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

**Daniel Ari Friedman** (2026) · *Zenodo*

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.20834846.svg)](https://doi.org/10.5281/zenodo.20834846)

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## Abstract

<div>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 &mdash; 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 &mdash; 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.&nbsp;</div>
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<div>All manuscript and code source materials are available at <a href="https://github.com/docxology/realizing_emptiness">https://github.com/docxology/realizing_emptiness</a></div>

## Keywords

active inference · Bayesian model reduction · quantum reference frames · emptiness · formal methods · pymdp

## Publication Details

| Field | Value |
|------|-------|
| **DOI** | [10.5281/zenodo.20834846](https://doi.org/10.5281/zenodo.20834846) |
| **Published** | 2026-06-24 |
| **Version** | 1.0.0 |
| **Zenodo record** | https://zenodo.org/records/20834847 |
| **GitHub release** | https://github.com/docxology/realizing_emptiness/releases/tag/v1.0.0 |
| **Source repository** | https://github.com/docxology/realizing_emptiness |

## Files

- `realizing_emptiness_combined.pdf` - Zenodo PDF

## Citation

> Friedman, D. A. (2026). *Realizing Emptiness: Operational Surrogates for No-Self-Evidence, QRF Opacification, and Bayesian Model Reduction*. Zenodo. https://doi.org/10.5281/zenodo.20834846

## Related

- Zenodo record: https://zenodo.org/records/20834847
- GitHub release: https://github.com/docxology/realizing_emptiness/releases/tag/v1.0.0
- Source repository: https://github.com/docxology/realizing_emptiness
- [Full Bibliography](../../pages/BIBLIOGRAPHY.md) · [All Papers](../README.md)
