PHOEBE 2.0 Documentation

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IPython Notebook | Python Script

“Third” Light

Setup

As always, let’s do imports and initialize a logger and a new bundle. See Building a System for more details.

%matplotlib inline
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt

logger = phoebe.logger()

b = phoebe.default_binary()
WARNING: Constant u'Gravitational constant' is already has a definition in the u'si' system [astropy.constants.constant]
WARNING: Constant u'Solar mass' is already has a definition in the u'si' system [astropy.constants.constant]
WARNING: Constant u'Solar radius' is already has a definition in the u'si' system [astropy.constants.constant]
WARNING: Constant u'Solar luminosity' is already has a definition in the u'si' system [astropy.constants.constant]
/usr/local/lib/python2.7/dist-packages/astropy/units/quantity.py:782: FutureWarning: comparison to None will result in an elementwise object comparison in the future.
  return super(Quantity, self).__eq__(other)

Relevant Parameters

The ‘l3’ parameter describes how much third light exists in a given passband. Since this is passband dependent and only used for flux measurments - it does not yet exist for a new empty Bundle.

b.filter(qualifier='l3')
<ParameterSet: EMPTY>

So let’s add a LC dataset

b.add_dataset('lc', times=np.linspace(0,1,101), dataset='lc01')
<ParameterSet: 15 parameters | contexts: compute, dataset>

We now see that the LC dataset created ‘l3’ parameters for each of the stars in the system hierarchy

b.filter(qualifier='l3')
<ParameterSet: 1 parameters>

We can also see that these belong in the ‘dataset’ section and in the ‘lc_dep’ kind. This just means that these are passband-dependent parameters.

This also means that ‘l3’ will be relevant (and will be created) for RV datasets (when using the ‘flux-weighted’ method).

print b['l3@lc01']
Parameter: l3@lc01@dataset
                       Qualifier: l3
                     Description: Third light
                           Value: 0.0 W / m3
                  Constrained by:
                      Constrains: None
                      Related to: None

Influence on Light Curves (Fluxes)

“Third” light is simply additional flux added to the light curve from some external source - whether it be crowding from a background object, light from the sky, or an extra component in the system that is unaccounted for in the system hierarchy.

To see this we’ll compare a light curve with and without “third” light.

b.run_compute(irrad_method='none', model='no_third_light')
<ParameterSet: 2 parameters | qualifiers: fluxes, times>
b['l3@lc01'] = 5
b.run_compute(irrad_method='none', model='with_third_light')
<ParameterSet: 2 parameters | qualifiers: fluxes, times>

As expected, adding 5 W/m^3 of third light simply shifts the light curve up by that exact same amount.

fig = plt.figure()
ax1, ax2 = fig.add_subplot(121), fig.add_subplot(122)

axs, artists = b['lc01'].plot(model='no_third_light', ax=ax1)
axs, artists = b['lc01'].plot(model='with_third_light', ax=ax2)
../../_images/l3_18_0.png

Influence on Meshes (Intensities)

“Third” light does not affect the intensities stored in the mesh (including those in relative units). In other words, like distance, “third” light only scales the fluxes.

NOTE: this is different than pblums which DO affect the relative intensities. Again, see the pblum tutorial for more details.

To see this we can run both of our models again and look at the values of the intensities in the mesh.

b.add_dataset('mesh', times=[0], dataset='mesh01')
<ParameterSet: 2 parameters | contexts: compute, dataset>
b['l3@lc01'] = 0.0
b.run_compute(irrad_method='none', model='no_third_light')
Fri, 10 Feb 2017 16:32 BUNDLE       WARNING overwriting model: no_third_light
<ParameterSet: 76 parameters | kinds: mesh, lc>
b['l3@lc01'] = 5
b.run_compute(model='with_third_light')
Fri, 10 Feb 2017 16:32 BUNDLE       WARNING overwriting model: with_third_light
<ParameterSet: 76 parameters | kinds: mesh, lc>
print "no_third_light abs_intensities: ", b.get_value(qualifier='abs_intensities', component='primary', dataset='lc01', model='no_third_light').mean()
print "with_third_light abs_intensities: ", b.get_value(qualifier='abs_intensities', component='primary', dataset='lc01', model='with_third_light').mean()
no_third_light abs_intensities:  5.57734332537e+13
with_third_light abs_intensities:  5.62248236311e+13
print "no_third_light intensities: ", b.get_value(qualifier='intensities', component='primary', dataset='lc01', model='no_third_light').mean()
print "with_third_light intensities: ", b.get_value(qualifier='intensities', component='primary', dataset='lc01', model='with_third_light').mean()
no_third_light intensities:  5.43366313707e-19
with_third_light intensities:  5.47763932987e-19
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Last update: 06/07/2017 11:30 a.m. (CET)