Systemic Consistency Synchronization Protocol (SCSP): A Logical Reconstruction of Maxwell's Equations

This paper introduces the Systemic Consistency Synchronization Protocol (SCSP), a novel logical architecture designed to reconstruct classical electrodynamics (Maxwell’s Equations) through the lens of pure informational logic. By discarding traditional physical entities in favor of system-level primitives—such as Logic Depth, Decision Step, Static Correlation, and Dynamic Correction—we demonstrate that physical laws are isomorphic to consistency maintenance mechanisms in a distributed system. The SCSP framework establishes that: Electromagnetic phenomena are emergent "patches" required to offset synchronization latency and maintain causal consistency across network indices. The speed of light ( c) is not a physical constant but a fundamental system constraint defined by the ratio of the minimum decision scale to logic depth units. Physical "laws" are essentially low-level protocols designed to prevent logical conflicts (bugs) within the universal substrate. By providing a rigorous mapping between Maxwell’s equations and SCSP axioms, this research proves that physics can be treated as a subset of logic. This work provides a theoretical foundation for understanding the universe as a self-synchronizing computational entity.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-27
DOI
https://doi.org/10.5281/zenodo.19813171
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Systemic Consistency Synchronization Protocol (SCSP): A Logical Reconstruction of Maxwell's Equations

Yue Lu
Zenodo (CERN European Organization for Nuclear Research)
Modular Robots and Swarm Intelligence
article

Systemic Consistency Synchronization Protocol (SCSP): A Logical Reconstruction of Maxwell's Equations

Yue Lu
article en

Abstract

This paper introduces the Systemic Consistency Synchronization Protocol (SCSP), a novel logical architecture designed to reconstruct classical electrodynamics (Maxwell’s Equations) through the lens of pure informational logic. By discarding traditional physical entities in favor of system-level primitives—such as Logic Depth, Decision Step, Static Correlation, and Dynamic Correction—we demonstrate that physical laws are isomorphic to consistency maintenance mechanisms in a distributed system. The SCSP framework establishes that: Electromagnetic phenomena are emergent "patches" required to offset synchronization latency and maintain causal consistency across network indices. The speed of light ( c) is not a physical constant but a fundamental system constraint defined by the ratio of the minimum decision scale to logic depth units. Physical "laws" are essentially low-level protocols designed to prevent logical conflicts (bugs) within the universal substrate. By providing a rigorous mapping between Maxwell’s equations and SCSP axioms, this research proves that physics can be treated as a subset of logic. This work provides a theoretical foundation for understanding the universe as a self-synchronizing computational entity.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Modular Robots and Swarm Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Systemic Consistency Synchronization Protocol (SCSP): A Logical Reconstruction of Maxwell's Equations — Yue Lu · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS