We have recently developed a new Monte Carlo (MC) code to follow the
long term evolution of galactic
nuclei (Freitag &
Benz, 2002; Freitag
& Benz, 2001; Freitag,
2001). This tool is based on the scheme
first proposed by Hénon (Hénon,
1973) to simulate globular clusters
but, in addition to relaxation, it also includes collisions, tidal
disruptions, stellar evolution and captures. The MC technique assumes
that the cluster is spherically symmetric and represents it as a set
of particles, each of which may be considered as a homogeneous
spherical shell of stars sharing the same orbital and stellar
properties. The number of simulated stars may be larger than the
number of particles, provided the number of stars per particle is
constant. Another important assumption is that the system is always in
dynamical equilibrium so that orbital time scales need not be resolved
and the natural time-step is a fraction of the relaxation (or
collision) time. The relaxation is treated as a diffusive
process (Binney & Tremaine, 1987).
The MC code offers a unique combination of
physical realism (collisions, mass segregation, velocity
anisotropy...are easily taken into account) and computational
efficiency (
),
compared to
for direct
-body codes) which allows
Hubble-time simulations to be carried on standard PCs with
multi-million particle resolution.
We assume that a star is irremediably captured by the MBH if it gets
on an orbit with a time scale for shrinkage by emission of
gravitational radiation (Peters, 1964)
shorter than the time over which 2-body relaxation could significantly
modify the pericenter distance (Ivanov, 2002; Sigurdsson & Rees, 1997),
.
is
the usual relaxation time (Binney &
Tremaine, 1987) and
is the angle between the trajectory and the direction
to the
centre.
We concentrate here on a model set to represent the nucleus of the
Milky Way (Genzel et al., 2000),
with a central BH of mass and a total mass in stars of
. A stellar population with a broad
mass
spectrum (Kroupa, 2001) is assumed.
There is no initial mass
segregation. The number of particles is
.