In the 1D attractive Fermi polaron the quasi-particle residue decays as Z = W N^{-2 δ_F² / π²} with δ_F the Bethe-ansatz phase shift at the Fermi edge and W obtained numerically.
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Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.
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Explicit proof of Anderson's orthogonality catastrophe for the one-dimensional Fermi polaron with attractive interaction
In the 1D attractive Fermi polaron the quasi-particle residue decays as Z = W N^{-2 δ_F² / π²} with δ_F the Bethe-ansatz phase shift at the Fermi edge and W obtained numerically.
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Getting large-scale quantum neural networks ready for quantum hardware
Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.