Question

我使用简单的编码结构模拟尺寸大于3的Ising Model铁磁体但是在效率方面存在一些问题。在我的代码中，有一个特定的功能是瓶颈。

在模拟过程中，有必要找到所谓的最近邻居。例如，在2D Ising模型中，自旋在每个点占据晶格，由两个数字表示：（x，y）。（x，y）处的点的最近邻居是四个相邻值，即（x + 1，y），（x-1，y），（x，y + 1），（x，y-1）。在5D中，在一些点阵位置的自旋具有坐标（a，b，c，d，e）与10个最近邻居，其形式与之前相同，但对于元组中的每个点。

现在这里是给出以下输入的代码：

"site_i is a random value between 0 and n-1 denoting the site of the ith spin"
"coord is an array of size (n**dim,dim) that contains the coordinates of ever spin"
"spins is an array of shape (n**dim,1) that contains the spin values (-1 or 1)"
"n is the lattice size and dim is the dimensionality"
"neighbor_coupling is the number that tells the function to return the neighbor spins that are one spacing away, two spacing away, etc."

def calc_neighbors(site_i,coord,spins,n,dim,neighbor_coupling):
    # Extract all nearest neighbors
    # Obtain the coordinates of each nearest neighbor
    # How many neighbors to extract
    num_NN = 2*dim
    # Store the results in a result array 
    result_coord = np.zeros((num_NN,dim))
    result_spins = np.zeros((num_NN,1))
    # Get the coordinates of the ith site
    site_coord = coord[site_i]
    # Run through the + and - for each scalar value in the vector in site_coord
    count = 0
    for i in range(0,dim):
        assert count <= num_NN, "Accessing more than nearest neighbors values."
        site_coord_i = site_coord[i]
        plus = site_coord_i + neighbor_coupling
        minus = site_coord_i - neighbor_coupling

        # Implement periodic boundaries
        if (plus > (n-1)): plus = plus - n
        if (minus < 0): minus = n - np.abs(minus)

        # Store the coordinates
        result_coord[count] = site_coord
        result_coord[count][i] = minus
        # Store the spin value
        spin_index = np.where(np.all(result_coord[count]==coord,axis=1))[0][0]
        result_spins[count] = spins[spin_index]
        count = count + 1

        # Store the coordinates
        result_coord[count] = site_coord
        result_coord[count][i] = plus
        # Store the spin value
        spin_index = np.where(np.all(result_coord[count]==coord,axis=1))[0][0]
        result_spins[count] = spins[spin_index]
        count = count + 1

我真的不知道如何让它更快，但它会有很大帮助。也许是存储一切的不同方式？

Ising Model：如何缩短模拟时间？

0 个答案: