Symphy 2025 posters

The poster presents the first complete X-ray fluorescence (XRF) line ratios map of the lunar surface, derived from Chandrayaan-2 data. By analyzing XRF emissions, the study provides insights into the Moon’s elemental composition, independent of solar flux variations. A novel detection algorithm using the CLASS spectrometer enables accurate mapping, accounting for dynamic background effects such as solar flares and geotail influences. Gaussian Mixture Models (GMM) are employed to cluster compositional data, distinguishing lunar regions like Maria, highlands, and transition zones. This work enhances our understanding of lunar crust formation and elemental distribution.

This poster won an award for the best poster at Symphy 2025.

We present an improved pipeline for detecting fast transients using AstroSat's CZTI (Cadmium Zinc Telluride Imager), focusing on Gamma-Ray Bursts (GRBs), electromagnetic counterparts to gravitational wave sources, and Fast Radio Bursts (FRBs). Two search methods are employed:

• Triggered Search: Responds to external alerts from missions like Fermi and LIGO-Virgo

• Blind Search: Scans all CZTI data for transients 

CIFT uses multiple algorithms (SumThreshold, NSigma, TopN, and CumSum) across different energy bands. The automated pipeline ensures rapid response times, crucial for early follow-up observations. Since 2015, around 700 GRBs have been detected, comparable to Swift-BAT. Future plans involve running searches on over a decade of CZTI data to uncover previously missed faint transients.

This poster won an award for the best poster at Symphy 2025.

The poster introduces PolPy, a universal tool for hard X-ray gamma-ray burst (GRB) polarimetry, designed to standardize and streamline polarization analysis. Polarization studies provide insights into radiation sources, magnetic field alignment, and emission mechanisms beyond spectral studies. However, GRB polarimetry faces challenges due to low Compton efficiency, statistical uncertainties, and inconsistent data formats across instruments. PolPy addresses these issues by using a standardized file format, modular functions for time- and energy-resolved analysis, and compatibility with the 3ML framework for multi-instrument parameter inference. Several current and upcoming space-based polarimeters, including India's AstroSat and Daksha, plan to adopt PolPy for enhanced collaboration and comparative studies.

This poster won an award for the best poster at Symphy 2025.

We introduce a new concept of a semi-transparent Coded Aperture Mask (CAM) for Daksha, a pair of satellites designed to monitor high-energy transients like Gamma-Ray Bursts (GRBs) across the 1-1000 keV range. The workhorse for Daksha are the Medium Energy Detector Packages (MEPs) that operate in the 20-200 keV energy range. This novel CAM design uses a 1 mm iron layer to absorb low-energy photons (20-50 keV) for precise localization while allowing high-energy photons to pass through for spectroscopy and polarization studies. The CAM design is based on Uniform Redundant Arrays for accurate sky imaging. The localisation algorithms used, achieve good source recovery with minimal contamination. This approach enhances Daksha’s ability to study electromagnetic counterparts of gravitational wave sources and GRB emissions.

The poster details the characterization of the GROWTH-India Telescope (GIT) and its CCD camera, which has been operational since 2018 at the Indian Astronomical Observatory, Hanle. The study focuses on camera properties such as gain, read noise, and thermal noise, using flat frames, bias, and dark frames for calibration. Bad pixels are identified and masked using a thresholding technique. The focus loop script is refined by analyzing median FWHM vs. focuser values to optimize image sharpness, improving the telescope’s ability to detect faint objects. Future work includes refining focus algorithms and determining atmospheric extinction coefficients for different filters.

The poster presents a novel method to determine asteroid rotation rates using fast-moving streaks in sky survey data, focusing on Near-Earth Asteroids (NEAs). Traditional asteroid tracking is resource-intensive, making wide-field sky surveys like the Zwicky Transient Facility (ZTF) more efficient for detecting thousands of NEAs nightly. By analyzing variations in brightness along asteroid streaks, the study extracts photometric data to infer rotation rates and surface features. A custom asteroid filtering protocol applied to 35,000 candidates yielded 7,482 unique detections, with an average of 6 observations per asteroid. Preliminary results demonstrate successful flux variation extraction, though further work is needed to derive rotation periods. Future directions include periodogram analysis, correlations with physical properties, and mass-strength relationships for small bodies.

The poster presents a machine learning (ML)-based pipeline for real-bogus classification of transient events detected by the GROWTH-India Telescope (GIT). Transients, such as supernovae, kilonovae, and gamma-ray bursts (GRBs), provide crucial insights into cosmology and stellar evolution but are often obscured by false detections caused by noise and artifacts. To address this, the ML pipeline automates transient classification, improving efficiency over manual vetting. The model achieves 99.14% training accuracy and 94.82% test accuracy, using a convolutional neural network (CNN) to classify sources. Challenges include limited real data, requiring synthetic injections, and bogus diversity, where noise mimics real transients. Future improvements focus on refining classification robustness and integrating larger datasets.

The poster discusses the localization of Gamma-Ray Bursts (GRBs) using the AstroSat Cadmium Zinc Telluride Imager (CZTI). GRBs are highly energetic cosmic explosions that emit gamma-ray photons, and their precise localization is crucial for discovering and studying the multiwavelength properties of their afterglows. AstroSat CZTI has detected close to 700 GRBs in the "Hard X-ray" regime (20–200 keV). This study uses a Mass Model simulation of AstroSat, generating Detector Plane Histograms (DPHs) to compare simulated and observed GRB patterns. A χ² minimization approach determines the most probable source location, while enclosed probability contours estimate localization accuracy. As expected, brighter GRBs are localised better. The focus of this study is to extend the localisation abilities to fainter bursts.