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High Accuracy Transition Metal Effective Cores for Many-body Diffusion Monte Carlo

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DataCite Commons2024-02-26 更新2025-04-15 收录
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https://www.materialsdatafacility.org/detail/bennett_high_accuracy_carlo_v1.1
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Practical applications of the real-space diffusion Monte Carlo (DMC) method require the removal of core electrons, where currently localization approximations of semi-local potentials are generally used in the projector. Accurate calculations of complex solids and large molecules demand minimizing the impact of approximated atomic cores. Prior works have shown the errors from such approximations can be sizable in both finite and periodic systems. In this work, we show that a class of differential pseudopotentials, known as pseudo-Hamiltonians, can be constructed for the $3d$ transition metal atoms, entirely removing the need for any localization scheme in the DMC projector. As a proof of principle, we demonstrate the approach for the case of Co. In order to minimize errors in the pseudo-Hamiltonian at the many-body level, we generalize the recently proposed correlation-consistent pseudopotential generation scheme to successively close semi-local representations of the differential potentials. Our generation scheme successfully produces potentials tailored specifically for real space projector quantum Monte Carlo methods with low error at the many-body level, i.e., with many-body scattering properties very close to relativistic all-electron results. In particular, we show that the agreement with respect to atomic and molecular quantities reach chemical accuracy in many cases -- on par with the most accurate semi-local pseudopotentials available. Further, our pseudo-Hamiltonian generation scheme utilizes standard quantum chemistry codes designed only to work with semi-local pseudopotentials, enabling straightforward generation of pseudo-Hamiltonians for additional elements in future works.The entire set of input and output files used in this project are provided here.
提供机构:
Materials Data Facility
创建时间:
2021-12-08
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