I'm attempting to apply some line broadening to a data set (made up of energy values (x) and transition probabilities (y)), and I'd like to apply a Gaussian broadening on the order of 5 meV to the set.
My thought on doing this was to apply DiscreteConvolve, but I can't seem to create a Gaussian kernel that is a set of x and y data points (DiscreteConvolve seems to only work with the y values, and ignores the x values, using the row index instead). Ideally, with such a convolution (and a properly normalized Gaussian kernel), the area underneath the two curves would remain the same as well.
Since I can't get the DiscreteConvolve function to account for the x (energy) value on the kernel, doing a normalization only compounds my second issue, which is that the intensity of the convoluted output is much larger than the input data. Can someone point me in the right direction? I've attached a sample data notebook, let me know if any clarification is needed.
Attachment: Sample broadening.nb, URL: ,