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This study introduces a new bottom-up framework for field-theoretic simulations, enabling scalable modeling of molecular liquids directly from atomistic data. This approach overcomes limitations of traditional methods for large-scale simulations.

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Area of Science:

  • Computational Chemistry and Physics
  • Materials Science
  • Statistical Mechanics

Background:

  • Particle-based simulations face limitations in exploring large spatiotemporal scales due to computational expense.
  • Existing field-theoretic simulations often rely on top-down approximations and lack direct connection to atomistic interactions.

Purpose of the Study:

  • To develop a hierarchical bottom-up framework for constructing field-theoretic models of molecular liquids from microscopic details.
  • To generalize field-theoretic methods to arbitrary pair potentials, extending their applicability.
  • To provide a theoretical foundation for scalable, bottom-up field-theoretic simulations.

Main Methods:

  • Developed a hierarchical coarse-graining framework mapping atomistic interactions to coarse-grained potentials.
  • Utilized a perturbative expansion in reciprocal space to regularize short-range divergences.
  • Generalized the Hubbard-Stratonovich transformation using two auxiliary fields for arbitrary pair potentials.

Main Results:

  • Introduced a generalized mode theory extending bottom-up field-theoretic modeling beyond positive-definite kernels.
  • Demonstrated compatibility with existing field-theoretic sampling strategies.
  • Established a theoretical foundation combining formal derivations with numerical regularization and mode-truncation.

Conclusions:

  • The presented framework enables the construction of field-theoretic models directly from atomistic simulations.
  • This approach overcomes limitations of existing methods, paving the way for efficient, large-scale simulations of molecular systems.
  • The generalized mode theory offers a powerful tool for multiscale modeling in chemistry and physics.