SAMOP 2021 – scientific programme

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QI: Fachverband Quanteninformation

QI 2: Quantum Computing and Algorithms I

QI 2.7: Talk

Monday, September 20, 2021, 12:15–12:30, H5

Scalable approach to many-body localization via quantum data — •Alexander Gresch, Lennart Bittel, and Martin Kliesch — Quantum Technology Group, Heinrich Heine University Düsseldorf

We are interested in how quantum data can allow for practical solutions to otherwise difficult computational problems. Such a notoriously difficult phenomenon from quantum many-body physics is the emergence of many-body localization (MBL). So far, is has evaded a comprehensive analysis. In particular, numerical studies are challenged by the exponential growth of the Hilbert space dimension. As many of these studies rely on exact diagonalization of the system's Hamiltonian, only small system sizes are accessible.

In this work, we propose a highly flexible neural network based learning approach that, once given training data, circumvents any computationally expensive step. In this way, we can efficiently estimate common indicators of MBL such as the adjacent gap ratio or entropic quantities. Moreover, our estimator can be trained on data from various system sizes at once which grants the ability to extrapolate from smaller to larger ones. We hope that our approach can be applied to large-scale quantum experiments to provide new insights into quantum many-body physics.