Quantifying gravitational lensing by dark matter

May 23, 2011
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

The latest prediction competition at Kaggle is literally "out of this world": the goal is to quantify the shape of 2-D images of galaxies from a simulated telescope, to test models for how invisible dark matter in the Universe distorts the images through gravitational lensing (as shown in the image below; see the FAQ for more details). If you're thinking about tackling this in R, the pixmap package will be handy for importing the images, and wavelet analysis might be a good way of dealing with the noise issues. The winner will receive an trip to JPL in Pasadena, Calfornia to attend the GREAT10 challenge workshop "Image Analysis for Cosmology". 

Galaxy ellipticity
Kaggle: Mapping Dark Matter

 

 

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: ,

Comments are closed.

Search R-bloggers


Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)