Quantum Benchmarking: My Qubits Are Better Than Yours

When it comes to computers, technologies for bits are not created equal.

It shows in a quick stroll through your local electronics store. Photographers can take an SD card, while gamers can take discs for their home console. Meanwhile, down the next aisle, a back-to-school shopper will pick up the latest Macbook with “SSD.” Ultimately, every photo, video game, or final report comes down to a list of 0s and 1s. depends entirely on the specifics of the application.

Finding the right qubit for the right job

Today, we are still in the early stages of quantum computing, so it is hard to believe that we will ever have to make these kinds of choices: what type of qubit (quantum bit) is suitable for what job? But over the next decade – as quantum computers hit the market – we expect to see a similar breakthrough. Key to all of this will be the ability to objectively compare performance against claims made.

Just as there are many ways to store a traditional bit, there are many types of qubits. today’s advanced technologies include qubits built from atoms, ions, photons, superconductors and ions. Each of these technologies scores differently on key metrics such as speed, scalability, reliability, interoperability, robustness, and cost. Importantly, no one type of qubit wins in all categories. In fact, many of these measures are in opposition, for example, the fastest qubits also tend to be the least scalable.

Borrowing from a rich benchmarking tradition

In the absence of a single dominant qubit type, we should instead assess the ability of each qubit type to support different use cases like machine learning, quantum dynamics, optimization, sensing or materials science. These benchmarks, which are finely tuned to real-world applications, will determine industry preferences and demand for specific quantum hardware models. Just as in traditional computing, we expect a diversity of qubit types to emerge, each of which will drive different software applications.

Designing an effective and useful suite of benchmarks is a daunting task, but fortunately we can borrow several benchmarking principles from classic computers over the past three decades.

As business leaders begin to craft their quantum strategies, performance benchmarking should be a key part of any long-term plan. Hardware vendors will be fighting for market share and there will be no shortage of options. Understanding everyone’s performance objectively will give business leaders the clarity they need to make the best possible choices. Plus, high-quality SKUs also allow executives to cut through the hype and let the data guide buying decisions.

A Stallion to the Holy Grail: Quantum Error Correction

While early applications of quantum computing are expected to unlock speedups for niche use cases, the broadest market applicability is tied to a key technology: quantum error correction (QEC). This technology, which allows qubits to behave perfectly, is the primary focus of many of the major quantum hardware vendors. The first qubit types to demonstrate QEC will be well positioned to capture latent industry demand for applications that require much more reliable quantum computers than what we have today.

With this in mind, quantum benchmarks should include quantum error correction itself as a benchmark for progress. In our own work, we have found that QEC “constrains” very different parts of a quantum computer than other applications. For example, a critical component of QEC is the software’s ability to adapt on the fly (or in technical terms, “feed-forward measurement”). This component is unique to QEC and currently an area where hardware vendors need to make continuous progress.

In this sense, setting appropriate benchmarks, informed by real industry demand, can accelerate progress towards tomorrow’s quantum computers. Just as benchmarks have both chronicled and influenced the design of traditional computers, benchmarks will play an important role in quantum computers by matching qubits to applications. Let’s work to make it as easy as a walk through the electronics store.

About the Author

Pranav Gokhale is Vice President of Quantum Software at ColdQuanta. ColdQuanta is a global quantum technology company solving the world’s toughest problems. ColdQuanta leverages quantum mechanics to build and integrate a range of quantum computers, sensors and networks. From fundamental physics to cutting-edge commercial products, ColdQuanta enables “quantum everywhere” through our ecosystem of devices and platforms.

Featured Image: ©Vchalup

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