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In this paper, a recently developed numerical technique [{\em Tuncer E andGuba{\'n}ski S M, IEEE Trans Diel El Insul {\bf 8}(3)(2001) 310-320}] isapplied to poly(propylene glycol) complex dielectric data to extract moreinformation about the molecular relaxation processes. The method is based on aconstrained-least-squares (\clsq) data fitting procedure together with theMonte Carlo (\mc) method. We preselect the number of relaxation times with no{\em a-priori} physical assumption, and use the Debye single relaxation as``kernel'', then the obtained weighting factors at each \mc step from the \clsqmethod builds up a relaxation time spectrum. When the analysis is repeated fordata at different temperatures a {\em relaxation-image} is created. Theobtained relaxation are analyzed using the Lorentz (Cauchy) distribution, whichis a special form of the L{\'e}vy statistics. In the present report the $\beta$and $\alpha$ relaxations are resolved for the \ppg. A comparison of therelaxations to those earlier reported in the literature indicate that thepresented method provides additional information compared to methods based onempirical formulas. The distribution of relaxation times analysis is especiallyuseful to probe the crossover region where the $\alpha$- and $\beta$-relaxations merge and the results show that the relaxation after the crossoverregion at higher temperatures is Arrhenius-type as the $\beta$-relaxation.Moreover, this relaxation is more likely to be the continuation of the$\beta$-relaxation, but with a different activation energy.Comment: 11 pages 11 figures and 2 table

Resolving distribution of relaxation times in poly(propylene glycol) on the crossover region