A neural network trained on 2D SU(2) lattices with inserted thin Z2 vortices, after random gauge transformations, noise, and cooling, can locate center vortices at moderate visibility levels and scales via tiling.
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Lattice calculations of nucleon wavefunctions reveal superposition nodes from mixing interpolating fields and built-in nodes intrinsic to individual s-wave Dirac components.
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First steps towards gauge-independent vortex identification through machine learning
A neural network trained on 2D SU(2) lattices with inserted thin Z2 vortices, after random gauge transformations, noise, and cooling, can locate center vortices at moderate visibility levels and scales via tiling.
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Understanding the structure of nucleon excitations from their wavefunctions
Lattice calculations of nucleon wavefunctions reveal superposition nodes from mixing interpolating fields and built-in nodes intrinsic to individual s-wave Dirac components.