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Exact and Asymptotic Computations of Elementary Spin Networks: Classification of the Quantum–Classical Boundaries

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Computational Science and Its Applications – ICCSA 2012 (ICCSA 2012)

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Abstract

Increasing interest is being dedicated in the last few years to the issues of exact computations and asymptotics of spin networks. The large–entries regimes (semiclassical limits) occur in many areas of physics and chemistry, and in particular in discretization algorithms of applied quantum mechanics. Here we extend recent work on the basic building block of spin networks, namely the Wigner 6j symbol or Racah coefficient, enlightening the insight gained by exploiting its self–dual properties and studying it as a function of two (discrete) variables. This arises from its original definition as an (orthogonal) angular momentum recoupling matrix element. Progress also derives from recognizing its role in the foundation of the modern theory of classical orthogonal polynomials, as extended to include discrete variables. Features of the imaging of various regimes of these orthonormal matrices are made explicit by computational advances –based on traditional and new recurrence relations– which allow an interpretation of the observed behaviors in terms of an underlying Hamiltonian formulation as well. This paper provides a contribution to the understanding of the transition between two extreme modes of the 6j, corresponding to the nearly classical and the fully quantum regimes, by studying the boundary lines (caustics) in the plane of the two matrix labels. This analysis marks the evolution of the turning points of relevance for the semiclassical regimes and puts on stage an unexpected key role of the Regge symmetries of the 6j.

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Bitencourt, A.C.P., Marzuoli, A., Ragni, M., Anderson, R.W., Aquilanti, V. (2012). Exact and Asymptotic Computations of Elementary Spin Networks: Classification of the Quantum–Classical Boundaries. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31125-3_54

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  • DOI: https://doi.org/10.1007/978-3-642-31125-3_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31124-6

  • Online ISBN: 978-3-642-31125-3

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