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Titlebook: GRMS or Graphical Representation of Model Spaces; Vol. 1 Basics W. Duch Book 1986 Springer-Verlag Berlin Heidelberg 1986 RMS.classification

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发表于 2025-3-21 17:34:52 | 显示全部楼层 |阅读模式
书目名称GRMS or Graphical Representation of Model Spaces
副标题Vol. 1 Basics
编辑W. Duch
视频video
丛书名称Lecture Notes in Chemistry
图书封面Titlebook: GRMS or Graphical Representation of Model Spaces; Vol. 1 Basics W. Duch Book 1986 Springer-Verlag Berlin Heidelberg 1986 RMS.classification
描述The purpose of these notes is to give some simple tools and pictures to physicists and ‘ chemists working on the many-body problem. Abstract thinking and seeing have much in common - we say "I see" meaning "I understand" , for example. Most of us prefer to have a picture of an abstract object. The remarkable popularity of the Feynman diagrams, and other diagrammatic approaches to many-body problem derived thereof, may be partially due to this preference. Yet, paradoxically, the concept of a linear space, as fundamental to quantum physics as it is, has never been cast in a graphical form. We know that is a high-order contribution to a two-particle scattering process (this one invented by Cvitanovic(1984)) corresponding to a complicated matrix element. The lines in such diagrams are labeled by indices of single-particle states. When things get complicated at this level it should be good to take a global view from the perspective of the whole many-particle space. But how to visualize the space of all many-particle states ? Methods of such visualization or graphical representation of the ,spaces of interest to physicists and chemists are the main topic of this work.
出版日期Book 1986
关键词RMS; classification; element; many-body problem; mechanics; mutation; physics; quantum mechanics; quantum ph
版次1
doihttps://doi.org/10.1007/978-3-642-93347-9
isbn_softcover978-3-540-17169-0
isbn_ebook978-3-642-93347-9Series ISSN 0342-4901 Series E-ISSN 2192-6603
issn_series 0342-4901
copyrightSpringer-Verlag Berlin Heidelberg 1986
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发表于 2025-3-22 00:05:14 | 显示全部楼层
Book 1986and seeing have much in common - we say "I see" meaning "I understand" , for example. Most of us prefer to have a picture of an abstract object. The remarkable popularity of the Feynman diagrams, and other diagrammatic approaches to many-body problem derived thereof, may be partially due to this pre
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A Just Society for Ireland? 1964-1987 graph is simpler if we regard vertices and arcs of these larger graphs as ‘virtually present’: existing, but giving a null contribution to the real graph. The fixed-slope graphs, by virtue of this embedding property, admit a natural ordering of paths.
发表于 2025-3-22 11:43:31 | 显示全部楼层
The Collective Unconscious and Beyond in ,c molecule in Born-Oppenheimer approximation requires such states when a strong spin-orbit interaction is present. Graphical representation of the states that do not posses any symmetry other that being antisymmetric (corresponding to determinants) is particularly simple.
发表于 2025-3-22 16:29:15 | 显示全部楼层
Sharon Wilson,Surita Mogan,Kiran Kaurmpty arc is most frequently set to zero making the arc vertical. The difference . — hm. should be choosen in such a way that . is always different from the slope of an empty arc and that each vertex is uniquely labeled by (., .) values.
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发表于 2025-3-22 23:43:35 | 显示全部楼层
L̂z—adapted graphsmpty arc is most frequently set to zero making the arc vertical. The difference . — hm. should be choosen in such a way that . is always different from the slope of an empty arc and that each vertex is uniquely labeled by (., .) values.
发表于 2025-3-23 05:08:56 | 显示全部楼层
https://doi.org/10.1007/978-3-319-41510-9e second group at the bottom levels of a graph. In this way two subgraphs, the first describing the space of s. particles in ∣.〉 basis and the second representing the space of s. particles in ∣.〉 basis, are obtained (Fig 4). The two subgraphs are joined by one vertex.
发表于 2025-3-23 08:55:04 | 显示全部楼层
https://doi.org/10.1007/978-1-349-00178-1 is not how to construct spin eigenfunctions, but how to find proper graphical labels for them. In the second part of this work I will show how the information contained in the labels or in the structure of graphs may be used to calculate arbitrary matrix elements.
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