Computer Physics Communications Program LibraryPrograms in Physics & Physical Chemistry |

[Licence| Download | New Version Template] aepb_v1_0.tar.gz(45 Kbytes) | ||
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Manuscript Title: FlowPy - a numerical solver for functional renormalization group equations | ||

Authors: Thomas Fischbacher, Franziska Synatschke-Czerwonka | ||

Program title: FlowPy | ||

Catalogue identifier: AEPB_v1_0Distribution format: tar.gz | ||

Journal reference: Comput. Phys. Commun. 184(2013)1931 | ||

Programming language: Python, C. | ||

Computer: PC or workstation. | ||

Operating system: Unix. | ||

RAM: approx. 40 MB | ||

Keywords: Functional Renormalization Group Equations, Momentum dependent flow equations. | ||

PACS: 11.10.Gh, 11.10.Hi. | ||

Classification: 4.12, 11.1. | ||

External routines: Python, libpython, SciPy, NumPy, python-simpleparse. | ||

Nature of problem:In the study of functional renormalization group equations non-local integro-differential equations arise which furthermore can contain singular coefficient functions for the highest derivative and may only be given implicitly. Solving these equations beyond the simplest cases thus provides a numerical challenge. | ||

Solution method:A combination of numerical differentiation, integration, interpolation, and ODE solving. | ||

Restrictions:Due to the nature of FRG problems, computational effort (run time) will scale quadratically with the number of discretization points. Using more than at most a few hundred discretization points may be impractical. | ||

Running time:For the SUSY_QM example: ~ 10 seconds for 10 support points, ~ 5 minutes for 100 discretization points. For the momentum_dependent_wavefunction example: ~ 40 minutes for 5 discretization points. |

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