Coordinate-wise descent methods for leading eigenvalue problem

Abstract

Leading eigenvalue problems for large scale matrices arise in many applications. Coordinate-wise descent methods are considered in this work for such problems based on a reformulation of the leading eigenvalue problem as a non-convex optimization problem. The convergence of several coordinate-wise methods is analyzed and compared. Numerical examples of applications to quantum many-body problems demonstrate the efficiency and provide benchmarks of the proposed coordinate-wise descent methods.

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Cited by in corpus (4)

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• A greedy algorithm for computing eigenvalues of a symmetric matrix
• Hamiltonian models of lattice fermions solvable by the meron-cluster algorithm
• A Finite Element Configuration Interaction Method for Wigner Localization