Results of the single-Gaussian simulation tests. From top to bottom: reconstructions of simulated Gaussian ξ(Τ) profiles by means of the basis pursuit (BP) technique (Cheung et al. 2015), the FIR inversion method of Plowman et al. (2013), the iterative SITES technique (Morgan & Pickering 2019), the regularization technique of Hannah & Kontar (2012, REG), the ML method defined in Eq. (18), and finally our proposed RML technique. The black solid lines represent the “ground truth” configurations, which are all Gaussian functions of log₁₀ Τ with total Emission Measure EM = ∫ ξ(Τ)dT = 10²⁸ cm⁻⁵ and standard deviation equal to 0.15 dex. From left to right, the centroid temperatures are given by log₁₀ T_c = 6.1, 6.2, 6.3, and 6.4. The gray lines represent the reconstructions from 25 different realizations of Poisson-noise-perturbed data; the red lines represent the mean values of these 25 reconstructions. The ξ(Τ) profiles are plotted as a function of the (base 10) logarithm of the temperature (K), so that the peak value of each Gaussian is inversely proportional to 10^x, where x is the abscissa.