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emcee: The MCMC Hammer
We introduce a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code is open source andExpand
A seven-planet resonant chain in TRAPPIST-1
The TRAPPIST-1 system is the first transiting planet system found orbiting an ultra-cool dwarf star. At least seven planets similar to Earth in radius and in mass were previously found to transitExpand
corner.py: Scatterplot matrices in Python
TLDR
This Python module uses matplotlib (Hunter 2007) to visualize multidimensional samples using a scatterplot matrix and each one and two-dimensional projection of the sample is plotted to reveal covariances. Expand
Exoplanet population inference and the abundance of Earth analogs from noisy, incomplete catalogs
No true extrasolar Earth analog is known. Hundreds of planets have been found around Sun-like stars that are either Earth-sized but on shorter periods, or else on year-long orbits but somewhatExpand
Calibrating gyrochronology using Kepler asteroseismic targets
Among the available methods for dating stars, gyrochronology is a powerful one because it requires knowledge of only the star's mass and rotation period. Gyrochronology relations have previously beenExpand
EVEREST: Pixel Level Decorrelation of K2 Light curves
We present EVEREST, an open-source pipeline for removing instrumental noise from K2 light curves. EVEREST employs a variant of pixel level decorrelation (PLD) to remove systematics introduced by theExpand
The High-mass Stellar Initial Mass Function in M31 Clusters
We have undertaken the largest systematic study of the high-mass stellar initial mass function (IMF) to date using the optical color?magnitude diagrams (CMDs) of 85 resolved, young (), intermediateExpand
A Systematic Search for Transiting Planets in the K2 Data
TLDR
This work applies a method for searching K2 light curves for evidence of exoplanets by simultaneously fitting for these systematics and the transit signals of interest, and presents posterior distributions on the properties of each system based strictly on the transit observables. Expand
Fast Direct Methods for Gaussian Processes
TLDR
This work shows that for the most commonly used covariance functions, the matrix C can be hierarchically factored into a product of block low-rank updates of the identity matrix, yielding an O(n log2 n) algorithm for inversion and enables the evaluation of the determinant det(C), permitting the direct calculation of probabilities in high dimensions under fairly broad assumptions on the kernel defining K. Expand
Fast and Scalable Gaussian Process Modeling with Applications to Astronomical Time Series
TLDR
A novel method for Gaussian processes modeling in one dimension where the computational requirements scale linearly with the size of the data set, and is fast and interpretable, with a range of potential applications within astronomical data analysis and beyond. Expand
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