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Area of Science:

  • Computational Chemistry
  • Quantum Dynamics
  • Theoretical Physics

Background:

  • Standard Gaussian products are common for representing potential energy surfaces (PESs) and wavefunctions.
  • Basis set size requirements increase significantly with dimensionality, impacting computational efficiency.

Purpose of the Study:

  • To develop novel Gaussian basis sets for improved accuracy and efficiency in high-dimensional quantum simulations.
  • To enhance the representation of potential energy surfaces and time-dependent wavefunctions.

Main Methods:

  • Recasting Gaussian basis functions into an "additive" form for PES regression.
  • Proposing and implementing "stretched" and "tethered" Gaussian wavepacket (GWP) basis functions for quantum dynamics.
  • Evaluating convergence of time-dependent observables with new GWP basis sets.

Main Results:

  • Additive Gaussian basis functions improve fitting convergence for higher-dimensional PES regression.
  • Tethered GWP basis sets demonstrate improved convergence for time-dependent observables compared to standard GWPs.
  • The proposed GWP basis sets are compatible with existing GWP-based quantum dynamics methods.

Conclusions:

  • Novel GWP basis sets offer a pathway to more accurate quantum dynamics predictions.
  • The new basis sets enable the use of smaller basis sets for achieving higher accuracy in high-dimensional systems.
  • This work enhances the applicability of Gaussian-based methods in complex quantum simulations.