  Dynamic density-matrix renormalization provides valuable numerical
information on dynamic correlations by computing convolutions of the
corresponding spectral densities. Here we discuss and illustrate how and to
which extent such data can be deconvolved to retrieve the wanted spectral
densities. We advocate a nonlinear deconvolution scheme which minimizes the
bias in the ansatz for the spectral density. The procedure is illustrated for
the line shape and width of the Kondo peak (low energy feature) and for the
line shape of the Hubbard satellites (high energy feature) of the single
impurity Anderson model. It is found that the Hubbard satellites are strongly
asymmetric.
