A self-consistent systematic optimization of range-separated hybrid functionals from first principles
Abhisek Ghosal, Amlan K. Roy

TL;DR
This paper introduces a self-consistent, first-principles method to optimize range-separated hybrid functionals by relating the range-separation parameter to the system's density, improving predictive accuracy for electronic properties.
Contribution
The authors develop a novel, density-dependent optimization procedure for range-separated hybrid functionals, enhancing their accuracy and consistency from first principles.
Findings
Optimized range-separation parameter improves property predictions.
Method maintains piece-wise linearity of fractional orbital energies.
Statistical analysis confirms method's viability.
Abstract
In this communication, we represent a self-consistent systematic optimization procedure for the development of optimally tuned (OT) range-separated hybrid (RSH) functionals from \emph{first principles}. This is an offshoot of our recent work, which employed a purely numerical approach for efficient computation of exact exchange contribution in the conventional global hybrid functionals through a range-separated (RS) technique. We make use of the size-dependency based ansatz i.e., RS parameter, , is a functional of density, , of which not much is known. To be consistent with this ansatz, a novel procedure is presented that relates the characteristic length of a given system (where exponentially decays to zero) with self-consistently via a simple mathematical constraint. In practice, is obtained through an…
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