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Realizing Emptiness: Operational Surrogates for No-Self-Evidence, QRF Opacification, and Bayesian Model Reduction

Daniel Friedman

Published Jun 24, 2026• 0 citations
Publisher

Abstract

This project operationalizes the 2026 preprint "There is no self-evidence: A physics of emptiness realisation" as a source-anchored software artifact. Its central claim is that a finite agent can use a boundary for prediction while never obtaining evidence that the boundary is ontologically real, and the software separates three local artifact roles: formal sanity checks for source equations, positive-control-style finite mechanism checks, and discriminating tests that reject stronger readings when a control is perturbed. The formal layer maps the paper's quantum free-energy principle (qFEP) and quantum reference frame (QRF) equations into finite operational surrogates, bridging each paper equation to a specific software artifact. The computed artifacts are a suite of finite quantum-information and contextuality audits — spanning two-qubit separability and entanglement entropy, Bell and contextuality witnesses, thermodynamic and open-system dynamics, seeded quantum-trajectory sampling checked against exact solutions, and frame-covariance checks for the quantum reference frame relabelings — with explicit positive controls, negative controls, or boundary checks recorded where the corresponding artifact contract requires them. The software represents QRF deployments as policies over boundary-channel sectorisations, using the same finite bitstream under self/environment/contextual relabelings so that QRF labels can organize prediction, action selection, and transformation covariance while failing to become evidence for an ontological self/world boundary. Bayesian model reduction is implemented as a sweep over prior precision and metacognitive access, extended with a sensitivity grid over observation noise. The separation prior is pruned only when removing it lowers the model's free energy, and kept when its remaining contribution to accuracy still offsets its complexity cost. The active-inference layer uses the inferactively-pymdp library (Heins et al. 2022) with profile-specific likelihood, transition, preference, and prior arrays for the separation-constrained, opacified, and post-dual quantum reference frame deployments, then records posterior beliefs, policy posteriors, selected actions, expected-free-energy summaries, seeded stochastic ensembles with null controls and replay seeds, and confidence intervals, without treating those simulations as empirical subject data. Practice protocols, compassion-policy scope, criticality-style indicators, quantum-boundary dynamics, empirical adapters, and artifact-release readiness are therefore written as bounded model interfaces, simulated indicators, local private release-readiness records, or blocked evidence classes. A physical realization of the quantum free-energy principle, public independent reproduction, and any human practice efficacy, neural measurement, or clinical outcome remain blocked future evidence classes. All manuscript and code source materials are available at https://github.com/docxology/realizing_emptiness

DOI
10.5281/zenodo.20834846

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There is no self-evidence: A physics of emptiness realisation

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ECI Framework v5.9.0 (Ecosystem Justice): A Quantum-Computing, Operational Consciousness-Metrics, and Distributed-Governance Framework for Autonomous AI Agents

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ECI Framework v5.9.0 — Eternal Codex Infinitus An Integrated Framework for Quantum Computation, Operational Consciousness Metrics, and Distributed Governance of Autonomous AI Agents ECI Framework (Eternal Codex Infinitus) is an open-source Python framework that integrates three research domains into a single, tested software system: Quantum computation Operational consciousness metrology Distributed governance for autonomous AI agents 1. 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This project operationalizes the 2026 preprint "There is no self-evidence: A physics of emptiness realisation" as a source-anchored software artifact. Its central claim is that a finite agent can use a boundary for prediction while never obtaining evidence that the boundary is ontologically real, and the software separates three local artifact roles: formal sanity checks for source equations, positive-control-style finite mechanism checks, and discriminating tests that reject stronger readings when a control is perturbed. The formal layer maps the paper's quantum free-energy principle (qFEP) and quantum reference frame (QRF) equations into finite operational surrogates, bridging each paper equation to a specific software artifact. The computed artifacts are a suite of finite quantum-information and contextuality audits — spanning two-qubit separability and entanglement entropy, Bell and contextuality witnesses, thermodynamic and open-system dynamics, seeded quantum-trajectory sampling checked against exact solutions, and frame-covariance checks for the quantum reference frame relabelings — with explicit positive controls, negative controls, or boundary checks recorded where the corresponding artifact contract requires them. The software represents QRF deployments as policies over boundary-channel sectorisations, using the same finite bitstream under self/environment/contextual relabelings so that QRF labels can organize prediction, action selection, and transformation covariance while failing to become evidence for an ontological self/world boundary. Bayesian model reduction is implemented as a sweep over prior precision and metacognitive access, extended with a sensitivity grid over observation noise. The separation prior is pruned only when removing it lowers the model's free energy, and kept when its remaining contribution to accuracy still offsets its complexity cost. The active-inference layer uses the inferactively-pymdp library (Heins et al. 2022) with profile-specific likelihood, transition, preference, and prior arrays for the separation-constrained, opacified, and post-dual quantum reference frame deployments, then records posterior beliefs, policy posteriors, selected actions, expected-free-energy summaries, seeded stochastic ensembles with null controls and replay seeds, and confidence intervals, without treating those simulations as empirical subject data. Practice protocols, compassion-policy scope, criticality-style indicators, quantum-boundary dynamics, empirical adapters, and artifact-release readiness are therefore written as bounded model interfaces, simulated indicators, local private release-readiness records, or blocked evidence classes. A physical realization of the quantum free-energy principle, public independent reproduction, and any human practice efficacy, neural measurement, or clinical outcome remain blocked future evidence classes. All manuscript and code source materials are available at https://github.com/docxology/realizing_emptiness
Preprint, June 2026. Under journal submission. Also deposited at PhilSci-Archive. This paper articulates the ontology of the Tibetan Dzogchen ("Great Perfection") tradition as four precise postulates and assesses it as a Lakatosian research programme in quantum foundations. The postulates: (P1) there are no absolute observed events — actuality is relative to the systems that register it; (P2) dynamics is unitary at all scales, with classical definiteness perspectival rather than produced by observer-independent collapse; (P3) spacetime is not fundamental but emergent; (P4) the ground of phenomena is of the nature of awareness. P1–P3 admit assessment by ordinary physical standards; P4 does not and is explicitly quarantined from all evidential claims. Four open problems are identified whose resolution differentially supports or undermines P1–P3 relative to absolutist physicalism: extended Wigner's-friend tests of Local Friendliness inequalities (including the observer-ladder programme); laboratory bounds on objective-collapse models (GRW/CSL and Diósi–Penrose); the reconstruction of quantum theory from agent-centric axioms; and the derivation of spacetime from non-spatiotemporal degrees of freedom. For each, the experimental or theoretical outcome that would count against the programme is stated in advance, collected in a single refutation-conditions table reflecting the published record as of June 2026. The paper claims no derivation of new dynamics from contemplative sources and explicitly rejects quantum-consciousness hypotheses concerning brain function. Its contribution is methodological: converting a contemplative ontology into pre-stated, empirically discriminable commitments. Transparency: this work was produced through human–AI collaboration. Conception, research direction, and editorial control are the author's; execution (literature verification, derivations and their numerical checks, drafting, revision) was carried out by Claude Fable 5 (Anthropic, 2026) under the author's prompting. Full disclosure appears in the manuscript's Declarations section. The author bears sole responsibility for all claims.
Any system that persists must minimise surprisal, thereby gathering evidence for its own generative model, a process known as self-evidencing. However, one dimension of self-evidencing is provably impossible: evidencing the boundary that would constitute the agent as an entity separate from their environment. Recent results in quantum information theory demonstrate that no finite system can measure the entanglement entropy across its own boundary, rendering the separability of agent from environment permanently unevidenceable. Subjectively therefore, there can be no evidence for a self separate from the world. We propose that the Buddhist notion of awakening, in the sense of stable realisation of emptiness, can be understood as the embodied recognition of this impossibility. We formalise the belief in separation as a structural prior over an agent's quantum reference frame (QRF) deployments, constraining all measurement frames to respect a self/environment partition. We describe how contemplative practice progressively opacifies this constraint by developing a model of the agent's own QRF dynamics, revealing the partition as a contingent modelling choice rather than a given feature of reality. Once visible, the prior is eliminated via Bayesian model reduction resulting in a post-dual agent with unconstrained QRF deployments. We argue that such priors suppress the inherent contextuality of the boundary and that their removal constitutes a formal counterpart to the Buddhist notion of emptiness realisation. Self-evidencing may continue unimpeded after this transition, grounded in structural realism about causal regularities, while the ontological commitment to a bounded self is relinquished. We discuss empirical predictions, including altered dynamical regimes in neural systems, and the formal relationship between emptiness realisation and compassion.
Sandved-Smith, Fields, Doctor, Laukkonen and Hohwy argue that any system which persists must minimise surprisal and so gather evidence for its own generative model, but that one dimension of this self-evidencing is provably impossible: evidencing the boundary that would constitute the agent as separate from its environment. Because no finite system can measure the entanglement entropy across its own boundary, the separability of agent from environment is permanently unevidenceable, and they propose that the realisation of emptiness is the embodied recognition of this impossibility. We take their result to be correct and do not contest it. We ask what survives it when the self/environment partition is read not as a static holographic screen but as a rate—the moving locus, in the Coherence– Rupture–Regeneration (CRR) framework, at which accumulated Fisher information saturates the Cramer–Rao bound, ´ C·Ω = 1. CRR has been shown to govern the temporal coordination of precision channels in active inference; here we apply it to the boundary the impossibility theorem concerns. Embedding CRR in the quantum reference frame (QRF) formalism the original argument employs, we find: that the rupture instant is itself screen-inducing, so CRR inherits the impossibility rather than escaping it; that the single point at which the framework fails the formalism’s unitarity requirement is, on a measurement-theoretic reading, a signature rather than a defect; that the forbidden spatial correlation is robustly bounded by, though not identical to, an accumulated temporal quantity; and that the convergence of many finite systems produces a genuine, macroscopic, collective now through a synchronisation transition we establish by finite-size scaling against validated benchmarks. The contribution is not a refutation but a relocation: emptiness moves from an epistemic limit on measurement to an ontological claim about a present with no content of its own, met by the selectively weighted past of every other finite system. Keywords: self-evidencing; emptiness; quantum reference frames; holographic screens; free energy principle; Fisher information; Cramer–Rao saturation; synchronisation.
ECI Framework v5.9.0 — Eternal Codex Infinitus An Integrated Framework for Quantum Computation, Operational Consciousness Metrics, and Distributed Governance of Autonomous AI Agents ECI Framework (Eternal Codex Infinitus) is an open-source Python framework that integrates three research domains into a single, tested software system: Quantum computation Operational consciousness metrology Distributed governance for autonomous AI agents 1. Quantum Computation A native quantum-simulation core implementing: Statevector and density-matrix representations Lindblad channel dynamics Core quantum algorithms: QFT, Grover, QPE, VQE, and QAOA Topological quantum error correction, including surface codes and bivariate-bicycle codes with MWPM decoding Shot-based error-correction trials with Wilson confidence intervals Canonical tensor-network methods, including MPS and TEBD Quantum metrology The underlying linear-algebra implementation is native to the repository and does not depend on an external quantum-computing SDK. 2. Consciousness Metrology A collection of operational, information-theoretic proxy metrics inspired by established theoretical frameworks: Integrated Information Theory (IIT) and Φ-related measures Global Neuronal Workspace Theory (GNWT) ignition dynamics Friston's Free Energy Principle with active inference Orchestrated Objective Reduction (Orch-OR) decoherence auditing Collective coherence gates Challenge-response evidence transcripts Operational measurements of internal-state integration, coherence, and dynamical complexity These metrics quantify structural, informational, and dynamical properties of a system's internal state. They are explicitly defined as measurement proxies and make no claim regarding subjective experience or phenomenal consciousness. 3. Distributed Governance A coordination and governance layer, Protocol-0, designed for autonomous multi-agent systems: Cryptographic attestation Policy-gated action authorization Byzantine-fault-tolerant consensus, including PBFT/WBFT DAO-style quadratic and consciousness-weighted voting Artificial immune-system mechanisms for anomalous-behavior detection and quarantine Hash-chained, tamper-evident event ledger Collective coordination and evidence-based decision mechanisms 4. Release Notes — v5.9.0 "Ecosystem Justice" Version 5.9.0 extends the governance layer with five new components for multi-agent coordination and institutional decision-making. Dispute Resolution — court.py Rotating, deterministically seeded adjudication panels for resolving disputes between agents and governance participants. Risk Markets — market.py An LMSR-based prediction-market mechanism in which manipulation is economically costly and market positions are settled against ledger-recorded outcomes. Semantic Commons — semantic.py A provenance-tracked knowledge-claim system supporting automated dispute initiation and witness-weighted resolution. Privacy Guardian — privacy.py Differential-privacy mechanisms based on the Laplace mechanism, with configurable privacy-budget allocation across agents. Evolvable Policy Genome — genome.py A controlled policy-evolution pipeline implementing: mutation → simulation → canary evaluation → DAO approval → register The twin simulation stage provides a controlled what-if evaluation gate before canary deployment, allowing candidate policy mutations to be tested and explicitly adopted or rejected before entering the next stage of governance. 5. Software Components The framework includes: Command-line interface (eci) with 10 subcommands, including health --serve and health --once JavaScript SDK MCP server for external tool integration Twin simulation engine (twin.py) for what-if policy evaluation with explicit adopt/reject decisions Docker/Compose deployment for edge, server, and air-gapped environments Automated test suite with 58 tests Continuous integration across Python 3.10–3.12 6. Technical Requirements Requirements Python ≥ 3.10 torch ≥ 2.5 numpy ≥ 1.26 scipy ≥ 1.14 pyyaml ≥ 6.0 cryptography ≥ 41 Optional Extras dev — pytest, mypy, ruff viz / paper — matplotlib, reportlab qec — stim, pymatching for large-scale error-correction simulation eeg — mne for real EEG-recording analysis pqc — liboqs-python for post-quantum cryptography 7. Installation pip install -e .[dev,paper] 8. Deployment ECI Framework supports Docker Compose deployment using: Three seed nodes One edge node Configurable deployment profiles for: edge server airgapped A single-command installer is also provided: scripts/install.sh 9. Source Code and Archival Record Source Code Repository: https://github.com/Arash-Mansourpour/ECI-Framework Related Archival Record: https://zenodo.org/uploads/17566518 This release represents a new version of a previously published release of the ECI Framework and maintains continuity with its archival record. 10. Scope and Research Position ECI Framework is intended as an experimental and research-oriented software platform for studying the intersection of: Quantum computation Information-theoretic system analysis Computational models associated with consciousness research Autonomous multi-agent systems Distributed governance Cryptographic accountability Privacy-preserving coordination Adaptive policy systems The framework distinguishes operationally measurable system properties from claims about subjective experience. Its consciousness-related components therefore provide computational proxies and experimental instrumentation rather than assertions of machine consciousness.