so there were actually only about 106500 samples used in the calculation
External Quote:
We use the transient candidates from Solano et al. (2022), but with the additional requirement that they have no counterparts within 5″ in Gaia, Pan-STARRS and NeoWise. Furthermore, we restrict our analysis to objects in the northern hemisphere (decl. > 0°). This yields a sample of 106,339 transients, which we use for our study.
I'm internally screaming at this.
Solano(2022) ran its data against
Gaia EDR3 and
Pan-STARRS DR2 in the "Selection" step, which resulted in the 298165 transients. In the "Analysis" step, they ran this data against more databases:
These searches significantly reduced the number of candidates (from 298 165 to 9 395). A significant number (∼59 per cent) of the identified sources were visible in infrared catalogues (Neowise, CatWISE2020, unWISE, and the infrared catalogues included in VOSA) but not in the optical (KIDS, Skymapper, and the optical catalogues included in VOSA) or the ultraviolet (GALEX).
WISE (Wide-field Infrared Survey Explorer) is an
infrared telescope. So "they have no counterparts within 5″ in Gaia, Pan-STARRS and NeoWise" not only bypasses many of the steps performed in Solano(2022) to eliminate false positives. We know Solano(2022)
found at least (298165-9395)*41%=
118395 false positives in the visible+UV spectrum, which means they are
not included in "Gaia, Pan-STARRS and NeoWise". The restriction to the Northern hemisphere trims this number down, but it still means that
the overwhelming number of data points in the 106339 set is actual astronomical objects that don't care whether they're in Earth's shadow or not.
This should not be off the expected value by a factor of 4.
When you have 96000 astronomical objects, you cannot add 10000 UFOs such that the sample density outside the shadow is 4 times the sample density inside the shadow, if it wasn't like that to begin with. Because the shadow is so small, you'd need to quadruple the number, i.e. find about 300,000 UFO—you can't get there with 10,000 or less.
The "expected value" that Villaroel is using in her shadow calculation must therefore be false.
Using her own sources, her proof is false, the 'shadow effect' does not exist as claimed.
A proper proof would:
1) explicitly list the criteria for "in shadow"
2) compute the coverage of shadow per plate area total [*]
3) compute the coverage of shadow per all astronomical objects
4) compute the coverage of shadow on a random distribution of points across all plates that conforms to the actual plate defect distribution (more near the edges etc.)
and then compare that with what was observed in the experimental data used in the study.
What we have in the study is misleading.
And why does she use 3 different data sub(sets) without any explanation of the choices involved?
Edit: footnote added
[*] They sort of do this.in a Monte Carlo kind of way.