9 papers
A Hierarchical Likelihood Model for Non-linear Inverse Problems under Additive and Multiplicative Noise
Nicolas Goeman, Pierre-Antoine Thouvenin, Pierre Chainais
Ill-posed inverse problems are encountered in numerous applications, possibly characterized by a highly non-linear forward model, both additive and multiplicative sources of noise,…
Chemical diversity of dense cores in Orion B: The role of the environment
Helena J. Mazurek, Maryvonne Gerin, Pierre Gratier +26
Prestellar cores are the sites of the earliest stages of star formation. Dust continuum observations are often used to identify and characterize their properties yet only a small f…
A Distributed Plug-and-Play MCMC Algorithm for High-Dimensional Inverse Problems
Maxime Bouton, Pierre-Antoine Thouvenin, Audrey Repetti +1
Markov Chain Monte Carlo (MCMC) algorithms are standard approaches to solve imaging inverse problems and quantify estimation uncertainties, a key requirement in absence of ground-t…
Estimating the dense gas mass of molecular clouds using spatially unresolved 3 mm line observations
Antoine Zakardjian, Annie Hughes, Jérôme Pety +28
We aim to develop a new method to infer the sub-beam probability density function (PDF) of H2 column densities and the dense gas mass within molecular clouds using spatially unreso…
Tracers of the ionization fraction in dense and translucent molecular gas: II. Using mm observations to constrain ionization fraction across Orion B
Ivana BeÅ¡liÄ, Maryvonne Gerin, Viviana V. Guzmán +28
The ionization fraction () is a crucial parameter of interstellar gas, yet estimating it requires deep knowledge of molecular gas chemistry…
Time and covariance smoothing for restoration of bivariate signals
Yusuf Yigit Pilavci, Pierre Palud, Julien Flamant +3
In many applications and physical phenomena, bivariate signals are polarized, i.e. they trace an elliptical trajectory over time when viewed in the 2D planes of their two component…