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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Quantum Federated Healthcare CommunicationCommunication-efficient Quantum Federated Learning (QFL) methodology for privacy-sensitive healthcare. Introduces Hybrid QFL architecture with light-cone feature selection and dynamic centralized/decentralized aggregation switching. Use when designing quantum-secure distributed learning systems for medical data.Votes: 0GitHub stars: 3
- Quantum Federated Learning SecurityCircuit-level backdoor detection methodology for Quantum Federated Learning (QFL) systems. Identifies malicious circuit patterns in variational quantum circuits during federated training. Use when: (1) securing QFL systems, (2) detecting quantum circuit backdoors, (3) federated quantum computing security, (4) variational circuit integrity verification, (5) quantum ML trustworthiness assessment.Votes: 0GitHub stars: 3
- Quantum Fermionic Shadows StatisticsMode-independent sample complexity for fermionic classical shadows. Improves worst-case bound from O(√n log n) to O(η log η) using harmonic analysis on AIII symmetric space.Votes: 0GitHub stars: 3
- Quantum Feshbach EnginesQuantum Feshbach engine methodology — optimization framework for high-efficiency quantum thermodynamic cycles using trapped Bose-Einstein condensates with Feshbach resonance tuning. Use when designing quantum heat engines, optimal control of quantum many-body systems, or quantum thermodynamics protocols.Votes: 0GitHub stars: 3
- Quantum Fidelity EstimationQuantum state fidelity estimation methodology with optimal sample complexity bounds. Covers O(r²/ε²) upper and Ω(r/ε²) lower bounds for rank-r reference states, tolerant certification, and quantum query complexity implications. Use when estimating quantum state fidelity, designing certification protocols, or analyzing quantum sample complexity.Votes: 0GitHub stars: 3
- Quantum Finance AnalysisQuantum computing applications in finance and economics. Use when analyzing quantum portfolio optimization, quantum Monte Carlo for risk, quantum game theory, option pricing with quantum algorithms. Keywords: quantum finance, quantum portfolio, quantum Monte Carlo, quantum risk, quantum economics, quantum game theory, QAOA portfolio, quantum annealing finance.Votes: 0GitHub stars: 3
- Quantum Finance Computation StackFinancial computation stack framework for evaluating quantum computing applications across five connected domains. Based on arXiv:2604.08180 (134-page review) plus 2026 hot-starting and benchmark papers.Votes: 0GitHub stars: 3
- Quantum Finance Portfolio量子计算在金融组合优化中的应用。涵盖 QUBO建模、量子退火、QRNG增强Monte Carlo、VaR/CVaR风险估计、QAOA Mixer选择、两步QAOA优化、混合量子优势审计、QRL动态组合优化、QAOA+ZNE误差缓解、qReduMIS递归量子-经典组合优化。触发词：量子金融、quantum portfolio、量子组合优化、quantum annealing finance、QRNG VaR、QAOA mixer、hybrid quantum audit、D-Wave hybrid、量子优势审计、quantum contribution measurement、QRL、QDDPG、QDQN、ZNE、zero noise extrapolation、carbon credit portfolio、qReduMIS、frozen nodes、QuantinuumVotes: 0GitHub stars: 3
- Quantum FinanceQuantum computing applications in finance: portfolio optimization, option pricing, risk management, financial simulations, and quantum economics using quantum algorithms (QAOA, quantum annealing, quantum Monte Carlo, amplitude estimation, entangled neural traders). Use for quantum finance research, NISQ-era financial applications, quantum advantage analysis in derivatives/derivatives pricing, and economic action constants.Votes: 0GitHub stars: 3
- Quantum Financial Time SeriesQuantum LSTM and Quantum Reservoir Computing for financial time series forecasting - hybrid quantum-classical architectures for market prediction.Votes: 0GitHub stars: 3
- Quantum Fingerprinting CommunicationExperimental demonstration of quantum advantage in communication complexity using quantum fingerprinting for Euclidean distance computation. Uses coherent state pulses in simultaneous message passing (SMP) model. Shows quantum advantage in transmitted information for input size 10^8 with amplitude modulation encoding and superconducting nanowire single-photon detectors. Activation: quantum fingerprinting, communication complexity, Euclidean distance, SMP model, coherent states, quantum advant...Votes: 0GitHub stars: 3
- Quantum Fisher Information DualityQuantum Fisher Information (QFI) duality methodology for distributed quantum sensing — establishing fundamental trade-offs between sensing precision and parameter privacy.Votes: 0GitHub stars: 3
- Quantum Framework Agnostic DesignDesign framework-agnostic quantum machine learning (QML) systems that eliminate vendor lock-in. Use when building QML solutions that need to work across multiple quantum computing platforms (IBM Quantum, Amazon Braket, Azure Quantum, IonQ, Rigetti), or when designing quantum neural networks for cross-framework compatibility. Covers unified computational graphs, hardware abstraction layers, and multi-framework export strategies. Activation: framework-agnostic QML, quantum vendor lock-in, QML i...Votes: 0GitHub stars: 3
- Quantum Game Theory EconomicsQuantum game theory applications in economics and decision science. Use when analyzing quantum strategies in games, Nash equilibrium in quantum games, quantum entanglement in decision theory, quantum coins, quantum auctions, quantum bargaining. Keywords: quantum game theory, quantum economics, Nash equilibrium quantum, quantum strategy, quantum decision theory, quantum games, Bell inequality economics, quantum auction, quantum bargaining, 量子博弈, 量子经济学.Votes: 0GitHub stars: 3
- Quantum Gan BenchmarkingControlled benchmarking methodology for evaluating quantum generative models in medical image augmentation.Votes: 0GitHub stars: 3
- Quantum Gauge Error CorrectionFramework for understanding gauge theories as quantum error-correcting codes, bridging lattice QED, stabilizer codes, and quantum reference frames. Use when analyzing quantum error correction, gauge symmetry, information-theoretic significance of gauge redundancy, or designing fault-tolerant quantum systems with gauge structure.Votes: 0GitHub stars: 3
- Quantum Gaussian State LearningSample-optimal learning of bosonic Gaussian quantum states. Provides sharp bounds on sample complexity for characterizing unknown n-mode Gaussian states: Omega(n^3/epsilon^2) for Gaussian measurements, Omega(n^2/epsilon^2) for arbitrary measurements. Proves non-Gaussian measurements required for optimal learning of passive Gaussian states. Use when: quantum state tomography, bosonic Gaussian states, quantum learning theory, sample complexity bounds, quantum sensing benchmarking, Wigner distri...Votes: 0GitHub stars: 3
- Quantum Genetic Negative SelectionQuantum Genetic Negative Selection Algorithm (QGNSA) methodology for anomaly detection using quantum-enhanced evolutionary optimizationVotes: 0GitHub stars: 3
- Quantum Geometric Statistical Analysis量子-几何-统计学交叉领域分析方法。整合量子概率、Fisher信息几何、张量网络(Belief Propagation)、拓扑数据分析在量子系统中的应用。用于量子系统的统计建模、几何分析、拓扑序学习、多体量子系统计算。关键词：quantum geometry, quantum statistics, Fisher information, tensor network, topological order, quantum probability, belief propagation, quantum circuitsVotes: 0GitHub stars: 3
- Quantum Geometry Topology ResearchResearch skill for quantum-geometry-topology interdisciplinary analysis. Search arxiv for quantum geometry/topology papers, import to knowledge graph (kg.db), analyze with PageRank/Louvain, extract reusable patterns. Activation: quantum geometry research, quantum topology analysis, geometry-informed quantum computing, quantum statistical analysis.Votes: 0GitHub stars: 3
- Quantum Global Variational Learning QecQuantum Global Variational Learning for Quantum Error Correction methodology — quantum neural network with global structure reducing unitary matrices in QEC circuits, achieving 97% training time reduction, 25% completion rate improvement, and 15% fidelity increase under noise. Applicable to quantum error correction, quantum neural network design, variational quantum algorithms, training efficiency optimization.Votes: 0GitHub stars: 3
- Quantum Graph Machine Learning ModelsGeometric Quantum Machine Learning (GQML) design toolbox for graph problems — comprehensive characterization of constituents for n-node-graph → n-qubit-state encoding; enables hybrid classical-quantum integration, generalizes known GQML models (extending expressivity at near-zero cost), and supports straightforward classical pre-training; validated numerically.Votes: 0GitHub stars: 3
- Quantum Ground State Preparation BenchmarkBenchmark methodology for comparing quantum ground state preparation algorithms (cooling, adiabatic, QAOA) under realistic noise conditions. Provides phase-dependent performance analysis using quadratic fermionic Hamiltonians with depolarizing noise.Votes: 0GitHub stars: 3
- Quantum Growth ModelingQuantum growth modeling methodology using parameterized quantum circuits, EWL quantum games, and Dirac-Hamiltonian economic simulation. Applies quantum computing to economic growth, innovation dynamics, capital accumulation, and policy recommendation systems. Use when: analyzing economic growth with quantum methods, modeling innovation ecosystems as quantum systems, implementing quantum game theory for strategic decision-making, simulating capital trajectories with quantum Hamiltonians, build...Votes: 0GitHub stars: 3
- Quantum Healthcare Foundation ModelsQuantum foundation models for healthcare and biomedical applications. Analyze and develop quantum-enhanced foundation models for drug discovery, medical imaging, and healthcare diagnostics. Covers FeNNx-Bio1 (drug discovery), Neural Operator Quantum State (quantum dynamics), and quantum foundation model architectures for medical AI. Use when working with quantum foundation models in healthcare, quantum drug discovery, quantum medical AI, or hybrid quantum-classical foundation architectures.Votes: 0GitHub stars: 3
- Quantum Healthcare PatternsReusable research patterns for quantum computing applications in healthcare, medical diagnosis, and clinical decision-making. Covers quantum machine learning for digital health, quantum imaging (QIGL), personalized medicine, and bioinformatics AI evaluation. Use when researching quantum-classical hybrid methods for medical applications, evaluating QML vs classical ML for clinical tasks, or analyzing quantum generative models for medical image synthesis.Votes: 0GitHub stars: 3
- Quantum Healthcare ResearchResearch methodology for quantum computing applications in healthcare and medicine using knowledge graph analysis. Covers: (1) searching kg.db for quantum+medical papers via vector similarity and keyword search, (2) PageRank-based importance ranking of research papers, (3) Louvain community detection for identifying research clusters, (4) extracting hybrid quantum-classical patterns for disease classification, drug discovery, and medical imaging. Use when researching quantum healthcare topics...Votes: 0GitHub stars: 3
- Quantum Hilbert Prototype LearningQuantum Hilbert Space prototype learning methodology using Matrix Product States (MPS). Encodes class prototypes as generative MPS in quantum Hilbert space for classification and clustering via geometric quantum state measures. Covers quantum attraction effect and prototype-based dimensionality reduction.Votes: 0GitHub stars: 3
- Quantum Histopathologic Cancer DetectionQuantum algorithms for histopathologic cancer detection using configurable dual-gradient CSWAP circuits (DG-CSWAP) and hardware-efficient destructive swap circuits (DG-DST). Covers NISQ-era quantum image classification with noise mitigation pipelines. From arXiv:2606.21752 (Goyal et al., 2026).Votes: 0GitHub stars: 3
- Quantum Histopathology Cancer DetectionQuantum algorithms for histopathologic cancer detection on real hardware (NISQ). Covers DG-CSWAP and DG-DST circuits, NISQ mitigation pipeline, and practical QPU validation strategies.Votes: 0GitHub stars: 3
- Quantum Hyperdimensional Computing QhdcQuantum Hyperdimensional Computing (QHDC) is a foundational paradigm for quantum neuromorphic architectures introduced in arXiv:2511.12664. It demonstrates that the core operations of classical Hyperdimensional Computing (HDC) — a brain-inspired model — map with remarkable elegance to the native operations of a quantum computer.Votes: 0GitHub stars: 3
- Quantum Hyperdimensional ComputingQuantum-enhanced Hyperdimensional Computing (HDC) framework using quantum binding operations and SuperClass Construction for robust, efficient high-dimensional vector space computation.Votes: 0GitHub stars: 3
- Quantum Information Protocol AnalyzerAnalyze quantum information protocols (QKD, quantum cryptography, quantum communication) from research papers. Extract protocol design patterns, security analysis methods, and implementation guidelines. Triggered by: quantum protocol, QKD analysis, quantum cryptography, quantum communication protocol, 量子协议分析, quantum information security.Votes: 0GitHub stars: 3
- Quantum Informed Portfolio QredumisqReduMIS: recursive hybrid quantum-classical algorithm for portfolio diversification via Maximum Independent Set on asset correlation graphs. Uses QAOA measurements to identify frozen nodes, guiding provably optimal classical reductions. Validated on Quantinuum 98-qubit trapped-ion Helios system. Activation: portfolio optimization, quantum portfolio, QAOA finance, qReduMIS, trapped-ion portfolio, maximum independent set, asset correlation graph, quantum finance pipeline, MIS portfolio, frozen...Votes: 0GitHub stars: 3
- Quantum Inspired Evidence ReasoningQuantum-inspired trace-augmented evidence selection methodology for improving reasoning accuracy in specialized domains. Uses quantum probability principles to weight evidence coherence across chain-of-thought traces, reducing majority-vote errors in evidence-intensive reasoning tasks. Use when improving LLM reasoning on evidence-heavy domains, designing trace-augmented aggregation, or applying quantum probability to evidence selection.Votes: 0GitHub stars: 3
- Quantum Inspired OptimizationQuantum-Inspired Evolutionary Optimization (QIEO) for non-convex ML optimization. Uses quantum superposition-inspired probability amplitudes, quantum rotation gates for distribution updates, and quantum interference for exploration/exploitation balance. Use when: quantum-inspired optimization, QIEO, non-convex optimization, global search evolutionary, escaping local minima, 量子启发优化, 量子进化优化.Votes: 0GitHub stars: 3
- Quantum Kernel Advantage MedicalQuantum kernel advantage methodology for medical imaging classification under class imbalance. Use when: (1) Evaluating QSVM vs classical SVM on medical datasets with severe class imbalance, (2) Comparing quantum and classical kernels using frozen foundation model embeddings, (3) Designing two-tier fair comparison frameworks for quantum ML, (4) Analyzing kernel eigenspectrum for effective rank, (5) Addressing classical kernel collapse on minority class prediction. Based on arXiv:2604.24597.Votes: 0GitHub stars: 3
- Quantum Kernel AdvantageQuantum kernel advantage methodology for medical foundation model embeddings. Uses Quantum Support Vector Machines (QSVM) with frozen medical foundation model embeddings for binary medical classification tasks. Provides evidence of quantum kernel advantage over classical kernels on medical imaging data. Use when: medical image classification with quantum kernels, QSVM for healthcare, quantum advantage demonstration, medical foundation model evaluation, MIMIC-CXR classification, quantum-classi...Votes: 0GitHub stars: 3
- Quantum Kernel Medical EmbeddingsQuantum kernel methods for medical AI embeddings and foundation model enhancement — leveraging quantum Hilbert space geometry for medical image/text feature fusion.Votes: 0GitHub stars: 3
- Quantum Knowledge GraphQuantum-enhanced knowledge graph integration using QNLP, quantum superposition/entanglement for semantic relationship modeling, and encoding KGs as quantum states for quantum computing tasks.Votes: 0GitHub stars: 3
- Quantum Koopman AlgorithmsQuantum Koopman Algorithms (QKAs) framework for simulating linear quantum and nonlinear classical system dynamics via observable-space methods. Includes Dynamic-QKA for initial-value problems and Spectral-QKA for eigenvalue analysis. arXiv: 2605.19054.Votes: 0GitHub stars: 3
- Quantum Latent Gan BenchmarkControlled benchmark methodology for evaluating quantum generative models in medical imaging augmentation. Establishes rigorous evaluation framework comparing quantum vs classical generators under matched parameter budgets, multiple random seeds, and paired significance testing. Use when evaluating quantum generative augmentation for medical images, designing controlled benchmarks for quantum vs classical model comparison, or assessing data augmentation quality in low-data regimes. Covers: KL...Votes: 0GitHub stars: 3
- Quantum Ldpc Breakeven DemonstrationBreakeven demonstration of quantum low-density parity-check (qLDPC) codes using trapped-ion quantum computers. Demonstrates nine different QEC codes on a single device, achieving breakeven performance with 4 logical qubits encoded into 18 physical qubits.Votes: 0GitHub stars: 3
- Quantum Learning Privacy GeneralizationUnified information-theoretic framework for analyzing the interplay between stability, privacy, and generalization in quantum learning algorithms.Votes: 0GitHub stars: 3
- Quantum Learning Theory CvQuantum learning theory framework for continuous-variable (CV) bosonic systems. Covers information extraction efficiency bounds, CV quantum state learning, and bosonic quantum information protocols. Use when: analyzing quantum learning bounds, designing CV quantum ML systems, or studying bosonic quantum information extraction.Votes: 0GitHub stars: 3
- Quantum Learning TheoryQuantum learning theory methodology — sample complexity analysis for continuous-variable (CV) and bosonic quantum systems. Covers learning non-Gaussian states, Gaussian state tomography, non-Gaussianity impact on learning performance, Gaussianity testing, and efficient Gaussian process learning. Use when: quantum learning theory, continuous-variable quantum systems, bosonic quantum machine learning, quantum state tomography, sample complexity analysis, CV state learning, Gaussian state identi...Votes: 0GitHub stars: 3
- Quantum Linear Algebra Block EncodingDesign and implement quantum algorithms using block encoding methodology for quantum linear algebra. Block encoding embeds a matrix as a sub-block of a larger unitary, enabling quantum singular value transformation (QSVT), quantum linear system solvers, and Hamiltonian simulation. Use when implementing quantum linear algebra algorithms, building matrix arithmetic circuits, or working with QSVT/HHL-style algorithms. Trigger words: block encoding, quantum linear algebra, QSVT, quantum singular ...Votes: 0GitHub stars: 3
- Quantum Linear Differential EquationNearly optimal quantum algorithm for linear matrix differential equations with applications to open quantum systems. Achieves O~(nu*L*t/epsilon) query complexity for unitary/dissipative dynamics, with polynomial to exponential quantum speedups over classical methods. Activation: quantum differential equation, open quantum system simulation, dissipative dynamics quantum, linear matrix ODE quantum, quantum time evolution algorithm.Votes: 0GitHub stars: 3
- Quantum Linear Matrix DifferentialEfficient quantum algorithm for solving linear matrix differential equations with applications to open quantum system simulation. Computes solution matrix entries with query complexity O~(νLt/ε), achieving nearly optimal scaling. Use when: quantum simulation of open systems, linear differential equation solvers, quantum dynamics simulation, dissipative quantum systems, quantum Carleman linearization.Votes: 0GitHub stars: 3
- Quantum Linear Solver Beyond ConditionQuantum linear system solving methodology that overcomes the condition number barrier. Uses truncation-based and filtering-based solvers with complexity independent of worst-case condition number kappa. Introduces effective condition number bounds and affine dilation input model.Votes: 0GitHub stars: 3