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Updated: Jun 17, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

A density-division embedding potential inversion technique.

O Roncero¹, A Zanchet, P Villarreal

¹Instituto de Física Fundamental, C.S.I.C., Unidad Asociada UAM-CSIC, Serrano 123, 28006 Madrid, Spain. oroncero@imaff.cfmac.csic.es

The Journal of Chemical Physics

|December 23, 2009

Summary

This summary is machine-generated.

A novel embedding potential method partitions electronic density for quantum chemistry calculations. This approach ensures accurate v-representability and improves upon previous techniques for describing interactions like van der Waals forces.

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Last Updated: Jun 17, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

Area of Science:

Quantum Chemistry
Computational Physics
Electronic Structure Theory

Background:

Accurate electronic density partitioning is crucial for complex molecular systems.
Existing embedding potential methods face challenges in simultaneously determining density and potential.
Previous techniques required pre-partitioned densities, limiting their applicability.

Purpose of the Study:

To develop a new method for partitioning electronic density into subsystems.
To introduce an iterative approach for obtaining embedding potentials.
To ensure the v-representability of partitioned electronic densities.

Main Methods:

A modified Fock equation incorporating an iterative embedding potential is solved.
The embedding potential is derived by minimizing density differences between the total system and subsystems.
The method is validated on a linear H(10) chain and for van der Waals interactions.

Main Results:

The proposed method simultaneously determines electronic density partition and the embedding potential.
Obtained orbitals are localized within subsystems, enabling local electronic correlation.
Accurate van der Waals interactions (approx. 12 meV) between H(10) chains and H(2) molecules were reproduced.

Conclusions:

The new iterative embedding potential method offers a significant improvement for density partitioning.
This approach guarantees v-representability, enhancing the reliability of calculations.
The method is effective for describing intermolecular interactions and can be integrated with existing ab initio programs.