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- 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
- Cim Lwe Qubo CryptanalysisCIM-BDD methodology for LWE cryptanalysis via penalty-free QUBO reduction on Coherent Ising Machines. Use when: analyzing Learning With Errors (LWE) problem security, reducing lattice problems to QUBO for quantum annealing/Ising machines, performing penalty-free mapping of cryptanalytic problems, designing hybrid quantum-classical cryptanalysis workflows, evaluating post-quantum cryptography parameter security. Core insight: algebraic elimination of the secret + nearest-plane decomposition yi...Votes: 0GitHub stars: 3
- Certified Higher Order Qaoa CollateralCR-HO-QAOA framework for certified higher-order quantum collateral allocation with CSA-aware constraints and feasible-subspace mixers. Uses higher-order binary models for margin requirements, concentration limits, and substitution structure, with CP-SAT certification. Use when: collateral optimization, margin-aware quantum optimization, CSA constraints, higher-order QAOA with certification, quantum-classical hybrid solver.Votes: 0GitHub stars: 3
- Green Wearable Computing PhysicsTowards Green Wearable Computing: A Physics-Aware Spiking Neural Network for Energy-Efficient IMU-ba... Activation: 物理感知, spiking, physics-aware, snnVotes: 0GitHub stars: 3
- Exploratory Experience Shapes The Geometry Of PredDerived from arXiv:2605.27929 - Exploratory Experience Shapes the Geometry of Predictive RepresentationsVotes: 0GitHub stars: 3
- Devotg Temporal Graph ConnectomicsDevoTG: Temporal Graph Neural Networks for modeling C. elegans developmental connectomics, capturing dynamic wiring through continuous-time and discrete-time dynamic graphs.Votes: 0GitHub stars: 3
- Continuous Spiking Graph Neural Networks**arXiv ID:** 2404.01897 **Authors:** Nan Yin, Mengzhu Wan, Li Shen, Hitesh Laxmichand Patel, Baopu Li, Bin Gu, Huan Xiong **Published:** 2024-04-02T12:36:40Z **Abstract:** Continuous graph neural networks (CGNNs) have garnered significant attention due to their ability to generalize existing discrete graph neural networks (GNNs) by introducing continuous dynamics. They typically draw inspiration from diffusion-based methods to introduce a novel propagation scheme, which is analyzed using ord...Votes: 0GitHub stars: 3
- A Logical Reconception Of Neural Networks Hamiltonian Bitwise Partwhole Architecture**arXiv ID:** 2602.04911 **Authors:** E Bowen, R Granger, A Rodriguez **Published:** 2026-02-04T01:16:37Z **Abstract:** We introduce a simple initial working system in which relations (such as part-whole) are directly represented via an architecture with operating and learning rules fundamentally distinct from standard artificial neural network methods. Arbitrary data are straightforwardly encoded as graphs whose edges correspond to codes from a small fixed primitive set of elemental pairwise...Votes: 0GitHub stars: 3
- Vacuum Entanglement ExtractionVacuum entanglement extraction protocols from quantum field theory. Covers local operation protocols for harvesting entanglement from vacuum states and applications to distributed quantum computing and quantum networking. Use when: vacuum entanglement, entanglement harvesting, quantum field theory communication, distributed quantum computing, quantum networking, vacuum resource, QFT entanglement, local operations entanglement.Votes: 0GitHub stars: 3
- Topological Quantum ComputingDesign quantum computing systems using topological structures. Apply 3-manifold topology, surface topology, and knotted quantum states for information protection. Activation: topological quantum, topology quantum computing, 拓扑量子计算, 量子拓扑, topological qubit, anyon braiding.Votes: 0GitHub stars: 3
- Thoughtseeds Dual Process MeditationA computational phenomenology framework for modeling focused-attention meditation using dual-process active inference and hierarchical Markov-blanket architecture. Use when modeling meditation states, attentional dynamics, or cognitive phenomenology with latent mental content representations.Votes: 0GitHub stars: 3
- Tensor Network Readout MitigationTensor network (MPO) framework for characterizing and mitigating correlated readout errors in quantum processors. Use when modeling readout noise beyond uncorrelated approximations, estimating nonlocal observables with correlated measurement errors, or integrating readout mitigation with quantum error correction decoders. Triggers: tensor network readout, MPO readout error, correlated measurement error, readout mitigation, matrix product operator calibration, classical shadows readout, noise-...Votes: 0GitHub stars: 3
- Tensor Network Neurological PredictorTensor Network Feature Engineering methodology for multi-class neurological disorder prediction from MRI data. Uses tensor network decompositions to extract high-dimensional features from sparse medical imaging. Activation: tensor network MRI, neurological disorder prediction, tensor feature engineering, multi-class brain disorder, MRI tensor decomposition.Votes: 0GitHub stars: 3
- Tensor Network Frontend Quantum MedicalTensor-network frontend methodology for quantum-enhanced federated medical diagnosis. Combines MPS, TTN, and MERA tensor networks for client-side compression with quantum-enhanced processor (QEP) refinement for medical image classification.Votes: 0GitHub stars: 3
- Supertrust Foundational Alignment Mutual Trust Must Replace Permanent Control For Safe Superintelligence**arXiv ID:** 2407.20208 **Authors:** James M. Mazzu **Published:** 2024-07-29T17:39:52Z **Abstract:** It's widely expected that humanity will someday create AI systems vastly more intelligent than us, leading to the unsolved alignment problem of "how to control superintelligence." However, this commonly expressed problem is not only self-contradictory and likely unsolvable, but current strategies to ensure permanent control effectively guarantee that superintelligent AI will distrust humanit...Votes: 0GitHub stars: 3
- Stp Stabilizes Goal Conditioned DynamicsShort-Term Synaptic Plasticity (STP) stabilizes goal-conditioned dynamics in PFC-inspired reservoir model for multistep goal-directed action planning. Preserves action-relevant goal information under noise with 89.2% success rate vs 49.5% without STP. Activation: short-term synaptic plasticity, goal-conditioned dynamics, reservoir computing, PFC model, goal-directed planning, dynamic connectivity, facilitation-dominant STP.Votes: 0GitHub stars: 3
- Splitting Variational Quantum AlgorithmOperator-splitting variational quantum algorithm (sVQA) for simulating nonlinear quantum equations on quantum computers. Decomposes state-dependent nonlinear evolution into linear substeps (implementable as fixed unitaries) and nonlinear variational corrections (measurement-based). Use when: (1) simulating nonlinear differential equations on quantum hardware, (2) implementing nonlinear quantum dynamics via VQA, (3) handling state-dependent interactions that cannot be unitary, (4) designing op...Votes: 0GitHub stars: 3
- Spikerestormer Unified Event ReasoningSpikeRestormer methodology for energy-efficient all-in-one image restoration using Spiking Neural Networks with unified event reasoning. Solves the challenge of applying SNNs to static images by generating internal spike events for degradation perception and restoration construction. Use when working with SNN-based image restoration, energy-efficient computer vision, or neuromorphic computing for static image processing.Votes: 0GitHub stars: 3
- Sparse Weight Decomposition Circuit ExtractionSparse Weight Decomposition (SWD) for efficient circuit extraction from pretrained transformers. Reparameterizes linear projections by factorizing weight matrices into two sparse factors with shared intermediate coordinates as circuit units.Votes: 0GitHub stars: 3
- Shot Based Quantum EncodingShot-Based Quantum Encoding (SBQE) methodology for quantum neural network data loading. Addresses the bottleneck of inefficient data loading on NISQ devices by distributing shots according to data-dependent classical distributions over multiple input states. Use when designing QML data loading strategies, optimizing quantum encoding for near-term hardware, or comparing encoding schemes (angle, amplitude, basis, shot-based). Activation: shot-based encoding, SBQE, quantum data loading, quantum ...Votes: 0GitHub stars: 3
- Sdpc Quantum CloningSemidefinite Programming framework for optimal quantum cloning using Choi-Jamiolkowski isomorphism and primal-dual strong duality certificationVotes: 0GitHub stars: 3
- Scalable On Hardware Qnn TrainingScalable 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 applications like missing patient data imputation. Validated on IonQ Forte Enterprise at 16 qubits with 32-qubit inference on hardware. Use when: QNN training on quantum hardware, clinical quantum ML, gradient estimation optimization, scal...Votes: 0GitHub stars: 3
- Sam Mt Realtime Multi Target VosDecouples VOS latency from target count for real-time multi-target video segmentation.Votes: 0GitHub stars: 3
- Rt Semamba Speech Enhancement MambaRT-SEMamba for real-time speech enhancement with Mamba.Votes: 0GitHub stars: 3