We prefer to fit data in the original measurement domain, which is (τ 1 , T w , ω 3 ). Therefore, our model requires a Fast Fourier Transform (FFT) along the probe axis. The FFT assumes equal spacing along the probe axis, but, due to the spectrograph, our experimental data points are nonlinearly spaced along the probe axis. Therefore, to match the data and model in Eq. 1, users should preprocess the data by interpolating along a linear probe axis. This is a straightforward task using the spline function in MATLAB. The GUI version of our program does this automatically when loading data. Time domain data are commonly padded by an equal number of zeros just prior to the Fourier Transform to enforce causality, which we call causal zero-padding. We refer to zero padding beyond this point as superfluous, but it is a common practice to interpolate the data in the frequency domain. More precisely, this approach results in sinc interpolation in the frequency domain. Sinc ringing is nearly always mitigated by choosing a non-rectangular windowing function to make the data smoothly taper to zero prior to zero padding. Both superfluous zero padding and apodization manipulate data in different ways, and these perturbations will propagate into the fitting results. In fact, assuming the true parameters are known, the change in fitting parameters d𝐩𝐩 due to a perturbation in data 𝐝𝐝𝐃𝐃 is computed by Eq. S10. Therefore, we generally recommend fitting data in the original measurement domain without causal or superfluous zero padding, or apodization. When this is not an option, the data should be transformed back into the original measurement domain and the non-rectangular apodization window inverted to retrieve the original data. Careful consideration is needed when constructing the inverse window function (1) to avoid divide by zero or near divide by zero and (2) whether the original filter had ½ scaling of the DC component, which is common practice. Data are collected using a pulse shaper which ensures accurate phasing of all 2D IR spectra, though we have added an optional fitting parameter to account for a uniform zero order phasing error across all spectra. Results of model fitting to simulated data with phasing errors are provided in supporting information section G.