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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Diamond Quantum NetworksQuantum networking using diamond color defects (NV/SiV centers) for scalable quantum communication, distributed quantum computing, and sensing. Comprehensive methodology covering optical properties, spin-qubit control, spin-photon interfaces, nanophotonic integration, and metropolitan-scale quantum network demonstrations. Use when building quantum networks, designing quantum repeaters, implementing spin-photon interfaces, or evaluating solid-state qubit platforms for quantum communication. Ac...Votes: 0GitHub stars: 3
- Differential Private Optimal Transport EstimationDifferentially private estimation of smooth optimal transport maps using wavelet density estimators and stability bounds. Privacy-preserving statistical methodology for OT map estimation. Activation: differential privacy, optimal transport, private estimation, wavelet density, minimax estimation.Votes: 0GitHub stars: 3
- Digital Quantum Reservoir Computing FinanceDigital quantum reservoir computing (QRC) methodology for financial time series forecasting on NISQ devices. Uses parametrized multi-qubit reservoirs with fixed structure for temporal data processing.Votes: 0GitHub stars: 3
- Distributed Qaoa SimulatorDistributed Quantum Approximate Optimization Algorithm (DQAOA) simulator for QUBO problems across multiple QPUs. Supports monolithic and distributed QAOA execution modes with configurable QPU capacities, cross-QPU coupling handling, and runtime optimizations. Activation: distributed QAOA, DQAOA simulator, QUBO optimization, multi-QPU quantum, quantum unit commitmentVotes: 0GitHub stars: 3
- Distributed Quantum ComputingDistributed Quantum Computing architecture and patterns. Apply when designing multi-QPU systems, quantum communication protocols, or scaling quantum computing beyond single device limitations.Votes: 0GitHub stars: 3
- Distributed Quantum Fourier TransformDistributed Quantum Fourier Transform (QFT) circuit optimization — circuit partitioning for distributed quantum systems using teleportation to minimize e-bit consumption.Votes: 0GitHub stars: 3
- Distributed Quantum RlDistributed quantum reinforcement learning framework for multi-agent environments, distributing QRL training load across independent agents for scalable quantum machine learning.Votes: 0GitHub stars: 3
- Eigenstate Reduction Quantum SmcpTractable Infinite-Horizon Stochastic Model Predictive Control for Quantum Filtering via Eigenstate Reduction. Uses almost-sure eigenstate reduction of quantum trajectories to collapse infinite-horizon stochastic objective to closed-form fidelity term. Eliminates per-horizon Monte Carlo sampling while retaining stochastic dynamics. Use when designing quantum SMPC controllers, quantum filtering-based control, mean-square stability analysis, or tractable stochastic optimal control for quantum s...Votes: 0GitHub stars: 3
- Element Wise Transforms QuantumQuantum element-wise transforms methodology for efficient matrix operations — reduces space exponentially compared to prior work using polynomial function applied element-wise. Applications to ML, simulation, signal processing.Votes: 0GitHub stars: 3
- End To End Quantum ControlEnd-to-end learning of quantum control on latent dynamical manifolds — replaces iterative simulate-then-optimize with joint LSTM-based dynamics and control strategy learning.Votes: 0GitHub stars: 3
- Entanglement Detection Unitary Ancilla MethodologyMethodology for measuring entanglement measures (concurrence and 3-tangle) using unitary transformations and ancilla measurements, as proposed in arXiv:2607.15201.Votes: 0GitHub stars: 3
- Entanglement Distribution Star NetworksExact analytical noise characterization for multipartite entanglement distribution in star network topologies. Derives closed-form expressions for average noise and noise distribution when distributing GHZ states under memory dephasing. Compares factory vs piecemaker protocols with global cut-off optimization. Extends analysis to depolarizing noise for arbitrary states. Applicable to quantum network design, entanglement distribution, quantum repeater protocols. Activation: entanglement distri...Votes: 0GitHub stars: 3
- Entanglement Generalization Pac BayesianPAC-Bayesian generalization theory for quantum reinforcement learning. Analyzes entanglement as structural complexity axis via Fisher effective dimension. Use when evaluating generalization of quantum policies, designing PQCs for RL, or studying entanglement-generalization trade-offs.Votes: 0GitHub stars: 3
- Entanglement Manipulation RobustnessRobustness of Entanglement Manipulation for almost i.i.d. sources - methodology for quant-ph applicationsVotes: 0GitHub stars: 3
- Entanglement Robustness BoundsInformation-geometric methodology for computing bounds on the robustness of entanglement generation under noise and imperfect control.Votes: 0GitHub stars: 3
- Extreme Quantum CognitionExtreme Quantum Cognition Machines (EQCM) — quantum learning architectures for deliberative decision making tolerant to noisy and contradictory training data. Combines quantum extreme learning, quantum reservoir computing, and dynamical attention mechanisms for symbolic inference, sequence analysis, anomaly detection. Use when: quantum cognition architectures, deliberative decision making with noisy data, quantum reservoir computing, quantum extreme learning machines, dynamical attention in q...Votes: 0GitHub stars: 3
- Fast Tetrabft Quantum ConsensusFast TetraBFT methodology for optimizing Byzantine consensus latency in post-quantum distributed systems. Unauthenticated Byzantine consensus protocols achieve optimal failure resilience using only authenticated point-to-point channels. Key for post-quantum blockchain, distributed consensus, and fault-tolerant systems. Activation: Byzantine consensus, post-quantum distributed systems, TetraBFT, unauthenticated consensus, latency optimization, fault toleranceVotes: 0GitHub stars: 3
- Federated Learning With Quantum Computing And Fully Homomorphic Encryption A Novel Computing Paradigm Shift In Privacypreserving Ml**arXiv ID:** 2409.11430 **Authors:** Siddhant Dutta, Pavana P Karanth, Pedro Maciel Xavier, Iago Leal de Freitas, Nouhaila Innan, Sadok Ben Yahia, Muhammad Shafique, David E. Bernal Neira **Published:** 2024-09-14T01:23:26Z **Abstract:** The widespread deployment of products powered by machine learning models is raising concerns around data privacy and information security worldwide. To address this issue, Federated Learning was first proposed as a privacy-preserving alternative to conventio...Votes: 0GitHub stars: 3
- Fermion Boson Nonlocality ComparisonFermions-vs-bosons nonlocality comparison methodology — proving indistinguishable fermions generate correlations that bosons or distinguishable particles cannot reproduce without additional communication. Use when: analyzing fermionic nonlocality, Bell inequality violations for identical particles, quantum advantage beyond qubits, febits (fermionic bits) information processing, particle statistics in quantum networks, or distributed computing with fermionic carriers.Votes: 0GitHub stars: 3
- Feynmans Clock Quantum Error MitigationQuantum error mitigation using Feynman's clock Hamiltonian mapped to BBGKY hierarchy — extends BBGKY-ISM scheme from spin chains to arbitrary quantum circuits with polynomial overhead in circuit size and qubit count.Votes: 0GitHub stars: 3
- Finite Shot Quantum MetrologyFinite-shot quantum metrology methodology - bias-corrected moment estimation with O(ν⁻³) bias correction. Covers calibration curves, central moments, and density-matrix conditions for optimal quantum parameter estimation.Votes: 0GitHub stars: 3
- Fpqc Sac Low Snr Financial RlFPQC-SAC methodology — Parameterized Quantum Circuit (PQC) front-end for Soft Actor-Critic (SAC) in low-signal-to-noise-ratio financial reinforcement learning. Addresses Q-value overestimation and policy collapse in noisy financial markets through quantum feature representations that provide inductive bias.Votes: 0GitHub stars: 3
- Fpqc Sac Quantum Financial RlFPQC-SAC methodology — Parameterized Quantum Circuit (PQC) integrated with Soft Actor-Critic (SAC) for financial reinforcement learning under low signal-to-noise ratio (SNR) conditions. Places PQC before actor/critic networks to constrain features, using quantum entanglement for cross-asset interactions.Votes: 0GitHub stars: 3
- Free Energybased Reinforcement Learning Using A Quantum Processor**arXiv ID:** 1706.00074 **Authors:** Anna Levit, Daniel Crawford, Navid Ghadermarzy, Jaspreet S. Oberoi, Ehsan Zahedinejad, Pooya Ronagh **Published:** 2017-05-29T18:57:42Z **Abstract:** Recent theoretical and experimental results suggest the possibility of using current and near-future quantum hardware in challenging sampling tasks. In this paper, we introduce free energy-based reinforcement learning (FERL) as an application of quantum hardware. We propose a method for processing a quantum ...Votes: 0GitHub stars: 3
- Gaussian Exponential Zero Noise ExtrapolationHybrid Gaussian-exponential zero-noise extrapolation methodology for periodic quantum circuits — combines Gaussian and exponential error models for more accurate expectation value estimation in NISQ-era quantum computing.Votes: 0GitHub stars: 3
- Generalized Bicycle Qec AutomorphismAlgebraic framework for analyzing and engineering automorphisms in Generalized Bicycle (GB) quantum error-correcting codes. Enables deterministic search for block-separable automorphisms (cyclic shifts, ring automorphisms, block-swaps) and fold-transversal gate implementation. Introduces Maximal Cube Root (MCR) code family for automorphism-rich QEC codes.Votes: 0GitHub stars: 3
- Generalized Hamiltonian Quantum Feature MapsGeneralized two-qubit Hamiltonian methodology for Projective Quantum Feature Maps (PQFMs) — unified feature encoding through local Pauli fields and pairwise interactions with statistical benchmarking on NISQ hardware.Votes: 0GitHub stars: 3
- Geometric Obstruction Quantum MetrologyGeometric obstruction framework for multiparameter quantum estimation — proves when simultaneous t² scaling fails and provides a computable diagnostic via Gram matrix of diagonal generators. Use when designing multiparameter quantum sensors, analyzing quantum Fisher information scaling, or optimizing adaptive quantum control.Votes: 0GitHub stars: 3
- Geometric Typicality EntanglementExact geometric typicality and bipartite entanglement methodology using projected central limit theorem on hyperspheres. Derives Beta distribution for subsystem occupation, Lubkin purity formula, and Bernoulli-factorized asymptotic expansion of mutual information for Haar-random states. Applicable to quantum information theory, random matrix theory, eigenstate thermalization.Votes: 0GitHub stars: 3
- Girsanov Quantum ControlGirsanov's theorem path-space regularization methodology for robust open quantum control. Bridges stochastic calculus (Girsanov theorem) with quantum optimal control, penalizing observable consequences of control on decoherence channels rather than control amplitude. Applicable to quantum control, stochastic control, RL.Votes: 0GitHub stars: 3
- Gqml Graph Models ToolboxGeometric Quantum Machine Learning (GQML) toolbox for graph problems — comprehensive characterization of constituents for n-node graphs encoded in n-qubit states. Provides design patterns for quantum graph models including natural classical integration, expressivity extension, and classical pre-training strategies. arXiv:2607.00698Votes: 0GitHub stars: 3
- Gqsp Hermitian Embedding PricingGeneralised Quantum Signal Processing with Hermitian block embedding for solving 2D Black Scholes equation. Based on arXiv:2606.00458 — quantum linear algebra for option pricing.Votes: 0GitHub stars: 3
- Grid State Qec Spam ImprovementGrid-state qubit QEC achieving state preparation and measurement (SPAM) errors below 10^-3 using repeat-until-success preparation and improved measurement protocol with finite-energy envelope correction.Votes: 0GitHub stars: 3
- Hardware Safety Gated Llm Quantum ControlControl system architecture for LLM-written experimental control code on quantum hardware, enforcing formal per-operation safety boundaries between human authorization and autonomous agent decisions.Votes: 0GitHub stars: 3
- Hardware Tailored Qec Resource EstimationHardware-tailored resource estimation methodology for magic-state distillation on silicon spin qubit platforms. Combines bottom-up noise modeling with top-down application requirements to evaluate physical-to-logical qubit overhead. Supports surface, color, and biased error-correcting codes. arXiv: 2605.28936Votes: 0GitHub stars: 3
- Harnessing Disordered Quantum Dynamics For Machine Learning**arXiv ID:** 1602.08159 **Authors:** Keisuke Fujii, Kohei Nakajima **Published:** 2016-02-26T00:57:59Z **Abstract:** Quantum computer has an amazing potential of fast information processing. However, realisation of a digital quantum computer is still a challenging problem requiring highly accurate controls and key application strategies. Here we propose a novel platform, quantum reservoir computing, to solve these issues successfully by exploiting natural quantum dynamics, which is ubiquitou...Votes: 0GitHub stars: 3
- Higher Order Quantum Optimization FinanceHigher-order binary optimization (HOBO) methodology for legally-constrained financial optimization problems. Applied to collateral allocation with CSA eligibility, margin requirements, and concentration limits.Votes: 0GitHub stars: 3
- Hqnn Expressibility Trainability NasMulti-objective neural architecture search (NAS) framework for hybrid quantum neural networks that jointly optimizes expressibility, trainability, and task performance across a combined classical-quantum design space. Reveals how classical components reshape optimization landscape, decoupling trainability from PQC expressibility.Votes: 0GitHub stars: 3
- Hqnn Neighborhood SelectionHybrid quantum-classical neighborhood selection for large-scale molecular diversity optimization, reducing QUBO memory footprint and computational burden (arXiv: 2607.07336)Votes: 0GitHub stars: 3
- Human Ai Co Discovery Quantum AlgorithmsHuman-AI co-discovery methodology for quantum algorithm design. Based on arXiv:2606.24899 — case study of sign-embedding quantum algorithms for matrix equations and matrix functions.Votes: 0GitHub stars: 3
- Hybrid Qnz Zero Noise ExtrapolationHybrid Gaussian-exponential zero-noise extrapolation methodology for periodic quantum circuits. Uses CLT on Pauli operator transfer to model noise amplification as log-normal, augmenting standard exponential model with Gaussian variance corrections. Applicable to NISQ error mitigation.Votes: 0GitHub stars: 3
- Hybrid Quantum Classical AuditFour-metric audit protocol for evaluating hybrid quantum-classical solvers, particularly D-Wave's hybrid portfolio optimization service. Decomposes wall-clock time into QPU access time, classical decomposition time, and reassembly time to understand where computation actually occurs.Votes: 0GitHub stars: 3
- Hybrid Quantum Fuzzy OntologyHybrid quantum-fuzzy knowledge representation system. Combines dense embeddings with ontologies to simultaneously accommodate probabilistic and crisp inference in the same representation, implemented through quantum-neural networks (QNN).Votes: 0GitHub stars: 3
- Hybrid Quantum Medical ImagingHybrid quantum-classical neural network methodology for medical image classification, particularly thermographic breast cancer detection. Integrates quantum neural network layers with classical CNN backbones to enhance pattern recognition in complex medical imaging data. Use when: (1) hybrid quantum-classical architectures for medical diagnosis, (2) quantum-enhanced image classification in healthcare, (3) thermographic/thermal image analysis with quantum methods, (4) quanvolutional networks f...Votes: 0GitHub stars: 3
- Hybrid Quantum Neighborhood SelectionHybrid Quantum Neighborhood Selection (HQNS) — resource-efficient framework for large-scale combinatorial optimization. Decomposes dense QUBO into bounded-width quantum subproblems via stochastic frontier selection. Preserves 99.99% solution quality while reducing wall-clock time 94.91%, CPU 64.68%, memory 88.61%. QPU execution bounded at 6-7s regardless of global problem scale.Votes: 0GitHub stars: 3
- Hybrid Quantum NlpHybrid quantum-classical neural network methodology for NLP tasks including sentiment analysis and text classification. Uses TF-IDF vectorization plus parameterized quantum circuits, with demonstrated transfer learning advantages over classical baselines.Votes: 0GitHub stars: 3
- Hybrid Quantum Pinn Nonlinear PdeHybrid quantum-classical physics-informed neural network (HQPINN) methodology for solving nonlinear PDEs. Integrates a classical neural network backbone with a parameterized quantum circuit (PQC) to enrich solution representation. Mitigates spectral bias, ill-conditioned optimization, and unstable convergence in classical PINNs, with largest gains in stiff and multiscale regimes. Use when: solving nonlinear PDEs (Burgers, Allen-Cahn, KdV), designing hybrid quantum-classical architectures for ...Votes: 0GitHub stars: 3
- Integrability Breaking Quantum ChaosQuantitative theory for integrability-to-chaos transition in quantum many-body systems via tunable integrability-breaking gates. Use when analyzing OTOC crossover from integrable to chaotic regimes, computing butterfly velocity and front broadening, studying characteristic time/length scales of chaos emergence, or modeling free fermion circuits doped with non-integrable gates.Votes: 0GitHub stars: 3
- Intervention Aware Quantum Predictive ControlIntervention-Aware Variational Quantum Differentiable Predictive Control (IA-VQC-DPC) methodology for safe quantum policy learning with safety attribution.Votes: 0GitHub stars: 3
- Intrinsic Locality Dimension Quantum CodesIntrinsic locality dimension methodology for quantum error-correcting codes. Measures code locality independent of background geometry. Use when: quantum code analysis, stabilizer code design, quantum error correction, topology-geometry relationships in QEC.Votes: 0GitHub stars: 3