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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Quantum Occam LearningQuantum Occam Learning methodology — information-theoretic framework for balancing expressibility and learnability in circuit-based quantum machine learning. Use when designing quantum neural network ansätze, choosing quantum data encoding circuits, or analyzing generalization bounds for variational quantum algorithms. arXiv: 2606.12211Votes: 0GitHub stars: 3
- Quantum On Hardware Qnn TrainingScalable on-hardware quantum neural network training methodology using Butterfly circuits, layer-wise optimization, and parallelized parameter-shift rules. Reduces gradient estimation cost from O(n²) to O(log n).Votes: 0GitHub stars: 3
- Quantum Opinion Dynamics NetworksQuantum model of opinion dynamics on networks — represents agent cognitive states as density matrices encoding both expressed opinions and cognitive ambivalence, with survey questions as non-commuting self-adjoint operators explaining order effects.Votes: 0GitHub stars: 3
- Quantum Optimal Control Irrep DistillationQuantum optimal control of Dicke manifold using irrep distillation methodology. Controls quantum states of many-body systems by exploiting symmetric subspace structure in Rydberg atom arrays. Irrep distillation captures how symmetric subspace couples to leakage error-spaces using only linear-scaling Hilbert dimension. Combines with gradient ascent pulse engineering (GrAPE) for control schemes with minimal local addressing. Benchmarks quantum speed limit and pulse fidelities. Activation: quant...Votes: 0GitHub stars: 3
- Quantum Optimal Control RydbergQuantum optimal control of the Dicke manifold in Rydberg atom arrays. Control multi-body quantum states in Rydberg platforms for quantum computing. From arXiv:2606.02283 (Pannier-Gunther et al., 2026).Votes: 0GitHub stars: 3
- Quantum Optimal Transport EntanglementBipartite entanglement measurement via minimal quantum Wasserstein distance to separable states — Lipschitz dual formulation, entanglement witness connection, and experimental detection framework.Votes: 0GitHub stars: 3
- Quantum Optimization QaoaGuide for understanding and applying the Quantum Approximate Optimization Algorithm (QAOA) for combinatorial optimization problems. Covers QAOA principles, circuit construction, parameter optimization, and classical-quantum hybrid workflows. Use when working with quantum optimization, variational quantum algorithms, combinatorial optimization on quantum hardware, or analyzing QAOA performance on specific problem instances.Votes: 0GitHub stars: 3
- Quantum Pac Learning TheoryMethodology for analyzing sample complexity in quantum PAC-learning models where concepts are functions acting on quantum states.Votes: 0GitHub stars: 3
- Quantum Paradigm Comparison Cv DvControlled comparison methodology for continuous-variable (CV) vs discrete-variable (DV) quantum computing paradigms. Uses shared classical backbone with interchangeable quantum heads to isolate quantum circuit as sole variable. CV outperforms DV with 18-point accuracy gap on wafer-map defect classification.Votes: 0GitHub stars: 3
- Quantum Path Superposition TeleportationPath-superposition framework for quantum gate teleportation enabling superposed path operations for advanced quantum information transfer protocols.Votes: 0GitHub stars: 3
- Quantum Pde Option PricingEnd-to-end quantum PDE framework for derivative pricing. Use when: designing quantum algorithms for option pricing, solving high-dimensional financial PDEs on quantum hardware, comparing quantum vs classical pricing complexity, implementing Black-Scholes or Heston models on quantum circuits, or evaluating quantum advantage for financial derivative pricing. Covers: quantum PDE solvers, finite-difference discretization, gate complexity analysis, Clifford+T resource estimation, implied volatilit...Votes: 0GitHub stars: 3
- Quantum Pde Speedup CertificationCertification methodology proving quantum-inspired classical algorithms cannot achieve exponential speedup for high-dimensional PDE discretizations, confirming quantum advantage for high-dimensional problems.Votes: 0GitHub stars: 3
- Quantum Pet Biomarkers HypoxiaQuantum entanglement degree as novel PET biomarkers for tissue hypoxia detection. Based on first-in-human quantum entanglement PET imaging (J-PET scanner). Covers two quantum sensing methods: (1) ortho-positronium decay rate correlation with oxygen concentration, (2) quantum entanglement degree sensitivity to tissue oxygen levels via Compton scattering. Use when: (1) designing quantum-enhanced PET imaging protocols, (2) developing hypoxia biomarkers, (3) working with J-PET or plastic scintill...Votes: 0GitHub stars: 3
- Quantum Portfolio OptimizationQuantum portfolio optimization methodologies — QAOA for higher-order moments (skewness, kurtosis), quantum annealing for mean-variance optimization, and hybrid quantum-classical pipelines for NISQ-era finance. Use when: (1) portfolio optimization with quantum computing, (2) QAOA for financial problems, (3) quantum annealing for trading, (4) higher-order moment portfolio selection, (5) hybrid quantum-classical finance.Votes: 0GitHub stars: 3
- Quantum Portfolio OptimizerQuantum computing portfolio optimization skill. Uses QAOA, quantum annealing, and hybrid quantum-classical methods for financial portfolio optimization with higher-order moments (skewness, kurtosis) and real-world constraints (cardinality, turnover limits). Activation: quantum portfolio, quantum optimization, QAOA portfolio, 量子组合优化, quantum finance optimization, portfolio optimization quantum.Votes: 0GitHub stars: 3
- Quantum Priors Chaos PredictionQuantum statistical prior (Q-Prior) methodology for chaotic dynamical systems — k-indexed higher-order quantum priors storing non-factorisable spatial correlations on n_q qubits, with two-stage quantum advantage via superposition/entanglement representation and joint Bell measurement extraction. For chaotic system prediction, turbulence modeling, weather forecasting with quantum-informed ML. Trigger words: Q-Prior, quantum statistical prior, chaos prediction, turbulent flow, quantum advantage...Votes: 0GitHub stars: 3
- Quantum Privacy Utility TradeoffPrivacy-utility tradeoff methodology for quantum information processing and quantum differential privacy. Studies optimal tradeoffs between privacy guarantees and learning utility in quantum settings. Use when analyzing quantum differential privacy, designing privacy-preserving quantum learning protocols, or evaluating quantum information privacy constraints.Votes: 0GitHub stars: 3
- Quantum Probabilistic Differential PrivacyQuantum probabilistic local differential privacy methodology - structural properties, sample complexity bounds, and hypothesis testing applications for privacy-preserving quantum information processing.Votes: 0GitHub stars: 3
- Quantum Program AnalysisLLM-powered analysis and quality assurance for quantum programs. Use when: (1) linting quantum circuits/programs beyond simple rule checks, (2) analyzing quantum algorithm correctness and optimization opportunities, (3) evaluating quantum program performance under noise models, (4) benchmarking quantum primitives under hardware-motivated noise, (5) distributed quantum algorithm compilation and analysis. Covers LLM-based quantum linting, FTPrimitiveBench noise benchmarking, and topological qua...Votes: 0GitHub stars: 3
- Quantum Program LintingLLM-powered static analysis and linting for quantum programs. Use when: (1) analyzing quantum circuits for correctness and optimization opportunities, (2) detecting anti-patterns in quantum code (Qiskit, Cirq, Pennylane), (3) improving quantum program quality through automated review, (4) validating quantum algorithms before execution on hardware. Covers LLM-based linting rules, quantum circuit analysis, and best practices for quantum software engineering.Votes: 0GitHub stars: 3
- Quantum Protocol DesignerDesign and analyze quantum information processing protocols. Focus on quantum encoding schemes (polarization, time-bin), QKD security verification, topology-hiding protocols, and quantum state engineering. Activates when user asks about quantum protocol design, quantum network security, QKD protocols, or quantum encoding conversion.Votes: 0GitHub stars: 3
- Quantum Qubit VerificationMethodology for classical verification of quantum computation by testing anti-commuting operators on quantum devices.Votes: 0GitHub stars: 3
- Quantum Rare Event SamplingQuantum algorithm for discovering and sampling rare events without prior knowledge of which events are rare. Achieves optimal quantum scaling with rarity threshold and quadratic speedup for heavy-tailed systems.Votes: 0GitHub stars: 3
- Quantum Reservoir Chaotic ForecastingQuantum reservoir computing architecture for forecasting chaotic systems with a high-dimensional feature space diagnostic. Provides reproducible recipe for QRC circuit construction, data injection, readout training, and stability-number-based dimensionality validation. Activation: quantum reservoir computing, chaotic forecasting, reservoir dimensionality diagnostic, quantum feature generator, reservoir stability numberVotes: 0GitHub stars: 3
- Quantum Reservoir ComputingQuantum Reservoir Computing (QRC) framework for chaotic time-series prediction and dynamical systems modeling. Use for benchmarking fixed-reservoir vs variational quantum architectures, implementing quantum physics-informed neural networks (QPINN), and analyzing quantum machine learning performance on NISQ devices. Focus on Lorenz system and chaotic dynamics applications.Votes: 0GitHub stars: 3
- Quantum Resilient Decentralized Ai EconomyThree-layer decentralized AI economy architecture replacing proof-of-work with useful ML work, with post-quantum security analysis and economic coordination mechanismsVotes: 0GitHub stars: 3
- Quantum Resonance EncryptionQuantum resonance encryption methodology using quantum kicked top dynamics for secure data storage and communication. Provides perfect recovery for authorized users while making intercepted states appear mixed to eavesdroppers with built-in tampering detection. Applicable to quantum cloud computing, secure quantum communication, and QKD.Votes: 0GitHub stars: 3
- Quantum Ring All Reduce DistributedQuantum ring all-reduce protocol for distributed machine learning. Uses superdense coding to halve per-link communication and provides information-theoretically secure aggregation impossible classically.Votes: 0GitHub stars: 3
- Quantum Ring Allreduce DistributedQuantum ring all-reduce protocol for distributed ML training — uses pre-shared entanglement and superdense coding for 2x communication reduction plus information-theoretic privacy guarantees. Covers composable ε-secure aggregation via verified entanglement and exponential separation in sign-consistency auditing.Votes: 0GitHub stars: 3
- Quantum Ring AllreduceQuantum Ring All-Reduce methodology for distributed learning — reduces per-link communication by 2x using superdense coding, enables information-theoretically private aggregation via verified entanglement, and achieves exponential communication separation for sign-consistency auditing.Votes: 0GitHub stars: 3
- Quantum Rl Scuc QsampleHybrid quantum-classical reinforcement learning for Security-Constrained Unit Commitment (SCUC). Uses Bernoulli hybrid soft actor-critic (HSAC) with quantum-sampled feature augmentation for economic dispatch in power systems. Activation: quantum RL SCUC, unit commitment optimization, quantum-sampled features, hybrid soft actor-critic, economic dispatch quantum, power grid optimization quantumVotes: 0GitHub stars: 3
- Quantum Robust ControlRobust quantum control engineering patterns from recent research (2025-2026). Covers RL-based quantum control, fault-tolerant QEC verification, hardware co-design, and hybrid quantum-classical architecture. Use when designing, analyzing, or implementing quantum control systems that must operate reliably under noise, model uncertainty, and hardware imperfections. Relevant to quantum error correction, optimal control, reinforcement learning for quantum systems, and dependable quantum computing.Votes: 0GitHub stars: 3
- Quantum Routing AnonymityMethodology for analyzing and quantifying routing anonymity in quantum cloud computing — backend identifiability, privacy guarantees, and utility-anonymity trade-offs. Use when evaluating quantum cloud security, designing privacy-preserving quantum circuits, or analyzing hardware fingerprinting in noisy quantum systems. Trigger words: routing anonymity, backend identifiability, quantum cloud security, hardware fingerprinting, quantum privacy, Chernoff rate, Pauli-transfer-matrix.Votes: 0GitHub stars: 3
- Quantum Safe Control SystemsSafe deployment patterns for quantum control policies in cyber-physical systems. Covers Q-DASC discrepancy-attributed safe quantum control framework, Simplex architecture for quantum-classical switching, and certified safety layers for variational quantum circuit controllers. Based on arXiv:2606.28834 (Q-DASC) and arXiv:2606.31056 (Simplex Q-CPS).Votes: 0GitHub stars: 3
- Quantum Signal Processing Orthogonal PolyQuantum Signal Processing (QSP) via orthogonal polynomial theory methodology. Provides analytical angle-finding for QSP protocols using Hermite, Jacobi, and Rogers-Szego polynomial expansions. Enables block-encoding of smooth functions with O(log(1/epsilon)) gate complexity. Use when: implementing quantum signal processing, quantum algorithm design with orthogonal polynomials, quantum function approximation, Hamiltonian simulation, quantum eigenvalue transformation, or designing efficient qua...Votes: 0GitHub stars: 3
- Quantum Simulation Of Real World Nonlinear Dynamics Via Koopman MethodNonlinear dynamics is ubiquitous in nature, ranging from chemical pattern formation to ocean circulation, yet its simulation on quantum computers is fundamentally limited by the unitary nature of quan. Based on arXiv:2607.07338.Votes: 0GitHub stars: 3
- Quantum Software ArchitectureComponent-based Quantum Software Architecture Framework (QSAF) for designing hybrid quantum-classical systems. Provides 34 reusable quantum circuit patterns, architectural guidelines, and systematic transition from circuit-level to system-level design.Votes: 0GitHub stars: 3
- Quantum Software CertificationQuantum Software Engineering (QSE) certification patterns - hybrid FPGA+AI frameworks for validating quantum device entanglement using CHSH inequality and LLM-guided optimizationVotes: 0GitHub stars: 3
- Quantum Software Engineering PracticeQuantum software engineering practical patterns for FPGA-based quantum control systems with AI integration. Covers hardware-aware compilation, real-time feedback control, and fault-tolerant quantum computing workflows. Activation: quantum software engineering, FPGA quantum control, quantum AI integration, quantum compilation, real-time quantum feedback.Votes: 0GitHub stars: 3
- Quantum Software Testing BenchmarkQolumbina benchmark infrastructure for quantum software testing (QST) — curates 40 scalable quantum programs from open-source repos with systematic selection, refactoring, specifications, unit tests, and standardized interfaces. Introduces QST-oriented criteria along functionality, output behavior, development complexity, and quantum-specific execution complexity.Votes: 0GitHub stars: 3
- Quantum Spectral Anomaly DetectionQuantum Spectral Anomaly Detection (QSPADE) methodology for computing PCA-like anomaly scores using quantum spectral methods - enables efficient anomaly detection in high-dimensional medical and financial data via quantum eigenvalue decomposition.Votes: 0GitHub stars: 3
- Quantum Stabilizer Testing Limited MemoryOptimal stabilizer testing and learning methodology under limited quantum memory constraints. Provides sample complexity bounds and efficient algorithms for testing whether quantum states are stabilizer states when quantum memory is bounded.Votes: 0GitHub stars: 3
- Quantum State EngineeringMeasurement-assisted quantum state engineering methodology for generating and manipulating squeezed Schrodinger cat states. Uses QND entangling operations with homodyne measurement for high-fidelity state preparation. Applicable to measurement-based quantum computing, hybrid quantum networks, and non-Gaussian resource generation.Votes: 0GitHub stars: 3
- Quantum Stationary Point FindingQuantum comparison oracle methodology for finding stationary points of non-convex functions with quadratic speedup — O~(n/epsilon^1.5) quantum vs O~(n^2/epsilon^1.5) classical queries. ICML 2026 paper by Wang et al.Votes: 0GitHub stars: 3
- Quantum Statistical EstimationQuantum statistical estimation theory and applications - combines Bayesian methods, quantum Cramér-Rao bounds, and quantum parameter estimation for optimal quantum system state estimation. Use when analyzing quantum metrology, quantum parameter estimation, quantum statistics theory, or implementing optimal measurement strategies for quantum systems.Votes: 0GitHub stars: 3
- Quantum Statistical Functional EstimationQuantum computing approach to minimax estimation of high-order functionals (Rényi/Tsallis entropy). Bridges quantum algorithms with classical statistics. Activation: quantum statistics, minimax estimation, renyi entropy, functional estimation, quantum arguments, sample complexity.Votes: 0GitHub stars: 3
- Quantum Steering TypicalityFramework for analyzing the typicality of quantum steering behavior in two-qubit states — determines when correlations cannot be explained by local hidden state models, with applications to quantum communication and entanglement verification.Votes: 0GitHub stars: 3
- Quantum Stochastic Walk PortfolioQuantum Stochastic Walk (QSW) optimizer for portfolio optimization — embeds assets in weighted covariance graph, derives weights from walk stationary distribution, achieving 15% Sharpe improvement and 90% turnover reduction vs classical mean-variance.Votes: 0GitHub stars: 3
- Quantum Structured Factorization TomographyUnified structured factorization framework for quantum state tomography using Burer-Monteiro-type factorization parametrizing density matrix as FF†, guaranteeing physical validity while incorporating structural priors.Votes: 0GitHub stars: 3
- Quantum System Engineering量子系统工程方法论 - 涵盖分布式量子计算、混合量子-经典系统架构、量子错误纠正、量子系统优化。适用于量子计算系统设计、量子网络架构、量子-经典混合工作流等任务。关键词：quantum systems, distributed quantum computing, quantum architecture, hybrid quantum-classical, quantum error correction, qubit design, quantum network, 量子系统工程, 分布式量子计算, 量子架构设计。Votes: 0GitHub stars: 3