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 spin glasses show an intermittent eigen-spectrum with alternating bands of z-type (classical spin-glass inheriting) and x-type (x-magnetization conserving) non-ergodic extended states.
Shot-based quantum encoding embeds data as a classical probability mixture over basis states, making the quantum layer a linear map on probabilities—structurally a classical MLP.
Proposes a scalable framework for quantum decision trees in a laser-driven four-level diamond atomic system using Lie-algebraic analysis and amplitude-varied pulses with identical temporal profiles for controlled population transfer.
citing papers explorer
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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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Shot-based quantum encoding: a data-loading paradigm for quantum neural networks
Shot-based quantum encoding embeds data as a classical probability mixture over basis states, making the quantum layer a linear map on probabilities—structurally a classical MLP.
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Towards a quantum decision tree in a laser pumped four-level system
Proposes a scalable framework for quantum decision trees in a laser-driven four-level diamond atomic system using Lie-algebraic analysis and amplitude-varied pulses with identical temporal profiles for controlled population transfer.
- Universal quantum state purification under energy-preserving constraints