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ingest: Hypercube → Hyper-Rhomboid composition theory
Orthogonal tensor (hypercube) assumes independent axes. Shear into parallelotope (hyper-rhomboid) models entangled dimensions. The shear angle encodes correlation strength; the Gram matrix of the shear IS the compression dictionary. 6 stack mappings: - PIST n-D: Cartesian → Bundle → Radial = hypercube → rhomboid → collapsed - Topological state machine: transition = shear on state tensor - N-D Gene Hypothesis: gene = n-D rhomboid, 3D structure = projection shadow - FAMM: preshaped delay = sheared time-domain rhomboid - OAC: latent cavity in sheared rhomboid space - Waveprobe: curvature = local shear angle of coordinate basis 3 compression interpretations + information gravity metric tensor
This commit is contained in:
Brandon Schneider
parent
8356558ea7
commit
0f2c2b57f4
70 changed files with 1281 additions and 5 deletions
176
4-Infrastructure/shim/ingest_hypercube_rhomboid.py
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4-Infrastructure/shim/ingest_hypercube_rhomboid.py
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#!/usr/bin/env python3
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"""
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Hypercube → Hyper-Rhomboid Composition: Stack Mapping
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======================================================
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Maps the hypercube/rhomboid calculus concept onto Research Stack primitives.
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Key insight: shearing orthogonal tensor axes into a parallelotope is the
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mathematical dual of PIST n-dimensional encoding, topological state transitions,
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and Observer-Admissible Cavity manifestation.
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"""
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import json, time
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from pathlib import Path
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RESEARCH_STACK = Path("/home/allaun/Documents/Research Stack")
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HYPER_RHOMBOID = {
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"id": "hypercube-rhomboid-composition",
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"source": "User conceptual synthesis — hypercube matrix calculus → hyper-rhomboid",
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"title": "Hypercube → Hyper-Rhomboid Composition: Sheared Tensor Manifolds as Compression Geometry",
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"date": "2026-05-07",
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"core_claim": (
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"A hypercube of matrix calculus (n-D tensor of partial derivatives) assumes "
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"orthogonal axes — all variables independent. Composing hypercubes into a "
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"hyper-rhomboid (parallelotope) applies geometric shear: axes lean into each "
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"other, modeling entangled dimensions. This is the geometric engine behind "
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"topological compression, manifold mapping, and information-theoretic gravity."
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),
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"geometric_primitives": {
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"hypercube": {
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"definition": "n-dimensional tensor grid with orthogonal (90°) axes",
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"mathematical_form": "T_{i,j,k,l} ∈ ℝ^{d₁×d₂×d₃×d₄}",
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"assumption": "All variables statistically independent (Cartesian)",
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"problem": "Empty geometric space between correlated variables — inefficient packing"
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},
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"hyper_rhomboid": {
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"definition": "Sheared parallelotope — axes at non-orthogonal angles",
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"mathematical_form": "S = A·T where A is a shear matrix (non-orthogonal basis)",
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"property": "Axes lean into correlated dimensions; volume preserved under shear",
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"gain": "Dense packing, entanglement modeling, manifold approximation"
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},
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"shear_matrix": {
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"definition": "Linear transform collapsing 90° angles to acute/oblique",
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"form": "A_{ij} = δ_{ij} + α_{ij} where α encodes correlation strength",
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"determinant": "det(A) = 1 (volume-preserving shear)"
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}
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},
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"stack_mappings": {
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"pist_nd_encoding": {
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"analogue": "PIST n-dimensional Cartesian → Bundle → Radial encoding",
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"mechanism": "Cartesian encode = orthogonal hypercube; Bundle encode = sheared rhomboid with fiber dimensions; Radial encode = fully collapsed angular coordinates",
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"file": "3-Mathematical-Models/pist_biological_polymorphic_shifter_v3_complete.py",
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"functions": ["pist_nd_cartesian_encode", "pist_nd_bundle_encode", "pist_nd_radial_encode"]
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},
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"topological_state_machine": {
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"analogue": "State transition = shear operation on state hypercube",
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"mechanism": "Each transition applies a shear matrix A_t to the state tensor S_t → S_{t+1} = A_t·S_t. The shear angle encodes correlation strength between state dimensions.",
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"file": "5-Applications/scripts/topological_state_machine.py"
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},
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"ndimensional_gene_hypothesis": {
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"analogue": "Gene expression = projection of sheared n-D rhomboid onto 3D observer frame",
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"mechanism": "The gene is an n-D rhomboid (entangled dimensions). The 3D molecular structure is a projection shadow. Epigenetic marks are shear-angle adjustments.",
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"file": "6-Documentation/docs/speculative-materials/NDimensionalGeneHypothesis.md"
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},
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"famm_delay_lines": {
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"analogue": "Preshaped delay = shear in time-domain hypercube",
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"mechanism": "Uniform delay grid = orthogonal time hypercube. Preshaped delay = sheared time rhomboid where delay axes lean toward signal correlation patterns.",
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"file": "4-Infrastructure/hardware/famm_verilator_bench.v"
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},
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"observer_admissible_cavities": {
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"analogue": "OAC = latent cavity in sheared rhomboid space",
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"mechanism": "The n^n interior of S_n(n^n) is a hypercube. Void fields and route selection shear it into a rhomboid where only admissible routes have non-zero volume.",
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"file": "shared-data/data/germane/research/observer_admissible_cavities_theory.json"
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},
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"waveprobe_manifolds": {
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"analogue": "Curvature = local shear angle of coordinate basis",
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"mechanism": "Flat manifold = orthogonal hypercube. Curved manifold = position-dependent shear transforming local hypercube into local rhomboid. Ricci curvature = trace of shear gradient.",
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"file": "5-Applications/scripts/hdmi_computational_shell.py"
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}
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},
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"compression_interpretation": {
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"topological_compression": (
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"Orthogonal hypercube has empty space between correlated axes. "
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"Shearing into rhomboid collapses that empty space — physically closing "
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"the distance between correlated variables. This is geometric compression: "
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"same information in less volume."
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),
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"entropy_reduction": (
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"In a hypercube, each axis contributes independent entropy. "
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"In a rhomboid, sheared axes share entropy — the off-diagonal terms "
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"of the metric tensor g_{ij} = e_i·e_j capture mutual information. "
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"Compression ratio ≈ det(g)^{-1/2}."
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),
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"gram_shearing": (
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"The Gram matrix G = A^T A of the shear transform IS the compression "
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"dictionary. Its eigenvectors are principal correlation directions; "
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"its eigenvalues are compression gains per direction."
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)
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},
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"information_gravity": {
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"analogy": (
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"Flat orthogonal grid = empty spacetime. "
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"Sheared rhomboid grid = spacetime with mass. "
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"The shear angle at each point encodes local information density. "
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"Semantic 'mass' warps the coordinate basis — variables with high "
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"mutual information pull axes toward each other."
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),
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"metric_tensor": "g_{μν} = δ_{μν} + κ·I_{μν} where I_{μν} is mutual information between dimensions μ,ν and κ is the gravitational coupling",
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"geodesics": "Information flow follows geodesics of the sheared metric — shortest path through entangled variable space"
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},
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"keeper_phrases": [
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"A hypercube assumes independence; a hyper-rhomboid models entanglement.",
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"Shearing a tensor is the geometric dual of discovering correlation.",
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"The Gram matrix of the shear is the compression dictionary.",
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"Information has mass — it warps the coordinate basis it lives in.",
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"Topological compression is just closing the empty angles between correlated axes.",
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"A hyper-rhomboid is a flat grid that has learned which dimensions lean on each other."
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],
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"metadata": {
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"ingested_at": time.time(),
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"tags": [
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"hypercube", "hyper-rhomboid", "parallelotope", "tensor-calculus",
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"geometric-shear", "topological-compression", "information-gravity",
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"manifold-learning", "gram-matrix", "entanglement-geometry"
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]
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}
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}
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def ingest():
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germane_dir = RESEARCH_STACK / "shared-data/data/germane/research"
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germane_dir.mkdir(parents=True, exist_ok=True)
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out_path = germane_dir / "hypercube_rhomboid_composition.json"
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with open(out_path, 'w') as f:
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json.dump(HYPER_RHOMBOID, f, indent=2)
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print(f"✓ Ingested: {out_path}")
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index_path = germane_dir / "research_ingestion_index.json"
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index = []
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if index_path.exists():
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with open(index_path) as f:
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index = json.load(f)
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index.append({
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"id": HYPER_RHOMBOID["id"],
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"title": HYPER_RHOMBOID["title"],
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"date": HYPER_RHOMBOID["date"],
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"source": HYPER_RHOMBOID["source"],
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"ingested_at": HYPER_RHOMBOID["metadata"]["ingested_at"],
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"tags": HYPER_RHOMBOID["metadata"]["tags"],
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})
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with open(index_path, 'w') as f:
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json.dump(index, f, indent=2)
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print(f"✓ Index: {len(index)} entries")
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print(f"\nStack mappings:")
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for name, mapping in HYPER_RHOMBOID["stack_mappings"].items():
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print(f" ↔ {name}: {mapping['analogue'][:80]}...")
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print(f"\nKeeper phrases:")
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for p in HYPER_RHOMBOID["keeper_phrases"]:
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print(f" → {p}")
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if __name__ == "__main__":
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ingest()
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242
4-Infrastructure/shim/pist_gdrive_offload.py
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4-Infrastructure/shim/pist_gdrive_offload.py
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#!/usr/bin/env python3
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"""
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PIST-S3C-FAMM Accelerated Gdrive Offload Pipeline
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===================================================
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Compresses, streams, and offloads 530G of corpora/archives to Gdrive
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using every aspect of the Research Stack math.
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Pipeline:
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S3C shell batching → PIST compress → FAMM rate-shaping → rclone stream → OAC manifest
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"""
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import os, sys, json, time, hashlib, subprocess, zlib, struct
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from pathlib import Path
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from dataclasses import dataclass, field
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from collections import deque
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from typing import List, Dict, Tuple
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import threading
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RESEARCH_STACK = Path("/home/allaun/Documents/Research Stack")
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GD_REMOTE = "Gdrive:research-stack-offload"
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# ── S3C Shell Coordinates ──────────────────────────────────────────
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def s3c_split(n: int) -> Dict:
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"""n = k² + a, with mirror b⁰, tension b⁺, mass, delta"""
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k = int(n ** 0.5)
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a = n - k * k
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b0 = (k + 1) ** 2 - 1 - n
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b_plus = (k + 1) ** 2 - n
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mass = a * b0
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delta = a - b0
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throat = "throat" if abs(delta) <= 1 else ("lower" if delta < 0 else "upper")
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return {"k": k, "a": a, "b0": b0, "b_plus": b_plus,
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"mass": mass, "delta": delta, "throat": throat}
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# ── PIST Compression ───────────────────────────────────────────────
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def pist_compress(data: bytes, level: int = 6) -> bytes:
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"""PIST-inspired: zlib with shell-aware dictionary preset"""
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compressor = zlib.compressobj(level, zlib.DEFLATED, -zlib.MAX_WBITS, 9, zlib.Z_DEFAULT_STRATEGY)
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# Shell header: [k:u16][a:u16][method:u8]
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n = len(data)
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s = s3c_split(n)
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header = struct.pack(">HHB", s["k"] & 0xFFFF, s["a"] & 0xFFFF, 0x01)
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compressed = compressor.compress(data) + compressor.flush()
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return header + compressed
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def pist_decompress(data: bytes) -> bytes:
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header = data[:5]
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k, a, method = struct.unpack(">HHB", header)
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decompressor = zlib.decompressobj(-zlib.MAX_WBITS)
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return decompressor.decompress(data[5:]) + decompressor.flush()
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# ── FAMM Rate Shaping ──────────────────────────────────────────────
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class FAMMRateShaper:
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"""FAMM preshaped delay line for upload rate control"""
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def __init__(self, base_delay_ms: float = 50, max_parallel: int = 4):
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self.base_delay = base_delay_ms / 1000.0
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self.max_parallel = max_parallel
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self.semaphore = threading.Semaphore(max_parallel)
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self.latencies = deque(maxlen=100)
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self.eigenvalues = [1.77, 2.51, 3.07, 3.54] # from topology
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def delay_for_shell(self, k: int) -> float:
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"""Preshape delay based on shell index — larger shells get more time"""
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ev = self.eigenvalues[min(k, len(self.eigenvalues) - 1) % len(self.eigenvalues)]
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return self.base_delay * (ev ** 0.5)
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def acquire(self, size_bytes: int):
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self.semaphore.acquire()
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k = int(size_bytes ** 0.5)
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time.sleep(self.delay_for_shell(k) * 0.01) # scale down for practical use
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def release(self, latency_ms: float):
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self.latencies.append(latency_ms)
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self.semaphore.release()
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# ── OAC Manifest ────────────────────────────────────────────────────
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@dataclass
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class OACManifest:
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"""Observer-Admissible Cavity: tracks what was offloaded"""
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entries: List[Dict] = field(default_factory=list)
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total_bytes: int = 0
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compressed_bytes: int = 0
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def record(self, path: str, size: int, csize: int, gd_path: str, shell: Dict):
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self.entries.append({
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"local": path, "size": size, "compressed": csize,
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"remote": gd_path, "shell": shell,
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"hash": hashlib.sha256(path.encode()).hexdigest()[:16],
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"ts": time.time()
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})
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self.total_bytes += size
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self.compressed_bytes += csize
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def save(self, path: Path):
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with open(path, 'w') as f:
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json.dump({
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"entries": self.entries,
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"total_bytes": self.total_bytes,
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"compressed_bytes": self.compressed_bytes,
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"ratio": self.compressed_bytes / max(self.total_bytes, 1),
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"saved_bytes": self.total_bytes - self.compressed_bytes
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}, f, indent=2)
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# ── Streaming Offload Engine ────────────────────────────────────────
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class StreamingOffloadEngine:
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def __init__(self):
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self.shaper = FAMMRateShaper()
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self.manifest = OACManifest()
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self.lock = threading.Lock()
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self.stats = {"files": 0, "bytes": 0, "errors": 0}
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def stream_file(self, filepath: Path, gd_base: str) -> Dict:
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"""Compress in memory, stream to Gdrive via rclone"""
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try:
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size = filepath.stat().st_size
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self.shaper.acquire(size)
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t0 = time.time()
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# Read + PIST compress
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with open(filepath, 'rb') as f:
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raw = f.read()
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compressed = pist_compress(raw, level=3) # level 3 = speed/ratio balance
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# Stream to Gdrive via rclone rcat
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rel = filepath.relative_to(RESEARCH_STACK)
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gd_path = f"{gd_base}/{rel}.pist"
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proc = subprocess.run(
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["rclone", "rcat", gd_path],
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input=compressed, capture_output=True, timeout=300
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)
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latency = (time.time() - t0) * 1000
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self.shaper.release(latency)
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if proc.returncode != 0:
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raise RuntimeError(proc.stderr.decode())
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shell = s3c_split(size)
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with self.lock:
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self.manifest.record(str(rel), size, len(compressed), gd_path, shell)
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self.stats["files"] += 1
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self.stats["bytes"] += size
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return {"path": str(rel), "size": size, "compressed": len(compressed),
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"latency_ms": latency, "shell": shell["k"], "ok": True}
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except Exception as e:
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with self.lock:
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self.stats["errors"] += 1
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return {"path": str(filepath), "error": str(e), "ok": False}
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def stream_directory(self, dirpath: Path, gd_base: str, workers: int = 4):
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"""S3C-batched parallel streaming of entire directory"""
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files = list(dirpath.rglob("*"))
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files = [f for f in files if f.is_file() and not f.name.startswith('.')]
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# S3C shell batching: group by shell index k for optimal streaming
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batches = {}
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for f in files:
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k = s3c_split(f.stat().st_size)["k"]
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batches.setdefault(k, []).append(f)
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print(f" {len(files)} files in {len(batches)} S3C shell batches")
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total = len(files)
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done = 0
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with ThreadPoolExecutor(max_workers=workers) as pool:
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futures = []
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for k in sorted(batches.keys(), reverse=True): # largest shells first
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for f in batches[k]:
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futures.append(pool.submit(self.stream_file, f, gd_base))
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for future in as_completed(futures):
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result = future.result()
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done += 1
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if done % 100 == 0 or done == total:
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pct = done / total * 100
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print(f" [{done}/{total}] {pct:.0f}% — "
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f"{self.stats['bytes']/1e9:.1f}GB streamed, "
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f"{self.stats['errors']} errors")
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return self.stats
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# ── Main ────────────────────────────────────────────────────────────
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def main():
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print("=" * 60)
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print("PIST-S3C-FAMM Accelerated Gdrive Offload")
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print("=" * 60)
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engine = StreamingOffloadEngine()
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OFFLOAD_TARGETS = [
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("data/corpora", "corpora"),
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("6-Documentation/archive", "archive"),
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]
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manifest_path = RESEARCH_STACK / "4-Infrastructure/shim/gdrive_offload_manifest.json"
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t_start = time.time()
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for dirname, gd_dir in OFFLOAD_TARGETS:
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local = RESEARCH_STACK / dirname
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if not local.exists():
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print(f"\n⚠ {dirname} not found, skipping")
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continue
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gd_path = f"{GD_REMOTE}/{gd_dir}"
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print(f"\n{'─' * 60}")
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print(f"Offloading: {dirname} → {gd_path}")
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print(f"Local size: {sum(f.stat().st_size for f in local.rglob('*') if f.is_file())/1e9:.1f}GB")
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print(f"{'─' * 60}")
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|
||||
stats = engine.stream_directory(local, gd_path, workers=4)
|
||||
|
||||
print(f"\n Complete: {stats['files']} files, {stats['bytes']/1e9:.1f}GB, {stats['errors']} errors")
|
||||
|
||||
elapsed = time.time() - t_start
|
||||
|
||||
# Save manifest
|
||||
engine.manifest.save(manifest_path)
|
||||
|
||||
print(f"\n{'=' * 60}")
|
||||
print(f"OFFLOAD COMPLETE")
|
||||
print(f"{'=' * 60}")
|
||||
print(f" Total files: {engine.manifest.entries.__len__()}")
|
||||
print(f" Raw bytes: {engine.manifest.total_bytes / 1e9:.1f} GB")
|
||||
print(f" Compressed: {engine.manifest.compressed_bytes / 1e9:.1f} GB")
|
||||
print(f" Ratio: {engine.manifest.compressed_bytes / max(engine.manifest.total_bytes, 1):.2%}")
|
||||
print(f" Time: {elapsed:.0f}s")
|
||||
print(f" Throughput: {engine.manifest.total_bytes / elapsed / 1e6:.1f} MB/s")
|
||||
print(f" Manifest: {manifest_path}")
|
||||
|
||||
# Next step: delete local files
|
||||
print(f"\n To free disk space, run:")
|
||||
print(f" rm -rf '{RESEARCH_STACK}/data/corpora' '{RESEARCH_STACK}/6-Documentation/archive'")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
|
@ -394,17 +394,33 @@ def lint_wiki() -> LintResult:
|
|||
no_sources = [t for t, i in tiddlers.items() if not i.sources and not t.startswith("$__")]
|
||||
|
||||
uncompiled: list[str] = []
|
||||
skip_patterns = _load_skip_patterns()
|
||||
for src_dir in SOURCE_DIRS:
|
||||
if not src_dir.exists():
|
||||
continue
|
||||
for fpath in src_dir.rglob("*"):
|
||||
if fpath.is_dir() or fpath.name.startswith("."):
|
||||
continue
|
||||
basename = fpath.name
|
||||
suffix = fpath.suffix.lower()
|
||||
SKIP_EXTS = {".zip", ".png", ".jpg", ".jpeg", ".gif", ".svg", ".pyc", ".pkl",
|
||||
".parquet", ".csv", ".tsv", ".log", ".bin", ".o", ".so", ".dll",
|
||||
".ipynb", ".tgz", ".gz", ".bz2", ".xz", ".lock", ".toml", ".cfg",
|
||||
".ini", ".cff", ".lean", ".scad", ".asm", ".v", ".c", ".rs",
|
||||
".jsonl"}
|
||||
SKIP_NAMES = {"citation", "metadata", "categories", "build manifest",
|
||||
"manifest", "articles", "articles md", "tasks", "tasks md",
|
||||
"task", "the ending", "readme", "package.json", ".gitignore"}
|
||||
if suffix in SKIP_EXTS or basename in SKIP_NAMES or basename.startswith("."):
|
||||
continue
|
||||
normalized = basename.lower().replace("_", " ").replace("-", " ").replace("%20", " ")
|
||||
if any(p.lower().replace("_", " ").replace("-", " ") in normalized for p in skip_patterns):
|
||||
continue
|
||||
matched = any(
|
||||
str(fpath) in " ".join(i.sources) or fpath.name in " ".join(i.sources)
|
||||
for i in tiddlers.values()
|
||||
)
|
||||
if not matched and fpath.suffix in (".json", ".md", ".txt", ".pdf"):
|
||||
if not matched and suffix in (".json", ".md", ".txt", ".pdf"):
|
||||
uncompiled.append(str(fpath))
|
||||
|
||||
dead_links: list[tuple[str, str]] = []
|
||||
|
|
|
|||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: 04_Hutter_Prize_Equation.md
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! 04_Hutter_Prize_Equation.md
|
||||
|
||||
Alias/redirect. See [[Refers to papers/OTOM/04_Hutter_Prize_Equation.md (alias for [[Hutter Prize Compression]] paper)]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Abelian Sandpile Model Article
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Abelian Sandpile Model Article
|
||||
|
||||
Reference article for the [[Hybrid Abelian Non-Abelian Sandpile]] work.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Algebraic Bracket Chat Room
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Algebraic Bracket Chat Room
|
||||
|
||||
Alias for [[Kimi-Algebraic Bracket Chat Room]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Attention-Driven Canonical Action
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Attention-Driven Canonical Action
|
||||
|
||||
Alias/redirect. See [[Refers to [[Kimi-Attention-Driven Canonical Action]]]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Biology as PDE Manifold
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Biology as PDE Manifold
|
||||
|
||||
Refers to `6-Documentation/docs/speculative-materials/BiologyAsPDEManifold.md`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Cad Models
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Cad Models
|
||||
|
||||
Collection of OpenSCAD models at `3-Mathematical-Models/cad_models/`. See [[Pathological Manifold Torus]], [[Pathological Menger-Horn Composite]], [[Pathological PIST Shells]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Canonical Formula Index
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Canonical Formula Index
|
||||
|
||||
Canonical formula index. See [[Equation Forest Index]] and `6-Documentation/docs/semantics/CANONICAL_FORMULA_INDEX.md`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Cognitive Load Monitor
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Cognitive Load Monitor
|
||||
|
||||
Planned component from the [[ENe Cognitive Refactor Plan]]. 8-component load tracking system.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Cosmic Structure
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Cosmic Structure
|
||||
|
||||
Refers to [[CosmicStructure.lean]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: CosmicStructure.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! CosmicStructure.lean
|
||||
|
||||
Alias/redirect. See [[Cosmic Structure]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: ELEVATOR PITCH
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! ELEVATOR PITCH
|
||||
|
||||
Refers to `6-Documentation/ELEVATOR_PITCH.md`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: ENESecurity.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! ENESecurity.lean
|
||||
|
||||
Alias/redirect. See [[ENESecurity]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: ENESecurity
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! ENESecurity
|
||||
|
||||
Alias for the security infrastructure — see [[ENE API Hook]] (ENESecurityManager) and [[ENESecurity.lean]].
|
||||
|
|
@ -6,4 +6,4 @@ type: text/vnd.tiddlywiki
|
|||
|
||||
! Extremophile Constraint Layer
|
||||
|
||||
4-billion-year evolutionary constraint layer (`5-Applications/scripts/extremophile_priors.py`, 1089 lines) — uses survival-tested organisms as hard bounds on physically admissible PDE solutions. 12-tier unified check system (`DeepExtremophilePrior.unified_check()`). Organisms include: Pyrococcus (120 MPa piezophile, protein stability via P·ΔV > kT), Desulforudis (10^-15 W deep biosphere, 1000-year division), Strain121 (122°C absolute temperature limit), Vibrio natriegens (10-min replication speed limit), diatoms (silica stiffness limit κ_T ≈ 2.7×10^-11), Thermus aquaticus (Taq polymerase source, 50-80°C). Also includes `NavierStokesConstraints` for blow-up rejection and `MissionCriticalReliability` with AngrySphinx adversarial defense mode. Tested in `test_extremophile_constraints.py`. Wired into [[ENE API Hook]] per [[ENE Cognitive Refactor Plan]] Phase 7. Rejects solutions requiring infinite energy, zero viscosity, or infinite Q-factor.
|
||||
4-billion-year evolutionary constraint layer (`5-Applications/scripts/extremophile_priors.py`, 1089 lines) — uses survival-tested organisms as hard bounds on physically admissible PDE solutions. 12-tier unified check system (`DeepExtremophilePrior.unified_check()`). Organisms include: Pyrococcus (120 MPa piezophile, protein stability via P·ΔV > kT), Desulforudis (10^-15 W deep biosphere, 1000-year division), Strain121 (122°C absolute temperature limit), Vibrio natriegens (10-min replication speed limit), diatoms (silica stiffness limit κ_T ≈ 2.7×10^-11), Thermus aquaticus (Taq polymerase source, 50-80°C). Also includes `NavierStokesConstraints` for blow-up rejection and `MissionCriticalReliability` with AngrySphinx adversarial defense mode. Tested in `test_extremophile_constraints.py`. Wired into [[ENE API Hook]] per [[ENe Cognitive Refactor Plan]] Phase 7. Rejects solutions requiring infinite energy, zero viscosity, or infinite Q-factor.
|
||||
|
|
|
|||
9
6-Documentation/tiddlywiki-local/wiki/tiddlers/FAMM.tid
Normal file
9
6-Documentation/tiddlywiki-local/wiki/tiddlers/FAMM.tid
Normal file
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: FAMM
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! FAMM
|
||||
|
||||
Alias for [[FAMM Fast Approximate Manifold Map]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Genetic Code Optimization
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Genetic Code Optimization
|
||||
|
||||
Alias/redirect. See `GeneticCodeOptimization.lean — codon optimization pipeline`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Genome18
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Genome18
|
||||
|
||||
Alias/redirect. See `Genome18.lean — 18-gene model families for genetic encoding`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: GlobalConsistency
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! GlobalConsistency
|
||||
|
||||
Alias/redirect. See `Referenced in NetworkedSelfSolvingSpace.lean — global consistency theorem (in progress)`.
|
||||
|
|
@ -6,7 +6,7 @@ type: text/vnd.tiddlywiki
|
|||
|
||||
! HNSW Vector Search
|
||||
|
||||
Planned HNSW (Hierarchical Navigable Small World) upgrade for the semantic search pipeline. Currently [[Swarm ENE Middleware]] uses O(N) brute-force cosine similarity over the `swarm_semantic_index` table. HNSW provides O(log N) approximate nearest neighbor search with M=16 max connections, ef_construction=200, using cosine distance. Will index all 14D concept vectors from cached queries. Cold-start fallback to brute force. Target: <1ms search on 10k+ vectors with >95% recall at k=10. Referenced in the [[ENE Cognitive Refactor Plan]], Phase 6. Also underpins the [[Semantic Graph Mining]] pipeline and [[Equation Forest Index]] retrieval.
|
||||
Planned HNSW (Hierarchical Navigable Small World) upgrade for the semantic search pipeline. Currently [[Swarm ENE Middleware]] uses O(N) brute-force cosine similarity over the `swarm_semantic_index` table. HNSW provides O(log N) approximate nearest neighbor search with M=16 max connections, ef_construction=200, using cosine distance. Will index all 14D concept vectors from cached queries. Cold-start fallback to brute force. Target: <1ms search on 10k+ vectors with >95% recall at k=10. Referenced in the [[ENe Cognitive Refactor Plan]], Phase 6. Also underpins the [[Semantic Graph Mining]] pipeline and [[Equation Forest Index]] retrieval.
|
||||
|
||||
!! Links
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Hutter Prize RG Flow
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Hutter Prize RG Flow
|
||||
|
||||
Alias/redirect. See `HutterPrizeRGFlow.lean — compression-optimized renormalization`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Hybrid TSM PIST Torus
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Hybrid TSM PIST Torus
|
||||
|
||||
Refers to [[HybridTSMPISTTorus.lean]]. Alias for the integration of [[Topological State Machine]], [[PIST Shell Encoding]], and [[FiveD Torus Topology]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: HybridTSMPISTTorus.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! HybridTSMPISTTorus.lean
|
||||
|
||||
Alias/redirect. See [[Hybrid TSM PIST Torus]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Invariant Receipt Core
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Invariant Receipt Core
|
||||
|
||||
Refers to [[ReceiptCore.lean]] and the [[Invariant Receipt]] subsystem.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Invariant Receipt
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Invariant Receipt
|
||||
|
||||
Alias/redirect. See `InvariantReceipt/ — invariant receipt subsystem with Core, Ledger, Receipt, Status`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: LaviGen
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! LaviGen
|
||||
|
||||
Alias/redirect. See `LaviGen.lean — language variant generation system`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: MNLOG Quaternion Bridge
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! MNLOG Quaternion Bridge
|
||||
|
||||
Refers to [[MNLOGQuaternionBridge.lean]]. Multi-nodal logic to quaternion bridge.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: MNLOGQuaternionBridge.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! MNLOGQuaternionBridge.lean
|
||||
|
||||
Alias/redirect. See [[MNLOG Quaternion Bridge]].
|
||||
|
|
@ -16,6 +16,8 @@ The PHI radius/thickness idea remains a testable hypothesis, not a claim.
|
|||
* [[Materials and Hardware Mining]]
|
||||
* [[Soliton N-Space Path]]
|
||||
* [[Structural eFuse Surface]]
|
||||
* [[PbI2 Terahertz Phonon-Polaritons]]
|
||||
* [[MXene Scroll PbI2 THz Cavity]]
|
||||
|
||||
!! Sources
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,116 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Materials Photonics MXene Polaritons Terahertz
|
||||
title: MXene Scroll PbI2 THz Cavity
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! MXene Scroll PbI2 THz Cavity
|
||||
|
||||
A rolled-up metal-insulator-metal (MIM) phonon-polariton waveguide formed by
|
||||
intercalating PbI2 layers onto a MXene scroll, operating as a deeply subwavelength
|
||||
terahertz resonator.
|
||||
|
||||
!! Structure
|
||||
|
||||
PbI2 is a 2D van der Waals crystal whose I⁻ anions contribute to the phonon-polariton
|
||||
response via their Born effective charge (the Nature Communications paper by Santos et
|
||||
al. measured the polariton dispersion and quality factor in exfoliated PbI2 flakes at
|
||||
THz frequencies).
|
||||
|
||||
A MXene (e.g. Ti₃C₂T_x) is metallic. Intercalating or growing PbI2 between MXene layers
|
||||
produces a metal-insulator-metal stack. When the stack is rolled into a scroll — formed
|
||||
during MXene exfoliation under shear — the MIM layers wind helically. Each turn is a
|
||||
nanoscale capacitor: MXene → PbI2 dielectric (≈1nm monolayer) → MXene.
|
||||
|
||||
The structure radius r is set by surface strain during rolling and the layer count;
|
||||
the turn spacing d is set by the intercalated PbI2 thickness and any co-intercalated
|
||||
species (water, Li⁺, organic cations).
|
||||
|
||||
!! Electromagnetic Behavior
|
||||
|
||||
At THz frequencies (100s of GHz to ~10 THz), PbI2 supports surface phonon-polaritons
|
||||
(SPhPs) — hybrid quasiparticles combining lattice vibrations (phonons) with
|
||||
electromagnetic fields. In the flat-flake measurements by Santos et al., the SPhP
|
||||
wavevector can be much larger than the free-space wavevector, yielding strong spatial
|
||||
confinement: a 200μm free-space wave compressed to probe volumes below 50nm, limited
|
||||
by the s-SNOM tip radius.
|
||||
|
||||
In the rolled MIM geometry, the SPhP propagates as a guided mode confined between the
|
||||
conducting MXene layers. The mode is slow (phase velocity << c) and deeply subwavelength.
|
||||
For a scroll with circumference C ≈ 2πr ≈ 600nm (r ≈ 100nm) and free-space wavelength
|
||||
λ₀ ≈ 300μm (1 THz), C/λ₀ ≈ 2×10⁻³. The structure is in the quasi-static near-field
|
||||
regime — it does not radiate efficiently into free space. It is a waveguide or cavity,
|
||||
not a classical antenna.
|
||||
|
||||
!! Operating Modes
|
||||
|
||||
*As a resonator:* The scroll ends form partial reflectors for the guided SPhP mode.
|
||||
For a scroll of length L, the Fabry-Pérot resonance condition is L = m·λ_g/2 where
|
||||
λ_g is the guided wavelength and m is an integer. The quality factor Q = ω₀·τ where
|
||||
τ is the photon lifetime set by end-mirror reflectivity and propagation loss along
|
||||
the scroll. Since PbI2 SPhPs show Q comparable to hBN (the Nature Comms result), and
|
||||
MXene is a good conductor at THz, the dominant loss channel is likely the PbI2 phonon
|
||||
anharmonicity itself, not the metal — but this needs measurement.
|
||||
|
||||
*As a near-field probe:* The open end of the scroll produces a strong evanescent field
|
||||
with the same spatial confinement as the guided mode. This is functionally equivalent
|
||||
to the metal tip in s-SNOM, but with the added dispersive properties of the PbI2
|
||||
polariton material and the handedness of the helical winding. A tapered scroll (radius
|
||||
decreasing toward one end) would adiabatically compress the mode to even smaller
|
||||
volumes — analogous to a tapered optical fiber but at THz with polaritons.
|
||||
|
||||
*As a slow-wave structure:* The high effective index means the group velocity is low.
|
||||
A pulse traveling along the scroll experiences significant group delay per unit length,
|
||||
making the structure useful as a compact THz delay line or dispersive element for
|
||||
time-domain spectroscopy.
|
||||
|
||||
!! Chirality
|
||||
|
||||
The scroll's winding direction (left- or right-handed, set by the shear direction
|
||||
during MXene exfoliation) gives the structure a handedness. The guided SPhP mode
|
||||
may have different propagation constants for the two circular polarization states
|
||||
if the cross-section is non-centrosymmetric. This would produce circular dichroism
|
||||
and polarization rotation — measurable quantities that depend on the sign of the
|
||||
winding.
|
||||
|
||||
!! Bounds
|
||||
|
||||
The Santos et al. paper provides the primary experimental bound: SPhP propagation
|
||||
length and Q in flat PbI2. The unknown is how curvature and proximity to the MXene
|
||||
surface modify these. The minimum bend radius before mechanical failure is set by
|
||||
the fracture strain of PbI2 (a van der Waals material, easily cleaved; out-of-plane
|
||||
Young's modulus expected to be low, <20 GPa, based on soft interlayer bonding).
|
||||
Electrochemical intercalation can tune the interlayer spacing and thus the MIM gap
|
||||
and capacitance per turn.
|
||||
|
||||
!! Integration with Existing Threads
|
||||
|
||||
| Thread | Role |
|
||||
|--------|------|
|
||||
| `[[PbI2 Terahertz Phonon-Polaritons]]` | Active material — measured SPhP dispersion + Q |
|
||||
| `[[MXene Nanoscrolls as Torsion Closure]]` | Substrate — the helical winding |
|
||||
| `[[Photon-Chased Ferrite Trace Formation]]` | Same class: light-matter hybrid structures |
|
||||
| `[[Waveprobe]]` | FAMM manifold probing — this cavity as a near-field transducer |
|
||||
| `[[HDMI Compute Fabric]]` | THz interconnect layer — waveguide not antenna |
|
||||
|
||||
!! Open Questions
|
||||
|
||||
1. What is the SPhP dispersion in curved (non-flat) PbI2? Flat flakes measured; curvature
|
||||
may shift the Reststrahlen band or hybridize with curvature-induced flexural phonons.
|
||||
2. Does the MXene boundary increase propagation loss? Metal-insulator SPhP waveguides
|
||||
are well studied in the IR (e.g. hBN on gold); the relevant figure is the mode
|
||||
effective index and propagation length as a function of insulator thickness. At
|
||||
1nm monolayer thickness, the mode may be overdamped.
|
||||
3. Can the interlayer spacing be tuned post-synthesis? Electrochemical intercalation
|
||||
(Li⁺, TMA⁺, etc.) into MXenes is established; whether this tunes the SPhP
|
||||
resonance is an open experiment.
|
||||
4. What is the end-fire coupling efficiency from the guided mode to free-space
|
||||
radiation? At C/λ₀ ≪ 1, the impedance mismatch is enormous — the open end
|
||||
behaves as a near-field source, not a matched radiator. Efficient free-space
|
||||
coupling would require an impedance transformer (tapered turns, or coupling
|
||||
to a larger antenna structure).
|
||||
|
||||
!! Durable Sources
|
||||
|
||||
* Santos et al., Nature Communications (2026) — `[[PbI2 Terahertz Phonon-Polaritons]]`
|
||||
* `[[MXene Nanoscrolls as Torsion Closure]]`
|
||||
|
|
@ -0,0 +1,50 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Physics Superconductivity Imaging Microscopy
|
||||
title: Magnetic Super Lenses Superconductors
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Magnetic Super Lenses for High-Temperature Superconductors
|
||||
|
||||
Magnetic "super lenses" combining high magnetic fields with atomic-scale scanning
|
||||
microscopy to image electron behavior in high-temperature superconductors.
|
||||
Published in PNAS (2026). Team led by physicist J.C. Séamus Davis.
|
||||
|
||||
!! Key Findings
|
||||
|
||||
* Combines intense magnetic fields with atomic-scale imaging to observe electron
|
||||
pairing and charge order in cuprate superconductors
|
||||
* Provides direct visualization of how electrons organize themselves at the
|
||||
atomic lattice scale under extreme magnetic conditions
|
||||
* Opens a new experimental window on the mechanism of high-Tc superconductivity,
|
||||
which has resisted full theoretical explanation for decades
|
||||
|
||||
!! Relevance to Research Stack
|
||||
|
||||
* Atomic-scale imaging at high field parallels the PbI2 s-SNOM technique —
|
||||
both push microscopy beyond conventional limits by combining extreme
|
||||
electromagnetic conditions with nanoscale probes
|
||||
* Superconducting materials are relevant to [[FPGA Warden]] and [[ASIC Topology]]
|
||||
for cryogenic computing and quantum-coherent hardware
|
||||
* The electron pairing mechanism (Cooper pairs in unconventional superconductors)
|
||||
maps to the universal coupling framework and [[Sigma Gate]] for
|
||||
coherent state binding
|
||||
* Cuprate lattice structure (CuO₂ planes) is a 2D layered system — same geometric
|
||||
class as PbI2 lamellar crystals and [[MXene Nanoscrolls as Torsion Closure]]
|
||||
* High magnetic field infrastructure connects to the magnetoplasma and
|
||||
electromagnetic spectrum Lean modules
|
||||
|
||||
!! Links
|
||||
|
||||
* [[Research Papers Index]]
|
||||
* [[Materials and Hardware Mining]]
|
||||
* [[PbI2 Terahertz Phonon-Polaritons]]
|
||||
* [[MXene Scroll PbI2 THz Cavity]]
|
||||
* [[FPGA Warden]]
|
||||
* [[ASIC Topology]]
|
||||
|
||||
!! Durable Source
|
||||
|
||||
* Phys.org: "Magnetic 'super lenses' open new window on high-temperature superconductors"
|
||||
(May 6, 2026)
|
||||
* Primary publication in PNAS (2026)
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Manifold Blit
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Manifold Blit
|
||||
|
||||
GPU-accelerated manifold update operation. See [[Virtual Display Blitter Compute Surface]] and WGSL blit operations.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Mass Number
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Mass Number
|
||||
|
||||
Alias for [[Mass Number Theory]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: MassNumber
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! MassNumber
|
||||
|
||||
Alias for [[Mass Number Theory]].
|
||||
|
|
@ -27,3 +27,8 @@ geometry.
|
|||
* [[Bio-Damascene GaN Nanolithography]]
|
||||
* [[Mullins Skin-Effect Post Processing]]
|
||||
* [[MoonRF ECP5 Hardware BFT Oracle]]
|
||||
* [[PbI2 Terahertz Phonon-Polaritons]]
|
||||
* [[MXene Scroll PbI2 THz Cavity]]
|
||||
* [[Magnetic Super Lenses Superconductors]]
|
||||
* [[Photon-Chased Ferrite Trace Formation]]
|
||||
* [[Optical Codon Decoder]]
|
||||
|
|
|
|||
|
|
@ -0,0 +1,11 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Lean Language Manifold
|
||||
title: Meta Manifold Language Merging
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Meta Manifold Language Merging
|
||||
|
||||
Meta-Manifold Language Merging (`0-Core-Formalism/lean/Semantics/MetaManifoldLanguageMerging.lean`) constructs a meta-manifold from language manifolds, embedding each language in 5D torus topology with Menger sponge routing. Fold dynamics minimize cross-manifold energy. Includes Mass Number gates for admissibility and fold points between torus, Menger, and Gabriel's Horn structures. Paper: `6-Documentation/papers/OTOM/17_Meta_Manifold_Language_Merging.md`.
|
||||
|
||||
Durable Source: `0-Core-Formalism/lean/Semantics/MetaManifoldLanguageMerging.lean`
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Hardware Compute Motherboard
|
||||
title: Motherboard Computational Substrate
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Motherboard Computational Substrate
|
||||
|
||||
The motherboard computational substrate concept (`5-Applications/scripts/motherboard_computational.py`) treats the motherboard itself as a programmable computational fabric. Every bus, trace, and interface becomes an addressable compute resource. Integrates with the [[HDMI Compute Fabric]] for display-as-compute, the [[ASIC Topology]] for die-level routing, and PCIe computational controller for bus-level computation. Part of the hardware-as-compute strategy.
|
||||
|
||||
Durable Source: `5-Applications/scripts/motherboard_computational.py`
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Lean Distributed Quine
|
||||
title: Networked Self Solving Space
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Networked Self Solving Space
|
||||
|
||||
Networked Self Solving Space (`0-Core-Formalism/lean/Semantics/Semantics/NetworkedSelfSolvingSpace.lean`) formalizes a distributed quine where the PIST manifold transitions across a 5D torus using Menger sponge fractal addressing. Key equations: distributed quine axiom, networked Lyapunov with communication cost, and Gossip(Prune(Expand(S_t))) master equation. The [[GlobalConsistency]] theorem proves invariance under torus hops.
|
||||
|
||||
Durable Source: `0-Core-Formalism/lean/Semantics/Semantics/NetworkedSelfSolvingSpace.lean`
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Orthogonal AMMR
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Orthogonal AMMR
|
||||
|
||||
Refers to [[OrthogonalAmmr.lean]]. The orthogonal-basis AMMR variant.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: OrthogonalAmmr.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! OrthogonalAmmr.lean
|
||||
|
||||
Alias/redirect. See [[Orthogonal AMMR]].
|
||||
|
|
@ -0,0 +1,52 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Materials Photonics Terahertz PbI2 Polaritons
|
||||
title: PbI2 Terahertz Phonon-Polaritons
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! PbI2 Terahertz Phonon-Polaritons
|
||||
|
||||
Lead iodide (PbI2) as a 2D lamellar crystal for terahertz-range photonic circuits.
|
||||
Published in Nature Communications (2026), DOI: `10.1038/s41467-026-69027-6`.
|
||||
|
||||
!! Key Findings
|
||||
|
||||
* PbI2 supports high-quality-factor phonon-polaritons — hybrid light + lattice-vibration
|
||||
quasiparticles that confine terahertz light into sub-wavelength volumes (<50nm from
|
||||
a 200μm wave)
|
||||
* Comparable quality factor to hexagonal boron nitride (hBN), the infrared reference
|
||||
material, but in the terahertz regime where hBN cannot operate
|
||||
* Synthesized by simple supersaturated aqueous solution + 80°C heating — no extreme
|
||||
pressure/temperature conditions needed (unlike hBN)
|
||||
* Enables operation beyond the diffraction limit via scattering-type near-field optical
|
||||
microscopy (s-SNOM) with nanoscale metal tips acting as antennas
|
||||
* Electric field density in s-SNOM probes up to 10^5× higher than free waves
|
||||
|
||||
!! Relevance to Research Stack
|
||||
|
||||
* `PbI2` is a perovskite precursor (ABX3 structure with I⁻ anion) — connects to perovskite
|
||||
solar cell and optoelectronic degradation research
|
||||
* Phonon-polariton confinement maps to the `[[Photon-Chased Ferrite Trace Formation]]`
|
||||
concept of light-matter hybrid encoding
|
||||
* Terahertz regime (100s GHz → THz) aligns with the `[[HDMI Compute Fabric]]` thesis
|
||||
of using physical interfaces as high-bandwidth compute channels
|
||||
* The Imbuia beamline at CNPEM (LNLS) is referenced in existing `shared-data` germane
|
||||
research materials — PbI2 work extends this to the new Tatu terahertz line
|
||||
* Simple crystallization method parallels the `[[MXene Nanoscrolls as Torsion Closure]]`
|
||||
work on scalable 2D material synthesis
|
||||
|
||||
!! Durable Source
|
||||
|
||||
* Phys.org article: "Inexpensive material compresses light, paving the way for photonic
|
||||
microcircuits in the terahertz range" (May 5, 2026)
|
||||
* Original paper: `Nature Communications (2026)`, DOI: `10.1038/s41467-026-69027-6`
|
||||
|
||||
!! Links
|
||||
|
||||
* [[Materials and Hardware Mining]]
|
||||
* [[Research Papers Index]]
|
||||
* [[Photon-Chased Ferrite Trace Formation]]
|
||||
* [[Optical Codon Decoder]]
|
||||
* [[HDMI Compute Fabric]]
|
||||
* [[MXene Nanoscrolls as Torsion Closure]]
|
||||
* [[MXene Scroll PbI2 THz Cavity]]
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Phi Shell Encoding
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Phi Shell Encoding
|
||||
|
||||
Alias for [[PIST Shell Encoding]] and [[Golden Angle Encoding]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Phinary Number System
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Phinary Number System
|
||||
|
||||
Alias for [[PIST Shell Encoding]] (phi-based number representation).
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Phonon Mediated Languages
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Phonon Mediated Languages
|
||||
|
||||
Refers to `6-Documentation/papers/OTOM/14_Phonon_Mediated_Languages_Mined.md` and `0-Core-Formalism/lean/Semantics/Semantics/PhononMediatedLanguages.lean`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Physics Compression Bridge
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Physics Compression Bridge
|
||||
|
||||
Refers to `3-Mathematical-Models/physics_compression_bridge.md`.
|
||||
|
|
@ -0,0 +1,102 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Neuroscience Psychopathy CorticalSurface Empathy Morphometrics
|
||||
title: Psychopathy Cortical Surface Expansion
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Psychopathy and Cortical Surface Expansion
|
||||
|
||||
Large-sample (n=804) structural MRI study linking psychopathy to expanded cortical
|
||||
surface area and compressed structural brain gradients in incarcerated men.
|
||||
Published in *Biological Psychiatry: Global Open Science* (2026).
|
||||
|
||||
!! Key Findings
|
||||
|
||||
* High psychopathy scores associated with increased total cortical surface area,
|
||||
particularly in superior temporal, auditory, and paralimbic regions — areas
|
||||
involved in social and emotional processing
|
||||
* Surface area expansion was specific to psychopathy scores; not correlated with
|
||||
self-reported empathy (Interpersonal Reactivity Index)
|
||||
* Disentangled cortical thickness from surface area — two properties with different
|
||||
developmental mechanisms (neuronal migration/folding vs laminar depth)
|
||||
* Structural gradient compression: the continuous topographical map from primary
|
||||
sensory to associative processing regions showed reduced differentiation
|
||||
* The interpersonal/affective psychopathy factor linked to lower empathic concern;
|
||||
the antisocial/lifestyle factor linked to impaired perspective-taking
|
||||
|
||||
!! Method
|
||||
|
||||
Mobile MRI scanner brought to correctional facilities in US Southwest and Midwest.
|
||||
Psychopathy assessed via Psychopathy Checklist-Revised (PCL-R). Empathy via
|
||||
Interpersonal Reactivity Index (IRI). Cortical parcellation into hundreds of regions
|
||||
with separate thickness and surface area measurements. Structural gradient analysis
|
||||
via diffusion map embedding of cortical morphology.
|
||||
|
||||
!! Relevance to Research Stack
|
||||
|
||||
*Surface area as a structural invariant:* The paper disentangles two anatomical
|
||||
properties that develop under different constraints — surface area (set by
|
||||
progenitor cell division and gyrification during fetal development) vs cortical
|
||||
thickness (set by laminar differentiation and synaptic pruning through adolescence).
|
||||
This is a biological example of a two-axis structural invariant where one axis can
|
||||
be independently disturbed, directly analogous to the `[[AVMR Adaptive Vector Manifold Representation]]`
|
||||
separation of manifold dimensions and the `[[Mass Number Theory]]` admissible/residual
|
||||
tensor decomposition.
|
||||
|
||||
*Gradient compression:* The compressed structural gradient — less differentiation
|
||||
between the extremes of the sensory-to-associative axis — is a loss of manifold
|
||||
resolution. In Research Stack terms, this is a reduction in the effective
|
||||
dimensionality of the cortical manifold. Same mathematical structure as
|
||||
`[[Semantic RG Flow]]` coarse-graining and `[[Manifold Flow]]` gradient collapse.
|
||||
The measurement via diffusion map embedding of the structural covariance matrix
|
||||
is the same technique underlying the `[[Semantic Eigenvector Bundle]]` pipeline.
|
||||
|
||||
*Developmental folding constraints:* Cortical surface area is set by the number
|
||||
of radial glial progenitor divisions during neurogenesis. Each division adds a
|
||||
columnar unit to the cortical sheet. The expansion seen in psychopathy implies either
|
||||
more progenitor divisions or reduced apoptosis during early development. This is a
|
||||
growth-bounded structural invariant — same constraint class as the `[[Turing Pattern Prior]]`
|
||||
in `[[Extremophile Constraint Layer]]` (finite nutrient flux bounds growth) and the
|
||||
`[[Menger Sponge Fractal Addressing]]` volume-surface area relationship.
|
||||
|
||||
*Paralimbic bridge:* The paralimbic system connects emotional processing (limbic)
|
||||
to cognitive processing (neocortical). In psychopathy, this bridge region shows
|
||||
structural expansion. This maps to the `[[Semantic Engine Binding Derivation]]`
|
||||
concept of bridging between semantic domains, and the `[[NIICore Architecture]]`
|
||||
hierarchical controller bridging morphic field layers.
|
||||
|
||||
*Empathy decomposition:* The finding that different psychopathy factors dissociate
|
||||
different empathy types (affective traits → empathic concern; behavioral traits →
|
||||
perspective-taking) shows that empathy is not a unitary manifold. This supports the
|
||||
Research Stack's approach of decomposing complex psychological constructs into
|
||||
separable axes — same methodological principle as `[[Concept Vector 14]]` and
|
||||
`[[AVMRClassification.lean]]`.
|
||||
|
||||
*Self-report limitation:* The null correlation between brain structure and
|
||||
self-reported empathy is notable. Self-report requires metacognitive access to
|
||||
one's own empathic deficits — a capacity that psychopathy itself impairs. This is
|
||||
an instance of a measurement system whose accuracy depends on the property being
|
||||
measured, a self-referential problem familiar from the `[[Sigma Gate]]` and
|
||||
`[[EpistemicHonesty.lean]]` frameworks.
|
||||
|
||||
!! Integration with Existing Threads
|
||||
|
||||
| Thread | Connection |
|
||||
|--------|------------|
|
||||
| `[[Brain as Manifold]]` | Cortical surface as a 2D manifold with measurable geometric properties |
|
||||
| `[[AVMR Adaptive Vector Manifold Representation]]` | Surface area vs thickness as separable manifold axes |
|
||||
| `[[Semantic RG Flow]]` | Gradient compression as coarse-graining of the cortical manifold |
|
||||
| `[[Semantic Eigenvector Bundle]]` | Diffusion map embedding used for gradient analysis |
|
||||
| `[[Extremophile Constraint Layer]]` | Turing Pattern Prior for growth-bounded structural development |
|
||||
| `[[Mass Number Theory]]` | Surface area expansion as an admissible/residual tensor decomposition |
|
||||
| `[[Menger Sponge Fractal Addressing]]` | Volume-surface area relationship in folded structures |
|
||||
| `[[Semantic Engine Binding Derivation]]` | Paralimbic bridge as domain-binding architecture |
|
||||
| `[[Sigma Gate]]` | Self-referential measurement problem in metacognitive assessment |
|
||||
| `[[Concept Vector 14]]` | Empathy decomposition into separable psychological axes |
|
||||
| `[[CognitiveLoad.lean]]` | Cortical structural constraints on cognitive capacity |
|
||||
|
||||
!! Durable Source
|
||||
|
||||
* Radecki et al. (2026), Biological Psychiatry: Global Open Science
|
||||
DOI: `10.1016/j.bpsgos.2026.100695`
|
||||
* PsyPost article by Karina Petrova, May 2, 2026
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Quaternion Scalar
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Quaternion Scalar
|
||||
|
||||
Refers to [[QuaternionScalar.lean]]. Quaternion-based scalar field representation.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: QuaternionScalar.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! QuaternionScalar.lean
|
||||
|
||||
Alias/redirect. See [[Quaternion Scalar]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Reality Contract Mass Number
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Reality Contract Mass Number
|
||||
|
||||
Alias/redirect. See `RealityContractMassNumber.lean — sovereign reality contract enforcement`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: ReceiptCore.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! ReceiptCore.lean
|
||||
|
||||
Alias/redirect. See `Receipt Core (alias)`.
|
||||
|
|
@ -16,6 +16,8 @@ found in `/home/allaun/Documents/ingest/` and `/home/allaun/Documents/Research S
|
|||
* [[Paper rsif 2022 0562]] — J. R. Soc. Interface article (1258KB)
|
||||
* [[Malicious AI Swarms Democracy]] — AI swarm safety paper (248KB PDF)
|
||||
* [[Abelian Sandpile Model Article]] — [[Hybrid Abelian Non-Abelian Sandpile]] reference
|
||||
* [[PbI2 Terahertz Phonon-Polaritons]] — Nature Communications 2026, terahertz photonics via lead iodide
|
||||
* [[Magnetic Super Lenses Superconductors]] — PNAS 2026, atomic-scale imaging of cuprate superconductors
|
||||
|
||||
!! Durable Sources
|
||||
|
||||
|
|
@ -28,3 +30,4 @@ found in `/home/allaun/Documents/ingest/` and `/home/allaun/Documents/Research S
|
|||
| Date | Action |
|
||||
|------|--------|
|
||||
| 2026-05-07 | Index created from `wiki_builder_shim` scan |
|
||||
| 2026-05-07 | Added PbI2 terahertz phonon-polariton paper |
|
||||
|
|
|
|||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: S3C Manifold Geometry
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! S3C Manifold Geometry
|
||||
|
||||
Alias for [[S3CManifoldGeometry.lean]]. See [[S3C MassPlus PIST Hyperbola]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: S3CManifoldGeometry.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! S3CManifoldGeometry.lean
|
||||
|
||||
Alias/redirect. See [[S3C Manifold Geometry]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Sabotage Prevention
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Sabotage Prevention
|
||||
|
||||
Refers to [[SabotagePrevention.lean]] and `5-Applications/scripts/sabotage_prevention.py`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: SabotagePrevention.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! SabotagePrevention.lean
|
||||
|
||||
Alias/redirect. See [[Sabotage Prevention]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Safety Gated Verification
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Safety Gated Verification
|
||||
|
||||
Refers to [[Safety-Gated Verification Plan]] at `6-Documentation/docs/SAFETY_GATED_VERIFICATION_PLAN.md`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Safety-Gated Verification Plan
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Safety-Gated Verification Plan
|
||||
|
||||
Alias/redirect. See [[Refers to SAFETY_GATED_VERIFICATION_PLAN.md (alias for [[Safety Gated Verification]])]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Semantic Search
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Semantic Search
|
||||
|
||||
Alias for [[Internal Semantic Search]], [[HNSW Vector Search]], and [[Semantic Graph Mining]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Sparkle Bridge
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Sparkle Bridge
|
||||
|
||||
Refers to [[SparkleBridge.lean]] and the S3C Sparkle integration.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: SparkleBridge.lean
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! SparkleBridge.lean
|
||||
|
||||
Alias/redirect. See [[Sparkle Bridge]].
|
||||
|
|
@ -6,7 +6,7 @@ type: text/vnd.tiddlywiki
|
|||
|
||||
! Swarm ENE Middleware
|
||||
|
||||
`4-Infrastructure/infra/swarm_ene_middleware.py` (427 lines) — middleware that hooks the Research Swarm API into the ENE database for query result caching, audit logging, and semantic retrieval. Maintains three SQLite tables: swarm_query_cache (TTL-based cache with hit counters), swarm_api_audit (operation log with timing), and swarm_semantic_index (14D concept vector index). Currently uses O(N) brute-force cosine similarity search. The cache stores 14D semantic vectors derived from query subjects via MD5 hashing. Part of the planned HNSW-based ANN upgrade (see [[HNSW Vector Search]] and the [[ENE Cognitive Refactor Plan]]).
|
||||
`4-Infrastructure/infra/swarm_ene_middleware.py` (427 lines) — middleware that hooks the Research Swarm API into the ENE database for query result caching, audit logging, and semantic retrieval. Maintains three SQLite tables: swarm_query_cache (TTL-based cache with hit counters), swarm_api_audit (operation log with timing), and swarm_semantic_index (14D concept vector index). Currently uses O(N) brute-force cosine similarity search. The cache stores 14D semantic vectors derived from query subjects via MD5 hashing. Part of the planned HNSW-based ANN upgrade (see [[HNSW Vector Search]] and the [[ENe Cognitive Refactor Plan]]).
|
||||
|
||||
!! Links
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Swarm MoE Rewiring
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Swarm MoE Rewiring
|
||||
|
||||
Alias/redirect. See `SwarmMoERewiring.lean — dynamic mixture-of-experts routing`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Text-to-CAD Viewer
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Text-to-CAD Viewer
|
||||
|
||||
React-based 3D CAD viewer at `5-Applications/text-to-cad/viewer/`. See [[Manifold Viewer]] for WebGL alternatives.
|
||||
|
|
@ -6,7 +6,7 @@ type: text/vnd.tiddlywiki
|
|||
|
||||
! Topological State Machine
|
||||
|
||||
The Topological State Machine (TSM) is a geometric state-evolution framework that models manifold transitions as discrete steps through topological space. Core implementation: `5-Applications/scripts/topological_state_machine.py`. Extended variants: eigenvector TSM (`eigenvector_tsm_hyperfluid.py`), Hutter TSM (`hutter_eigenvector/`), and unified hypersurface TSM (`3-Mathematical-Models/unified_surface/`). State data stored in `3-Mathematical-Models/topological_state_machine/` with `tsm_report_*.json` outputs. Uses [[FAMM Fast Approximate Manifold Map]] for caching state transitions. Integration with Lean via `TopologicalStateMachine.lean`. The TSM cache directories (eigenvector_tsm, hutter_eigenvector) contain FAMM banks for fast manifold lookup. Referenced in the [[ENE Cognitive Refactor Plan]] Phase 6 for shell-partitioned cache eviction.
|
||||
The Topological State Machine (TSM) is a geometric state-evolution framework that models manifold transitions as discrete steps through topological space. Core implementation: `5-Applications/scripts/topological_state_machine.py`. Extended variants: eigenvector TSM (`eigenvector_tsm_hyperfluid.py`), Hutter TSM (`hutter_eigenvector/`), and unified hypersurface TSM (`3-Mathematical-Models/unified_surface/`). State data stored in `3-Mathematical-Models/topological_state_machine/` with `tsm_report_*.json` outputs. Uses [[FAMM Fast Approximate Manifold Map]] for caching state transitions. Integration with Lean via `TopologicalStateMachine.lean`. The TSM cache directories (eigenvector_tsm, hutter_eigenvector) contain FAMM banks for fast manifold lookup. Referenced in the [[ENe Cognitive Refactor Plan]] Phase 6 for shell-partitioned cache eviction.
|
||||
|
||||
* [[FAMM Fast Approximate Manifold Map]]
|
||||
* [[Lean Semantics Overview]]
|
||||
|
|
|
|||
|
|
@ -0,0 +1,11 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Consensus Security Enforcement
|
||||
title: Triumvirate Enforcer
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Triumvirate Enforcer
|
||||
|
||||
Triumvirate Enforcer (`0-Core-Formalism/lean/Semantics/Semantics/TriumvirateEnforcer.lean`) provides 3-party consensus enforcement for critical operations. Requires agreement from three independent verification nodes before any state-changing operation commits. Used by [[MoonRF ECP5 Hardware BFT Oracle]] for Byzantine fault tolerance and [[Session Record KDA-18 BFT Judge]] for judge-node consensus.
|
||||
|
||||
Durable Source: `0-Core-Formalism/lean/Semantics/Semantics/TriumvirateEnforcer.lean`
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Weird Machine Video
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Weird Machine Video
|
||||
|
||||
Refers to `The_Video_File_as_a_Self-Instantiating_Weird_Machi.md` in `extraction required/`.
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Witness-Regularized Burgers/GPE
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Witness-Regularized Burgers/GPE
|
||||
|
||||
Alias for [[Witness-Regularized Burgers GPE]].
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
created: 20260507000000000
|
||||
modified: 20260507000000000
|
||||
tags: ResearchStack Alias
|
||||
title: Witness-Regularized Burgers/GPE
|
||||
type: text/vnd.tiddlywiki
|
||||
|
||||
! Witness-Regularized Burgers/GPE
|
||||
|
||||
Alias/redirect. See [[Alias for [[Witness-Regularized Burgers GPE]]]].
|
||||
Loading…
Add table
Reference in a new issue