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SkillsMP has collected 4,114 skills from hiyenwong/ai_collection. Open a skill to review its source and details.
hiyenwong/ai_collectionShowing 40 of 4,114 collected skills.
Design 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…
Quantum 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:…
Controlled benchmarking methodology for evaluating quantum generative models in medical image augmentation.
Sample-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…
Source text: Mixed languages
Quantum Genetic Negative Selection Algorithm (QGNSA) methodology for anomaly detection using quantum-enhanced evolutionary optimization
Research 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 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…
Geometric 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…
Benchmark 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.
Quantum 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…
Reusable 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.…
Quantum 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…
Quantum 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…
Quantum algorithms for histopathologic cancer detection on real hardware (NISQ). Covers DG-CSWAP and DG-DST circuits, NISQ mitigation pipeline, and practical QPU validation strategies.
Quantum-enhanced Hyperdimensional Computing (HDC) framework using quantum binding operations and SuperClass Construction for robust, efficient high-dimensional vector space computation.
Analyze 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…
qReduMIS: 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…
Quantum-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…
Quantum 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…
Quantum 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…
Quantum kernel methods for medical AI embeddings and foundation model enhancement — leveraging quantum Hilbert space geometry for medical image/text feature fusion.
Quantum-enhanced knowledge graph integration using QNLP, quantum superposition/entanglement for semantic relationship modeling, and encoding KGs as quantum states for quantum computing tasks.
Source text: Chinese
Quantum 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.
Controlled 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…
Breakeven 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.
Unified information-theoretic framework for analyzing the interplay between stability, privacy, and generalization in quantum learning algorithms.
Quantum 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…
Design 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…
Nearly 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…
Quantum 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…
Residual-based quantum linear system algorithm with dynamic stopping methodology. Use when solving linear systems Ax=b on quantum computers, implementing HHL-type algorithms, quantum PDE solvers, or designing efficient quantum algorithms with adaptive…
Quantum logic framework for human-centric AI in finance, extending classical rationality to contextual reasoning using quantum-inspired neural networks for algorithmic trading, portfolio management, and robo-advisory. Based on arXiv:2510.05475v1.
Methodology for applying quantum logic to human-centric AI in finance — moving from classical rationality to contextual reasoning. Explores quantum-inspired neural networks for financial statement analysis, algorithmic trading, portfolio management, and…
Leakage-free evaluation of quantum ML for UAV anomaly detection. Group-aware temporal protocol + three-mode feature audit + hybrid XGBoost-DRU classifier.
Analyze quantum algorithms by quantifying magic (non-stabilizerness) as the core quantum resource. Connect magic generation to number-theoretic complexity in Shor's algorithm and other quantum routines. Use when analyzing quantum algorithm resource costs,…
Quantum Margulis Codes methodology for fault-tolerant quantum computation. A new class of QLDPC codes derived from Margulis classical LDPC construction via two-block group algebra (2BGA) framework. Unlike bivariate bicycle codes, these can be efficiently…
Quantum market stabilization via entangled neural traders methodology. Uses quantum entanglement between traders' valuations as endogenous mechanism to mitigate runaway devaluation in speculative busts. RL agents with quantum-correlated qubit-encoded…
Double Covariance Model (DCM) stochastic subquantum framework for deriving macroscopic quantum Markovian dynamics from microscopic correlated fluctuations. Extends DCM to interacting multi-particle systems. Use when: stochastic quantum mechanics, open quantum…
Cross-disciplinary methodology for quantum computing combining mathematical theory, system engineering, and multi-objective optimization. Use for quantum neural architecture search, distributed quantum compilation, entropy geometric analysis, and quantum…
Quantum Mechanical Data Assimilation (QMDA) methodology for combining dynamical models with partial, noisy observations. Uses operator-theoretic framework (Koopman/transfer operators) for uncertainty representation, forecast propagation, and assimilation…