{"id":34846674,"url":"https://github.com/selfapplied/zetadiffusion","last_synced_at":"2026-05-23T00:06:03.809Z","repository":{"id":327124580,"uuid":"1107860945","full_name":"selfapplied/zetadiffusion","owner":"selfapplied","description":"Numerical Lab for Proving RH via Bundle Dynamics, RG Flow, and Topological Energy Harvesting","archived":false,"fork":false,"pushed_at":"2025-12-02T09:09:31.000Z","size":300,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-12-04T11:55:23.418Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/selfapplied.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-12-01T17:48:09.000Z","updated_at":"2025-12-02T09:09:34.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/selfapplied/zetadiffusion","commit_stats":null,"previous_names":["selfapplied/zetadiffusion"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/selfapplied/zetadiffusion","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/selfapplied%2Fzetadiffusion","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/selfapplied%2Fzetadiffusion/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/selfapplied%2Fzetadiffusion/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/selfapplied%2Fzetadiffusion/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/selfapplied","download_url":"https://codeload.github.com/selfapplied/zetadiffusion/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/selfapplied%2Fzetadiffusion/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28034132,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-12-25T02:00:05.988Z","response_time":58,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-12-25T18:17:20.628Z","updated_at":"2025-12-25T18:17:22.153Z","avatar_url":"https://github.com/selfapplied.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ZetaDiffusion\n\n**Numerical Lab for Proving RH via Bundle Dynamics, RG Flow, and Topological Energy Harvesting.**\n\nVersion: 0.3.0\n\n## Overview\n\nZetaDiffusion v0.3 implements the complete **Field Equationist Generator (FEG-0.3)** architecture. It unifies the analytic study of the Riemann Zeta function with dynamical systems theory and thermodynamic information extraction.\n\n## Architecture\n\n### 1. Spectral Line Probe (`zetadiffusion.field`)\n- Samples the Riemann field $\\xi(1/2 + it)$.\n- Detects zeros as topological defects in the complex phase.\n\n### 2. Bundle Dynamics (`zetadiffusion.dynamics`)\n- Maps spectral data to circle maps on $X \\times S^1$.\n- Generates rotation number spectra (\"Devil's Staircase\") using type-safe modular arithmetic (`Radians`/`Turns`).\n\n### 3. Local RG Operator (`zetadiffusion.renorm`)\n- Applies the Feigenbaum renormalization operator to local field potentials.\n- Estimates the scaling dimension $\\delta$ of the underlying universality class.\n\n### 4. Topological Harvester (`zetadiffusion.energy`)\n- **The Negentropic Engine**.\n- Models the extraction of work from geometric shock waves.\n- Implements the Hamiltonian $H_{extract} = -\\eta \\cdot \\dot{\\chi} \\cdot \\Phi$.\n- Simulates the \"Loading -\u003e Shock -\u003e Harvest -\u003e Reset\" anti-fragile cycle.\n\n## Usage\n\nRun the lab demonstration to see the full pipeline:\n\n```bash\npython3 demo.py\n```\n\nRun the energy harvesting simulation directly:\n\n```bash\npython3 zetadiffusion/energy.py\n```\n\n## Theoretical Basis\n\nThe system treats the Riemann Critical Line not as a static object, but as the **attractor** of a dynamical system. The zeros are the discrete points where the system achieves perfect phase locking (rational rotation numbers). The Energy Harvester demonstrates how a cognitive system can extract \"insight\" (computational work) by surfing the shock waves generated near these critical points.\n\n## Documentation\n\n### Status \u0026 Results\n- **VALIDATION_STATUS.md** - Current validation results, issues, and next steps\n- **PROJECT_STATUS.md** - Project overview and quick start guide\n- **RESEARCH_FINDINGS.md** - Detailed diagnostic analysis and root causes\n\n### Guides\n- **FEG-0.4_Field_Manual.md** - Operator theory and implementation details\n- **NOTION_SETUP.md** - Notion integration setup guide\n- **SCRIPT_STANDARDS.md** - Code standards and conventions\n- **NEXT_STEPS.md** - Historical roadmap and future directions\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fselfapplied%2Fzetadiffusion","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fselfapplied%2Fzetadiffusion","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fselfapplied%2Fzetadiffusion/lists"}