  Stars of low and intermediate mass that exhibit oscillations may show tens of
detectable oscillation modes each. Oscillation modes are a powerful to
constrain the internal structure and rotational dynamics of the star, hence
tool allowing one to obtain an accurate stellar age. The tens of thousands of
solar-like oscillators that have been discovered thus far are representative of
the large diversity of fundamental stellar properties and evolutionary stages
available. Because of the wide range of oscillation features that can be
recognized in such stars, it is particularly challenging to properly
characterize the oscillation modes in detail, especially in light of large
stellar samples. Overcoming this issue requires an automated approach, which
has to be fast, reliable, and flexible at the same time. In addition, this
approach should not only be capable of extracting the oscillation mode
properties of frequency, linewidth, and amplitude from stars in different
evolutionary stages, but also able to assign a correct mode identification for
each of the modes extracted. Here we present the new freely available pipeline
FAMED (Fast and AutoMated pEak bagging with DIAMONDS), which is capable of
performing an automated and detailed asteroseismic analysis in stars ranging
from the main sequence up to the core-Helium-burning phase of stellar
evolution. This, therefore, includes subgiant stars, stars evolving along the
red giant branch (RGB), and stars likely evolving toward the early asymptotic
giant branch. In this paper, we additionally show how FAMED can detect rotation
from dipolar oscillation modes in main sequence, subgiant, low-luminosity RGB,
and core-Helium-burning stars. FAMED can be downloaded from its public GitHub
repository (https://github.com/EnricoCorsaro/FAMED).
