All Outputs (3)

Time evolution of uniform sequential circuits (2023)
Journal Article
Astrakhantsev, N., Lin, S., Pollmann, F., & Smith, A. (2023). Time evolution of uniform sequential circuits. Physical Review Research, 5(3), Article 033187. https://doi.org/10.1103/physrevresearch.5.033187

Simulating time evolution of generic quantum many-body systems using classical numerical approaches has an exponentially growing cost either with evolution time or with the system size. In this work we present a polynomially scaling hybrid quantum-cl... Read More about Time evolution of uniform sequential circuits.

Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks (2023)
Journal Article
Liu, Y., Smith, A., Knap, M., & Pollmann, F. (2023). Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks. Physical Review Letters, 130(22), Article 220603. https://doi.org/10.1103/physrevlett.130.220603

Quantum convolutional neural networks (QCNNs) have been introduced as classifiers for gapped quantum phases of matter. Here, we propose a model-independent protocol for training QCNNs to discover order parameters that are unchanged under phase-preser... Read More about Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks.

Numerical simulation of non-Abelian anyons (2023)
Journal Article
Kirchner, N., Millar, D., Ayeni, B. M., Smith, A., Slingerland, J. K., & Pollmann, F. (2023). Numerical simulation of non-Abelian anyons. Physical Review B, 107(19), Article 195129. https://doi.org/10.1103/physrevb.107.195129

Two-dimensional systems such as quantum spin liquids or fractional quantum Hall systems exhibit anyonic excitations that possess more general statistics than bosons or fermions. This exotic statistics makes it challenging to solve even a many-body sy... Read More about Numerical simulation of non-Abelian anyons.