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A projection-based reduced-order method for electron transport problems with long-range interactions.

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This study introduces a reduced-order model for electron transport simulations, simplifying calculations of long-range interactions. The new method accurately captures electron density profiles for efficient Coulomb potential computation.

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Area of Science:

  • Quantum mechanics
  • Computational physics
  • Materials science

Background:

  • Long-range interactions are crucial for electron transport but computationally expensive for simulations.
  • Accurate Coulomb potential calculation requires large system sizes, posing a challenge for direct computer simulations.

Purpose of the Study:

  • To develop a reduced-order approach for simulating electron transport dynamics.
  • To enable accurate computation of the Coulomb potential in large systems by addressing simulation challenges.

Main Methods:

  • Derivation of an open quantum model for the reduced density matrix.
  • Application of a Petrov-Galerkin projection to the Liouville-von Neumann equation for reduced-order dynamics.
  • Implementation of a domain decomposition strategy with logarithmic grids to include bath segments for Coulomb potential calculation.

Main Results:

  • A multi-component self-energy was derived, integrated into an effective Hamiltonian.
  • The reduced model demonstrated accuracy in simulations of a molecular junction using lithium chains.
  • The approach successfully recovers the global electron density profile.

Conclusions:

  • The reduced-order model provides an efficient and accurate method for simulating electron transport with long-range interactions.
  • This approach overcomes computational limitations in modeling complex quantum systems.
  • The method is validated for molecular junctions, suggesting broader applicability.