Invarians

FOUNDATIONS

How Invarians measures blockchain infrastructure state — architecture, measurement method, calibration, and two output primitives.

01 Architecture — Three Distinct Layers

Blockchain infrastructure is not one system. It is three structurally distinct layers — each with different operating constraints, different failure modes, and different measurement requirements. Invarians measures each layer independently.

L1
Base Chain
The consensus layer. Blocks are produced by a validator set operating under protocol rules. Structural anomalies manifest as rhythm disruptions and cadence deviations — often without any economic signature on fees.
τ structural · π demand
→ four regimes (SxDx)
L2
Rollup
The execution layer. A sequencer produces blocks at fixed cadence — the structural clock is architecturally constant. Measurement focuses on execution characteristics: activity intensity, transaction profile, and L1-anchored batch signals.
π demand · μ composition · σ adaptation
→ regime S1Dx (τ non-discriminant)
Bridge
Cross-Chain Connection
The transfer layer between L1 and L2. Operates on short time scales. State reflects current latency and backlog — binary and fast-moving, distinct in nature from the structural regimes of L1 and L2.
latency · backlog
→ two states (BS1 / BS2)
EIP-4844 — Why L2 measurement is structurally distinct

Since the Dencun upgrade (March 2024), L2 rollups post batch data to Ethereum via blobs — a separate fee market that does not flow through L1 basefee. An L2 sequencer incident or batch posting gap now produces no economic signature on L1. Fee monitors watching L1 are structurally blind to it. Invarians measures L2 infrastructure state directly — from rollup block data and from L1-anchored batch signals.

02 Structure and Demand — The Two Measurement Axes

For L1 chains, infrastructure state is the product of two independent axes: a structural axis and a demand axis. The separation is critical — structural stress and demand pressure can occur independently, simultaneously, or in opposition. Reading both independently is what makes S2D1 detectable.

τ
Structural axis — rhythm and cadence
Measures the internal structural behavior of the chain: block production rhythm, consensus sequence integrity, validator cadence. Captures deviations that occur independently of economic activity. Key signal: rhythm_ratio — normalized departure from calibrated historical cadence.

Threshold S2: rhythm_ratio ≥ chain-specific calibrated value.
π
Demand axis — block space pressure
Measures pressure on block space: transaction volume, block size saturation, gas utilization relative to capacity. Captures elevated economic activity. Logic: 2-of-3 dimensions must exceed calibrated thresholds simultaneously.

Dimensions: sigma_ratio · size_ratio · tx_ratio
Each chain measures itself

There is no cross-chain normalization. Every threshold is derived from each chain's own multi-year historical distribution. What constitutes an anomaly on Ethereum is calibrated from Ethereum data. What constitutes an anomaly on Solana is calibrated from Solana data.

03 Regime Classification — SxDx

The combination of the two axes produces four certified regimes. The classification is discrete and unambiguous — each measurement window maps to exactly one regime. Four certified regimes: S1D1 · S1D2 · S2D1 · S2D2.

S1D1
τ nominal · π nominal
Infrastructure operating within its calibrated historical norms on both axes. All measured dimensions within baseline.
S1D2
τ nominal · π elevated
Infrastructure structurally sound. Demand above calibrated historical percentiles — high-activity period. DeFi Summer and NFT Mania periods were S1D2 on Ethereum.
S2D1
τ stressed · π nominal
Structural stress without economic signature. Not detectable by fee monitors. The Ethereum Merge, Shanghai Upgrade, Solana outages, and Polygon Reorg Storm were all S2D1.
S2D2
τ stressed · π elevated
Structural stress coinciding with elevated demand. Compounded pressure — both axes degraded simultaneously. Rarest documented regime.
S2D1 — the critical regime

S2D1 is the regime with the highest diagnostic value. It captures infrastructure events — validator behavior anomalies, timing disruptions, network-layer issues — that produce no fee signature. A fee monitor would report S1D1 during an S2D1 period. This is the core of the two-axis approach: the structural and demand layers must be read independently to detect it.

On L2 rollups, the structural axis (τ) is architecturally constant — the sequencer produces blocks at fixed cadence. Only the demand axis varies. L2 rollups are currently classified as S1D1 or S1D2. Full regime coverage (S2D1 · S2D2) requires alternative structural instruments under development (Phase D — April 2026).

04 Bridge State — BS1 / BS2

The bridge layer operates on different time scales and with different signal characteristics from L1 and L2. Its state is binary and fast-moving — it reflects the current operational condition of the cross-chain transfer path, not a structural regime.

BS1
Bridge nominal
Transfer latency and message backlog within calibrated historical norms. Cross-chain path operating normally.
latency: within baseline
backlog: within baseline
BS2
Bridge congested
Elevated transfer latency or message backlog. Cross-chain path under stress — transfers pending or delayed.
latency: above threshold
backlog: above threshold
Why bridge state is not a regime

L1/L2 regimes (SxDx) reflect structural conditions — inertial, slow-moving, derived from multi-year calibration. Bridge state (BS1/BS2) reflects operational throughput — fast-moving, binary, measured in seconds to minutes. The distinction is architectural. Mixing them would distort both signals.

Bridge signal collection (Phase 2A) active since March 2026. Threshold calibration and full BS1/BS2 classification (Phase 2C) — Q3 2026. Current default: BS1 nominal.

05 Divergence

Beyond discrete regime classification, the instrument exposes a continuous divergence signal. This captures cross-layer dynamics that the four-regime classification does not encode — direction and magnitude of infrastructure movement between layers.

Divergence scalar

Infrastructure layers can move in the same direction, in opposite directions, or independently. The divergence scalar encodes this relationship as a single continuous value — available in the API response as divergence_index.

Regime classification remains the primary output. Divergence provides supplementary resolution for systems that require it — trend detection, early signal, or continuous monitoring.

06 Calibration

Every threshold is derived empirically. No assumption is introduced by design.

Data source
Multi-year historical calibration per chain
Ethereum: 34,697 hourly windows 2020–2024. Polygon: 25,906 windows 2020–2023. Solana: backtest 2021–2024 (partial). Each chain calibrated independently — no cross-chain normalization.
Method
Empirical threshold derivation
Thresholds are derived from each chain's own distributional behavior — structural and demand axes independently. Regime frequency validated to ensure statistical consistency across market cycles and network upgrades.
Baseline formation
Adaptive per-chain baseline
Each chain maintains a dynamic baseline using dual-speed exponential moving averages — a fast window for responsiveness and a slow window for structural stability. No manual recalibration required as network conditions evolve.
Integrity
Cryptographically anchored output
Input data is sourced from finalized, public on-chain data only. No mempool. No price feeds. Each attestation is HMAC-SHA256 signed and timestamped — independently verifiable via the /verify endpoint.
Chain τ structural π demand Regime coverage
Ethereum Calibrated — backtest 2020–2024 Calibrated — FPR 0.99% S1D1 · S1D2 · S2D1 · S2D2
Polygon Calibrated — backtest 2020–2023 Calibrated — FPR 1.20% S1D1 · S1D2 · S2D1 · S2D2
Solana Calibrated — partial (τ FPR 1.77%) Pending — tx_count unavailable in dataset S1D1 · S2D1 (S1D2 · S2D2 pending)
Avalanche Empirical estimate — no BigQuery backtest Empirical estimate — confidence LOW Operational — confidence LOW
L2 Rollups — distinct measurement framework
Base τ non-discriminant (sequencer constant cadence) 7-day calibration March 2026 — σ threshold 1.10 S1D1 · S1D2 (S2D1 · S2D2 pending Phase D)
Optimism τ non-discriminant (sequencer constant cadence) 7-day calibration March 2026 — σ threshold 1.06 S1D1 · S1D2 (S2D1 · S2D2 pending Phase D)
Arbitrum τ compressed (P99/P50 = 1.086) π broken — gasLimit ≈ 2⁵⁰ (gas_complexity_ratio Phase B) Recalibration pending
07 Empirical Evidence

Validated on real incidents. Not synthetic data. Invarians has been calibrated and backtested against documented historical events — each one verified against independent sources.

ETH — March 2024

ETF speculation congestion — +12.2h advance over fee monitors

Invarians detected structural demand elevation 12.2 hours before gas P80 confirmed it. L1 structural regime (S1D2) was measurable from finalized block data alone — no mempool, no prediction.

FPR: 1.23% — 4 years of ETH data (Φ=280 blocks) · TPR: 100% — all 4 major events detected
ARB — June 20, 2024

Sequencer incident — 37-minute batch posting gap invisible on L1

Arbitrum batch posting stopped from 16:47 to 17:24 UTC. During the entire incident, L1 ETH showed S1D1 — structurally normal. Fee monitors: no signal. Invarians: BS2 bridge state, L2 regime S1D2 (×1649 block ratio).

L1 during incident: S1D1. The event had zero economic signature on L1 — exactly what EIP-4844 predicts.
08 Two Primitives

The measurement chain — architecture, structure, demand, calibration — produces two distinct outputs. Not one.

Primitive 1
Proof of Execution Context
The certified infrastructure state at the moment of the query: L1 structural regime · L2 rollup regime · Bridge state. HMAC-SHA256 signed, timestamped. Message integrity independently verifiable via the /verify endpoint.

This is what the infrastructure is at a given moment. A cryptographic proof the agent can store in its decision log.
Proof of Execution Context →
Primitive 2
Pattern Reference
The reference mapping of execution contexts to documented historical events. Each pattern is a specific combination of L1 regime × L2 regime × bridge state. The reference shows which patterns have been observed and what occurred during each — anchored to historical record.

Not prescriptive. The agent reads the pattern and applies its own policy.
View Pattern Reference →
The boundary

Invarians certifies what the infrastructure is. It does not prescribe what the agent should do. Execution policy — thresholds, risk tolerance, fallback logic — belongs to the agent. The two primitives provide the factual basis for that policy. The decision does not.

09 Design Principles
Finalized blocks only
Post-PBS compatible. No mempool dependency.
No narrative
Measurement, not interpretation or advice.
Chain measures itself
Each chain calibrated against its own history.
No price feeds
Structural, not economic. Independent of market.
Integrity-certified
HMAC-SHA256 signed and timestamped. Verifiable via /verify.
Falsifiable by design
The instrument accepts its own failure modes.