Tutorial notebooks of the course "Introduction to AGNs" at the University of Belgrade in Spring 2023. Instructors: Dragana Ilic, Isidora Jankov

Dipp - distributed image processing pipeline with various distribution methods

This repository contains the code and data for the Astronomical Object Classification Project. The project focuses on classifying celestial objects (stars, galaxies, and quasars) based on their spectral characteristics using data from the Sloan Digital Sky Survey (SDSS).

asteroid detection from Sloan Digital Sky Survey (SDSS) images (ALPHA - unstable under development)

LVM spectral pipeline (based off DESI)

Calculate Anomalously Low Metallicity (ALM) spaxels and galaxies using MaNGA data. Find the relation between HI gas and ALM.

Classify stars, galaxies, and quasars with SDSS DR16 data. Balanced dataset using resampling techniques improves AdaBoost classifier's performance, enhancing astronomical object classification accuracy.

Phosphorpy is python package to mine multiple databases with astronomical data

General DESI utilities, shell scripts, desiInstall, etc.

Quick simulations of spectrograph response

All code to reproduce results from "Validation of the Bond et al. (2010) SDSS-derived kinematic models for the Milky Way's disk and halo stars with Gaia Data Release 3 proper motion and radial velocity data"

Repo for a Data analysis project to find Distances, Luminosities, Fluxes, Star Formation Rates, and WISE image processing for galaxies in the MaNGA survey.

MaNGA plate design utilities

Double Nuclei Galaxy Finder from SDSS. Check https://arxiv.org/abs/2011.12177

GaMorNet is a CNN based on AlexNet to classify galaxies morphologically

SDSS observer graphical interface

This project is a full machine learning pipeline for Star/Galaxy classification using the SDSS dataset. It also contains a detailed report on the development and a DockerFile to easily replicate the results.

The MCP