Astronomical Data
The Astronomical Data group develops, maintains and propagates advanced methods and open-source tools for the astrophysics community, especially for building probabilistic models, discovering sources in noisy data and making precise measurements. It builds these methods and tools by carrying out in-house data analysis projects that answer important scientific questions. It also hosts events and workshops that are designed to create new data analysis opportunities for members of the astronomical community.
The Astronomical Data group is currently concentrating on extrasolar planet discovery and characterization, precision measurement of stellar chemical abundances and precise kinematic and dynamical mapping of the Milky Way. Many members of the Data group are cross listed in the Exoplanets and Nearby Universe groups according to their scientific interests. As new data become available and the challenges evolve, so will the scope of the group’s work. By sharing all its data and results publicly, and by developing and maintaining open-source software, the Astronomical Data group directly supports scientific reproducibility and open science. The group structures its activities around people, with mentoring, education and career development all important goals.
Group members are involved in the planning and operations of several large data-intensive projects with lasting value. These include the Terra Hunting Experiment, the ESA Gaia Mission and the Sloan Digital Sky Survey V.
Projects
Research Highlights
Temperatures and Metallicities of M dwarfs in the APOGEE Survey
J. Birky, D. Hogg, A.W. Mann, A. Burgasser
M dwarfs have enormous potential for our understanding of structure and formation on both Galactic and exoplanetary scales through their…
arXiv:2001.04962emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC
D. Foreman-Mackey, W. Farr, M. Sinha, A.M. Archibald, D. Hogg, J.S. Sanders, J. Zuntz, P.K.G. Williams, A.R.J. Nelson, M. del Val-Borro, T. Erhardt, I. Pashchenko, O.A. Pla
arXiv:1911.07688 Spectroscopy of the Young Stellar Association Price-Whelan 1: Origin in the Magellanic Leading Arm and Constraints on the Milky Way Hot Halo
D.L. Nidever, A. Price-Whelan, Y. Choi, R.L. Beaton, T.T. Hansen, D. Boubert, D. Aguado, R. Ezzeddine, S. Oh, N.W. Evans
arXiv:1910.05360 News & Announcements
Software
STARRY
starry enables the computation of fast and precise light curves for various applications in astronomy: transits and secondary eclipses of exoplanets, light curves of eclipsing binaries, rotational phase curves of exoplanets, light curves of planet-planet and planet-moon occultations, and more.
George
George is a fast and flexible Python library for Gaussian Process Regression. It capitalizes on the Hierarchical Off-Diagonal Low-Rank formalism to make controlled approximations for fast execution.
celerite
celerite is a library for fast and scalable Gaussian Process (GP) Regression in one dimension with implementations in C++, Python, and Julia.
Astrometry.net
If you have astronomical imaging of the sky with celestial coordinates you do not know—or do not trust—then Astrometry.net is for you. Input an image and we'll give you back astrometric calibration meta-data, plus lists of known objects falling inside the field of view.
DAFT
Daft is a Python package that uses matplotlib to render pixel-perfect probabilistic graphical models for publication in a journal or on the internet.
emcee
emcee is an extensible, pure-Python implementation of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler. It's designed for Bayesian parameter estimation.
