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Area of Science:

  • Quantum Chemistry
  • Computational Physics
  • Materials Science

Background:

  • Selected configuration interaction (sCI) methods are crucial for accurate quantum chemical calculations.
  • Phaseless auxiliary field quantum Monte Carlo (ph-AFQMC) offers a powerful approach for solving the electronic structure problem.
  • Integrating sCI with ph-AFQMC presents computational challenges for large systems.

Purpose of the Study:

  • To develop and present efficient algorithms for incorporating sCI trial wave functions into ph-AFQMC.
  • To optimize computational performance for ph-AFQMC calculations with extended configuration interaction expansions.
  • To enable the use of up to a million configurations in ph-AFQMC trial states.

Main Methods:

  • Development of novel algorithms for efficient sCI trial state generation and utilization within ph-AFQMC.
  • Implementation of techniques to manage computational cost for large configuration expansions.
  • Strategies to mitigate scalability issues by restricting sCI to active spaces and leveraging error cancellation.

Main Results:

  • Demonstrated efficient use of sCI trial wave functions in ph-AFQMC, allowing for up to 10^6 configurations.
  • Showed a minimal increase in computational cost (approx. 3x) for 10^4 configurations compared to a single configuration.
  • Established a method to systematically study the convergence of the phaseless approximation in ph-AFQMC.

Conclusions:

  • The developed algorithms significantly enhance the capability of ph-AFQMC by enabling the use of complex sCI trial states.
  • The favorable scaling of computational cost allows for rigorous assessment of ph-AFQMC accuracy and systematic error reduction.
  • Restricting sCI to active spaces provides a viable strategy for applying ph-AFQMC to large, complex systems.