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Sovereign Computing Whitepaper Project

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Release v1.0.0 Apache 2.0 License Windows x64 OpenCL VRAM 6 validated tests 4 demos included

Enterprise reference package for reproducing software-defined quantum logic experiments on a classical OpenCL GPU substrate. Sovereign_Computing

This repository is a curated, self-contained project copy built for technical review, reproducibility, and executive demonstration. It packages the driver source, the whitepaper evidence chain, validated test workloads, demo programs, and captured result artifacts in one handoff-ready structure.

The engineering claim of this repository is deliberately narrow: a standard GPU VRAM field can be driven as a persistent phase substrate that supports phase-gating, lattice-style error localization, adaptive homeostasis, stigmergic transport, and small-scale period-finding logic. It does not claim physical identity with a superconducting quantum processor or a blanket asymptotic quantum advantage result.

Executive Summary

  • Room-temperature substrate: all included workloads run on standard GPU hardware through OpenCL.
  • Reproducible proof chain: the repository packages the exact tests behind the whitepaper.
  • Validated demos: four product-facing demo programs are already wired to the measured workloads.
  • Research-grade claim discipline: scope, evidence, and non-claims are documented explicitly.

Quick Links

Why This Repository Exists

  • Provide a reviewable package for research, architecture, diligence, and internal innovation teams.
  • Demonstrate software-defined quantum-style control logic on standard GPU hardware.
  • Preserve the exact test path behind the whitepaper instead of exposing the full development repository surface.
  • Offer both validation workloads and product-facing demos built directly on the validated tests.

What Is Included

  • driver/: curated CC_OpenCl driver source required for the whitepaper experiments
  • artifacts/bin/CC_OpenCl.dll: prebuilt Windows DLL for immediate execution
  • tests/: whitepaper-relevant validation tests and dependencies
  • demos/: product-style demo programs backed by the same validated workloads
  • demo_outputs/: generated Markdown and JSON reports from the demo runs
  • results/: raw logs and compact result summaries
  • whitepaper/: whitepaper and supporting appendices
  • docs/: GitHub-facing documentation and branding assets
  • scripts/: build and execution helpers

Validated Evidence Chain

The repository is centered on a narrow proof chain with measurable outcomes.

Test Focus Area Current Verified Outcome
test_17 Phase selectivity Best separation ratio 26.036x, full sweep pass 9/9
test_18 Agent resonance tracking 1024/1024 agents reached target, discovery rate 1.0
test_21 Agent scaling 16,384 agents, discovery rate 98.08%, semantic pass 100%
test_37 Willow-style syndrome localization and graft Trigger-to-remote ratio 70.44x, graft payload 13,207 bytes
test_39 Adaptive v8 homeostasis Safe load multiplier 2.0, echo retention ratio 2.11e5
test_40 Shor-Light operating point Period 4, factors [3, 5], post-algorithm echo preserved

These values are summarized in results/RESULTS_SUMMARY.md and expanded in the whitepaper.

Architecture at a Glance

The project operates on a 1024 x 1024 VRAM-backed substrate exposed through OpenCL kernels and orchestrated from Python validation code.

  • Field substrate: VRAM is treated as a persistent computational field rather than only transient buffer memory.
  • Phase-gating: logic is separated through constructive and destructive interference patterns.
  • Lattice dynamics: an 8 x 8 logical Willow layout is mapped onto the larger substrate for syndrome and echo experiments.
  • ISA-grafting: harvested correction paths are written back into the field as executable resonance structure.
  • Stigmergic bus: agent populations move state across the substrate without a traditional shared-memory message bus.
  • Adaptive v8 control: a host-side AIMD-style regulator stabilizes load before lattice collapse.

Repository Layout

SovereignComputing_Whitepaper_Project/
  artifacts/
    bin/CC_OpenCl.dll
  demo_outputs/
    *.md
    *.json
  demos/
    demo_all_product_showcase.py
    demo_homeostatic_runtime_console.py
    demo_resonance_search_explorer.py
    demo_shor_light_workbench.py
    demo_willow_fault_monitor.py
    README.md
  docs/
    assets/
      github-social-preview.png
      github-social-preview.svg
    GITHUB_BRANDING.md
  driver/
    CMakeLists.txt
    CL/
    include/
    src/
  results/
    RESULTS_SUMMARY.md
    *.log
  scripts/
    build_driver.ps1
    run_product_demos.ps1
    run_whitepaper_tests.ps1
  tests/
    test_16_...
    test_17_...
    test_18_...
    test_21_...
    test_22_...
    test_30_...
    test_37_...
    test_38_...
    test_39_...
    test_40_...
    subqg_tests/
  whitepaper/
    COMPLEXITY_SCALING_APPENDIX.md
    DEMO_APP_ROADMAP.md
    PRODUCT_IDEAS_COMPANIES_APPLICATIONS.md
    PROGRAM_EXAMPLES_CURRENT_PROJECT.md
    SOVEREIGN_COMPUTING_WHITEPAPER.md
  CONTRIBUTING.md
  LICENSE
  requirements.txt

System Requirements

  • Windows x64
  • Python 3.11 or newer
  • numpy
  • CMake 3.20 or newer for source builds
  • OpenCL-capable GPU driver
  • For source builds: OpenCL SDK or usable headers/libraries

Install Python dependencies:

pip install -r .\requirements.txt

Quick Start

The fastest path is to use the included prebuilt DLL:

artifacts/bin/CC_OpenCl.dll

Run a single validation workload:

cd .\tests
python .\test_40_subqg_willow_shor_light_operating_point.py --dll ..\artifacts\bin\CC_OpenCl.dll --gpu 1 --grid 1024

Run the full whitepaper validation chain:

.\scripts\run_whitepaper_tests.ps1

All validation logs are written to results\.

Product Demos

Four demo applications are included and already mapped to validated workloads.

Demo Purpose Backing Test
Resonance Search Explorer Phase-selective search and signal separation test_17
Willow Fault Monitor Defect localization, syndrome response, and graft replay test_37
Homeostatic Runtime Console Adaptive stabilization under dynamic load test_39
Shor-Light Workbench Period-finding and small-factor demonstration test_40

Run all demos plus the aggregate showcase index:

.\scripts\run_product_demos.ps1

Run demos individually:

cd .\demos
python .\demo_resonance_search_explorer.py
python .\demo_willow_fault_monitor.py
python .\demo_homeostatic_runtime_console.py
python .\demo_shor_light_workbench.py

Demo outputs are generated in demo_outputs\:

Build From Source

Option A: helper script

.\scripts\build_driver.ps1

Default output:

build/bin/CC_OpenCl.dll

Option B: manual CMake build

cmake -S .\driver -B .\build
cmake --build .\build --config Release

If find_package(OpenCL REQUIRED) does not locate a usable OpenCL installation, point CMake at the local driver\CL bundle:

cmake -S .\driver -B .\build `
  -DOpenCL_INCLUDE_DIR=.\driver\CL `
  -DOpenCL_LIBRARY=.\driver\CL\OpenCL.dll
cmake --build .\build --config Release

If the local OpenCL.dll is not accepted as a link target in your environment, use the platform import library or the OpenCL SDK installed on the host machine.

Run Validation Tests Individually

From the tests directory:

python .\test_17_subqg_grover_v7_phase_selectivity_sweep.py --dll ..\artifacts\bin\CC_OpenCl.dll --gpu 1 --grid 1024 --steps 1
python .\test_18_subqg_agents_v7_resonance_tracking.py --dll ..\artifacts\bin\CC_OpenCl.dll --gpu 1 --grid 1024
python .\test_21_subqg_agents_v7_native_coupled_scaling.py --dll ..\artifacts\bin\CC_OpenCl.dll --gpu 1 --grid 1024
python .\test_37_subqg_willow_surface_code_syndrome_graft.py --dll ..\artifacts\bin\CC_OpenCl.dll --gpu 1 --grid 1024
python .\test_39_subqg_willow_v8_adaptive_gating.py --dll ..\artifacts\bin\CC_OpenCl.dll --gpu 1 --grid 1024
python .\test_40_subqg_willow_shor_light_operating_point.py --dll ..\artifacts\bin\CC_OpenCl.dll --gpu 1 --grid 1024

Dependency note:

  • test_17 depends on test_16
  • test_37, test_39, and test_40 also rely on test_22, test_30, test_38, and tests/subqg_tests/cc_driver.py

Key Documents

Intended Audience

  • Advanced R&D and applied research teams
  • GPU systems and runtime engineers
  • Cryptography and algorithm exploration groups
  • Innovation, strategy, and technical diligence stakeholders
  • Teams evaluating non-von-Neumann or field-computing experiments

Scientific Scope and Claim Boundary

This repository demonstrates:

  • software-defined quantum-style control logic on a classical GPU substrate
  • phase-selective interference behavior
  • surface-code-inspired syndrome localization
  • direct correction-path grafting back into the field
  • adaptive stabilization under dynamic load
  • small-scale Shor-like period-finding behavior on a stabilized operating point

This repository does not claim:

  • physical identity with a superconducting quantum processor
  • full BQP equivalence
  • asymptotic quantum advantage proof
  • production-grade cryptanalytic scale

The package is intended as a reproducible experimental platform and a high-signal engineering artifact, not as a universal quantum computing claim.

Validation Environment

The included result set and demo outputs were validated on an AMD OpenCL device path using the packaged Windows workflow. The captured runs in this package were executed against the gfx1034 device path. Logs and generated artifacts are preserved in results\ and demo_outputs\.

References

Both are discussed in the whitepaper for architectural comparison only; this repository stands on its own empirical tests and captured logs.

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Enterprise reference package for reproducing software-defined quantum logic experiments on a classical OpenCL GPU substrate.

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Apache-2.0 license

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v1.0.0 Latest
May 11, 2026

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