Learning conservation laws in unknown quantum dynamics

ORAL

Abstract

We present a learning algorithm for discovering conservation laws given as sums of geometrically local observables in quantum dynamics. This includes conserved quantities that arise from local and global symmetries in closed and open quantum many-body systems. The algorithm combines the classical shadow formalism for estimating expectation values of observable and data analysis techniques based on singular value decompositions and robust polynomial interpolation to discover all such conservation laws in unknown quantum dynamics with rigorous performance guarantees. Our method can be directly realized in quantum experiments, which we illustrate with numerical simulations, using closed and open quantum system dynamics in a Z2-gauge theory and in many-body localized spin-chains.

Publication: arXiv:2309.00774v1

Presenters

  • Yongtao Zhan

    Caltech

Authors

  • Yongtao Zhan

    Caltech

  • Yu Tong

    California Institute of Technology

  • Hsin-Yuan Huang

    Caltech, Google Quantum AI

  • Andreas Elben

    Caltech