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This study introduces a novel quantum chemistry approach using Cartesian component separability for improved computational efficiency. This method significantly reduces computational resources for quantum computing applications.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Quantum Computing

Background:

  • Traditional quantum chemistry methods utilize particle separability within Slater-determinant representations.
  • This approach faces limitations in computational scalability for complex systems.

Purpose of the Study:

  • To explore an alternative quantum chemistry approach based on Cartesian component separability.
  • To develop efficient computational methods for both classical and quantum computing.

Main Methods:

  • Implementation of Cartesian component separability on classical computers using 3D grid-based methods.
  • Development of a quantum computing algorithm for first-quantized quantum computational chemistry (QCC).

Main Results:

  • Numerical calculations with four electrons achieved accuracy equivalent to full-CI with 10^15 Slater determinants.
  • The quantum computing implementation shows significant reductions in qubit count and quantum gates.

Conclusions:

  • Cartesian component separability offers a promising alternative for quantum chemistry calculations.
  • This approach has the potential to dramatically reduce the resource requirements for quantum computational chemistry.