  We propose an adaptive scheme of broadening the discrete spectral data from
numerical renormalization group (NRG) calculations to improve the resolution of
dynamical properties at finite energies. While the conventional scheme
overbroadens narrow features at large frequency by broadening discrete weights
with constant width in log-frequency, our scheme broadens each discrete
contribution individually based on its sensitivity to a z-shift in the
logarithmic discretization intervals. We demonstrate that the adaptive
broadening better resolves various features in non-interacting and interacting
models at comparable computational cost. The resolution enhancement is more
significant for coarser discretization as typically required in multi-band
calculations. At low frequency below the energy scale of temperature, the
discrete NRG data necessarily needs to be broadened on a linear scale. Here we
provide a method that minimizes transition artefacts in between these
broadening kernels.
