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Efficient spectral computation of the stationary states of rotating Bose-Einstein condensates by the preconditioned nonlinear conjugate gradient method

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  • معلومة اضافية
    • Contributors:
      Systems with physical heterogeneities : inverse problems, numerical simulation, control and stabilization (SPHINX); Inria Nancy - Grand Est; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria); Institut Élie Cartan de Lorraine (IECL); Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS); Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS); École des Ponts ParisTech (ENPC); MATHematics for MatERIALS (MATHERIALS); École des Ponts ParisTech (ENPC)-École des Ponts ParisTech (ENPC)-Inria de Paris; Laboratoire de Mathématiques Raphaël Salem (LMRS); Université de Rouen Normandie (UNIROUEN); Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS); ANR-12-MONU-0007,BECASIM,Simulation numérique avancée pour les condensats de Bose-Einstein : Modèles numériques déterministes et stochastiques, Calcul haute performance, Simulation d'expériences physiques(2012)
    • بيانات النشر:
      HAL CCSD
      Elsevier
    • الموضوع:
      2017
    • Collection:
      Université de Lorraine: HAL
    • نبذة مختصرة :
      International audience ; We propose a preconditioned nonlinear conjugate gradient method coupled with a spectral spatial dis-cretization scheme for computing the ground states (GS) of rotating Bose-Einstein condensates (BEC), modeled by the Gross-Pitaevskii Equation (GPE). We first start by reviewing the classical gradient flow (also known as imaginary time (IMT)) method which considers the problem from the PDE standpoint, leading to numerically solve a dissipative equation. Based on this IMT equation, we analyze the forward Euler (FE), Crank-Nicolson (CN) and the classical backward Euler (BE) schemes for linear problems and recognize classical power iterations, allowing us to derive convergence rates. By considering the alternative point of view of minimization problems, we propose the preconditioned gradient (PG) and conjugate gradient (PCG) methods for the GS computation of the GPE. We investigate the choice of the preconditioner, which plays a key role in the acceleration of the convergence process. The performance of the new algorithms is tested in 1D, 2D and 3D. We conclude that the PCG method outperforms all the previous methods, most particularly for 2D and 3D fast rotating BECs, while being simple to implement.
    • Relation:
      info:eu-repo/semantics/altIdentifier/arxiv/1611.02045; hal-01393094; https://hal.science/hal-01393094; https://hal.science/hal-01393094/document; https://hal.science/hal-01393094/file/paper.pdf; ARXIV: 1611.02045
    • الرقم المعرف:
      10.1016/j.jcp.2017.04.040
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.83664E4C