  Jets with a large radius $R\gtrsim 1$ and grooming algorithms are widely used
to fully capture the decay products of boosted heavy particles at the Large
Hadron Collider (LHC). Unlike most discriminating variables used in such
studies, the jet radius is usually not optimized for specific physics
scenarios. This is because every jet configuration must be calibrated, insitu,
to account for detector response and other experimental effects. One solution
to enhance the availability of large-$R$ jet configurations used by the LHC
experiments is {\it jet re-clustering}. Jet re-clustering introduces an
intermediate scale $r<R$ at which jets are calibrated and used as the inputs to
reconstruct large radius jets. In this paper we systematically study and
propose new jet re-clustering configurations and show that re-clustered large
radius jets have essentially the same jet mass performance as large radius
groomed jets. Jet re-clustering has the benefit that no additional large-R
calibration is necessary, allowing the re-clustered large radius parameter to
be optimized in the context of specific precision measurements or searches for
new physics.
