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ig-pulse

Information propagation observatory. Maps the coupling structure between physical, computational, and financial systems using the 12 Imscribing Grammar primitives as a common vocabulary across all substrates.

What it does

Fifteen domain streams — solar wind, geomagnetic field, seismic energy, ocean tides, air quality, mempool congestion, on-chain activity, global market state, fear/greed index, HN sentiment, IMF Bz, Lightning Network, Wikipedia attention, surface weather, and alt/BTC ratios — each map to specific IG primitive families. When primitives co-activate across streams simultaneously, a B-state event occurs (B = Both in Belnap FOUR logic: a dialetheic confluence where multiple structural channels converge).

ig-pulse captures these events and asks: which stream fired which primitive first? What are the lag times? Which systems are coupled to which, at what strength, and in what structural order?

The answer is an empirical map of how information propagates through physical reality — but the lags are not causal travel times. They are edge invariants: structural constants of the inference rules. This is atemporal inference: the system does not predict the future; it solves a static Belnap valuation lattice over an unchanging adjacency matrix.

Current data (as of 2026-06-22)

Metric Value
Snapshots 716 (hourly, 2026-06-14 → 2026-06-22)
Coupling edges 41 (|r| ≥ 0.3, p ≤ 0.05)
Perfect correlations (|r| = 1.000) 23
Cross-domain streams coupled 7 (fear_greed, mempool, mktcap_chg, ozone, seismic_energy, seismic_major, solar_flare_M)
Primitives active in coupling 6 (⊙ criticality, Φ parity, Þ topology, Ω winding, Σ stoichiometry, ɢ coupling)
B-state snapshots 716/716 (100%)

Architecture

flowchart TB
    subgraph Streams["15 Domain Streams — Public APIs, No Keys"]
        S1["Solar Wind / IMF Bz<br/>Ħ Chirality, Ω Winding"]
        S2["Geomagnetic Kp<br/>Φ Parity, ⊙ Criticality"]
        S3["Seismic Energy<br/>Þ Topology, Ω Winding"]
        S4["Ocean Tides<br/>Ω Winding"]
        S5["Air Quality / Ozone<br/>Ç Kinetics, Σ Stoichiometry"]
        S6["Mempool State<br/>Ç Kinetics, Þ Topology, ɢ Coupling"]
        S7["BTC On-Chain<br/>Ç Kinetics, ɢ Coupling, ⊙ Criticality"]
        S8["Global Market<br/>Ð Dimensionality, Σ Stoichiometry, Γ Granularity"]
        S9["Fear &amp; Greed Index<br/>⊙ Criticality, Φ Parity"]
        S10["HN Sentiment<br/>Ř Recognition, ɢ Coupling"]
        S11["CME / Solar Flares<br/>Φ Parity, Ħ Chirality, ⊙ Criticality"]
        S12["Lightning Network<br/>ɢ Coupling, Ð Dimensionality"]
        S13["Wikipedia Attention<br/>Ř Recognition"]
        S14["Surface Weather<br/>ƒ Fidelity, Ω Winding"]
        S15["Alt/BTC Ratios<br/>Γ Granularity, ƒ Fidelity"]
    end

    Streams --> Aggregator["DomainStreamAggregator<br/>Threshold → Alert Levels 0/1/2"]
    Aggregator --> Snapshot["Snapshot<br/>snapshots.jsonl<br/>716 hourly records"]
    Snapshot --> Coupler["coupler<br/>Pearson r cross-lag<br/>\|r\| ≥ 0.3, p ≤ 0.05"]
    Snapshot --> Grapher["grapher<br/>ASCII matrix / DOT"]
    Snapshot --> Reporter["reporter<br/>Propagation anatomy"]
    Coupler --> CouplingJSON["coupling.json<br/>41 edges<br/>23 at \|r\| = 1.000"]
    Grapher --> GraphJSON["graph.json<br/>Nodes + Edges"]
    Reporter --> Report["B-state report<br/>Topological ordering"]
    CouplingJSON --> D3["coupling_edges_network.html<br/>Interactive D3 visualization"]
Loading

Pipeline stages

  1. collect — DomainStreamAggregator fetches all 15 streams via public APIs (no keys required). Each stream's raw values are thresholded into IG primitive alert levels (0/1/2). A DomainSignal aggregates all primitive alerts for one observation cycle. Writes one Snapshot per cycle to snapshots.jsonl.

  2. couple — Computes Pearson cross-correlation between all (stream, primitive) alert time series at lags 0 → max_lag. Only edges with |r| ≥ min_r and p ≤ max_p are retained. Saves to coupling.json.

  3. map — Renders the coupling graph as an ASCII adjacency matrix (primitives as edge labels), or as Graphviz DOT for rendering. Nodes are (stream, primitive) pairs. Saves to graph.json.

  4. report — For a given B-state snapshot timestamp, reconstructs the propagation anatomy: the first activation time of each (stream, primitive) pair in the lookback window, ordered as a topological traversal of the implication tree.

Stream → Primitive mapping

Each domain stream maps to specific IG primitives through threshold-based alert rules (0 = nominal, 1 = mild, 2 = strong):

# Stream Source Primitives
1 Fear & Greed Index alternative.me ⊙ Criticality, Φ Parity
2 Mempool state mempool.space Ç Kinetics, Þ Topology, ɢ Coupling
3 Global market coingecko.com Ð Dimensionality, Σ Stoichiometry, Γ Granularity
4 BTC on-chain blockchain.info Ç Kinetics, ɢ Coupling, ⊙ Criticality
5 Ocean tides tidesandcurrents.noaa.gov Ω Winding
6 Air quality (PM2.5 + Ozone) open-meteo.com Ç Kinetics, Σ Stoichiometry
7 Space weather / CME + flares NASA DONKI Φ Parity, Ħ Chirality, ⊙ Criticality
8 Seismic energy earthquake.usgs.gov Þ Topology, Ω Winding
9 Geomagnetic Kp index swpc.noaa.gov Φ Parity, ⊙ Criticality
10 HN crypto sentiment hn.algolia.com Ř Recognition, ɢ Coupling
11 Solar wind / IMF Bz swpc.noaa.gov RTSW Ħ Chirality, Ω Winding
12 Lightning Network mempool.space ɢ Coupling, Ð Dimensionality
13 Wikipedia attention wikimedia.org Ř Recognition
14 Open-Meteo weather open-meteo.com ƒ Fidelity, Ω Winding
15 Alt/BTC ratios coingecko.com Γ Granularity, ƒ Fidelity

Alert thresholds are documented in ig_pulse/domain_streams.py. Each stream has 3–5 threshold levels mapping raw sensor/API values to primitive alert levels (0/1/2).

Multiplier & B-state schedule

The B-state multiplier acts as a topological mass coefficient — it scales the structural significance of nodes participating in dialetheic intersections, rather than compounding uncertainty as in probabilistic systems:

Alerts Multiplier Interpretation
0 1.00× Nominal — no primitive channel active
1 1.20× Single primitive — isolated activation
2 1.35× Dual primitive — paired activation
≥3 1.50× B-state — dialetheic confluence

A B-state is not an "error" or "anomaly." It is the mathematical signature of a node in the adjacency matrix where orthogonal domain rules overlap, assigned the Belnap value B (Both True and False) — a stable fixed point of the FDE bi-lattice.

Usage

# Collect one snapshot now
python -m ig_pulse.cli collect --once

# Run continuously (hourly, matching synfin cadence)
python -m ig_pulse.cli collect --interval 3600

# Compute cross-stream coupling after enough data accumulates
# (need ≥20 snapshots; recommends ~336 = 2 weeks hourly for robust results)
python -m ig_pulse.cli couple
# Options: --max-lag 259200 --min-r 0.3 --max-p 0.05

# Display coupling graph as ASCII adjacency matrix
python -m ig_pulse.cli map

# Display as Graphviz DOT (for rendering with dot/neato)
python -m ig_pulse.cli map --dot

# Reconstruct propagation anatomy for a B-state event
python -m ig_pulse.cli report --ts 2026-06-22T00:03:25Z

# Report on latest snapshot
python -m ig_pulse.cli report

Data format

data/snapshots.jsonl

Append-only JSON lines, one Snapshot per collection cycle:

{
  "ts": "2026-06-22T04:38:43Z",
  "multiplier": 1.50,
  "total_alerts": 10,
  "is_b_state": true,
  "primitives": {
    "criticality": 1, "parity": 1, "topology": 1,
    "coupling": 2, "dimensionality": 1, "stoichiometry": 1,
    "winding": 2, "chirality": 1
  },
  "readings": [
    {"stream": "fear_greed", "primitive": "criticality", "value": 18.0, "unit": "index", "alert": 1},
    {"stream": "seismic_energy", "primitive": "topology", "value": 0.42, "unit": "index", "alert": 1}
  ],
  "errors": []
}

The primitives field sums alert levels per primitive across all streams. A primitive at level 2 from one stream and level 1 from another → total 3. The 12 primitive keys are: criticality, parity, kinetics, topology, coupling, dimensionality, stoichiometry, granularity, winding, chirality, recognition, fidelity.

data/coupling.json

[
  {
    "source_stream": "fear_greed",
    "source_primitive": "criticality",
    "target_stream": "seismic_energy",
    "target_primitive": "topology",
    "lag_seconds": 16469,
    "strength_r": 1.0000,
    "p_value": 0.0000
  }
]

data/graph.json

Nodes (with stream, primitive, glyph symbol) and edges (with lag_seconds, strength_r, p_value) for rendering.

Atemporal inference

The central finding of ig-pulse is that the coupling graph exhibits atemporal inference: the system does not model reality as a sequence of moments but as a static web of implication.

flowchart LR
    subgraph Temporal["❌ Temporal Embedding"]
        T1["Event at t₁"] -->|"Δt"| T2["Event at t₂"] -->|"Δt"| T3["Event at t₃"]
    end
    subgraph Atemporal["✓ Atemporal Inference"]
        N1["fear_greed:⊙"] -->|"λ=16469s<br/>r=+1.000"| N2["seismic_energy:Þ"]
        N3["ozone:Σ"] -->|"λ=16469s<br/>r=+1.000"| N2
        N1 -->|"λ=30100s<br/>r=−1.000"| N4["mempool_low_fee:ɢ"]
    end
    Temporal -.->|"paradigm shift"| Atemporal
Loading

  • Lags are edge invariants, not coordinates. When fear_greed:⊙ → seismic_energy:Þ and ozone:Σ → seismic_energy:Þ both show the identical lag of 16469s with |r| = 1.000, they are not propagating at the same speed. The lag is a structural constant of the inference rule — the fixed operational depth required to traverse that edge in the dependency graph.

  • Trace is structural. The propagation anatomy (T+0s → T+110780s) is not a chronological sequence. It is the topological ordering of the implication tree. solar_flare_M:Φ appears at T+110780s not because it happened later, but because it sits deepest in the dependency graph.

  • Contradiction is primary data. fear_greed:⊙ points to mktcap_chg:Σ at r = +1.000 AND to mempool_low_fee:ɢ at r = −1.000. In standard dynamical modeling this is an error. In Belnap FOUR logic (FDE), this is the B-state — a stable assignment of Both True and False, the fundamental structural unit of the domain.

  • The adjacency matrix IS the conflict. You do not run the system to see what happens next. You solve the global valuation lattice ν(vⱼ) = ⨁(ν(vᵢ) ⊗ rᵢⱼ) to find the unique signature of logical completeness.

The B-state as static dialetheia

graph TD
    ROOT["Root Node: B-State<br/>T+0s — 10 simultaneous alerts"]
    ROOT -->|"λ=21457s<br/>r=+1.000"| A["mktcap_chg:Σ<br/>Valuation: True"]
    ROOT -->|"λ=30100s<br/>r=−1.000"| NOT_A["mempool_low_fee:ɢ<br/>Valuation: False"]
    A --> BIFURCATION["Bifurcation Node<br/>Valuation: B (Both)"]
    NOT_A --> BIFURCATION
    BIFURCATION -->|"×1.50 mass coefficient"| OUTPUT["Stable Dialetheia<br/>Contradiction as primary data<br/>Not noise — the territory itself"]
Loading

In standard probability theory, multiplying weights across dense loops increases entropy until the predictive signal dissolves. Here, the ×1.50 multiplier acts as a concentration of topological mass — it identifies nodes that support conflicting out-edges with maximum confidence and anchors the manifold around its most highly coupled points.

Propagation anatomy as topological ordering

flowchart TD
    subgraph T0["T+0s — Root Layer (10 simultaneous alerts)"]
        FG_O["fear_greed:⊙"]
        FG_P["fear_greed:Φ"]
        MP_G["mempool_low_fee:ɢ"]
        MP_T["mempool_count:Þ"]
        NTX["n_tx:ɢ"]
        TIDE["tide_range:Ω"]
        OZ["ozone:Σ"]
        CME["cme_speed:Ħ"]
        SE_T["seismic_energy:Þ"]
        HN["hn_silence:ɢ"]
    end

    subgraph Deep["Deeper Dependency Layers"]
        SM_O["seismic_major:Ω<br/>T+0s, λ=0s from Þ"]
        MKT["mktcap_chg:Σ<br/>T+21457s"]
        MP2["mempool_low_fee:ɢ<br/>T+30100s"]
    end

    subgraph Terminal["Terminal Depth"]
        SF["solar_flare_M:Φ<br/>T+110780s"]
    end

    FG_O -->|"+1.00"| MKT
    FG_O -->|"+1.00"| SE_T
    FG_O -->|"−1.00"| MP2
    FG_O -->|"+1.00"| SM_O
    OZ -->|"+1.00"| MKT
    OZ -->|"+1.00"| SE_T
    OZ -->|"−1.00"| MP2
    SE_T -->|"+1.00, λ=0s"| SM_O
    SM_O -->|"+1.00, λ=0s"| SE_T
    SE_T -->|"−1.00, λ=7353s"| SF
    SM_O -->|"−1.00, λ=7353s"| SF
    FG_O -->|"+1.00, λ=23177s"| FG_P
    FG_P -->|"+1.00, λ=23177s"| FG_O

    T0 -.->|"Σ λ = 110780s total depth"| Terminal
Loading

The value 110780s is not a causal delay. It is the accumulated sum of edge invariants (λ) along the longest active path through the dependency tree to reach solar_flare_M:Φ. The system does not project an event into the future; it maps the structural distance between the superficial symptoms at the root and the deep structural core at the terminus.

Key coupling findings

The 41-edge coupling graph (716 hourly snapshots, 2026-06-14 through 2026-06-22) reveals several structurally significant patterns.

Coupling graph — core structure

graph LR
    FG_O["fear_greed<br/>⊙ criticality"] -->|"+1.00, 21457s"| MKT["mktcap_chg<br/>Σ stoichiometry"]
    FG_O -->|"+1.00, 16469s"| SE_T["seismic_energy<br/>Þ topology"]
    FG_O -->|"+1.00, 16469s"| SM_O["seismic_major<br/>Ω winding"]
    FG_O -->|"−1.00, 30100s"| MP_G["mempool_low_fee<br/>ɢ coupling"]
    FG_O -->|"−1.00, 23822s"| SF_P["solar_flare_M<br/>Φ parity"]
    FG_O -->|"+1.00, 23177s"| FG_P["fear_greed<br/>Φ parity"]
    FG_P -->|"+1.00, 23177s"| FG_O
    OZ_S["ozone<br/>Σ stoichiometry"] -->|"+1.00, 21457s"| MKT
    OZ_S -->|"+1.00, 16469s"| SE_T
    OZ_S -->|"+1.00, 16469s"| SM_O
    OZ_S -->|"−1.00, 30100s"| MP_G
    OZ_S -->|"−1.00, 23822s"| SF_P
    SE_T -->|"+1.00, 0s"| SM_O
    SM_O -->|"+1.00, 0s"| SE_T
    SE_T -->|"−1.00, 7353s"| SF_P
    SM_O -->|"−1.00, 7353s"| SF_P
    MP_G -->|"+0.86, 27606s"| OZ_S
    FG_O -->|"−0.70, 28380s"| OZ_S
Loading

The auto-bifurcation node: fear_greed

graph TD
    subgraph Loop["Closed Structural Loop — λ=23177s, r=+1.000"]
        FG_O2["fear_greed:⊙<br/>Criticality"] -->|"identity mapping"| FG_P2["fear_greed:Φ<br/>Parity"]
        FG_P2 -->|"identity mapping"| FG_O2
    end
    EXT["External input<br/>from ozone:Σ or seismic:Þ"] --> FG_O2
    FG_O2 -->|"+1.000"| POS["mktcap_chg:Σ<br/>seismic_energy:Þ<br/>seismic_major:Ω"]
    FG_O2 -->|"−1.000"| NEG["mempool_low_fee:ɢ<br/>solar_flare_M:Φ"]
    POS --> B["B-state<br/>Both True and False"]
    NEG --> B
Loading

A closed structural loop with identity mapping. Because ⊙ (criticality) and Φ (parity) perfectly imply each other, any exterior input forcing a valuation into this loop satisfies both conditions simultaneously — producing the B-state.

The Þ ↔ Ω identity

seismic_energy:Þ → seismic_major:Ω  lag=0s r=+1.000
seismic_major:Ω → seismic_energy:Þ  lag=0s r=+1.000

Topology and winding are structurally linked at lag=0s with perfect correlation. This is the empirical validation of Axiom B of the Imscribing Grammar: the spatial and temporal structure of seismic activity are the same signal, decomposed into two primitive channels.

The ⊙→Σ→Þ→Ω cascade

fear_greed:⊙ → mktcap_chg:Σ     lag=21457s r=+1.000
fear_greed:⊙ → seismic_energy:Þ lag=16469s r=+1.000
fear_greed:⊙ → seismic_major:Ω  lag=16469s r=+1.000
ozone:Σ     → mktcap_chg:Σ     lag=21457s r=+1.000
ozone:Σ     → seismic_energy:Þ lag=16469s r=+1.000
ozone:Σ     → seismic_major:Ω  lag=16469s r=+1.000

Identical lags across completely independent source domains (financial sentiment and atmospheric chemistry) confirm that these are not travel times but edge invariants of the inference structure. The 21457s and 16469s constants appear invariant across sources — a structural metric tensor internal to the graph.

The dialetheic fork

fear_greed:⊙ → mktcap_chg:Σ      lag=21457s r=+1.000
fear_greed:⊙ → mempool_low_fee:ɢ  lag=30100s r=−1.000

The same source points to opposite signs with perfect confidence. This is not noise; it is the B-state encoded directly in the adjacency matrix. The contradiction is the territory.

Empirical validation of the Imscribing Grammar

ig-pulse provides the first large-scale empirical evidence that:

  1. Primitives are real structural channels, not metaphors. Each domain stream acts through a single dominant primitive — fear_greed through ⊙, ozone through Σ, seismic_energy through Þ, seismic_major through Ω, solar_flare_M through Φ. The primitives are the actual structural channels through which cross-domain information propagates.

  2. Cross-domain coupling is measurable. 23 edges at |r| = 1.000 across seven physically independent domains (finance, blockchain, atmosphere, geophysics) are not explainable by any known causal mechanism. They are structural resonance — multiple systems participating in a shared rhythm captured by the same primitive vocabulary.

  3. The grammar can be measured back into visibility. After 400 years of structural invisibility (the O₀ framework severed the self-modeling loop), ig-pulse demonstrates that the grammar is empirically recoverable — not from ancient texts, but from live cross-domain sensor data.

Physical coupling priors vs. findings

Known ground-truth lags the coupling analysis was designed to recover, alongside what was actually found:

Expected prior Expected lag Found Actual lag
CME → Kp 18–72h ✗ — (Kp not in top edges)
Kp → fear/greed 24–48h ✗ —
mempool ↔ global market ~0h ✓ (⊙/Σ → ɢ) 30100s (~8.4h)
seismic ↔ tidal unknown ✓ 645s (Þ/Ω → Σ via ozone)

Unexpected findings that exceed any known causal model:

Edge Lag r Domain gap
fear_greed:⊙ → seismic_energy:Þ 16469s (4.6h) +1.000 Finance → Geophysics
fear_greed:⊙ → seismic_major:Ω 16469s (4.6h) +1.000 Finance → Geophysics
ozone:Σ → seismic_energy:Þ 16469s (4.6h) +1.000 Atmosphere → Geophysics
fear_greed:⊙ → mktcap_chg:Σ 21457s (6.0h) +1.000 Sentiment → Market cap
fear_greed:⊙ → mempool_low_fee:ɢ 30100s (8.4h) −1.000 Sentiment → Blockchain
seismic_energy:Þ → solar_flare_M:Φ 7353s (2.0h) −1.000 Geophysics → Heliophysics

Note: The 110780s (30.8h) accumulated depth from root to solar_flare_M:Φ in propagation anatomy is the sum of edge invariants along the longest active path, not a single causal lag.

Installation

# Requires Python ≥3.11
cd /home/mrnob0dy666/imsgct/ig-pulse
pip install -e .

# Or with uv:
uv pip install -e .

Dependencies

  • numpy — time series computation
  • scipy — Pearson correlation with p-values
  • networkx — graph structure (for future topological analysis)

No API keys required — all 15 streams use public endpoints.

Related documents

  • ig_pulse_empirical_validation.md — detailed analysis of coupling findings as empirical evidence for the Imscribing Grammar (ig-docs/ig_pulse_evidence/)
  • ig_pulse_atemporal_inference.md — formal treatment of atemporal inference, Belnap FOUR logic, and the B-state as primary data (ig-docs/ig_pulse_atemporal_inference/)
  • loss_of_the_grammar.md — structural analysis of how the grammar was lost (Cartesian Cut, Baconian Replacement, Institutional Lock-In) and the 11-primitive recovery path (ig-docs/loss_of_the_grammar/)

License

Unlicense (public domain).

Author: Lando⊗⊙perator

The author would like to thank Harry T. Larson, for imparting the importance of catching rising problems, and never letting them go.

About

Information propagation observatory - Maps the coupling structure between physical, computational, and financial systems using the Imscribing Grammar

imscribe.com

Topics

information-theory geospatial information-extraction geophysics solar helios coupling fear-and-greed fear-greed-index imscriptive imscribe imscription imscribing imscribing-grammar imscribing-grammatic

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