SED_Tools is a sofware suite to provide easy attainment, manipulation and creation of synthetic photometry data products
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Updated
Jul 23, 2026 - Jupyter Notebook
SED_Tools is a sofware suite to provide easy attainment, manipulation and creation of synthetic photometry data products
slcomp: compilation of strong lensing objects
This repository contains files related to the Python programming workshop conducted for astrophysics and cosmology work at Nagpur. The repository includes sample codes, datasets, and presentations used during the workshop. These materials can be useful for beginners who want to learn Python programming for astrophysics and cosmology work.
It is an astrophysical data analytics project, which I did with MySQL. The project was a graded by Sebastien Derriere of the Strasbourg Astronomical Observatory.
Routine used to correct the 1/f correlated noise observed in the detector images of the JWST instruments
Collection of all Segmented Spacetime (SSZ) plots used in the current papers
A toolkit for efficient compression and analysis of redshift probability distribution functions
HECAT3KG X3ML & RML Mappings
A dashboard web application for visualizing astrophysics data, to aid in exoplanets discovery. Uses Plotly Dash, Pandas and Flask, styled with Bootstrap 5.
Demonstration of comprehensive machine learning analysis in iPython of the quasar candidates catalog by Richards et al., ApJS 219 (2015).
Coursework written for: Astrophysical Data Reduction and Analysis Techniques, MASS course offered at the University of Belgrade
📊 Generate and validate segmented spacetime zone plots using peer-reviewed data for enhanced analysis and visualization in research contexts.
Code for Renzo et al. 2019 - Space astrometry of the very massive 150 Msun candidate runaway star VFTS682
This repository contains two astronomy research projects developed during Data-Driven Astronomy Internship at India Space Academy – Summer School 2025 and uploaded to GitHub subsequently for documentation, reproducibility, and portfolio purposes, with both projects applying observational data analysis.
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