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Found 4 papers, 0 papers with code
Demonstration of Robust and Efficient Quantum Property Learning with Shallow Shadows
This combined theoretical and experimental analysis positions the robust shallow shadow protocol as a scalable, robust, and sample-efficient protocol for characterizing quantum states on current quantum computing platforms.
Digital-analog quantum learning on Rydberg atom arrays
We propose hybrid digital-analog learning algorithms on Rydberg atom arrays, combining the potentially practical utility and near-term realizability of quantum learning with the rapidly scaling architectures of neutral atoms.
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.
