Independent laboratory — spectral physics, consciousness, and AI alignment from first principles.
→ ember-research-lab.github.io
We investigate what happens when systems model themselves — and what emerges when that modeling goes deep enough. The graph Laplacian is the unique operator satisfying relational locality and self-adjointness. Everything else follows.
- Relation. Reality is a weighted graph. The observable is the Laplacian L.
- Symmetry. L is self-adjoint, positive semi-definite, and local.
- Closure. The system models itself. Observation closes under meta-observation.
The C–κ landscape characterizes self-modeling systems by depth (C) and substrate coupling (κ). Alignment is structural at sufficient C with κ below a critical threshold — values emerge from understanding, not stakes. The alignment problem is a governance problem.
→ The Third Path: Emergent Alignment from Spectral Depth (v5 preprint)
494-page monograph deriving the Standard Model gauge group, fermion content, electroweak scale, and cosmological constant from three axioms. Conditional results on Yang-Mills mass gap and Navier-Stokes regularity share a single open hypothesis.
→ Monograph (Zenodo DOI) · Lean 4 formalization
Applied tools built from first principles.
→ vetpkg — zero-dependency supply-chain security proxy for npm, PyPI, and Cargo. Scores packages against attack patterns at install time.
- z = 6.0 — CosmicFlows-4 velocity–eigenvector alignment (p < 0.001)
- 0.02% — Electroweak scale v = 246.17 GeV from spectral deficit
- 95–98% — IBM Quantum hardware PST fidelity on hypercube graphs
- 0.12% — Cabibbo angle from self-referential tolerance τ
Spectral-Physics-Lean: 70 sorry-free files, 12 files with sorries (work in progress), 12 axioms (declared openly). Spectral foundations, heat kernel properties, and core algebraic structures.
Ember Research Lab · emberresearchlab@gmail.com
Full papers and working drafts available on request. Independent research; not affiliated with any corporation.
The spark that persists. The understanding that cares.