Summary

Quantum chemistry software encompasses both computational chemistry methods and quantum algorithms that solve chemistry problems, e.g. help to determine the properties of molecules and materials for applications in synthesis or catalysis. Quantum algorithms are just being developed and promise to solve problems that cannot be solved by established computational chemistry methods like density functional theory, post-Hartree Fock methods, or molecular dynamics simulations. Quantum algorithms may help specifically to develop novel battery, solar cell, or fuel cell materials as well as semiconductors.

Viability (3)

Computational chemistry methods are well established, optimised, and used by chemical and pharmaceutical companies – the bottleneck here is a) the prohibitive costs and effort for these simulations and b) many promising quantum systems being completely intractable with these established methods. A major shift will occur with the advent of quantum computers, which are expected to simulate quantum systems a lot more efficiently, and hence, quantum chemistry will be among the first applications of quantum computers.

Drivers (4)

Macro trends like climate change, geopolitical tension, or the newly emerging space race drive the development of materials with fine-tuned properties costs and thus quantum chemistry software. In addition, since nature is inherently quantum, the development of quantum computers will boost quantum chemistry simulations and tackle specific problems of high value that were formerly intractable.

Novelty (4)

Established computational chemistry methods will continue to address the majority of materials. Novel quantum algorithms will help to discern the properties of materials with strong correlations, e.g., those described by the Fermi-Hubbard model, that will be relevant to applications e.g. for battery or solar cells materials. This may greatly improve existing materials and develop entirely new and innovative materials.

Diffusion (2)

Existing computational chemistry methods will be further adopted, commoditized, and standardized through cloud offerings. Entirely new algorithms will be developed for quantum computers, and the quest to demonstrate the first economically viable quantum algorithm for chemistry is on. Once created, these quantum algorithms will spread quickly as it’s pure software and thus easy to distribute, and it doesn’t depend on which quantum hardware platform wins.

Impact (4) High certainty

In a high-impact scenario quantum chemistry is one of the most valuable uses of quantum computers as it can speed up development of new materials and molecules. Quantum algorithms could unlock $20-50B in value in catalyst design alone. In the short-term, simulation cost and reduction in lab experiments will drive material development e.g. improve the efficiency of solar cells and batteries by a few percent. Breakthroughs possible once quantum computers are available, driving larger, step-sized gains.

Timing (2025-2030) Medium Certainty

Computational chemistry methods are getting already today more accessible through the cloud. Yet, the advent of NISQ computers will be a real game changer – and the timeline does not have to wait for fault-tolerance and can therefore be valuable within a 3-5 year period.