Quantum technologies have had a meteoric rise and become a key area of prioritization for governments, academics, and businesses. Government funding commitments total almost $40 billion, while private investments since 2021 total nearly $8 billion. The US agency, National Institute of Standards and Technology, released this year three new post-quantum security standards, which governments classify as ‘critical resources’ for the economy and national defense. Meanwhile, users of quantum technologies experiment with them, from industry applications in drug development and materials science to energy grid optimization and logistics efficiency.

In the quantum industry, discoveries and innovations emerge daily, and startups are engulfed in a whirlwind of go-to-market challenges, looking for ways to stand out within an ever-expanding ecosystem. It isn’t just about standing out but navigating a new school of problems when transitioning from lab to market.

To effectively model natural phenomena at the molecular level, researchers must capture how matter and energy operate, which is an incredibly computationally intensive task. To do that, scientists use classical computers and machine learning, with or without quantum computation, to develop applicable models.