Programs in Physics & Physical Chemistry
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|Manuscript Title: ILTHII - analysis of the spectrum of a thermal radioastronomical source.|
|Authors: M. Salem|
|Program title: ILTHII|
|Catalogue identifier: AAEF_v1_0|
Distribution format: gz
|Journal reference: Comput. Phys. Commun. 9(1975)247|
|Programming language: Fortran.|
|Computer: IBM 360/65.|
|Operating system: OS.|
|Program overlaid: yes|
|RAM: 24K words|
|Word size: 32|
|Keywords: Astrophysics, Radioastronomy, Hii region, Thermal source, Laplace transform, Inverse, Continuum spectrum.|
Nature of problem:
It has been shown by Salem and Seaton that, given the spectrum of a thermal radioastronomical source, information on the structure can be deduced in the form of a function Omega(E), which is the total angular area within which the emission measure is greater than or equal to E. A spherical model of the object can also be constructed. An estimate of the electron temperature, Te, (assumed to be constant) is required. In some cases this estimate may be improved by comparing Omega(E) with observations of high angular resolution. The computer program ILTHII (Inverse Laplace Transform - HII region) computes Omega(E) and the spherical model from the flux density spectrum, and also compares Omega(E) with high resolution observations.
Observations of the flux density, Sv, as a function of frequency, v, are transformed to the form y(x), where x is essentially a frequency variable, and y depends upon Sv and v. An analytic function is fitted numerically to the observations; the inverse Laplace transform of this function is [Te Omega (E)]. An improved estimate of Te can, in principle, be made by adjusting Omega(E) to agree with high angular resolution observations. If spherical symmetry is assumed, the electron density, Ne, can be determined as a function of distance from the center by analytical solution of an integral equation.
The function Omega(E) is determined on the assumption that all continuum radio emission from the object is thermal, and that the electron temperature is essentially constant.
The running time depends upon the number of observations, the number of coefficients which define the function which fits the observations, and other user-specified quantities. The example provided took approximately 20 s to compile (excluding the minimization program), and 20 s to run on an IBM 360/65.
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