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Moment expansion of the linear density-density response function.

Arne Scherrer1, Daniel Sebastiani1

  • 1Institute of Theoretical Chemistry, Martin-Luther-University Halle-Wittenberg, Von-Danckelmann-Platz 4, 06120, Halle, (Saale), Germany.

Journal of Computational Chemistry
|November 13, 2015
PubMed
Summary
This summary is machine-generated.

We developed a new method to simplify calculations of electronic response functions. This approach reduces computational complexity for studying molecular interactions, improving accuracy for systems like water molecules.

Keywords:
density functional perturbation theorydensity-density response functionmolecular interactionmultipoles

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Area of Science:

  • Computational chemistry
  • Quantum mechanics
  • Electronic structure theory

Background:

  • The linear density-density response function is crucial for understanding electronic properties and intermolecular interactions.
  • Calculating this function for complex systems is computationally demanding due to its nonlocal nature.

Purpose of the Study:

  • To develop a computationally efficient method for calculating the linear density-density response function.
  • To reduce the dimensionality of the response function while retaining essential physical information.

Main Methods:

  • A low-rank moment expansion of the linear density-density response function.
  • Spectral decomposition using iterative Lanczos diagonalization within linear density functional perturbation theory.
  • Derivation of a unitary transformation to generate irreducible representations with respect to SO(3) rotations.

Main Results:

  • A dimensionality reduction of the density-density response function, condensing physically relevant information.
  • Separation of contributions to the electronic response density based on multipole moments.
  • Accurate computation of the electronic response density for a water molecule.

Conclusions:

  • The proposed low-rank moment expansion offers a significant reduction in computational cost for electronic response function calculations.
  • This method effectively captures key information for modeling intermolecular interactions.
  • The scheme demonstrates high performance and accuracy, particularly for molecular systems.