  Collimated streams of particles produced in high energy physics experiments
are organized using clustering algorithms to form jets. To construct jets, the
experimental collaborations based at the Large Hadron Collider (LHC) primarily
use agglomerative hierarchical clustering schemes known as sequential
recombination. We propose a new class of algorithms for clustering jets that
use infrared and collinear safe mixture models. These new algorithms, known as
fuzzy jets, are clustered using maximum likelihood techniques and can
dynamically determine various properties of jets like their size. We show that
the fuzzy jet size adds additional information to conventional jet tagging
variables. Furthermore, we study the impact of pileup and show that with some
slight modifications to the algorithm, fuzzy jets can be stable up to high
pileup interaction multiplicities.
