Empirical Discovery of a Universal Linear Correction to the Original Bethe-Weizsäcker
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Beschrijving
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The Bethe-Weizsäcker (BW) liquid drop model, developed in 1936, represents a cornerstone of nuclear physics. For nearly 90 years, it has served as the foundational framework for understanding nuclear binding energies. However, the original formula with its historical parameters exhibits systematic errors that have been recognized but never fully characterized.This study investigates the original, unmodified BW formula to identify systematic patterns in its residuals, without any parameter optimization or adjustment.MethodologyData Sources:· Nuclear masses: 2548 nuclei from AME2020 database (A ¿ 2)· Charge radii: 909 nuclei from IAEA LiveChart database + 908 nuclei from IAEA charge radii CSV databaseAnalysis Approach:· Implemented exact original BW formula with historical parameters (a_v = 15.8, a_s = 18.3, a_c = 0.714, a_a = 23.2, a_p = 12.0 MeV)· Calculated prediction errors: ¿M = M_exp - M_BW and ¿R = R_exp - R_classic· Performed multiple linear regression and correlation analysis· Discovered strong correlation with linear combination (5.18Z + 6.56N)
The Bethe-Weizsäcker (BW) liquid drop model, developed in 1936, represents a cornerstone of nuclear physics. For nearly 90 years, it has served as the foundational framework for understanding nuclear binding energies. However, the original formula with its historical parameters exhibits systematic errors that have been recognized but never fully characterized.This study investigates the original, unmodified BW formula to identify systematic patterns in its residuals, without any parameter optimization or adjustment.MethodologyData Sources:· Nuclear masses: 2548 nuclei from AME2020 database (A ¿ 2)· Charge radii: 909 nuclei from IAEA LiveChart database + 908 nuclei from IAEA charge radii CSV databaseAnalysis Approach:· Implemented exact original BW formula with historical parameters (a_v = 15.8, a_s = 18.3, a_c = 0.714, a_a = 23.2, a_p = 12.0 MeV)· Calculated prediction errors: ¿M = M_exp - M_BW and ¿R = R_exp - R_classic· Performed multiple linear regression and correlation analysis· Discovered strong correlation with linear combination (5.18Z + 6.56N)
AmazonPagina's: 44, Paperback, Eliva Press
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