Reggie Bernardo

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Reggie Bernardo

Say Hi (  Email /  Twitter )

Your Friendly Neighborhood Cosmologist

Senior Scientist at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute)

Contents:

Contents:

Minimalistic — Theme by vaibhavvikas

At a glance 52 papers and preprints since 2014 43 as first author 3 public codes Most published in Physical Review D and Journal of Cosmology and Astroparticle Physics
Research CV GitHub INSPIRE ORCID Google Scholar Email

Interests (astro-ph.CO/astro-ph.HE/gr-qc)

Gravitational Waves, Gravity, Cosmology, Machine Learning, Data Analysis, Dark Energy

Highlights

Codes:

Selected Papers:

Full publication list at Inspire HEP, ORCID, and Google Scholar, or my CV.

Slideshow
Binned timing-residual variance of a pulsar timing array compared with the best-fit stochastic gravitational wave background signal
Signal of a stochastic gravitational wave background in the timing residuals in a pulsar timing array (arXiv:2409.01218)
Inter-pulsar correlation curve induced by a stochastic gravitational wave background, with cosmic variance
SGWB-induced inter-pulsar correlations with cosmic variance (arXiv:2209.14834)
Hubble expansion rate reconstructed from observational data with Gaussian processes
Hubble expansion rate reconstructed from observational data via Gaussian Processes (arXiv:2105.12970)
Hubble rate evolution in a well-tempered cosmology reaching the same de Sitter final state from different initial conditions
Well tempering: a de Sitter final state independent of the initial conditions and the CC (arXiv:2107.08762)


Research Statement

I study what the nanohertz gravitational wave sky and the timing of pulsars can tell us about gravity and the Universe. A pulsar timing array turns the Galaxy into a gravitational wave detector, but a faint correlated signal buried in irregular timing data is only as trustworthy as our understanding of the processes that shape the data. My work addresses both sides of this problem: how gravity and cosmology imprint themselves on the correlations between pulsars, and how the stochastic behavior of the pulsars themselves must be modeled before a signal can be claimed.

My path to this question went through gravity and cosmology. I started with theories of gravity beyond general relativity, studying self-tuning and well-tempered cosmologies and black holes and their perturbations in Horndeski theories, and then turned to data-driven reconstructions of the expansion history with Gaussian processes and approximate Bayesian computation. These threads share one habit and asks what a model predicts, then what the data can actually support. Pulsar timing arrays are a natural place to apply it, because the cosmology lives in the correlations and the statistics are the experiment.

In pulsar timing, my work has followed the signal from prediction to test: inter-pulsar correlations beyond the Hellings-Downs curve, including non-Einsteinian polarizations; the pulsar and cosmic variances of these correlations; simulations of Gaussian background signals; and tests of whether the background is Gaussian. More recently I have turned to the pulsar side, namely spin noise, stationarity, angular momentum conservation, and the non-stationarity that observations themselves induce in timing residuals. Non-stationarity is not a flaw to be hidden; it is a property of the data that has to be identified and interpreted, and it bears directly on how well arrays can separate astrophysical noise from a gravitational wave background.

A promising direction is to bring the cosmological and the pulsar sides into one statistical framework, so that a detection, a non-detection, and a test of gravity all rest on the same model of the data. I also develop open-source tools for this work, such as PTAfast and cosmo-learn, and I enjoy mentoring students who are learning to do the same.

Leadership and Service

Experience

Education: University of the Philippines Diliman, Quezon City 1101, Philippines

Awards

Miscellaneous

Languages: English (fluent), Filipino (mother tongue)
Coding: Command Line, Python, Mathematica, LaTeX

Community Involvement

Referee: PRL, PRD, JCAP, CQG, Phys. Dark Universe, EPJC, Astron. Comput., MNRAS, ApJ, MPLA, Chinese J. Phys., Sci. Rep., GRG, JKPS, Proceedings of the Physics Society of the Philippines, Philippine Journal of Science

Editor: Proceedings of the Physics Society of the Philippines

Member: CosmoVerse COST Action—Data Analysis and Fundamental Physics Working Groups; SKAO—Pulsars and Cosmology Science Working Groups