scholarly journals R-MATRICES AND THE TENSOR PRODUCT GRAPH METHOD

2002 ◽  
Vol 16 (14n15) ◽  
pp. 2145-2151 ◽  
Author(s):  
MARK D. GOULD ◽  
YAO-ZHONG ZHANG
Keyword(s):  
Tensor Product ◽  
Quantum Algebra ◽  
Systematic Method ◽  
Graph Method ◽  
Product Graph ◽  
Multiplicity Free

A systematic method for constructing trigonometric R-matrices corresponding to the (multiplicity-free) tensor product of any two affinizable representations of a quantum algebra or superalgebra has been developed by the Brisbane group and its collaborators. This method has been referred to as the Tensor Product Graph Method. Here we describe applications of this method to untwisted and twisted quantum affine superalgebras.

scholarly journals Multivariableq-Hahn polynomials as coupling coefficients for quantum algebra representations

2001 ◽  
Vol 28 (6) ◽  
pp. 331-358 ◽  
Author(s):  
Hjalmar Rosengren
Keyword(s):  
Tensor Product ◽  
Quantum Group ◽  
Quantum Algebra ◽  
Coupling Coefficients ◽  
Highest Weight ◽  
Hahn Polynomials ◽  
Highest Weight Representations

We study coupling coefficients for a multiple tensor product of highest weight representations of theSU(1,1)quantum group. These are multivariable generalizations of theq-Hahn polynomials.

scholarly journals Affinity Learning with Diffusion on Tensor Product Graph

2013 ◽  
Vol 35 (1) ◽  
pp. 28-38 ◽  
Author(s):  
Xingwei Yang ◽  
Lakshman Prasad ◽  
Longin Jan Latecki
Keyword(s):  
Tensor Product ◽  
Product Graph

Least Levels Disassembly Graph Method for Selective Disassembly Planning

2014 ◽  
Author(s):  
Chenggang Wang ◽  
Peter Mitrouchev ◽  
Guiqin Li ◽  
Lixin Lu
Keyword(s):  
Target Component ◽  
Graph Method ◽  
Product Graph ◽  
Sequence Generation ◽  
Selective Disassembly ◽  
Disassembly Planning

As known, the number of possible disassembly sequences increases significantly with the number of parts in a product. For selective disassembly, for instance, it is important to eliminate the components unrelated with the target component prior to sequence generation. In order to address this configuration, a method for disassembly sequences generation in the case of selective disassembly is presented in this paper. Based on the least levels of disassembly product graph it allows reducing computation resources. Instead of considering the geometric constrains for each pair of components, the proposed method considers the geometric contact and collision relationships among the components in order to generate the disassembly graph for sequences planning. The method is applied for automatically generating the selective disassembly sequences thus allowing reducing the computation resources and is illustrated through an example.

Learning contextual dissimilarity on tensor product graph for visual re-ranking

2018 ◽  
Vol 79 ◽  
pp. 1-10 ◽  
Author(s):  
Danchen Zheng ◽  
Wangshu Liu ◽  
Min Han
Keyword(s):  
Tensor Product ◽  
Product Graph

scholarly journals The tensor product of two oriented quantum algebras

2019 ◽  
Vol 19 (06) ◽  
pp. 2050104
Author(s):  
Tianshui Ma ◽  
Haiyan Yang ◽  
Tao Yang
Keyword(s):  
Tensor Product ◽  
Knot Theory ◽  
Quantum Algebra ◽  
Quantum Algebras ◽  
Special Case

In this paper, we give the oriented quantum algebra (OQA) structures on the tensor product of two different OQAs by using Chen’s weak [Formula: see text]-matrix in [J. Algebra 204 (1998) 504–531]. As a special case, the OQA structures on the tensor product of an OQA with itself are provided, which are different from Radford’s results in [J. Knot Theory Ramifications 16 (2007) 929–957].

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