A machine learning framework finds splitting method coefficients that are provably second-order convergent and more efficient than classical integrators for limited computational budgets on the Schrödinger equation.
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Learning efficient and provably convergent splitting methods
A machine learning framework finds splitting method coefficients that are provably second-order convergent and more efficient than classical integrators for limited computational budgets on the Schrödinger equation.