Monogate – EML operator family, hybrid framework, 108-node sin(x)

Name: Monogate – EML operator family, hybrid framework, 108-node sin(x)
Availability: InStock
Author: zonked45

by zonked45·Apr 15, 2026·2 points·0 comments

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AI Analysis

●●●BangerWizardryBig BrainNiche Gem

Found phantom attractors and cut node counts 52-74% beyond the original paper.

Strengths

•Discovered new mathematical insights in 36 hours beyond the published paper
•HybridOperator achieves machine-precision sin(x) at just 108 nodes
•Challenge board creates community engagement around open mathematical problems

Weaknesses

•Extremely niche audience — mathematical programming is a tiny community
•Documentation assumes familiarity with EML operator theory and principal-branch ln

Post Description

EML operator family, 52-74% node reduction, and empirical results from 36 hours of building We spent 36 hours implementing and extending arXiv:2603.21852 (Odrzywołek, 2026 — the "NAND gate for continuous math" paper that was on the front page two days ago). What we found: phantom attractors in EML symbolic regression, a Lambert W fixed point governing right-chain trees, two new operators (EDL, EXL), a HybridOperator that cuts node counts 52-74%, and machine-precision Taylor sin(x) at 108 nodes. npm install monogate / pip install monogate Live explorer: https://explorer.monogate.dev/ Challenge board: monogate.dev Paper draft: github.com/almaguer1986/monogate/blob/main/python/PAPER.md

just vibe coding this with claude and grok

hopefully this is helpful or useful to someone