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# Line 139 | Line 139 | in Fig.~\ref{timestep}.
139   average 7\% increase in computation time using the DLM method in
140   place of quaternions. This cost is more than justified when
141   comparing the energy conservation of the two methods as illustrated
142 < in Fig.~\ref{timestep}.
142 > in Fig.~\ref{methodFig:timestep}.
143  
144   \begin{figure}
145   \centering
# Line 474 | Line 474 | Bond constraints are applied at the end of both the {\
474   \end{equation}
475  
476   Bond constraints are applied at the end of both the {\tt moveA} and
477 < {\tt moveB} portions of the algorithm.  Details on the constraint
478 < algorithms are given in section \ref{oopseSec:rattle}.
477 > {\tt moveB} portions of the algorithm.
478  
479   \subsection{\label{methodSection:NPTf}Constant-pressure integration with a
480   flexible box (NPTf)}
# Line 793 | Line 792 | systems\cite{Garcia-Palacios1998,Berkov2002,Denisov200
792   between the native and denatured states. Because of its stability
793   against noise, Langevin dynamics is very suitable for studying
794   remagnetization processes in various
795 < systems\cite{Garcia-Palacios1998,Berkov2002,Denisov2003}. For
796 < instance, the oscillation power spectrum of nanoparticles from
797 < Langevin dynamics simulation has the same peak frequencies for
798 < different wave vectors,which recovers the property of magnetic
799 < excitations in small finite structures\cite{Berkov2005a}. In an
800 < attempt to reduce the computational cost of simulation, multiple
801 < time stepping (MTS) methods have been introduced and have been of
802 < great interest to macromolecule and protein
803 < community\cite{Tuckerman1992}. Relying on the observation that
804 < forces between distant atoms generally demonstrate slower
805 < fluctuations than forces between close atoms, MTS method are
806 < generally implemented by evaluating the slowly fluctuating forces
807 < less frequently than the fast ones. Unfortunately, nonlinear
808 < instability resulting from increasing timestep in MTS simulation
809 < have became a critical obstruction preventing the long time
810 < simulation. Due to the coupling to the heat bath, Langevin dynamics
811 < has been shown to be able to damp out the resonance artifact more
813 < efficiently\cite{Sandu1999}.
795 > systems\cite{Palacios1998,Berkov2002,Denisov2003}. For instance, the
796 > oscillation power spectrum of nanoparticles from Langevin dynamics
797 > simulation has the same peak frequencies for different wave
798 > vectors,which recovers the property of magnetic excitations in small
799 > finite structures\cite{Berkov2005a}. In an attempt to reduce the
800 > computational cost of simulation, multiple time stepping (MTS)
801 > methods have been introduced and have been of great interest to
802 > macromolecule and protein community\cite{Tuckerman1992}. Relying on
803 > the observation that forces between distant atoms generally
804 > demonstrate slower fluctuations than forces between close atoms, MTS
805 > method are generally implemented by evaluating the slowly
806 > fluctuating forces less frequently than the fast ones.
807 > Unfortunately, nonlinear instability resulting from increasing
808 > timestep in MTS simulation have became a critical obstruction
809 > preventing the long time simulation. Due to the coupling to the heat
810 > bath, Langevin dynamics has been shown to be able to damp out the
811 > resonance artifact more efficiently\cite{Sandu1999}.
812  
813   %review rigid body dynamics
814   Rigid bodies are frequently involved in the modeling of different
# Line 898 | Line 896 | term\cite{Beard2001}. As a complement to IBD which has
896   average acceleration is not always true for cooperative motion which
897   is common in protein motion. An inertial Brownian dynamics (IBD) was
898   proposed to address this issue by adding an inertial correction
899 < term\cite{Beard2001}. As a complement to IBD which has a lower bound
899 > term\cite{Beard2003}. As a complement to IBD which has a lower bound
900   in time step because of the inertial relaxation time, long-time-step
901   inertial dynamics (LTID) can be used to investigate the inertial
902   behavior of the polymer segments in low friction

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