Birleştirilmiş Cornell ve Kuadratik Potansiyeller ile Sinir Ağı Kullanarak bc ̅ Mezon Kütle Spektrumlarının Tahmini

Abstract

Bu makale, Cornell potansiyelini ek bir kuadratik potansiyel ile harmanlayan bir sinir ağı (NN) yöntemi kullanarak bc ̅ mezon kütle spektrumlarını incelemektedir. Teorik ve deneysel referanslarla karşılaştırılan sonuçlarımız, bc ̅ mezonlarının özelliklerini tanımlamak için birleşik potansiyel modelinin geçerliliğini doğrulamaktadır. Ayrıca, ek boyutların kuarkonyum sistemleri üzerindeki etkisinin tanımlanması için teorik bir çerçeve vermek üzere yöntemi varsayımsal dört boyutlu bir uzaya uyguluyoruz. Sonuçlar, karmaşık potansiyel modellemesi ile geliştirilmiş NN yönteminin ağır mezon spektroskopisi çalışmalarına uygulanabilirliği ile tutarlıdır.

Keywords

• Hadronlar
• Makine Öğrenmesi
• QCD

Predicting bc ̅ Meson Mass Spectra Using Neural Network with Combined Cornell and Quadratic Potentials

Abstract

This paper examines the bc ̅ meson mass spectra employing a neural network (NN) method which blends Cornell potential with an additional quadratic potential. Our results, which were compared with theoretical and experimental references, confirm the validity of the combined potential model for the description of the properties of bc ̅ mesons. We further apply the method to a hypothetical four-dimensional space to give a theoretical framework for the description of the effect of additional dimensions on quarkonium systems. The results are consistent with the applicability of the NN method, enhanced with the modeling of complex potential, to the study of heavy meson spectroscopy

Keywords

• Hadrons
• Machine Learning
• QCD

References

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