Publication record · 18.cifr/2017.kandala.vqe-hardware-efficient
18.cifr/2017.kandala.vqe-hardware-efficientQuantum computers can be used to address electronic structure problems and problems in materials science and condensed matter physics that are beyond the capabilities of classical computers. Here we report the experimental optimization of Hamiltonian problems with up to six qubits and more than one hundred Pauli terms, realized on a superconducting quantum processor.
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Barren plateaus in hardware-efficient ansatze limit scaling to larger systems. Noise-aware optimization, symmetry-preserving variants, and integration with classical pre-training are natural extensions. Coherence time improvements are needed before tackling molecules beyond BeH2.