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Bulletin of the American Physical Society

Quantum Simulator Package (QuSP): A Robust and Flexible Integrated Modeling Environment for Entangled Quantum Dynamics

Lincoln D. Carr

Published May 27, 2019• 0 citations
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Simulating the dynamics of molecular excitons in complex nanophotonic environments requires integrating rigorous electromagnetic simulations with accurate treatments of open quantum system dynamics. In this work, we develop MQED-QD (Macroscopic Quantum Electrodynamics for Quantum Dynamics), a robust computational package for simulating exciton dynamics in arbitrary dielectric and plasmonic environments. Based on the MQED framework, the package offers a unified workflow for constructing the dyadic Green's functions from classical electromagnetic solvers, parametrizing quantum master equations, and propagating the time evolution to determine the molecular subsystem's dynamical properties. To demonstrate the package's capabilities, we simulate exciton transport within a one-dimensional molecular chain near a silver nanostructure, including benchmarking against planar surfaces and exploring the influence of silver nanorods. Our results reveal that surface plasmon polaritons on nanorods dramatically enhance long-range dipole-dipole interactions, accelerating exciton delocalization and yielding higher participation ratios compared to planar geometries. By elucidating accurate molecular exciton dynamics in conjunction with nanophotonics and plasmonics, MQED-QD provides a powerful, open-source package that facilitates the rational design of nanoscale architectures.
This paper investigates a novel approach to model complex physical systems utilizing a hybrid model fusion technique based on quantum entanglement. The core claim is that this method, employing intricate entanglement-based integration of model fragments, dramatically improves model accuracy and computational efficiency compared to traditional model fusion strategies. We explore how entanglement can enhance the representation of correlations within the system, leading to a more robust and flexible model. The study employs a series of simulations to demonstrate the effectiveness of this approach in simulating [mention specific system, e.g., fluid dynamics, molecular dynamics], showcasing a significant increase in precision and reduced computational cost.