Lia Medeiros, Astrophysicist

NASA Einstein Fellow, Princeton University


I am a computational high-energy astrophysicist interested in compact objects. I see space as the ultimate laboratory where theories can be tested in the most extreme environments imaginable, and compact objects are one of the best examples of this. I'm currently a NASA Hubble Fellowship Program, Einstein Fellow at Princeton University, was a member of the Institute for Advanced Study (IAS) from 2019 to 2023, and was a National Science Foundation (NSF) Astronomy and Astrophysics Postdoctoral Fellow from 2019 to 2022. I am a member of the Event Horizon Telescope Collaboration (EHTC) and much of my work has focused on preparing for these observations, as well as analyzing and interpreting the data. I co-coordinated the Gravitational Physics Inputs Working Group within the EHT for two and a half years and co-coordinated that working group's most ambitious project, the sixth paper in the Sgr A* series. A few of my past and current research projects are highlighted below.

New machine learning algorithm provides a sharper look at the M87 black hole
PRIMO produced image of black hole in M87 galaxyImage credit: Medeiros et al. 2023

After the EHT published the first image of the black hole in the galaxy M87, I was inspired to develop an algorithm that could produce a crisper image. This lead to the development of the machine learning based algorithm PRIMO, which is described below. We used PRIMO to re-analyze EHT data and produced an image that is consistent with the previous EHT image of M87 and achieves the maximum resolution of the array. The ring diameter is consistent with previous publications, but the constraint on the ring width is smaller by a factor of two. The brightness depression at the center is significantly deeper than earlier images. The press release can be found here and the full paper can be found here. The article was also highlighted in a AAS NOVA article, which can be found here.

PCA-based algorithm for interferometric data analysis: PRIMO
Comparison between simulated imagine and its reconstruction using PRIMO Figure from Medeiros et al. 2022

I developed a novel algorithm for interferometric data analysis that uses a large library of high-fidelity general relativistic magnetohydrodynamic plus radiative ray-tracing simulations as a training set. Principal-component interferometric modeling (PRIMO) uses dictionary learning to fill in regions of the Fourier domain where the EHT does not observe. PRIMO produces higher resolution images that are free of artifacts, such as the bright "knots" along the ring in both the M87 and Sgr A* images.

This figure compares a simulated image of a black hole at 1.3 mm wavelength (left) to a PRIMO reconstruction of the image (right). The PRIMO reconstruction is the result of fitting 20 principal components to synthetic data. The data were created by simulating an EHT observation (that mimics the 2017 EHT observations of M87) of the original simulated image.

First resolved image of our black hole (Sgr A*)
Comparison between M87 and Sagittarius A star black hole imagesImage credit: EHT, Lia Medeiros, Randall Munroe.

On May 12, 2022 the EHT published the first image of the black hole at the center of our own galaxy called Sagittarius A * (Sgr A*) in a series of six papers. The papers can be found here and the IAS press release can be found here. I was the co-lead of Paper VI in this series, which focuses on using these new results to test fundamental physics. I discuss some of the main results of this paper in my article entitled "Black Holes as Laboratories" in the Fall 2022 edition of the IAS Institute Letter.

The figure shows the EHT image of the black hole in M87 (left) and the EHT image of the black hole in the center of our own galaxy (Sagittarius A*, Sgr A*, right). The sizes of the images denote their relative size on the sky as seen from the Earth. The Sgr A* image is also shown in the center of the M87 image to scale but is too small to see. I also compare the real size scales of these two black holes with the sizes of orbits and objects in our solar system (inspired by an XKCD comic of the M87 results).

Testing gravity with the EHT
Testing gravity with the EHTLia Medeiros, IAS

In October 2020, my collaborators and I published a new test of gravity using the image of the black hole in M87 (article, EHT press release, IAS press release). This work uses the measured size and uncertainty of the M87 black hole shadow (the shadow that the black hole casts on the surrounding emission) to place constraints on deviations away from the black hole predicted by general relativity. We employ a set of parametrized metrics that deviate from the Kerr metric and use both analytic calculations and geodesic ray-tracing simulations to place constraints on the deviation parameters in these metrics. The simulations used in this paper were originally presented in Medeiros et al. 2020

The interactive plots at the bottom of this webpage show how the observer's inclination, the black hole's spin, and different deviation parameters affect the size and shape of the black hole shadow.

First M87 EHT Results
Testing gravity with the EHTEvent Horizon Telescope Collaboration

The Event Horizon Telescope (EHT) is a Very Long Baseline Interferometer (VLBI) that consists of several radio telescopes spread all over the world. The EHT performed its first observations in early 2017 and the first results, the first image of a black hole at event-horizon scale resolution, were published on April 10th, 2020.

As a member of the EHT I contributed to several different aspects of this project including running simulations to predict and understand what the EHT observes, imaging, and model comparison.

Links to papers
Original Press Release
Variability and Principal Components Analysis

I've been using general relativistic magnetohydrodynamic (GRMHD), plus radiative transfer simulations of hot plasma falling into supermassive black holes, to try to understand how the intrinsic variability from the source will affect the EHT data. Furthermore, we want to understand how we can use this variability to learn more about accretion physics and general relativity see e.g. Medeiros et al. 2017, Medeiros et al. 2018.

I also explored the use of principal components analysis (PCA) to characterize and understand the variability in GRMHD simulations and to identify the images that are unusual (or outliers) within a set of images. This work was highlighted in a AAS Nova article, and the original paper can be found here.

About me

Lia Medeiros HeadshotDan Komoda, Institute for Advanced Study

I am currently a NASA Hubble Fellowship Program, Einstein Fellow at Princeton University. Previously, I was member of the IAS (2019-2023), and was an NSF Astronomy and Astrophysics Postdoctoral Fellow 2019-2022. I completed my undergraduate education at the University of California-Berkeley in Physics and Astrophysics, class of 2013. I then received my Masters and PhD (2019) in Physics from the University of California-Santa Barbara. After completing my classes in Santa Barbara, I took advantage of the flexibility allowed by an NSF Graduate Research Fellowship and spent three years at the Steward Observatory at The University of Arizona and one year at the Black Hole Initiative at Harvard. My PhD thesis was completed in collaboration with University of Arizona Professors Feryal Özel and Dimitrios Psaltis.

I was born in Rio de Janeiro, Brazil and spent most of my childhood living in several cities in Brazil and a few years in Cambridge, England. One of the highlights of my career has been having the opportunity to engage with the scientific community in Brazil. I've given many talks in Brazil to both academic and public audiences in both English and Portuguese. When I'm not simulating supermassive black holes, I love horseback riding, practicing aerial silks, salsa dancing, and almost any type of art, especially ceramics and drawing.


Getting others excited about physics and astronomy is one of my favorite things. To me black holes are just about the coolest things out there and I love sharing my enthusiasm with others. I frequently give public talks and really enjoy visiting classrooms. If you would like me to come to your classroom or event send me an email at lmedeiros AT I include a few links to talks I've given below.

Public Talks
Public Talks in Portuguese
Science Talks
Outreach Materials

Interactive Shadows Plots

Plots are not mobile compatible. Please use a laptop or desktop for the full experience.


Astrophysical black holes are expected to be described by the Kerr solution to Einstein's equations. Kerr black holes have mass and spin but do not have a charge, astrophysical black holes are not expected to have a significant charge. The size and shape of the black hole shadow of the Kerr black hole will depend on the spin of the black hole and the inclination angle, the angle between the observer's line of sight and the spin axis of the black hole.


The Johannsen and Psaltis metric (2011, JP) also deviates from the Kerr black hole metric. You can increase the deviations by increasing the α2,2 and α1,3 parameters below.


= 0.1
= 10
= 0
= 0
*These graphics are only approximate, the original shadows were used in the paper


The Modified Gravity Bumpy Kerr metric by Vigeland et al. (2011, MGBK) also deviates from Kerr black hole. You can increase the deviations by increasing the γ3,1, γ3,3, γ1,2, and γ4,2 parameters below.


= 0.1
= 10
= 0
= 0
= 0
= 0
*These graphics are only approximate, the original shadows were used in the paper