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

Autor: Vipin Kerala Varma, Marlon Brenes, Ivan Girotto, Antonello Scardicchio
Přispěvatelé: Fluids and Flows, Computational Multiscale Transport Phenomena (Toschi)
Rok vydání: 2017
Předmět:
FOS: Computer and information sciences
Theoretical computer science
Quantum dynamics
Matrix representation
Parallel algorithm
General Physics and Astronomy
FOS: Physical sciences
01 natural sciences
010305 fluids & plasmas
Computational science
Condensed Matter - Strongly Correlated Electrons
Quantum state
0103 physical sciences
Distributed memory parallelism
010306 general physics
Massively parallel
Mathematics
Unitary quantum dynamics
Strongly Correlated Electrons (cond-mat.str-el)
Strongly interacting systems
Krylov subspace
Disordered Systems and Neural Networks (cond-mat.dis-nn)
Condensed Matter - Disordered Systems and Neural Networks
Computational Physics (physics.comp-ph)
Computer Science - Distributed
Parallel
and Cluster Computing
Hardware and Architecture
Krylov subspace methods
Distributed memory
Distributed
Parallel
and Cluster Computing (cs.DC)
Physics - Computational Physics
Subspace topology
Zdroj: Computer Physics Communications, 235, 477-488. Elsevier
ISSN: 0010-4655
DOI: 10.48550/arxiv.1704.02770
Popis: 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 on 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.
Comment: 16 pages, 6 figures, 3 tables
Databáze: OpenAIRE
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