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Tensor decomposed distinguishable cluster. I. Triples decomposition.

Charlotte Rickert1, Denis Usvyat1, Daniel Kats2

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The Journal of Chemical Physics
|August 8, 2025
PubMed
Summary
This summary is machine-generated.

We developed a cost-effective distinguishable cluster approximation to coupled cluster with singles, doubles, and iterative triples (DC-CCSDT) using tensor decomposition. This method significantly reduces computational cost while maintaining accuracy for quantum chemistry calculations.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Theoretical Chemistry

Background:

  • Coupled cluster methods are essential for accurate electronic structure calculations.
  • High-level coupled cluster methods like CCSDT are computationally expensive.
  • Approximations are needed to make these methods applicable to larger systems.

Purpose of the Study:

  • To present a cost-reduced approach for the distinguishable cluster approximation to coupled cluster with singles, doubles, and iterative triples (DC-CCSDT).
  • To improve the efficiency of high-level coupled cluster calculations.
  • To maintain accuracy while reducing computational scaling.

Main Methods:

  • Tensor decomposition of triples amplitudes using singular-value-decomposition (SVD) basis.
  • Density fitting or Cholesky factorization of electron repulsion integrals.
  • Approximation of triples residuals and use of approximate CC3 density matrices.

Main Results:

  • Reduced computational scaling to N6.
  • Demonstrated small SVD-error with moderate truncation thresholds, especially with CCSD(T) energy correction.
  • Confirmed linear growth of SVD-error with system size, indicating size extensivity.

Conclusions:

  • The SVD-based DC-CCSDT method offers a significant cost reduction.
  • The method maintains high accuracy comparable to more expensive methods.
  • The approach is suitable for studying larger molecular systems in quantum chemistry.