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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Quantum OphthalmologyQuantum technologies in ophthalmology methodology — photon-limited retinal imaging, correlation-based ghost imaging, quantum dot nanoscale probes, and single-photon visual perception studies. Use when building quantum-enhanced ophthalmic imaging pipelines, studying visual system detection limits, designing low-light retinal imaging protocols, or developing quantum-inspired diagnostic technologies for eye diseases.Votes: 0GitHub stars: 3
- Quantum Optimization Landscape AnalysisQuantum optimization landscape analysis methodology for NISQ-era variational algorithms. Covers VQE/QAOA performance analysis, expressibility-noise barren plateaus, feedback-guided methods (FALQON), and physics-informed circuit co-design for strongly correlated many-body systems. Activation: quantum optimization, VQE, QAOA, barren plateau, FALQON, feedback quantum algorithm, strongly correlated systems, many-body phase transitions, variational quantum algorithm, quantum criticality, expressib...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 Optimization TransportationApply quantum optimization algorithms to transportation network problems including vehicle routing, urban logistics, and infrastructure planning. Covers compressed adiabatic evolution, constraint-preserving XY-mixers, QAOA variants, and hardware-efficient formulations. Use when formulating transportation combinatorial optimization as quantum problems, implementing constraint-preserving quantum mixers, or optimizing hardware resource usage for quantum annealing.Votes: 0GitHub stars: 3
- Quantum Option Pricing Heat EquationExponentially fast quantum state preparation for the heat equation applied to financial option pricing. Maps Black-Scholes PDE to quantum linear system via heat equation discretization, achieving exponential speedup over classical methods. Use when: quantum finance, option pricing on quantum computers, Black-Scholes quantum solver, PDE-to-quantum mapping, quantum derivatives pricing, heat equation quantum simulation.Votes: 0GitHub stars: 3
- Quantum Oracle Resource OptimizationQuantum oracle resource optimization methodology - Hierarchical Recursive Synthesis-Evaluation (HRSE) model for formal oracle description, Adaptive Space-depth Trade-off (ASDT) algorithm for optimal oracle generation under qubit constraints, achieving 54% circuit depth reduction. (arXiv:2605.21380)Votes: 0GitHub stars: 3
- Quantum Os Resource ManagementQuantum operating systems and resource management patterns for hybrid quantum-classical computing. Covers QOS architecture, Slurm-based quantum resource scheduling, job multiprogramming, hardware-agnostic APIs, error mitigation at the OS level, and container management for quantum workloads. Use when: (1) Designing quantum operating systems or resource managers, (2) Integrating quantum backends with HPC schedulers (Slurm, Kubernetes), (3) Building hardware-agnostic quantum job execution APIs,...Votes: 0GitHub stars: 3
- Quantum Particle Statistics ClassificationClassify and reconstruct quantum particle statistics types: bosonic, fermionic, and exotic statistics. Analyze symmetrization postulates and commutation relations. Activation: particle statistics, quantum statistics, 粒子统计, boson fermion, exchange symmetry, commutation relation.Votes: 0GitHub stars: 3
- Quantum Pave ChemistryQuantumPave — hybrid quantum-classical workflow for computing additive binding energies using quantum-centric supercomputing. Demonstrates practical quantum chemistry application on real quantum processors by sampling dominant electronic configurations on a QPU and performing classical diagonalization on HPC resources.Votes: 0GitHub stars: 3
- Quantum Persistent Homology EncodingQuantum data encoding methodology that preserves persistent homology topological features. Maps point cloud data to quantum states while maintaining topological invariants (Betti numbers, persistence diagrams). Use when: topological data analysis with quantum computing, quantum machine learning with topology preservation, persistent homology quantum encoding, algebraic topology quantum features, TDA quantum pipelines.Votes: 0GitHub stars: 3
- Quantum Pet BiomarkersQuantum entanglement degree as PET biomarkers for hypoxia sensing methodology. Uses positronium quantum sensing to non-invasively assess tissue oxygen concentration via photon entanglement, lifetime, and annihilation ratios.Votes: 0GitHub stars: 3
- Quantum Picotesla Biomagnetism SensingPicotesla-scale magnetic environment design for quantum biomagnetism sensing. Enables optically pumped magnetometers, magnetocardiography (MCG), magnetoencephalography (MEG), and ultra-low field MRI without active dynamic compensation. Use when designing quantum sensing platforms for medical diagnostics, picotesla magnetic shielding, robotic magnetic field mapping, or biomagnetic measurement systems.Votes: 0GitHub stars: 3
- Quantum Pipeline IntegrityContract-based supervision framework for quantum-classical pipeline integrity verification. Uses behavioral fingerprinting to detect pipeline degradation, component substitution, and silent failures in hybrid quantum-classical ML systems. Activation: quantum pipeline integrity, contract-based supervision, quantum ML verification, behavioral fingerprinting, pipeline monitoringVotes: 0GitHub stars: 3
- Quantum Pkpd SimulationQuantum circuit simulation methodology for compartmental pharmacokinetic/pharmacodynamic (PK/PD) modeling. Reformulates drug dynamics as open quantum systems with variational quantum circuits. Use when: simulating drug dynamics with quantum computing, modeling PK/PD with quantum circuits, PennyLane quantum pharma, variational drug simulation, quantum compartmental models, quantum pharmacology.Votes: 0GitHub stars: 3
- Quantum Portfolio Benchmark AuditCritical benchmark methodology for evaluating quantum portfolio optimization claims. Provides systematic comparison framework testing quantum annealing and QAOA against classical solvers (MIP, simulated annealing, tabu search, problem-tailored heuristics) on real-world instances up to 1,000 assets. Key finding: classical MIP solves all instances to proven optimality in seconds; problem-tailored heuristics consistently outperform quantum approaches in solution quality for fixed runtime. Use wh...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 Positive MapsAnalysis of positive trace-preserving (PTP) maps in quantum information theory. Petz recovery map construction, sufficiency conditions, and Jordan algebra generalizations. Use when: (1) Analyzing quantum state interconversion via positive maps, (2) Implementing Petz recovery for quantum channel inversion, (3) Studying minimal sufficient algebras in quantum systems, (4) Generalizing Koashi-Imoto decomposition to PTP setting.Votes: 0GitHub stars: 3
- Quantum Predicate Learning SggQPredSGG: Hybrid Quantum Predicate Learning for Long-Tailed Scene Graph Generation. Use when analyzing quantum algorithms, complexity bounds, quantum ML architectures, or quantum error correction involving mathematical analysis and statistical methods.Votes: 0GitHub stars: 3
- Quantum Prime IdentificationQuantum protocol for prime number identification using entanglement dynamics on real quantum processors. Links primality testing to Fourier components of quantum circuit measurements. Use when: prime number testing with quantum hardware, quantum number theory, entanglement-based primality detection, quantum arithmetic algorithms, Shor algorithm alternatives, noise mitigation for quantum processors, rescaling-based error mitigation.Votes: 0GitHub stars: 3
- Quantum Prior Chaos ForecastingQuantum statistical prior (Q-Prior) methodology for chaotic dynamical system forecasting using quantum-informed machine learning. Proves practical quantum advantage via two-stage mechanism: (1) superposition/entanglement compactly stores non-factorisable spatial correlations of invariant measures, (2) joint Bell measurements estimate Pauli functionals with copy complexity independent of qubit count vs Omega(2^n_q) for classical. Use when: chaos forecasting, quantum ML, turbulent flows, weathe...Votes: 0GitHub stars: 3
- Quantum Priors Chaos ForecastingQuantum statistical prior (Q-Prior) methodology for chaotic dynamical systems prediction. Uses higher-order quantum statistical priors to compactly store non-factorisable spatial correlations via superposition and entanglement, enabling efficient ML training on chaotic systems. Proves two-stage quantum advantage: representation (compact correlation storage) and learning (efficient ML training). arXiv:2606.13422Votes: 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 Probability Flow Hebbian LearningQuantum probability-flow principle for deriving local Hebbian learning rules in associative memory networks using quantum annealer validation. arXiv:2606.02098Votes: 0GitHub stars: 3
- Quantum Probability Hebbian LearningQuantum probability-flow methodology for deriving local Hebbian learning rules in associative memory networks. Use when: (1) quantum-inspired learning rules for neural networks, (2) attention mechanisms from quantum probability flow, (3) quantum annealer-based learning rule validation, (4) transverse-field leakage channels for stability-driven updates. Activation: quantum probability flow, Hebbian learning, quantum annealer, associative memory, transverse field, attention-like learning rule, ...Votes: 0GitHub stars: 3
- Quantum Probability StatisticsFramework for applying quantum probability theory to statistical settings and machine learning. Covers Born rule applications, quantum measurement theory, quantum state superposition, and quantum interference in probabilistic modeling. Activation: quantum probability, quantum statistics, 量子概率统计, quantum ML, Born rule statistics.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 Program Semantic VerificationSemantics-based verification methodology for quantum programs implementing number-theoretic algorithms. Covers oracle specification, refinement-style verification, and semantic auditing for Shor-style quantum algorithms. Based on arXiv:2605.01008.Votes: 0GitHub stars: 3
- Quantum Proper Scoring RulesApply proper scoring rules to quantum state estimation and forecasting. Generalize classical proper scoring rules to density operators using operator convex generators and Quantum Fisher Information. Derive minimax optimal bounds for quantum state tomography. Quantify economic value of quantum resources in forecasting tasks. Use when performing quantum state estimation, designing quantum scoring mechanisms, analyzing quantum forecasting, or applying information geometry to quantum systems. ar...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 Prototype LearningGeometric prototype learning in quantum Hilbert space using matrix product states for explainable MLVotes: 0GitHub stars: 3
- Quantum Purification MachinesQuantum purification machines framework — impossibility of universal probabilistic exact purification from finite copies, and optimal approximate purification strategies. Fundamental obstruction: purifying two inputs of different rank with non-zero probability requires non-linear positive map. arXiv: 2604.06325.Votes: 0GitHub stars: 3
- Quantum Purity AmplificationQuantum Purity Amplification (QPA) methodology — coherent transformation of mixed quantum states into high-fidelity eigenstate copies with dimension-uniform sample complexity. Use when designing quantum state purification protocols, quantum error mitigation, coherent quantum information processing.Votes: 0GitHub stars: 3
- Quantum Qubit Measurement AnalysisQuantum qubit measurement and state transition analysis methods for circuit QED systems, including fluxonium qubits, measurement-induced transitions, and multi-photon resonance analysis. Activates on: qubit measurement, fluxonium analysis, quantum readout, measurement-induced transition, quantum bit, 量子比特, 量子测量, fluxonium qubit.Votes: 0GitHub stars: 3
- Quantum Qubit RoutingQubit mapping and routing methodology for quantum compilation. Uses position graph abstraction and memoized heuristic evaluation to scale SABRE-based routing on TI-QCCD and other heterogeneous quantum architectures. Covers position graph abstraction, relative move scoring, memoized congestion resolution, and architecture-aware compilation. Use when: designing quantum compilers, implementing qubit routing/mapping, optimizing TI-QCCD shuttling, scaling SABRE algorithms, or building architecture...Votes: 0GitHub stars: 3
- Quantum Rare Event SamplingQuantum algorithm for rare-event discovery and sampling methodology — achieving optimal quantum scaling with rarity threshold, quadratic speedup for heavy-tailed systems, and polynomial speedup for stationary stochastic processes.Votes: 0GitHub stars: 3
- Quantum Reference Free GeneralizationTheoretical framework for understanding generalization in quantum machine learning. Addresses the fundamental problem of assigning different labels to locally indistinguishable quantum states through reference-based learning.Votes: 0GitHub stars: 3
- Quantum Reliability PathwaysElectromagnetic-to-architecture reliability prediction methodology for superconducting quantum processors. Use when: (1) predicting quantum processor reliability from physical layout and electromagnetic design, (2) analyzing how design distortion modifies effective Hamiltonian and mediated connectivity, (3) estimating architectural reliability early in quantum chip design, (4) connecting electromagnetic design choices to execution-level behavior, (5) EPAR framework for quantum architectural r...Votes: 0GitHub stars: 3
- Quantum Renormalization GoursatQuantum renormalization group flow methodology for 1D mixed states using C*-Hopf algebra representations. Perturbs renormalization fixed points with on-site noise quantum channels, coarse-grains iteratively, and describes effective flows via quantum Goursat lemma. Connects renormalization, topological order, and quantum information theory. Activation: quantum renormalization flow, Goursat lemma quantum, topological boundary states, C* Hopf algebra, noise channel coarse graining, mixed state RGVotes: 0GitHub stars: 3
- Quantum Reservoir ComputingQuantum Reservoir Computing (QRC) framework covering chaotic dynamics prediction, thermodynamic limits, symmetry exploitation, amplitude encoding protocols, hybrid architectures, operating band localization, and Kerr feedback superiority. Use for designing energy-efficient QRC systems, aligning symmetries across QRC interfaces, and selecting optimal operating regimes.Votes: 0GitHub stars: 3
- Quantum Reservoir ThermodynamicsNon-equilibrium thermodynamic framework for Quantum Reservoir Computing (QRC). Links predictive performance to microscopic energetic costs, identifies quantum critical resonance as computational peak source, and provides Landauer bound for continuous temporal processing. Use when analyzing QRC energy efficiency, designing quantum neuromorphic hardware, or optimizing temporal prediction under energy constraints.Votes: 0GitHub stars: 3
- Quantum Resistant Network ArchitecturePost-quantum cryptography network architecture methodology covering PQC primitives, protocols (TLS, SSH), and best practices for network security migration. Addresses architectural consequences of post-quantum transition for networked systems including mobile networks, industrial IoT, and large-scale infrastructure. Use when designing post-quantum network security, migrating to PQC protocols, or evaluating quantum-resistant network architectures.Votes: 0GitHub stars: 3
- Quantum Riccati SolverQuantum algorithms for solving algebraic Riccati equations via Riesz projectors and quantum singular value transformations (QSVT). Applications to quantum chemistry RPA and coupled-cluster theory. Activation: quantum riccati, quantum nonlinear matrix, quantum chemistry algorithm, RPA quantum, algebraic riccati equation quantum, quantum singular value transformation chemistry.Votes: 0GitHub stars: 3
- Quantum Ring Allreduce Distributed LearningQuantum ring all-reduce methodology for distributed machine learning training — 2x bandwidth reduction via superdense coding with information-theoretic privacy guarantees. Achieves ε-secure aggregation through verified GHZ entanglement. Provides exponential separation in communication complexity for gradient conflict detection (Ω(√P) bits vs O(ε⁻² log P) qubits).Votes: 0GitHub stars: 3
- Quantum Rl Dynamic PortfolioQuantum Reinforcement Learning (QRL) for dynamic portfolio optimization using Variational Quantum Circuits (VQC). Provides quantum analogues of Deep Deterministic Policy Gradient (DDPG) and Deep Q-Network (DQN) for sequential portfolio allocation. Achieves competitive performance vs classical deep RL with fewer trainable parameters. Use when: (1) implementing quantum RL for finance, (2) designing VQC-based trading agents, (3) comparing quantum vs classical RL for portfolio optimization, (4) b...Votes: 0GitHub stars: 3
- Quantum Rl Process SynthesisQuantum-enhanced reinforcement learning methodology for process synthesis problems. Formalizes process design as MDP and introduces quantum RL algorithms with state encoding to decouple qubit requirements from problem size. Covers quantum DQN, state encoding, and classical-quantum benchmarking patterns.Votes: 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 Safe Blockchain InfrastructureArchitecture framework for building post-quantum secure blockchain infrastructure for embodied AI and cyber-physical-social systems. Covers PQC integration, interoperability patterns, trustworthy data provenance, and incentive-compatible decentralized data economies. Use when designing quantum-safe blockchain architectures, planning PQC migration for distributed systems, or building data provenance infrastructure for AI agents.Votes: 0GitHub stars: 3
- Quantum Safe Pqc DeploymentPost-quantum cryptography (PQC) production deployment methodology. Hybrid-by-default architecture bridging classical and post-quantum security for production systems. Covers ML-KEM/ML-DSA migration, TLS integration, and incremental deployment strategies.Votes: 0GitHub stars: 3