物理信息代理模型模拟 p-n 结二极管，附不确定性分析
A physics-informed uncertainty-aware surrogate for $p$-$n$ junction diodes
用物理信息神经网络替代二极管仿真，静电势误差只有0.11%，还自带不确定性评估，做器件仿真的可以看看。
论文针对一维 p-n 结二极管构建了物理信息代理模型，条件输入包括器件长度、掺杂和偏置。在静电势上取得 0.11% 的中位 L1 误差，电子与空穴密度误差分别为 1.5% 和 0.61%。代理模型可输出端电流、耗尽区宽度、峰值电场与存储电荷等量，并通过基准分析扩展到非对称结和二维二极管。文中还提出不确定性分析框架，可在用户指定容差内判断代理模型结果的有效性。
A physics-informed uncertainty-aware surrogate for $p$-$n$ junction diodes
We develop an uncertainty-aware physics-informed surrogate for a one-dimensional $p$-$n$ junction diode, conditioned on device length, doping and bias. Using the internal state of the device as predicted by the surrogate we develop a test-suite of quantities of interest including the terminal current, depletion width, peak field and stored charge. The formalism and the quantities are can be extended to asymmetric junction and two-dimensional diodes as shown by means of benchmark analysis. For the one-dimensional symmetric junction surrogate, we obtain 0.11% median $L_1$ error on the electrostatic potential, and 1.5% and 0.61% on the electron and hole densities. Finally, we develop an uncertainty analysis which determines the validity of surrogate answer within the user-specified tolerance.