Massively parallel implementation and approaches to simulate quantum dynamics using Krylov subspace techniques

  • Marlon Brenes (Contributor)
  • Vipin Kerala Varma (Contributor)
  • Antonello Scardicchio (Contributor)
  • Ivan Girotto (University of Modena and Reggio Emilia, Abdus Salam International Centre for Theoretical Physics) (Contributor)

Dataset

Description

We have developed an application and implemented parallel algorithms in order to provide a computational framework suitable for massively parallel supercomputers to study the unitary dynamics of quantum systems. We use renowned parallel libraries such as PETSc/SLEPc combined with high-performance computing approaches in order to overcome the large memory requirements to be able to study systems whose Hilbert space dimension comprises over 9 billion independent quantum states. Moreover, we provide descriptions of the parallel approach used for the three most important stages of the simulation: handling the Hilbert subspace basis, constructing a matrix representation for a generic Hamiltonian operator and the time evolution of the system by means of the Krylov subspace methods. We employ our setup to study the evolution of quasidisordered and clean many-body systems, focussing on the return probability and related dynamical exponents: the large system sizes accessible provide novel insights into their thermalization properties.
Date made available27 Sept 2018
PublisherMendeley Data

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