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We developed a practical MP2 accuracy predictor (MAP) by analyzing deviations from the linear behavior of the exact adiabatic connection curve. This method accurately assesses MP2 performance for various molecular systems with minimal computational overhead.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Theoretical Chemistry

Background:

  • Second-order Møller-Plesset perturbation theory (MP2) is a widely used method for approximating electron correlation.
  • MP2 approximates the exact adiabatic connection (AC) curve with a straight line, which can lead to inaccuracies.

Purpose of the Study:

  • To develop a reliable indicator for predicting the accuracy of MP2 calculations.
  • To introduce a practical MP2 accuracy predictor (MAP) with negligible computational cost.

Main Methods:

  • Constructing an indicator based on the deviation of the exact HF AC curve from linear behavior.
  • Utilizing interpolation along the HF AC to transform the indicator into a practical predictor.
  • Applying the predictor to dissociation into nondegenerate ground state fragments.

Main Results:

  • The developed indicator effectively predicts MP2 accuracy.
  • The MP2 accuracy predictor (MAP) is computationally inexpensive.
  • The method demonstrates applicability to systems dissociating into nondegenerate ground states.

Conclusions:

  • The novel MP2 accuracy predictor (MAP) offers a reliable and efficient way to assess MP2 performance.
  • This approach enhances the utility of MP2 calculations in quantum chemistry.
  • The MAP is validated on benchmark datasets like S22 and S66.