Simulating 2D topological quantum phase transitions on a digital quantum computer

ORAL

Abstract

Efficient preparation of many-body ground states is key to harnessing the power of quantum computers in studying quantum many-body systems. In this talk, we present a simple method to design exact linear-depth parameterized quantum circuits which prepare a family of ground states across topological quantum phase transitions in 2D. We achieve this by constructing ground states represented by isometric tensor networks (isoTNS), which form a subclass of tensor network states that are efficiently preparable. By continuously tuning a parameter in the wavefunction, the many-body ground state undergoes quantum phase transitions, exhibiting distinct quantum phases. We illustrate this by constructing isoTNS paths with bond dimension D=2 interpolating between distinct symmetry-enriched topological (SET) phases. At the transition points, the wavefunctions are related to a gapless point in some classical statistical models. Furthermore, the critical wavefunctions support power-law correlation along certain spatial direction. We provide explicit parametrized local quantum circuits for the paths and show that the isoTNS can also be efficiently simulated by a holographic quantum algorithm requiring only a quantum hardware in one dimension lower than the isoTNS.

*Y.-J.L. and F.P. acknowledge support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy–7EXC–2111–390814868 and the TRR 360 – 492547816, the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 771537), as well as the Munich Quantum Valley, which is supported by the Bavarian state government with funds from the Hightech Agenda Bayern Plus.

Publication: arXiv:2312.05079

Presenters

  • Yu-Jie Liu

    • Massachusetts Institute of Technology

Authors

  • Yu-Jie Liu

    • Massachusetts Institute of Technology
  • Kirill Shtengel

    • University of California, Riverside
  • Frank Pollmann

    • TU Munich