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Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

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Published on: June 8, 2018

Benchmark calculations for reduced density-matrix functional theory.

N N Lathiotakis1, Miguel A L Marques

  • 1Theoretical and Physical Chemistry Institute, National Hellenic Research Foundation, 48 Vass. Constantinou Avenue, Athens, Greece. lathiot@eie.gr

The Journal of Chemical Physics
|June 6, 2008
PubMed
Summary
This summary is machine-generated.

Reduced density-matrix functional theory (RDMFT) offers a new way to study electron correlation. Recent RDMFT functionals show excellent accuracy for molecular energies, rivaling traditional methods.

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Last Updated: Jun 23, 2026

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Area of Science:

  • Computational chemistry
  • Quantum mechanics
  • Materials science

Background:

  • Electron correlation poses a significant challenge in quantum chemistry.
  • Standard density functional theory (DFT) relies on approximations for exchange-correlation functionals.
  • Reduced density-matrix functional theory (RDMFT) presents a promising alternative for accurately describing electron correlation.

Purpose of the Study:

  • To benchmark recent approximations of exchange-correlation functionals within RDMFT.
  • To evaluate the performance of RDMFT functionals against established quantum chemistry and DFT methods.
  • To assess the accuracy of RDMFT for predicting total and atomization energies of molecules.

Main Methods:

  • Implementation and application of various RDMFT functionals.
  • Benchmarking against a diverse set of molecular systems.
  • Comparison of calculated total energies and atomization energies.

Main Results:

  • Recent RDMFT functionals demonstrate high accuracy in energy calculations.
  • RDMFT results show strong agreement with standard quantum chemistry approaches.
  • The performance of RDMFT functionals is competitive with state-of-the-art DFT methods.

Conclusions:

  • RDMFT is a viable and accurate method for addressing electron correlation.
  • The evaluated RDMFT functionals provide reliable predictions for molecular energies.
  • RDMFT shows significant potential as a powerful tool in computational chemistry.