On the algebraic structure of the set of long flat virtual knot diagrams with the connected sum operation

In [Y. H. Im, S. Kim and K. Lee, Embeddings from the set of long flat virtual knots to the set of long virtual knots and applications, J. Knot Theory Ramifications 29(5) (2020) 2050025], Im et al. introduced two embeddings from the set of long flat virtual knot diagrams to the set of long virtual knot diagrams so that we constructed invariants for long flat virtual knots via invariants for long virtual knots. We investigate one of the image sets of these embeddings in the set of long virtual knot diagrams and show examples that the connected sum operation is non-commutative in the set of long flat virtual knot diagrams.

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Publication Details

Journal
Journal of Knot Theory and Its Ramifications
Published
2025-03-07
DOI
https://doi.org/10.1142/s0218216525500191
Primary Topic
Topological and Geometric Data Analysis
Type
article
Field-Weighted Citation Impact
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article

On the algebraic structure of the set of long flat virtual knot diagrams with the connected sum operation

Sera Kim
Journal of Knot Theory and Its Ramifications
Topological and Geometric Data Analysis
article

On the algebraic structure of the set of long flat virtual knot diagrams with the connected sum operation

Sera Kim
article en

Abstract

In [Y. H. Im, S. Kim and K. Lee, Embeddings from the set of long flat virtual knots to the set of long virtual knots and applications, J. Knot Theory Ramifications 29(5) (2020) 2050025], Im et al. introduced two embeddings from the set of long flat virtual knot diagrams to the set of long virtual knot diagrams so that we constructed invariants for long flat virtual knots via invariants for long virtual knots. We investigate one of the image sets of these embeddings in the set of long virtual knot diagrams and show examples that the connected sum operation is non-commutative in the set of long flat virtual knot diagrams.

Journal of Knot Theory and Its RamificationsVol. 34(05)
Korea Naval Academy (KR)
Openalex Percentile: Top 95%
Topological and Geometric Data Analysis
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