In the Galactic disk, stellar [Fe/H] and age predict orbits and precise [X/Fe]
We explore the structure of the element abundance–age–orbit distribution of the stars in the Milky Way’s low-α disk, by (re-)deriving…
arXiv:1907.10606Astronomical Data
The Astronomical Data group solves hard problems in measurement and discovery. Depending on the context, the challenges in these problems can stem from the sheer size or complexity of the datasets, the precision requirements for measurements, or the subtlety or structure of the signals of interest.
The group develops and maintains advanced tools for the astrophysics community, especially ones for building and using probabilistic or generative models, but it does so by carrying out in-house data analysis projects that answer important scientific questions. Currently the team is concentrating on extrasolar planet discovery and characterization, precision measurement of stellar chemical abundances, and precise mapping of the Milky Way and of large-scale cosmological structure. As new data become available and the challenges evolve, so will the scope of the work. By sharing all its results, and by developing and maintaining open-source software, the Astronomical Data group directly supports scientific reproducibility and open science. The group blogs some of its current activities here.
Research Highlights
Detecting Thin Stellar Streams in External Galaxies: Resolved Stars & Integrated Light
S. Pearson, T. Starkenburg, K. Johnston, BF Williams, RA Ibata
The morphology of thin stellar streams can be used to test the nature of dark matter. It is therefore crucial…
arXiv.:1906.03264The Galactic Midplane Is Not a Plane: Implications for Dynamical Analysis with Gaia Data and Beyond
A Beane, R. Sanderson, M. Ness, K. Johnston, DG Filho, M. Mac Low, D. Angles-Alcazar, D. Hogg, C. Laporte
Orbital properties of stars, computed from their six-dimensional phase space measurements and an assumed Galactic potential, are used to understand…
arXiv:1905.08803News & 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.
