发表机构
Proxima Fusion GmbH; Max Planck Institute for Plasma Physics（普罗克西玛聚变有限公司; 马克斯·普朗克等离子体物理研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出PQLS准线性陀螺动力学输运求解器，采用贝叶斯推断校准饱和规则，量化不确定性并提高预测鲁棒性，与非线性模拟结果高度一致。
AI 中文摘要
准线性模型使陀螺动力学湍流输运预测足够快，适用于集成建模，但其预测能力受两个因素限制：线性求解器的物理和几何适用性，以及用于闭合模型的饱和规则的有效性。我们提出了预测性准线性求解器（PQLS），一种在一般磁几何中表述的准线性陀螺动力学输运求解器。其作为特征值求解器的实现保留了电磁和碰撞效应，提供对主模和次主模的访问，并且对所有等离子体参数可微。与GENE的线性基准测试重现了增长率、频率和本征函数。我们还将饱和规则闭合表述为贝叶斯推断问题，该问题区分了其拟合系数中的不确定性来自残差模型形式的不确定性。该方法通过在PQLS准线性权重上校准SAT3规则，并与已发表的非线性CGYRO案例进行对比来展示。除了提高校准的鲁棒性外，新方法还量化了每个拟合系数的不确定性。这种不确定性通过输运计算传播，产生具有误差感知的剖面，并与从完整陀螺动力学模拟获得的剖面进行比较，显示出极好的一致性。
英文摘要
Quasilinear models make gyrokinetic turbulent-transport predictions sufficiently fast for integrated modelling, but their predictive capability is limited by two factors: the physical and geometrical applicability of the linear solver, and the validity of the saturation rule used to close the model. We present the Predictive Quasilinear Solver (PQLS), a quasi- linear gyrokinetic transport solver formulated in general magnetic geometry. Its implementation as an eigenvalue solver retains electromagnetic and collisional effects, provides access to dominant and subdominant modes and is differen- tiable with respect to all plasma parameters. Linear benchmarks against GENE reproduce the growth rates, frequencies, and eigenfunctions. We additionally formulate the saturation-rule closure as a Bayesian inference problem that distin- guishes uncertainty in its fitted coefficients from the residual model-form uncertainty. The approach is demonstrated by calibrating the SAT3 rule on PQLS quasilinear weights against published nonlinear CGYRO cases. In addition to improving the robustness of the calibration, the new method also quantifies the uncertainty in each of the fit coefficients. Such uncertainty is propagated through transport calculations to produce error-aware profiles that are compared to the ones obtained from the full gyrokinetic simulation, showing excellent agreement.
