Random states from symplectic and orthogonal unitaries show exponentially large strong state complexity and near-orthogonality, with average-case hardness for learning circuits from these groups.
Barren plateaus in quantum neural network training landscapes.Nature communications, 9(1):4812, 2018
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A quantum framework introduces C-Estimator and E-Estimator for classical covariance matrices using variational circuits, with regularization to ensure positive definiteness and mitigate barren plateaus, validated via simulations.
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On the Complexity of Quantum States and Circuits from the Orthogonal and Symplectic Groups
Random states from symplectic and orthogonal unitaries show exponentially large strong state complexity and near-orthogonality, with average-case hardness for learning circuits from these groups.
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Quantum Learning of Classical Correlations with continuous-domain Pauli Correlation Encoding
A quantum framework introduces C-Estimator and E-Estimator for classical covariance matrices using variational circuits, with regularization to ensure positive definiteness and mitigate barren plateaus, validated via simulations.