The authors introduce MuTA as a universal quantum neural network for MBQC and numerically demonstrate its ability to learn gates, classify quantum states, and process data under noise, including photonic hardware constraints.
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QUEST is a new adaptive framework for quantum state engineering that constructs states one Pauli rotation at a time to satisfy multiple expectation-value targets simultaneously.
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Measurement-based quantum machine learning
The authors introduce MuTA as a universal quantum neural network for MBQC and numerically demonstrate its ability to learn gates, classify quantum states, and process data under noise, including photonic hardware constraints.
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Quantum State Engineering Under Multiple Expectation-Value Constraints
QUEST is a new adaptive framework for quantum state engineering that constructs states one Pauli rotation at a time to satisfy multiple expectation-value targets simultaneously.