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Area of Science:

  • Quantum computing
  • Computational chemistry
  • Materials science

Background:

  • Classical computers struggle to simulate complex chemical systems.
  • Hybrid quantum-classical methods show promise for determining molecular ground states.
  • Simulating time-dependent quantum processes remains a challenge.

Purpose of the Study:

  • To extend near-term quantum simulations to time-dependent chemical processes.
  • To simulate exciton dynamics in organic semiconducting molecules.
  • To develop and validate a multiscale modeling workflow for quantum dynamics.

Main Methods:

  • Developed a multiscale workflow combining molecular dynamics, quantum chemistry, and variational quantum algorithms.
  • Computed exciton dynamics in both single excitation (Frenkel Hamiltonian) and multiexciton regimes.
  • Implemented and tested on IBM Q devices, incorporating an error mitigation technique.

Main Results:

  • Demonstrated the feasibility of quantum simulations for molecular energy transfer.
  • Observed qualitative exciton dynamics on quantum hardware, despite initial errors.
  • Achieved significantly improved quantum dynamics through a novel error mitigation strategy.

Conclusions:

  • Hybrid quantum-classical approaches are viable for simulating quantum dynamics in chemical systems.
  • Error mitigation is crucial for obtaining accurate results from near-term quantum simulations.
  • This work opens new avenues for quantum-assisted modeling in chemistry, biology, and materials science.