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\documentclass[craaa]{aaa2014}

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\usepackage[spanish,activeacute,english]{babel}
\usepackage[utf8]{inputenc}
\usepackage{verbatim}
\usepackage{amsmath}
\usepackage{amsfonts}
\usepackage{amssymb}

\begin{document}

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\journalvol{57}
\journalyear{2014}
\journaleditors{A.C. Rovero, C. Beaugé, L.J. Pellizza, M. Lares}

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\contribtype{2}

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\thematicarea{22}

\title{Uncertainty determination of X-ray spectral parameters 
in the low photon statistics regime in {\it Chandra} ACIS-I spectra}

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\author{Albacete Colombo, J. F.\inst{1}, Flaccomio, E.\inst{2}}

\institute{University of Rio Negro, UNRN - CONICET, Viedma, R.N., Argentina. \and
  Osservatorio Astronomico di Palermo, Palermo, 90134, Italy.}

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\abstract{The aim of this work is to estimate the uncertainty of the X-ray flux and the stellar parameters that 
are obtained from a set of X-ray spectral fits. We adopted two different X-ray emission models: i) an 
absorbed thermal (APEC) model; ii) a non-thermal (POWER-LAW) model. We use Monte-Carlo (MC)
simulations to construct a set of fake X-ray spectra in the low photon statistic regime, i.e. 10 to 350 
net counts. We initially assume a low source background fraction.
We perform the analysis from the true instrumental responses of Chandra ACIS-I camera, 
to get more than 112000 and 46000 MC simulations of thermal and non-thermal absorbed models, 
respectively. The set of spectra were fitted and analyzed according to a set of input parameters:
source net count of the spectra (net\_cnts) , the stellar-interstellar absorption (N$_{\rm H}$) , and
the X-ray plasma temperature (kT) in thermal models, or the power-law index ($\Gamma$) for 
non-thermal models. 
The spectra were simulated in low photon statistic regime and fitted with a set of different input parameters.
We computed residuals according to the C-statistic minimization criteria to get quantitative estimation 
of the error for spectral parameters and fluxes. We study these errors as a function of the 1$\sigma$ Quantiles
(Q) to perform numerical estimation on how it correlate with different stellar parameters and photon spectra
statistics. We computed bi-dimensional maps of 1$\sigma$ Quantiles in terms of N$_{\rm H}$-kT or
N$_{\rm H}$-$\Gamma$ parameters, according to a source emission from a thermal or non-thermal model, 
respectively. We also fit MC simulated spectra by considering different source background contamination and
bi-dimensional Quantile maps were corrected as a function of the source background fraction. 
We use our results for Cyg\,OB2 sources that were detected in the new Chandra Cygnus OBS Legacy Survey,
to give explicit determination of X-ray flux uncertainty in 1690 X-ray sources detected in the low photon statistic regime.\\
All the results presented here becomes a valuable tool to determine the uncertainty of the X-ray spectral parameters
and flux in faint sources detected or to be detected with the Chandra ACIS-I camera. The on-line implementation 
of these results could be used interactively to compute exposure times for further Chandra ACIS-I proposals.}
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\keywords{Method: X-ray data analysis -- spectral fitting -- statistical -- X-rays: general}


\mail{albacete.facundo@conicet.gov.ar}

\maketitle

\end{document}
