English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present an approach to preconditioning for large, relatively dense linear systems and verify the validity of our method. We restrict the target of our method to Molecular Orbital (MO) calculations. Sparse Approximate Inverse (SAI) is typically less effective at accelerating the convergence and requires a huge computational cost in its construction when a large number of nonzero entries are kept in the approximate inverse matrix. We explain a construction of Block SAI and a cutoff strategy to reduce the number of nonzero elements, and investigate the efficiency of a cutoff strategy and Block SAI.

A block sparse approximate inverse with cutoff preconditioner for semi-sparse linear systems derived from Molecular Orbital calculations