def plot_klf_with_jwst():
"""
Plot up a simulated KLF for the young star cluster at the Galactic Center
and show spectroscopic and photometric detections today with Keck and in the
future with TMT.
"""
from jlu.gc.imf import bayesian as b
fitAlpha = 1.7
fitAge = 3.9e6
fitMcl = 9.2e3
fitDist = 7900
fitLogAge = math.log10(fitAge)
theAKs = 2.7
distance = 8000.0
# Use our best fit IMF for 0.5 - 150 Msun
# Use Weidner_Kroupa_2004 IMF between 0.1 - 0.5 Msun
# Stop at 0.1 Msun as we don't have evolution models below that mass.
massLimits = np.array([0.1, 0.5, 150])
powers = np.array([-1.3, -fitAlpha])
Mcl1 = 3.4e4
Mcl2 = 3.0e4
cluster1 = b.model_young_cluster_new(fitLogAge, massLimits=massLimits,
imfSlopes=powers, clusterMass=Mcl1,
makeMultiples=True,
AKs=theAKs, distance=distance)
Mcl1_1_150 = cluster1.systemMasses[cluster1.mass >= 1].sum()
Mcl1_01_1 = cluster1.systemMasses[cluster1.mass < 1].sum()
print 'Cluster with multiples:'
print ' Total Cluster Mass = %d' % Mcl1
print ' Mass [1 - 150] Msun = %d' % Mcl1_1_150
print ' Mass [0.1 - 1] Msun = %d' % Mcl1_01_1
# Assign arbitrary magnitudes for WR stars. Uniformly distributed from Kp=9-11
idx = np.where(cluster1.isWR == True)[0]
cluster1.mag[idx] = 9.0 + (np.random.rand(len(idx))*2)
# Plot the mass luminosity relationship
py.clf()
py.semilogy(cluster1.mag, cluster1.mass, 'k.', ms=2, label="Multiples")
py.xlabel('Kp Magnitude')
py.ylabel('Stellar Mass (Msun)')
py.savefig('jwst_mass_luminosity.png')
kbins = np.arange(9.0, 24, 0.5)
# Plot the KLF
py.clf()
py.hist(cluster1.mag, bins=kbins, histtype='step', linewidth=2, label='Multiples')
py.gca().set_yscale('log')
py.xlabel('Kp Magnitude')
py.ylabel('Number of Stars')
py.title('Galactic Center Young Cluster')
py.xlim(9, 28)
py.ylim(1, 1e4)
rng = py.axis()
py.axvline(15.5, color='black', linestyle='--', linewidth=2)
py.text(15.6, 6e3, r'13 M$_\odot$', horizontalalignment='center')
ar1 = FancyArrow(15.5, 1e3, -1, 0, width=1e2, color='black', head_length=0.3)
py.gca().add_patch(ar1)
py.text(15.3, 7e2, 'Keck\nSpectra', horizontalalignment='right', verticalalignment='top')
py.axvline(21, color='black', linestyle='-', linewidth=2)
py.text(21.0, 6e3, r'0.4 M$_\odot$', horizontalalignment='center')
ar1 = FancyArrow(21, 4e3, -1, 0, width=4e2, color='black', head_length=0.3)
py.gca().add_patch(ar1)
py.text(20.8, 3e3, 'TMT\nSpectra', horizontalalignment='right', verticalalignment='top')
ar1 = FancyArrow(17.8, 10, 0, 13, width=0.1, color='blue', head_length=10)
py.gca().add_patch(ar1)
py.text(18, 9, 'Pre-MS\nTurn-On', color='blue',
horizontalalignment='center', verticalalignment='top')
py.savefig('jwst_klf_spectral_sensitivity.png')
def plot_gc_yng_klf_imf(age):
"""
Plot up a simulated KLF, IMF, mass-luminosity relationship for the young star
cluster at the Galactic Center.
"""
from jlu.gc.imf import bayesian as b
# Use our best fit IMF for 0.5 - 150 Msun
# Use Weidner_Kroupa_2004 IMF between 0.1 - 0.5 Msun
# Stop at 0.1 Msun as we don't have evolution models below that mass.
massLimits = np.array([0.1, 0.5, 150])
powers = np.array([-1.3, -fitAlpha])
Mcl1 = 3.4e4
Mcl2 = 3.0e4
logAge = math.log10(age * 1e6)
cluster1 = b.model_young_cluster_new(logAge, massLimits=massLimits, imfSlopes=powers,
clusterMass=Mcl1, makeMultiples=True,
AKs=theAKs, distance=distance)
cluster2 = b.model_young_cluster_new(logAge, massLimits=massLimits, imfSlopes=powers,
clusterMass=Mcl2, makeMultiples=False,
AKs=theAKs, distance=distance)
Mcl1_1_150 = cluster1.systemMasses[cluster1.mass >= 1].sum()
Mcl2_1_150 = cluster2.systemMasses[cluster2.mass >= 1].sum()
Mcl1_01_1 = cluster1.systemMasses[cluster1.mass < 1].sum()
Mcl2_01_1 = cluster2.systemMasses[cluster2.mass < 1].sum()
print 'Cluster with multiples:'
print ' Total Cluster Mass = %d' % Mcl1
print ' Mass [1 - 150] Msun = %d' % Mcl1_1_150
print ' Mass [0.1 - 1] Msun = %d' % Mcl1_01_1
print 'Cluster with singles:'
print ' Total Cluster Mass = %d' % Mcl2
print ' Mass [1 - 150] Msun = %d' % Mcl2_1_150
print ' Mass [0.1 - 1] Msun = %d' % Mcl2_01_1
# Assign arbitrary magnitudes for WR stars. Uniformly distributed from Kp=9-11
idx1 = np.where(cluster1.isWR == True)[0]
cluster1.mag[idx1] = 9.0 + (np.random.rand(len(idx1))*2)
idx2 = np.where(cluster2.isWR == True)[0]
cluster2.mag[idx2] = 9.0 + (np.random.rand(len(idx2))*2)
# Plot the mass luminosity relationship
py.clf()
py.semilogy(cluster1.mag, cluster1.mass, 'k.', ms=2, label="Multiples", mec='black')
py.semilogy(cluster2.mag, cluster2.mass, 'b.', ms=2, label='Single', mec='blue')
py.xlabel('Kp Magnitude')
py.ylabel('Stellar Mass (Msun)')
py.title('Age: {0:.1f} Myr'.format(age))
py.legend(loc='upper right', numpoints=1)
py.ylim(0.1, 200)
py.savefig('{0}plots/mass_luminosity_{1:.1f}Myr.png'.format(workDir, age))
kbins = np.arange(9.0, 24, 0.5)
# Plot the KLF
py.clf()
py.hist(cluster1.mag, bins=kbins, histtype='step', linewidth=2, label='Multiples', color='blue')
py.hist(cluster2.mag, bins=kbins, histtype='step', linewidth=2, label='Singles', color='black')
py.gca().set_yscale('log')
py.xlabel('Kp Magnitude')
py.ylabel('Number of Stars')
py.title('Age: {0:.1f} Myr'.format(age))
py.legend(loc='upper left')
py.xlim(7, 22)
py.ylim(1, 1e4)
rng = py.axis()
outRoot = '{0}plots/klf_{1:.1f}Myr'.format(workDir, age)
py.savefig('{0}.png'.format(outRoot))
