Reflection and Heating

For a comparison between "Horvat" and "Wilson" methods in the "irad_method" parameter, see the tutorial on Lambert Scattering.

Setup

Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).


In [ ]:
!pip install -I "phoebe>=2.0,<2.1"

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


In [1]:
%matplotlib inline

In [2]:
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt

logger = phoebe.logger('error')

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 parameters that define reflection and heating are all prefaced by "irrad_frac" (fraction of incident flux) and suffixed by "bol" to indicate that they all refer to a bolometric (rather than passband-dependent) process. For this reason, they are not stored in the dataset, but rather directly in the component.

Each of these parameters dictates how much incident flux will be handled by each of the available processes. For now these only include reflection (heating with immediate re-emission, without heat distribution) and lost flux. In the future, heating with distribution and scattering will also be supported.

For each component, these parameters must add up to exactly 1.0 - and this is handled by a constraint which by default constrains the "lost" parameter.


In [3]:
print b['irrad_frac_refl_bol']


ParameterSet: 2 parameters
  irrad_frac_refl_bol@primary...: 0.6
  irrad_frac_refl_bol@seconda...: 0.6

In [4]:
print b['irrad_frac_lost_bol']


ParameterSet: 4 parameters
* irrad_frac_lost_bol@primary...: 0.4
  irrad_frac_lost_bol@primary...: 1.000000 - {irrad_frac_refl_bol@primary@component}
* irrad_frac_lost_bol@seconda...: 0.4
  irrad_frac_lost_bol@seconda...: 1.000000 - {irrad_frac_refl_bol@secondary@component}

In [5]:
print b['irrad_frac_refl_bol@primary']


Parameter: irrad_frac_refl_bol@primary@component
                       Qualifier: irrad_frac_refl_bol
                     Description: ratio of incident bolometric light that is used for reflection (heating without redistribution)
                           Value: 0.6
                  Constrained by: 
                      Constrains: irrad_frac_lost_bol@primary@component
                      Related to: irrad_frac_lost_bol@primary@component


In [6]:
print b['irrad_frac_lost_bol@primary@component']


Parameter: irrad_frac_lost_bol@primary@component
                       Qualifier: irrad_frac_lost_bol
                     Description: ratio of incident bolometric light that is lost/ignored
                           Value: 0.4
                  Constrained by: irrad_frac_refl_bol@primary@component
                      Constrains: None
                      Related to: irrad_frac_refl_bol@primary@component

In order to see the effect of reflection, let's set "irrad_frac_refl_bol" of both of our stars to 0.3 - that is 30% of the incident flux will go towards reflection and 70% will be ignored.


In [7]:
b.set_value_all('irrad_frac_refl_bol', 0.3)

Since reflection can be a computationally expensive process and in most cases is a low-order effect, there is a switch in the compute options that needs to be enabled in order for reflection to be taken into account. If this switch is False (which it is by default), the albedos are completely ignored and will be treated as if all incident light is lost/ignored.


In [8]:
print b['irrad_method@compute']


Parameter: irrad_method@phoebe01@compute
                       Qualifier: irrad_method
                     Description: Which method to use to handle all irradiation effects (reflection, redistribution)
                           Value: wilson
                         Choices: none, wilson, horvat

Reflection has the most noticeable effect when the two stars are close to each other and have a large temperature ratio.


In [9]:
b['sma@orbit'] = 4.0

In [10]:
b['teff@primary'] = 10000


Fri, 10 Feb 2017 16:51 PARAMETERS   WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32

In [11]:
b['teff@secondary'] = 5000


Fri, 10 Feb 2017 16:51 PARAMETERS   WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32

Influence on Light Curves (fluxes)


In [12]:
b.add_dataset('lc', times=np.linspace(0,1,101))


Fri, 10 Feb 2017 16:51 PARAMETERS   WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Fri, 10 Feb 2017 16:51 PARAMETERS   WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Fri, 10 Feb 2017 16:51 PARAMETERS   WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Out[12]:
<ParameterSet: 15 parameters | contexts: compute, dataset>

Let's run models with the reflection switch both turned on and off so that we can compare the two results. We'll also override delta to be a larger number since the computation time required by delta depends largely on the number of surface elements.


In [13]:
b.run_compute(irrad_method='none', ntriangles=700, model='refl_false')


Fri, 10 Feb 2017 16:51 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Out[13]:
<ParameterSet: 2 parameters | qualifiers: fluxes, times>

In [14]:
b.run_compute(irrad_method='wilson', ntriangles=700, model='refl_true')


Fri, 10 Feb 2017 16:52 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Out[14]:
<ParameterSet: 2 parameters | qualifiers: fluxes, times>

In [15]:
axs, artists = b.plot()



In [16]:
artists = plt.plot(b['value@times@refl_false'], b['value@fluxes@refl_true']-b['value@fluxes@refl_false'], 'r-')


Influence on Meshes (Intensities)


In [17]:
b.add_dataset('mesh', times=[0.2])


Fri, 10 Feb 2017 16:53 PARAMETERS   WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Out[17]:
<ParameterSet: 2 parameters | contexts: compute, dataset>

In [18]:
b.run_compute(irrad_method='none', ntriangles=700, model='refl_false')


Fri, 10 Feb 2017 16:53 BUNDLE       WARNING overwriting model: refl_false
Fri, 10 Feb 2017 16:53 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Out[18]:
<ParameterSet: 76 parameters | kinds: mesh, lc>

In [19]:
b.run_compute(irrad_method='wilson', ntriangles=700, model='refl_true')


Fri, 10 Feb 2017 16:54 BUNDLE       WARNING overwriting model: refl_true
Fri, 10 Feb 2017 16:54 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=10000K>8000K), for which gravb_bol=1.00 might be a better approx than gravb_bol=0.32
Out[19]:
<ParameterSet: 76 parameters | kinds: mesh, lc>

In [20]:
axs, artists = b.plot(kind='mesh', model='refl_false', facecolor='intensities')


/usr/lib/python2.7/dist-packages/matplotlib/colors.py:489: RuntimeWarning: invalid value encountered in less
  np.copyto(xa, -1, where=xa < 0.0)

In [21]:
axs, artists = b.plot(kind='mesh', model='refl_true', facecolor='intensities')



In [ ]: