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Title: IMFIT: A FAST, FLEXIBLE NEW PROGRAM FOR ASTRONOMICAL IMAGE FITTING

Abstract

I describe a new, open-source astronomical image-fitting program called IMFIT, specialized for galaxies but potentially useful for other sources, which is fast, flexible, and highly extensible. A key characteristic of the program is an object-oriented design that allows new types of image components (two-dimensional surface-brightness functions) to be easily written and added to the program. Image functions provided with IMFIT include the usual suspects for galaxy decompositions (Sérsic, exponential, Gaussian), along with Core-Sérsic and broken-exponential profiles, elliptical rings, and three components that perform line-of-sight integration through three-dimensional luminosity-density models of disks and rings seen at arbitrary inclinations. Available minimization algorithms include Levenberg-Marquardt, Nelder-Mead simplex, and Differential Evolution, allowing trade-offs between speed and decreased sensitivity to local minima in the fit landscape. Minimization can be done using the standard χ{sup 2} statistic (using either data or model values to estimate per-pixel Gaussian errors, or else user-supplied error images) or Poisson-based maximum-likelihood statistics; the latter approach is particularly appropriate for cases of Poisson data in the low-count regime. I show that fitting low-signal-to-noise ratio galaxy images using χ{sup 2} minimization and individual-pixel Gaussian uncertainties can lead to significant biases in fitted parameter values, which are avoided if a Poisson-based statistic is used;more » this is true even when Gaussian read noise is present.« less

Authors:
 [1];  [2]
  1. Max-Planck-Insitut für Extraterrestrische Physik, Giessenbachstrasse, D-85748 Garching, GermanyAND (Germany)
  2. (Germany)
Publication Date:
OSTI Identifier:
22364311
Resource Type:
Journal Article
Resource Relation:
Journal Name: Astrophysical Journal; Journal Volume: 799; Journal Issue: 2; Other Information: Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; ALGORITHMS; AVAILABILITY; BRIGHTNESS; DATA ANALYSIS; GALACTIC EVOLUTION; GALAXIES; IMAGE PROCESSING; IMAGES; LUMINOSITY; MAXIMUM-LIKELIHOOD FIT; MINIMIZATION; NOISE; PHOTOMETRY; POTENTIALS; SENSITIVITY; SIGNAL-TO-NOISE RATIO; THREE-DIMENSIONAL CALCULATIONS; TWO-DIMENSIONAL CALCULATIONS

Citation Formats

Erwin, Peter, and Universitäts-Sternwarte München, Scheinerstrasse 1, D-81679 München. IMFIT: A FAST, FLEXIBLE NEW PROGRAM FOR ASTRONOMICAL IMAGE FITTING. United States: N. p., 2015. Web. doi:10.1088/0004-637X/799/2/226.
Erwin, Peter, & Universitäts-Sternwarte München, Scheinerstrasse 1, D-81679 München. IMFIT: A FAST, FLEXIBLE NEW PROGRAM FOR ASTRONOMICAL IMAGE FITTING. United States. doi:10.1088/0004-637X/799/2/226.
Erwin, Peter, and Universitäts-Sternwarte München, Scheinerstrasse 1, D-81679 München. Sun . "IMFIT: A FAST, FLEXIBLE NEW PROGRAM FOR ASTRONOMICAL IMAGE FITTING". United States. doi:10.1088/0004-637X/799/2/226.
@article{osti_22364311,
title = {IMFIT: A FAST, FLEXIBLE NEW PROGRAM FOR ASTRONOMICAL IMAGE FITTING},
author = {Erwin, Peter and Universitäts-Sternwarte München, Scheinerstrasse 1, D-81679 München},
abstractNote = {I describe a new, open-source astronomical image-fitting program called IMFIT, specialized for galaxies but potentially useful for other sources, which is fast, flexible, and highly extensible. A key characteristic of the program is an object-oriented design that allows new types of image components (two-dimensional surface-brightness functions) to be easily written and added to the program. Image functions provided with IMFIT include the usual suspects for galaxy decompositions (Sérsic, exponential, Gaussian), along with Core-Sérsic and broken-exponential profiles, elliptical rings, and three components that perform line-of-sight integration through three-dimensional luminosity-density models of disks and rings seen at arbitrary inclinations. Available minimization algorithms include Levenberg-Marquardt, Nelder-Mead simplex, and Differential Evolution, allowing trade-offs between speed and decreased sensitivity to local minima in the fit landscape. Minimization can be done using the standard χ{sup 2} statistic (using either data or model values to estimate per-pixel Gaussian errors, or else user-supplied error images) or Poisson-based maximum-likelihood statistics; the latter approach is particularly appropriate for cases of Poisson data in the low-count regime. I show that fitting low-signal-to-noise ratio galaxy images using χ{sup 2} minimization and individual-pixel Gaussian uncertainties can lead to significant biases in fitted parameter values, which are avoided if a Poisson-based statistic is used; this is true even when Gaussian read noise is present.},
doi = {10.1088/0004-637X/799/2/226},
journal = {Astrophysical Journal},
number = 2,
volume = 799,
place = {United States},
year = {Sun Feb 01 00:00:00 EST 2015},
month = {Sun Feb 01 00:00:00 EST 2015}
}
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