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Area of Science:

  • Quantum computing
  • Computational physics
  • Quantum chemistry

Background:

  • Calculating real-time single-particle Green's functions and nonlinear susceptibilities is crucial for understanding Hamiltonian systems.
  • Traditional methods face challenges with complex quantum systems, necessitating novel computational approaches.

Purpose of the Study:

  • To present and benchmark quantum computing approaches for calculating real-time Green's functions and nonlinear susceptibilities.
  • To demonstrate the feasibility of these methods on near-term quantum processors.

Main Methods:

  • Leveraging adaptive variational quantum algorithms for state preparation and propagation.
  • Utilizing automatically generated compact circuits for dynamical evolution.
  • Employing statevector simulators on classical hardware for benchmarking.

Main Results:

  • Accurate Green's function calculations for Fermi-Hubbard chains (4 and 6 sites) and the LiH molecule.
  • Successful calculation of third-order nonlinear susceptibilities for a quantum spin-1 model with Dzyaloshinskii-Moriya interaction.
  • Demonstrated feasibility with varying ansatz circuit depths.

Conclusions:

  • Real-time quantum computing approaches using adaptive parametrized circuits are viable for evaluating linear and nonlinear response functions.
  • These methods show potential for application with near-term quantum processors.
  • The study provides a pathway for quantum simulations in condensed matter and molecular systems.