Introduces a minimal matchgate circuit representation for fermionic Gaussian states together with a Yang-Baxter update algorithm, then maps out entanglement transitions in unitary circuit games under braiding and generic matchgate rules.
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A hybrid policy with classical preprocessing and a parameterized quantum circuit learns effective multiqubit disentanglement scheduling from partial two-qubit reduced-state observations, with preprocessing dominating performance and wider circuits outperforming deeper ones.
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Disentangling strategies and entanglement transitions in unitary circuit games with matchgates
Introduces a minimal matchgate circuit representation for fermionic Gaussian states together with a Yang-Baxter update algorithm, then maps out entanglement transitions in unitary circuit games under braiding and generic matchgate rules.
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Learning quantum disentanglement scheduling from reduced states via modular hybrid policies
A hybrid policy with classical preprocessing and a parameterized quantum circuit learns effective multiqubit disentanglement scheduling from partial two-qubit reduced-state observations, with preprocessing dominating performance and wider circuits outperforming deeper ones.