A systematic fitting scheme for caustic-crossing microlensing events

N. Kains  ...[et al]; Uffe Gråe Jørgensen

doi:10.1111/j.1365-2966.2009.14615.x

A systematic fitting scheme for caustic-crossing microlensing events

N. Kains ...[et al], Uffe Gråe Jørgensen

12 Citationer (Scopus)

Abstract

We outline a method for fitting binary-lens caustic-crossing microlensing events based on the alternative model parametrization proposed and detailed by Cassan. As an illustration of our methodology, we present an analysis of OGLE-2007-BLG-472, a double-peaked Galactic microlensing event with a source crossing the whole caustic structure in less than three days. In order to identify all possible models we conduct an extensive search of the parameter space, followed by a refinement of the parameters with a Markov Chain Monte Carlo algorithm. We find a number of low-chi(2) regions in the parameter space, which lead to several distinct competitive best models. We examine the parameters for each of them, and estimate their physical properties. We find that our fitting strategy locates several minima that are difficult to find with other modelling strategies and is therefore a more appropriate method to fit this type of event.

Originalsprog	Engelsk
Tidsskrift	Royal Astronomical Society. Monthly Notices
Vol/bind	395
Udgave nummer	2
Sider (fra-til)	787-796
Antal sider	9
ISSN	0035-8711
DOI	https://doi.org/10.1111/j.1365-2966.2009.14615.x
Status	Udgivet - 11 maj 2009

Adgang til dokumentet

10.1111/j.1365-2966.2009.14615.x

Citationsformater

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title = "A systematic fitting scheme for caustic-crossing microlensing events",

abstract = "We outline a method for fitting binary-lens caustic-crossing microlensing events based on the alternative model parametrization proposed and detailed by Cassan. As an illustration of our methodology, we present an analysis of OGLE-2007-BLG-472, a double-peaked Galactic microlensing event with a source crossing the whole caustic structure in less than three days. In order to identify all possible models we conduct an extensive search of the parameter space, followed by a refinement of the parameters with a Markov Chain Monte Carlo algorithm. We find a number of low-chi(2) regions in the parameter space, which lead to several distinct competitive best models. We examine the parameters for each of them, and estimate their physical properties. We find that our fitting strategy locates several minima that are difficult to find with other modelling strategies and is therefore a more appropriate method to fit this type of event. ",

author = "{Kains ...[et al]}, N. and J{\o}rgensen, {Uffe Gr{\aa}e}",

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T1 - A systematic fitting scheme for caustic-crossing microlensing events

AU - Kains ...[et al], N.

AU - Jørgensen, Uffe Gråe

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N2 - We outline a method for fitting binary-lens caustic-crossing microlensing events based on the alternative model parametrization proposed and detailed by Cassan. As an illustration of our methodology, we present an analysis of OGLE-2007-BLG-472, a double-peaked Galactic microlensing event with a source crossing the whole caustic structure in less than three days. In order to identify all possible models we conduct an extensive search of the parameter space, followed by a refinement of the parameters with a Markov Chain Monte Carlo algorithm. We find a number of low-chi(2) regions in the parameter space, which lead to several distinct competitive best models. We examine the parameters for each of them, and estimate their physical properties. We find that our fitting strategy locates several minima that are difficult to find with other modelling strategies and is therefore a more appropriate method to fit this type of event.

AB - We outline a method for fitting binary-lens caustic-crossing microlensing events based on the alternative model parametrization proposed and detailed by Cassan. As an illustration of our methodology, we present an analysis of OGLE-2007-BLG-472, a double-peaked Galactic microlensing event with a source crossing the whole caustic structure in less than three days. In order to identify all possible models we conduct an extensive search of the parameter space, followed by a refinement of the parameters with a Markov Chain Monte Carlo algorithm. We find a number of low-chi(2) regions in the parameter space, which lead to several distinct competitive best models. We examine the parameters for each of them, and estimate their physical properties. We find that our fitting strategy locates several minima that are difficult to find with other modelling strategies and is therefore a more appropriate method to fit this type of event.

U2 - 10.1111/j.1365-2966.2009.14615.x

DO - 10.1111/j.1365-2966.2009.14615.x

M3 - Journal article

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