Void Dynamics Model
Published September 10, 2025 | Version v4
Working paper Open

Counterfactual Echo Gain (CEG): Future-Aware Metriplectic Assistance Yields Gate-Certified Echo Improvement

Authors/Creators

Contributors

Project member:

Description

Summary:

This now includes the preregistered CEG outcome and gate statuses for the metriplectic assisted‑echo experiment. It makes no novelty claims about echo mechanisms; the claim is strictly that a model‑aware assistance micro‑sequence yields a statistically positive echo gain under instrument gates and an energy‑match constraint. Numerical scheme is treated as the measuring instrument per VDM canon.
 
Under preregistered conditions and strict gates, the metriplectic assisted‑echo exhibits a statistically positive CEG (median\_max 0.054552 at λ=0.5) while preserving J‑Noether and M‑monotonicity and passing Strang defect QC. This supports the preregistered claim that internal J/M knowledge can be operationally exploited to improve echo recovery without cheating via energy injection.
 

Original proposal description:

This is a T4 preregistration for an experiment that tests whether a metriplectic, model-aware assisted time-reversal can improve echo fidelity in the Void Dynamics Model (VDM). We define the preregistered metric Counterfactual Echo Gain (CEG) and a set of strict physics gates (J-Noether drift, M-monotonicity / H-theorem, and energy-matching) that must be satisfied. The primary hypothesis is that the median CEG across preregistered seeds will be ≥ 0.05 under the gates and controls. No results or artifacts are included here — this deposit documents the exact predictions, machine-readable specs, and provenance (commit SHA) prior to running the preregistered experiments.

Original results description:

A structure‑preserving, metriplectic Strang‑composed KG⊕RD solver is paired with a preregistered, equal‑work assisted‑echo meter (CEG). Under strict J‑Noether, M‑Lyapunov, and Strang order gates, the instrument exhibits a statistically positive counterfactual echo gain (medianλ_\lambdaλ CEG =0.054552=0.054552=0.054552 at λ=0.5\lambda=0.5λ=0.5, n=12n=12n=12 seeds), with energy parity and invariants within machine‑precision tolerances. Artifacts (CSV/JSON/PNG) and seeds are pinned for reproduction.

Table of contents

CEG_FULL_PACKAGE/  (28.9 MB){13.0 compressed}
├── 20251104_123411_assisted_echo__assisted-echo-t4-prereg-v1c.json  (15.2 MB)
├── 20251104_123412_20251104_123412_assisted_echo_phase__assisted-echo-t4-prereg-v1c.png  (249.6 KB)
├── 20251104_123412_assisted_echo_telemetry__assisted-echo-t4-prereg-v1c.csv  (5.3 MB)
├── 20251104_123413_20251104_123412_assisted_echo_ceg_vs_lambda__assisted-echo-t4-prereg-v1c.png  (120.6 KB)
├── 20251104_123413_20251104_123412_assisted_echo_energy_budget__assisted-echo-t4-prereg-v1c.png  (65.7 KB)
├── 20251104_123413_20251104_123412_assisted_echo_error_timeseries__assisted-echo-t4-prereg-v1c.png  (139.4 KB)
├── 20251104_123414_20251104_123412_assisted_echo_endpoint_distance__assisted-echo-t4-prereg-v1c.png  (65.2 KB)
├── 20251104_123414_20251104_123412_assisted_echo_entropy_production__assisted-echo-t4-prereg-v1c.png  (68.5 KB)
├── 20251104_123414_20251104_123412_assisted_echo_noether_drift__assisted-echo-t4-prereg-v1c.png  (31.2 KB)
├── 20251104_123415_20251104_123412_assisted_echo_assist_alignment__assisted-echo-t4-prereg-v1c.png  (37.2 KB)
├── 20251104_123415_20251104_123412_assisted_echo_seed_stability__assisted-echo-t4-prereg-v1c.png  (26.7 KB)
├── 20251104_123415_20251104_123412_assisted_echo_telemetry_overlay__assisted-echo-t4-prereg-v1c.png  (182.1 KB)
├── 20251104_123415_20251104_123412_assisted_echo_work_partition__assisted-echo-t4-prereg-v1c.png  (35.6 KB)
├── T4_PROPOSAL_CEG_AssistedECHO.pdf  (279.5 KB)
├── T4_PROPOSAL_CEG_Metriplectic_Assisted-Echo_Experiment.md  (15.8 KB)
├── T4_RESULTS_CEG_AssistedECHO.pdf  (1.2 MB)
├── T4_RESULTS_CEG_Metriplectic_Assistance.zip  (5.9 MB)
├── T4_RESULTS_CEG_Metriplectic_Assisted-Echo_Experiment.md  (9.1 KB)
└── ceg_instrumentation.zip  (26.1 KB)

Total: 19 files, 28.9 MB

Technical info

This package is presented with redundant front-facing figures, the paper, and
CEG_PROVENANCE_manifest_20260416161851.json as a Zenodo reviewing convenience.

The CEG_FULL_PACKAGE.zip package contains everything discussed.

Notes

Along with the figures and tables referenced in the paper, the ZIP package
includes the Counterfactual Echo Gain instrumentation you can test and use yourself.
Honest effort has been made to create a genuinely unbiased and falsifiable
perspective. In addition, an instrumentation package, and a
CEG_PROVENANCE_manifest_20260416161851.json have been included to give a reviewer full
observability and control over their own review process.

Attempts to disprove the work of Neuroca, Inc. and our affiliated researchers
are highly encouraged. If your critique successfully falsifies any of our
findings and we are able to verify your results, we will publish a formal
follow-up paper confirming your criticisms, officially conceding the original
claims, and giving you full credit for the correction.

Contact: justin@neuroca.ai

Other

HOW TO CONTRIBUTE
=================

You are encouraged to find flaws, try to break the proofs or claims contained
in this work, or look for additional overlooked findings. You can also
contribute by emailing me at justin@neuroca.ai with research ideas,
improvement suggestions for my research strategies, or relevant external
research I should be aware of.

Another powerful way to contribute - without doing research of your own - is
to tell people about the work. When doing so, please explain that none of the
Void Dynamics Model research is meant to be ethereal. It should always be
concrete, falsifiable, and grounded in reality. If it cannot be computed,
observed, measured, or destroyed, then it should not have been published.

Lastly, you can contribute by checking out my other educational,
entertainment, or social engagement resources to learn more about the research
and help spread visibility:

LINKS
-----
X                  - https://x.com/quantumjunk
YouTube            - https://www.youtube.com/@NeurocaAI
Podcast            - https://rss.com/podcasts/void-dynamics-model/
Zenodo Community   - https://zenodo.org/communities/void-dynamics-model/records?q=&l=list&p=1&s=10&sort=newest
Academia.edu       - https://independent.academia.edu/justinlietz
License            - https://github.com/justinlietz93/Prometheus_VDM/blob/main/LICENSE.md
GitHub             - https://github.com/justinlietz93
ORCID              - https://orcid.org/0009-0008-9028-1366
Medium             - https://medium.com/@jlietz93
Neuroca.ai         - https://www.neuroca.ai/
LinkedIn           - https://www.linkedin.com/in/justinlietz1993/
Instagram          - https://www.instagram.com/justin_k_lietz/
Hugging Face       - https://huggingface.co/jlietz93
Reddit             - https://www.reddit.com/r/VoidDynamicsModel/

CODE REPOSITORIES
-----------------
Active VDM Repo              - https://github.com/justinlietz93/Prometheus_VDM.git
Cogito Research (de-prio)    - https://github.com/Neuroca-Inc/Cogito-Research
Neuroca Software (de-prio)   - https://github.com/Neuroca-Inc/_Neuroca

Files

T4_RESULTS_CEG_AssistedECHO.pdf

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Additional details

Additional titles

Other (En)
Counterfactual Echo Gain (CEG): A Metriplectic Assisted-Echo Experiment Proposal in VDM

Cites
Software: https://github.com/justinlietz93/Prometheus_VDM (URL)
Describes
10.5281/zenodo.19570286 (DOI)
10.5281/zenodo.18726328 (DOI)
10.5281/zenodo.19567850 (DOI)
10.5281/zenodo.19155003 (DOI)
10.5281/zenodo.17220869 (DOI)
10.5281/zenodo.19550007 (DOI)
Is supplemented by
10.5281/zenodo.19380435 (DOI)
10.5281/zenodo.19380257 (DOI)
10.5281/zenodo.19379928 (DOI)
10.5281/zenodo.19164028 (DOI)
10.5281/zenodo.19163200 (DOI)
10.5281/zenodo.19163157 (DOI)
10.5281/zenodo.19163003 (DOI)

Dates

Submitted
2025-11-04
Added to Zenodo for provenance
Updated
2025-11-10
Attached preregistered results
Updated
2026-04-16
Added existing instrumentation package for reproducibility, dramatically enhanced Zenodo presentation
Created
2025-09-10
Collected results

Software

Repository URL
https://github.com/justinlietz93/Prometheus_VDM/tree/main/Derivation/code/physics/metriplectic
Programming language
Python
Development Status
Active

References

  • J. K. Lietz, T4 — Counterfactual Echo Gain (CEG): A Metriplectic Assisted-Echo Experiment in VDM (Preregistration / Proposal), 2025. Zenodo / repository draft (preregistration text). Commit: 80ee5476e4f887fed3c34534a99daa878f55382f. Contact: justin@neuroca.ai. ORCID: 0009-0008-9028- 1366.
  • J. K. Lietz, VDM: Metriplectic Assisted-Echo — code and experiment artifacts (repository snapshot), 2025. Git repository, commit 80ee5476e4f887fed3c34534a99daa878f55382f (useful for provenance).
  • VDM EQUATIONS Registry, EQUATIONS Registry — discrete action, Euler–Lagrange and RD/KG update forms, 2024. VDM instrument registry (instrument manual for assisted-echo experiment).
  • E. Hairer, C. Lubich, and G. Wanner, Geometric Numerical Integration: Structure-Preserving Algorithms for Ordinary Differential Equations, 2nd ed., Springer, 2006.
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  • Miroslav Grmela and Hans Christian Öttinger. Dynamics and thermodynamics of complex fluids. ii. illustra- tions of a general formalism. Physical Review E, 56(6):6633–6655, 1997. doi:10.1103/PhysRevE.56.6633.
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  • T. Gorin, T. Prosen, T. H. Seligman, and M. Znidaric. Dynamics of loschmidt echoes and fidelity decay. Physics Reports, 435(2-5):33–156, 2006. doi:10.1016/j.physrep.2006.09.003.
  • A. I. Larkin and Y. N. Ovchinnikov. Quasiclassical method in the theory of superconductivity. Soviet Journal of Experimental and Theoretical Physics, 28:1200, 1969.
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