Brief history of computational chemistry: Three distinct eras and the relative importance of theoretical insights and computing power in advancing the field

The past influence the present and future; for example, in computational chemistry, simplifying assumptions and approximations important to problem solving in the pre-computing era remains relevant today in allowing simulation of larger systems with reasonable amount of computer time. By highlighting significant milestones in efforts (theoretical and simulation) aimed at understanding the nature of chemical bond, a short essay traces the development and evolution of electronic structure calculation methods over the years. Placing the various methods along a time line and observing the temporal relationships between them reveals the clustering of methods into three distinct eras, each defined by their relative reliance on theory, approximations, experiment data and computing power for problem solution. Specifically, building of theoretical models for explaining spectroscopic emission spectra laid the foundation of the field when theory lagged behind experiment. Promulgation of the Schrodinger equation shifted the focus of the field towards developing methods for solving it. However, difficulty in solving the equation during the pre-computing era spawned an entire subfield seeking to develop increasingly refined methods for obtaining approximate solutions. Specifically, semi-empirical methods rely on experiment data to supply parameter values inaccessible through direct calculations from first principles, while approximate methods use simplifications to obviate the need for calculating cross interacting terms. Availability of large amount of inexpensive computing power in recent years brought forth ab initio (first principles) simulation methods capable of calculating electronic structure properties of large systems (e.g., long chain biomolecules) with few or no simplifying assumptions and at increasingly finer scales. However, high power computational resources are not easily accessible outside of research institutes. Hence, in what is known as coarse-graining, contemporary focus has been on developing methods for simulating, in high resolution, only important aspects of the problem while leaving other areas of the problem definition (i.e., simulation model) to coarser techniques, which in total, facilitates probing realistic system sizes for answers in sync with reality. The delineated chronological thread also provides the backdrop for asking counterfactual (“what if”) questions examining, from a historical vantage point, the relative roles of computing power and theoretical intuition in the development of computational chemistry. Contrary to widespread notions that advances in computational chemistry are solely potentiated by increases in computing power, the essay argues that the relationship between theoretical imagination and computing power is more nuanced: specifically, the two exert their influence at different junctures in the field’s evolution.