Information as the Foundation of Reality: From Observation to Distinction

This report proposes a radical revision of the scientific paradigm, asserting the primacy of information over matter, energy, and time. We proceed from the thesis that reality fundamentally consists not of objects, but of distinctions that manifest through informational structures and are fixed in consciousness. The work demonstrates the limitations of existing scientific methodology based on locality, materialism, and neutrality of observation, and proposes a new methodology of distinction, where the subject is recognized as an ontologically primary element of scientific cognition. The concept of the muktashif—a new type of researcher capable of distinguishing tensions in the information field—is introduced, along with the spinor as a mathematical instrument for formalizing the process of distinction. The practical application of the new paradigm is an information-fractal model for predicting seismic activity, based not on linear causality but on recognizing nonlocal patterns. We also present an organizational structure for implementing this approach in the form of a fractal network of distinguishing nodes. This report aims not only to propose a new scientific model but to initiate an ontological transformation of our understanding of reality, returning meaning and the subject to the center of scientific cognition.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-05
DOI
https://doi.org/10.5281/zenodo.15342076
Primary Topic
Chaos, Complexity, and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Information as the Foundation of Reality: From Observation to Distinction

Zenodo (CERN European Organization for Nuclear Research)
Chaos, Complexity, and Education
article

Information as the Foundation of Reality: From Observation to Distinction

article en

Abstract

This report proposes a radical revision of the scientific paradigm, asserting the primacy of information over matter, energy, and time. We proceed from the thesis that reality fundamentally consists not of objects, but of distinctions that manifest through informational structures and are fixed in consciousness. The work demonstrates the limitations of existing scientific methodology based on locality, materialism, and neutrality of observation, and proposes a new methodology of distinction, where the subject is recognized as an ontologically primary element of scientific cognition. The concept of the muktashif—a new type of researcher capable of distinguishing tensions in the information field—is introduced, along with the spinor as a mathematical instrument for formalizing the process of distinction. The practical application of the new paradigm is an information-fractal model for predicting seismic activity, based not on linear causality but on recognizing nonlocal patterns. We also present an organizational structure for implementing this approach in the form of a fractal network of distinguishing nodes. This report aims not only to propose a new scientific model but to initiate an ontological transformation of our understanding of reality, returning meaning and the subject to the center of scientific cognition.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 56%
Chaos, Complexity, and Education
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.

Information as the Foundation of Reality: From Observation to Distinction · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS