The Goodness of Simultaneous Fits in ISIS

TL;DR

This paper introduces three methods to evaluate the quality of simultaneous spectral fits in X-ray astronomy, demonstrating their effectiveness in detecting weak features and calibration issues across multiple datasets.

Contribution

It presents novel goodness-of-fit assessment tools for simultaneous spectral fitting, enhancing detection of subtle features in complex datasets.

Findings

Identified calibration features in RXTE spectra of GRO 1008-57.

Detected fluorescent emission lines in Vela X-1 and XTE J1859+083.

Improved detection of weak spectral features through residual stacking.

Abstract

In a previous work, we introduced a tool for analyzing multiple datasets simultaneously, which has been implemented into ISIS. This tool was used to fit many spectra of X-ray binaries. However, the large number of degrees of freedom and individual datasets raise an issue about a good measure for a simultaneous fit quality. We present three ways to check the goodness of these fits: we investigate the goodness of each fit in all datasets, we define a combined goodness exploiting the logical structure of a simultaneous fit, and we stack the fit residuals of all datasets to detect weak features. These tools are applied to all RXTE-spectra from GRO 1008-57, revealing calibration features that are not detected significantly in any single spectrum. Stacking the residuals from the best-fit model for the Vela X-1 and XTE J1859+083 data evidences fluorescent emission lines that would have gone undetected otherwise.