If you have your own equipment and want to observe an exoplanet transit,
read the steps below!
If you don’t have your own equipment and want to practise on how to analyse a transit observation,
you can try analysing one of the datasets kindly provided by our observing partners:
All the information needed to plan your observation can be found on our Transit Scheduler.
If you aim to contribute to the ARIEL ExoClock project, you can sign up to this page, register your telescopes and get your personalised schedule. It’s that simple!
- Use a RED PHOTOMETRIC filter, preferably.
- Set your camera temperature to the lowest available (below -10o, preferably).
- Set your binning to 1.
- Test your exposure time. Keep the number of counts below the point where your camera becomes non-linear (below 2/3 of the full well-depth, preferably).
- Check for at least one good comparison star in the field (similar magnitude to the target). If there is no such star move your target away from the centre of the image and try to find one.
- You can use a subframe to reduce the size of the images but be careful to include at least one good comparison star (similar magnitude to the target).
- Use the same camera temperature, binning and subframe as the science frames.
- For every transit (before or after) record:
a) 5 bias frames (zero exposure, using a cover),
b) 5 dark frames (same exposure time as the science frames, using a cover),
c) 5 flat frames (pointing to a uniformly illuminated surface, with the counts at 2/3 of the full well-depth).
Organising your data
It is convenient to organise your data in a way that you can have easy access to them, during analysis. The following strategy is just a suggestion:
- Keep all scientific and reduction frames in one folder without subfolders.
- Use a specific identifier for the scientific frames, for example: “WASP-10b-001.fits”, “WASP-10b-002.fits”, “WASP-10b-003.fits”, etc…
- Use a specific identifier for the bias frames, not containing the same identifier as the scientific frames, for example: “bias-001.fits”, “bias-002.fits”, “bias-003.fits”, etc…
- Use a specific identifier for the dark frames, not containing the same identifier as the scientific frames, for example: “dark-001.fits”, “dark-002.fits”, “dark-003.fits”, etc…
- Use a specific identifier for the flat frames, not containing the same identifier as the scientific frames, for example: “flat-001.fits”, “flat-002.fits”, “flat-003.fits”, etc…
Analysing a transit observation
There are four main steps in analysing a transit observation:
- image reduction
- image alignment
- transit modelling
We have created a user-friendly, python-based photometric software - HOPS, the HOlomon Photometric Software - to
assist you during this process. You can find all the information on how to use the software in our
HOPS user manual.
To successfully use the software, the following computer set up is necessary:
- either of the main operating systems: Windows, Mac OSX, or Linux,
- minimum RAM of 4 GB,
- minimum of 4 GB space available to install Python and HOPS.
Contribute to the ARIEL ExoClock project
Every observation counts! After analysing your data, you can upload the light curve to the ExoClock
database. You can find how to do that at exoclock.space.
If you are using HOPS, you will find a text file named “ExoClock_info.txt” in your photometry results,
with information on what to upload to the ExoClock website.