Chordless cycle filtrations from topological data analysis combined with a neural network trained on synthetic graphs provide a data-driven estimate of the dimensionality of hyperbolic geometry in complex networks.
Hatcher,Algebraic Topology(Cambridge University Press, 2002)
2 Pith papers cite this work. Polarity classification is still indexing.
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A Hyperbolic Cycle Basis algorithm is introduced within a unified framework for constructing and benchmarking CSS quantum error correction codes on hyperbolic lattices, with performance metrics evaluated on two example codes.
citing papers explorer
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Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis
Chordless cycle filtrations from topological data analysis combined with a neural network trained on synthetic graphs provide a data-driven estimate of the dimensionality of hyperbolic geometry in complex networks.
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Systematic Approach to Hyperbolic Quantum Error Correction Codes
A Hyperbolic Cycle Basis algorithm is introduced within a unified framework for constructing and benchmarking CSS quantum error correction codes on hyperbolic lattices, with performance metrics evaluated on two example codes.