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Operator-Guided Model Reduction for Generative Sampling in Lattice Field Theory
Neural generative samplers for lattice field theory can be costly to train and evaluate. When they miss modes or assign them incorrect relative weights, biased observables do not reveal which collective variables are responsible. We project a trained flow-matching velocity onto vector fields built f
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