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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.
Privacy-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…
Quantum probability-flow principle for deriving local Hebbian learning rules in associative memory networks using quantum annealer validation. arXiv:2606.02098
LLM-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…
LLM-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…
Semantics-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.
Apply 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.…
Design 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…
Geometric prototype learning in quantum Hilbert space using matrix product states for explainable ML
Quantum 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…
Quantum 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,…
Quantum 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.
Theoretical 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.
Electromagnetic-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…
Non-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…
Post-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…
Quantum 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…
Quantum 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…
Quantum 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…
Robust 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…
Architecture 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…
Post-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.
Quantum sequence models for learning and generating stochastic processes. Quantum circuits that generate coherent superpositions of stochastic processes enable quantum-accelerated risk analysis, importance sampling, and DNA sequencing. Addresses the challenge…
Quantum-based side-channel leakage verification methodology. Uses quantum algorithms for verifying side-channel countermeasures against leakage attacks. Applicable to cryptographic hardware security, side-channel analysis, and countermeasure validation.
Quantum Signal Processing (QSP) via orthogonal polynomial theory methodology. Provides analytical angle-finding for QSP protocols using Hermite, Jacobi, and Rogers-Szego polynomial expansions. Enables block-encoding of smooth functions with O(log(1/epsilon))…
Implement Quantum Signal Processing (QSP) using orthogonal polynomial theory. Derive QSP angles analytically for Hermite, Jacobi, and Rogers-Szego polynomial families. Achieve O(log(1/ε)) gate complexity for ε-approximation of smooth functions via Hermite…
Component-based Quantum Software Architecture Framework (QSAF) for designing hybrid quantum-classical systems. Provides 34 reusable quantum circuit patterns, architectural guidelines, and systematic transition from circuit-level to system-level design.
Quantum solver evaluation and quantum neural network assessment methodology. Covers Q-SAGE iterative quantum solver generation evaluation, equivariant RL for Clifford circuit synthesis, photonic QNN algorithmic advantage assessment, LUNA LUT-based qubit…
Quantum sparsity design principle for robust VQAs using topological Entanglement Entropy (TEE) as cost function regularizer. Guides optimization along the critical edge of chaos, mitigating barren plateaus in Variational Quantum Algorithms. Activation:…
Quantum spectral methods for machine learning - leveraging quantum computing's natural ability to manipulate Fourier spectrum for ML tasks. Use when exploring quantum ML algorithms, spectral methods in quantum context, or Fourier-based quantum ML approaches.…
Quantum Spectral Framework for solving PDEs using Quantum Block Encoding (QBE) with quantum reversible arithmetic. Exploits filter structure in Fourier space to solve second-order linear PDEs. Extends to quantum group Fourier transforms, wavelet-based…
Neural network-based quantum state preparation methodology from arXiv:2605.31006. Trains classical neural networks to map input data directly to quantum circuit parameters, avoiding per-instance variational optimization. Achieves 0.992 fidelity on unseen…
Quantum statistical metrology methodology for multi-parameter quantum estimation using purification-based strategies. Covers quantum Cramér-Rao bounds, Holevo bounds, and sequential hypothesis testing for quantum state discrimination.
Quantum statistics measurement in extended collider systems coupled to qubits. Methodology for probing mutual statistics of quantum particles using mesoscopic colliders with qubit coupling. Use when analyzing quantum statistics, anyon detection, quantum point…
Quantum-like structure in AI language: Bell inequality violation and Bose-Einstein statistics in LLMs. Use when analyzing non-classical probability in language models, quantum cognition applied to AI, conceptual combinations in LLMs, evolutionary convergence…
Quantum subgradient estimation methodology for Conditional Value-at-Risk (CVaR) minimization using amplitude estimation. Provides near-quadratic query complexity improvement O(1/eps) vs O(1/eps^2) classical Monte Carlo for tail-risk optimization. Use when…
Symmetry exploitation methodology for Quantum Reservoir Computing. Shows that symmetric Hamiltonian alone is insufficient for symmetry matching; introduces observable-orbit completion that aligns encoding, dynamics, measurement, and readout interfaces. Use…
Cross-disciplinary analysis of mathematical symmetry principles in quantum physics. Combines number theory, statistics, algebraic geometry with quantum mechanics. Covers: mirror dual symmetry (Rabi-Dirac), symplectic forms (L∞-Lagrangian), quantum memory…
Adaptive syndrome processing for quantum error correction decoding. Dynamically adjusts decoder parameters based on syndrome patterns and noise characteristics to improve logical qubit fidelity.
Quantum system architecture design skill - systems engineering approach to quantum computing. Covers hybrid quantum-classical systems, dataflow frameworks, distributed quantum computing models, fault-tolerant architecture (FTQC), resource optimization…
量子系统工程方法论 - 涵盖分布式量子计算、混合量子-经典系统架构、量子错误纠正、量子系统优化。适用于量子计算系统设计、量子网络架构、量子-经典混合工作流等任务。关键词：quantum systems, distributed quantum computing, quantum architecture, hybrid quantum-classical, quantum error correction, qubit design, quantum network, 量子系统工程, 分布式量子计算,…
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