A python package for Bayesian inference of gravitational-wave data

The vault of references of Megrez Lu in BibLaTeX

Supplementary materials for our GW-GRB search of the first observing run of advanced LIGO.

First Open Gravitational-wave Catalog of Compact Binary Mergers from Advanced LIGO's first observing run.

Candidates from the O1 + O2 search for eccentric binary neutron star mergers

How heavy are Neutron Stars in binary systems within our Galaxy? A demonstration of how bayesian inference and nested sampling allows us to explore the mass distributions of Galactic Double Neutron Star systems.

A repository for my PhD thesis "Modeling the (proto)neutron star crust: toward a controlled estimation of uncertainties"

Mitigation of periodic as well as narrow-band and spiky/bursty RFI from time-domain filterbank data.

Second Open Gravitational-wave Catalog of Compact Binary Mergers. Parameter estimates for O1 and O2 mergers. Sub-threshold BNS/NSBH/BBH candidates.

This will be the first official public release of the VItamin code base. VItamin is a python package for producing fast gravitational wave posterior samples.

My first intership about the inside properties of neutron stars

General-relativistic ray-tracing package for axisymmetric metrics aimed at describing the exterior spacetime around a neutron star

Binary Neutron Star Remnants: the most extreme matter in the Universe. This is the repo for my PhD thesis which has been examined and passed.

Third Open Gravitational-wave Catalog of Compact Binary Mergers. Using the data from LIGO and Virgo from 2015-2019, a comprehensive catalog including 57 detected mergers (55 BBH, 2 BNS) and sub-threshold candidates throughout O1, O2, and O3a.

Rust port of the RNS C code. This code calculates the rotation profiles of rapidly rotating neutron stars.

Python package for solving TOV equation and calculating tidal properties

Predictions for LISA detectable BH and NS binaries - Wagg et al. (2022)

Inferring the Dense Matter Equation of State from Neutron Star Observations via Artificial Neural Networks

Pulsar classification app using supervised learning

Constructs neutron star models in the context of Damour-Esposito-Farese (DEF) scalar tensor theory and R^2 gravity model.