Hands-on Sessions Software available for download!
Dr. Nikole Lewis and Dr. Xavier Dumusque, who organized and led the hands on sessions at the 2016 Sagan workshop, have generously agreed to share their software with the attendees.
Warning: We advise against using this package for publication. The software has pedagogical applications only!
Radial Velocity package:
Reminders! Remember to bring the power source for your computer. Also, if you will be using a MacBook Air or tablet for the hands-on sessions, remember to bring an ethernet adaptor.
NoMachine is a program that connects your laptop to a virtual machine on the cloud where you will run various applications during the hands-on sessions. These instructions describe the process of setting up NoMachine on your computer. These instructions apply to both Windows and Macs.
Complete steps 1 and 3 in the Getting Started section of the instructions before the Hands-on Sessions. You'll complete step 2 once you receive your user name and password for Amazon Web Services (AWS) upon your arrival at the workshop.
Linux users: If you use Linux, there are instructions on the NoMachine company site with specific links for each version of Linux.
Click here to download the NoMachine key. Right click and choose "save link as" to save the file to your computer.
State of the Field: Extreme Precision Radial Velocities by D. A. Fischer, et al. (2016)
Observations of Transiting Exoplanets with the James Webb Space Telescope (JWST) by C. A. Beichman, et al. (2014)
Characterizing Transiting Exoplanet Atmospheres with JWST by T. Greene, et al. (2016)
References for the Radial Velocity Hands-on Session:
The hands-on sessions for the 2016 Summer Workshop will rely heavily on the knowledge of Bayesian analysis. We list some resources below that serve as an introduction to Bayesian analysis. Note that other resources are also available and you do not need to limit yourself to these.
Data Analysis: A Bayesian Tutorial, by D. S. Silvia, Second Edition, Oxford Science Publication
The first four chapters of this book are particularly relevant.
Bayesian Logical Data Analysis for the Physical Sciences, by P. Gregory, First Edition, Cambridge University Press
Many astronomy-related examples and a good basic introduction
Bayesian Data Analysis, by A. Gelman et al, third edition, Chapman and Hall/CRC
This contains predominantly life/social science examples, but is more advanced than the Gregory book. There is also a supporting website here.
Click here for information and presentations from previous summer workshops.
(last updated August 23rd, 2016 14:36:26)