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Nature Physics
Article . 2024 . Peer-reviewed
License: CC BY
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Article . 2024
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https://dx.doi.org/10.17169/re...
Other literature type . 2024
License: CC BY
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Nature Physics
Article . 2024 . Peer-reviewed
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Unravelling quantum dynamics using flow equations

Authors: S. J. Thomson; J. Eisert;

Unravelling quantum dynamics using flow equations

Abstract

AbstractThe study of many-body quantum dynamics in strongly correlated systems is extremely challenging. To date, few numerical methods exist that are capable of simulating the non-equilibrium dynamics of two-dimensional quantum systems, which is partly due to complexity theoretic obstructions. In this work, we present a technique able to overcome this obstacle, by combining continuous unitary flow techniques with the newly developed method of scrambling transforms. We overcome the assumption that approximately diagonalizing the Hamiltonian cannot lead to reliable predictions for relatively long times. Rather, we show that the method achieves good accuracy in both localized and delocalized phases and makes reliable predictions for a number of quantities including infinite-temperature autocorrelation functions. We complement our findings with rigorous incremental bounds on the truncation error. Our approach shows that, in practice, the exploration of intermediate-scale time evolution may be more feasible than is commonly assumed, challenging near-term quantum simulators.

Country
Germany
Keywords

Computational science ; Information theory and computation ; Mean field theory, Computational science, 500 Naturwissenschaften und Mathematik::530 Physik::530 Physik, Information theory and computation, Statistical physics, thermodynamics and nonlinear dynamics, Condensed-matter physics, Theoretical physics

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    popularity
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    Top 10%
    influence
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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!
4
Top 10%
Average
Average
Green
hybrid