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.
Title resolution pending
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
representative citing papers
A general framework for universal quantum state purification under energy-conservation constraints, including necessary and sufficient conditions for nonexistence and optimal protocols for depolarizing noise.
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
-
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.
-
Universal quantum state purification with energy-preserving operations
A general framework for universal quantum state purification under energy-conservation constraints, including necessary and sufficient conditions for nonexistence and optimal protocols for depolarizing noise.
-
Intermittency of dynamical phases in a quantum spin glass
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: 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.
-
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.