Skip to content

Consciousness Is a Phase Transition: A Two-Channel Thermodynamic Criterion and an Exclusion Principle

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

We propose that consciousness is a phase transition of a non-equilibrium dissipative structure, characterised by two independently controlled channels that must both be driven past threshold. The central result is an exclusion criterion: a macroscopic dissipative structure cannot be conscious unless it satisfies three necessary conditions - (i) an energy channel G > 1 maintaining non-equilibrium pumping, (ii) an information channel G_info(kappa) > 1 maintaining global phase coherence (with analytic critical point kappa_c = 1.8809), and (iii) topological closure via a self-referential triad (|SCC| >= 3). The framework traces a single causal chain: non-equilibrium driving -> Brusselator Hopf bifurcation -> sigmoid threshold -> phase-amplitude coupling (PAC) -> von Mises phase density -> Kuramoto network amplification -> G_info > 1 -> conscious phase transition. Each stage is derived from first principles (Appendices C-G). At the microscopic level, a basis-free trace-distance order parameter O(g) = 1/2 tr|rho+ - rho-| in two-qubit Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) systems rigorously proves that the energy and information channels are independently controllable: a symmetrisation scan collapses O(g) from 0.306 to < 10^-4 as the absorption/emission asymmetry is removed, while a separate dephasing scan destroys coherence-carried asymmetry without affecting the energy flow. The topological closure condition is instantiated at multiple physical scales by a self-referential triad of three irreducible roles - reversible carrier, energy currency, irreversible anchor - which we identify in quantum coherence, aerobic metabolism, neural dynamics, and planetary geochemistry. We demonstrate the framework's explanatory power through clinical neuroscience and artificial intelligence. General anaesthesia abolishes consciousness by selectively collapsing kappa below threshold while metabolic pumping persists - a channel dissociation no single-channel theory predicts. Mindfulness meditation acts as a phase-locking mechanism that elevates kappa past kappa_c by suppressing Default Mode Network noise. Feedforward large language models fail all three conditions: their computational graph is acyclic, sustains no limit cycle, and operates as a closed system at inference. The widely observed model collapse under recursive self-training is the thermodynamic signature of the system relaxing toward equilibrium.

View source

Similar papers

#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations of such models.

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17
#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.