Proper evaluation of spatially correlated noise in interferometric images

TL;DR

This paper introduces a method to accurately evaluate statistical uncertainties caused by spatially correlated noise in interferometric images, improving analysis of astronomical data from modern telescopes.

Contribution

It presents a novel approach to estimate uncertainties and simulate correlated noise directly from the noise autocorrelation function in interferometric images.

Findings

Effective estimation of statistical uncertainty in flux and spectra.

Simulation of correlated noise for Monte Carlo analysis.

Applicable to various astronomical imaging methods.

Abstract

Recent interferometers (e.g. ALMA and NOEMA) allow us to obtain the detailed brightness distribution of the astronomical sources in 3 dimension (R.A., Dec., frequency). However, the interpixel correlation of the noise due to the limited uv coverage makes it difficult to evaluate the statistical uncertainty of the measured quantities and the statistical significance of the obtained results. The noise correlation properties are characterized by the noise autocorrelation function (ACF). We will present the method for (1) estimating the statistical uncertainty due to the correlated noise in the spatially integrated flux and spectra directly from the noise ACF and (2) simulating the correlated noise to perform a Monte Carlo simulation in image analyses. Our method has potential applications to a range of astronomical images of not only interferometers but also single dish mapping observation and interpolated and resampled optical images.