Massively parallel implementation and approaches to simulate quantum dynamics using Krylov subspace techniques
Copyright policy )Massively parallel implementation and approaches to simulate quantum dynamics using Krylov subspace techniques
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.
16 pages, 6 figures, 3 tables
- University of Modena and Reggio Emilia Italy
- University of Pittsburgh at Bradford United States
- Technical University Eindhoven Netherlands
- University of Pittsburgh United States
- College of Staten Island United States
FOS: Computer and information sciences, Strongly Correlated Electrons (cond-mat.str-el), Strongly interacting systems, FOS: Physical sciences, Parallel numerical computation, Disordered Systems and Neural Networks (cond-mat.dis-nn), strongly interacting systems, Condensed Matter - Disordered Systems and Neural Networks, Computational Physics (physics.comp-ph), unitary quantum dynamics, distributed memory parallelism, Condensed Matter - Strongly Correlated Electrons, Computer Science - Distributed, Parallel, and Cluster Computing, Software, source code, etc. for problems pertaining to quantum theory, Krylov subspace methods, Packaged methods for numerical algorithms, Distributed memory parallelism, Distributed, Parallel, and Cluster Computing (cs.DC), Physics - Computational Physics, Unitary quantum dynamics
FOS: Computer and information sciences, Strongly Correlated Electrons (cond-mat.str-el), Strongly interacting systems, FOS: Physical sciences, Parallel numerical computation, Disordered Systems and Neural Networks (cond-mat.dis-nn), strongly interacting systems, Condensed Matter - Disordered Systems and Neural Networks, Computational Physics (physics.comp-ph), unitary quantum dynamics, distributed memory parallelism, Condensed Matter - Strongly Correlated Electrons, Computer Science - Distributed, Parallel, and Cluster Computing, Software, source code, etc. for problems pertaining to quantum theory, Krylov subspace methods, Packaged methods for numerical algorithms, Distributed memory parallelism, Distributed, Parallel, and Cluster Computing (cs.DC), Physics - Computational Physics, Unitary quantum dynamics
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