hiyenwong/ai_collection - Page 57

quantum-medical-imaging-patterns

Patterns and methodologies for applying quantum computing and quantum information principles to medical imaging, diagnostics, and edge AI healthcare applications.

quantum-network-authentication

Quantum network authentication methodology - systematic framework for analyzing, selecting, and deploying authentication schemes in quantum communication networks. Covers classical message authentication, quantum message authentication, and entity…

quantum-neuron-activation-observable

Quantum activation observable measurement methodology derived from canonical quantization of neurons.

quantum-opinion-dynamics-networks

Quantum model of opinion dynamics on networks — represents agent cognitive states as density matrices encoding both expressed opinions and cognitive ambivalence, with survey questions as non-commuting self-adjoint operators explaining order effects.

quantum-paradigm-comparison-cv-dv

Controlled comparison methodology for continuous-variable (CV) vs discrete-variable (DV) quantum computing paradigms. Uses shared classical backbone with interchangeable quantum heads to isolate quantum circuit as sole variable. CV outperforms DV with…

quantum-path-superposition-teleportation

Path-superposition framework for quantum gate teleportation enabling superposed path operations for advanced quantum information transfer protocols.

quantum-ring-all-reduce-distributed

Quantum ring all-reduce protocol for distributed machine learning. Uses superdense coding to halve per-link communication and provides information-theoretically secure aggregation impossible classically.

quantum-ring-allreduce-distributed

Quantum ring all-reduce protocol for distributed ML training — uses pre-shared entanglement and superdense coding for 2x communication reduction plus information-theoretic privacy guarantees. Covers composable ε-secure aggregation via verified entanglement…

quantum-routing-anonymity

Methodology for analyzing and quantifying routing anonymity in quantum cloud computing — backend identifiability, privacy guarantees, and utility-anonymity trade-offs. Use when evaluating quantum cloud security, designing privacy-preserving quantum circuits,…

quantum-software-testing-benchmark

Qolumbina benchmark infrastructure for quantum software testing (QST) — curates 40 scalable quantum programs from open-source repos with systematic selection, refactoring, specifications, unit tests, and standardized interfaces. Introduces QST-oriented…

quantum-spectral-anomaly-detection

Quantum Spectral Anomaly Detection (QSPADE) methodology for computing PCA-like anomaly scores using quantum spectral methods - enables efficient anomaly detection in high-dimensional medical and financial data via quantum eigenvalue decomposition.

quantum-stabilizer-testing-limited-memory

Optimal stabilizer testing and learning methodology under limited quantum memory constraints. Provides sample complexity bounds and efficient algorithms for testing whether quantum states are stabilizer states when quantum memory is bounded.

quantum-structured-factorization-tomography

Unified structured factorization framework for quantum state tomography using Burer-Monteiro-type factorization parametrizing density matrix as FF†, guaranteeing physical validity while incorporating structural priors.

quantum-topology-information-scrambling

Graph-theoretic methodology for analyzing quantum information scrambling and chaos diagnostics via OTOCs across network topologies (path, Erdos-Renyi, Watts-Strogatz). Combines information theory with quantum many-body physics.

ravine-quantum-cost-landscape

Ravine analysis framework for quantum cost landscapes — exploiting ravine structures for improved VQA optimization. Use when analyzing VQA convergence, diagnosing optimization failures, or improving quantum circuit parameter optimization.

routing-anonymity-quantum-cloud

Formal framework for backend identifiability and routing anonymity in quantum cloud services with utility-anonymity trade-offs.

self-modulating-quantum-fast-weight

Stable Self-Modulating Quantum Fast-Weight Programmers with bounded memory gates. Quantum sequence modeling using dynamically programmed variational-circuit parameters with bounded old-state modulation for long-sequence stability. Activation: quantum fast…

spatially-coupled-quantum-codes

Spatial coupling methodology for quantum LDPC/CSS codes. Proves that belief-propagation decoding on spatially coupled CSS codes (MN/HA-type) achieves the quantum erasure hashing bound. Uses coupled-vector potential method and density evolution analysis to…

spectral-geometry-quantum-learning

Spectral geometry framework for diagnosing quantum learning systems using bosonic-Bloch probes. Links learned spectral partitions to two-boson interference signatures, Bloch-space drift for anomaly detection, and quantum Fisher information geometry.…

stable-self-modulating-quantum-fwps

Self-Modulating Quantum Fast-Weight Programmers with bounded memory gates for stable sequence processing via variational circuit parameters.

tensor-network-emotional-memory-modeling

Tensor network modeling for order-dependent emotional memory in children (arXiv:2606.28470)

vqe-active-space-benchmarking

Systematic benchmarking methodology for evaluating active space selection strategies in VQE pipelines for quantum drug discovery. Use when benchmarking VQE ansatz choices, designing quantum chemistry validation workflows, or evaluating active space-driven…

zero-memory-quantum-dot-reservoir

Geometric approach to zero-memory quantum dot reservoir computing - engineers memory capacity extrinsically in memoryless systems via spatial degrees of freedom exploiting computational space-time tradeoff.

optimal-stabilizer-testing-limited-memory

Stabilizer state testing and learning under limited quantum memory constraints - sample complexity bounds for testing and learning with k-qubit memory.

dendritic-in-context-learning-snn

DendriCL methodology for in-context learning in single-layer spiking neural networks using dendritic compartment dynamics. Use when: implementing ICL in biologically-plausible SNNs, designing compartmental spiking architectures, studying online LMS in…

dic-neuron-reconstruction-spike-times

Deep learning + Dynamic Input Conductances (DICs) methodology for fast reconstruction of degenerate conductance-based neuron populations from spike times alone, enabling scalable and interpretable inference from experimental recordings.

event-driven-fly-inspired-motion-detection

Event-driven framework for fly-inspired visual motion detection using event cameras and biologically structured neural computation

gelneuro-neuromorphic-tactile-system

Fully integrated sensing-computing neuromorphic visuo-tactile system for texture recognition on edge hardware

spiking-sequence-generator-polar-trajectories

Spiking neural network architecture for generating polar trajectories on neuromorphic hardware using winner-take-all dynamics and shunting inhibition. Enables energy-efficient, interpretable motor control with 2-3 orders of magnitude speedup and 3-4 orders of…

diffusion-learning-viable-parameter-manifolds

Diffusion models for learning viable parameter manifolds and compensation geometry in biological dynamical systems. Use when studying parameter degeneracy, model fitting, neural dynamics, or systems biology.

local-learning-rules-physical-generative-models

Local learning rules for out-of-equilibrium physical generative models using score-based generative modeling in driven nonlinear oscillator networks. Demonstrates that SGM driving protocols can be learned via local measurements without backpropagation.…

ravine-ensemble-vqa-optimization

NEB-based ensemble framework for VQAs that leverages ravine-like structure of quantum cost landscapes to build resource-light ensemble predictions outperforming naive quantum alternatives.

vlms-human-alignment-natural-reading

Research methodology comparing LLM and VLM alignment with human brain responses during natural reading. Uses controlled text-only evaluation to isolate multimodal training effects. Based on arXiv:2605.28818 (May 2026). Use when studying VLM vs LLM alignment,…

kg-research-workflow

End-to-end academic research workflow using knowledge graphs. Searches papers from arxiv/web, imports to KG database, generates embeddings, runs graph algorithms (PageRank, vector search), and extracts patterns for skill creation. Use for: automated research…

flow-matching-in-context-brain-dynamics

Flow Matching with In-Context Priors for Out-of-Distribution Brain Dynamics methodology. First generative model of whole-cortex fMRI dynamics for unseen cognitive tasks. Per-timestep conditioned diffusion transformer with compositional language priors and…

metabolic-quantum-limit-meg

Metabolic quantum limit methodology for magnetoencephalography (MEG) — combining quantum sensor energy resolution with neural metabolic power to derive fundamental information capacity bounds for brain imaging.

quantum-boltzmann-bilevel

Build fully connected Quantum Boltzmann Machines using bilevel optimization to overcome QAOA's fixed target Hamiltonian limitation and classical Boltzmann machines' partial connectivity constraint. Use when designing quantum generative models, energy-based…

quantum-circuit-spectral-analysis

Spectral analysis of quantum circuits using Circuit Harmonic Matrices. Predict quantum machine learning model performance from circuit architecture without training. Analyze circuit expressivity, trainability, and generalization capacity via frequency-domain…

quantum-cognition

Quantum cognition methodology for modeling cognitive processes using quantum probability theory. Combines neuroscience insights with quantum information formalism to model decision making, context-dependent reasoning, mental state dynamics, and non-classical…

stm-sequence-timing-replay

Spiking Temporal Memory (sTM) model for learning sequence timing and controlling replay speed via oscillatory background inputs. Provides biologically plausible mechanisms for encoding element-specific timing and flexible speed control.