Reliability of in-band and broadband spectral index measurement: systematic study of the effect of signal to noise for uGMRT data

TL;DR

This study systematically evaluates the accuracy of different spectral index measurement methods for uGMRT data, highlighting the reliability of broadband and sub-band methods over in-band techniques at various signal-to-noise ratios.

Contribution

It provides a comprehensive analysis of the reliability of in-band and broadband spectral index estimation methods using simulated uGMRT data, guiding improved observational strategies.

Findings

MT-MFS produces unreliable in-band spectral indices at SNR < 100.

Sub-band splitting yields more accurate in-band spectral indices at similar SNR.

Broadband spectral indices remain reliable at SNR > 15.

Abstract

Low radio frequency spectral index measurements are a powerful tool to distinguish between different emission mechanisms and, in turn, to understand the nature of the sources. Besides the standard method of estimating the ``broadband" spectral index of sources from observations in two different frequency ``bands", if the observations were made with large instantaneous bandwidth, the ``in-band" spectral index can be determined, either using images of emission at multiple frequency ranges within a band or using the novel Multi Term-Multi Frequency Synthesis (MT-MFS) imaging algorithm. Here, using simulated upgraded Giant Metrewave Radio Telescope (uGMRT) data, we have systematically studied the reliability of various methods of spectral index estimation for sources with a wide range of signal-to-noise ratio (SNR). It is found that, for synthetic uGMRT point source data, the MT-MFS imaging algorithm produces in-band spectral indices for SNR~$\lesssim100$ that have errors $\gtrsim 0.2$, making them unreliable. However, at a similar SNR, the sub-band splitting method produces errors $\lesssim 0.2$, which are more accurate and unbiased in-band spectral indices. The broadband spectral indices produce errors $\lesssim 0.2$ even for SNR $\gtrsim 15$, and hence, they are most reliable if there are no higher-order variations in the spectral index. These results may be used to improve the uGMRT observation and data analysis strategies depending on the brightness of the target source.