Just a small comment about why observing exo-planet transits is best done with specialized software such as AstroimageJ or Holomon Hops.
While seeing the relative flux drop is, in itself, very cool and rewarding analyzing those drops requires very specific methods. Why? Because exo-planetary researchers try to extract as much information as it is possible from a very limited set of data (the transit depth, its timing and its shape). The simplest example is answering the question "is it a small exo-planet close to its sun or a larger exo-planet far from its sun". On a single transit your ability to decide suffers from great uncertainty, on multiple transits Kepler's Law comes to the rescue reducing the uncertainty. There are many other parameters that come into play. How the plane of the planet orbit is inclined from our point of view will change the shape of the drop, but so will the type of star where the transit happens because of different limb darkening profiles.
If one looks at AstroImageJ in action as it analyzes the light curve, one gets a hint of what the software is really doing

How in the world does AstroImageJ knows what the lightcurve I am currently observing should behave the way it does in the future? The reason is that it runs a model of an exo-planet transit behind the scene and fits the incoming data to the model. What it does is progressively (and probabilistically) constrain a set of model parameters as your data come in).
Each and every parameter comes with its own uncertainties. Here is a simple example where you have a probability distribution for two parameters that have a non idependent impact on the light curve. There's obviously a resulting joint bi-dimensional distribution of those two probabilities and, on the base of the data you have acquired, a Markov Chain Montecarlo can sample that distribution and find the optimal fit (which is just that: the theoretical best fit according to your data, certainly not with a very high confidence that the planet precisely has those characteristics)
On what is happening behind the scene, those core papers are interesting, especially for those cloudynights.
Analytic Light Curves For Planetary Transit Searches (Mandel – Agol)
https://iopscience.i...1086/345520/pdf
Parameter Estimation From Time-Series Data With Correlated Errors: a Wavelet-Based Method And Its Application To Transit Light Curves (Carter and Winn1)
https://iopscience.i...X/704/1/51/meta
Equations for the analysis of the light curves of extra-solarplanetary transits(Gimenez)
https://www.aanda.or...8/aa4445-05.pdf
Efficient, uninformative sampling of limb darkening coefficients for two-parameter laws (Kipping)
https://academic.oup.../3/2152/1024138
I hope none of these are behind a paywall.
Edited by pvdv, 26 December 2022 - 11:50 AM.