Weighted Trace-Penalty Minimization for Full Configuration Interaction

01/18/2023
by   Weiguo Gao, et al.
0

A novel unconstrained optimization model named weighted trace-penalty minimization (WTPM) is proposed to address the extreme eigenvalue problem arising from the Full Configuration Interaction (FCI) method. Theoretical analysis reveals the global minimizers are desired eigenvectors instead of the eigenspace. Analyzing the condition number of the Hessian operator in detail contributes to the determination of a near-optimal weight matrix. With the sparse feature of FCI matrices in mind, the coordinate descent (CD) method is adapted to WTPM and results in WTPM-CD method. The reduction of computational and storage costs in each iteration shows the efficiency of the proposed algorithm. Finally, the numerical experiments demonstrate the capability to address large-scale FCI matrices.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/09/2019

Iteratively reweighted penalty alternating minimization methods with continuation for image deblurring

In this paper, we consider a class of nonconvex problems with linear con...
research
05/11/2019

Sparse Optimization Problem with s-difference Regularization

In this paper, a s-difference type regularization for sparse recovery pr...
research
08/11/2022

Regularizing Deep Neural Networks with Stochastic Estimators of Hessian Trace

In this paper we develop a novel regularization method for deep neural n...
research
11/04/2021

A note on using the mass matrix as a preconditioner for the Poisson equation

We show that the mass matrix derived from finite elements can be effecti...
research
10/16/2020

The conditioning of least squares problems in preconditioned variational data assimilation

Data assimilation algorithms combine prior and observational information...
research
01/30/2021

Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training

In recent years, the Deep Learning Alternating Minimization (DLAM), whic...

Please sign up or login with your details

Forgot password? Click here to reset