39 Quantum Services

Quantum-signed AI agent actions

Every AI agent decision is sealed with IBM quantum entropy — provides physical proof that agent actions were not pre-determined or backdated.

Quantum commit-reveal oracle

Commit-reveal scheme where the reveal key is derived from quantum entropy — eliminates front-running attacks on oracle price feeds.

Verifiable quantum random draws

Lottery, NFT drops, DAO sampling — all backed by IBM hardware randomness with an auditable job_id anyone can verify on the IBM Quantum Network.

Quantum threshold voting

Multi-party consensus with quantum nonces preventing vote-order manipulation. Each tally is sealed with a QRNG-derived entropy stamp.

Quantum-certified device enrollment

IoT and hardware attestation where each enrollment certificate is sealed with quantum entropy — physically irrefutable timestamp.

Quantum-sealed delegation tokens

Delegated authority tokens sealed with quantum entropy — prevents token replay attacks and provides unforgeable proof of delegation time.

t-of-n quantum authorization

Shamir secret sharing where the dealer randomness is quantum-certified — eliminates the trusted dealer assumption in threshold cryptography.

Quantum sealed-bid auctions

Bid commitments are quantum-randomized preventing bid-shadowing. The winner is determined by quantum-sealed reveal with on-chain verifiability.

Quantum anomaly detection in P2P

Swap-test kernel detects Sybil attacks, eclipse attacks, and coordinated MEV in mempool traffic — achieves 2^n dimensional feature separation.

Quantum mining difficulty prediction

Quantum Amplitude Estimation builds a probability distribution over next-epoch difficulty — gives miners a sharper prediction than classical EMA.

Quantum kernel vulnerability scoring

Encodes smart contract opcode distribution as a quantum state and computes kernel similarity against calibrated vulnerable/safe anchor profiles — detects reentrancy, unchecked delegatecall, and flash-loan exposure patterns invisible to static analysis.

QAOA transaction batching — minimize gas spend

Formulates transaction batch selection as a QUBO maximising net value (fees + MEV) subject to block gas limit. QAOA evaluates all 2^n combinations simultaneously, outperforming greedy ordering on correlated gas profiles.

QAOA transaction ordering for MEV

QAOA p=1 solves the block-packing QUBO — maximises miner extractable value (fees + MEV) subject to gas limit, outperforming greedy by measurable margin.

QRNG validator selection — no RANDAO bias

XOR quantum entropy with RANDAO mix eliminates the last-revealer attack. Each committee selection is provably unbiased and auditable on IBM Network.

Quantum-certified cross-chain bridge

Bridge authorization sealed with quantum entropy — provides physical proof that cross-chain messages were not replayed or front-run between networks.

Quantum reserve attestation

Reserve snapshots sealed with QRNG — the quantum_entropy + job_id are publicly auditable on IBM Network, proving reserves were not backdated.

QAOA crypto portfolio optimization

QAOA p=1 explores 2^n asset combinations simultaneously, selecting the portfolio that maximises Sharpe ratio — outperforms classical Markowitz on concentrated allocations.

Quantum Monte Carlo DeFi VaR

QRNG-seeded Monte Carlo paths + Cornish-Fisher correction for fat tails — produces tighter VaR confidence intervals than pseudo-random simulation.

QAOA DeFi yield allocation

Optimal capital allocation across DeFi protocols via QAOA QUBO — balances APY vs risk vs lock period simultaneously, beating greedy allocation.

Quantum amplitude estimation options pricing

QAE builds a quadratic speedup over classical Monte Carlo for options pricing — provides quantum confidence intervals narrower than Black-Scholes approximation.

QAOA cross-exchange arbitrage

DFS enumerates all profitable cycles; QAOA p=1 selects the optimal path among candidates via quantum superposition over all n paths simultaneously.

Quantum kernel whale clustering

Swap-test kernel computes pairwise wallet similarity in 2^n dimensional quantum feature space — detects coordinated whale groups invisible to classical clustering.

QRNG CAT bond pricing & Expected Shortfall

Cholesky-correlated quantum Monte Carlo paths for catastrophe bond pricing and ES/VaR at 99.5% confidence (Solvency II SCR). Quantum entropy ensures non-reproducible simulation.

Quantum walk supply chain resilience

Discrete-time quantum walk on the supplier graph achieves ballistic spreading (σ∝t vs σ∝√t classical) — identifies critical nodes and hidden fragility faster than PageRank.

ZZFeatureMap swap-test fraud kernel

ZZFeatureMap encodes 4 transaction features onto quantum states. Swap-test circuits compute kernel similarity to fraud/legitimate anchor profiles in 2^4=16 dimensional feature space.

QAOA satellite collision avoidance

QUBO formulation of maneuver selection: H = -Σwᵢxᵢ + λ(Σcᵢxᵢ−F)². QAOA finds the fuel-optimal avoidance maneuver set respecting the fuel budget constraint.

Quantum kernel industrial failure prediction

Encodes multi-sensor readings (vibration, temperature, pressure, current) as a quantum state and computes similarity against failure/healthy anchor profiles. Returns failure probability, time-to-failure estimate, and recommended action.

Quantum kernel credit risk — 2¹⁶ feature space

ZZFeatureMap encodes credit_score, DTI, LTV, payment history onto 4-qubit state. Swap-test kernel classifies default probability in 2^4=16 dimensional quantum space vs 4D classical.

QAOA optimal power grid dispatch

QUBO H = −Σprofitᵢxᵢ + λ(Σcapᵢxᵢ − demand)² is solved by QAOA — minimises fuel cost while satisfying grid demand, outperforming classical merit-order dispatch.

QAOA carbon credit portfolio optimization

Selects the optimal carbon credit portfolio via QAOA QUBO — maximises quality-adjusted offset volume and standard diversity (VCS, Gold Standard, ACR) subject to budget and tonnage constraints. Outperforms classical greedy on multi-standard portfolios.

Quantum options pricing for physical commodities

Prices European commodity options via QAE incorporating convenience yield, seasonal demand multipliers, and commodity-specific volatility floors — produces tighter confidence intervals than Black-Scholes for oil, gas, gold, wheat, copper.

Quantum pricing for weather-linked instruments

Prices parametric weather derivatives (HDD, CDD, rainfall, wind speed) via QAE over stochastic weather models calibrated from historical index data. Achieves tighter pricing intervals than classical Monte Carlo for reinsurance and agriculture.

Quantum content provenance certificate

Every piece of content — article, image, NFT, document — receives a quantum provenance certificate. IBM job_id serves as an unforgeable physical timestamp; SHA-256 + HMAC seal makes backdating mathematically impossible.

Quantum walk Sybil-resistant trust score

Discrete quantum walk over peer graph achieves ballistic spreading (σ∝t vs σ∝√t classical), making Sybil clusters computationally expensive to fake. Returns trust score, quantum centrality, and Sybil risk flag for any user or node.

Q-PUF quantum behavioral fingerprint

Behavioral signals (device, timing, gesture) are encoded as a ZZFeatureMap quantum state. IBM hardware noise acts as a Quantum Physical Unclonable Function — every execution is physically unique, making identity spoofing impossible even with the same input.

GDPR quantum consent certificates

GDPR/CCPA consent records sealed with quantum entropy. Each consent_id is backed by an IBM job_id that serves as Art. 7 GDPR forensic proof — physically impossible to forge, replay, or backdate. Supports medical, financial, and marketing consent types.

QAE ensemble forecasting — O(1/ε) CI

Quantum Amplitude Estimation builds tighter confidence intervals [O(1/ε)] over weighted model ensembles vs classical Monte Carlo [O(1/√N)]. Works for any business metric: sales, demand, price, traffic. No quantum expertise required.

Quantum kernel ML model IP protection

Detects stolen or distilled AI models via ZZFeatureMap swap-test kernel in 2^n dimensional quantum feature space. Behavioral signatures invisible to classical similarity metrics are amplified in quantum space — flags unauthorized model copies even after fine-tuning or quantization.

Quantum content fingerprinting — multilingual hate & fake detection

Extracts 4 weighted semantic features (indicator density, sensationalism, target-cluster, repetition) using tiered vocabularies in EN/ES/PT/FR with context modifiers (negation, intensifiers, conditionals, quotes). Encodes a danger score as RY(θ) on q0 + CNOT star to q1–q3, producing P(|1111⟩) = sin²(θ/2) as a monotonic quantum fingerprint. Returns classification, danger_score, per-feature breakdown, and requires_human_review flag for ambiguous descriptors.