The goal of this paper is to push forward the study of those properties of log-concave measures that help to estimate their Poincar{ \'e} constant. First we revisit E. Milman's result [40] on the link between weak (Poincar{ \'e} or concentration) inequalities and Cheeger's inequality in the logconcave cases, in particular extending localization ideas and a result of Latala, as well as providing a simpler proof of the nice Poincar{ \'e} (dimensional) bound in the inconditional case. Then we prove alternative transference principle by concentration or using various distances (total variation, Wasserstein). A mollification procedure is also introduced enabling, in the logconcave case, to reduce to the case of the Poincar{ \'e} inequality for the mollified measure. We finally complete the transference section by the comparison of various probability metrics (Fortet-Mourier, bounded-Lipschitz,...).
Categories: math.PR math.FA