PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 19, 20260 citationsOpen Access

Predictive Discovery Engine for Heavy Exotic Hadrons and Accessibility at 37 TeV

Toward a Predictive Discovery Engine for Persistence-Defined Heavy Exotic Hadrons: Calibration, Unknown-Object Prediction, and Collision-Level Accessibility at 37 TeV

View Full Paper
Ask AI
Bookmark
Share

Authors

KAKearon Allen

Discussion

Loading...

Member takes

Overview

Computational analysis predicts heavy exotic hadrons, indicating a pathway to experimental validation.

Key Points

  • The research aims to advance a predictive system for identifying unknown heavy exotic hadrons using computational methods.
  • Developed the Predictive Discovery Engine for object mapping.
  • Established four predictive bridges for classification: composition, mass mapping, decay lanes, and collision scoring.
  • Implemented a calibration-first approach ensuring integrity before predictions are made.
  • Successfully recovered the known exotic hadron Pc(4450) through a five-layer process.
  • Predicted a candidate B*Σb hadronic molecule with a mass window of 11096.2 to 11122.2 MeV.
  • Forecasted a dominant decay channel and analyzed its production accessibility at 37 TeV.

Cite This Study

Kearon Allen (2026) studied this question.

synapsesocial.com/papers/69e473bd010ef96374d8f7e0https://doi.org/10.5281/zenodo.19635509
View Full Paper
Ask AI
Bookmark
Share