Quantum Systemic Oracle - Crypto Risk
Daily crypto systemic-risk score - IonQ Forte Hardware

forte36

Goal

Distill many noisy crypto-market signals into one daily, tamper-evident, on-chain number - a "how stressed is the crypto market right now?" oracle that smart contracts, dashboards, and risk systems can consume. This reading covers an 8-asset crypto cohort (BTC, ETH, BNB, XRP, SOL, DOGE, ADA, LINK), scored 0-10,000 BPS and packaged for Chainlink-style oracle publication (qrs-3.0.0).

Market Signals

Live momentum, volatility, breadth, stablecoin-peg, leverage/funding, liquidity and macro inputs are captured in one snapshot and blended, by weight, into the headline index. A higher index means a more stressed regime. The same primitives are asset-class agnostic: each signal (implied vol, funding, breadth, TVL/liquidity) and the QAOA risk core can be re-pointed at equities, FX, commodities, or tokenized RWAs by swapping the underlying feeds - this instance is scoped to crypto.

Quantum Stack

A QAOA portfolio optimizer (14-qubit, p=2) runs on IonQ to pick the lowest-risk held cohort; how close it lands to the classical optimum (the "gap") becomes a solution-quality signal that feeds the index and sets confidence. The final score is hashed and written to the Chainlink publish manifest.

Move the sliders below to stress-test how the index responds to each signal.
Market signals 06/15/2026 20:33 UTC Quantum run · took 0s (queue + exec) 06/15/2026 21:24 UTC Published 06/15/2026 20:36 UTC
Quantum Systemic Risk Score
NEUTRAL
0.00%
0% Calm25%50%75%100% Crisis
Calm (<25%)
Neutral (25-50%)
Stressed (50-75%)
Crisis (≥75%)
QAOA Gap vs Optimum
-
QAOA Gap vs Optimum

Measures how close the quantum optimizer (QAOA) came to the classical brute-force optimal portfolio. A near-zero gap means it recovered optimal-quality answers.

Discussed further in the "How QAOA compares (the "gap")" section lower on the page.

What this score means

A single 0-100% reading of how stressed the crypto cohort (of 8 measured assets) is right now: 0% = calm, 100% = crisis. The colored band above (Calm / Neutral / Stressed / Crisis) is the headline regime that downstream consumers act on.

How it's calculated

It is a weighted blend of nine signals - the sliders above. Each signal is normalized to 0-100 and multiplied by its weight; the weighted sum is the index. Eight are classical market signals (implied volatility, volatility trend, cross-asset correlation, sentiment, funding crowding, prediction-market uncertainty, DeFi stress, stablecoin dominance). A higher reading on any one pushes the score up by its weight - hover the ? on each slider for what it means, how it's compiled, and its data source.

Where the quantum computer comes in

The ninth signal, QAOA solution quality, is produced by a quantum optimizer (QAOA) running on IonQ. It searches for the lowest-risk basket and measures how close it lands to the provably-optimal one (the "gap") plus how concentrated its samples are. A clean, near-optimal quantum result lowers this term; a noisy or far-from-optimal one raises it. It carries a deliberately small 5% weight, so the published number never hinges on quantum-solver perfection while still folding a genuine quantum measurement into the index. As QPUs scale (e.g. IonQ Tempo), the same routine extends to far larger cohorts a classical search could never enumerate.

How it's used on-chain

The final integer is hashed and published to a Chainlink-style AggregatorV3 oracle. Smart contracts read it as a market-stress primitive - adjusting collateral ratios, gating deposits, throttling leverage, triggering kill-switches or vault deleveraging, and resolving prediction markets - so any on-chain protocol can react to system-wide risk automatically, without trusting an off-chain API.

Quantum Portfolio & Investment Outlook

QAOA Recommended Portfolio
Classical Optimum (brute-force)
Per-Asset Directives
Ranked by conviction (highest first)

QAOA Recommended Portfolio - the lowest-risk set of assets to hold that the quantum optimizer (QAOA running on IonQ) actually found and sampled. This is the recommendation the oracle publishes. It can hold a slightly different number of assets than the classical optimum below (for instance four names instead of three). That is expected, not an error: this is a budget-dominated problem where many baskets sit within a few percent of each other on cost (that spread is the gap shown up top), so the quantum run settles on a near-optimal neighbor of the brute-force best, sometimes carrying one extra, nearly cost-neutral asset, rather than reproducing the exact same set.

Classical Optimum (brute-force) - the provably best hold set, found by brute force: exhaustively scoring every one of the 2N possible hold/skip combinations (28 = 256 for this 8-asset cohort) and keeping the lowest-cost one. It is the ground-truth benchmark, but brute force only stays feasible because the cohort is small.

How QAOA compares (the "gap") - for a small cohort the brute-force optimum is unbeatable on cost, so QAOA's job is to match it. The QAOA gap vs optimum (shown above) measures how close it came; a near-zero gap means the quantum run recovered optimal-quality answers. QAOA's real advantage is scale: brute force explodes as 2N (≈1018 combinations at just 60 assets*) and quickly becomes impossible, while QAOA stays tractable - so it is the path to large cohorts a classical search could never enumerate.

*What 60 assets needs on hardware - this encoding uses only N + 6 qubits (N asset-decision + 6 global-witness), so a 60-asset book is ≈66 logical qubits, not 60. That is within reach of IonQ's upcoming Tempo (100 physical qubits, #AQ 64, 99.9% two-qubit fidelity). Crucially, the binding limit here is two-qubit-gate error, not qubit count: Tempo's ≈10× lower gate error vs Forte widens the usable two-qubit-gate envelope by roughly the same factor (Forte's today is ≈90 gates), so the deeper, fully-coupled circuit a ~60-asset QAOA requires would stay structured where Forte flattens toward uniform. Fittingly, #AQ 64 (≈264 usable states) lands right at the ≈1018-combination scale this 60-asset problem reaches - so a ~66-qubit Tempo run is the natural home for a cohort this size. At its full 100-qubit width the same N + 6 encoding tops out around ≈94 assets (100 − 6 witnesses) - a cohort whose ≈294 (≈1028) combinations are hopelessly beyond any classical brute force. (Order-of-magnitude estimate; actual capacity depends on circuit depth, coupling, and error mitigation.)

Action Glossary

How these are determined. Every asset gets an action from two inputs: whether the QAOA optimizer placed it in the recommended hold basket, and a small directional signal score. The score sums three live signals - the asset's 30-day price z-score (oversold adds points, overbought subtracts), the Polymarket bull-minus-bear skew (net-bullish adds, net-bearish subtracts), and the OKX perpetual funding rate (crowded longs subtract, negative funding adds).

That score is then read against basket membership. For assets QAOA picked to hold: a strongly positive score is BUY (signals align), a flat-to-positive score is ACCUMULATE, and a negative score is HOLD (stay at target weight, do not add). For assets it did not pick: a strongly negative score is EXIT, a flat-to-negative score is AVOID, and a positive score is WATCH (bullish, but excluded by the diversification / budget math so it is not held this run).

Actions describe a target state and do not depend on what you currently hold - net them against your existing positions. Like everything here, they are experimental research outputs, not financial advice.

Hardware Run Diagnostics

Data Sources & Circuit

Assets (8)

    Market Signals

    • Deribit DVOL (BTC/ETH implied vol)
      Deribit

      Website: www.deribit.com

      API docs: docs.deribit.com/

      Free tier: Free. Public market-data endpoints (e.g. public/get_volatility_index_data) need no account or key; throttled per-IP and unauthenticated callers are limited more strictly, so cache and poll gently.

    • Polymarket bull/bear probabilities
      Polymarket

      Website: polymarket.com

      API docs: docs.polymarket.com/

      Free tier: Free, no key for read-only market data (Gamma API). General limit ~4,000 req/10s; the /events endpoint ~500 req/10s.

    • OKX perpetual funding & OI
      OKX

      Website: www.okx.com

      API docs: www.okx.com/docs-v5/en/

      Free tier: Free. Public market-data endpoints (funding-rate, open-interest) need no key; rate-limited per-IP per endpoint. Note: OKX is unavailable to US users.

    • CoinGecko price & correlation
      CoinGecko

      Website: www.coingecko.com

      API docs: docs.coingecko.com/

      Free tier: Free Demo plan: 10,000 calls/month, 30 calls/min, needs a free API key. Attribution to CoinGecko is required on the free tier.

    • DeFiLlama TVL stress
      DeFiLlama

      Website: defillama.com

      API docs: api-docs.defillama.com/

      Free tier: Free open API (api.llama.fi), no key, standard per-IP rate limit. Their terms ask you not to scrape/resell for commercial use outside the official API; credit DeFiLlama as the source.

    • Stablecoin dominance
      CoinGecko

      Website: www.coingecko.com

      API docs: docs.coingecko.com/

      Free tier: Free Demo plan: 10,000 calls/month, 30 calls/min, needs a free API key. Attribution to CoinGecko is required on the free tier.

    • Fear & Greed sentiment
      Alternative.me (Crypto Fear & Greed Index)

      Website: alternative.me/crypto/fear-and-greed-index/

      API docs: alternative.me/crypto/api/

      Free tier: Free, no key (~60 requests/min). Personal and commercial use allowed; a visible 'Data from alternative.me' credit next to the value is requested.

    Quantum Stack

    • QAOA p=2
    • Circuit 14 qubits
    • 8 decision + 6 global witnesses
    • Lean witness bias (hardware-aligned)
    • Qiskit + IonQ simulator / Forte QPU