A boundary integral method for computing electron repulsion integrals in heterogeneous dielectric environments
Abstract
We present a boundary integral method for evaluating electron repulsion integrals (ERIs) in dielectric environments of piecewise constant permittivity. This generalizes conventional bare-Coulomb ERIs by incorporating screening from structured dielectric surroundings, such as the substrates and/or encapsulating layers present in modern two-dimensional-material devices. We formulate the problem as a second-kind boundary integral equation for the induced surface charge on the dielectric interfaces,...
Description / Details
We present a boundary integral method for evaluating electron repulsion integrals (ERIs) in dielectric environments of piecewise constant permittivity. This generalizes conventional bare-Coulomb ERIs by incorporating screening from structured dielectric surroundings, such as the substrates and/or encapsulating layers present in modern two-dimensional-material devices. We formulate the problem as a second-kind boundary integral equation for the induced surface charge on the dielectric interfaces, and discretize it with a Nyström method on adaptively refined panels. The incident potential generated by each smooth orbital source density is evaluated by a Fourier truncated-kernel method in or near to its source box, and by fast multipole method (FMM) accelerated quadrature farther away. The linear system is solved by a Krylov iteration also accelerated by the FMM. We focus on cuboidal device geometries, and retain efficiency at high aspect ratios via close-to-touching panel quadratures. We further develop a distributed pipeline that computes the full ERI tensor, comprising thousands of orbital pairs, embedded in a single dielectric geometry. We demonstrate the method on an effective three-layer graphene slab over a Si/SiO heterojunction, focusing on the central graphene layer represented by -like orbitals, retaining the non-negligible entries of the -sized ERI tensor. The model is resolved on million surface unknowns, achieving a relative error of , at a cost of node-hours.
Source: arXiv:2610.26745v1 - http://arxiv.org/abs/2610.26745v1 PDF: https://arxiv.org/pdf/2610.26745v1 Original Link: http://arxiv.org/abs/2610.26745v1
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Oct 20, 2026
Mathematics
Mathematics
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