相对论费斯巴赫-维拉尔自旋-1/2 方程的解法

IF 1.7 4区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Few-Body Systems Pub Date : 2024-03-23 DOI:10.1007/s00601-024-01902-8

D. Wingard, A. Garcia Vallejo, Z. Papp

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引用次数: 0

摘要

我们提出了一种通过求解相应的费什巴赫-维拉斯方程来计算相对论自旋-1/2粒子的方法。我们发现，Feshbach-Villars 自旋-1/2 哈密顿可以写成两个自旋耦合的 Feshbach-Villars 自旋-0 哈密顿。在求解方法上，我们采用了积分方程形式主义。势算子以离散的希尔伯特空间为基础表示，相关的格林算子通过矩阵续分计算得出。

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Solution of Relativistic Feshbach–Villars Spin-1/2 Equations

We propose a computational method for relativistic spin-1/2 particles by solving the corresponding Feshbach–Villars equation. We have found that the Feshbach–Villars spin-1/2 Hamiltonian can be written as two spin-coupled Feshbach–Villars spin-0 Hamiltonians. For the solution method, we adopted an integral equation formalism. The potential operators are represented in a discrete Hilbert space basis and the relevant Green’s operator has been calculated by a matrix continued fraction.

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来源期刊

Few-Body Systems 物理-物理：综合

CiteScore

2.90

自引率

18.80%

发文量

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).