Second wave of quantum physics from a data scientist’s perspective

By Tina Cummins

My knowledge of physics consists of one semester of high school physics in the tenth grade. It was not my best subject and quantum physics seems to defy all logic. I recently read an article in The Economist (see box below) about how quantum physics are set to change several industries, including communications, meteorology, and computing.

Here, there and everywhere: Quantum technology is beginning to come into its own

Once again, the concepts that they discussed do not make logical sense to me. The fact that two entangled photons can be separated by vast distances and changing one will cause changes in the other is mind boggling. One of the comments for the article summarizes my feelings exactly, “As I read through the articles in “Here, There And Everywhere” it struck me that, the more we learn about quantum mechanics and the way the universe really works, the more physics sounds like a Dr. Seuss book. In that spirit, I propose that who ever produces the first mass-market quantum computer should name it the “US,” for “Utterly Sputter.” This was one of the inventions created in the good Doctor’s brilliant take on arms races, ‘the Butter Battle Book.’” So, they say it is true and I guess I will just have to believe them. And if it is, the implications for the field of data science have been spinning in my head since I read the article. Below are a few of my thoughts and findings on the topic during the last week.

The potential for quantum physics, particularly the concept of entanglement, to change industries seems imminent and vast.

The Smithsonian lists the following five practical applications for quantum mechanics: ultra-precise clocks, uncrackable codes, super powerful computers, improved microscopes, and biological compasses. Others have put forward quantum mechanics applications for improving the harnessing, transmission, and storage of solar power.

Within the European Union 3,400 individuals from academia and industry proclaim their beliefs for the future implications of quantum physics in Quantum Manifesto: A new era of technology (May 2016), stating, “developing Europe’s capabilities in quantum technologies will create a lucrative knowledge-based industry, leading to long-term economic, scientific and societal benefits. It will result in a more sustainable, more productive, more entrepreneurial and more secure European Union.”

So what does all of this mean to a data scientist? On the surface it means that data will become more accurate, we will receive it even faster than we do today, we will be able to secure data more efficiently, and I am sure there are many other improvements I have not yet thought of. But what does this mean for particular applications? Here are three that I have personally encountered in the last week.

I attended a NASA conference last Tuesday at the Cerritos Performing Arts Center. The talk focused on their efforts to send the first manned mission to Mars in early 2030. One of the greatest challenges is the length of time to communicate back to mission control and receive an answer. Travelling at the speed of light, communications will take approximately 12.5 minutes to travel in one direction. The response then spends another 12.5 minutes on the return. The minimum time, assuming no delay in composing a response is 25 minutes.

If entanglement can be used to transmit information faster than the speed of light, how much additional data can we obtain from space travel? How much safer can we make the transmission of that information? There are most likely many data scientist at NASA currently thinking of these issues and NASA is a large proponent of teaming with private industry, so what companies are set to take advantage of this opportunity?

A professor recently sent me a few articles on the importance of deep learning for the field of data science. As I read through these articles, I pondered how advances in quantum technologies will change deep learning and other data science computing. An article from Wired Magazine, explains that Amanda Hodgson is collecting aerial images over the Indian Ocean and using deep learning to identify sightings of sea cows, an endangered marine mammal. At this time these drone images can only capture what they see on the surface of the ocean. Will quantum mechanics allow us to gather data on the deep ocean at a much faster pace and with much greater accuracy? And does this extend for gathering data and using deep learning to analyze what is found under the earth’s surface? How can data scientist capitalize on these abilities to improve companies and society in general?

I have a lot to learn about both data science and quantum mechanics, but I am excited to see what the interaction of two brings in the next five years. The cartoon below contains the extent of my knowledge of entanglement at this point in time. I hope it helps you understand what it is and consider ways that it will impact data science and other business industries in the near future.

Written by Tina Cummins a graduate student studying data analytics and economics at the University of Montana.

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