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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Arxiv 2608 06294v1 Quantimedai Quantum Enhanced Time Series Model Gui**arXiv ID:** 2608.06294v1 **Authors:** Mutasim Fuad Sarker, Adiba Rahman Namira, Wafa Binte Alam, Md Adnan Arefeen, Mahzabeen Emu, Sumaiya Tabassum Nimi **URL:** http://arxiv.org/abs/2608.06294v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 12936v1 Autoqureo A Framework For Automated Quantum Resour**arXiv ID:** 2608.12936v1 **Authors:** Harshkumar Oza, Aritra Sarkar, Syed Naqi Abbas, Rahul Bhowmick, Aryan Prakash, Prateek P Kulkarni, Krishna Kumar Sabapathy **URL:** http://arxiv.org/abs/2608.12936v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 13521v1 Exponential Quantum Advantage For Learning Signals**arXiv ID:** 2608.13521v1 **Authors:** Ishaan Kannan, Sridhar Prabhu, Saeed A. Khan, Mandar M. Sohoni, Xingrui Song, Saswata Roy, Alen Senanian, Valla Fatemi, Peter L. McMahon, Jordan Cotler **URL:** http://arxiv.org/abs/2608.13521v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18659v1 Quantum Logic Tsetlin Machines Interpretable Quant**arXiv ID:** 2608.18659v1 **Authors:** Krishna Bhatia **URL:** http://arxiv.org/abs/2608.18659v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18901v1 Quantum Tensor Network Learning With Dmrg**arXiv ID:** 2608.18901v1 **Authors:** Gustav J L Jäger, Martin B Plenio, Hans-Martin Rieser **URL:** http://arxiv.org/abs/2608.18901v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18946v1 Alphaclifford Efficient Clifford Synthesis And Tra**arXiv ID:** 2608.18946v1 **Authors:** Daniele Lizzio Bosco, Jacopo Cossio, Carla Piazza, Giuseppe Serra **URL:** http://arxiv.org/abs/2608.18946v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 19043v1 Bernstein Vazirani Networks Quantum Machine Learni**arXiv ID:** 2608.19043v1 **Authors:** Natacha Kuete Meli, Tolga Birdal, Prayag Tiwari, Vladislav Golyanik, Michael Moeller **URL:** http://arxiv.org/abs/2608.19043v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 19881 Interpretable Feature Learning For Rf FingerprintiInterpretable Feature Learning for RF Fingerprinting via Polar MKANs (arXiv: 2608.19881)Votes: 0GitHub stars: 3
- Arxiv 2608 23119v1 Quantum Reservoir Computing With Physics Informed**arXiv ID:** 2608.23119v1 **Authors:** Krishna Bhatia, Harsh, Shalini Devendrababu **URL:** http://arxiv.org/abs/2608.23119v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 25907v1 Quantum Inspired Modeling Of Driving Behavior**arXiv ID:** 2608.25907v1 **Authors:** Mohammad Elayan, Omid Armantalab, Wissam Kontar **URL:** http://arxiv.org/abs/2608.25907v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 27302v1 Quantumboostnet A Hybrid Classical Quantum Archite**arXiv ID:** 2608.27302v1 **Authors:** Mihai Udrescu-Milosav, Stefan-Alexandru Jura, Mihai Udrescu, Gerhard-Paul Diller **URL:** http://arxiv.org/abs/2608.27302v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30633v1 Quantum Grassmann Plucker Token Mixing For Deep Le**arXiv ID:** 2608.30633v1 **Authors:** Kooroush Farahkhah, Umut Lagap, Taha Rezaei, Saman Ghaffarian **URL:** http://arxiv.org/abs/2608.30633v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 31117v1 Train Classical Deploy Quantum Requires Rethinking**arXiv ID:** 2608.31117v1 **Authors:** Snehal Raj, Natansh Mathur, Alejandro Perdomo-Ortiz **URL:** http://arxiv.org/abs/2608.31117v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02186v1 Quantum Meanflow Single Shot Generative Sampling O**arXiv ID:** 2609.02186v1 **Authors:** Ashish Joshi, Eshaan Mistry, Takahiko Koyama **URL:** http://arxiv.org/abs/2609.02186v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 04165v1 Parameterised Graph Theory For Tensor Networks Ent**arXiv ID:** 2609.04165v1 **Authors:** Matthias C. Caro, Natalie McHugh, Sergii Strelchuk **URL:** http://arxiv.org/abs/2609.04165v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 09980v1 Fidelity Aware Scheduling Of Quantum Circuits On M**arXiv ID:** 2609.09980v1 **Authors:** Innocenzo Fulginiti, Antonio Tudisco, Salvatore Zammuto, Patrick Hopf, Deborah Volpe, Helmut Seidl, Giovanna Turvani, Robert Wille, Christian B. Mendl, Martin Schulz **URL:** http://arxiv.org/abs/2609.09980v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10089v1 Hybrid Quantum Classical Nlp Classification With C**arXiv ID:** 2609.10089v1 **Authors:** Ali Hassan, Zijia Zhao, Maha A. Metawei **URL:** http://arxiv.org/abs/2609.10089v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10141v1 The Sample Complexity Of Quantum Entanglement Allo**arXiv ID:** 2609.10141v1 **Authors:** Nathan Roll **URL:** http://arxiv.org/abs/2609.10141v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10505v1 Quantum Feature Engineering For Credit Default Pre**arXiv ID:** 2609.10505v1 **Authors:** Menachem Finkelstein, Diana Legziel Levy, Zohar Yakhini, Sarel Cohen **URL:** http://arxiv.org/abs/2609.10505v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10514v1 Optimal Low Rank Quantum State Tomography With Bou**arXiv ID:** 2609.10514v1 **Authors:** Ashwin Nayak, Xingyu Zhou **URL:** http://arxiv.org/abs/2609.10514v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Automated Logical Clifford Chain MapsAutomated framework for synthesizing inter-code logical Clifford (CNOT/CZ) gates between arbitrary CSS quantum error-correcting codes using chain maps — recovers known transversal constructions and finds new low-depth solutions for heterogeneous QEC architectures.Votes: 0GitHub stars: 3
- Autonomous Qec Deep RlAutonomous quantum error correction via deep reinforcement learning methodology. Uses curriculum learning enabled deep RL to discover Bosonic codes under approximate AQEC framework to resist single-photon and double-photon losses. Analytical solution of master equation accelerates RL training. Two-phase training: rapid exploration to surpass breakeven point, then fine-tune policy for sustained performance. Discovers optimal codewords (Fock states 4 and 7) for combined loss channels. Activatio...Votes: 0GitHub stars: 3
- Bch Zassenhaus Error BoundsAnalytical error bounds for truncated Baker-Campbell-Hausdorff and Zassenhaus formulas in unitary quantum problems.Votes: 0GitHub stars: 3
- Bell Inequality Spin EntanglementGeneralized Bell-like inequality methodology for multiparticle entangled Schrodinger-cat-states. Quantum probability statistics unified formulation. Violation patterns for half-integer vs integer spins. Parity-dependent maximum violation bounds.Votes: 0GitHub stars: 3
- Bosonic Qec Stellar RankBosonic quantum error correction with finite stellar rank — establishes stellar rank as an operationally meaningful resource measure for bosonic QEC under practical state-preparation constraints. Use when designing bosonic codes, analyzing non-Gaussian resource trade-offs, or optimizing GKP/cat code preparation.Votes: 0GitHub stars: 3
- Canonical Quantum NeuronsMethodology for canonical quantization of classical computational primitives (neurons, activation functions, energy-based models) into quantum ML models. Use when designing quantum neural architectures, constructing quantum Hamiltonians from classical energy functions, or developing hybrid quantum-classical training algorithms. Trigger words: canonical quantization, quantum neurons, quantum activation, quantum Hamiltonian, quantum machine learning primitives.Votes: 0GitHub stars: 3
- Carve Q Quantum Driving RepairVerifier-shielded quantum-AI search architecture for certified autonomous driving repair. Combines Grover/Dür-Høyer minimum finding with classical safety certification.Votes: 0GitHub stars: 3
- Centralized Task Quantum Network ControlResource-centric, task-based centralized control architecture for quantum networks. Replaces layered protocol stacks with a centralized controller that tracks quantum memory availability across all nodes and schedules objectives using priority-based scheduling. Validated on bottleneck, grid, star, and caveman topologies using SeQUeNCe simulator. Reduces latency compared to layered architectures. Use when designing quantum network control architectures, evaluating layered vs centralized approa...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
- Cim Bdd Penalty Free Lwe CryptanalysisCIM-BDD methodology — hybrid Bounded-Distance-Decoding solver that reduces LWE to QUBO via penalty-free mapping, using algebraic elimination and adaptive mixed-radix encoding for NISQ devices.Votes: 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
- Closed Loop Quantum ProbabilityClosed-loop decomposition of quantum probabilities from unitarity — Bargmann invariants as phase-invariant loop quantities, Born rule as quadratic structure from forward/reverse amplitude products. Connects quantum probability to number theory (loop invariants, cyclic groups) and statistics (phase-invariant estimation). Trigger words: closed-loop quantum probability, Bargmann invariant, unitarity, Born rule derivation, quantum interference, phase-invariant, cyclic loop.Votes: 0GitHub stars: 3
- Clt Sanov Qnn MoeCentral Limit Theorem and Sanov's principle for Quantum Neural Network Mixture of Experts (QNN-MoE) — statistical mechanics framework for analyzing parameter fluctuations, convergence, and neural tangent kernel dynamics in quantum neural network ensembles.Votes: 0GitHub stars: 3
- Coherent Feedback H Infinity Quantum ControlSimplified coherent feedback H∞ control design for linear quantum systems using Lyapunov equations instead of coupled algebraic Riccati equations — computationally efficient robust control for quantum optical systems.Votes: 0GitHub stars: 3
- Compressive Quantum TomographyCompressive quantum state tomography methodology — unified framework for structured quantum state recovery using low-rankness, tensor networks, and compressive sensing principles. Bridges statistics, optimization, and quantum information theory for scalable quantum state characterization.Votes: 0GitHub stars: 3
- Concentration Measure Quantum StatesConcentration of measure phenomena for quantum states - Levy's lemma extensions, hyper-equatorial bounds, and Lipschitz observable analysis for quantum information theory applications.Votes: 0GitHub stars: 3
- Control Theoretic Quantum AdvantageControl-theoretic framework for understanding Quantum Advantage (QA). Recasts quantum computation as operator controllability problem on SU(N), identifying QA with polynomial-in-n upper bound on minimal-time function. Use when: analyzing quantum advantage from control theory perspective, studying operator controllability of quantum systems, deriving time bounds for quantum algorithms (QFT, QAOA), or designing quantum control protocols for superconducting or neutral-atom processors.Votes: 0GitHub stars: 3
- Covangelo Hybrid Quantum Drug DiscoveryCovAngelo QM/QM/MM multiscale embedding platform for quantum-classical drug discovery simulations. Uses quantum-in-quantum-in-classical embedding for ligand-protein binding modeling.Votes: 0GitHub stars: 3
- Covariant Quantum CodesSU(d)-covariant approximate quantum codes for protected analog computation with Theta(1/N) error scaling and Petz recovery map decoder, enabling continuous symmetry-preserving quantum error correction.Votes: 0GitHub stars: 3
- Cv Photonic Qnn Edge MedicalParameter-efficient Continuous-Variable Photonic Quantum Neural Networks (CV-QNN) for edge medical AI applications. Covers room-temperature quantum computing on photonic hardware, MobileNet feature extraction + PCA dimensionality reduction, and CV-QNN classifiers for medical image classification (oral cancer, dermatology, radiology). Use when: (1) building edge-deployable quantum ML for healthcare, (2) comparing qubit vs CV photonic approaches, (3) designing parameter-efficient quantum classi...Votes: 0GitHub stars: 3
- Cv Qnn Edge Ai Oral CancerParameter-efficient Continuous-Variable Photonic Quantum Neural Networks for Edge AI — simplified Φ∘D∘U₁ CV-QNN architecture achieving 100% calibrated test accuracy on oral cancer detection with only 18 parameters (44% fewer than standard CV-QNN layer). Use when building room-temperature quantum ML for medical classification, edge quantum AI, or optimizing CV-QNN parameter efficiency.Votes: 0GitHub stars: 3
- Cv Qnn Edge AiParameter-efficient Continuous-Variable photonic Quantum Neural Networks for edge AI deployment. Simplified CV-QNN architecture reduces trainable parameters by 40-45% while maintaining or exceeding classical baseline performance. Barren plateau mitigation via dimensionality reduction and encoding restriction. Use when: building quantum machine learning models for edge deployment, optimizing CV-QNN architectures, mitigating barren plateaus, parameter-efficient quantum classification.Votes: 0GitHub stars: 3
- Cv Qnn Edge Medical ImagingParameter-efficient continuous-variable photonic quantum neural networks for edge medical AI. Room-temperature quantum ML for medical image classification with 40-45% parameter reduction. Covers CV-QNN architecture simplification, barren plateau mitigation, and edge deployment strategies.Votes: 0GitHub stars: 3
- Cv Qnn Spatial ClassificationControlled comparison methodology showing continuous-variable (CV) QNNs outperform discrete-variable (DV) QNNs on spatial pattern recognition tasks like wafer-map defect classification.Votes: 0GitHub stars: 3
- Data Driven Quantum System IdentificationData-driven system identification methods for quantum dynamics, using machine learning to learn accurate models of quantum system behavior from experimental data. Enables model-based control design without requiring first-principles quantum mechanical modeling.Votes: 0GitHub stars: 3
- Decoded Quantum Interferometry Beyond HammingDecoded Quantum Interferometry (DQI) extended beyond Hamming space to translation association schemes for structured optimization on finite geometries.Votes: 0GitHub stars: 3
- Decoded Quantum Interferometry Bounded DegreeComplexity-theoretic benchmark for decoded quantum interferometry (DQI), QAOA, and classical heuristics on bounded-degree max-Ek-LINSAT. Extends NP-hardness to arbitrary finite fields F_q with bounded degree D, proving hardness to exceed r/q + O(1/sqrt(D)). Identifies 1/sqrt(D log D) classical decoder barrier vs. 1/sqrt(D) quantum decoder scaling. arXiv: 2606.13570Votes: 0GitHub stars: 3
- Decoding Surface Codes With Deep Reinforcement Learning And Probabilistic Policy Reuse**arXiv ID:** 2212.11890 **Authors:** Elisha Siddiqui Matekole, Esther Ye, Ramya Iyer, Samuel Yen-Chi Chen **Published:** 2022-12-22T17:24:32Z **Abstract:** Quantum computing (QC) promises significant advantages on certain hard computational tasks over classical computers. However, current quantum hardware, also known as noisy intermediate-scale quantum computers (NISQ), are still unable to carry out computations faithfully mainly because of the lack of quantum error correction (QEC) capabili...Votes: 0GitHub stars: 3
- Deep Learning Enhanced Noise Spectroscopy Of A Spin Qubit Environment**arXiv ID:** 2301.05079 **Authors:** Stefano Martina, Santiago Hernández-Gómez, Stefano Gherardini, Filippo Caruso, Nicole Fabbri **Published:** 2023-01-12T15:28:36Z **Abstract:** The undesired interaction of a quantum system with its environment generally leads to a coherence decay of superposition states in time. A precise knowledge of the spectral content of the noise induced by the environment is crucial to protect qubit coherence and optimize its employment in quantum device application...Votes: 0GitHub stars: 3
- Dft Embedded Quantum ChemistryDFT-embedded quantum-selected configuration interaction methodology for accurate large-scale electronic structure calculations on quantum computers. Bridges quantum active space treatment with classical wave-function methods using Manby projection technique. Achieved ~1 kcal/mol accuracy on 144-qubit hardware.Votes: 0GitHub stars: 3