From Theory to Fabrication: An Inflection Point for Quantum Computing

The year 2017 was a transition period for quantum computing when it moved from theoretical research to engineering and development. Though there is no quantum computer today that can beat conventional supercomputers, yet the rate of progress indicates that it will be able to outperform them in the next five to seven years.

Quantum computing has been a major research topic for multiple companies for the past few years, with D-Wave, IBM, and Intel all launching their systems and enhancing them at a fairly rapid rate. This month at the Consumer Electronics Show (CES), Intel unveiled its new 49-qubit quantum computer, which represented a step towards “quantum supremacy.”

A few leading companies are already using various techniques to make quantum hardware available for purchase and shared use; others are working to offer cloud-based quantum computing platforms and software applications to access quantum computing power.

While the realization of viable quantum computers for everyday business use is some years off, advances in silicon chips may form the foundation of commercially affordable machines in the not-too-distant future. Some universities, such as Princeton, the Delft University of Technology in the Netherlands, and the University of New South Wales (UNSW) in Sydney, Australia are working on fast-moving projects in this field.

Quantum computing principles

A quantum computer utilizes the physical phenomena of superposition and entanglement of subatomic particles like electrons. Superposition allows a single quantum bit (qubit); say an electron, to store both 0 and 1 values simultaneously until observed when it collapses to one of the two states. Statistically, 50 percent of the time the result is 0, and 1 for the other 50 percent, when there is no bias. Quantum computing circuitry puts appropriate bias to the qubits, causing changes in their probabilities, which leads to the solution of a problem.

When two or more qubits are entangled, they correlate to each other. Then the state of one qubit may depend on the state of another. That allows a quantum computer to create arrays of interconnected switches that are more complex than normal digital circuitry with only on/off positions. Because of properties of superposition and entanglement, a quantum computer needs a much lesser number of qubits than the number of bits needed in a conventional computer to solve a similar problem.

Quantum computers operate very differently from classical computers. A classical computer is like a large calculator that is very good at step by step analysis and solution of a problem. However, a quantum computer solves a problem by a network of complex nodes. Thus there is no sequential operation involved, and there is little need for conventional programming; the trick lies in setting up appropriate connections between the qubits to solve a given problem. That may be done manually or by programs running on conventional computers. Additionally, quantum computers do not produce exact solutions but generate results that are statistically correct. So, each problem needs to be run multiple times to generate a correct (most probable) solution.

Types of problems where quantum computer has the advantage

The type of problems where quantum computing does not offer any significant advantage over conventional computing includes normal mathematical calculations where there are a limited number of input variables that do not interact in such ways as to create huge number combinations that need to be processed. These are common problems that we face in every life and in controlling many of the manufacturing processes.

Types of problems that are more suited for quantum computation are those that a have a number of interacting variables. Combinatorial explosions happen there creating a large number of intermediate variables. That may be too large for a classical computer to tackle within a reasonable time frame. For example:

• Cracking the most sophisticated encryption in use today
• Optimization of a traveling salesman problem
• Big data search
• Analyzing the US power grid
• Analyzing the internal wiring of a brain
• Portfolio optimization and fraud detection by financial services companies
• Improved weather forecasting
• Improved traffic routing

Examples In manufacturing industries include:

• Optimization of chemical and biochemical reactors, where there are a number of interacting variables
• Simulation of a chain of reactions needed to design new and complex compounds and materials
• Optimization of oil exploration and production
• Optimizing and managing supply chains
• Asset degradation modeling and predictive maintenance

Major players in the design and fabrication of quantum computing hardware and software

D-Wave 

D-Wave is the only company that is presently offering quantum computers in the open market. It sold its first system in 2011, and its latest version has 2,000 qubits, which is called the D-Wave 2000Q. However, D-Wave computers are not general purpose and can only be used for specific applications, such as optimization, sampling, anomaly detection, and image analysis. Customers of D-Wave’s quantum computers include Los Alamos National Laboratory, Google, NASA, Lockheed Martin, and Virginia Tech.

Google

Google built a 9-qubit processor in 2015. Late last year, Google, in collaboration with researchers from University of California Santa Barbara, has built a 50-qubit chip, which is now in the test phase.

IBM

In 2016, IBM launched its IBM Q with six qubits as an attempt to build commercial quantum computers for business and science. IBM has made this quantum platform accessible to researchers and developers around the world. Then, in May 2017, the platform was upgraded with a 17 qubit processor. IBM-Q also offers a quantum computer simulation environment where large conventional computers are used to simulate quantum computer functions. To date, about 300,000 quantum experiments have been run by developers on this platform. In November 2017, IBM announced the fabrication of a 50-qubit prototype.

Intel

In October 2017 Intel announced its 17-qubit chip, the first quantum computing hardware by a chipmaker. The processor was developed in conjunction with its Dutch partners, QuTech and Delft University of Technology. Intel claimed that its expertise in fabrication, control electronics, and architecture would give them a competitive edge. Apparently, that wasn’t just boasting as it unveiled a 49 qubit processing chip at the Consumer Electronics Show in January 2018 in Las Vegas. In three months, the company has managed to scale their technology to the level competitors like Google and IBM who have been working for years.

Microsoft

Back in 2005, Microsoft launched “Station Q” a research lab focused on quantum computing, but whose progress remained unknown for years. In September 2017, Microsoft announced the launch of a new coding language and computing simulators for quantum computing. This programming language and simulators will be available in late 2018.

Rigetti

Founded in 2014, Rigetti is a California-based private company specialized in quantum hardware and software with a mission to build the world’s most powerful computer. In June 2017, Rigetti announced its 8-qubit chip and a software environment, called Forest. Rigetti’s quantum roadmap includes a chip with over 50 qubits, which is expected to be ready within a year.

Major Users of quantum computing

Airbus: In 2015, Airbus established a research team, tasked with the study of potential applications of quantum technologies. It seeks to use quantum computing systems to tackle some of the problems that are inherent to its activity, which includes data storage and sorting, satellites imagery analysis, and the development of new materials for its aircrafts.

Biogen: As a leading biotech company, Biogen is seeking to advance the development of drugs for neurological and neurodegenerative diseases. In June 2017, it announced the teaming up with Accenture Labs and 1QBit, a quantum software startup, to speed up the discovery of new drugs.

Lockheed Martin: Lockheed has partnered with D-Wave since its launch and was its first client. It acquired a D-Wave One system in late 2010. Then, in 2013, it upgraded its system to the 512-qubit D-Wave Two, and once again, in 2015, to the 1000+ qubit D-Wave 2X. Lockheed has partnered with the University of Southern California, to create USC-Lockheed Martin Quantum Computation Center, where the D-Wave quantum system is being used to explore “adiabatic quantum computing.”

Raytheon: Raytheon is working to put quantum technology to good use, from computers and sensors to imaging technology and cybersecurity. BBN Technologies, a research subsidiary of Raytheon, in a joint effort with IBM Research has demonstrated in May 2017 the first proofs of quantum computing advantage over conventional computing.

Make your business ready for quantum computing

The quantum revolution is coming; therefore, it is essential for business leaders to make sure that their businesses are ready for this cutting-edge technology. You may start learning about this technology while identifying applications that will give the largest returns. That will enable your business to deploy quantum-based optimizations faster. Those who move ahead with experimentation and innovation will be prepared to take advantage of the opportunities that the quantum revolution is bound to bring.

Plan for actions:

• Learn quantum computing fundamentals and the tools available to harness them.
• Identify application areas where quantum computation can make a difference.
• Try solving some of your problems in quantum simulation environments that are available now

• Create a plan for scaling up the applications with the advancement in quantum computing and reevaluate it throughout the year.
• Set an advanced technology group to monitor trends and generate monthly reports.
• For the longer term: Build device independent applications that may run on quantum computers as they evolve.

About the Author

Asish Ghosh is a Control Systems Engineer with over 40 years of professional experience. He held various research, engineering, and consulting positions while working for ICI in England, The Foxboro Company, and ARC Advisory Group in Massachusetts. His recent publications include “Dynamic Systems for Everyone – Understanding How Our World Works” a book on system science for engineers and the general public.