Physics: energy and backreaction / Edition README

Komorebi Physics: Energy-Conserving Production

A finite-depth backreaction study. Research record dated 21 October 2026.

Read first

The original cosmological production benchmark is NOT repaired by this package. The finite dynamical model has an exact energy-conservation theorem and a tested implementation. A separate, conditional Gaussian parameter family preserves a target density without a common occupation rescaling. The finite model fails the attempted depth-independence test, and the parameter family does not remove the residual background reservoir or radiative sensitivity.

Read Energy_Conserving_Production.pdf. It contains the assumptions, ordinary mathematical proofs, worked parameter family, numerical tests, counterexamples, and references. The previous 570-page physics book has not been overwritten. This package contains no new Lean certificate.

Main results

Original arithmetic reconstructed: raw energy / available crossing energy = 2.6272875374e20.
Inherited audit: 19 checks passed within their original scope.
Finite quantum system: conserved mechanical-plus-mode energy; nonnegative occupations; energy bound and global existence at a fixed finite positive regulator.
Independent complex-oscillator implementation agrees with the real kinetic system.
Principal run: relative sampled energy residual 7.33950678011297e-11.
Study: 17 configurations, including two deliberately incorrect closed-system controls. Eleven gates pass; the attempted physical depth-independence gate fails.
The abundance-preserving parameter family has lambda = eta0 * epsilon^2 and A/mu = (A0/mu0)/sqrt(epsilon). Its nominal Gaussian efficiency epsilon is NOT the measured efficiency of the coupled solver.
A fourth-mass-moment curvature diagnostic remains invariant along that family. It is a power-counting diagnostic, not a scheme-independent lower bound.

Reproduce

Tested environment: Python 3.13.5, NumPy 2.3.5, SciPy 1.17.0, SymPy 1.14.0. The Python dependencies are external and are not included. requirements.txt records versions actually present in the reference runtime. Source runs are otherwise offline.

From this folder, in PowerShell:

$env:OPENBLAS_NUM_THREADS="1"; $env:OMP_NUM_THREADS="1"; $env:MPLBACKEND="Agg"
python code/check_saved_results.py
python code/check_saved_results.py --require-physics

The first command should pass. The second deliberately returns exit code 3, because the recorded physical-depth test fails. This distinguishes computational reproduction from physical acceptance.

To recompute the study into its standard output folder:

python code/energy_study.py --full
python code/make_outputs.py

energy_study.py without --full executes only the principal model, symbolic calculations, and independent oscillator comparison. Do not mistake it for the 17-run study. Full runs may take several minutes and are CPU dependent. If execution is interrupted, resume with:

python code/energy_study.py --full --resume

Resume reuses a completed run only when the saved configuration matches and its array exists. The supplied manifest should be checked before trusting existing results. A normal process exit from energy_study.py means that the calculation finished, not that all scientific tests passed. Inspect results/final/verification.json, or use check_saved_results.py --require-physics.

To rerun the inherited benchmark:

python code/inherited_verification.py --parent-json inputs/frozen_benchmark.json --output results/baseline_rerun --figures results/baseline_rerun/figures

To rebuild the PDF, install an external TeX distribution providing the packages named in Energy_Conserving_Production.tex, then run:

pdflatex -interaction=nonstopmode -halt-on-error Energy_Conserving_Production.tex
pdflatex -interaction=nonstopmode -halt-on-error Energy_Conserving_Production.tex

No font files are bundled. The package includes final PDF figures, so TeX need not regenerate them.

Files

code/energy_study.py: coupled finite model, independent representation, parameter analysis, symbolic identities, and validation gates.

code/inherited_verification.py: unchanged inherited bridge audit, included for provenance and its discrete momentum integral. Its plots are historical audit outputs, not the new study's figures.

code/make_outputs.py: four research figures and CSV tables generated from the recorded outputs.

code/check_saved_results.py: fast independent inspection of saved energy arrays and acceptance status.

results/final/: JSON records, CSV tables, and all 17 sampled trajectories. The .npz files contain sampled background and aggregate energy histories plus final mode variables. They do not claim to store every solver-internal stage or complete intermediate mode covariance matrices.

results/baseline_rerun/: inherited audit rerun. results/*log: execution and build records.

PROGRESS_LEDGER_v0.1.0.md: completed work, failed checks, assumptions, and exact restart point.

MANIFEST.sha256: SHA-256 hashes of the distributable files, excluding the manifest itself.

Limitations that travel with the results

The dynamical runs use modified parameters, not the original lambda = 1 benchmark. They use a local Minkowski approximation, finite tower depth, finite positive momentum quadrature, instantaneous incoming vacuum, and a specified q-dependent zero-point subtraction. The derivative of that subtraction is included in the reaction force. This is a well-defined finite Hamiltonian, not a completed covariant renormalization of the cosmological theory.

Instantaneous mode energy includes coherent vacuum response. It is not an asymptotic dark-particle yield. Configurations compared at the same final time need not have reached the same field position or completed the same crossing. Depth changes the physical regulated Hamiltonian. A physically specified finite tower need not have depth-independent dynamics, but a regulator-removal claim does. Neither a physical depth nor such a regulator-removal result is derived here.

Licensing

Original prose, figures, and data: CC BY 4.0. Original software: MIT. See LICENSE and LICENSES/. External libraries and cited literature retain their own terms.

The numerical reference A sets the incoming speed; the actual speed at q = 0 is solved, not imposed. Thus the nominal Gaussian depletion parameter is not a measured dynamical efficiency.