5 papers
Interpreting map-based / spectral properties of CMB foregrounds
Gilles Weymann-Despres, Léo Vacher, Léo Vacher +6
Map-space / decompositions of linear polarization are attractive for foreground and CMB analyses because they separate parity families: -family patterns directly contamina…
Modeling Foreground Spatial Variations in 21 cm Gaussian Process Component Separation
Kangning Diao, Richard D. P. Grumitt, Yi Mao
Gaussian processes (GPs) have been extensively utilized as nonparametric models for component separation in 21 cm data analyses. This exploits the distinct spectral behavior of the…
: A Differentiable and GPU-accelerated Synchrotron Simulation Package
Kangning Diao, Zack Li, Richard D. P. Grumitt +1
We introduce synax, a novel library for automatically differentiable simulation of Galactic synchrotron emission. Built on the JAX framework, synax leverages JAX's capabilities, in…
Sequential Kalman Tuning of the -preconditioned Crank-Nicolson algorithm: efficient, adaptive and gradient-free inference for Bayesian inverse problems
Richard D. P. Grumitt, Minas Karamanis, Uroš Seljak
Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when appl…
Hierarchical Bayesian CMB Component Separation with the No-U-Turn Sampler
R. D. P. Grumitt, Luke R. P. Jew, C. Dickinson
In this paper we present a novel implementation of Bayesian CMB component separation. We sample from the full posterior distribution using the No-U-Turn Sampler (NUTS), a gradient-…