Token Utility and Economics

Pim Protocol runs on two tokens with deliberately separate jobs. QOL is the everyday currency: a demand-responsive, energy-backed unit meant to function as cash for payments, fees, and savings, targeting 1–2% daily volatility. PYM is the governance and staking token: a fixed supply, capped at 100 million from the genesis block, with no further issuance ever possible. Separating these two roles is a deliberate choice — it keeps the currency people actually transact with insulated from the speculative pressures that typically affect a governance token, while keeping governance power tied to a token whose supply cannot be diluted by monetary policy decisions.

7.1EQCF — The Energy Quotient Calibration Formula

QOL's issuance rate is not set by a single ratio, the way many "energy-backed" tokens work. It is calibrated through a seven-stage pipeline that combines five independently measured signals into one smoothly adjusting value. The purpose of this multi-stage design is to solve a specific failure mode: a single noisy or temporarily anomalous input — a brief dip in energy reporting, a thin trading session — should never be able to swing currency issuance on its own. Each stage adds a specific safeguard.

1. Raw Signal Collection

Five inputs are sampled every 12-hour cycle: energy cost (from weighted energy-proof submissions), hashrate deviation, on-chain currency velocity, market liquidity depth, and price volatility. Each is normalised to a 0–1 scale before being combined.

2. Weighted Composition

The five signals are combined into a single composite score, with energy cost weighted most heavily because it is the signal backed by hardware-verified proof — the others contribute lighter, stabilising corrections.

3. Confidence Scoring

Each cycle's composite score is assigned a confidence weight based on how complete energy-proof reporting was that cycle and whether the system's anomaly detection flagged anything unusual. Low-confidence cycles are down-weighted, never simply thrown away.

4. Smoothing

The confidence-weighted score is blended with the running average from previous cycles, so that a single anomalous cycle can move the smoothed output by at most a small, bounded fraction of the deviation — turning short-term noise into a gradual, observable drift rather than a sudden jump.

5. Persistence Gate

A directional change must hold steady for three consecutive 12-hour cycles — 36 hours — before it is allowed to cross a policy-relevant threshold. This is the primary defence against any single-cycle noise driving an actual monetary policy reaction.

6. Hard Bounds

The calibration value is hard-capped within a fixed range, enforced directly by the consensus rules. No combination of inputs can push it outside this range; changing the range itself would require a full protocol upgrade.

7. Minting Formula

The final issuance amount is the lesser of two independent limits — one derived from the calibration pipeline, one from network hashrate — multiplied by a demand factor. Neither limit alone determines issuance; both must agree.

κ_t = 0.55·Ê_t + 0.20·Ĥ_t + 0.10·V̂_t + 0.10·L̂_t + 0.05·σ̂_t

EQCF_t = λ·κ_t + (1−λ)·EQCF_(t−1)

λ = 0.15

EQCF_t ∈ [0.40, 2.50]

Δ(EQCF_t) ≤ 3% per cycle

1.5% during Tightening

QOL_minted = min(effective_signal(EQCF_t, state) × E_agg_t, β × HR_t) × F_t

In plain terms: Ê_t is the normalised energy-cost signal, Ĥ_t the hashrate-deviation signal, V̂_t the currency-velocity signal, L̂_t the market-liquidity signal, and σ̂_t the inverse-volatility signal — each measured at cycle t. The weights (0.55, 0.20, 0.10, 0.10, 0.05) reflect how much each signal is trusted, with the hardware-verified energy signal dominating by design. λ controls the smoothing speed described in Stage 4. The final minting formula takes the smaller of two outcomes — the calibrated signal applied to aggregate reported energy E_agg_t, or a fixed multiple β of network hashrate HR_t — and then scales the result by a demand factor F_t.

The Demand Factor

F_t = clip((TPS_realized / 15,100) × (V_7d / V_hist), 0.5, 1.5)

This compares realised transaction throughput against the network's stable-state benchmark of 15,100 TPS, and compares seven-day currency velocity against its historical average, then bounds the result between 50% and 150% of the base issuance rate.

The Liquidity Signal

The market-liquidity signal, L̂_t, is derived entirely from on-chain trading-pool data rather than from any external price feed.

7.2ADTMS — The Four-State Monetary Circuit Breaker

CSI_t = 0.45·PriceDeviation_t + 0.25·(1 − C_PoEC,t) + 0.20·TPSDeficit_t + 0.10·EQCFDrift_5c

Recovery back toward Stable is deliberately conservative: six conditions must hold simultaneously for four consecutive cycles.

7.3Proof-of-Energy Cost — Verifying the Energy Backing Is Real

7.4The Pim Cell Type Standard — Native Ledger Objects

Object_valid = verify_lock(object.lock_script, tx.signature)
AND
verify_type(object.type_script, tx.inputs, tx.outputs)

7.5The Protocol-Level Exchange

k = QOL_reserve × PYM_reserve

7.6Fee Flows and the Stability Reserve

Penalties for dishonest or non-compliant node behaviour are routed into a Stability Reserve rather than being destroyed.

7.7Optional Privacy — Cash Mode

7.8How the Stability Mechanisms Work Together

"The calibration formula makes small, smooth adjustments. The circuit breaker blocks extreme reactions to short-term noise. Recovery requires sustained, multi-condition stability before normal operation resumes. Every parameter in this system is bounded, observable on-chain, and adjustable only through governance — never through unilateral intervention."