本文中,我们利用随机过程理论,对随机游动高分子链构象提出了数学模型加以模拟,在这种模型下得到了关于高分子链构象的一系列结果。这些结果不仅在数学上更加严密化,而且包含了以往研究者的成果。在理想状态条件下,我们用三维布朗运动{r_t(ω)、t>0}来模拟随机游动高分子链构象,同时指出了三维布朗运动中各个变量在高分子链构象里重新赋予的直观意义。在这个基础上,定义了链键矢量和末端距矢量,得到了高分子链构象的分布和简约分布,例如作为高分子链柔性的一种量度的末端距矢量分布为:P(R;n)=integral from P({r_t(ω))}δ(sum from j=1 to n R_(tj)-R)d{r_t(ω)}经过富里埃变换和幂级数展开,它的特征函数有:K(ρ)=sum from m=(?)to ∞ ((-1)~m)/((2m+1)!) ρ~(2m)同时从讨论链键长度恒定的简单情况着手,可以求得末端距矢量分布P(R;n)=(3/(2π))~(3/2)exp{-(3((?)R(?))~2)/(2)}链键矢量分布f[R_(tj)(ω)]=(3/(2πl~2))~(3/2)exp{-(3(?)R_(tj)(?)~2)/(2l~2)}以及各阶矩,例如二阶矩为: In this paper, we use the stochastic process theory to simulate the random walk polymer chain conformation, and get a series of results about the polymer chain conformation under this model. These results are not only more mathematically mathematically, but also include the fruits of past researchers. Under the ideal conditions, we use the Brownian motion {r_t (ω), t> 0} to simulate the random conformation of the polymer chains, and at the same time we point out the intuition that the variables in the 3D Brownian motion are re-assigned in the conformation of the polymer chains significance. On this basis, the chain bond vector and the terminal distance vector are defined, and the distribution and the simple distribution of the molecular chain conformation are obtained. For example, the distribution of the terminal distance vector as a measure of the flexibility of the polymer chain is: P (R; n) = (integral from j = 1 to n R_ (tj) - R) d {r_t (ω)} after Fourier transform and power series expansion, the eigenfunctions of : Ρ (m) (1) ~ m) / ((2m + 1)!) ρ ~ (2m) In the simple case, the end-point vector distribution P (R; n) = (3 / (2π )) ~ (3/2) exp {- )) ~ 2) / (2