2019
DOI: 10.1016/j.jcp.2019.04.006
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Analyzing the positivity preservation of numerical methods for the Liouville-von Neumann equation

Abstract: The density matrix is a widely used tool in quantum mechanics. In order to determine its evolution with respect to time, the Liouville-von Neumann equation must be solved. However, analytic solutions of this differential equation exist only for simple cases. Additionally, if the equation is coupled to Maxwell's equations to model light-matter interaction, the resulting equation set -the Maxwell-Bloch or Maxwell-Liouville-von Neumann (MLN) equations -becomes nonlinear. In these advanced cases, numerical methods… Show more

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Cited by 16 publications
(10 citation statements)
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“…An analysis of different methods and their advantages and disadvantages can be found at Ref. [32]. Box 6.…”
Section: Properties Of the Lindblad Master Equationmentioning
confidence: 99%
“…An analysis of different methods and their advantages and disadvantages can be found at Ref. [32]. Box 6.…”
Section: Properties Of the Lindblad Master Equationmentioning
confidence: 99%
“…In order to have a CPTP splitting in Eq. (A3) and thus obtain numerical solutions compatible with physics, we must assure that all the discrete operators (namely,Ĝ t rec ,Ĝ t imp ,Ĝ t coh , andL t ) are CPTP [65]. In case of two VB levels, the recombination operator introduces recombination process from each CB level to each VB level (k = 0, k = −1) with the same characteristic time scale τ rec similarly to the case of one VB [Eq.…”
mentioning
confidence: 99%
“…which preserves all the properties of density matrixρ. There are several possibilities of obtaining a CPTP discrete Liouville-von Neumann operator, such as the Crank-Nicolson approach [66,67], Runge-Kutta methods [68][69][70], and the matrix exponential approach [26,65]. The latter technique is chosen in this paper because it adapts well to the alternatively updating nature of FDTD codes.…”
mentioning
confidence: 99%
“…[256] Furthermore, it was found that both the predictor-corrector and Runge-Kutta method yield negative populations in certain cases (e.g., long simulation end time combined with unfortunate choices for the time step size), while the matrix exponential method preserves the properties of the density matrix independent of the simulation settings. [273]…”
Section: Comparison Of Numerical Methods For the Bloch Equationsmentioning
confidence: 99%