To decode mysteries of Mars, scientists are turning to machine learning

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To decode mysteries of Mars, scientists are turning to machine learning
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A chemist turned science writer, Victoria Corless completed her Ph.D. in organic synthesis at the University of Toronto and, ever the cliché, realized lab work was not something she wanted to do for the rest of her days.

Jam packed issues filled with the latest cutting-edge research, technology and theories delivered in an entertaining and visually stunning way, aiming to educate and inspire readers of all ages"This machine learning algorithm can help us by quickly filtering the data and pointing out which data are likely to be the most interesting or important for us to examine," said Xiang"Shawn" Li, a mass spectrometry scientist in the Planetary Environments lab at NASA Goddard.

While being carried through the instrument in the gaseous phase, depending on their structure, elements, and general chemistry, different molecules in a sample mixture will interact differently with the column's stationary phase — some will linger, forming temporary, weak bonds while others will just blast on through.

The duration of each laser pulse is incredibly short, less than two nanoseconds to be precise . This ultrafast pulse ensures that the process happens very quickly, allowing the preservation of weak chemical bonds and enhancing the precision of molecular identification. "The more we do to optimize the data analysis, the more information and time scientists will have to interpret the data," said Victoria Da Poian, a data scientist at NASA Goddard who co-leads development of the machine learning algorithm."This way, we can react quickly to results and plan next steps as if we are there with the rover, much faster than we previously would have.

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