NOTE: The idea is right, the machine-salad framing is not entirely right yet in terms of what to prove, the obervations otherwise are good. Haven't had time to finish moving this over yet.

Characteristic Impedance Python

Python-first research instrument for testing whether the characteristic impedance of vacuum behaves like an unusually generative information substrate inside the published catalog of fundamental physical constants.

Status

This is an early research instrument, not a completed proof. The project begins with one strong legacy observation and turns it into code, tests, baselines, and failure conditions.

Current project state:

• The pre-2019 Z0 circular-XOR loop result is reproduced in tested Python code.
• The information-first thesis and legacy BigCalc2 observations are captured in GitHub-readable Markdown notes, with companion HTML versions for local/static viewing.
• A complete pre-2019 CODATA 2014 evidence chain exists under docs/codata/, including the raw NIST-style source text, 336 parsed official rows, derived binary rows, and a bits-only corpus.
• A separate legacy physics-token catalog exists under docs/tokens/ for the quark and hadron rows that BigCalc2 appended after the official CODATA table.
• CODATA documentation generation tools exist under tools/codata/.
• Unit tests cover the Z0 anchor, core bit operations, XOR loop behavior, and CODATA document generation.
• GitHub Actions runs the Python unit test suite on push and pull request.

The next major implementation step is catalog-level experimentation: scanning all constants, building randomized controls, and producing reproducible reports from code outputs rather than hand-written observations.

Claim Under Test

This project tests the claim that the pre-2019 CODATA significant-digit representation of the characteristic impedance of vacuum is not merely an arbitrary decimal artifact. Under a minimal binary encoding and a minimal circular XOR evolution, it appears to behave as an unusually generative seed inside the catalog of physical constants.

The claim is not that the ohm is sacred. The claim is that the pre-2019 published Z0 value may preserve a privileged information object whose structure became harder to see after the 2019 SI redefinition changed the exact/measured status of vacuum electromagnetic constants.

Thesis

Mature physics compresses empirical reality into a finite symbolic catalog of authoritative constants. Once a constant is published, its significant digits can be treated as an information object.

The working hypothesis is that the characteristic impedance of vacuum is not just another constant in that catalog. It may be the impedance boundary between physical measurement and symbolic compression: a compact seed whose simple binary evolution reconstructs or intersects an unusually large fraction of the other published constant bit patterns.

That claim is testable.

Core Experiment

1. Load pre-2019 CODATA constants as published significant-digit records.

2. Convert each constant's significant digits into a binary information object.

3. Generate four canonical orientations: forward, reverse, inverse, and inverse-reverse.

4. Evolve each seed as a circular XOR ring:

   next[i] = current[i] XOR current[(i + 1) mod n]
   

5. Detect halt, loop, period, and generated orbit text.

6. Scan each orbit for other constant bit patterns.

7. Compare the characteristic impedance of vacuum (Z0) against all other constants and randomized controls.

8. Repeat under precision choices, unit translations, CODATA editions, and alternative encodings.

Known Verified Result

The legacy observation uses pre-2019 CODATA:

name:   characteristic impedance of vacuum
digits: 376730313461
bits:   101011110110110111000000110001011110101
len:    39

The current Python implementation verifies that the forward circular-XOR evolution of this seed closes a loop at period 4095:

seed        = 101011110110110111000000110001011110101
period      = 4095
halted      = false
closed_loop = true

This is the first anchor result. The project should not make stronger claims until the catalog-level and randomized-control tests are implemented.

Evidence Chain

The project now keeps the full pre-2019 source and derived binary evidence in-tree:

• CODATA Evidence Chain explains the conversion rule and rebuild process.
• Pre-2019 CODATA 2014 Raw Text preserves the raw NIST-style all-values text used as the import source.
• Pre-2019 CODATA 2014 Source preserves 336 official named/value/unit rows currently used by the project.
• Pre-2019 CODATA 2014 Binary preserves the same rows with significant digits and binary forms.
• Pre-2019 CODATA 2014 Bits Only is the stripped corpus for pure bit experiments.
• Legacy Physics Token Catalog preserves the non-CODATA quark/hadron/convenience rows that BigCalc2 appended to its local NIST file so they could be treated like named bit tokens.
• Z0 Orientation Geometry Report preserves the four canonical Z0 orientations, the known forward manual layout, and candidate natural traversals without treating them as proof.

The conversion rule intentionally uses the published value mantissa only:

376.730 313 461... -> 376730313461 -> binary
6.626 070 040 e-34 -> 6626070040   -> binary
299 792 458        -> 299792458    -> binary

That rule ignores sign, decimal point, digit-grouping spaces, ellipsis, uncertainty, unit, and exponent marker. This is not an accident; it is the information-object hypothesis made explicit and testable.

Future reports must state which catalog they used: official CODATA only, legacy tokens only, or a combined catalog.

Falsification Criteria

This claim weakens or fails if:

• Z0 does not outperform other constants under the same encoding and evolution.
• Randomized bitstrings with the same length and density perform comparably.
• Shuffled catalog controls perform comparably.
• The observed structure disappears under reasonable precision and unit transformation tests.
• Post-selection explains the apparent matches.
• The result depends on undocumented choices that cannot be preregistered and repeated.

Why Pre-2019 Z0 Matters

The 2019 SI revision is not treated here as a mere bookkeeping change. It is treated as a change in the published information structure of the constants catalog.

Before the revised SI, the vacuum electromagnetic constants occupied a different definitional status. After the revision, the SI is defined through exact values assigned to selected defining constants, including c, h, and e. Under that regime, the vacuum magnetic permeability and the impedance of free space are no longer fixed in the same way; they become tied to the measured fine-structure constant.

This project therefore treats the pre-2019 Z0 value as a historically specific information object. The question is not whether a unit convention is sacred. The question is whether the pre-2019 catalog preserved a compact symbolic seed that is structurally special under simple computational tests.

Methodological Context

The computational stance is close to the Wolfram-style lesson that very simple programs can produce unexpectedly rich behavior. The rule used here is much smaller than a physics model:

circular binary seed -> XOR with one-bit rotation -> generated orbit

If that minimal rule produces non-random reconstruction behavior against a catalog of physical constants, the next move is not rhetoric. The next move is controls.

Install And Run

No virtual environment is checked into the repository. You can either run the tests directly from the checkout, or create your own local .venv.

Quick local test from the repository root:

Windows PowerShell:

$env:PYTHONPATH = "$PWD\src"
python -m unittest discover -s tests -p "test_*.py"

Linux/macOS:

PYTHONPATH="$PWD/src" python -m unittest discover -s tests -p "test_*.py"

Editable install, optional local virtual environment:

python -m venv .venv

Windows PowerShell:

.venv\Scripts\Activate.ps1
pip install -e .
python -m unittest discover -s tests -p "test_*.py"

Windows cmd:

.venv\Scripts\activate.bat
pip install -e .
python -m unittest discover -s tests -p "test_*.py"

Linux/macOS:

source .venv/bin/activate
pip install -e .
python -m unittest discover -s tests -p "test_*.py"

Initial Notes

• Information-First Position states the central thesis: physical constants are compressed information artifacts before they are physics classroom objects, and unit objections must be tested as encoding transformations rather than used as a dismissal.
• Legacy Genetic Sequence Analysis explains what the old BigCalc2 "gene" machinery was doing: circular tape decomposition, Z0-facet compression, ablation controls, and Z0-as-running-tape scans.
• Legacy Physics Token Catalog calls out the appended quark and hadron rows from BigCalc2, including their values, significant digits, and binary strings.
• Z0 Orientation Geometry Report makes fixed bits, orientation, layout, traversal, and interpretation explicit before later quark genetic sequence decomposition work.
• Z0 Binary Structure captures the 2019 PDF/RTF observation that the characteristic impedance bits already contain whole quark mass-signature words, arrange naturally into a gluon-like chart, and come from a prime significant-digit integer with a primitive Pythagorean triple identity.

Note: the Markdown documents linked above are the GitHub-readable versions. The companion HTML files in docs/ are much nicer looking when opened locally or through a static site, but GitHub's repository file browser shows them as source code unless GitHub Pages or another static host is used.

Design Posture

• Treat constants as information artifacts with provenance.
• Treat units as translations to be tested, not as automatic disqualifiers.
• Prefer small, inspectable algorithms over GUI-first exploration.
• Require randomized and cross-constant baselines before making strong claims.
• Keep generated reports separate from core library code.

Roadmap

Done

• Reproduce the legacy Z0 XOR-ring period result.
• Add core bit helpers: significant digits to bits, reverse, invert, canonical orientations, XOR ring step, and XOR ring run.
• Add Apache 2.0 licensing, notice, package metadata, and GitHub Actions tests.
• Capture the information-first thesis in project docs.
• Capture the Z0 quark/gluon binary-structure observation in project docs.
• Analyze and document the legacy BigCalc2 genetic-sequence machinery.
• Add a complete pre-2019 CODATA 2014 evidence chain with raw source, 336 parsed official rows, generated binary rows, and bits-only files.
• Add tests for the CODATA conversion and document rebuild path.

Next

• Move CODATA records from documentation artifacts into importable Python catalog objects.
• Add catalog-wide orientation, period, orbit, and run-tape scans.
• Port the legacy token/gene decomposer as clean Python modules: tokens, decompose, z0_substrate, and run_tape.
• Add shuffled-bit, random-seed, and alternate-constant baselines.
• Generate reproducible Markdown/HTML reports directly from Python outputs.

Later

• Add unit-translation and precision-cut experiments.
• Compare pre-2019 CODATA against post-2019 and alternate CODATA editions.
• Add stability-basin scans for uncertain quark mass signatures.
• Publish null results and failed variants alongside positive results.

References

• BIPM, The International System of Units (SI).
• NIST, SI Redefinition.
• Pierre Fayet, Completing the International System of units with c = hbar = mu0 = epsilon0 = kB = NA = 1, arXiv:1906.05123.
• Wolfram, Wolfram Science.