&= \frac{N_f k_{u0}}{\kappa v}\exp\p({\frac{F\Delta x_u}{k_B T}})
= \frac{1}{\rho}\exp\p({\frac{F-\alpha}{\rho}}) \;,
\end{align}
-where $N_f$ is the number of folded domain,
-$\kappa=(1/\kappa_c+N_u/\kappa_\text{WLC})^{-1}$ is the spring
-constant of the cantilever-polymer system ($\kappa_\text{WLC}$ is the
-effective spring constant of one unfolded domain, assumed constant for
-a particular polymer/cantilever combination), $\kappa v$ is the force
+where $N_f$ is the number of folded domain, $\kappa$ is the spring
+constant of the cantilever-polymer system, $\kappa v$ is the force
loading rate, and $k_u$ is the unfolding rate constant
(\cref{eq:sawsim:bell}). In the last expression, $\rho\equiv
k_BT/\Delta x_u$, and $\alpha\equiv-\rho\ln(N_fk_{u0}\rho/\kappa v)$.
+We can approximate $\kappa$ as a series of Hookean springs,
+\begin{equation}
+ \kappa=\p({\frac{1}{\kappa_c}+\frac{N_u}{\kappa_\text{WLC}}})^{-1} \;,
+ \label{eq:kappa-system}
+\end{equation}
+where $\kappa_\text{WLC}$ is the effective spring constant of one
+unfolded domain, assumed constant for a particular polymer/cantilever
+combination.
+
The event probability density for events with an exponentially
increasing likelihood function follows the Gumbel (minimum)
probability density\citep{NIST:gumbel} with $\rho$ and $\alpha$ being
as far as I know, nobody has found an analytical form for the
unfolding force histograms produced under such a variable loading
rate.
+%
\nomenclature{$r_{uF}$}{Unfolding loading rate (newtons per second)}
\nomenclature{$\gamma_e$}{Euler-Macheroni constant, $\gamma_e=0.577\ldots$}
\end{center}
\end{figure}
+\citet{benedetti11} have since proposed an alternative
+parameterization for \cref{eq:kappa-system}, using
+\begin{equation}
+ \kappa = \p({\frac{1}{\kappa_c}
+ + \frac{N_f}{\kappa_f} + \frac{N_u}{\kappa_u}})^{-1}
+ \equiv \frac{\kappa'}{1 - A N_f} \;,
+ \label{eq:kappa-system-benedetti}
+\end{equation}
+where $\kappa'$ is the spring constant of the completely unfolded
+chain and $A$ is a correction term for the supramolecular scaffold.
+This is effectively a first order Taylor expansion for $\kappa^{-1}$
+about $N_f=0$, but the remaining analysis is identical.
+\begin{align}
+ f(N_f) \equiv \kappa^{-1}
+ &= \frac{1}{\kappa_c} + \frac{N_f}{\kappa_f} + \frac{N - N_f}{\kappa_u} \\
+ &= f(0) + \left.\deriv{N_f}{f}\right|_{N_f=0} N_f + \order{N_f^2} \\
+ &\approx \p({\frac{1}{\kappa_c} + \frac{N}{\kappa_u}}) +
+ \p({\frac{1}{\kappa_f} - \frac{1}{\kappa_u}}) N_f
+ \label{eq:kappa-system-taylor}
+\end{align}
+In the case where the wormlike chain stiffnesses $\kappa_f$ and
+$\kappa_u$ are fairly constant over the unfolding region, there are no
+higher order terms and the first order expansion in
+\cref{eq:kappa-system-taylor} is exact. Comparing
+\cref{eq:kappa-system-benedetti,eq:kappa-system-taylor}, we see
+\begin{align}
+ \kappa' &= \frac{1}{\kappa_c} + \frac{N}{\kappa_u} \\
+ -\kappa' A &= \frac{1}{\kappa_f} - \frac{1}{\kappa_u} \\
+ A &= \frac{\frac{1}{\kappa_u} - \frac{1}{\kappa_f}}
+ {\frac{1}{\kappa_c} + \frac{N}{\kappa_u}}
+\end{align}
+By focusing on the $A=0$ case (\ie~$\kappa_f=\kappa_u$),
+\citet{benedetti11} avoid running Monte Carlo simulations when
+modeling unfolding histograms. This simplification does not hold for
+our simulated data (\cref{fig:sawsim:order-dep}), but for some
+experimental analysis the loss of accuracy may be acceptable in return
+for the reduced computational cost.
\subsection{The effect of cantilever force constant}
\label{sec:sawsim:cantilever}