A novel approach to detect line emission under high background in high-resolution X-ray spectra

TL;DR

This paper introduces a new statistical method for detecting emission lines in high-resolution X-ray spectra with high background noise, demonstrated on Chandra data, successfully identifying known features and setting limits on others.

Contribution

The paper presents a novel statistical approach combining smooth tests and likelihood ratio tests for emission line detection in high-background spectra, accounting for multiple comparisons.

Findings

Successfully detected known Fe emission lines in Chandra data.

Placed upper limits on undetected thermal emission lines.

Serendipitously discovered a new spectral line at 16.93 Å.

Abstract

We develop a novel statistical approach to identify emission features or set upper limits in high-resolution spectra in the presence of high background. The method relies on detecting differences from the background using smooth tests and using classical likelihood ratio tests to characterise known shapes like emission lines. We perform signal detection or place upper limits on line fluxes while accounting for the problem of multiple comparisons. We illustrate the method by applying it to a Chandra LETGS+HRC-S observation of symbiotic star RT Cru, successfully detecting previously known features like the Fe line emission in the 6-7 keV range and the Iridium-edge due to the mirror coating on Chandra. We search for thermal emission lines from Ne X, Fe XVII, O VIII, and O VII, but do not detect them, and place upper limits on their intensities consistent with a $\approx$1 keV plasma. We serendipitously detect a line at 16.93 $\unicode{x212B}$ that we attribute to photoionisation or a reflection component.