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Normalization of twisted Alexander invar...

Kitayama, Takahiro...

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Normalization of twisted Alexander invariants by Kitayama, Takahiro ( Author )

Content Provider	Lemonjar Open Access
Publisher	Australian National University
Publication Date	04-08-2023
Summary	Twisted Alexander invariants of knots are well-defined up to multiplication of units. We get rid of this multiplicative ambiguity via a combinatorial method and define normalized twisted Alexander invariants. We then show that the invariants coincide with sign-determined Reidemeister torsion in a normalized setting, and refine the duality theorem. We further obtain necessary conditions on the invariants for a knot to be fibered, and study behavior of the highest degrees of the invariants.
ISBN	-
Item Type	Article
File Type	pdf
File Size	29.34 KB
Language	English
Subjects	-
Unlimited	MYR 0.01
Total read	-
URL	http://arxiv.org/abs/0705.2371

Citation

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AMA 11th EditionReferences

Kitayama, Takahiro. Normalization of twisted Alexander invariants. Australian National University. August 04, 2023. Accessed August 12, 2025. https://online.provdatabase.com/cite/10358

APA 7th EditionReferences

Kitayama, Takahiro. (2023). Normalization of twisted Alexander invariants. Australian National University. https://online.provdatabase.com/cite/10358

Chicago 17th EditionReferences

Kitayama, Takahiro. Normalization of twisted Alexander invariants. Australian National University. 2023. https://online.provdatabase.com/cite/10358

HarvardReferences

Kitayama, Takahiro. (2023). Normalization of twisted Alexander invariants. [Online]. Australian National University. Available from: https://online.provdatabase.com/cite/10358. (Accessed 12 August 2025).

Harvard AustraliaReferences

Kitayama, Takahiro, 2023, Normalization of twisted Alexander invariants, Australian National University, viewed 12 August 2025, <https://online.provdatabase.com/cite/10358>

MLA 9th EditionWorks Cited

Kitayama, Takahiro. Normalization of twisted Alexander invariants. Australian National University, 2023. PROV Database, https://online.provdatabase.com/cite/10358.

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