  Hamiltonian Flow Monte Carlo(HFMC) methods have been implemented in
engineering, biology and chemistry. HFMC makes large gradient based steps to
rapidly explore the state space. The application of the Hamiltonian dynamics
allows to estimate rare events and sample from target distributions defined as
the change of measures. The estimates demonstrated a variance reduction of the
presented algorithm and its efficiency with respect to a standard Monte Carlo
and interacting particle based system(IPS). We tested the algorithm on the case
of the barrier option pricing.
