Estimating Statistical Uncertainties of Internal Kinematics of Galaxies
and Star Clusters Derived Using Full Spectrum Fitting
I. Chilingarian, and K. Grishin. (2019)cite arxiv:1912.05269Comment: 8 pages, 2 figures, submitted to PASP; the code is available here https://bitbucket.org/extragalactic/pxf_kin_err/src/master/.
Abstract
Pixel-space full spectrum fitting exploiting non-linear $\chi^2$ minimization
became a de facto standard way of deriving internal kinematics from
absorption line spectra of galaxies and star clusters. However, reliable
estimation of uncertainties for kinematic parameters remains a challenge and is
usually addressed by running computationally expensive Monte-Carlo simulations.
Here we derive simple formulae for the radial velocity and velocity dispersion
uncertainties based solely on the shape of a template spectrum used in the
fitting procedure and signal-to-noise information. Comparison with Monte-Carlo
simulations provides perfect agreement for different templates, signal-to-noise
ratios and velocity dispersion between 0.5 and 10 times of the instrumental
spectral resolution. We provide IDL and python implementations of
our approach. The main applications are: (i) exposure time calculators; (ii)
design of observational programs and estimates on expected uncertainties for
spectral surveys of galaxies and star clusters; (iii) a cheap and accurate
substitute for Monte-Carlo simulations when running them for large samples of
thousands of spectra is unfeasible or when uncertainties reported by a
non-linear minimization algorithms are not considered reliable.
Description
Estimating Statistical Uncertainties of Internal Kinematics of Galaxies and Star Clusters Derived Using Full Spectrum Fitting
cite arxiv:1912.05269Comment: 8 pages, 2 figures, submitted to PASP; the code is available here https://bitbucket.org/extragalactic/pxf_kin_err/src/master/
%0 Generic
%1 chilingarian2019estimating
%A Chilingarian, Igor V.
%A Grishin, Kirill A.
%D 2019
%K dispersion fitting uncertainty velocity
%T Estimating Statistical Uncertainties of Internal Kinematics of Galaxies
and Star Clusters Derived Using Full Spectrum Fitting
%U http://arxiv.org/abs/1912.05269
%X Pixel-space full spectrum fitting exploiting non-linear $\chi^2$ minimization
became a de facto standard way of deriving internal kinematics from
absorption line spectra of galaxies and star clusters. However, reliable
estimation of uncertainties for kinematic parameters remains a challenge and is
usually addressed by running computationally expensive Monte-Carlo simulations.
Here we derive simple formulae for the radial velocity and velocity dispersion
uncertainties based solely on the shape of a template spectrum used in the
fitting procedure and signal-to-noise information. Comparison with Monte-Carlo
simulations provides perfect agreement for different templates, signal-to-noise
ratios and velocity dispersion between 0.5 and 10 times of the instrumental
spectral resolution. We provide IDL and python implementations of
our approach. The main applications are: (i) exposure time calculators; (ii)
design of observational programs and estimates on expected uncertainties for
spectral surveys of galaxies and star clusters; (iii) a cheap and accurate
substitute for Monte-Carlo simulations when running them for large samples of
thousands of spectra is unfeasible or when uncertainties reported by a
non-linear minimization algorithms are not considered reliable.
@misc{chilingarian2019estimating,
abstract = {Pixel-space full spectrum fitting exploiting non-linear $\chi^2$ minimization
became a \emph{de facto} standard way of deriving internal kinematics from
absorption line spectra of galaxies and star clusters. However, reliable
estimation of uncertainties for kinematic parameters remains a challenge and is
usually addressed by running computationally expensive Monte-Carlo simulations.
Here we derive simple formulae for the radial velocity and velocity dispersion
uncertainties based solely on the shape of a template spectrum used in the
fitting procedure and signal-to-noise information. Comparison with Monte-Carlo
simulations provides perfect agreement for different templates, signal-to-noise
ratios and velocity dispersion between 0.5 and 10 times of the instrumental
spectral resolution. We provide {\sc IDL} and {\sc python} implementations of
our approach. The main applications are: (i) exposure time calculators; (ii)
design of observational programs and estimates on expected uncertainties for
spectral surveys of galaxies and star clusters; (iii) a cheap and accurate
substitute for Monte-Carlo simulations when running them for large samples of
thousands of spectra is unfeasible or when uncertainties reported by a
non-linear minimization algorithms are not considered reliable.},
added-at = {2019-12-12T17:23:51.000+0100},
author = {Chilingarian, Igor V. and Grishin, Kirill A.},
biburl = {https://www.bibsonomy.org/bibtex/202cf69f4e896aaf4654bcb261f0062b5/heh15},
description = {Estimating Statistical Uncertainties of Internal Kinematics of Galaxies and Star Clusters Derived Using Full Spectrum Fitting},
interhash = {8b77829ff0594883b64fc9708df4645f},
intrahash = {02cf69f4e896aaf4654bcb261f0062b5},
keywords = {dispersion fitting uncertainty velocity},
note = {cite arxiv:1912.05269Comment: 8 pages, 2 figures, submitted to PASP; the code is available here https://bitbucket.org/extragalactic/pxf_kin_err/src/master/},
timestamp = {2019-12-12T17:23:51.000+0100},
title = {Estimating Statistical Uncertainties of Internal Kinematics of Galaxies
and Star Clusters Derived Using Full Spectrum Fitting},
url = {http://arxiv.org/abs/1912.05269},
year = 2019
}