Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T04:36:26.206806Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 0 inbound Pith citation observations for arXiv:2607.02626.
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One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
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76 of 76 outbound references displayed
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Fundamentals of
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Unresolved cited work
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Dummit and Richard M
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability On the dynamical Lie algebras of quantum approximate optimization algorithms
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Unresolved cited work
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Beltrametti and Ettore Carletti and Dionisio Gallarati and Giacomo Monti Bragadin , title =
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Hall , title =
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Gutknecht and Thomas Schmelzer , title =
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Random quantum circuits are approximate unitary t -designs in depth O\! (nt^
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability CUAOA: A Novel CUDA-Accelerated Simulation Framework for the QAOA
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability Classification of dynamical Lie algebras for translation-invariant 2-local spin systems in one dimension
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Krylov-Lie Algebras for Variational Quantum Algorithms: Geometric, Depth-Aware Insights into Expressivity and Trainability A Maximum Independent Set Method for Scheduling Earth Observing Satellite Constellations
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