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Solving the Lindblad equation with methods from computational fluid dynamics

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arxiv 2410.10925 v1 pith:3E4SUGSV submitted 2024-10-14 quant-ph nucl-th

classification quant-phnucl-th
keywords equationlindbladsystemscomputationaldynamicstermsconditionsefficiency
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Liouvillian dynamics describes the evolution of a density operator in closed quantum systems. One extension towards open quantum systems is provided by the Lindblad equation. It is applied to various systems and energy regimes in solid state physics as well as also in nuclear physics. A main challenge is that analytical solutions for the Lindblad equation are only obtained for harmonic system potentials or two-level systems. For other setups one has to rely on numerical methods. In this work, we propose to use a method from computational fluid dynamics, the Kurganov-Tadmor central (finite volume) scheme, to numerically solve the Lindblad equation in position-space representation. We will argue, that this method is advantageous in terms of the efficiency concerning initial conditions, discretization, and stability. On the one hand, we study, the applicability of this scheme by performing benchmark tests. Thereby we compare numerical results to analytic solutions and discuss aspects like boundary conditions, initial values, conserved quantities, and computational efficiency. On the other hand, we also comment on new qualitative insights to the Lindblad equation from its reformulation in terms of an advection-diffusion equation with source/sink terms.

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  1. Functional Renormalization Group meets Computational Fluid Dynamics: RG flows in a multi-dimensional field space

    cond-mat.stat-mech 2024-12 conditional novelty 6.0 of 10

    A two-dimensional Kurganov-Tadmor finite-volume scheme accurately solves FRG flow equations for effective potentials in multi-dimensional field space, benchmarked against exact zero-dimensional path integrals and appl...

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