sawsim/introduction.tex: Add a lead in paragraph (why this chapter?)

A number of my readers have been confused about why I lead off my
contributions with the sawsim chapter.  This paragraph is an attempt
to lay that out for them.

diff --git a/src/sawsim/introduction.tex b/src/sawsim/introduction.tex
index 094ea76b7cd796c39e9a45692fdc3ac6538ddf17..c8287582c562b820d22dfb3d9b48ea3bfa7402fd 100644 (file)
--- a/src/sawsim/introduction.tex
+++ b/src/sawsim/introduction.tex
@@ -1,3 +1,22 @@
+% Why simulations?  And why are we leading with them?
+Unfolding proteins by pulling on them with an AFM yields a series of
+force curves (\cref{fig:expt-sawtooth}).  How do we get from the
+unfolding curves to a deeper understanding of the unfolding physics?
+In this chapter, I present my \sawsim\ simulator, which performs
+discrete-state unfolding simulations using theoretical models of
+protein unfolding.  By finding the models and parameters that best
+reproduce the experimental data, we can find unforced unfolding rates
+and other unfolded polymer distances that can be cross checked in
+chemical unfolding experiments and used to validate more detailed
+molecular dynamics simulations.  The \sawsim\ simulations discussed
+here are carried out after the unfolding experiments
+(\cref{sec:pyafm}), cantilever calibration (\cref{sec:calibcant}), and
+post-processing (\cref{sec:hooke}), but I discuss \sawsim\ first
+because it provides the cleanest description of the underlying
+physical processes.  After we cover the theory here, we will be better
+prepared for the realistic complications discussed in the following
+chapters.
+
 % AFM unfolding analysis, what we'll do.
 Much theoretical and computational work has been done in order to
 extract information about the structural, kinetic, and energetic