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Fitting high-dimensional potential energy surface using active subspace and tensor train (AS+TT) method.

Vitaly Baranov1, Ivan Oseledets1

  • 1Skolkovo Institute of Science and Technology, Novyaa St. 100, Skolkovo, Moscow 143025, Russia.

The Journal of Chemical Physics
|November 9, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a new tensor-train cross approximation method for potential energy surface fitting. Combining this with active subspaces significantly reduces computational complexity for molecular simulations.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Numerical Analysis

Background:

  • Potential energy surfaces (PES) are crucial for understanding molecular behavior.
  • Accurate PES fitting is computationally intensive, limiting its application.
  • Existing methods struggle with high dimensionality and complexity.

Purpose of the Study:

  • To develop a more efficient method for potential energy surface fitting.
  • To reduce the computational complexity of PES calculations.
  • To apply a novel tensor-train (TT) cross approximation procedure for PES fitting.

Main Methods:

  • Application of the tensor-train (TT) cross approximation procedure.
  • Integration of an affine transformation into active subspaces.
  • Utilizing active subspaces to capture the most significant PES variability.

Main Results:

  • Demonstrated the first application of TT cross approximation for PES fitting.
  • Successfully combined TT-approach with active subspaces for complexity reduction.
  • Numerical experiments confirmed the efficiency of the combined approach for water and nitrous acid molecules.

Conclusions:

  • The proposed method offers a significant reduction in computational complexity for PES fitting.
  • This approach is efficient and applicable to molecular systems like water and nitrous acid.
  • This work paves the way for more accurate and feasible PES calculations in computational chemistry.