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相关论文: AI-Assisted analysis of $^{28}$Si$^*$ $\rightarrow…

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We perform a comprehensive analysis of complete fusion cross section data with the aim to derive, in a completely data-driven way, a model suitable to predict the integrated cross section of the fusion between light to medium mass nuclei at…

We describe low-lying collective excitations of atomic nuclei with the multi-reference covariant density functional theory, and combine them with coupled-channels calculations for heavy-ion fusion reactions at energies around the Coulomb…

核理论 · 物理学 2015-04-16 K. Hagino , J. M. Yao

We investigate the existence of weakly coupled gas-like states comprised of three $\alpha$ particles around an $^{16}$O core in $^{28}$Si. We calculate the excited states in $^{28}$Si using the multi-configuration mixing method based on the…

核理论 · 物理学 2015-06-05 T. Ichikawa , N. Itagaki , Y. Kanada-En'yo , Tz. Kokalova , W. von Oertzen

Most classification algorithms used in high energy physics fall under the category of supervised machine learning. Such methods require a training set containing both signal and background events and are prone to classification errors…

数据分析、统计与概率 · 物理学 2015-06-03 Mikael Kuusela , Tommi Vatanen , Eric Malmi , Tapani Raiko , Timo Aaltonen , Yoshikazu Nagai

The results presented in this paper clearly suggest that a coherent framework may exist which connects the topics of heavy-ion molecular resonances, hyperdeformation effects, and fission shape isomerism. New data on…

核实验 · 物理学 2007-05-23 C. Beck

The formation of hypernuclei in hadron-induced reactions and in heavy-ion collisions within a combination of a covariant transport model and a statistical fragmentation approach is investigated. We study the applicability and limitations of…

核理论 · 物理学 2015-05-13 T. Gaitanos , H. Lenske , U. Mosel

Fragment-fragment-$\gamma$ triple coincident measurements of the $^{28}$Si + $^{28}$Si reaction at E$_{lab.}$ = 111.6 MeV carefully chosen to populate J = 38$^{+}$ resonance have been performed at the VIVITRON tandem facility by using…

核实验 · 物理学 2007-05-23 R. Nouicer , C. Beck , S. J. Sanders , A. Szanto de Toledo , Sl. Cavallaro

A direct comparison and analysis of published spectra for the 7$\alpha$ disassembly of $^{28}$Si projectiles excited in collisions with $^{12}$C at 35 MeV/u reveals significant agreement in the derived excitation energies of high excitation…

核实验 · 物理学 2025-11-18 J. B. Natowitz , X. G. Cao , A. Bonasera , T. Depastas

We analyzed recent experimental data on the disassembly of $^{28}$Si into 7$\alpha$ in terms of a hybrid $\alpha$-cluster model. We calculated the probability of breaking into several $\alpha$-like fragments for high $l$-spin values for…

核理论 · 物理学 2021-09-28 Hua Zheng , Aldo Bonasera

We develop here a semiparametric Gaussian mixture model (SGMM) for unsupervised learning with valuable spatial information taken into consideration. Specifically, we assume for each instance a random location. Then, conditional on this…

统计方法学 · 统计学 2025-10-21 Baichen Yu , Jin Liu , Hansheng Wang

The connection between molecular resonance phenomena in light heavy-ion collisions, alpha-clustering and extremely deformed states in light $\alpha$-like nuclei is discussed. For example, the superdeformed bands recently discovered in light…

核实验 · 物理学 2009-11-10 C. Beck

Fragment-fragment-$\gamma$ triple coincidence measurements of the $^{28}$Si~$+$~$^{28}$Si reaction at E$_{\rm c.m.}$~=~55.8 MeV, carefully chosen to populate a well known quasi-molecular resonance in $^{56}$Ni, have been performed at the…

核实验 · 物理学 2007-05-23 R. Nouicer , C. Beck , S. J. Sanders , A. Szanto de Toledo , Sl. Cavallaro , E. Uegaki , Y. Abe

The excitation function for the 7 alpha de-excitation of $^{28}$Si nuclei excited to high excitation energies in the collisions of 35 MeV/nucleon $^{28}$Si with $^{12}$C reveals resonance structures that may indicate the population of high…

We develop the use of mutual information (MI), a well-established metric in information theory, to interpret the inner workings of deep learning models. To accurately estimate MI from a finite number of samples, we present GMM-MI…

数据分析、统计与概率 · 物理学 2023-04-12 Davide Piras , Hiranya V. Peiris , Andrew Pontzen , Luisa Lucie-Smith , Ningyuan Guo , Brian Nord

Hidden Markov Models with an underlying Mixture of Gaussian structure have proven effective in learning Human-Robot Interactions from demonstrations for various interactive tasks via Gaussian Mixture Regression. However, a mismatch occurs…

Semi- and non-parametric mixture of regressions are a very useful flexible class of mixture of regressions in which some or all of the parameters are non-parametric functions of the covariates. These models are, however, based on the…

统计方法学 · 统计学 2026-01-21 Peterson Mambondimumwe , Sphiwe B. Skhosana , Najmeh Nakhaei Rad

We use artificial intelligence (AI) to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non precessing binary black hole mergers. We trained AI models using 14 million waveforms, produced…

天体物理仪器与方法 · 物理学 2022-10-28 Asad Khan , E. A. Huerta , Prayush Kumar

Aspects of nuclear structure in alpha-conjugate nuclei have long been associated with alpha clustering, including the existence of superdeformed bands. In this paper, an alpha-particle inelastic scattering experiment investigating the…

Graphical models are commonly used tools for modeling multivariate random variables. While there exist many convenient multivariate distributions such as Gaussian distribution for continuous data, mixed data with the presence of discrete…

机器学习 · 统计学 2014-04-30 Jianqing Fan , Han Liu , Yang Ning , Hui Zou

Subbarrier fusion of the 7Li + 12C reaction is studied using an antisymmetrized molecular dynamics model (AMD) with an after burner, GEMINI. In AMD, 7Li shows an \alpha + t structure at its ground state and it is significantly deformed.…

核理论 · 物理学 2015-06-11 M. Huang , F. Zhou , R. Wada , X. Liu , W. Lin , M. Zhao , J. Wang , Z. Chen , C. Ma , Y. Yang , Q. Wang , J. Ma , J. Han , P. Ma , S. Jin , Z. Bai , Q. Hu , L. Jin , J. Chen , Y. Su , Y. Li
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