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May 28, 20260 citationsOpen Access

Prediction of Undiscovered Planet Factories. Resonant Accretion in the Tetrahedral Network: A Map for Astronomers.

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MMMark Markov

Key Points

  • The aim is to formulate a predictive model for identifying undiscovered planet factories based on resonant accretion.
  • Developed a predictive framework using resonant frequency and scaling laws.
  • Identified a region beyond Jupiter's orbit as a site for generating planetesimals.
  • Utilized Python code for target generation and visualization of potential planet factories.
  • Predicted 3–5 undiscovered carbonaceous chondrite groups from the Jovian region.
  • Calculated the accretion frequency as approximately 21.82 Hz.
  • Predicted the position of planet factories in various stellar systems including Beta Pictoris and HR 8799.

Abstract

This work (Publication №22 of Resonance Group) builds upon the discovery announced on May 26, 2026, by researchers from the Max Planck Institute for Solar System Research (MPS) — Joanna Drążkowska, Thorsten Kleine, and Nerea Gurrutxaga — who identified a ring-shaped region of elevated gas pressure just beyond Jupiter's orbit that acted as a planet factory, producing multiple generations of planetesimals with different compositions over about two million years. Using the resonant picture of space (standing layer at 57. 142857 Hz, golden ratio φ = 1. 618034, and transition coefficient √7 ≈ 2. 64575), we formulate a predictive framework for undiscovered planet factories. The accretion frequency is derived as fₐcc = 57. 142857 / φ² ≈ 21. 82 Hz. The position of a planet factory scales as Rfactory = 5. 8 × (Mₛtar/Mₛun) ¹ᐟ³ × (Mₚlanet/MJupiter) ¹ᐟ³ au. Predictions are made for Beta Pictoris (24 au), HR 8799 (38 au), TW Hydrae (21 au), and other systems. Additionally, we predict the existence of 3–5 undiscovered carbonaceous chondrite groups (CH, CB, C-ungrouped) from the same Jovian region. Python code for target generation and visualization is included.

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Cite This Study

Mark Markov (2026) studied this question.

synapsesocial.com/papers/6a17dd723fad632b0f9da1eahttps://doi.org/10.5281/zenodo.20400000
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