Technology

How researchers are mapping the future of quantum computing, using the tech of today

Pacific Northwest National Laboratory computer scientist Sriram Krishnamoorthy. (PNNL Photo)

Imagine a future where new therapeutic drugs are designed far faster and at a fraction of the cost they are today, enabled by the rapidly developing field of quantum computing.

The transformation on healthcare and personalized medicine would be tremendous, yet these are hardly the only fields this novel form of computing could revolutionize. From cryptography to supply-chain optimization to advances in solid-state physics, the coming era of quantum computers could bring about enormous changes, assuming its potential can be fully realized.

Yet many hurdles still need to be overcome before all of this can happen. This one of the reasons the Pacific Northwest National Laboratory and Microsoft have teamed up to advance this nascent field.

The developer of the Q# programming language, Microsoft Quantum recently announced the creation of an intermediate bridge that will allow Q# and other languages to be used to send instructions to different quantum hardware platforms. This includes the simulations being performed on PNNL’s own powerful supercomputers, which are used to test the quantum algorithms that could one day run on those platforms. While scalable quantum computing is still years away, these simulations make it possible to design and test many of the approaches that will eventually be used.

“We have extensive experience in terms of parallel programming for supercomputers,” said PNNL computer scientist Sriram Krishnamoorthy. “The question was, how do you use these classical supercomputers to understand how a quantum algorithm and quantum architectures would behave while we build these systems?”

That’s an important question given that classical and quantum computing are so extremely different from each other. Quantum computing isn’t Classical Computing 2.0. A quantum computer is no more an improved version of a classical computer than a lightbulb is a better version of a candle. While you might use one to simulate the other, that simulation will never be perfect because they’re such fundamentally different technologies.

Classical computing is based on bits, pieces of information that are either off or on to represent a zero or one. But a quantum bit, or qubit, can represent a zero or a one or any proportion of those two values at the same time. This makes it possible to perform computations in a very different way.

However, a qubit can only do this so long as it remains in a special state known as superposition. This, along with other features of quantum behavior such as entanglement, could potentially allow quantum computing to answer all kinds of complex problems, many of which are exponential in nature. These are exactly the kind of problems that classical computers can’t readily solve — if they can solve them at all.

For instance, much of the world’s electronic privacy is based on encryption methods that rely on prime numbers. While it’s easy to multiply two prime numbers, it’s extremely difficult to reverse the process by factoring the product of two primes. In some cases, a classical computer could run for 10,000 years and still not find the solution. A quantum computer, on the other hand, might be capable of performing the work in seconds.

That doesn’t mean quantum computing will replace all tasks performed by classical computers. This includes programming the quantum computers themselves, which the very nature of quantum behaviors can make highly challenging. For instance, just the act of observing a qubit can make it decohere, causing it to lose its superposition and entangled states.

Such challenges drive some of the work being done by Microsoft Azure’s Quantum group. Expecting that both classical and quantum computing resources will be needed for large-scale quantum applications, Microsoft Quantum has developed a bridge they call QIR, which stands for “quantum intermediate representation.” The motivation behind QIR is to create a common interface at a point in the programming stack that avoids interfering with the qubits. Doing this makes the interface both language- and platform-agnostic, which allows different software and hardware to be used together.

“To advance the field of quantum computing, we need to think beyond just how to build a particular end-to-end system,” said Bettina Heim, senior software engineering manager with Microsoft Quantum, during a recent presentation. “We need to think about how to grow a global ecosystem that facilitates developing and experimenting with different approaches.”

Because these are still very early days — think of where classical computing was 75 years ago — many fundamental components still need to be developed and refined in this ecosystem, including quantum gates, algorithms and error correction. This is where PNNL’s quantum simulator, DM-SIM comes in. By designing and testing different approaches and configurations of these elements, they can discover better ways of achieving their goals.

As Krishnamoorthy explains: “What we currently lack and what we are trying to build with this simulation infrastructure is a turnkey solution that could allow, say a compiler writer or a noise model developer or a systems architect, to try different approaches in putting qubits together and ask the question: ‘If they do this, what happens?’ ”

Of course, there will be many challenges and disappointments along the way, such as an upcoming retraction of a 2018 paper in the journal, Nature. The original study, partly funded by Microsoft, declared evidence of a theoretical particle called a Majorana fermion, which could have been a major quantum breakthrough. However, errors since found in the data contradict that claim.

But progress continues, and once reasonably robust and scalable quantum computers are available, all kinds of potential uses could become possible. Supply chain and logistics optimization might be ideal applications, generating new levels of efficiency and energy savings for business. Since quantum computing should also be able to perform very fast searches on unsorted data, applications that focus on financial data, climate data analysis and genomics are likely uses, as well.

That’s only the beginning. Quantum computers could be used to accurately simulate physical processes from chemistry and solid-state physics, ushering in a new era for these fields. Advances in material science could become possible because we’ll be better able to simulate and identify molecular properties much faster and more accurately than we ever could before. Simulating proteins using quantum computers could lead to new knowledge about biology that would revolutionize healthcare.

In the future, quantum cryptography may also become common, due to its potential for truly secure encrypted storage and communications. That’s because it’s impossible to precisely copy quantum data without violating the laws of physics. Such encryption will be even more important once quantum computers are commonplace because their unique capabilities will also allow them to swiftly crack traditional methods of encryption as mentioned earlier, rendering many currently robust methods insecure and obsolete.

As with many new technologies, it can be challenging to envisage all of the potential uses and problems quantum computing might bring about, which is one reason why business and industry need to become involved in its development early on. Adopting an interdisciplinary approach could yield all kinds of new ideas and applications and hopefully help to build what is ultimately a trusted and ethical technology.

“How do you all work together to make it happen?” asks Krishnamoorthy. “I think for at least the next couple of decades, for chemistry problems, for nuclear theory, etc., we’ll need this hypothetical machine that everyone designs and programs for at the same time, and simulations are going to be crucial to that.”

The future of quantum computing will bring enormous changes and challenges to our world. From how we secure our most critical data to unlocking the secrets of our genetic code, it’s technology that holds the keys to applications, fields and industries we’ve yet to even imagine.

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