究，下一步则是在测量发布上进行部署。