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What’s New in Quantum Computing?

May 2, 2022
Many businesses are already working on various ways to create large, stable qubits that will power the quantum future. But how close are we to this, and what do we need to do to get there?

What you’ll learn:

  • How companies can adopt a strategy of exploring quantum as an insurance policy.
  • The key industries in which quantum computers are close to bringing real business value.
  • What concepts in electronic design are most relevant to quantum computing?

Quantum computers offer tantalizing competitive advantages to those companies that master their use. Governments, academic institutions, and private companies alike are investing in a quantum future. 

As a reminder, quantum computers work with qubits—quantum bits—similar to transistors or classical bits. These qubits are operated on by quantum gates, just like logical gates in classical computers. The number of qubits in a quantum computer is a good first approximation to the power of the computer. The fidelity, or error rate, of the gates also is an important parameter. 

Multiple vendors are working on various ways—often called modalities—of creating a large number of stable qubits. Some of these qubit modalities include ion trap (IonQ), superconducting (IBM), photonic (PsiQuantum and Xanadu), cold atoms (ColdQuanta and Atom Computing), and topological (Microsoft). Among the recent announcements are IBM reaching 127 qubits, Microsoft achieving a major milestone in topological qubits, and IonQ reporting increased fidelity of its qubits.

While these are just interim waypoints, they drive us closer to being able to deliver true business value from quantum computers. Though many advances are still needed in the hardware, some are predicting that just 420 qubits would be enough to outperform supercomputers capable of 1018 floating-point operations per second. 

Another important implication is that a chasm is starting to form between quantum computers and classical computers. Generally speaking, any software that can be written for a 50-qubit quantum computer can be simulated on a classical computer. But as we get to 100, 200 qubits and beyond, such simulation is no longer possible.

We are entering uncharted territory with regard to what can be done with quantum computers, as well as with practical issues such as how to debug a program that you can’t simulate, how to test that algorithms scale up correctly with the number of qubits, and more.  

Why are Quantum Computers Considered a Strategic Technology?

The prospects of developing new compounds and better EV batteries, optimizing the supply chain to achieve substantial cost reductions, obtaining more accurate risk analysis, or gleaning new insights from quantum machine learning are exciting to business managers and CTOs alike.

The same is true not just for companies, but also for countries. Many governments see quantum computing as a strategic, enabling technology and have started national quantum programs. As of the beginning of this year, governments across the world have invested over $25 billion in quantum technology, with China ($15B) and the European Union ($7B) leading the pack.

Adm. Michael Rogers (USN, Ret.), former Director of the National Security Agency, says “Many nations around the world, particularly the most industrialized or the most developed [ones], have identified quantum as a technology that once perfected has both significant economic as well as national security impact and that there will be advantage to be gained by having those sets of capabilities. Particularly if you're able to do it earlier than some of your competition, whether that competition be from an economic perspective, from a national security perspective, or from an espionage perspective.”

Realizing the potential of quantum, several companies are adopting a strategy of exploring quantum as an insurance policy. Just like in a regular insurance policy, one pays a small amount relative to the potential cost of an adverse event.

Thus, companies are exploring proof of concepts and training their people. They believe that such relatively modest investments can help them avoid situations where they’re hopelessly behind competitors, where they’re struggling to find qualified people, or where they’re at some terrible disadvantage.

Can You Really Crack RSA Encryption with a Quantum Computer? Do These Computers Have Other Cybersecurity-Related Uses? 

Yes, quantum computers have the potential to break the RSA encryption that secures most financial transactions around the world. RSA encryption uses two large prime numbers, known only to the sender and recipient. The product of these two numbers is made public, but RSA designers were confident that no machine would be capable of factoring it without spending several billions of years. 

But quantum computers have unique properties, called superposition, entanglement, and interference. Algorithm developers utilize these properties to create algorithms that dramatically outperform their classical counterparts. One such algorithm, called Shor’s algorithm, is a method for finding prime factors of a number much more efficiently than a classical computer, and thus break the RSA code.

We expect that sufficiently large quantum computers would require only a few minutes to break RSA, whereas a classical computer might take billions of years. However, such computers are still years away, giving companies some time to prepare for this change. 

Indeed, companies have been working on communication methods called “quantum-resistant,” meaning that they could not be broken by quantum computers. For example, J.P. Morgan Chase, Toshiba, and Ciena successfully ran a proof of concept for quantum key distribution, which is a mathematically proven defense against a quantum computing cybersecurity attack. It’s important to respect the power of quantum computing, but don’t lose sleep over Shor’s algorithm breaking our financial systems overnight.

How Soon Before One Can Own a Quantum Computer?

Most quantum computers today are hosted in the cloud. And, since the rate of hardware change is so big, it makes sense to keep it this way. Though some new advances make it possible for smaller quantum computers to run at room temperature, we’re quite far from the time of personal quantum computers. 

Cloud-based quantum computers make it easy to experiment with quantum technology without spending large amounts of money to purchase them. Indeed, many companies now look at quantum as an operating expense, as opposed to a capital expense.

Hosting on the cloud makes it easier to run what’s known as hybrid algorithms. They utilize both quantum- and classical-computing methods to combine the advantages of each technology

How Soon Would Quantum Computers Deliver True Business Value, and in What Areas is this Expected? 

Although the truly groundbreaking impact of quantum computing is predicted within the decade, a broad range of industries are exploring plenty of use cases. Some companies are taking the first steps of implementations.

One sector that is embracing quantum computing is the financial arena. J.P. Morgan Chase & Co., for instance, is integrating its framework with quantum technology for portfolio optimization and pricing financial options. NTT Data has explored credit risk analysis. Goldman Sachs has a large team of quantum experts. Some organizations, such as insurance giant AXA, understood the promise of quantum and are taking the long view—performing proof of concepts, building support inside the organization, and educating multiple busines units. 

In the automotive industry, companies like Volkswagen are building internal quantum competencies. It did this after successful proof of concepts showed that using logistic optimization and quantum machine learning can minimize production costs and predict traffic patterns for autonomous vehicles. Volkswagen also used quantum computing for successful optimization of its paint shop scheduling. BMW recently completed a quantum challenge focused on multiple areas including sensor placement, configuration management, and more. 

The power of quantum computing also can be seen when simulating interactions between molecules. This type of research can help scientists better understand the nature of this world, discovering new molecules for more efficient and powerful EV batteries or for pharmaceutical use, cutting down on time spent in early phases of trials searching for possible substances. In addition, energy and logistics companies have found quantum to be an intriguing way to optimize the supply chain.

The time when quantum computers outperform their classical counterparts doesn’t rely strictly on qubit count. We also need these systems to be scalable and enduring.

Today’s quantum computers are noisy, meaning that the fidelity of their calculation can easily be impacted by slight imperfections or small environmental changes. As a result, many quantum computing experiments use hybrid quantum/classical algorithms. There’s much to gain in using quantum computers for a small portion of the calculations and letting classical computers handle the rest.

There is widespread expectation that every month, quantum companies are improving their quantum computers: more qubits, less noise, greater fidelity. While the time to true quantum utility is still unknown, it’s mostly a question of when, not if. 

Though the quantum computer for everyday people is still a dream of the future, some investments are already paying off.

What are Key Challenges in Creating and Working with Nex-Gen Quantum Computers?

The most evident challenge in getting to the point of quantum computing producing massive, real-world changes is the scalability of hardware. Real, powerful use can only be achieved with larger, more complex systems. And there’s much to do to grow these systems while reducing errors and noise.

Quantum physicists are hard at work engineering new solutions as more problems arise. They’re creating more stable qubits, more accurate quantum gates, and more compact and scalable physical systems. 

It’s not easy to build larger systems—more qubits means more particles to tend to. Each addition to the system may affect the qubits’ abilities to interact with each other productively or could introduce all sorts of errors.

There’s also the need for larger and more efficient cryogenic systems for those hardware vendors dealing with close to absolute-zero temperatures. More qubits means more wires and equipment that needs to be stored in these cold chambers, which are not easy or cheap to make. 

And as these systems scale up, the process of creating the software for larger computers becomes more difficult. Today, most software is designed by explicitly specifying the connections of qubits to quantum gates, or by cobbling together pre-written code blocks. As systems become larger, this manual process becomes difficult and will soon turn into being nearly impossible.

If we think about analogies from other disciplines, this progression isn’t surprising. It’s not difficult to write a few lines of code in assembly language, but you wouldn’t want to write a mathematical simulation this way. It’s relatively easy to connect together a few digital AND, OR, and NOR gates, but this isn’t how companies design high-end CPUs. The process of writing software will need to evolve.

What Concepts in Electronic Design Might be Applicable to Quantum Computing?

When learning about digital electronic circuits, hands-on gate-based design is crucial to develop a basic understanding of digital concepts. However, once the basics are learned, very few people design large, meaningful systems by connecting discrete logic gates.

Instead, real solutions are implemented by specifying high-level functional models, while computer-aided design solutions (such as those from Cadence or Synopsys) handle the heavy lifting of synthesizing such a system from the functional design. A computer can do a much better job at finding appropriate implementations to the functional model, minimizing the number of gates, or fulfilling other design constraints that are important to the human designer.

Companies like Classiq are starting to apply this method to quantum computing, synthesizing sophisticated gate-level quantum circuits from high-level functional models. They apply similar methods to turn models into circuits while meeting a set of constraints (such as the number of qubits or type of gates being used) and optimizing the circuit to the hardware platform of choice.

Without the right software, quantum computers might be useless, so it’s good to see that the ability to write sophisticated software progresses alongside hardware improvements.

Quantum computing is a game-changing technology for those that harness it. Don’t wait to get started.


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