The self-consistent field (SCF) iteration, combined with its variants, is one of the most widely used algorithms in quantum chemistry. We propose a procedure to adapt the SCF iteration for the p-Laplacian eigenproblem, which is an important problem in the field of unsupervised learning. We formulate the p-Laplacian eigenproblem as a type of nonlinear eigenproblem with one eigenvector nonlinearity , which then allows us to adapt the SCF iteration for its solution after the application of suitable regularization techniques. The results of our numerical experiments confirm the viablity of our approach.
翻译:自相兼容的迭代场及其变异体是量子化学中最广泛使用的算法之一。我们提议了一个程序来调整 SCF 的迭代,以适应p-Laplaceian egenroblem,这是未受监督的学习领域的一个重要问题。我们将p-Laplicaian egenblem 编成一种非线性无源性非源性,从而使我们能够在应用适当的正规化技术后,将 SCF 迭代用于解决方案。我们的数字实验结果证实了我们方法的细微性。