skip to main content

Search for: All records

Award ID contains: 1931366

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract

    In this paper, we report an implementation of the quantum trajectory‐guided adaptive Gaussian (QTAG) method in a modular open‐source Libra package for quantum dynamics calculations. The QTAG method is based on a representation of wavefunctions in terms of a quantum trajectory‐guided adaptable Gaussians basis and is generalized for time‐propagation on multiple coupled surfaces to be applicable to model nonadiabatic dynamics. The potential matrix elements are evaluated within either the local harmonic or bra‐ket‐average (linear) approximations to the potential energy surfaces, the latter being a more practical option. Performance of the QTAG method is demonstrated and discussed for the Holstein and Tully models, which are the standard benchmarks for method development in the area of nonadiabatic dynamics.

    more » « less
  2. Abstract

    We report the implementation of a hierarchical equations of motion (HEOM) module within the open‐source Libra software. It includes the standard and scaled HEOM algorithms for computing the dynamics of open quantum systems interacting with a harmonic bath. The module allows the computing of the evolution of the reduced density matrix, as well as spectral lineshapes. The truncation, filtering, and “update list” schemes, as well as OpenMP parallelization, allow for further computational saving. The package is written in a mix of C++ and Python languages, delivering the best compromise between user friendliness and efficiency. The Python layer of the package takes advantage of standard Python libraries, such as h5py, which allows efficient storage and retrieval of the generated results. The package can be seamlessly used within Jupyter notebooks; its careful design shall provide the maximal convenience and intuitiveness to its users.

    more » « less
  3. Free, publicly-accessible full text available August 1, 2024
  4. null (Ed.)
  5. null (Ed.)