Today’s biggest classical computing systems contain massive amounts of processing power — to exascale and beyond — but quantum computing has the potential to accelerate that power exponentially. One day in the not-too-distant future, quantum computing could make the speed of today’s classical computing look like a letter shipped across the ocean. But it’s not just about speed – quantum computers “think” differently than classical machines, unlocking previously intractable problems.

Unlike classical computing’s binary bits (zeroes and ones), the qubits used in quantum computing can contain a superposition of every conceivable state until they’re measured (e.g., Schrödinger's cat is simultaneously alive and dead inside a box, or a coin flip is both heads and tails until it lands — both simple classical metaphors for quantum potential) – which has incredible real-world implications for science, research, and product development.

But there’s a problem. Quantum computers still have error rates that are too high to unlock any real-world applications. This is where something called quantum error correction (QEC) comes in. QEC is a set of techniques used to protect the information stored in qubits from errors and decoherence caused by noise — aka the influence of environmental variables, like temperature and power fluctuations, on the quantum system.

Cambridge, U.K.-based Riverlane is working on exactly this problem: detecting, diagnosing, and correcting quantum errors as they occur by developing a full QEC Stack called Deltaflow. 

In our first article in this series we talked about advancing the quantum landscape. Now let’s look at how quantum computing is poised to transform the world of science and engineering once the errors that these machines currently suffer from have been corrected. 

Transforming Science and Engineering

Supercomputers have already transformed science, engineering, and business, making possible advances like speedy, inexpensive DNA sequencing and high-fidelity simulation of space phenomena including supernovas. Artificial intelligence (AI) has become an additional driving force, rapidly processing machine learning data to enhance and speed up analytics and discovery.

Quantum computers are expected to have a similar impact, unlocking use cases beyond what’s possible with today’s high-performance computing (HPC) systems. Using a quantum computer we could, for example, accurately simulate complex molecules and materials — something which is outside the scope of supercomputers, where chemical modeling using classical techniques requires simplifications and approximations that limit the accuracy of results. The state-of-the-art accuracy possible with quantum computing exceeds anything that’s possible with even today’s most sophisticated classical computer.

This is where quantum simulation will help scientists and engineers broaden their research, analytics, and design and development capabilities. 

The Road to Accurate Quantum Computing

Because qubits are noisy, there’s more work ahead to lower error rates and unlock new use cases. Riverlane predicts we could start seeing early use cases as soon as 2028, by which time we expect the first error-correcting quantum computers to be available. 

As quantum computers become bigger and less noisy, we’ll be able to simulate larger and larger quantum systems, enabling scientists and engineers to improve our understanding of materials and chemical reactions. The implications for accelerated discovery in areas like chemistry and especially quantum chemistry, which studies a molecule’s subatomic particles, are significant.

Computational fluid dynamics (CFD) is another expected early use case. CFD uses complex, detailed simulations to determine how fluids move and how they interact with different materials. These simulations involve a huge number of calculations, straining the capabilities of classical computers. Quantum computers can process CFD data in parallel, dramatically speeding up simulation and producing more accurate results.

It’s not just chemistry and CFD that will benefit from a quantum impact. We can expect to see early use cases emerge in many other areas as well, including cryptography, finance, and logistics. These early use cases will start to appear in the next few years. By 2035, experts predict we’ll have reduced errors to the point where we can run trillions of error-free quantum operations — and that's when things get exciting. 

Scientific Impact

Quantum computers will allow scientists and engineers to rapidly prototype and test many different materials and chemicals, virtually testing all their physical parameters instead of having to physically make and test them in a lab. This will accelerate innovation, just as supercomputing has supercharged R&D efforts over the last 30 years. It will also be more cost-effective, drastically increasing computational ability without a corresponding price hike. 

Imagine being able to develop a new drug without laborious physical testing. Quantum computing will make that possible in a way today’s classical computers can’t, analyzing complex molecular systems efficiently and with incredible accuracy. That will benefit everyone by delivering faster, cheaper medicine and the potential for significant medical breakthroughs.

The same kind of impact could unlock quantum-enabled use cases like batteries, solar cells, and catalysts. Carbon-capture technology, supported by quantum computing, could help reduce the emission of carbon dioxide equivalents (CO₂e) — a standardized measurement of climate impact in which one metric ton equals around 2,500 miles driven in an average gas-powered car — by more than 7 gigatons per year, slowing climate change.

What to Do Now 

Start experimenting now. Companies can already allocate a portion of R&D resources to experiment with near-term quantum hardware and can set up problems in ways the computers can understand — even if existing hardware isn’t yet ready to capitalize on those opportunities. Dipping a toe in the quantum pool will help organizations be ready when quantum computing is ready for prime time.

Quantum computing will accelerate science and product development just as advancements in AI are bringing computing to a new level. Not only does quantum computing vastly increase the speed of processing information and calculating results, it also unlocks a new range of use cases thanks to its ability to simulate at the molecular scale. We’ll cover this in more detail in the next article.