Figure shows the normalized plots of singular values that are obtained by applying the standard PCA and wPCA on the observed data along with results by applying wPCA on the preliminarily denoised data using the moving average, the 1D Gaussian smoothing, and the proposed method considering both the smoothness of the spectra and low-rankness, respectively. The scree plot obtained by applying wPCA after the preliminary noise reduction indicates that there are three components. This is as expected from the sample's known composition. In contrast, the other plots indicate two components. This suggests that the proposed spectral smoothing got the data closer to the underlying low-dimensional subspace, while the other methods are affected by the correlated signals under heavy noise. We then fixed the number of components to three in the following experiments.