In this publication, we demonstrate the extension of our loss-less library approach previously limited to fitting ro-vibrational N₂ CARS spectra for thermometry purposes to accurate and efficient fitting of dual-pump CARS spectra with multiple species. The fundamental reasoning behind the compression approach is to make use of finite resolution effects arising from the laser linewidths, which are typically larger than the transitional linewidths. For accurate reconstruction at runtime of the fit, in addition to the squared modulus and real component, also the imaginary component as well as intra-region species cross terms have to be compressed and tabulated for dual-pump multi-species spectra. The resulting libraries do not require to tabulate combinations of mole fractions, leading to a near linear growth of the library with respect to the number of species. The accuracy and computational efficiency of the method is benchmarked using a reference implementation provided alongside this publication. Library generation times, mainly depending on the underlying spectral model, are typically in the order of seconds to a few minutes. The simulation of a single dual-pump spectrum containing three species is sped up by a factor of >5000 without significantly affecting the accuracy of reconstruction. In a simulated experiment with Stokes-noise imposed data, the time required to it temperature, mole fraction of three resonant species and wavenumber shift on a single spectrum required $$90 ms.

中文翻译：

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CARS.jl：使用压缩库高效拟合双泵多物种 CARS 谱

在本出版物中，我们展示了无损库方法的扩展，之前仅限于拟合用于测温目的的旋转振动 N ₂ CARS 光谱，以准确有效地拟合多个物种的双泵 CARS 光谱。压缩方法背后的基本原理是利用激光线宽产生的有限分辨率效应，激光线宽通常大于过渡线宽。为了在拟合运行时准确重建，除了平方模量和实部之外，还必须对双泵多物种光谱压缩虚部以及区域内物种交叉项并制成表格。所得文库不需要将摩尔分数的组合制成表格，从而导致文库相对于物种数量近乎线性增长。该方法的准确性和计算效率使用本出版物随附的参考实现进行基准测试。库生成时间主要取决于底层光谱模型，通常为几秒到几分钟。包含三个物种的单个双泵光谱的模拟速度提高了 >5000 倍，而不会显着影响重建的准确性。在使用斯托克斯噪声施加数据的模拟实验中，温度、三种共振物质的摩尔分数和单个光谱上的波数偏移所需的时间$$90 毫秒