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astro-ph.CO2026
ROBIN-PIP: Robust Bayesian Field-Level Inference with Physics-Informed Priors
Ludvig Doeser, Simon Ding, Guilhem Lavaux +1
Accurately extracting information from galaxy surveys, particularly at non-linear scales, requires increasingly complex and flexible forward models of the observed galaxy distribut…
astro-ph.CO2026
Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions
Ludvig Doeser, Jens Jasche
Accurate posterior estimation is central to scientific inference, as uncertainties determine what can be reliably learned from observational data. While Markov chain Monte Carlo me…
astro-ph.CO2026
The Manticore Project II: Bayesian digital twins of cosmic structure across the SDSS and BOSS volumes
Stuart McAlpine, Jens Jasche, Guilhem Lavaux +2
We present Manticore-Deep, a high-resolution Bayesian field-level reconstruction of cosmic large-scale structure over a comoving volume of to $z\approx…