2016
DOI: 10.1016/j.cpc.2016.08.005
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Hard-wall and non-uniform lattice Monte Carlo approaches to one-dimensional Fermi gases in a harmonic trap

Abstract: We present in detail two variants of the lattice Monte Carlo method aimed at tackling systems in external trapping potentials: a uniform-lattice approach with hard-wall boundary conditions, and a non-uniform Gauss-Hermite lattice approach. Using those two methods, we compute the groundstate energy and spatial density profile for systems of N = 4 − 8 harmonically trapped fermions in one dimension. From the favorable comparison of both energies and density profiles (particularly in regions of low density), we co… Show more

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Cited by 7 publications
(6 citation statements)
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“…[21]). Compared to systems with periodic boundary conditions, however, the computational cost at fixed system size for studies involving such trapping geometries has been found to increase [20,22] in case of our present MC approach.…”
Section: Introductionmentioning
confidence: 86%
See 1 more Smart Citation
“…[21]). Compared to systems with periodic boundary conditions, however, the computational cost at fixed system size for studies involving such trapping geometries has been found to increase [20,22] in case of our present MC approach.…”
Section: Introductionmentioning
confidence: 86%
“…A rigorous proof of this observation for general boundary conditions and observables is difficult, if possible at all. In any case, for a quantitative comparison with experimental data in the future (in particular with respect to the few-body limit), the numerical implementation of trap potentials [19,20] as used in experiments will be required. For example, harmonic traps are often considered in 1D experiments [16].…”
Section: Introductionmentioning
confidence: 99%
“…In this work we use the same quadrature points and weights as in our previous work of Refs. [29][30][31].…”
Section: Gaussian Quadraturementioning
confidence: 99%
“…In this work, we use the same quadrature points and weights as in our previous work of Refs. [33][34][35].…”
Section: Gaussian Quadraturementioning
confidence: 99%