Properties of N, \(\Delta \) Baryons with Screened Potential

IF 1.7 4区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Chandni Menapara, Ajay Kumar Rai
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引用次数: 0

Abstract

N and \(\Delta \), the foremost member of octet and decuplet have always been under attention, providing the great platform to reveal QCD dynamics. From light to heavy hadrons, the hypercentral Constituent Quark Model (hCQM) has been used in a number of research. The research of light baryon resonances in this paper has been conducted using screened potential. The slopes and intercepts, as well as the Regge trajectories, have all been displayed. For some channels, the strong decay widths to pion have been estimated using the current masses.

Abstract Image

具有屏蔽势能的 N, $$\Delta $$ 重子的性质
作为八元组和十元组最重要的成员,N和(\Delta \)一直受到关注,为揭示QCD动力学提供了很好的平台。从轻强子到重强子,超中心构成夸克模型(hCQM)已被用于多项研究。本文对轻重子共振的研究采用了屏蔽势。斜率和截距以及雷格轨迹都已显示出来。对于某些信道,还利用当前质量估算了到先驱的强衰变宽度。
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来源期刊
Few-Body Systems
Few-Body Systems 物理-物理:综合
CiteScore
2.90
自引率
18.80%
发文量
64
审稿时长
6-12 weeks
期刊介绍: The journal Few-Body Systems presents original research work – experimental, theoretical and computational – investigating the behavior of any classical or quantum system consisting of a small number of well-defined constituent structures. The focus is on the research methods, properties, and results characteristic of few-body systems. Examples of few-body systems range from few-quark states, light nuclear and hadronic systems; few-electron atomic systems and small molecules; and specific systems in condensed matter and surface physics (such as quantum dots and highly correlated trapped systems), up to and including large-scale celestial structures. Systems for which an equivalent one-body description is available or can be designed, and large systems for which specific many-body methods are needed are outside the scope of the journal. The journal is devoted to the publication of all aspects of few-body systems research and applications. While concentrating on few-body systems well-suited to rigorous solutions, the journal also encourages interdisciplinary contributions that foster common approaches and insights, introduce and benchmark the use of novel tools (e.g. machine learning) and develop relevant applications (e.g. few-body aspects in quantum technologies).
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