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Variational Learning of Quantum Ground States on Spiking Neuromorphic Hardware

13 Pages Posted: 18 Jan 2022 Publication Status: Published

See all articles by Robert Klassert

Robert Klassert

Ruprecht-Karls-Universit¨at Heidelberg - Kirchhoff-Institut f¨ur Physik

Andreas Baumbach

Ruprecht-Karls-Universit¨at Heidelberg - Kirchhoff-Institut f¨ur Physik

Mihai A. Petrovici

University of Bern - Department of Physiology

Martin Gärttner

Heidelberg University - Physikalisches Institut

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Abstract

Recent research has demonstrated the usefulness of neural networks as variational ansatz functions for quantum many-body states. However, high-dimensional sampling spaces and transient autocorrelations confront these approaches with a challenging computational bottleneck. Compared to conventional neural networks, physical-model devices offer a fast, efficient and inherently parallel substrate capable of related forms of Markov chain Monte Carlo sampling. Here, we demonstrate the ability of a neuromorphic chip to represent the ground states of quantum spin models by variational energy minimization. We develop a training algorithm and apply it to the transverse field Ising model, showing good performance at moderate system sizes (N ≤ 10). A systematic hyperparameter study shows that scalability to larger system sizes mainly depends on sample quality, which is limited by temporal parameter variations on the analog neuromorphic chip. Our work thus provides an important step towards harnessing the capabilities of neuromorphic hardware for tackling the curse of dimensionality in quantum many-body problems.

Suggested Citation

Klassert, Robert and Baumbach, Andreas and Petrovici, Mihai A. and Gärttner, Martin, Variational Learning of Quantum Ground States on Spiking Neuromorphic Hardware. Available at SSRN: https://ssrn.com/abstract=4012184 or http://dx.doi.org/10.2139/ssrn.4012184
This version of the paper has not been formally peer reviewed.

Robert Klassert

Ruprecht-Karls-Universit¨at Heidelberg - Kirchhoff-Institut f¨ur Physik ( email )

Heidelberg
Germany

Andreas Baumbach (Contact Author)

Ruprecht-Karls-Universit¨at Heidelberg - Kirchhoff-Institut f¨ur Physik ( email )

Heidelberg
Germany

Mihai A. Petrovici

University of Bern - Department of Physiology ( email )

Bern
Switzerland

Martin Gärttner

Heidelberg University - Physikalisches Institut ( email )

Heidelberg
Germany

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