By: April Carson
On a benchmark function that would previously take 9,000 years, a cleverly designed quantum device produced by Xanadu, a firm based in Toronto, Canada, bested conventional computers. The result, announced this week, is the first time that a quantum computer has been shown to offer an exponential speedup over classical machines on any task.
The answers came within 36 microseconds for the quantum chip Borealis. That's more than a million times faster than the time it would have taken even the best supercomputer to complete the same calculation.
To be clear, this isn't a general-purpose quantum computer that can solve any problem you throw at it. Borealis is designed specifically for a particular kind of optimization called quadratic unconstrained binary optimization, or QUBO. This kind of optimization is important for everything from route planning to machine learning, and it's the reason why IBM has been so interested in building quantum computers in the first place.
The power of quantum computing in extracting insights from enormous data sets has been demonstrated many times. The latest example is Xanadu, which showed that a seemingly basic notion—known as quantum advantage—can revolutionize a business's approach to information gathering and analytics.
In theory, it makes sense. Quantum computers exploit the quantum weirdness of the quantum world, where 0 and 1 might both be present at the same time with varying probabilities, unlike conventional computers that work in sequence using binary digits—0 or 1. Data is handled in qubits, a noncommittal unit that performs numerous operations as a result of its own physics.
A quantum computer is a hyper-efficient multitasker, but traditional computers are more linear. A quick quantum computer should be able to outpace any supercomputer in terms of speed and effectiveness when presented with the same problem. The concept of "quantum supremacy" has been the driving force behind efforts to develop new computers that are completely distinct from anything previously created.
The difficulty? Proving quantum dominance is quite difficult. As quantum computers get ready to tackle more practical issues in the real world, scientists are taking to an intermediate measure: quantum advantage, which states that a quantum computer can solve one task—any task—better than a regular computer.
In 2019, Google broke the internet when it unveiled the first example of a quantum computer, Sycamore, solving a computational problem in only 200 seconds with 54 qubits—comparable to a conventional supercomputer's estimate of 10,000 years. With an impressive demonstration of quantum computational advantage, another Chinese team quickly followed up with a second fascinating show featuring answers that would take a supercomputer over two billion years to compute.
However, the question of whether any of these quantum gadgets are even close to being ready for everyday applications is still unanswered. There are, however, many researchers and organizations racing to build a quantum computer that is useful for more than just breaking world records.
Computers, like anything else in the physical world, must be interpreted through physics. Our current technology, for example, utilizes electrons and clever chips to execute its operations. Quantum computers are similar because they also utilize alternative particle physics. Early generations of quantum computers appeared to be delicate, glittering chandeliers. While they are undoubtedly beautiful, compared to a small smartphone chip, they are also quite impractical. To minimize interference and enhance performance, the hardware frequently necessitates tightly controlled environments—for example, close to absolute zero temperature.
The fundamental idea of quantum computing is the same: qubits processing information in superposition, a quantum physics oddity that allows them to encode 0s, 1s, or both at the same time. The hardware required to execute it is quite varied.
Other tech companies, such as IBM and IonQ, have used superconducting metal loops in their quantum computing systems. Other versions from firms like Honeywell and IonQ took a different approach by relying on ions - atoms with one or more electrons removed - as the source for their quantum computing process.
Another option is to employ photons, which are particles of light. The Chinese demonstration of quantum advantage, for example, employed a photonic technology that has already been proven effective. But the concept has also been criticized as a stopgap towards quantum computing rather than a viable answer due to difficulties in engineering and installation.
The debut of Xanadu's chip was met with skepticism by naysayers. The new chip, Borealis, is similar to the one in the Chinese study in that it employs photons, rather than superconducting materials or ions, for computation.
It also has a significant benefit: it's programmable. "Previous experiments usually used static networks in which each component is fixed once manufactured,” according to Dr. Daniel Jost Brod of the Federal Fluminense University at Rio de Janeiro in Brazil, who was not involved in the research. In the Chinese experiment, a static microchip was employed as part of the earlier quantum advantage demonstration. The optical components of the Borealis, on the other hand, can all be readily programmed, making it less of a single-use gadget and more of a genuine computer that might solve numerous issues.
The flexibility of the chip is owing to an "ingenious concept" that provides "remarkable control and potential for scaling," according to Brod.
The researchers zeroed in on a problem known as Gaussian boson sampling, which serves as a benchmark for Quantum computing performance. The test, while computationally demanding, has little bearing on actual-world issues. However, it serves the purpose of an unbiased judge in chess and Go by providing a gold standard for measuring AI performance. It's sort of like "Gaussian boson sampling" is a method for demonstrating the benefits of quantum computers over traditional computers, according to Brod.
The team's quantum chip was able to solve the problem in just microseconds, while it would take a traditional computer billions of years to complete the same task. This is a significant achievement, as it demonstrates that quantum computers can outperform their classical counterparts by a huge margin.
The structure is like a funhouse mirror tent in a horror film with strange light (and photons) dubbed "squeezed states." A network of beam splitters is built on the chip containing the network of beam splitters. Each beam splitter functions like a semi-reflective mirror, splitting the light into multiple daughters depending on how it strikes. An array of photon detectors sits at the end of the device. The more beam splitters there are, the more difficult it becomes to predict where any given photon will go at any particular detector.
Consider a bean machine, a peg-studded board encased in glass, as another example. To play, drop a puck into the top pins. The puck drops randomly onto different pegs until it lands in a numbered slot after tumbling for some time.
The photons are replaced by Gaussian boson sampling, with the goal of recognizing which photon lands in which detector slot. The possible resultant distributions expand exponentially as a result of quantum properties, rapidly outpacing any supercomputer capabilities. It's a fantastic benchmark because we understand the physics behind it, and the setup implies that even a few hundred photons might be difficult for supercomputers to solve.
The study's researchers created a photonic quantum device with 200 qubits, which they believe is the world record for a solid-state quantum computer. Taking up the challenge, the new research reimagined a photonic quantum device with 216 qubits. The device calculated photons in bins of arrival time rather than the previous standard of direction, contradicting conventional designs. To delay photons so that they could interfere at particular locations important for quantum computing, the research used a technique called 'time-bin encoding.'
By reducing the number of beam splitters and adding new ones, we were able to drastically reduce the size of our device. Because all of the necessary delays for photons to interact and compute the task necessitate a large network of beam splitters—most often required for photon communication—the typical wide network can be reduced to three. The loop designs, as well as other components, are also "readily programmable" in that a beam splitter may be finely tuned in real time–similar to modifying computer code at the hardware level.
The group also completed a basic sanity check, which verified that the output data was correct. "This is the first time that anyone has experimentally demonstrated a photonic chip that can perform such a wide range of quantum operations so quickly," says Tilman Pfau, professor at the University of Stuttgart and one of the paper's co-authors.
For the time being, it appears that there are only a few studies demonstrating quantum supremacy. A half-century head start is common for conventional computers. As algorithms evolve on conventional computers—especially those with powerful AI-focused processors or neuromorphic computing designs—they may even easily outperform quantum systems, leaving them at a disadvantage.
The chip itself is made of just a few hundred transistors and other elements, arranged in a 5-by-5 grid. It's not much to look at, but it could be the key to unlocking the power of quantum computing.
But it's the thrill of the hunt. "The threshold for a quantum advantage is not well-defined, based on a single measure of excellence," said Brod. And as new experiments are conducted, artificial methods to simulate them will emerge— we can expect record-breaking quantum devices and classical algorithms to compete for the top spot in rapid succession.
For now, the race is on to build more powerful quantum computers. "I'm more bullish than ever that we'll see a commercial quantum computer within five years," said Brod. "The technology has progressed so rapidly in the past few years."
And it's not just about building bigger and better machines. With each new generation of quantum devices comes a new set of problems that can be tackled— and an opportunity to refine algorithms and find even better ways to solve them.
"It's an exciting time to be working in this field," said Brod. "Every day, there are new challenges and new opportunities."
“It may not be the end of the story,” he added. “However, this new research represents a significant stride for quantum physics in its pursuit to explain nature at the deepest level possible.”
The discovery was published in the journal Nature.
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