Research & Intellectual Property
Published papers (Zenodo) and filed intellectual property (provisional). Implementation details are intentionally limited here; this page is meant to establish scope, authorship, and research direction.
Papers (8)
AI Papers
- Fail-Closed Execution Governance for Reliable Exploratory Computational Systems
- Canonical Corpus-Based Governance for Enforcing Novelty and Deterministic Reasoning in AI-Assisted Invention
- Intent Resolution as an External System in AI-Assisted Workflows
- Externalized Authority and Artifact-Based Governance in AI Systems
- Control, Determinism, and Failure Modes in Large Language Model-Driven Systems
Physics Papers
- The Alexandrian Unified Field Geometry: A Conceptual and Computational Framework
- Alexandrian Unified Field Geometry 2.1: Conceptual Framework 2.1 — Post-Testing Update
- The Alexandrian Unified Field Geometry
Patents (17) — Provisional Filings
AI Patents
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Artifact-Only Authority Framework for Artificial Intelligence Decision Systems
A governance framework that restricts “authoritative decisions” in AI systems to externally validated artifacts (files, hashes, signed outputs, explicit state), preventing conversational or model-internal text from being treated as execution authority.
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Canonical Corpus-Based Governance System for Enforcing Novelty, Authority, and Deterministic Reasoning in AI-Assisted Invention and Research Workflows
A system that governs AI-assisted invention/research against a canonical, hash-verified corpus of prior work, enforcing novelty checks, authority boundaries, and deterministic reasoning protocols to reduce hallucinated overlap and corpus drift.
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Deterministic Prompt Translation and Compilation System for Large Language Models
A deterministic “intent-to-prompt” translation/compilation layer that converts user intent into constraint-compliant, optimized LLM prompts using non-model-driven rules, ensuring repeatable outputs and preventing hidden prompt drift.
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Fail-Closed Execution Governance System for Deterministic and Auditable Exploratory Computational Workflows
An execution architecture where runs are invalid unless correctness is established via mandatory preflight, runtime interface enforcement, deterministic seed authority, and artifact-first output reservation for auditable traceability.
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Fail-Closed Zero-Loop Control System for Artificial Intelligence Workflows
A control system that prevents runaway loops and ambiguous continuation in AI workflows by forcing explicit, validated state transitions and fail-closed behavior whenever preconditions, artifacts, or authority checks are not satisfied.
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File-Backed Temporal Memory and Deterministic Recall System for Artificial Intelligence Agents
A file-backed memory system that persists time-ordered state/decisions as authoritative artifacts, enabling deterministic recall, auditability, and consistent agent behavior across sessions without relying on chat-only context.
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Intent-Contract Enforcement System for Artificial Intelligence Execution
An enforcement system that binds execution to explicit “intent contracts” (allowed actions, invariants, outputs) and blocks progression if contract constraints are violated, enabling safe, auditable automation without ambiguous authority.
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Null-Result-Valid Artificial Intelligence Research and Decision Pipelines
A pipeline design where “null” outcomes remain valid and interpretable results, separating infrastructure validity from domain outcome and preventing systems from forcing narrative success when reality yields no effect.
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Speaker-Authorized Security and Control System for Artificial Intelligence Agents
A security/control architecture where sensitive actions require explicit speaker-authorization (voice identity or equivalent authority proof), preventing unauthorized execution and ensuring high-risk commands have strong, externally verifiable provenance.
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State-Locked Artificial Intelligence Orchestration System with Artifact-Based Authority Control
An orchestration system that locks execution to explicit state snapshots and artifact-validated transitions, preventing hidden state drift and ensuring every continuation step is justified by auditable, deterministic state changes.
Physics Patents
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Field-Geometry Materials & Manufacturing Framework
A framework for designing and fabricating physical structures/material systems intended to implement field- or geometry-driven behaviors, including constraints on geometry, assembly, and repeatable manufacturing to preserve intended interaction patterns.
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Field-Geometry Oscillation Engine for Controlled Cyclic Modulation of Energy Representations
An engine for producing controlled oscillatory behavior by cyclically modulating geometry/field representations, defining how oscillation patterns are generated, stabilized, and tuned to route energy into targeted response bands.
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Geometric Field Coupling Device for Controlled Interaction of Distinct Energy Geometries
A device class for coupling and translating between distinct energy-field “geometries” through structured spatial configuration, enabling controlled interaction and modulation across otherwise separate physical domains.
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Triangular-Petalled Resonance Manifold System And Method
A resonance/manifold system based on triangular-petalled geometry intended to generate weighted geometric field interactions, defining structural constraints and methods for producing stable, measurable resonance signatures.
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Dynamic Field Gradient Drive System
A drive/control architecture that uses dynamic field-gradient patterns as a governing mechanism for excitation, modulation, or actuation, defining how gradient sequences are generated, applied, and constrained for stable observable effects.
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Inertial Mass Modulation Device
A conceptual device architecture focused on modulating inertial response through structured field/geometry interaction, defining how modulation is produced, constrained, and measured without conflating execution validity with physical outcome.
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Field Resynchronization Computational Substrate (FRCS)
A computational substrate that re-synchronizes evolving system state under drift by enforcing consistent update ordering, phase/step alignment, and artifact-tracked checkpoints, enabling reproducible long-horizon runs and stable interpretation.