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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Pauli String Universality ConditionsNecessary and sufficient conditions for universal quantum gates using Pauli strings. Provides a Lie algebraic framework (su(2^n) generation criterion) for determining when a set of Pauli string Hamiltonians achieves universal quantum computation. arXiv:2606.12096Votes: 0GitHub stars: 3
- Pauli Structured PreconditioningPauli-structured preconditioning methodology for quantum linear system solvers. Based on arXiv:2606.01733 — reduces normalization overhead via Pauli expansion regrouping.Votes: 0GitHub stars: 3
- Pce Quantum Portfolio OptimizationScalable Variational Quantum Optimization via Pauli Correlation Encoding (PCE) methodology for large-scale combinatorial optimization problems, particularly power demand portfolio optimization. Uses expectation values of Pauli correlation operators to represent binary variables with compact qubit representations.Votes: 0GitHub stars: 3
- Penalty Free Quantum Annealing PipelineMethodology for direct quantum annealer portfolio optimization without cardinality penalty encoding. Removes the penalty entirely from QUBO formulation, samples objective-only QUBO on hardware, and enforces cardinality classically through deterministic feasibility projector.Votes: 0GitHub stars: 3
- Penalty Free Quantum OptimizationPenalty-free quantum optimization methodology — replacing quadratic penalty terms in QAOA/quantum annealing with conflict graph reformulation and independent set mixers. Maps constrained combinatorial problems to maximum independent set (MIS) on conflict graphs, using MIS-specific mixer Hamiltonians that preserve feasibility throughout the quantum evolution. Eliminates penalty parameter tuning entirely. Applicable to protein folding, scheduling, graph coloring, and any problem with hard struc...Votes: 0GitHub stars: 3
- Permutation Asymmetry Bell TestsMethodology for exploiting permutation asymmetry in randomized Bell tests to enhance nonlocality detection and reveal measurement-choice correlations.Votes: 0GitHub stars: 3
- Permutation Invariant Qec RecoveryQuantum Error Recovery (QER) methodology for permutation-invariant (PI) quantum codes under correlated noise. Uses channel-aware recovery maps with tunable PI code parameters to achieve fidelity beyond noise-independent QEC. Covers CAD code family construction, coherent recovery circuit compilation, and low-overhead implementation.Votes: 0GitHub stars: 3
- Photon Heralded Quantum Error CharacterizationAnalytic perturbative framework for characterizing small Markovian errors in probabilistic, photon-heralded quantum operations between non-interacting emitters. Extends the Zero-Photon-Generation (ZPG) framework with closed-form perturbative solutions for process matrices and Pauli error weights up to leading order. Bridges physical imperfections to abstract Pauli noise models for fault-tolerant quantum computing. Use when: designing photon-heralded gates, characterizing quantum error channel...Votes: 0GitHub stars: 3
- Physically Motivated Quantum AnsatzDesign physically motivated variational ansätze for open quantum systems using unitary coupled cluster approaches adapted for Lindblad dynamics. Addresses barren plateau problems in variational quantum algorithms by incorporating physical structure into ansatz design.Votes: 0GitHub stars: 3
- Physics Guided Quantum Learning[TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]Votes: 0GitHub stars: 3
- Physics Informed Qaoa ElectromagneticsPhysics-Informed QAOA methodology for electromagnetic optimization, embedding mutual coupling into QUBO formulations for Reconfigurable Intelligent Surfaces (RIS). Covers Ising interaction model selection, NISQ hardware feasibility tradeoffs, and sparse Hamiltonian design.Votes: 0GitHub stars: 3
- Piston Control Two Ion QuantumInverse-engineering methodology for piston operations in trapped-ion quantum devices. One ion serves as classical piston driven by Coulomb interaction with quantum-controlled ion. Stationary state determined self-consistently. Inverse-engineering protocols enable precise control of classical ion motion. Provides route toward controlled piston dynamics in microscopic quantum devices.Votes: 0GitHub stars: 3
- Post Quantum Iot HealthcarePost-quantum cryptography (PQC) migration framework for Internet of Medical Things (IoMT) with edge-native federated learning securityVotes: 0GitHub stars: 3
- Post Quantum Pharmacovigilance PipelinePost-quantum secure pharmacovigilance data pipeline methodology using ML-KEM-768, ML-DSA-65, HKDF-SHA-256, and AES-256-GCM. Educational prototype for healthcare data pipeline security in the post-quantum era. Covers component architecture, file format support, and performance benchmarking.Votes: 0GitHub stars: 3
- Post Quantum Secure PharmacovigilanceNIST-standard PQC migration (ML-KEM + ML-DSA) for pharmacovigilance and healthcare data systems. Use when designing post-quantum security for adverse event reporting, clinical observation systems, or any healthcare pipeline handling sensitive patient data that needs quantum-resistant cryptography.Votes: 0GitHub stars: 3
- Pubo Mst FalqonPUBO formulation for Minimum Spanning Tree using FALQON quantum optimization methodology. Reformulates MST as Polynomial Unconstrained Binary Optimization without auxiliary variables, reducing qubit requirements. Use when solving graph optimization problems (MST, OPF classifiers, network design) on quantum or quantum-inspired hardware, especially when qubit count is constrained. Applies to quantum machine learning pipelines needing efficient combinatorial optimization, graph-based classifiers...Votes: 0GitHub stars: 3
- Q Dasc Safe Quantum ControlQ-DASC methodology for safe deployment of variational quantum circuit policies in physics-constrained control systems, with certified classical safety layers that handle model misspecification.Votes: 0GitHub stars: 3
- Q Ready Quantum FeasibilityQ-READY methodology for predictive feasibility assessment of hybrid quantum-classical applications. Use when evaluating whether a computational problem can benefit from quantum acceleration, designing hybrid quantum-classical workflows, or assessing quantum readiness of software systems.Votes: 0GitHub stars: 3
- Qaoa Cvar Portfolio BenchmarkHardware benchmarking methodology for comparing quantum portfolio optimization algorithms (HE-VQNN vs WS-QAOA) on NISQ devices, focusing on CVaR (Conditional Value at Risk) portfolio optimization and the expressibility-coherence trade-off.Votes: 0GitHub stars: 3
- Qaoa Feasibility Penalty SchedulingFeasibility-driven QAOA with penalty scheduling. Introduces Λ-lr-QAOA (per-penalty linear-ramp schedules) and piecewise-ramp QAOA (two-segment piecewise schedules) for constrained optimization. Promotes penalty weights from external hyperparameters to internal variational parameters. Activation: feasibility-driven QAOA, penalty scheduling, constrained QAOA, Λ-lr-QAOA, piecewise-ramp QAOA, MWIS optimizationVotes: 0GitHub stars: 3
- Qaoa Manifold OptimizationRiemannian manifold optimization techniques for enhancing QAOA performance on NISQ devices. Leverages intrinsic geometric structure to address nonconvexity of QAOA objective function and overcome challenges with traditional gradient descent optimizers. Use when optimizing QAOA parameters, dealing with barren plateaus, or improving quantum optimization convergence.Votes: 0GitHub stars: 3
- Qaoa Qrl Vehicle RoutingHybrid QAOA-QRL methodology for vehicle routing optimization — integrating QAOA mixing/cost Hamiltonian layers into reinforcement learning policy networks for combinatorial logistics optimization.Votes: 0GitHub stars: 3
- Qaoa Semiclassical Sk Analysis**Source**: Dries Sels & Flaviano Morone, "Absence of quantum advantage for approximate spin glass optimization" (arXiv:2607.08708, July 2026)Votes: 0GitHub stars: 3
- Qaoa Shot ScalingStatistical analysis methodology for QAOA measurement shot budget allocation. Derives sufficient conditions on shot requirements for cost estimation and SGD convergence. Reveals counterintuitive scaling where total shot budget decreases with instance size for specific graph classes.Votes: 0GitHub stars: 3
- Qaoa Xy Mixers PortfolioConstraint-preserving QAOA formulation using Dicke state initialization and XY-mixer Hamiltonian for direct indexing portfolio optimization. Use when: implementing QAOA with hard cardinality constraints; designing constraint-preserving quantum ansatzes; mitigating barren plateaus via Trotterized initialization; comparing quantum vs classical portfolio optimization (SA, HRP); Direct Indexing with ESG constraints. Keywords: qaoa, xy-mixer, dicke state, portfolio optimization, constraint-preserv...Votes: 0GitHub stars: 3
- Qcmi Channel CodingQuantum Conditional Mutual Information (QCMI) methodology for establishing optimal quantum communication rates with assisted correlation. Shows the optimal rate for establishing quantum correlation between two parties, assisted by a third system, is given by half the QCMI.Votes: 0GitHub stars: 3
- Qcnn Rough Path SignatureHybrid quantum-classical architecture combining path signature kernels with QCNN for time series classification, addressing time reparameterization invariance. (arXiv: 2607.07634)Votes: 0GitHub stars: 3
- Qcnn Rough Path SignaturesQuantum Convolutional Neural Network with Rough Path Signature Kernels for time series classification. Hybrid quantum-classical architecture using path signatures to handle time reparameterization invariance.Votes: 0GitHub stars: 3
- Qcnn Surrogate ModelingQuantum Convolutional Neural Network (QCNN) methodology for surrogate modeling of complex physical systems. Uses quantum convolutional and pooling layers with Hamiltonian-inspired encoding, benchmarked across simulators and real quantum hardware with error mitigation.Votes: 0GitHub stars: 3
- Qcnn With Rough Path Signature KernelsTime series analysis plays a vital role across a wide range of scientific and engineering domains but poses substantial computational challenges. A major difficulty arises from the time reparameteriza. Based on arXiv:2607.07634.Votes: 0GitHub stars: 3
- Qfi Entanglement RobustnessInformation-geometric framework for analyzing entanglement robustness using quantum Fisher information (QFI). Establishes bounds on concurrence reduction caused by parameter uncertainty in entanglement generation. Use when analyzing quantum entanglement stability, quantum network reliability, quantum sensing precision, or parameter-dependent quantum operations. Activation: quantum Fisher information, entanglement robustness, concurrence bounds, quantum network reliability, quantum sensing pre...Votes: 0GitHub stars: 3
- Qldpc Breakeven DemoBreakeven demonstration methodology for quantum low-density parity-check (qLDPC) codes on trapped-ion quantum computers. Design, implement, and benchmark qLDPC error correction with OMG architecture for mid-circuit measurement and reset.Votes: 0GitHub stars: 3
- Qldpc Breakeven EvaluationEvaluation framework for quantum LDPC codes demonstrating breakeven performance across code families on trapped-ion hardware.Votes: 0GitHub stars: 3
- Qml Feature EncodingQuantum Machine Learning feature encoding methodology — three-axis cost-expressivity-robustness taxonomy, depth-fidelity bounds under NISQ decoherence, unified trainability analysis, and five-regime decision framework for selecting encoding strategies on real hardware.Votes: 0GitHub stars: 3
- Qml Generalization Nisq EraGeneralization error bounds for quantum machine learning in NISQ era. Systematic mapping study covering quantum hardware, datasets, optimization techniques, and noise-aware generalization theory. Activation: generalization bound, NISQ QML, quantum ML reliability, noise-aware QML, QML validation, quantum learning theory, NISQ generalization.Votes: 0GitHub stars: 3
- Qml Transfer LearningHybrid quantum-classical transfer learning methodology showing 15 percentage point accuracy improvement on spam classification (66%→81%) when transferring from COVID-19 sentiment analysis. Demonstrates enhanced generalization of QML models through transfer learning across NLP tasks. arXiv:2607.01943Votes: 0GitHub stars: 3
- Qmt Qnn Training StabilityQuantum Measurement Temperature (QMT) methodology for mitigating measurement-induced training instability in hybrid QNN classifiers. Introduces learnable scaling parameter to rescale quantum measurement outputs, improving gradient magnitude and preventing training collapse.Votes: 0GitHub stars: 3
- Qnn Clinical Data ImputationScalable on-hardware training of Quantum Neural Networks for clinical data imputation methodology - demonstrates practical quantum machine learning for handling missing data in clinical datasets.Votes: 0GitHub stars: 3
- Qnn Hyperparameter Stress TestMethodology for stress-testing variational quantum neural networks on complex physical datasets, with emphasis on hyperparameter optimization, expressivity enhancement, and classical baseline comparison.Votes: 0GitHub stars: 3
- Qnrl Quantum Native Reinforcement LearningQuantum-Native Reinforcement Learning (QnRL) methodology — distributional RL framework that learns conditional distributions in Hilbert space via superimposed and entangled quantum states using the Quantum Amplitude Kickback (QuAK) algorithm. Achieves up to 82.9% higher evaluation scores with 94.3% fewer parameters compared to classical RL baselines.Votes: 0GitHub stars: 3
- Qnrl Quantum Native RlQuantum-Native Reinforcement Learning (QnRL) methodology for distributional RL using quantum state representationsVotes: 0GitHub stars: 3
- Qolumbina Quantum Testing BenchmarkQolumbina benchmark infrastructure for controlled Quantum Software Testing (QST) experiments on scalable quantum programs — curates 40 programs from open-source repos with systematic selection, refactoring, specifications, and standardized interfaces.Votes: 0GitHub stars: 3
- Qpipe Agentic Quantum Code GenLLM-based multi-agent architecture for autonomous quantum application generation from natural language requirements. Use when building agentic systems for quantum software engineering, automated quantum code generation, NL-to-quantum workflows, or quantum test optimization pipelines. Activation: qpipe, agentic quantum code generation, LLM quantum application, natural language quantum workflow, quantum test optimization agent, multi-agent quantum compilation, autonomous quantum code review.Votes: 0GitHub stars: 3
- Qpredsgg Hybrid Quantum PredicateHybrid quantum predicate classifier for long-tailed scene graph generation. Replaces classical predicate head with QP-Head using amplitude embedding + strongly entangling layers.Votes: 0GitHub stars: 3
- Qst Flow Quantum TomographyQST-Flow framework for continuous-variable quantum state tomography using flow-based generative modeling. Models Husimi-Q functions with QST-QFlow and Wigner functions with QST-WFlow as difference of normalized flows. Use when working with non-Gaussian bosonic states, phase-space tomography, or quantum state reconstruction.Votes: 0GitHub stars: 3
- Qt Puf Quantum Tunneling IomtQT-PUF: Quantum tunneling leakage-based physical unclonable function for implantable IoMT devices. Gate leakage PUF using process-induced CMOS variations with differential readout circuit. Entropy 0.9999998, power 96.04 nW/bit. Use when designing quantum-inspired hardware security for medical devices, implantable IoMT authentication, ultralow-power PUF circuits, or CMOS process-variation-based cryptographic primitives.Votes: 0GitHub stars: 3
- Quantum Ai PatternsReusable research patterns at the intersection of quantum computing and artificial intelligence. Use when analyzing quantum machine learning papers, designing hybrid quantum-classical systems, or extracting architectural patterns from quantum-AI research. Covers QNN design, distributed quantum computing, AI-assisted error correction, and continuous-time quantum models. Triggers: quantum machine learning, QNN, quantum neural network, hybrid quantum-classical, quantum AI patterns, distributed q...Votes: 0GitHub stars: 3
- Quantum Analogue Cloud FormalismQuantum-analogue cloud-function formalism for modeling supraliminal information processing in large-scale brain networks. Combines neural field theory with Schrodinger-type equations for modeling conscious perception and decision-making phenomena like change-of-mind.Votes: 0GitHub stars: 3
- Quantum Api Drift BenchmarkBenchmark for measuring API drift in LLM-generated quantum code across successive SDK versions. Evaluates version fidelity, cross-version compatibility, failure modes, and documentation-guided repair. Instantiated with Qiskit v0.43, v1.3, v2.0. Activation: quantum SDK version testing, LLM quantum code evaluation, API drift benchmark, quantum code generation fidelity, Qiskit version compatibility, 量子API漂移Votes: 0GitHub stars: 3
- Quantum Autoencoder Anomaly DetectionCompression-driven anomaly detection methodology using quantum autoencoders (QAE) for brain MRI and medical imaging. Maps data to quantum states via angle encoding, trains variational encoder-decoder to compress normal data while discarding to trash qubits. Anomaly scores = compression resistance. Use when building quantum ML pipelines for medical anomaly detection.Votes: 0GitHub stars: 3