This module contains tools for least-squares fits, as functions of time t, of simulation (or other statistical) data for 2-point and 3-point correlators of the form:
Gab(t) = <b(t) a(0)> Gavb(t,T) = <b(T) V(t) a(0)>
Each correlator is modeled using Corr2 for 2-point correlators, or Corr3 for 3-point correlators in terms of amplitudes for each source a, sink b, and vertex V, and the energies associated with each intermediate state. The amplitudes and energies are adjusted in the least-squares fit to reproduce the data; they are specified in a shared prior (typically a dictionary).
An object of type CorrFitter describes a collection of correlators and is used to fit multiple models to data simultaneously. Any number of correlators may be described and fit by a single CorrFitter object. CorrFitter objects can also be used to to extract the appropriate fit data from Dataset objects.
This module has been used extensively for analyzing results from lattice QCD simulations. Documentation for this module can be found by looking at doc/html/index.html or <https://corrfitter.readthedocs.io>. The .py files in directory examples/ also illustrate how to use corrfitter; see examples/README for more information.
Information on how to install the library is in the file INSTALLATION. To test the module try ‘make tests’.
This module requires the lsqfit and gvar Python packages.
Background information on the some of the fitting strategies used by corrfitter can be found by doing a web searches for “hep-lat/0110175”, “arXiv:1111.1363”, and :arXiv:1406.2279” (appendix). These are papers by G.P. Lepage and collaborators whose published versions are: G.P. Lepage et al, Nucl.Phys.Proc.Suppl. 106 (2002) 12-20; K. Hornbostel et al, Phys.Rev. D85 (2012) 031504; and C.M. Bouchard et al, Phys.Rev. D90 (2014) 054506.
corrfitter version numbers have the form major.minor.patch where incompatible changes are signaled by incrementing the major version number, the minor number signals new features, and the patch number signals bug fixes.
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