Quantum local random networks and the statistical robustness of quantum scars
Federica Maria Surace, Marcello Dalmonte, Alessandro Silva

TL;DR
This paper explores the emergence and robustness of quantum scars in random Hamiltonian networks, identifying network motifs linked to localized eigenstates and analyzing how their number scales with system size.
Contribution
It introduces the concept of statistical scars in quantum local random networks and links their emergence to network motifs and energy signatures, providing a new understanding of their robustness.
Findings
Statistical scars are associated with network motifs and appear at specific energies.
The number of statistical scars scales with system size depending on network connectivity.
A transition exists between regimes with and without scalable scars, defining their statistical robustness.
Abstract
We investigate the emergence of quantum scars in a general ensemble of random Hamiltonians (of which the PXP is a particular realization), that we refer to as quantum local random networks. We find a class of scars, that we call "statistical", and we identify specific signatures of the localized nature of these eigenstates by analyzing a combination of indicators of quantum ergodicity and properties related to the network structure of the model. Within this parallelism, we associate the emergence of statistical scars to the presence of "motifs" in the network, that reflects how these are associated to links with anomalously small connectivity. Most remarkably, statistical scars appear at well-defined values of energy, predicted solely on the base of network theory. We study the scaling of the number of statistical scars with system size: by continuously changing the connectivity of the…
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