Pith. sign in

REVIEW 3 cited by

Twist formulas for one-row colored $A_2$ webs and $\mathfrak{sl}_3$ tails of $(2,2m)$-torus links

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2003.12278 v2 pith:FSQPX6K5 submitted 2020-03-27 math.GT math.QA

classification math.GTmath.QA
keywords mathfrakcoloredformulaslambdaone-rowcoloringcomputediagram
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

The $\mathfrak{sl}_3$ colored Jones polynomial $J_{\lambda}^{\mathfrak{sl}_3}(L)$ is obtained by coloring the link components with two-row Young diagram $\lambda$. Although it is difficult to compute $J_{\lambda}^{\mathfrak{sl}_3}(L)$ in general, we can calculate it by using Kuperberg's $A_2$ skein relation. In this paper, we show some formulas for twisted two strands colored by one-row Young diagram in $A_2$ web space and compute $J_{(n,0)}^{\mathfrak{sl}_3}(T(2,2m))$ for an oriented $(2,2m)$-torus link. These explicit formulas derives the $\mathfrak{sl}_3$ tail of $T(2,2m)$. They also give explicit descriptions of the $\mathfrak{sl}_3$ false theta series with one-row coloring because the $\mathfrak{sl}_2$ tail of $T(2,2m)$ is known as the false theta series.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A comprehensive Persian offline handwritten database for investigating the effects of heritability and family relationships on handwriting

    cs.CV 2025-09 conditional novelty 7.0 of 10

    A 2,128-writer Persian handwriting database with coded family relationships is presented, along with preliminary tests using image features to find similar handwriting among relatives.

  2. Enhancing AI microscopy for foodborne bacterial classification via adversarial domain adaptation across optical and biological variability

    eess.IV 2024-11 conditional novelty 5.0 of 10

    Adversarial domain adaptation with an EfficientNetV2 backbone improves classification of foodborne bacteria across microscopy modalities and magnifications using as few as 1 to 5 labeled target images per species.

  3. Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulations

    cs.LG 2024-12 reject novelty 4.0 of 10

    A quantum-tunnelling neural network is claimed to reproduce human-like classification uncertainty and train 50 times faster than a classical MLP, but the supporting evidence is absent.

Pith tools