This ab initio approach contrasts with other computational methods that rely on empirical parameters or approximations.
By solving this fundamental equation, ab initio methods seek to accurately predict various chemical properties, including electron densities, energies, and molecular structures.
The ability to run these calculations has enabled theoretical chemists to solve a range of problems and their importance is highlighted by the awarding of the 1998 Nobel prize to John Pople and Walter Kohn.
[3] The term ab initio was first used in quantum chemistry by Robert Parr and coworkers, including David Craig in a semiempirical study on the excited states of benzene.
One needs to consider the computational cost of ab initio methods when determining whether they are appropriate for the problem at hand.
However, in practice it can scale closer to N3 as the program can identify zero and extremely small integrals and neglect them.
Methods employing this scheme are denoted by the prefix "df-", for example the density fitting MP2 is df-MP2[8] (many authors use lower-case to prevent confusion with DFT).
This sharply reduces the scaling with molecular size, a major problem in the treatment of biologically-sized molecules.
[citation needed] The most popular classes of ab initio electronic structure methods: The simplest type of ab initio electronic structure calculation is the Hartree–Fock (HF) scheme, in which the instantaneous Coulombic electron-electron repulsion is not specifically taken into account.
It is then necessary to start with a wave function that includes more than one determinant such as multi-configurational self-consistent field (MCSCF) and methods have been developed that use these multi-determinant references for improvements.
Then a new isomer with an unusual structure was predicted by Brenda Colegrove in Henry F. Schaefer III's group.
Theoretical predictions of the vibrational frequencies were crucial in understanding the experimental observations of the spectra of a mixture of compounds.
[25] Valence bond (VB) methods are generally ab initio although some semi-empirical versions have been proposed.
Sign Learning Kink-based (SiLK) Quantum Monte Carlo (website):[14] The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is based on Feynman's path integral formulation of quantum mechanics, and can reduce the minus sign problem when calculating energies in atomic and molecular systems.