In Radiative transfer settings, we saw how to set some of the basic parameters that determine how Hyperion is run, and in this section we discuss some more advanced options.
By default, when producing images, the radiative transfer is done over all wavelengths where radiation is emitted. Every emitted photon is propagated, and may be scattered or absorbed and re-emitted (or both) and we follow the propagation until the photon escapes the grid. When the photon is binned into an image or SED (whether making images with the binning or peeling-off algorithms), the photon is binned into a wavelength grid.
This means that producing images at exact wavelengths can be very inefficient, because it may be that 99% of the photons end up at a different wavelength and do not contribute to the images. In order to get around this problem, Hyperion also implements the concept of monochromatic radiative transfer (see section 2.6.4 of the Hyperion paper). In short, the way this algorithm works is that since the temperature has already been computed by the time the images are being computed, it is possible to consider only the propagation, scattering, and absorption of photons at the specific wavelengths/frequencies of interest.
To enable monochromatic radiative transfer, before setting the number of photons, you should call the set_monochromatic() method. For example, to compute images at 1, 1.2, and 1.4 microns, you would need to do:
m.set_monochromatic(True, wavelengths=[1., 1.2, 1.4])
where the wavelength arguments takes a list of wavelengths in microns. It is also possible to specify the frequencies in Hz:
m.set_monochromatic(True, frequencies=[1.e11, 2.e11])
When using the monochromatic mode, it is then necessary to set the number of photons separately for the photons emitted from sources and the photons emitted from dust:
m.set_n_photons(..., imaging_sources=1000, imaging_dust=1000, ...)
This should be used instead of the imaging option. The number of photons is the number per wavelength/frequency.
In some cases, one might want to compute scattered light images at wavelengths where there is no dust emission. In this case, there is no need to compute the specific energy of the dust, and there is also no need in re-emitting photons when computing images/SEDs. Therefore, one can set:
m.set_n_initial_iterations(0)
m.set_kill_on_absorb(True)
m.set_raytracing(True)
which turns off the specific energy calculation, kills photons as soon as they are first absorbed, and enables raytracing for the source emission. For the photon numbers, one can set raytracing_dust=0 to zero, since this is not needed (there is no dust emission).
Note
This cannot be used for all scattered light images. For example, in a protostar, a K-band image may have a non-negligeable amount of scattered light flux originating from the inner rim of the disk. This technique can only be used when there is no dust emission.
This can be combined with the Monochromatic radiative transfer option described above to avoid wasting photons at wavelengths where they are not needed. When treating only scattering, you will then want to set the following options:
m.set_n_photons(imaging_sources=1000, imaging_dust=0,
raytracing_sources=1000, raytracing_dust=0)
where the values should be adjusted to your model, but the important point is that initial is not needed, and imaging_dust and raytracing_dust can be set to 0.
For a full example of a model computing scattered light images, see How to efficiently compute pure scattering models.
Set the maximum number of photon interactions:
m.set_max_interactions(100000)
Set the number of output bytes per floating point value for the physical arrays (4 = 32-bit, 8 = 64-bit):
m.set_output_bytes(4)
To set the minimum temperature for dust:
m.set_minimum_temperature(10.)
m.set_minimum_temperature([10., 5., 20.])
If a scalar value is specified, the same value is used for all dust types. If a list is specified, the list should have as many items as dust types, and each item corresponds to the minimum temperature for each dust type.
Similarly, to set the minimum specific energy:
m.set_minimum_specific_energy(1.e-4)
m.set_minimum_specific_energy([1.e-4, 1.e-5, 2.e-5])
By default, photon positions and cells are double-checked every 1 in 1000 cell crossings. This can be changed with set_propagation_check_frequency():
m.set_propagation_check_frequency(0.01)
Note that values higher than 0.001 (the default) will cause the code to slow down.