For now, absolutely nothing. But researchers and firms are optimistic about the applications.
). That molecule is related to triphenyl sulfonium , a photo-acid generator used in lithography that reacts to light of certain wavelengths. Understanding its molecular and photochemical properties could make the manufacturing technique more efficient, for instance.
Financial applications, such as risk management, as well as materials science and logistics optimization also have a high chance of benefiting from quantum computation in the near term, says Biercuk. Still, no one is taking their eyes off the longer-term, more speculative applications — including quantum versions of machine learning.
Quantum machine learning is nowhere near being able to outperform classical algorithms, but there is room to explore, Kim says.
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