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SkillsMP has collected 4,114 skills from hiyenwong/ai_collection. Open a skill to review its source and details.
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Systems engineering patterns for quantum computing systems. Covers hybrid quantum-classical architecture, distributed quantum computing, robust quantum control, QEC network architectures (SCOPE Pattern 20), network constraint modeling (Pattern 21), QLDPC…
Quantum tensor network methods for many-body quantum systems analysis. Combines belief propagation algorithms, tensor network expansions, and machine learning for efficient quantum state representation and computation. Use when: (1) analyzing many-body…
Local tensor-train surrogates methodology for quantum machine learning models. Constructs fast, cheap, provably accurate classical surrogates of fully trained QML models within local patches of input data space. Combines Taylor polynomial approximation with…
Quantum Time Lower Bounds by Permutation Invariance. Use when analyzing quantum algorithms, complexity bounds, quantum ML architectures, or quantum error correction involving mathematical analysis and statistical methods.
Unified framework for quantum tomography and quantum retrodiction — proves Petz recovery map equals gradient update of log-likelihood in maximum-likelihood tomography, with noncommutative generalization for arbitrary quantum channels. Use when working with…
Quantum and classical algorithms for topological data analysis (TDA) including persistent Betti numbers computation, simplicial complex construction, and persistence diagram interpretation. Use when analyzing topological features of data, persistent homology,…
Quantum topology spectroscopy methodology for detecting band topology via quantum optical signatures in high-harmonic generation (HHG). Use when: (1) analyzing topological phases via optical spectroscopy, (2) computing high-harmonic generation in solid-state…
Quantum transition state methodology — finding exact quantum counterparts to classical transition states using quantum flow geometry. Use when analyzing quantum reaction dynamics, tunneling rates, or quantum-classical correspondence in chemical physics.…
Qlustering: Unsupervised clustering via steady-state quantum transport in GKSL-governed quantum networks. Data encoded as input states, cluster assignments inferred from terminal output currents. Use when: quantum machine learning, unsupervised quantum…
Quantum algorithms for graph triangle cut sparsification methodology. Uses quantum walks and Grover search to list triangles faster than classical bounds, enabling efficient construction of ε-sparsifiers for large-scale network analysis.
Quantum Tug-of-War (QTOW) decision making model — contextuality arises generatively from physically grounded constraints on decision dynamics. Conservation-based internal state updates and measurement-induced disturbance produce KCBS-type contextuality…
Quantum-inspired evolutionary optimization for non-convex ML landscapes using superposition-inspired probabilistic encoding and simulated tunneling to escape local optima. Use when classical optimizers (ADAM, GA, DE) get stuck in local minima on sparse signal…
Quantum Viterbi decoding methodology for hidden quantum Markov models (HQMMs). Extends classical Viterbi algorithm to quantum sequential decision-making with proven advantage over classical diagonal strategies.
Quantum algorithm methodology for nonlinear and stochastic homogenization using Young-measure based linear programming formulation with provable quantum speedup.
QUBO-based hybrid quantum-classical optimization methodology for coordinated scheduling problems. Formulates time-dependent operational constraints as quadratic unconstrained binary optimization, then solves with quantum annealing validated by classical…
Qudit encoding methodology for variational quantum optimization of integer and multi-valued problems. Demonstrates exponential Hilbert space reduction vs binary qubit encoding while maintaining or improving optimization performance. Covers qudit-native QAOA,…
Qumode-based Variational Quantum Deflation (QumVQD) framework for excited-state quantum chemistry on bosonic quantum processors. Computes electronic and vibrational excited state energies with 1-2 orders lower gate counts than qubit-based methods. Keywords:…
Von Neumann entropy estimation in multi-qutrit quantum systems via variational quantum algorithms and classical neural networks. Use when estimating quantum entropy for d-level systems (qudits), selecting VQA ansatze for entropy estimation, or benchmarking…
Block permutation routing on Ramanujan hypergraphs for fault-tolerant quantum computing. Use when: routing surface code patches on reconfigurable lattices, analyzing quantum circuit compilation overhead, designing fault-tolerant qubit movement protocols,…
Random dimension reduction methodology for learning symmetric properties of quantum states. Black-box procedure that replaces dimension with maximum rank in sample complexity. Use when learning symmetric quantum properties, estimating state…
Quantum cloud platform authentication framework using multi-dimensional quantum fingerprints from raw measurement data. Constructs Mahalanobis-based fingerprints with drift early warning and adversarial detection to verify which physical device executes…
Expert guidance for React component architecture, maintainability, and best practices. Use when building React components, reviewing component structure, optimizing component performance, or working with React hooks. Triggers on: react component, component…
CoT-Control methodology for testing reasoning model control over internal reasoning. Finding - models struggle to control chains of thought, reinforcing monitorability as safety safeguard. Use when evaluating reasoning model safety or designing monitoring…
ReSCom可重构脉冲神经网络加速器，使用随机计算降低硬件复杂度。核心创新：乘法用随机算术，加法用精确定点，统一架构支持IF/LIF/Synaptic模型，运行时可权衡精度/延迟/能耗。MNIST上92.80%准确率，0.05mJ/image能效超越SOTA。触发词：可重构SNN加速器、随机计算SNN、神经形态FPGA、ReSCom。
Source text: Chinese
ReSCom: A Reconfigurable Spiking Neural Network Accelerator Using Stochastic Computing. Neuromorphic hardware architecture for energy-efficient SNN inference with runtime accuracy-latency-energy trade-offs.
Fallback strategies for automated research when external APIs fail. Use when: (1) arXiv/semantic scholar APIs return errors, (2) scheduled research jobs encounter connectivity issues, (3) need to pivot from live search to knowledge-based skill creation, (4)…
Build and analyze knowledge graphs from research literature. Automated pipeline: arxiv search → entity extraction → KG construction → vector embeddings → semantic search → skill pattern extraction. Use when user asks to analyze papers, build research…
Meta-skill that extracts reusable skill patterns from research papers (arxiv), scientific workflows, and knowledge graph analysis. Activates when analyzing papers for skill patterns, creating skills from research methodologies, or mining patterns from…
Ribbon ZX calculus framework for gauge theory — extends ZX diagrammatic calculus to 2D Yang-Mills theory with compact gauge groups via Hopf Frobenius algebraic structure.
Bures-Wasserstein metric-based Riemannian self-attention network for robust EEG decoding
Reinforcement learning for ion shuttling on trapped-ion quantum computers — RL-based optimization of ion transport in modular trapped-ion chips, achieving up to 36.3% reduction in shuttling operations.
Reinforcement Learning for Quantum Error Correction control methodology. Based on Google Quantum AI's Willow processor framework (arXiv:2511.08493). Use when: (1) designing RL-based calibration for quantum systems, (2) implementing continuous error correction…
Reinforcement Learning-driven Adaptive Listening for TSCH Networks
SAFE Quantum Machine Learning methodology — variational quantum classifiers with amplitude encoding, learnable classical pre-encoding, and SAFE-AI reliability metrics (Cramer-von-Mises-based accuracy/robustness/explainability evaluation). For designing…
Design layered control architectures (LCAs) using safety-liveness decomposition via heterogeneous assume-guarantee contracts. Use when: (1) designing hierarchical control systems with discrete planning + continuous execution, (2) enforcing safety constraints…
Surviving by Serving (SBS) principle for self-organization in complex adaptive systems. Components persist when outputs are utilized; non-utilization triggers adaptation. Emergence of functional networks without centralized control.
Scalable on-hardware training methodology for Quantum Neural Networks (QNNs) using Butterfly circuit architecture with layer-wise training and parallelized parameter-shift rule. Reduces gradient estimation cost from O(n²) to O(log n), enabling clinical data…
Open-source QEC system architecture using RISC-V-based quantum control with sub-microsecond decoding-feedback latency. FPGA-implemented distributed multi-board architecture for superconducting qubits.
SDA-QEC (Simplified Diffusion Augmentation with Quantum-Enhanced Classification) methodology for medical image diagnosis under severe class imbalance. Integrates lightweight diffusion augmentation for minority class rebalancing with quantum feature layers for…
Semidefinite Programming framework for optimal quantum cloning using Choi-Jamiolkowski isomorphism and primal-dual strong duality certification