deletions | additions       diff --git a/Filament selection and analysis.tex b/Filament selection and analysis.tex  index e8cc22e..d67c49a 100644  --- a/Filament selection and analysis.tex  +++ b/Filament selection and analysis.tex 
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\section{Filament selection and analysis}  After 1.25 Myr of self gravitating evolution, we selected by eye two filamentary features in one projection of the cloud's surface density, shown in figure \ref{finderimage}. In this image we plot the surface density calculated from contributions by gas in the range $10^3 < n/{\rm cm}^{-3} < 10^{4.5}$. This is roughly the density range traced by C$^{18}$O observations; we then convert the surface density to integrated line intensities. [SHOW EQUATION?] This approximate `observation' of our data yields an idea of what this simulation might look like in the motivating observations of \citet{2013A&A...554A..55H}. We chose one feature which, observationally speaking, would probably be deemed an obvious filament (the smaller feature to the lower right of figure \ref{finderimage}), and one that might be considered a ridge of star formation activity (the larger feature).  We The boxes surrounding the  selected outline  a rectangular region around each coordinate system oriented along the long axis or length $L$  of the filaments (see figure   \ref). filament, the width $W$, and the depth $D$ (which is the same line of sight used in the projected surface density).  Wethen  stepped along thelength  $L$ andwidth  $W$ coordinates  of the filaments with step sizes corresponding to the minimum base  resolution of the simulation. At each location in the filament boxes we calculated the density-weighted line-of-sight velocity along the projection axis. $D$ coordinate, again using the same density range to correspond to C$^{18}$O observations.  This velocity spectrum was binned into a histogram with bin width 0.075 0.05  km s$^{-1}$, a width chosen to roughly match the velocity resolution of H12. s$^{-1}$.  In figure X \ref{finderimage}  we show this velocity  data in two forms. First, we stack on righthand side. We summed  the histograms along the $W$ dimension, yielding the total velocity distribution along slices perpendicular to the filament's long axis.Second, we perform a velocity component analysis similar to that done in H12. For each point in the filament box, we normalize the velocity spectrum by its own rms value. Signals that intensities in excess of 3 times the rms value are retained. Rather than fit Gaussians to each individual feature, as in H12, we simply (crudely) take the average velocity of each separate feature above the cutoff as a `detected' velocity component. The spectra are thus reduced to points in the {\it L--W--v} position--position--velocity cube. We show the {\it L--v} projection of these cubes in figure X for each of the filaments.