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Counterdiabatic ADAPT-VQE for Molecular Simulation.

Diego Tancara1, Herbert Díaz-Moraga1, Dardo Goyeneche1

  • 1Facultad de Física, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile.

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|June 15, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a hybrid quantum algorithm combining adaptive derivative-assembled problem-tailored variational quantum eigensolver (ADAPT-VQE) with counterdiabatic driving. This novel approach enhances molecular simulation performance and reduces circuit depth for quantum computing applications.

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Area of Science:

  • Quantum Computing
  • Computational Chemistry
  • Quantum Algorithms

Background:

  • Variational quantum algorithms like ADAPT-VQE are robust against barren plateaus for molecular ground state estimation on NISQ devices.
  • Counterdiabatic algorithms offer improved performance and reduced circuit depth compared to standard adiabatic methods.

Purpose of the Study:

  • To propose and evaluate a hybrid quantum algorithm integrating ADAPT-VQE with counterdiabatic driving within an adiabatic evolution scheme.
  • To leverage the strengths of both ADAPT-VQE and counterdiabatic methods for more efficient molecular simulations.

Main Methods:

  • Mapping molecular Hamiltonians to qubit representations.
  • Constructing an adiabatic Hamiltonian and computing an approximate adiabatic gauge potential using nested commutators.
  • Applying the ADAPT-VQE algorithm to iteratively select operators from the computed pool for the ansatz.

Main Results:

  • The hybrid method demonstrated improved performance in molecular simulations.
  • Significant reductions in quantum circuit depth were observed compared to standalone counterdiabatic algorithms or ADAPT-VQE with fermionic excitation operators.

Conclusions:

  • The integration of ADAPT-VQE and counterdiabatic driving presents an effective hybrid paradigm for molecular simulations.
  • This combined approach offers a promising direction for advancing quantum computation in chemistry and materials science.