Topological quantum critical points exhibit anomalous dynamical scaling in boundary dynamics and defect production due to edge modes, beyond conventional Kibble-Zurek scaling.
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Machine learning reconstruction accuracy is substantially higher for spectral-edge eigenstates than for mid-spectrum eigenstates, providing a new quantitative measure of information content in many-body quantum states.
Momentum-space entanglement entropy reaches ln 2 at DQPTs via exact degeneracy p=1/2 in the post-quench eigenbasis, providing a time-independent diagnostic.
Interactions in the generalized SSH model produce interacting SPT phases, a sublattice-density-breaking phase, CDW phases, Luttinger liquids, and a gapless SPT phase with protected edge states.
A QMC-based framework tests the lattice-Bisognano-Wichmann ansatz for reconstructing entanglement Hamiltonians in 2D systems without Lorentz invariance or translational symmetry, finding good accuracy for ordinary boundaries.
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Anomalous Dynamical Scaling at Topological Quantum Criticality
Topological quantum critical points exhibit anomalous dynamical scaling in boundary dynamics and defect production due to edge modes, beyond conventional Kibble-Zurek scaling.
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Information in Many-body Eigenstates: A Question of Learnability
Machine learning reconstruction accuracy is substantially higher for spectral-edge eigenstates than for mid-spectrum eigenstates, providing a new quantitative measure of information content in many-body quantum states.