A machine learning approach for GRB detection in AstroSat CZTI data

Abstract

We present a machine learning (ML) based method for automated detection of Gamma-Ray Burst (GRB) candidate events in the range 60 keV - 250 keV from the AstroSat Cadmium Zinc Telluride Imager data. We use density-based spatial clustering to detect excess power and carry out an unsupervised hierarchical clustering across all such events to identify the different light curves present in the data. This representation helps understand the instrument's sensitivity to the various GRB populations and identify the major non-astrophysical noise artefacts present in the data. We use Dynamic Time Warping (DTW) to carry out template matching, which ensures the morphological similarity of the detected events with known typical GRB light curves. DTW alleviates the need for a dense template repository often required in matched filtering like searches. The use of a similarity metric facilitates outlier detection suitable for capturing previously unmodelled events. We briefly discuss the characteristics of 35 long GRB candidates detected using the pipeline and show that with minor modifications such as adaptive binning, the method is also sensitive to short GRB events. Augmenting the existing data analysis pipeline with such ML capabilities alleviates the need for extensive manual inspection, enabling quicker response to alerts received from other observatories such as the gravitational-wave detectors.

arXiv comment9 pages, 7 figures. Matches the published version in MNRAS

References in corpus (18)

• Scikit-learn: Machine Learning in Python
• GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral
• Gravitational Waves and Gamma-rays from a Binary Neutron Star Merger: GW170817 and GRB 170817A
• Collapsars - Gamma-Ray Bursts and Explosions in "Failed Supernovae"
• The Fermi Gamma-Ray Burst Monitor
• An Ordinary Short Gamma-Ray Burst with Extraordinary Implications: Fermi-GBM Detection of GRB 170817A
• Gamma-Ray Bursts as the Death Throes of Massive Binary Stars
• Spectroscopic Discovery of the Supernova 2003dh Associated with GRB 030329
• A `Hypernova' model for SN 1998bw associated with gamma-ray burst of 25 April 1998
• A decade of Gamma-Ray Bursts observed by $Fermi$-LAT: The 2${}^{nd}$ GRB catalog
• In-orbit Calibrations of the Ultra-Violet Imaging Telescope
• Gamma Ray Bursts
• The Cadmium Zinc Telluride Imager on AstroSat
• Transient Classification in LIGO data using Difference Boosting Neural Network
• A tale of two transients: GW170104 and GRB170105A
• Cadmium Zinc Telluride Imager onboard AstroSat : a multi-faceted hard X-ray instrument
• AstroSat CZT Imager observations of GRB 151006A: timing, spectroscopy, and polarisation study
• Central Engine Memory of Gamma-Ray Bursts and Soft Gamma-Ray Repeaters

Cited by in corpus (4)

• A review of unsupervised learning in astronomy
• Improving significance of binary black hole mergers in Advanced LIGO data using deep learning : Confirmation of GW151216
• Application of Deep Learning Methods for Distinguishing Gamma-Ray Bursts from Fermi/GBM TTE Data
• Machine learning prediction for mean motion resonance behaviour -- The planar case