plcabs: powerlaw observed through dense, cold matter
This model describes X-ray transmission of an isotropic source of photons located at the center of a uniform, spherical distribution of matter, correctly taking into account Compton scattering. The model can be used for radial column densities up to . The valid energy range for which data can be modeled is between 10 and 18.5 keV, depending on the column density. Details of the physics of the model, the approximations used and further details on the regimes of validity can be found in Yaqoob (1997; ApJ, 479, 184). In this particular incarnation, the initial spectrum is a power law modified by a high-energy exponential cut-off above a certain threshold energy.
Also, to improve the speed, a FAST option is available in which a full integration over the input spectrum is replaced by a simple mean energy shift for each bin. This option is obtained by setting parameter 9 to a value of 1 or greater and cannot be made variable. Further, for single-scattering albedos less than ACRIT (i.e. par8) energy shifts are neglected altogether. The recommended value is ACRIT=0.1 which corresponds to about 4 keV for cosmic abundances and is more than adequate for ASCA data.
Note that for column densities in the range 1023 – 1024 cm-2, the maximum number of scatterings which need be considered for convergence of the spectrum of better than 1% is between 1 and 5. For column densities as high as , the maximum number of scatterings which need be considered for the same level of convergence is 12. This parameter cannot be made variable.
par1 |
Column density in units 1022 cm–2 |
par2 |
Maximum number of scatterings to consider. |
par3 |
Iron abundance. |
par4 |
Iron K edge energy. |
par5 |
Power-law photon index. |
par6 |
High-energy cut-off threshold energy. |
par7 |
High-energy cut-off e-folding energy. |
par8 |
Critical albedo for switching to elastic scattering. |
par9 |
If par9 > 1, function uses mean energy shift, not integration. |
par10 |
Source redshift, z |
norm |
Normalization factor |