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Found 4 papers, 1 papers with code
Learning topological states from randomized measurements using variational tensor network tomography
Learning faithful representations of quantum states is crucial to fully characterizing the variety of many-body states created on quantum processors.
Many-body localized hidden generative models
Born machines are quantum-inspired generative models that leverage the probabilistic nature of quantum states.
Learning quantum symmetries with interactive quantum-classical variational algorithms
A symmetry of a state $\vert \psi \rangle$ is a unitary operator of which $\vert \psi \rangle$ is an eigenvector.
Analytic theory for the dynamics of wide quantum neural networks
We define wide quantum neural networks as parameterized quantum circuits in the limit of a large number of qubits and variational parameters.
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