X-ray: Generate and Analyse (XGA) provides a Python interface to high-energy astrophysics data product generation and analysis, enabling large scale interactive/scripted exploration of X-ray sources. XMM, eROSITA, and Chandra (partial) are supported. Product classes provide powerful Python interfaces with high-energy data products.

The Galaxy Cluster ‘Pypeline’ for X-ray Temperature Maps

Tools for analyzing galaxy clusters.

Python routines for computing Navarro-Frenk-White halo properties

Joint X-ray and SZ data fitting code for galaxy clusters in Python

Pressure Profile Fitter for galaxy clusters in Python

Likelihood Inference Neural Network Accelerator

Codes used in a wide variety of astronomy/astrophysics

Astronomical X-ray sources surface brightness profile fitting package

The Outer Stellar Mass of Massive Galaxies: A SimpleTracer of Halo Mass with Scatter Comparable to Richnessand Reduced Projection Effects

Simulation of metal diffusion in the ICM for the Perseus Cluster The aim of the project is to show the possible parameters for efficient metal distribution under reasonable diffusion timescales to reproduce observed abundance profile.

Friends-of-friends algorithm used to find galaxy clusters.

Algorithm to classify galaxy clusters using various architectures: CNN, MLP and Transformer - and to compare their efficiencies on the infrared (IR) data of the WISE survey (W1, W2 bands) and the microwave data of ACT+Planck (f90, f150, f220 frequencies)

University of Nottingham 3rd Year Astrophysics Project - Searching for Galaxy Clusters in the Dark Energy Survey

Package to measure and model weak gravitational lensing by sattelite galaxies in galaxy clusters

Repository for suppelementary material from my publications on the entropy core problem

a galaxy cluster SZ catalogue obtained in directions of SZcat by applying deep learning method to ACT+Planck maps to detect Sunyaev-Zeldovich effect

Fast simulations of Sunyaev-Zeldovich galaxy clusters

Website do grupo de pesquisa: IAG Machine Learning - Sistemas inteligentes para descoberta em astronomia. Instituto de Astronomia, Geofísica e Ciências Atmosféricas da Universidade de São Paulo - IAG/USP. Para acessar o código fonte do website, acesse: https://github.com/iagml/website. Este repositório possui apenas código gerado.