A Lean 4 machine-verified proof establishes that depth-p QAOA on the ring of disagrees attains approximation ratio (2p+1)/(2p+2) exactly.
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Equivariant sp-QCNN encodes general symmetries with group theory, splits circuits at pooling layers to preserve symmetry while enabling parallel measurements, and shows improved efficiency and trainability over standard equivariant QCNNs in noisy quantum data classification.
Numerical study of five symmetry-preserving HVAs for Z2 gauge theory finds overparametrization eliminates local minima and loss decay rate scales linearly with number of parameters.
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A Machine-Verified Proof of a Quantum-Optimization Conjecture
A Lean 4 machine-verified proof establishes that depth-p QAOA on the ring of disagrees attains approximation ratio (2p+1)/(2p+2) exactly.
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Resource-efficient equivariant quantum convolutional neural networks
Equivariant sp-QCNN encodes general symmetries with group theory, splits circuits at pooling layers to preserve symmetry while enabling parallel measurements, and shows improved efficiency and trainability over standard equivariant QCNNs in noisy quantum data classification.
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Symmetries and overparametrization properties of Hamiltonian variational ansatzes for the $(1+1)$d $\mathbb{Z}_2$ lattice gauge theory
Numerical study of five symmetry-preserving HVAs for Z2 gauge theory finds overparametrization eliminates local minima and loss decay rate scales linearly with number of parameters.