Compare the hidden patch with the whole star
Open Rackham’s Section 2.3. Its key comparison is between the spectrum along the transit chord and the spectrum averaged over the full visible star. If those differ, normalizing the blocked light by the whole star imprints stellar structure on the measured depth.
For an otherwise immaculate chord and unocculted dark regions, let their disk covering fraction be and their brightness relative to the ordinary photosphere be in one band. The disk baseline is reduced by the factor , while the planet hides the ordinary photosphere. The simple two-component depth becomes:
Take a one-percent ordinary depth, ten-percent covering fraction and half-bright regions in that band. The baseline factor is 0.95, so the apparent depth is about 0.01053. A uniform-area radius estimate grows by about 2.6 percent. This direction differs from extra constant companion light, which makes a dip shallower.
Reading: Rackham, Apai & Giampapa 2018, Transit Light Source Effect, v3 · Mandel & Agol 2002, Analytic Lightcurves, arXiv v1
Read the variability pictures as model experiments
Figure 2 shows an example constructed photosphere and the rotational light curve obtained by summing its visible brightness. Notice which parts rotate into view and how the peak-to-peak variation is measured. It is a model demonstration of what photometry responds to, not an image of a particular observed star.
Next compare the spot-size cases in Figure 4. The horizontal axis is covering fraction; the vertical axis is variability amplitude. The shaded spread shows that a given amplitude corresponds to a range of coverage in the simulated distributions. Different spot sizes and arrangements produce different relations.
A nearly symmetric distribution can cover considerable area with little rotational variation. Monitoring brightness therefore informs the nonuniform part of the surface, and an apparently quiet light curve need not supply an immaculate reference spectrum. The paper’s M-dwarf temperature contrasts and spectral models should remain attached to its numerical predictions when considering another kind of star.
Reading: Rackham, Apai & Giampapa 2018, Transit Light Source Effect, v3
Follow the wavelength dependence
Figure 6 plots contamination spectra for the specified model photospheres. Read its vertical quantity as a relative change to transit depth. It is not the planet’s own atmospheric absorption spectrum. Features of cooler regions can overlap wavelength bands used to interpret atmospheric molecules.
The distinction between a crossed and an uncrossed spot matters. Covering a dark patch during the transit hides less light and can make a bump within the dip. A dark region outside the chord lowers the baseline and can deepen the apparent transit. A broad-band light curve and a transmission spectrum sample these source effects differently.
Our fixed TESS fit does not infer a surface map or perform this spectral calculation. Its useful connection is narrower: the assumed chord brightness changes the inferred radius. The retained limb-brightness sensitivity fits show that dependency for one broad band.
Reading: Rackham, Apai & Giampapa 2018, Transit Light Source Effect, v3
Compare a planet with other eclipsing sources
Now open Morton’s Section 2. Its hypotheses include a planet and several configurations of eclipsing stellar companions, including systems blended with the target. A small dip can arise from a deep eclipse whose light is diluted. The probability comparison includes how often each configuration is expected and how well its possible shapes describe the signal.
Section 3 lists information beyond the transit depth: stellar properties, allowed sky region for a contaminating source and limits on secondary eclipses. Centroid measurements constrain where the dimming happens; a deep high-resolution image can constrain nearby sources that an ordinary aperture blends together.
A good planet-shaped fit supplies one likelihood within this comparison. It does not supply the full list of hypotheses or their prior frequencies. In particular, a planet orbiting an unresolved companion can still be a planet while its inferred radius refers to the wrong host-star scale. Radius accuracy and astrophysical classification are different questions.
Reading: Morton et al. 2016, False Positive Probabilities, arXiv v1 · NASA Exoplanet Archive, Kepler FPP Table Description
Keep the failure tests beside the probability
Read Section 4.2 before treating a small false-positive probability as a general reliability score. The calculation selects among specified astrophysical eclipse explanations. It does not include all instrumental artifacts or stellar variability. Separate vetting determines whether that comparison is appropriate.
Section 4.7 then lists failed fits, missing inputs and unconverged shape models. A missing probability is not zero. A formally successful calculation with a source position inconsistent with the target also needs care. The official NASA table description preserves these conditions and distinguishes its fixed catalog inputs from later property updates.
For the next candidate, make the sequence concrete: identify the changing image location; inspect repeated and secondary events; note the host-star information and allowed blends; then read the probability under its actual hypothesis set. For an already established planet, return to the surface-brightness question when interpreting its radius or spectrum.
Reading: Morton et al. 2016, False Positive Probabilities, arXiv v1 · NASA Exoplanet Archive, Kepler FPP Table Description