Pith. sign in

REVIEW 2 cited by

Zakharov-Ito equation and Generalized Heisenberg ferromagnet-type equation: equivalence and related geometric curve flows

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 2004.12816 v1 pith:SLJ3AST5 submitted 2020-04-23 nlin.SI

Zakharov-Ito equation and Generalized Heisenberg ferromagnet-type equation: equivalence and related geometric curve flows

Zhanbala Umbetova , Shynaray Myrzakul , Kuralay Yesmakhanova , Tolkynay Myrzakul , Gulgassyl Nugmanova , Ratbay Myrzakulov This is my paper
classification nlin.SI
keywords equationequivalentghfeequationsferromagnet-typegeneralizedheisenbergintegrable
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

These results continue our studies of integrable generalized Heisenberg ferromagnet-type equations (GHFE) and their equivalent counterparts. We consider the GHFE which is the spin equivalent of the Zakharov-Ito equation (ZIE). We have established that these equations are gauge and geometrical equivalent to each other. The integrable motion of space curves induced by the ZIE is constructed. The 1-soliton solution of the GHFE is obtained from the seed solution of the ZIE.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

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

  1. Quality-Assured Fuzz Harness Generation via the Four Principles Framework

    cs.CR 2026-05 unverdicted novelty 6.0

    QuartetFuzz introduces the Four Principles framework for harness correctness and deploys an autonomous LLM agent that produces verified harnesses, yielding 29 confirmed bugs across 23 projects and identifying violatio...

  2. Blink: CPU-Free LLM Inference by Delegating the Serving Stack to GPU and SmartNIC

    cs.DC 2026-04 unverdicted novelty 6.0

    Blink enables CPU-free LLM inference via SmartNIC offload and persistent GPU kernel, delivering up to 8.47x lower P99 TTFT, 3.4x lower P99 TPOT, 2.1x higher decode throughput, and 48.6% lower energy per token while re...