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Acceleration of Self-Consistent Field Calculations Using Basis Set Projection and Many-Body Expansion as Initial
Fiona C Y Yu1, Christopher Seidl2, Elise Palethorpe1
1School of Computing, The Australian National University, Canberra, Australian Capital Territory 2601, Australia.
Optimizing initial guesses in Self-Consistent Field (SCF) calculations using basis set projection (BSP) and many-body expansion (MBE) methods significantly reduces computational time. These advanced techniques outperform traditional methods for Hartree-Fock and DFT calculations.
Area of Science:
- Computational chemistry
- Quantum chemistry
- Theoretical chemistry
Background:
- Self-Consistent Field (SCF) calculations are fundamental in quantum chemistry.
- The initial guess significantly impacts SCF convergence speed and computational cost.
- Traditional superposition of atomic densities (SAD) may not be optimal for all systems.
Purpose of the Study:
- To evaluate the efficiency of basis set projection (BSP) and many-body expansion (MBE) for SCF initial guesses.
- To introduce and assess a hybrid MBE-BSP initial guess method.
- To compare these methods against SAD for Hartree-Fock (HF) and DFT (B3LYP, MN15) calculations.
Main Methods:
- Implementation and testing of BSP, MBE, and a hybrid MBE-BSP initial guess approach.
- Assessment of computational time, including initial guess generation and SCF iterations.
- Application to systems up to 14,386 basis functions, including challenging metalloprotein and triplet states.
Main Results:
- BSP, MBE, and hybrid methods show significant improvements over SAD.
- Total wall-time reductions of up to 27.6% were achieved across HF, B3LYP, and MN15.
- Speedups were observed for difficult systems, though triplet states showed increased convergence failures.
Conclusions:
- Advanced initial guess strategies like BSP and MBE offer substantial computational savings in SCF calculations.
- The hybrid MBE-BSP method provides a competitive alternative.
- Careful consideration of initial guess methods is crucial for optimizing quantum chemical computations, especially for complex systems.
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