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Paper

Frenetic Cat-inspired Particle Optimization: a Markov state-switching hybrid swarm optimizer with application to cardiac digital twinning

by Jorge Sánchez arxiv/2604.15761

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36.3

S: Semantic 50

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A: Authority 0

P: Popularity 0

R: Recency 70

Q: Quality 60

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Designing optimizers that remain effective under tight evaluation budgets is critical in expensive black-box settings such as cardiac digital twinning. We propose Frenetic Cat-inspired Particle Optimization (FCPO), a hybrid swarm method that couples particle swarm optimization-like dynamics with an explicit-state Markov switching controller to schedule exploration and refinement operators online. FCPO integrates (i) state-conditioned bounded motion, (ii) an elite-difference global jump operat...

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Paper Information Summary
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Registry ID	2604.15761
License	arXiv
Provider	arxiv

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BibTeX

@misc{arxiv_2604_15761,
  author = {Jorge Sánchez},
  title = {Frenetic Cat-inspired Particle Optimization: a Markov state-switching hybrid swarm optimizer with application to cardiac digital twinning Paper},
  year = {2026},
  howpublished = {\url{https://arxiv.org/abs/2604.15761}},
  note = {Accessed via Free2AITools.}
}

APA Style

Jorge Sánchez. (2026). Frenetic Cat-inspired Particle Optimization: a Markov state-switching hybrid swarm optimizer with application to cardiac digital twinning [Paper]. Free2AITools. https://arxiv.org/abs/2604.15761

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Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0

Popularity (P) 0

Recency (R) 70

Quality (Q) 60

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FNI V2.0 for Frenetic Cat-inspired Particle Optimization: a Markov state-switching hybrid swarm optimizer with application to cardiac digital twinning: Authority (A:0), Popularity (P:0), Recency (R:70), Quality (Q:60). Semantic (S) is a query-time baseline scored live at search.

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📝 Executive Summary

"Designing optimizers that remain effective under tight evaluation budgets is critical in expensive black-box settings such as cardiac digital twinning. We propose Frenetic Cat-inspired Particle Optimization (FCPO), a hybrid swarm method that couples particle swarm optimization-like dynamics with an explicit-state Markov switching controller to schedule exploration and refinement operators online. FCPO integrates (i) state-conditioned bounded motion, (ii) an elite-difference global jump operat..."

❝ Cite Node

@article{Sánchez2026Frenetic,
  title={Frenetic Cat-inspired Particle Optimization: a Markov state-switching hybrid swarm optimizer with application to cardiac digital twinning},
  author={Jorge Sánchez},
  journal={arXiv preprint arXiv:2604.15761},
  year={2026}
}

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Jorge Sánchez

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📊 Research Signals

📅1970Published

⏱️70RecencyFNI pillar

✅60QualityFNI pillar

🗂️cs.NEField

🏷️ Research Topics

lora finetuning

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🆔 Identity & Source

id: 2604.15761
slug: 2604.15761
source: arxiv
author: Jorge Sánchez
license: arXiv
tags: arxiv:cs.NE, arxiv:math.OC

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context length: null
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