Supervisors: Tim Bedding, Daniel Huber, Simon Murphy
Institution: The University of Sydney
A research project to see if it is possible to do meaningful photometry on B star contamination of Kepler K2 postage stamps. Specifically, we focus on examples in campaign 2, but create general techniques which can be applied to any other campaign (or to astronomy in general).
The real magic is inside scripts/analysis/clever.py
. To analyse the π Sco
data, run the following command in any *nix
shell:
% ./scripts/analysis/clever.py --csv \
-mf 400 -m data/pi_Sco/1.203442993/ap_203442993.txt -d 1 \
-s pi+analysis.csv -t data/pi_Sco/1.203442993/xy_203442993.csv \
data/pi_Sco/1.203442993/ktwo203442993-c02_lpd-targ.fits
% ./scripts/post/lc.py --no-title -w 1.2 -fp 1.570103 \
<(./scripts/post/highpass.py -w 401 -o 6 -sc 50 -ec -580 pi+analysis.csv) \
<(./scripts/etc/mag2flux.py -i \
<(./scripts/etc/phase2time.py --period 1.570103 --offset 2452025.96 data/pi_Sco/shobbrook_phase.csv))
This is an example of our analysis usnig aperture analysis, using
EPIC 203442993
. This photometric analysis mirrors ground-based surveys of
π Sco and has an incredible trendline.
The source code under scripts/
is licensed under the (GPLv3 or later)
License.
Copyright (C) 2015, 2016, 2017 Aleksa Sarai <cyphar@cyphar.com>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
The files under data/
are all publicly available and are
provided by NASA in compliance with their data use policy.
The *.json
metadata was collated using both SIMBAD and
MAST, both of which are also public resources.
A paper is currently in the works, so there's nothing to cite quite yet.
It'll hopefully all be done and ready to publish by early 2016 2017. Watch
this space to read the paper once it's published.