Radiation Sources

Rabacus provides classes to handle various radiation sources. These objects can be useful in their own right, but most likely you will be passing them as arguments to the geometric solvers. The following sources are available in Rabacus,

Note

The most important thing to remember is that source spectra (in general) need to be normalized after being created. See the section on Normalization for more details.

Note

All examples assume the numpy and rabacus packages have been imported.

import numpy as np
import rabacus as ra

Arguments

All source classes share a common set of arguments that determine their spectrum.

q_min (float): minimum photon energy

q_max (float): maximum photon energy

spectrum_type (string): {monochromatic, powerlaw, thermal, hm12, user}

The first two, q_min and q_max, are dimensionless floats. They determine the minimum and maximum photon energies to be considered. The are interpreted as multiples of the Rydberg energy (13.6 eV). The third argument, spectrum_type, should be set equal to one of the following strings {monochromatic, powerlaw, thermal, hm12, user}. All of the spectral types except monochromatic require additional keywords when used. For powerlaw spectra, a slope, alpha, must also be passed in. For thermal spectra, an effective temperature, T_eff, must be supplied. For the Haart and Madau 2012 model hm12, one must pass in a redshift, z. Finally, for the user defined spectrum, one must pass in both an array of energy samples, user_E, and an array indicating spectral shape, user_shape. We will go into more detail in the examples below.

Point source monochromatic spectrum

q_min = 2.3; q_max = 2.3
src = ra.PointSource(q_min, q_max, 'monochromatic')
print src.source_type + ' ' + src.spectrum_type
point monochromatic

Plane source power law spectrum

q_min = 1.0; q_max = 5.0
alpha = -2.0
src = ra.PlaneSource(q_min, q_max, 'powerlaw', alpha=alpha)
print src.source_type + ' ' + src.spectrum_type
plane powerlaw

Point source thermal spectrum

q_min = 1.0; q_max = 5.0
T_eff = 1.0e5 * ra.u.K
src = ra.PointSource(q_min, q_max, 'thermal', T_eff=T_eff)
print src.source_type + ' ' + src.spectrum_type
point thermal

Background source HM12 spectrum

q_min = 1.0; q_max = 5.0
z = 3.0
src = ra.BackgroundSource(q_min, q_max, 'hm12', z=z)
print src.source_type + ' ' + src.spectrum_type
background hm12

Background source user defined spectrum (broken power law)

Note that q_min and q_max are ignored for user defined spectra, but they still must be passed in.

q_min = q_max = 1.0
E = np.linspace(1.0, 5.0, 50) * 13.6 * ra.u.eV
ibrk = 25
E0 = E[ibrk]
alpha1 = -1.0
alpha2 = -2.0
shp = np.zeros(E.size)
shp[:ibrk+1] = (E[:ibrk+1]/E0)**alpha1
shp[ibrk:] = (E[ibrk:]/E0)**alpha2
src = ra.BackgroundSource(q_min, q_max, 'user', user_E=E, user_shape=shp)
print src.source_type + ' ' + src.spectrum_type
background user

Energy Samples

When a source is created, a spectrum is defined by uniformly (in log space) sampling Nnu energies between the variables q_min and q_max. The number of samples, Nnu, takes on a default value but can be passed in as a keyword to either increase or decrease spectral resolution. In general, attributes are defined to characterize the energy, frequency, and wavelength of photons.

Attribute Description
q energy samples / Ry
E energy samples
lam wavelengths
nu frequencies

For example, if we create a source with Nnu=8,

q_min = 1.0; q_max = 5.0; Nnu = 8
T_eff = 1.0e5 * ra.u.K
src8 = ra.PlaneSource( q_min, q_max, 'thermal', T_eff=T_eff, Nnu=Nnu )

Then it will have a dimensionless fundamental photon energy array q,

print src8.q
[ 1.          1.25849895  1.58381961  1.80808824
  2.50848455  3.15692518  4.00147059  5.        ] dimensionless

an array with units of energy E,

print src8.E
[ 13.6        17.11558573  21.53994668 24.59
  34.11538992 42.93418242  54.42       68.      ] eV

a wavelength array with units of length lam,

print src8.lam
[ 9.11648497e-06  7.24393530e-06 5.75601219e-06
  5.04205757e-06  3.63425996e-06 2.88777353e-06
  2.27828364e-06  1.82329699e-06] cm

and a frequency array with units of inverse time, nu,

print src8.nu
[ 3.28846544e+15   4.13853031e+15   5.20833605e+15
  5.94583568e+15   8.24906477e+15   1.03814394e+16
  1.31586978e+16   1.64423272e+16] Hz

Note that energy samples exist exactly at the hydrogen and helium ionizing thresholds, {13.6, 24.59, 54.42} eV. By default, uniform spacing is sacrificed to achieve this. If exactly uniform spacing is needed, set the keyword segmented to False.

Spectral Shape

Each source class has a fundamental spectral variable based on the characteristics of the radiation source. When a radiation source is created, the spectral_type variable along with the geometric type (i.e. point, plane, or background) are used to determine the value and units of the fundamental spectral variable at each energy sample. These variables take one form for polychromatic spectra and another for monochromatic spectra. The variables are listed in the tables below.

Monochromatic Sources

Source Fundamental Intensity Attribute Units
Point luminosity Lu erg/(s)
Plane flux Fu erg/(s cm^2)
Background specific intensity Inu erg/(s cm^2 sr)

For example,

pt = ra.PointSource( 2.0, 2.0, 'monochromatic' )
pl = ra.PlaneSource( 2.0, 2.0, 'monochromatic' )
bg = ra.BackgroundSource( 2.0, 2.0, 'monochromatic' )

print pt.Lu
print pl.Fu
print bg.Inu
[ 1.] erg/s
[ 1.] erg/(cm**2*s)
[ 1.] erg/(cm**2*s*sr)

Note

In general, all spectra have to be normalized after being instanciated. See the section on Normalization.

Polychromatic Sources

Source Fundamental Intensity Attribute Units
Point luminosity density dLu_over_dnu erg/(Hz s)
Plane flux density dFu_over_dnu erg/(Hz s cm^2)
Background specific intensity Inu erg/(Hz s cm^2 sr)

For example,

T = 1.0e5 * ra.u.K
pt = ra.PointSource( 1.0, 5.0, 'thermal', T_eff=T, Nnu=8 )
pl = ra.PlaneSource( 1.0, 5.0, 'thermal', T_eff=T, Nnu=8 )
bg = ra.BackgroundSource( 1.0, 5.0, 'thermal', T_eff=T, Nnu=8 )

print pt.dLu_over_dnu
print pl.dFu_over_dnu
print bg.Inu
[ 0.13632697  0.1662243   0.18637547  0.18957652
  0.16102251  0.11392481  0.06087262  0.02452717] erg/(s*Hz)

[ 0.13632697  0.1662243   0.18637547  0.18957652
  0.16102251  0.11392481  0.06087262  0.02452717] erg/(cm**2*s*Hz)

[ 0.13632697  0.1662243   0.18637547  0.18957652
  0.16102251  0.11392481  0.06087262  0.02452717] erg/(cm**2*s*sr*Hz)

Note

In general, all spectra have to be normalized after being instanciated. See the section on Normalization.

These variables, along with the energy sample variables in the previous section, are available as top level attributes in the returned object.

Optically Thin

When a source is created, all quantities that can be calculated by performing integrals over the fundamental intensity and without reference to optical depth are stored in a sub object called thin. We conceptually split these variables into two types. The first type are those that do not refer to any photo-ionization cross-sections.

Attribute Description Units
Ln photon luminosity 1/s
Lu energy luminosity erg/s
Fn photon flux 1/(s cm^2)
Fu energy flux erg/(s cm^2)
n photon density 1/cm^3
u energy density erg/cm^3

Note that the luminosity variables Ln and Lu will only be present in point sources as the concept does not translate to plane or background sources. We also note that the API documentation for each geometric source type (PointSource, PlaneSource, BackgroundSource) goes into detail about how each quantity above is calculated.

The second type of attribute stored in the thin object are photo-ionization and heating rates. These are related to photo-ionization cross-sections.

Attribute Description Units
H1i H I photo-ionization rate 1/s
He1i He I photo-ionization rate 1/s
He2i He II photo-ionization rate 1/s
H1h H I photo-heating rate erg/s
He1h He I photo-heating rate erg/s
He2h He II photo-heating rate erg/s

It’s important to note that many of these attributes will be variables in plane and background sources, but functions of distance in point sources.

Here we present some examples. First, the H I photoionization rate at a distance of 1 kpc from a thermal point source normalized to emit 1.0e50 photons per second,

T = 1.0e5 * ra.u.K
pt = ra.PointSource( 1.0, 5.0, 'thermal', T_eff=T )
pt.normalize_Ln( 1.0e50/ra.u.s )

H1i = pt.thin.H1i( 1.0*ra.u.kpc )
print H1i.round(15)
1.387e-12 1/s

Next, the same quantity for a thermal plane source normalized to have a flux of 1.0e6 photons per second per square centimeter,

T = 1.0e5 * ra.u.K
pl = ra.PlaneSource( 1.0, 5.0, 'thermal', T_eff=T )
pl.normalize_Fn( 1.0e6/ra.u.s/ra.u.cm**2 )

H1i = pl.thin.H1i
print H1i.round(15)
1.659e-12 1/s

Normalization

Normalization of spectra after creation is crucial to obtaining the results you expect. All sources except background sources with spectral type hm12 should be normalized after being created. Here we will list the normalization functions available for each source class.

Point

Plane

Background

User Defined Spectra

If the pre defined spectral types do not suite your needs, you can define your own. This is done by setting the keyword spectral_type to user and setting the keywords user_E and user_shape. The array user_E should have units of energy and the user_shape array should be dimensionless. Leaving the shape array without units allows for flexibility. If the user_shape array is passed to a background source it will take the units of specific intensity erg/(Hz s cm^2 sr). Likewise, if the array is passed to a plane source it will take the units erg/(Hz s cm^2) and if passed to a point source it will take the units erg/(Hz s). Note that for user defined spectra, q_min and q_max are ignored. For example, to create a background source with a flat spectrum.