Pith. sign in

REVIEW 3 cited by

The signature and cusp geometry of hyperbolic knots

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 2111.15323 v3 pith:ZPGGYAAL submitted 2021-11-30 math.GT cs.AIstat.ML

classification math.GTcs.AIstat.ML
keywords knothyperbolicslopecuspgeometryinequalitynaturalsignature
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We introduce a new real-valued invariant called the natural slope of a hyperbolic knot in the 3-sphere, which is defined in terms of its cusp geometry. We show that twice the knot signature and the natural slope differ by at most a constant times the hyperbolic volume divided by the cube of the injectivity radius. This inequality was discovered using machine learning to detect relationships between various knot invariants. It has applications to Dehn surgery and to 4-ball genus. We also show a refined version of the inequality where the upper bound is a linear function of the volume, and the slope is corrected by terms corresponding to short geodesics that link the knot an odd number of times.

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. OpenAlex reports about 5 citations worldwide. Full citation record

  1. Structure of the chromatic polynomial

    math.AT 2024-11 conditional novelty 6.0 of 10

    PCA and Ball Mapper show the chromatic polynomials of small graphs form an essentially one-dimensional cloud ordered by edges, with a second direction tied to irregularity.

  2. Pre-Strings Lectures on Artificial Intelligence

    hep-th 2026-07 accept novelty 5.5 of 10

    Lecture notes define neural-network field theory and survey how it recovers known QFT/string results plus applied AI techniques for string problems.

  3. PowerMLP: An Efficient Version of KAN

    cs.LG 2024-12 reject novelty 4.0 of 10

    PowerMLP is a ReLU-power MLP that trains about 40x faster than KAN in the reported benchmarks and often beats it, but the main proof that KANs are contained in PowerMLPs at the same depth is flawed.

Pith tools