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Distribution of segments on Gaussian chain

The probability distribution function of $P_i(\mathbf{r}_i-\mathbf{r}_\mathrm{cm})$ of ideal chain is evaluated, for $P_i$ represents the probability distribution fucntion of $i$th segment with respect to its centre of mass on the ideal chain. An ideal chain is modeled as multidimensional random walk, where the steps are independent, and the distribution of a step at mean length $b$ is given by $P(\mathbf{r})\sim\mathcal{N}(0,b^2)$. Let $\mathbf{b}_i=\mathbf{r}_{i+1}-\mathbf{r}_{i}$ be the $i$th bond vector, then we have $$\mathbf{r}_i=\sum_{j=1}^{i-1} \mathbf{b}_j$$ and the centre of mass $\mathbf{r}_\mathrm{cm}=\frac{1}{N}\sum_i \mathbf{r}_i$ is $$\mathbf{r}_\mathrm{cm}=\frac{1}{N}\sum_{j=1}^{N-1}(N-j)\mathbf{b}_j$$ then $$\mathbf{r}_i-\mathbf{r}_\mathrm{cm}=\sum_{j=1}^{i-1}\frac{j}{N}\mathbf{b}_j+\sum_{j=i}^{N-1}\frac{N-j}{N}\mathbf{b}_j$$ If variable $X$ is a Gaussian random variable with scale of $\sigma^2$, then $aX$ is a Gaussian random variable with scale of $a^2\si

Simple Examples of Parallel Computing of Cython

It is more convenient to calculate some properties during a molecular simulation process by accessing data from API of the molecular simulation program than calculating after the whole simulation progress and dumping all the coordinates. Especially, for sharply fluctuated properties such as Virial, RDF, etc., require massive frames to calculate. It is expensive to dump densely. For some Python-friendly molecular simulation softwares, e.g., lammps, hoomd-blue, galamost, etc.; it is easily to embed customized Python functions into the simulation control scripts. However, Python has a poor performance in massive calculations, numba.cuda.jit does dramatically boost up the program, however, due to unknown reasons, GPU-accelerated molecular simulation softwares like hoomd-blue and galamost produce errors during simulations if one uses numba.cuda.jit compiled functions. Therefore, I try to use Cython to generate C-functions to accelerate the calculations. Here I put a simple example of a p

Anisotropy of ideal chain

The Gaussian chain is isotropic when averaged over conformation space and all orientations. Therefore, a Gaussian chain is dealt as sphere with radius of $R_g$, it’s radius of gyration. In the 2nd chapter of Rubinstein’s Polymer Physics , an exercise shows that the $R_g^2$ is asymmetric if one set the coordinate frame on its end-to-end vector, $\mathbf{R}_{ee}$. i.e., the $\mathbf{R}_{ee}$ vector is set as the $x$-axis therefore $\mathbf{R}_{ee}=(R,0,0)^T$. Then the 3 components of $\mathbf{R}_{ee}$ are $\frac{Nb^2}{36}$, $\frac{Nb^2}{36}$ on $y$, $z$ direction and $\frac{Nb^2}{36}+\frac{R^2}{12}$ on $x$ direction. Here I make a very simple proof. Consider a Gaussian chain is fixed between $(0,0,0)^T$ and $\mathbf{R}_{ee}$. It’s actually a Brownian bridge, and the distribution is a multivariate Gaussian with mean at $\frac{i}{N}\mathbf{R}$ with variance $\frac{i(N-i)}{N}b^2$, the proof is simple: $$P_{0\mathbf{R}}(\mathbf{r},n)=\frac{G(\mathbf{r},0,n)G(\mathbf{R},\mathbf{r},N-n)}{G(

Flory characteristic ratio of hindered rotation chain

This is an exercise on Rubinstein's textbook of Polymer Physics . Definition of Flory characteristic ratio: $$C_\infty:=\lim_{n\to\infty}\frac{\langle \mathbf{R}^2 \rangle}{nb^2}$$ where $\langle \mathbf{R}^2 \rangle$ is the mean square end-to-end vector, $b$ is Kuhn length of the polymer and $n$ is corresponding chain length. Calculation of $\langle \mathbf{R}^2\rangle$: Let $\mathbf{r}_i$ be the bond vector between $i$ and $(i-1)$th particle, and $\mathbf{r}_1=\mathbf{R}_1-\mathbf{R}_0\equiv0$; for an $n$-bead chain,: $$\begin{align}\langle \mathbf{R}^2 \rangle&=\left\langle\left(\sum_{i=1}^n \mathbf{r}_i^2\right)\cdot\left(\sum_{j=1}^n \mathbf{r}_j^2\right)\right\rangle\\ &=\sum_i\sum_j\langle \mathbf{r}_i\cdot\mathbf{r}_j\rangle\end{align}$$ Calculation of $\langle\mathbf{r}_i\cdot\mathbf{r}_j\rangle$: Now consider a local coordinate frame that $\mathbf{r}_i=(b,0,0)^T$, then $\mathbf{r}_{i+1}$ could be considered as rotating $\mathbf{r}_i$ $\theta$ by $z$-axis

RTFM, pls RTFM!!!

I was trying to write a parallel version C-extension with Cython several days ago, to calculate Coulomb energy of $n$ points. I wrote the code as follows: @cython.cdivision(True) @cython.boundscheck(False) @cython.wraparound(False) def u(double[:,:] x): cdef long i cdef long j,k cdef double ret=0,tmp with nogil, parallel(): for i in prange(x.shape[0]-1, schedule='static'): for j in range(i + 1, x.shape[0]): tmp = 0 for k in range(x.shape[1]): tmp = tmp + pow(x[i,k]-x[j,k],2) ret = ret + 1 / sqrt(tmp) return ret