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Partitioning Quantum Chemistry Simulations with Clifford Circuits.

Philipp Schleich1,2,3, Joseph Boen3,4, Lukasz Cincio3

  • 1Department of Computer Science, University of Toronto, Toronto M5S 1A1, Canada.

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This summary is machine-generated.

This study explores efficient quantum chemistry calculations using variational quantum eigensolvers. It introduces novel, classically efficient ansatz to overcome hardware limitations for complex molecular simulations.

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Area of Science:

  • Quantum Computing
  • Computational Chemistry
  • Quantum Information Science

Background:

  • Current quantum computing hardware is limited by few, noisy qubits, restricting complex molecular simulations.
  • Near-term quantum computers face challenges in performing accurate quantum chemistry calculations for larger molecules.

Purpose of the Study:

  • To investigate the limits of classical and near-classical treatment for quantum chemistry calculations within the variational quantum eigensolver framework.
  • To develop efficient ansatz for parametrized wavefunctions suitable for near-term quantum hardware.

Main Methods:

  • Utilized classically efficient product ansatz, adapting the separable-pair ansatz form.
  • Incorporated post-treatment to manage subsystem interactions.
  • Employed purely Clifford or near-Clifford circuits to manage Hamiltonian terms and used simulated annealing and genetic algorithms for circuit optimization.

Main Results:

  • Demonstrated a method to enhance the capabilities of near-term quantum computers for molecular simulations.
  • Showcased the molecule-dependent circuit structure optimization for improved accuracy.
  • Investigated the reach and limitations of the proposed methodology on various molecules.

Conclusions:

  • The developed approach offers a pathway to perform more complex quantum chemistry calculations on current noisy quantum hardware.
  • Physically motivated, classically efficient ansatz combined with optimized circuit structures can mitigate limitations of limited qubit availability.
  • Further research can explore the application of this methodology to a broader range of chemical systems.