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Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
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DLMC Dynamic Local Mass Clustering – Numerical Framework and Analysis

Authors: djebassi, mounir;

DLMC Dynamic Local Mass Clustering – Numerical Framework and Analysis

Abstract

This 3D numerical framework introduces the Dynamic Local Mass Clustering (DLMC) paradigm as a robust alternative to collisionless dark matter particles. Unlike traditional MOND or CDM models, the DLMC hypothesis resolves the Bullet Cluster (1E 0657-56) paradox through Flux Inertia. The observed spatial decoupling between baryons and potential peaks corresponds to a dynamic lag of the local curvature response, rather than a particle-based separation. By unifying the Radial Acceleration Relation (RAR) at the galactic scale with gravitational lensing at the cluster scale via vacuum coupling coefficients, this model provides a continuous hybrid solution to the "Missing Mass" problem across all cosmic scales. Included files: Jupyter Notebook (.ipynb) Python scripts (.py) CSV files of DLMC analyses and maps PNG images of outputs PDF of the full report HTML and Markdown files for reference This resource allows researchers to reproduce, analyze, and extend the DLMC framework, offering a complete tool for studying galactic structures and clusters under modified gravity conditions.

Keywords

Dynamic Local Mass Clustering, DLMC, Dark Matter, Modified Gravity, Bullet Cluster, Radial Acceleration Relation, Gravitational Lensing, Cosmology, Numerical Simulation, Astrophysics, Physics, Computational Science, Space Science

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average