hippke / tls_k2 Goto Github PK

Try https://github.com/christinahedges/wellfit/blob/master/notebooks/1.04-Fitting-with-MCMC.ipynb
Re-run EVERERST with known transits to obtain correct transit depth (is 10% off)

make python script which takes as parameter the path of csv input file (light curve)
put epic_result.csv and epic_result.pdf in the same folder where input csv is

do not overwrite result files(csv, pdf)...because of stars being observed twice in different campaigns

• Result CSV, und doppelte nicht überschreiben
• Detrended flux noise (sigma) < X
• Require 2 transits
• Transit at edge of gap (201357643_02, 201102594_02)
• Secondary dip significant AND period > 2 days
• Wenn 2 transite und nur einer signifikant
• depth higher than 5%
• 2 transite, nur je 1 punkt
• wenn weniger als 50% der transits mit datenpunkten
• wenn transit duration < (literatur minimum - 50%)
• Wenn <5 transits, wenn transittiefen max/min um > 6 sigma variieren
• post-detection: intransit +2 sigma (test with 206011691.03 raus, behalte 201238110, behalte 205071984_04)
• wenn <5 transits und nur einer ist signifikant kleiner null

Offen
206543223_02

What filter? What parameters for the filter?

• Mayo 2018: First, low-frequency variations were removed via a basis spline and outliers were removed.
• Crossfield 2016: Gaussian process with a squared-exponential kernel.
• Vanderburg 2017: robustly fitting a basis spline to the light curve with breakpoints every 0.75 days and dividing it away