def cluster_init(N, mMin, mMax, alpha, mCluster, rCluster):
converter = nbody_system.nbody_to_si(mCluster, rCluster)
cluster = new_plummer_model(N, convert_nbody=converter)
mZAMS = new_powerlaw_mass_distribution(N, mMin, mMax, alpha)
cluster.mass = mZAMS
cluster.scale_to_standard(converter)
return cluster
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
R_galaxy = 0.1 | units.kpc
M_galaxy = 1.6e10 | units.MSun
converter = nbody_system.nbody_to_si(M_galaxy, R_galaxy)
galaxy = new_plummer_model(10000, convert_nbody=converter)
print "com:", galaxy.center_of_mass().in_(units.kpc)
print "comv:", galaxy.center_of_mass_velocity().in_(units.kms)
print len(galaxy)
galaxy_code = BHTree(converter, number_of_workers=2)
galaxy_code.parameters.epsilon_squared = (0.01 | units.kpc)**2
channe_to_galaxy = galaxy_code.particles.new_channel_to(galaxy)
channe_to_galaxy.copy()
galaxy_code.particles.add_particles(galaxy)
inner_stars = galaxy.select(lambda r: r.length() < Rinit, ["position"])
Minner = inner_stars.mass.sum()
print "Minner=", Minner.in_(units.MSun)
print "Ninner=", len(inner_stars)
vc_inner = (constants.G * Minner / Rinit).sqrt()
converter = nbody_system.nbody_to_si(Mcluster, Rcluster)
stars = new_king_model(N, W0, convert_nbody=converter)
masses = new_powerlaw_mass_distribution(N, 0.1 | units.MSun,
100 | units.MSun, -2.35)
stars.mass = masses
stars.scale_to_standard(converter)
stars.x += Rinit
stars.vy += 0.8 * vc_inner
cluster_code = ph4(converter, number_of_workers=2)
cluster_code.particles.add_particles(stars)
channel_to_stars = cluster_code.particles.new_channel_to(stars)
system = bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code, ))
system.add_system(galaxy_code, (cluster_code, ))
system.timestep = 0.1 * timestep
times = quantities.arange(0 | units.Myr, tend, timestep)
for i, t in enumerate(times):
print "Time=", t.in_(units.Myr)
channe_to_galaxy.copy()
channel_to_stars.copy()
inner_stars = galaxy.select(lambda r: r.length() < Rinit, ["position"])
print "Minner=", inner_stars.mass.sum().in_(units.MSun)
system.evolve_model(t, timestep=timestep)
plot_galaxy_and_stars(galaxy, stars)
galaxy_code.stop()
cluster_code.stop()
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
R_galaxy=0.1 | units.kpc
M_galaxy=1.6e10 | units.MSun
converter=nbody_system.nbody_to_si(M_galaxy, R_galaxy)
galaxy=new_plummer_model(10000,convert_nbody=converter)
print "com:", galaxy.center_of_mass().in_(units.kpc)
print "comv:", galaxy.center_of_mass_velocity().in_(units.kms)
print len(galaxy)
galaxy_code = BHTree(converter, number_of_workers=2)
galaxy_code.parameters.epsilon_squared = (0.01 | units.kpc)**2
channe_to_galaxy = galaxy_code.particles.new_channel_to(galaxy)
channe_to_galaxy.copy()
galaxy_code.particles.add_particles(galaxy)
inner_stars = galaxy.select(lambda r: r.length()<Rinit,["position"])
Minner = inner_stars.mass.sum()
print "Minner=", Minner.in_(units.MSun)
print "Ninner=", len(inner_stars)
vc_inner = (constants.G*Minner/Rinit).sqrt()
converter=nbody_system.nbody_to_si(Mcluster,Rcluster)
stars=new_king_model(N,W0,convert_nbody=converter)
masses = new_powerlaw_mass_distribution(N, 0.1|units.MSun, 100|units.MSun, -2.35)
stars.mass = masses
stars.scale_to_standard(converter)
stars.x += Rinit
stars.vy += 0.8*vc_inner
cluster_code=ph4(converter, number_of_workers=2)
cluster_code.particles.add_particles(stars)
channel_to_stars=cluster_code.particles.new_channel_to(stars)
system=bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code,))
system.add_system(galaxy_code, (cluster_code,))
system.timestep = 0.1*timestep
times = quantities.arange(0|units.Myr, tend, timestep)
for i,t in enumerate(times):
print "Time=", t.in_(units.Myr)
channe_to_galaxy.copy()
channel_to_stars.copy()
inner_stars = galaxy.select(lambda r: r.length()<Rinit,["position"])
print "Minner=", inner_stars.mass.sum().in_(units.MSun)
system.evolve_model(t,timestep=timestep)
plot_galaxy_and_stars(galaxy, stars)
galaxy_code.stop()
cluster_code.stop()
def make_galaxy_model(N, M_galaxy, R_galaxy, Mmin, Mmax):
converter = nbody_system.nbody_to_si(M_galaxy, R_galaxy)
n_halo = 0
n_bulge = 0
n_disk = N
galaxy = new_galactics_model(n_halo,
converter,
do_scale=True,
bulge_number_of_particles=n_bulge,
disk_number_of_particles=n_disk)
from amuse.lab import new_powerlaw_mass_distribution
masses = new_powerlaw_mass_distribution(len(galaxy), Mmin, Mmax, -2.0)
galaxy.mass = masses
galaxy.radius = 10 | units.parsec
galaxy.King_W0 = 3
return galaxy
def generate_power_law_mass_function(N, Mmin, Mmax, ximf):
masses = new_powerlaw_mass_distribution(N, Mmin, Mmax, ximf)
plot_mass_function(masses, ximf)
def generate_power_law_mass_function(N, Mmin, Mmax, ximf):
masses = new_powerlaw_mass_distribution(N, Mmin, Mmax, ximf)
plot_mass_function(masses, ximf)