The usefulness of quantum computing – 06/21/2023 – Marcelo Viana

Four years ago, the computing world was stirred by an article in the journal Nature in which Google researchers announced that they had achieved “quantum supremacy”: using a quantum computer, they had performed in just 3 minutes and 20 seconds a calculation that, according to them, , the world’s fastest conventional supercomputer would take 10,000 years to complete.

At the same time that they highlighted the feat, some specialists relativized its magnitude and relevance. In 2021, a group in China showed that, in fact, this calculation can be performed on a conventional computer in just 5 minutes. And other researchers, notably at IBM, pointed out that the problem Google solved was hand-picked for the experiment and was of no practical interest in itself.

Now it is IBM who proclaims, also in Nature, another important advance in the area, which would be opening the “age of utility” in quantum computing.

The idea of ​​quantum computing dates back to the 1980s, when it was proposed by physicist Paul Benioff and other scientists. Conventional computers store and process information in the form of bits, tiny units capable of assuming only two states: 1 (“on”) and 0 (“off”). Quantum computers, on the other hand, use quantum bits, called qubits, which take advantage of the strange properties of matter described by quantum mechanics to perform calculations at breakneck speed, far beyond the reach of classical computers.

The computer used by Google in 2019 had only 53 qubits, that of IBM is no more than 127 qubits. As a comparison, the chip of any smartphone contains billions of conventional transistors. But everything quantum computers lack in size, they make up for in speed.

However, qubits are difficult to maintain, as they are easily affected by their interactions with the environment. Therefore, quantum calculations are unreliable: if we repeat the same calculation, we are likely to get different answers each time.

It is this problem that IBM announces it is solving: its researchers have found a method to increase the reliability of calculations, in order to obtain effectively useful results.

To emphasize this last point, they apply this method to solve a magnetic systems modeling problem –too complex to be handled by any conventional supercomputer— which is really relevant in physics. I will comment next week.

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