A quantum computer that encodes information in light pulses completed a task in 36 microseconds, which would take the best supercomputer minimum of 9000 years to accomplish. The machine has also been connected to the internet, allowing others to program it for their use for the first time – the first time such a sophisticated quantum computer has been made accessible to the public.
Quantum computers use quantum mechanics’ odd characteristics to do calculations far faster than traditional computers theoretically. Demonstrating quantum advantage or supremacy has been a long-standing objective in science. With its Sycamore processor, Google was the first to achieve it in 2019, solving an issue involving sampling random integers that is essentially unachievable for classical computers.
Now, Jonathan Lavoie of Xanadu Quantum Technologies in Toronto, Canada, and his colleagues have developed Borealis, a quantum computer that solves a problem known as boson sampling by using light particles, or photons, traveling through a network of fiber-optic loops. The properties of a large group of entangled, or quantum-linked, photons separated by beam splitters are measured.
More About Borealis Quantum Computer
Because the difficulty of the calculations increases dramatically as the number of photons increases, boson sampling is a difficult operation for ordinary computers. Borealis work out the solution by directly analyzing the behavior of up to 216 entangled particles.
Although solving this problem isn’t extremely practical outside of confirming quantum advantage, it is an important test.
“We have proven fundamental technologies we require for future quantum computers by demonstrating these findings using Borealis,” says Lavoie.
The Borealis system is the second to show a quantum advantage in boson sampling. The first is Jiuzhang, a machine developed by researchers at China’s University of Science and Technology (USTC). It initially demonstrated quantum advantage with 76 photons in 2020 and then with 113 photons in 2021.
Last year, the USTC team used Zuchongzhi to demonstrate a quantum advantage in the random-number-sampling problem.
According to Peter Knight of Imperial College London, Borealis is a step forward from Jiuzhang because it is a more powerful system that can calculate with a higher number of photons and has a simpler architecture.
“We all thought the Chinese experiment was a triumph,” he adds, “but we couldn’t see it going any further since there was a limit to how much you could fit onto your optical table.”
In comparison to Borealis, Jiuzhaigou employs a greater number of beam splitters to deliver entangled photons in various directions. On the other hand, Borealis uses optical fiber loops to delay the passage of some photons relative to others, separating them in time rather than space.
Availing the Quantum Computer to the Public
The stripped-down architecture has the extra benefit of making this computer more programmable, allowing it to be reprogrammed remotely for users to run it with their settings.
“Borealis is the first device capable of quantum computational advantage that has been made openly available to anyone with an internet connection,” Lavoie explains.
Knight believes that people will most likely start by experimenting with different types of boson sampling. Still, later on, it may be able to apply Borealis to various problems. So far, no one has established quantum advantage for a “useful” computational activity – the Google-initiated random-sampling problem has no uses other than demonstrating quantum advantage.
While Borealis is a significant step forward in terms of scale over Jiuzhang, Raj Patel of the University of Oxford believes it falls short of a completely programmable quantum computers like Sycamore or Zuchongzhi.
An interferometer, which monitors interference patterns to extract information from photons, has been restricted to just recording particular photon interactions to obtain more accurate readings.
“You would ideally want the interferometer to be fully integrated to create a programmable machine and tackle real-world challenges,” Patel explains.
Lavoie and his colleagues are now aiming to adapt a blueprint they published last year into a scalable, fault-tolerant photonic processor built on an integrated chip, significantly boosting the quantum machine’s capabilities.