PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 25, 20260 citationsOpen Access

SMETA Framework: Interaction–Memory Coupled Dynamics via Dual Ātman Model with Computational Simulation

View Full Paper
RMRajatsubhra Mukhopadhyay

Key Points

  • This work aims to develop a computational model to explore the interactions between memory and dynamics in complex systems.
  • Implemented the SMETA framework with dual Ātman components (A and B) using Python for simulation.
  • Modeled the interaction and memory dynamics to observe their feedback effects.
  • Provided documentation and simulation code for replication and verification.
  • Demonstrated memory generation through interaction within the framework.
  • Showcased emergent behavior such as clustering, stabilization, and cycles of dissolution.
  • Confirmed the hypothesis of memory's role in regulating system evolution.

Abstract

This work presents a computational implementation of the SMETA framework (Space–Mass–Energy–Time–Ātman), introducing a dual-component operational model consisting of interaction (Ātman A) and memory (Ātman B). The system demonstrates how interaction generates memory, and accumulated memory regulates future evolution, forming a non-Markovian feedback system. The repository includes: • Full scientific manuscript (PDF) • Python simulation code (SMETAdumbbell. py) • Documentation (README. md) The model exhibits emergent phase behavior including clustering, stabilization, and dissolution cycles, supporting the hypothesis of memory-regulated dynamics in complex systems. This work is part of the ongoing SMETA research framework.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Rajatsubhra Mukhopadhyay (2026) studied this question.

synapsesocial.com/papers/69c37be2b34aaaeb1a67ec07https://doi.org/10.5281/zenodo.19186603
Ask AI
Helpful
Bookmark
Share
View Full Paper