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Next: Statistical Equilibrium Up: The Lambda Iteration Previous: The Emissivity Function

   
Solving the Radiative Transfer Equation

The first iteration now starts by calculating, for each ring and each transition, the new radiation field, given the present level populations. It does this by calculating, for each transition in each ring, the radiation intensity contributed by each line of sight. In each case this simply involves adding up the contributions from each ring segment that the line of sight intersects. Integrating the intensity around $4\pi$ steradians gives the total radiation intensity at any one point in that ring. However, as the rings may be moving relative to one another it is also necessary to take into account the Doppler shifting of the emitted frequencies. This is done by considering 11 different velocities (ie. frequencies) centred around the line centre4.9. Therefore rings whose emission is shifted so far in velocity that it falls outside these 11 velocities will not contribute to the line. This process will now be described in detail.

The calculations are performed on each segment ($m$) on each line of sight ($k$) for each velocity step ($l$) for each transition ($j$) in each ring ($i$). The first step is to adjust the optical depth to take into account the velocity shift due to the Doppler effect. The optical depth per unit length for each ring was calculated in the first pass through the convergence check section (equation 4.27) and is adjusted to give4.10

 \begin{displaymath}
\kappa_m=\tau_{i,k,m} \times e^{-\frac{0.4(l-6) \Delta V_i-v_m}{\Delta V_{i,k,m}}}
\end{displaymath} (4.28)

where $v_m$ is the velocity of the segment relative to the start of the line of sight (it is given by the average of the two relative velocities at the start and end of the segment as given in the $intersect$ array). $\Delta V_i$ is the velocity width of the ring in which the line of sight starts and $\Delta V_{i,k,m}$ is the velocity width of the ring in which segment lies. So $\kappa_{m}$ represents the optical depth per unit length of segment $m$ as seen by an observer in ring $i$ at a particular velocity shift, indexed by $l$. By multiplying this by the length of the segment the total optical depth for the segment at the required velocity shift is produced. This is stored in array $opt1$ by the program and represents $\kappa_n \times L_n$.

Now applying the radiative transfer equation yields the radiation intensity due to this segment on the starting position of the line of sight

 \begin{displaymath}
I_{i,j,k,l,m}=E_m \times e^{-\sum_{n=1}^m ( \kappa_n \times L_n)} \times L_m
\end{displaymath} (4.29)

where $L_m$ is the length of the segment. So $I_{i,j,k,l,m}$ represents the radiation intensity on ring $i$ due to the molecules in the ring containing segment $m$ that are radiating at velocity offset $l$ after taking into account the absorption of this radiation by the material in segment $m$ and all other intervening segments.

There   is unfortunately a problem with this when the optical depth for a particular segment gets too large. Consider equation 4.29 for $m=1$ (ie. the first segment on the line of sight), then if $\kappa_1$ is large the term $e^{\kappa_n \times L_n}$ will become very small and hence the intensity for that segment (and thereby the sum for all following segments) will be lower than it should be. In an extreme case the intensity calculated would be virtually zero whereas of course the actual intensity falling on the start position of the line of sight would not be zero. The solution for this is to split the segment up into sufficient shorter subsections such that the optical depth for each segment is small enough to reduce this effect to an insignificant level - this will mean an optical depth of around 0.2 for each segment4.11. The program therefore checks at this stage to see what the optical depth for the segment is. If it is greater than 0.2 the segment is split into $n=\frac{\kappa_n \times L_n}
{0.2}+1$ segments. It is also necessary to split a segment up if the velocity change across the segment becomes too large. Unacceptably large errors will occur if $\left\vert v_2-v_1 \right\vert > 0.3 \times \Delta V$ where $v_1$and $v_2$ are the velocities at the beginning and end of the segment and $\Delta V$ is the ring velocity width as defined in equation 4.20. If this condition occurs the segment is split into4.12 $\left[ \frac{\left\vert v_2-v_1 \right\vert}{0.3 \times \Delta V}
\right] + 1$ subsegments.

In addition the value for the total optical depth between the segment and the start of the line of sight is measured from the centre of the segment. This means that the summation that appears in equation 4.29 is actually represented in the program as

\begin{displaymath}I_{i,j,k,l,m}=E_m \times
e^{-\left[ \sum_{n=1}^{m-1} (\kappa_n \times L_n)+\frac{\kappa_m \times L_m}{2} \right]} \times L_m
\end{displaymath}

This primarily avoids problems with optically thin lines of sight, for example a line of sight that has only one segment on it with an optical depth of 0.2 would use this value in equation 4.29 without the modification whereas in reality the molecules near the start of the segment will be radiating through an optical depth of virtually zero and only the few molecules furthest away are radiating through an optical depth of 0.2. It therefore seems sensible to take some middle value and the program in fact would use 0.1 in this case. It is not clear whether this actually has any major effect on the lambda iteration for a full sized model cloud as it may well be that this problem only arises on a few lines of sight and the effect is 'drowned out' by all the other lines of sight. It is more likely to have an effect on the calculations for the line profiles especially when just one line of sight is used (ie. no beam simulation).

The question then arises as to what values the parameters in equations 4.28 & 4.29 should take on these new intersection boundaries. The original STEN program did a straight linear interpolation between the two surrounding shell intersections but didn't take into account whether the parameters applied to the shell or the shell boundary. An additional problem with this method was pointed out in Buckley [7], namely that when the line of sight takes a long path through a shell, not quite touching the next shell in, then this method does not take into account the variations of the parameters as the line moves closer to the centre of the cloud. The method used by Buckley was to interpolate using the distance to the centre of the cloud. This method is unfortunately not practical in this 2-D version as the $intersect$ array does not store information on the absolute position of the line of sight in the cloud. It is therefore necessary to use a variation on the original method. This implementation is, however, slightly modified.

The parameters that need adjusting for each segment are the section lengths, the systematic velocities (defined on the section intersections), the velocity widths (also defined on the intersections) and the optical depth function (defined for each segment).

The length of each new subsegment is easily calculated since the original segment is simply divided into equal subsegments. The systematic velocity was defined on the intersections so the velocity at each new intersection is given by

\begin{displaymath}v_i=v_e+i\frac{v_e-v_s}{[s]}
\end{displaymath}

where $i$ is the $i^{th}$ subsection along the line of sight.



\includegraphics[scale=0.6, angle=0]{interpparam.eps}  

However, the other parameters are defined for each segment (ie. not on the intersections) and there are many different ways of interpolating. The method that has been chosen here is shown in figure 4.14. A straight linear interpolation between parameter values at the center of each ring and the appropriate adjacent ring is made (except for the first and last rings). Each subsegment then picks the values for its parameters from the appropriate point on this interpolated line. For the special cases of the first and last segment the outer half of the ring is assigned a constant parameter value. The program actually does this process in two stages, as the interpolated line will have two sections of different gradient for each segment. This is shown in figure 4.14 where the thick line represents the interpolated value of a particular parameter along the line of sight. The section that covers the 4th segment is shown split into these 2 subsections, one as a dotted section and one as a dashed section. The new subsegments are shown drawn on as dotted line subsegments and show how the parameters would be chosen if the segment were split into 8 subsegments.

\includegraphics[scale=0.8, angle=0]{rmin.eps}  

\includegraphics{fail2.eps} \includegraphics{fail1.eps}
 Some thought needs to be given to situations where this interpolation does not work well. Figure 4.15 demonstrates the problem by considering a sample line of sight (the thick line) passing off centre through the cloud (assume it travels parallel to the planes and thus only the cylinder intersections are of concern). At each intersection the velocity is defined. When the line of sight segments are split up into subsegments as described above the velocities at the subsegment boundaries are defined by simple linear interpolation between these values. The graph on the right shows the value for the velocity at various positions in the cloud for a $r^{-\frac{1}{2}}$ velocity distribution (eg. a Keplerian disk) as a solid line. The velocity changes only slowly in the outer part of the cloud but then rises dramatically towards the centre. The velocities for the intersections (ie. 1, 2, 3, 5, 6, 7) are indicated through the dotted lines. The dashed line in the velocity graph joins the velocity values at these 6 points and represents the velocity values that the program uses for its calculations. It is immediately obvious that this method fails badly in the central part of the cloud (ie. between intersections 3 and 5). This is due to the intersections at 3 and 5 having identical velocities. The effect this has on the final output can be seen in figure 4.16. This is the result for a beam with 5 gridding points slightly offset from the centre of a cloud with an $r^{-\frac{1}{2}}$ velocity distribution and a constant ${\rm H_2}$and abundance distribution. The offset is sufficient so that none of the beam reaches to the centre of the cloud (hence why only one 'wing' is seen). It can be clearly seen that there is an artificial looking blip at the -7 km s$^{-1}$ position. This is caused by one of the offcentre lines in the grid (see section 4.8.3) experiencing the effect described above, all the material in the innermost section emits at the same velocity rather than being spread out over a range of velocities, thus there is too much emission at that velocity. The program deals with this by searching for the position along the line of sight that is closest to the central line of symmetry in the cloud (ie. the $r=0$ line). At that point the innermost segment is split into two and the correct velocity for that central point is calculated (ie. effectively point 4 in figure 4.15 is inserted). The interpolation then functions as shown by the dashed/dotted line in figure 4.15 which is a much closer representation of the actual velocity field. The result of this modification can be seen in figure 4.17. Further improvement will only come by adding more cylinders to the model. This system is not perfect, it deals quite well with an $r^{-\frac{1}{2}}$ velocity distribution however there are certainly other velocity distributions where it may not work as well. Anywhere where there are rapid velocity changes should be treated with care (eg. the edges of outflow regions).

Using the above method for calculating the emission from each segment the program then proceeds to add up all the contributions from all the segments along the line of sight. This then gives the total radiation intensity from that line of sight, ie.

\begin{displaymath}I_{i,j,k,l}= \sum^m_{n=1} I_{i,j,k,l,m} +
\frac{2h\nu^3_j}{c^...
...}} -1 \right)}
\times e^{-\sum_{n=1}^m ( \kappa_n \times L_n)}
\end{displaymath}

The second term here adds the radiation contribution from the cosmic background radiation (at 2.73 K), after taking into account its passage through the cloud. Since the lines of sight are distributed evenly in all directions it is now possible to calculate the radiation intensity on the ring at this particular frequency by summing all the lines of sight and integrating over $4\pi$ steradians

\begin{displaymath}I_{i,j,l}'=\frac{\sum_{k=1}^{n_{los}}I_{i,j,k,l}}{n_{los}}
\end{displaymath}

now adjust this to take into account its velocity shift

\begin{displaymath}I_{i,j,l}=I_{i,j,l}' \times e^{-\frac{0.4(l-6) \Delta V_i-v_m}{\Delta V_i}}
\end{displaymath}

Note that the factor of $4\pi$ does not appear here, this is because it will be cancelled in the next step by a factor of $\frac{1}{4\pi}$. The theory behind these steps is described on page [*] - these four equations are the implementation of equation 3.18. The radiation now needs to be integrated over the velocity range in order to finally yield the total radiation intensity on a ring due to all other rings (and the cosmic background) for each transition.

\begin{displaymath}\overline{J}_{i,j}=\frac{0.4}{\sqrt{\pi}} \int_{l=-5}^{5}I_{i,j,l} \, dl
\end{displaymath}

Once the radiation field has been established the new population levels based on this radiation field can be calculated. This is done in the levels subroutine.


next up previous contents index
Next: Statistical Equilibrium Up: The Lambda Iteration Previous: The Emissivity Function

1999-04-12