Continuous vs Discrete Chains¶
In Model Melt Chi AB, we discussed how to derive:
where \(\tilde{\nabla}^2 = R_g^2 \nabla^2\), \(s \in [0,\alpha_p]\), \(q(x,0) = 1\), \(\mu(r,s)\) is the field corresponding to the species at contour position s along molecule p.
Discuss operator splitting and how this leads to a form that is similar to the discrete chains
Note that Nref means different things for continuous vs discrete chains. For continuous chains, it is the contour length (with Nref + 1 contour steps). For discrete chains, N is the number of beads. This means that the reference lengths \(R_g\) or \(R_e\) will be slightly different depending on whether discrete or continuous chains are used. For continuous chains \(R_g^2 = \frac{b^2 N}{6}\) and \(R_e^2 = b^2 N\). For discrete chains \(R_g^2 = \frac{b^2 (N-1)}{6}\) and \(R_e^2 = b^2 (N-1)\).
The different meanings of Nref for different chain types is necessary so that when a user specifies Nref = 100 and nbeads = 100, the lengths in the simulation don’t need to be correted by a factor of N/(N-1) (TODO: is this correct?).
Discrete chains¶
References: GHF, Koski2013, Matsen2012 (Macromol 45:8502)
where \(K\) is the identity of the \(s+1\) bead. \(\Phi(r)\) is the bond probability which for a discrete Gaussian chain is:
The convolution can be solved using FFTs which requires the fourier transform of \(\Phi(\pmb{r})\),
For Rg units
Density operator:
the sum over s includes beads of species K.