Pith. sign in

REVIEW 1 cited by

A Spectral Sequence for a Graded Linear Map

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

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 2402.02560 v1 pith:X3G7VLL2 submitted 2024-02-04 math.AT

Larry Bates , Martin Bendersky , Richard Churchill This is my paper · ORCID
classification math.AT
keywords findingpolynomialspectralelementshamiltonianintegralskernellinear
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We apply the method of spectral sequences to study classical problems in analysis. We illustrate the method by finding polynomial vector fields that commute with a given polynomial vector field and finding integrals of polynomial Hamiltonian systems. For the later we describe the integrals for the Henon-Heiles Hamiltonian which arises in celestial mechanics. The unifying feature is that these problems seek elements in the kernel of a linear operator. The spectral sequence approach emphasizes the obstructions constructed from cokernel of the operator to finding elements in the kernel.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization

    cs.AI 2025-11 conditional novelty 5.0 of 10

    An adaptive summarization framework compresses chain-of-thought traces and transfers them across model families, claiming up to 40.5% accuracy gains over truncation on medical QA and 84% fewer configuration evaluation...

Pith tools