emcee delivers a stable Python implementation of the affine-invariant ensemble MCMC algorithm that requires minimal hand-tuning and supports easy parallelization.
Diffusive Nested Sampling
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abstract
We introduce a general Monte Carlo method based on Nested Sampling (NS), for sampling complex probability distributions and estimating the normalising constant. The method uses one or more particles, which explore a mixture of nested probability distributions, each successive distribution occupying ~e^-1 times the enclosed prior mass of the previous distribution. While NS technically requires independent generation of particles, Markov Chain Monte Carlo (MCMC) exploration fits naturally into this technique. We illustrate the new method on a test problem and find that it can achieve four times the accuracy of classic MCMC-based Nested Sampling, for the same computational effort; equivalent to a factor of 16 speedup. An additional benefit is that more samples and a more accurate evidence value can be obtained simply by continuing the run for longer, as in standard MCMC.
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dynesty is an open-source Python package for dynamic nested sampling that improves efficiency in Bayesian posterior and evidence estimation compared to MCMC on certain problems.
Three Jupiter-mass planets are detected around two low-luminosity red giants with 15–18 yr CORALIE RVs; a multi-exposure strategy averages pulsations below 5 m/s.
GJ 729 exhibits a weak, evolving large-scale magnetic field (50-145 G) and a persistent ~7 d radial velocity signal that could be a ~1.5-2 Earth-mass planet or residual stellar activity.
The paper reviews physical processes, modeling techniques, retrieval methods, and observational strategies for characterizing exoplanet atmospheres, emphasizing Swiss research progress.
citing papers explorer
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emcee: The MCMC Hammer
emcee delivers a stable Python implementation of the affine-invariant ensemble MCMC algorithm that requires minimal hand-tuning and supports easy parallelization.
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dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences
dynesty is an open-source Python package for dynamic nested sampling that improves efficiency in Bayesian posterior and evidence estimation compared to MCMC on certain problems.
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CORALIE radial-velocity search for companions around evolved stars (CASCADES) V. Three planetary companions and achievable precision
Three Jupiter-mass planets are detected around two low-luminosity red giants with 15–18 yr CORALIE RVs; a multi-exposure strategy averages pulsations below 5 m/s.
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RedDots: Magnetic field of the nearby active M dwarf GJ 729, and a search for companions
GJ 729 exhibits a weak, evolving large-scale magnetic field (50-145 G) and a persistent ~7 d radial velocity signal that could be a ~1.5-2 Earth-mass planet or residual stellar activity.
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NCCR PlanetS: Observational and computational characterization of exoplanet atmospheres
The paper reviews physical processes, modeling techniques, retrieval methods, and observational strategies for characterizing exoplanet atmospheres, emphasizing Swiss research progress.