Moreover, thanks to simulation reuse enabled by SBI, they could perform the combined analysis using *zero* calls to a Boltzmann solver

To illustrate their method, they combine the full Planck CMB likelihoods with a 3x2pt simulator for a Stage IV galaxy survey (e.g. Euclid), and test evolving dark energy. They find that future 3x2pt data *alone* could detect dynamical dark energy preferred by DESI at the *5sigma* level

Looking for a summer read? Check out this new GRAPPA paper! arxiv.org/abs/2507.22990 The authors introduce a simple method to construct an effective simulator for *any* explicit likelihood, using samples from a previous MCMC

Huge congratulations to Dr. Uddipta Bhardwaj, who successfully defended his PhD thesis "Sequentially learning Gravity" on the 19th of May 2025 🥳

Applying it to the case of dark matter (DM) spikes around massive black holes (BHs), they show that a fully relativistic treatment is needed to accurately model the environmental dephasing of gravitational wave (GW) signals from EMRIs

New GRAPPA paper! arxiv.org/abs/2505.097...
The authors (Rodrigo Vicente, Theophanes Karydas, @gfbertone.bsky.social) introduce a relativistic framework to model environmental effects on extreme mass-ratio inspirals (EMRIs) in collisionless media

Today we had a fantastic Colloquium by Dr. Malcolm Fairbairn (@KingsCollegeLon) to tell us about "Galaxies, Axions, Gravitational Waves, Black Holes and More Galaxies"

It's a real pleasure to have Dr. Jonathan Gair (@mpi_grav) giving the GRAPPA Colloquium today, to tell us about "Opportunities and challenges in SBI for future gravitational wave detectors"

Celebrating the start of the year with our fantastic GRAPPA members 🥂🥳🎉

Inspiring and wonderful article about former GRAPPA PhD student Gimmy Tomaselli on dutch newspaper NRC. Congratulations!
www.pressreader.com/netherlands/...

Paper alert!
The authors introduce a fast and accurate method to reconstruct the cosmological initial conditions from present-day dark matter density fields, including uncertainty quantification!
arxiv.org/abs/2410.15808
Led by GRAPPA PhD Oleg Savchenko

As an application to non-gaussian posteriors, the authors also test a model of 2-body decaying dark matter, finding that Stage IV surveys can improve current bounds by up to 1 order of magnitude!

They are able to recover the posterior distribution of all parameters with a speedup factor of ~40-60 compared to MCMC!

New GRAPPA paper!
arxiv.org/abs/2403.14750
The authors show the first application of Marginal Neural Ratio Estimation (MNRE) to accelerate parameter inference from upcoming Stage IV photometric surveys (like Euclid or LSST)

Celebrating and sharing the New Year with our fantastic GRAPPA members 🎉🎉🎉

Check out the new poetic-philosophical documentary "Neutrino", with the participation of GRAPPA member Patrick Decowski! More info at neutrinofilm.nl