1960
DOI: 10.1063/1.1731166
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Radial Distribution Functions from the Born-Green Integral Equation

Abstract: Comparisons are made between solutions to the Born-Green integral equation and radial distribution functions obtained by the Monte Carlo method by Wood and Parker for the Lennard-Jones potential. It is observed that multiplying the particle separation distance in the Born-Green case by a constant factor improves the agreement for loops beyond the first.

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Cited by 131 publications
(33 citation statements)
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“…This approximation has been used in the calculation of the pair distribution function for both an equilibrium system [16] and a non-equilibrium system under shear [17]. With this approximation, the evolution equation for the pair distribution function is derived as…”
Section: Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…This approximation has been used in the calculation of the pair distribution function for both an equilibrium system [16] and a non-equilibrium system under shear [17]. With this approximation, the evolution equation for the pair distribution function is derived as…”
Section: Modelmentioning
confidence: 99%
“…This equation is called the Born-Green equation [15], which has been solved numerically [16]. Then, writing…”
Section: Modelmentioning
confidence: 99%
“…At a particular iteration step i, the result from the previous iteration, ϕ i−1 (r), and the analytic result (24) are used as input to compute the r.h.s of Eq. (20). The resulting potential ϕ(r) is then used to produce the input for the next iteration step by mixing it with ϕ i−1 (r) according to…”
Section: Green's Function Methodologymentioning
confidence: 99%
“…This yields a new estimate h 1 (r) which is input to the closure relation to yield an improved estimate c 1 (r). This procedure usually only converges at low densities, and in order to obtain convergence at higher densities, it is necessary to mix old and new estimates to obtain a converged solution [1,24,25]. When using the Fourier space version Eq.…”
Section: Standard Algorithmsmentioning
confidence: 99%