Astro - Mitra
Probability Test
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This website was copyrighted along the process of peer review publications
The discovery of the Astro-Mitra starry matrix will surely trigger a paradigm shift in many aspects of our humanity’s sciences. On this page, we present the probability calculation that this matrix was founded intentionally by a creator beyond our material universe.
In probability, there are many ways to formulate a question that applies to all types of spherical coordinate grids.
Here's an example of our case using the globe grid:
We have placed 20 random points on our terrestrial globe. We want to know the probability that at least 12 of these points are aligned on 5 different meridians by aligning 2 or 3 points to within ±0.5° of error.
Monte-Carlo method, with 100,000 simulated placements, found 0 successes (consistent with this very small probability).
Poisson-based approximation → P ≈ 0.0000529% about 1 in 1,890,000.
You can ask your own question to an AI like https://chatgpt.com/
Context: In our case the grid is the ecliptic grid of our solar system. The grid is fixed upon the starry sky and is stable although the precession movement.
9 of the 20 brightest stars are aligned with the meridian of the ecliptic grid.
Arcturus - Spica
Deneb – Fomalhaut
Mintaka – Capella
Sirius – Canopus – Vega
3 stars are aligned on a meridian of the galactic grid:
Altair – Reglus – Sirius.
In our video, we name this alignment the Anzu Line.
The coincidences go far beyond these amazing alignments:
Sirius shares two lines.
Regulus is the only bright star on the ecliptic line which is the equator of our solar system and of the ecliptic grid.
The angular distances between the stars and in between the meridian alignments are so astonishing that there is no need for more probability calculation. These angular distances are based on integer denominators of 90⁰ (e.g., 45⁰ = 1/2 of 90⁰; 30⁰ = 1/3 of 90⁰).
You can explore in 3D how the angular distances of the Astro-Mitra are integer denominators of 90 degrees.
However, see the hypothesis of this calculation for the alignments of points during 1 million trials with the Monte Carlo method:
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20 points drawn independently, uniformly on the sphere.
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A meridian “alignment ±0.5°” = a 1° longitude window.
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We look for 5 meridians (5 such 1° windows) each containing 2 or 3 points, and the total number of distinct points covered by those five windows ≥ 12.
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Windows are taken among all possible 1° windows that can be realized given the points (implemented by sliding windows starting at each point’s longitude).
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Windows must cover distinct point-sets in the earlier simulation (so a point is counted only once toward the five meridians) — this is the natural interpretation if you want “at least 12 of the points” to be assigned to those 5 meridians.
Numerical evidence
We ran Monte-Carlo simulations:
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1,000,000 trials → 0 successes (gave a loose 95% upper bound ≲1.5×10⁻⁵).
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Then 1,000,000 trials with an optimized search → 0 successes. From zero successes in 1,000,000 trials the standard 95% conservative upper bound is
p ≲ - ln(0.05)/10⁶ ≈ 3.0×10⁻⁶
So, the best empirical statement is: probability ≲ 3×10⁻⁶ (about 3 chances in a million).
Intuition why it’s so tiny
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You require five separate narrow 1° windows, each containing 2 or 3 points, and together they must cover at least 12 distinct points — that is an extremely concentrated and structured arrangement for only 20 uniformly random points.
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The combinatorial and geometric constraints (many independent small-probability clustering events happening simultaneously with no point reuse) make the joint event astronomically unlikely.