Quantum Computing for Data Science

Published May. 05, 2021
Updated Oct. 18, 2021

What is quantum computing?

To better understand quantum computers, we must first know the basics of classical computing. First off, a classical computer is essentially the one you are using to read this post! They use voltage states across transistors to make their computations. This is called encoding data.

Unlike classical computers, quantum computers utilize the quantum states of subatomic particles for their encoding. Quantum computers exploit superposition and entanglement to perform computations of complex problems in a more efficient manner than a classical computer. The end result is a computer that can calculate very large and complex problems in minutes that would normally take a classical computer YEARS to compute!


How will they impact our daily lives?

Quantum computers will most likely NOT replace classical computers for most tasks, at least not at first. We will most likely see them implemented in large, complex computation tasks for large companies or organizations. Tasks such as modeling molecules and how they interact with the human body, or finding the optimal routes for all package deliveries simultaneously. It’s better to think of quantum computers as something that will work in parallel with classical computers rather than something that will replace them altogether.


What does this mean for data scientists? (Why should we care?)

While the research and development are still relatively young, we should expect to see the commercial use of quantum computers within the next few years. Once this happens, development will really begin to accelerate and quantum computers will become commonplace before we know it. Thus, data scientists should begin to get involved now in order to be a driving force in the industry.


What is the Unit for Data Science and Analytics is doing?

We are looking to help advance the research of quantum computers for use in data science problems. This includes staying on top of current technology trends & developments, working with other staff & faculty within ASU on the topic, and developing algorithms that could be used on quantum computers.


How can I get involved?

Contact us directly at datascience@asu.edu. We work with any and all students & faculty on cutting edge research in data science. We look forward to hearing from you!



Classical Computing

Quantum Computing

Performs calculations using transistors, which represent data as either a 0 or a 1.

Performs calculations using qubits, which represent data as any value between 0 and 1.

Computational power increases linearly as more transistors are added.

Computational power increases exponentially as more qubits are added.

Have low error rates and can operate at room temperature.

Currently have high error rates and must operate at extremely cold temperatures.

Well suited for everyday tasks such as video streaming, word processing, and other basic computations.

Well suited for optimization problems, simulations, and other exponentially complex computing tasks.


Further Learning:

Introductory resources


Advanced resources


Technology leaders