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This study reduces quantum circuit depth for noisy quantum computers by combining the transcorrelated (TC) approach with adaptive quantum algorithms. This enhances noise resilience and accuracy in quantum chemistry calculations.

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Area of Science:

  • Quantum Computing
  • Computational Chemistry
  • Quantum Algorithms

Background:

  • Quantum computer utility is limited by hardware noise.
  • Reducing circuit depth is key for noise resilience in hybrid quantum algorithms.

Purpose of the Study:

  • To demonstrate a method for reducing quantum circuit depth.
  • To improve noise resilience and accuracy in quantum chemistry simulations.

Main Methods:

  • Combined transcorrelated (TC) approach with adaptive quantum ansätze.
  • Implemented the TC-AVQITE method for variational quantum imaginary time evolution.
  • Calculated ground state energies for H₄, LiH, and H₂O.

Main Results:

  • Achieved energies close to the complete basis set (CBS) limit for H₄, LiH, and H₂O.
  • Significantly reduced circuit depth and the number of operators required.
  • Demonstrated improved noise resilience and accelerated convergence.

Conclusions:

  • The combined TC-AVQITE method yields compact, noise-resilient quantum circuits.
  • This approach enables accurate quantum chemistry results close to the CBS limit.
  • The method is easier to optimize and more robust against noise.