Uncovering the value of quantum technologies
By Jeffrey Cohen, Alex Khan, and Clark Alexander: Chicago Quantum, November 24, 2019
How do we know if a new technology has value? We look at how it is used by others and if it creates economic or strategic value. Would it help our organization? If we look at all the applications of that technology, will they evolve into applications we might use? Is there a trend?
We are sharing quantum computing and quantum technology use cases to help start a discussion on how quantum computing and quantum technologies may drive business value today, and as it matures.
Our hypothesis is that potential clients understand how it might improve business efficiency, increase revenue, drive customer engagement, achieve an organizational mission, or discover an innovation. We also see value created through increased speed, reduced risk, or lower variability of performance.
Our methodology is to research and share publicly available information about quantum computing, quantum technologies such as position, navigation and timing (PNT). We discover public references to a quantum project, then work to complete our understanding of the effort with publicly available information. For example, we might find public presentations from a conference, or GitHub projects, LinkedIn posts, a company website page, or an article published. We have been able to contact some of the project leads. To date, we have found 37 public use cases where we have enough information to discuss them.
On October 18, 2019, we published a summary presentation on our website, created five YouTube videos, and will release key findings in this article.
The use cases are grouped into three categories.
The first are optimization cases which look to maximize or minimize an objective function given constraints. Most of these cases run on annealing systems, either quantum annealing or simulated annealers. We see the most cases in this category. This can be to minimize travel distance, or avoid conflicts and backlogs by maximizing capacity and system throughput.
The second are the other cases (not optimization) that run on quantum computers or simulators. There is diversity in these cases. Some run on quantum gate based systems (universal quantum computers) and others on quantum annealers. A common use case is to support analysis and discovery of new products in chemistry, life sciences, or materials sciences.
The third are cases which run on more fundamental quantum elements (like streams of photons, streams of random numbers, quantum dots, or technology similar to atomic clocks). We see a few types of dual-use applications in fields like communications, sensing, and securing communications.
Many of the use cases are to optimize a repeatable business or logistical process. These could be in logistics or transportation, directing autonomous vehicles, or recommender systems. Others are to reduce expected variability of outcomes with an expected return (e.g., select advertising or optimizing a financial portfolio).
Another form of the optimization problem is to sequence and schedule in a way to reduce total elapsed time and/or effort spent. We have seen this in automotive robots, pick lists for a custom manufacturer, scheduling repair shop work orders, listing items in an eStore, or settling financial transactions. It still comes back to maximizing or minimizing a condition while meeting constraints.
The next set of use cases are more diverse. They are problems where today’s human processes or classical computers provide a result, but where there is significant room for improvement. The challenge is that existing methods are either too slow or too expensive. As we try to implement these algorithms in a quantum model, we learn and improve our way to solve them. Sometimes, just looking at a problem through a quantum computing lens gives us insight to solve it classically in a better way.
One example is verification and validation, which is like system testing. It is challenging enough to debug and release a product like a web or phone application, or even a software — hardware system like a smart-phone. However, today’s system are getting more complex. We need to do the same testing to a commercial airliner as we do to a smart-phone, but with exponentially more components and lines of code.
Another example is to work within 5G networks to help a significantly larger amount of cell phone data traffic to flow. Quantum computing is being evaluated to improve the data flow (speed and accuracy) at the cell phone and cell tower interface.
Another example is improving the resolution or reducing the time for magnetic resonance imaging (MRI) to either make the experience more comfortable, or to provide better diagnostic information to the physician. In the example of Case Western University working with Microsoft, they were able to progress on the MRI challenge using quantum inspired learnings on Microsoft Azure.
The first few examples above take a problem and attempt to solve it using graph-based, or graph theoretical structures. This is another way that quantum computers can be used to solve problems.
The final set of use cases leverage quantum physics and core properties of quantum technologies. Some of these core properties include true randomness which comes from a physical source, or the collapse of a wave function when observed, enhanced sensitivity in sensing and reading magnetic fields, the ability to detect entangled photons over long distances (they stay entangled) or the way colors are based on specific energy levels.
There are a range of use cases. These can have wide-ranging impacts on our quality of life, health, safety and security. We discuss these to show the wide range of benefits from quantum technologies. Many of which have dual uses, both to support the economy and enhance security. These cases give us confidence that this technology will continue to receive support and investment.
Here are a few examples: 1/ use the inherent randomness from quantum effects to secure communications, and ensure fair lotteries and games of chance. 2/ use quantum effects (observation collapses the wave function) to create un-hackable network connections. 3/ improve our ability to see and sense things over large and small distances, whether over the horizon or within the human body. A fun application is to make televisions, LEDs and lighting systems brighter, with better colors and that use less energy and cost to make and operate.
Finally, atomic clocks are single qubit systems, and can be used for global coordination.
In conclusion, we found a concerted effort from many companies in taking their existing processes to model them on quantum computers. Some early examples show promise especially using quantum random number generation, while others will require development of quantum algorithms and improvements in hardware.
With the Google team proving quantum advantage, the pace of change and effort will increase with teams, like ours, building intuition in solving new and unique problems, or finding unique quantum solutions without trying to map back to classical ways.
We see companies investing in proving the technology works to solve real-world challenges. They are investing in learning about how quantum computing can drive business value. They look at optimizing a business process or an ordering of options. For financial services, we see companies looking to calculate risk or evaluate assets using quantum computing. On the ‘mission’ side, we see investments to help with navigation, sensing, communications and timing.
In the physical sciences, we see companies performing advanced calculations to discover new drugs, chemicals, and materials to meet real-world applications. In one case, we know of a company working with quantum computing to find proteins to create drugs that fit precisely into a human body where the drug is needed most. We know of other large chemical companies doing exploratory research in materials science, to precisely calculate what previously had to be estimated.
So, what would you want to try and model on a quantum computer?
For more information, please download our eBook here, watch our five-part video series (1st video) here, or contact Jeffrey Cohen to discuss details on any specific case, or for help creating your quantum business advantage here.
Three members of Chicago Quantum (SM) supported this effort. Jeffrey Cohen performed the research into quantum use cases. Alex Khan and Clark Alexander contributed to the writing of this article.
Reference for photograph:
Towards Real Time Multi-robot Routing using Quantum Computing Technologies
HPC Asia 2019, January 2019, Guangzhou, China, pages 111–119. ISBN: 978–1–4503–6632–8 doi>10.1145/3293320.3293333
Photo: Page 35, Quantum Applications, by D-Wave Systems