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Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
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https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
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Data underpinning "Local integrals of motion and the stability of many-body localisation in disorder-free systems"

Authors: Bertoni, C; Eisert, J; Kshetrimayum, A; Nietner, A; Thomson, S J;

Data underpinning "Local integrals of motion and the stability of many-body localisation in disorder-free systems"

Abstract

Many-body localisation in disordered systems in one spatial dimension is typically understood in terms of the existence of an extensive number of (quasi)-local integrals of motion (LIOMs) which are thought to decay exponentially with distance and interact only weakly with one another. By contrast, little is known about the form of the integrals of motion in disorder-free systems which exhibit localisation. Here, we explicitly compute the LIOMs for disorder-free localised systems, focusing on the case of a linearly increasing potential. We show that while in the absence of interactions, the LIOMs decay faster than exponentially, the addition of interactions leads to the formation of a spatially extended plateau. We study how varying the linear slope affects the localisation properties of the LIOMs, finding that there is a significant finite-size dependence, and present evidence that adding a weak harmonic potential does not result in typical many-body localisation phenomenology. By contrast, the addition of disorder has a qualitatively different effect, dramatically modifying the properties of the LIOMs. Based on this, we speculate that disorder-free localisation is unlikely to be stable at long times and for large systems.

Dataset and metadata prepared by S J Thomson, using the PyFlow package (https://github.com/sjt48/PyFlow). Please direct all enquiries to SJT. The dataset contains a README file with details on how to use the data, as well as example Jupyter notebooks demonstrating how to plot various quantities.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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