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The challenge of predicting protein folding---a pivotal task in biology, chemistry, and drug design---has yet to be fully surmounted, due to the complexity of finding the lowest-energy configuration of the constituent amino acids. The current study provides a hybrid classical-quantum digitized counterdiabatic approach that enhances the performance of existing quantum algorithms, producing remarkable results even in the NISQ era. This innovative solution opens up possibilities for tackling complex problems in biology and chemistry, pushing the boundaries of what is achievable with quantum computing.
Chandarana et al. (Wed,) studied this question.