| | 当使用划分 <math>\Omega_\ell</math>将网络粗粒化至 <math>\ell + 1</math>层级时,构型 <math>A^{(\ell+1)}</math>的概率仍精确由方程{{EquationNote|10}}和{{EquationNote|11}}描述,其中 <math>\ell</math>替换为 <math>\ell + 1</math>且参数重整化为: | | 当使用划分 <math>\Omega_\ell</math>将网络粗粒化至 <math>\ell + 1</math>层级时,构型 <math>A^{(\ell+1)}</math>的概率仍精确由方程{{EquationNote|10}}和{{EquationNote|11}}描述,其中 <math>\ell</math>替换为 <math>\ell + 1</math>且参数重整化为: |
| − | <math>x_{i_{\ell+1}} = \sum_{i_{\ell} \in \Omega} x_{i_{\ell}}, \quad d_{i_{\ell+1},j_{\ell+1}} = f^{-1}\left(\dfrac{\sum_{\substack{i_{\ell} \in i_{\ell+1}, j_{\ell} \in j_{\ell+1}}} \delta x_{i_{\ell}} x_{j_{\ell}} f(d_{i_{\ell},j_{\ell}})}{\sum_{\substack{i_{\ell} \in i_{\ell+1}, j_{\ell} \in j_{\ell+1}}} \delta x_{i_{\ell}} x_{j_{\ell}} }\right),\tag{12}</math> | + | {{NumBlk|:|<math>x_{i_{\ell+1}} = \sum_{i_{\ell} \in \Omega} x_{i_{\ell}}, \quad d_{i_{\ell+1},j_{\ell+1}} = f^{-1}\left(\dfrac{\sum_{\substack{i_{\ell} \in i_{\ell+1}, j_{\ell} \in j_{\ell+1}}} \delta x_{i_{\ell}} x_{j_{\ell}} f(d_{i_{\ell},j_{\ell}})}{\sum_{\substack{i_{\ell} \in i_{\ell+1}, j_{\ell} \in j_{\ell+1}}} \delta x_{i_{\ell}} x_{j_{\ell}} }\right),\tag{12}</math>|{{EquationRef|12}}}} |