Optimal multigrid algorithms for the massive Gaussian model and path integrals | Zendy

Achi Brandt | Zendy; Meirav Galun | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Optimal multigrid algorithms for the massive Gaussian model and path integrals

Author(s) -

Achi Brandt,

Meirav Galun

Publication year - 1996

Publication title -

journal of statistical physics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.71

H-Index - 115

eISSN - 1572-9613

pISSN - 0022-4715

DOI - 10.1007/bf02183393

Subject(s) - multigrid method , observable , gaussian , path (computing) , mathematics , algorithm , grid , statistical physics , path integral formulation , standard deviation , computer science , physics , mathematical analysis , statistics , geometry , quantum mechanics , partial differential equation , programming language , quantum

Multigrid algorithms are presented which, in addition to eliminating the critical slowing down, can also eliminate the “volume factor”. The elimination of the volume factor removes the need to produce many independent fine-grid configurations for averaging out their statistical deviations, by averaging over the many samples produced on coarse grids during the multigrid cycle. Thermodynamic limits of observables can be calculated to relative accuracy εr in justO(ε

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research