
Utilizando toda la información empírica disponible, analizamos las distribuciones de espaciado de los niveles 2+ de baja altitud de los núcleos pares. Para obtener muestras estadísticamente relevantes, los núcleos se agrupan en clases definidas por la relación R4/2 de las energías de excitación de los primeros 4+ y 2+ niveles. Esta relación sirve como una medida de la colectividad en los núcleos. Con la ayuda de la inferencia bayesiana, determinamos el parámetro de caoticidad para cada clase. Se encuentra que este parámetro varía fuertemente con R4/2 y toma valores particularmente pequeños en núcleos que tienen una de las simetrías dinámicas del modelo de bosones interactuantes.
En utilisant toutes les informations empiriques disponibles, nous analysons les distributions d'espacement des niveaux inférieurs 2+ de noyaux pairs-pairs. Pour obtenir des échantillons statistiquement pertinents, les noyaux sont regroupés en classes définies par le rapport R4/2 des énergies d'excitation des premiers niveaux 4+ et 2+. Ce ratio sert de mesure de la collectivité dans les noyaux. À l'aide de l'inférence bayésienne, nous déterminons le paramètre de chaotisme pour chaque classe. Ce paramètre varie fortement avec R4/2 et prend des valeurs particulièrement faibles dans les noyaux qui ont l'une des symétries dynamiques du modèle de boson en interaction.
Using all the available empirical information, we analyze the spacing distributions of low-lying 2+ levels of even–even nuclei. To obtain statistically relevant samples, the nuclei are grouped into classes defined by the ratio R4/2 of the excitation energies of the first 4+ and 2+ levels. This ratio serves as a measure of collectivity in nuclei. With the help of Bayesian inference, we determine the chaoticity parameter for each class. This parameter is found to vary strongly with R4/2 and takes particularly small values in nuclei that have one of the dynamical symmetries of the interacting boson model.
باستخدام جميع المعلومات التجريبية المتاحة، نقوم بتحليل توزيعات التباعد لمستويات 2+ المنخفضة من النوى الزوجية. للحصول على عينات ذات صلة إحصائيًا، يتم تجميع النوى في فئات محددة بنسبة R4/2 من طاقات الاستثارة للمستويات 4+ و 2+ الأولى. تعمل هذه النسبة كمقياس للجماعية في النوى. بمساعدة الاستدلال البايزي، نحدد معلمة الفوضى لكل فئة. وجد أن هذا المتغير يختلف بشدة مع R4/2 ويأخذ قيمًا صغيرة بشكل خاص في النوى التي لها أحد التناظرات الديناميكية لنموذج البوزون المتفاعل.
Nuclear and High Energy Physics, Artificial intelligence, Nuclear Theory, parton distributions, Bayesian inference, FOS: Physical sciences, Geometry, Bayesian probability, Quantum mechanics, Nuclear Theory (nucl-th), Database, Theoretical and Experimental Nuclear Structure, Homogeneous space, Inference, FOS: Mathematics, Boson, Excitation, Interacting boson model, Physics, Hadron Physics and QCD, Statistics, Statistical and Nonlinear Physics, Measure (data warehouse), Computer science, Physics and Astronomy, Physics - Data Analysis, Statistics and Probability, Physical Sciences, Characterization of Chaotic Quantum Dynamics and Structures, Statistical physics, Data Analysis, Statistics and Probability (physics.data-an), Mathematics
Nuclear and High Energy Physics, Artificial intelligence, Nuclear Theory, parton distributions, Bayesian inference, FOS: Physical sciences, Geometry, Bayesian probability, Quantum mechanics, Nuclear Theory (nucl-th), Database, Theoretical and Experimental Nuclear Structure, Homogeneous space, Inference, FOS: Mathematics, Boson, Excitation, Interacting boson model, Physics, Hadron Physics and QCD, Statistics, Statistical and Nonlinear Physics, Measure (data warehouse), Computer science, Physics and Astronomy, Physics - Data Analysis, Statistics and Probability, Physical Sciences, Characterization of Chaotic Quantum Dynamics and Structures, Statistical physics, Data Analysis, Statistics and Probability (physics.data-an), Mathematics
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