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Deep Learning Beyond Lefschetz Thimbles · Around

2017

Deep Learning Beyond Lefschetz Thimbles

Alexandru, Andrei, Bedaque, Paulo, Lamm, Henry et al.

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The generalized thimble method to treat field theories with sign problems requires repeatedly solving the computationally-expensive holomorphic flow equations.

We present a machine learning technique to bypass this problem.
The central idea is to obtain a few field configurations via the flow equations to train a feed-forward neural network.
The trained network defines a new manifold of integration which reduces the sign problem and can be rapidly sampled.

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2015

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