The Center for Computational Astrophysics executes research programs on systems ranging in scales from planets to cosmology, creating and using computational tools for data analysis and theory. It also supports, trains, and equips diverse members of the global astrophysics community and convenes events and workshops in New York City.
▪ Solve important, hard problems in computational astrophysics. Focus on problems that we at Flatiron are uniquely positioned to solve. ▪ Invent and propagate better data-analysis practices, analytical methods and computational methods for the global astrophysics community, with a focus on rigor. ▪ Develop, maintain and contribute to open-source software packages, open data and their communities. ▪ Create and support a community of astrophysics doers, learners and mentors in New York City and beyond. ▪ Train and launch diverse early-career researchers in astrophysics with unique capabilities in computational methods.
This collaboration, directed by Greg Bryan of Columbia University, aims to understand and determine the evolution and initial conditions of our universe, using observations via a Bayesian forward modeling approach.
- | Columbia University
- | Lawrence Berkeley National Lab
- | Harvard University
- | Stockholm University
- | Institute D'Astrophysique de Paris
- | Université de Montreal
- | Princeton University
- | Carnegie Mellon University
- | Max-Planck Institute for Astrophysics
Major research efforts currently supported by
CCA in partnership with other institutions.
- Seminar 3:00 - 5:00 p.m.
- Seminar 3:00 - 5:00 p.m.
- Event 4:00 - 5:30 p.m.
- Event 3:30 - 4:30 p.m.
The Galactic disk exhibits complex chemical and dynamical substructure thought to be induced by the bar, spiral arms, and satellites.…The Astrophysical Journal
The Open Cluster Chemical Abundances and Mapping Survey. VI. Galactic Chemical Gradient Analysis from APOGEE DR17
The goal of the Open Cluster Chemical Abundances and Mapping (OCCAM) survey is to constrain key Galactic dynamic and chemical…The Astronomical Journal
Modules for Experiments in Stellar Astrophysics (MESA): Time-Dependent Convection, Energy Conservation, Automatic Differentiation, and Infrastructure
We update the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics (MESA). The new auto_diff module…arXiv: 2208.03651
Galactic Dynamics is the study of the formation, history, and evolution of galaxies using the orbits of objects — numerically-integrated trajectories of stars, dark matter particles, star clusters, or galaxies themselves.
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 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 is a library for fast and scalable Gaussian Process (GP) Regression in one dimension with implementations in C++, Python, and Julia.
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 is a Python package that uses matplotlib to render pixel-perfect probabilistic graphical models for publication in a journal or on the internet.
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.