Geometrical model fitting for interferometric data: GEM-FIND

TL;DR

GEM-FIND is a software tool that fits geometrical models to interferometric data to analyze the morphology and brightness distribution of astronomical objects, assessing the stability of parameter estimation under various observational conditions.

Contribution

The paper introduces GEM-FIND, a new tool for fitting geometrical models to interferometric data and evaluates its stability with synthetic datasets.

Findings

Parameter determination stability depends on uv-point number

Distribution of uv-plane points affects fitting accuracy

Noise level impacts the reliability of model fitting

Abstract

We developed the tool GEM-FIND that allows to constrain the morphology and brightness distribution of objects. The software fits geometrical models to spectrally dispersed interferometric visibility measurements in the N-band using the Levenberg-Marquardt minimization method. Each geometrical model describes the brightness distribution of the object in the Fourier space using a set of wavelength-independent and/or wavelength-dependent parameters. In this contribution we numerically analyze the stability of our nonlinear fitting approach by applying it to sets of synthetic visibilities with statistically applied errors, answering the following questions: How stable is the parameter determination with respect to (i) the number of uv-points, (ii) the distribution of points in the uv-plane, (iii) the noise level of the observations?