Data access and visualization for MaNGA. http://sdss-marvin.readthedocs.io/en/latest/

Materials for SDSS 2019, Bellevue WA

Estimating galaxy gas mass fractions using SDSS imaging

Risk Changes SDSS development page

Using SDSS imaging to predict galaxy metallicity. Maintained by @jwuphysics @boada

Retrieve and analysis data from SDSS (Sloan Digital Sky Survey)

The SDSS Python template and coding standards.

SDSS observer graphical interface

A tutorial on classification and photometric redshift regression of astronomical sources using supervised machine learning techniques.

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).

Using machine learning to predict the mass of quasar supermassive black holes

Curve fitting routines for astrophysical (SDSS) spectrographs

The Brain™ of Marvin.

FIREFLY is a chi-squared minimisation full fitting code for deriving stellar population properties from spectra. It fits combinations of single-burst stellar population models using the Bayesian Information Criterion and returns light- and mass-weighted ages, metallicities, dust attenuation, stellar mass, and star formation histories.

TensorFlow implementations of a Restricted Boltzmann Machine and an unsupervised Deep Belief Network, including unsupervised fine-tuning of the Deep Belief Network.

The Illustris Virtual Observatory is an expanded iteration of the Sunpy module(ptorrey) for creating synthetic SDSS, HST, or JWST images of galaxies from the Illustris simulation. For instructions on how to install/use this program, please go to this address:

Modeling tools for SDSS/APOGEE spectra

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

A selection of workbooks to analsyse SDSS data

GaMorNet is a CNN based on AlexNet to classify galaxies morphologically

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.

Product for managing the SDSS environment tree

Empirical PSFs of GALEX, SDSS, and 2MASS

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

Modular toolkit for efficient bulk downloading and management of SDSS spectra and imaging data, starting with a multithreaded downloader.

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

Stellar object classification pipeline on SDSS17 (Star/Galaxy/QSO).

Translation and optimisation of SEDMORPH's PawlikMorph IDL code for analysing images of galaxies from SDSS data release 7

Comparative study of AGN host galaxies in SDSS DR7 and IllustrisTNG, focused on green valley demographics and sSFR offsets.

Image API implementation for acquiring SDSS image based on location