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We developed a new computational method, hMACGIC-QUAPI, to accurately simulate complex quantum systems interacting with their environment. This scalable approach overcomes previous memory limitations for studying non-Markovian quantum dynamics.

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Area of Science:

  • Quantum dynamics
  • Computational physics
  • Chemical physics

Background:

  • Simulating quantum dynamics in non-Markovian environments is computationally challenging.
  • Structured environments with sharp resonances cause long-time system-bath correlations.
  • Existing methods struggle with memory bottlenecks for these complex systems.

Purpose of the Study:

  • To present a scalable, distributed memory implementation of the MACGIC-QUAPI method.
  • To address memory limitations using a premerging algorithm and hash-based look-up (hMACGIC-QUAPI).
  • To enable accurate simulations of dissipative quantum dynamics in structured non-Markovian environments.

Main Methods:

  • Developed a distributed memory implementation using MPI for path spreading.
  • Implemented efficient path management with a hash map for constant access time.
  • Utilized mask-assisted coarse graining of influence coefficients (MACGIC)-quasi-adiabatic propagator path integral (QUAPI).

Main Results:

  • The hMACGIC-QUAPI method demonstrates scalability and preserves numerical accuracy.
  • Simulations reveal resonance splitting and sideband emergence due to strong system-environment interactions.
  • The method accurately captures non-Markovian system-bath correlations, outperforming perturbative approaches.

Conclusions:

  • The hMACGIC-QUAPI method offers a versatile and efficient solution for simulating complex quantum dynamics.
  • It overcomes memory bottlenecks, enabling large-scale studies of systems with structured non-Markovian environments.
  • The open-source implementation facilitates broader research in quantum dynamics and condensed matter physics.