Speeding up GW Calculations to Meet the Challenge of Large Scale Quasiparticle Predictions

Gao, Weiwei; Xia, Weiyi; Gao, Xiang; Zhang, Peihong

doi:10.1038/srep36849

Cited by 74 publications

(68 citation statements)

References 39 publications

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“…A relation between the maximum number of bands and the cut-off energy for correlation has been observed for individual systems before, 36,37 although, to our knowledge, it has not been studied in a systematic way yet. It may be rationalized as follows.…”

Section: B Convergence Parametersmentioning

confidence: 89%

Automation methodologies and large-scale validation for GW : Towards high-throughput GW calculations

et al. 2017

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The search for new materials, based on computational screening, relies on methods that accurately predict, in an automatic manner, total energy, atomic-scale geometries, and other fundamental characteristics of materials. Many technologically important material properties directly stem from the electronic structure of a material, but the usual workhorse for total energies, namely density-functional theory, is plagued by fundamental shortcomings and errors from approximate exchange-correlation functionals in its prediction of the electronic structure. At variance, the GW method is currently the state-of-the-art ab initio approach for accurate electronic structure. It is mostly used to perturbatively correct density-functional theory results, but is however computationally demanding and also requires expert knowledge to give accurate results. Accordingly, it is not presently used in high-throughput screening: fully automatized algorithms for setting up the calculations and determining convergence are lacking. In this work we develop such a method and, as a first application, use it to validate the accuracy of G0W0 using the PBE starting point, and the Godby-Needs plasmon pole model (G0W GN 0 @PBE), on a set of about 80 solids. The results of the automatic convergence study utilized provides valuable insights. Indeed, we find correlations between computational parameters that can be used to further improve the automatization of GW calculations. Moreover, we find that G0W GN 0 @PBE shows a correlation between the PBE and the G0W GN 0

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Section: B Convergence Parametersmentioning

confidence: 89%

Automation methodologies and large-scale validation for GW : Towards high-throughput GW calculations

et al. 2017

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“…Although the GW approximation is recognized as one of the most accurate theories for predicting the quasiparticle properties of materials, large-scale GW calculations using the conventional approach are still very computationally expensive. Recently, we proposed an efficient energy-integration method [38] that can greatly speed up large-scale GW calculations without sacrificing the accuracy. This timely development enables fast and accurate predictions of the quasiparticle properties of SnSe under various strains.…”

Section: Computational Detailsmentioning

confidence: 99%

“…It would be extremely time consuming if the conventional method [25] were used. Recently, we developed an efficient integration method [38] that can drastically speed up fully converged GW calculations. Our method exploits the asymptotic behavior of the density of states (DOS) of materials at high energies and approximates the summation over highenergy conduction bands in both the dielectric function and self-energy calculations by a numerical integration on a sparse energy grid.…”

Section: B Atomic Origin Dependent Quasiparticle Self-energy Correctionmentioning

confidence: 99%

“…Our method exploits the asymptotic behavior of the density of states (DOS) of materials at high energies and approximates the summation over highenergy conduction bands in both the dielectric function and self-energy calculations by a numerical integration on a sparse energy grid. Using this new method, we have achieved a speed-up factor of about 10 times for small to medium-sized systems, and up to 100 times for large systems containing hundreds of atoms [38].…”

Section: B Atomic Origin Dependent Quasiparticle Self-energy Correctionmentioning

confidence: 99%

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Engineering the Near-Edge Electronic Structure of SnSe through Strains

Xia

Gao

et al. 2017

Phys. Rev. Applied

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The discovery of the unprecedented figure of merit ZT of SnSe has sparked a large number of studies on the fundamental physics of this material and further improvement through guided materials design and optimization. Motivated by its rich chemical bonding characters, unusual multi-valley electronic structure, and the sensitivity of the band edge states to lattice strains, we carry out accurate quasiparticle calculations for the low temperature phase SnSe under strains. We illustrate how the band edge states can be engineered by lattice strains, including the size and the nature of the band gap, the positions of the band extrema in the Brillouin zone, and the control of the number of electron and/or hole valleys. The distinct atomic origin and orientation of the wave functions of the different band edge states dictates the relative shift in their band energy, enabling active control of the near-edge electronic structure of this material. Our work demonstrates that strain engineering is a promising way to manipulate the low-energy electronic structure of SnSe, which can have profound influences on the optical and transport properties of this material.2

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“…The key CTSP expressions of Eqs. (21) and (32) contains sums over many high energy conduction bands which are computationally expensive to generate and manipulate. Thus, one may develop a modified terminator method 45 to reduce the number of needed high energy bands significantly, thereby reducing the O(N 3 ) prefactor.…”

Section: Discussionmentioning

confidence: 99%

Complex-time shredded propagator method for large-scale GW calculations

2020

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The GW method is a many-body electronic structure technique capable of generating accurate quasiparticle properties for realistic systems spanning physics, chemistry, and materials science. Despite its power, GW is not routinely applied to large complex assemblies due to its large computational overhead and quartic scaling with particle number. Here, the GW equations are recast, exactly, as Fourier-Laplace time integrals over complex time propagators. The propagators are then "shredded" via energy partitioning and the time integrals approximated in a controlled manner using generalized Gaussian quadrature(s) while discrete variable methods are employed to represent the required propagators in real-space. The resulting cubic scaling GW method has a sufficiently small prefactor to outperform standard quartic scaling methods on small systems ( 10 atoms) and also represents a substantial improvement over other cubic methods tested for all system sizes studied. The approach can be applied to any theoretical framework containing large sums of terms with energy differences in the denominator.

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Speeding up GW Calculations to Meet the Challenge of Large Scale Quasiparticle Predictions

Cited by 74 publications

References 39 publications

Automation methodologies and large-scale validation for GW : Towards high-throughput GW calculations

Automation methodologies and large-scale validation for GW : Towards high-throughput GW calculations

Engineering the Near-Edge Electronic Structure of SnSe through Strains

Complex-time shredded propagator method for large-scale GW calculations

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