A parallel quantum eigensolver for quantum machine learning
A parallel quantum eigensolver for quantum machine learning, Fan Yang, Dafa Zhao, Chao Wei, Xinyu Chen, Shijie Wei, Hefeng Wang, Guilu Long, Tao Xin
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A parallel quantum eigensolver for quantum machine learning, Fan Yang, Dafa Zhao, Chao Wei, Xinyu Chen, Shijie Wei, Hefeng Wang, Guilu Long, Tao Xin
<p>Whether ultramarine, cerulean, Egyptian or cobalt, blue pigments have colored artworks for centuries. Now, seemingly out of the blue, scientists have discovered a new blue pigment that uses less cobalt but still maintains a brilliant shine. Though something like this might only happen once in a blue moon, the cobalt-doped barium aluminosilicate colorant described in <em>ACS Applied Optical Materials </em>withstands the high temperatures found in a kiln and provides a bright color to glazed tiles.</p>
Scientists are using artificial intelligence, which has become more popular, to swiftly scan current medicines for new uses or forecast which compounds could alleviate diseases.
<p>Artificial intelligence has exploded in popularity and is being harnessed by some scientists to predict which molecules could treat illnesses, or to quickly screen existing medicines for new applications. Researchers reporting in <em>ACS Central Science</em> have used one such deep learning algorithm, and found that dihydroartemisinin (DHA), an antimalarial drug and derivative of a traditional Chinese medicine, could treat osteoporosis as well. The team showed that in mice, DHA effectively reversed osteoporosis-related bone loss.</p>
While Siri and Google Assistant may be able to organize meetings on demand, they currently lack the social intelligence to prioritize the appointments on their own.