A new backpropagation formula for complex-valued SVD is derived, with the key contribution a novel diagonal term absent from the real SVD case.
Wavefunction positivization via automatic differentiation
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abstract
We introduce a procedure to systematically search for a local unitary transformation that maps a wavefunction with a non-trivial sign structure into a positive-real form. The transformation is parametrized as a quantum circuit compiled into a set of one and two qubit gates. We design a cost function that maximizes the average sign of the output state and removes its complex phases. The optimization of the gates is performed through automatic differentiation algorithms, widely used in the machine learning community. We provide numerical evidence for significant improvements in the average sign for a two-leg triangular Heisenberg ladder with next-to-nearest neighbour and ring-exchange interactions. This model exhibits phases where the sign structure can be removed by simple local one-qubit unitaries, but also an exotic Bose-metal phase whose sign structure induces "Bose surfaces" with a fermionic character and a higher entanglement that requires deeper circuits.
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Automatic Differentiation for Complex Valued SVD
A new backpropagation formula for complex-valued SVD is derived, with the key contribution a novel diagonal term absent from the real SVD case.