Colored Jones Polynomials and the Volume Conjecture
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Abstract (arXiv)
Using the vertex model approach for braid representations, we compute polynomials for spin-1 placed on hyperbolic knots up to 15 crossings. These polynomials are referred to as 3-colored Jones polynomials or adjoint Jones polynomials. Training a subset of the data using a fully connected feedforward neural network, we predict the volume of the knot complement of hyperbolic knots from the adjoint Jones polynomial or its evaluations with 99.34% accuracy. A function of the adjoint Jones polynomial evaluated at the phase q=e 8 π i / 15 predicts the volume with nearly the same accuracy as the neural network. From an analysis of 2-colored and 3-colored Jones polynomials, we conjecture the best phase for n-colored Jones polynomials, and use this hypothesis to motivate an improved statement of the volume conjecture. This is tested for knots for which closed form expressions for the n-colored Jones polynomial are known, and we show improved convergence to the volume.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 59 references that are in the map. First posted on arXiv 25 Feb 2025.
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References · 7
- 2020Learning to Unknotcited by 40
- 2023Is deep learning a useful tool for the pure mathematician?cited by 14
- 2020Disentangling a Deep Learned Volume Formulacited by 12
- 2021Learning knot invariants across dimensionscited by 12
- 2024Rigor with Machine Learning from Field Theory to the Poincar'e Conjecturecited by 12
- 2019Big Data Approaches to Knot Theory: Understanding the Structure of the Jones Polynomialcited by 7
- 2024Learning BPS Spectra and the Gap Conjecturecited by 3
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