Solving complex computational problems in chemistry is a precursor for scaling up a compound design and process upgrades. Even the strongest computers used nowadays are limited in precision when used to describe molecular structures and chemical reactions. This is because chemical systems follow the laws of quantum mechanics on the atomic and subatomic level. The complexity of the wave function of a quantum system grows exponentially with the number of system units, which means that classical computers cannot precisely model these systems.  

Increased computation and simulation power of quantum computers pictures them as a high potential to upgrade solving of computational issues in chemistry. This would significantly advance development of new molecules, materials, process optimization… In broader context, that further relates to the applications in medicine, biology, pharmacology, genomics…  

Therefore, quantum computational chemistry is under expansion. Such a growth implies a need for increase in capabilities.

Many hardware issues are yet to be tackled to enable advance quantum chemistry (together with many other) quantum simulations. These are mainly related to the system stability and error corrections. However, this does not hinder the necessity to develop theory and methods behind the quantum chemistry algorithms and test the proof of concepts tackling subjects and applications of interest. Quantum computers could do a lot of us but this technology requires us to build a completely new logic behind it.