PIRSA:24040097

Video URL

https://pirsa.org/24040097

Efficient Simulation of Quantum Transport in 1D

Pollmann, F. (2024). Efficient Simulation of Quantum Transport in 1D. Perimeter Institute for Theoretical Physics. https://pirsa.org/24040097

Pollmann, Frank. Efficient Simulation of Quantum Transport in 1D. Perimeter Institute for Theoretical Physics, Apr. 18, 2024, https://pirsa.org/24040097 

          @misc{ scivideos_PIRSA:24040097,
            doi = {10.48660/24040097},
            url = {https://pirsa.org/24040097},
            author = {Pollmann, Frank},
            keywords = {Quantum Matter},
            language = {en},
            title = {Efficient Simulation of Quantum Transport in 1D},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2024},
            month = {apr},
            note = {PIRSA:24040097 see, \url{https://scivideos.org/index.php/pirsa/24040097}}
          }

Frank Pollmann Technical University of Munich (TUM)

Talk numberPIRSA:24040097
DOI10.48660/24040097
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

Tensor product states are powerful tools for simulating area-law entangled states of many-body systems. The applicability of such methods to the non-equilibrium dynamics of many-body systems is less clear due to the presence of large amounts of entanglement. New methods seek to reduce the numerical cost by selectively discarding those parts of the many-body wavefunction, which are thought to have relatively litte effect on dynamical quantities of interest. We present a theory for the sizes of “backflow corrections”, i.e., systematic errors due to these truncation effects and introduce the dissipation-assisted operator evolution (DAOE) method for calculating transport properties of strongly interacting lattice systems in the high temperature regime. In the DAOE method, we represent the observable as a matrix product operator, and show that the dissipation leads to a decay of operator entanglement, allowing us to capture the dynamics to long times. We benchmark this scheme by calculating spin and energy diffusion constants in a variety of physical models and compare to other existing methods.

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