Photometric Redshift Estimation for Gamma-Ray Bursts from the Early Universe

TL;DR

This paper evaluates the effectiveness of photometric methods to accurately identify high-redshift gamma-ray bursts in the early universe, crucial for guiding follow-up observations and understanding cosmic evolution.

Contribution

It introduces a simulation-based assessment of photometric redshift estimation for GRBs, analyzing false positive rates and the impact of host galaxy extinction on high-redshift identification.

Findings

Achieves 82-88% completeness in high-redshift GRB detection.

Maintains over 84% purity, with false alarms below 1 per 500 detections.

Demonstrates the effectiveness of optimized priors in reducing false positives.

Abstract

Future detection of high-redshift gamma-ray bursts (GRBs) will be an important tool for studying the early Universe. Fast and accurate redshift estimation for detected GRBs is key for encouraging rapid follow-up observations by ground- and space-based telescopes. Low-redshift dusty interlopers pose the biggest challenge for GRB redshift estimation using broad photometric bands, as their high extinction can mimic a high-redshift GRB. To assess false alarms of high-redshift GRB photometric measurements, we simulate and fit a variety of GRBs using phozzy, a simulation code developed to estimate GRB photometric redshifts, and test the ability to distinguish between high- and low-redshift GRBs when using simultaneously observed photometric bands. We run the code with the wavelength bands and instrument parameters for the Photo-z Infrared Telescope (PIRT), an instrument designed for the Gamow mission concept. We explore various distributions of host galaxy extinction as a function of redshift, and their effect on the completeness and purity of a high-redshift GRB search with the PIRT. We find that for assumptions based on current observations, the completeness and purity range from $\sim 82$ to $88\%$ and from $\sim 84$ to $>99\%$, respectively. For the priors optimized to reduce false positives, only $\sim 0.6\%$ of low-redshift GRBs will be mistaken as a high-redshift one, corresponding to $\sim 1$ false alarm per 500 detected GRBs.