Google’s Quantum Computing Lab has nailed a significant breakthrough. The company announced that its new quantum computing chip called Willow can perform complex computational tasks in less than 5 minutes. Google claims that one of the world’s fastest supercomputers would take 10 septillion years to complete this task—more than the age of the Universe.
This is a huge leap from 2019, when Google claimed that its quantum processor could solve a mathematical equation in three minutes, a task that would take a supercomputer 10,000 years. At that time, IBM challenged the claim.
Besides improved performance, researchers have also found a way to reduce the number of errors—a problem Google calls “one of the biggest challenges in quantum computing.” Unlike bits that represent 1 or 0, quantum computing uses qubits, which can exist in multiple states simultaneously (like 1, 0, or any state in between).
According to Google, qubits are prone to errors because they “tend to quickly exchange information with the external environment.” However, Google researchers discovered a way to reduce the number of errors by adding more qubits to the system and were able to correct these errors in real-time.
“This historic achievement in the field is called ‘below threshold’ — the ability to reduce the number of errors while scaling up the number of qubits,” writes Google Quantum AI founder Hartmut Neven in a Google blog. “Demonstrating this benchmark is crucial for progress in quantum error correction, which remains one of the most challenging tasks since Peter Shor introduced this concept in 1995.”
The Willow chip, which now has 105 qubits, boasts “best-in-class performance,” according to Neven. Microsoft, Amazon, and IBM are also working on their quantum computing systems.
Google’s next goal is to perform the first “useful, beyond-classical” computation that will be relevant for real-world applications and inaccessible for conventional computers. In the future, as Neven points out, quantum technologies will become “indispensable” for gathering data for training artificial intelligence, discovering new medications, developing more efficient batteries for electric vehicles, and accelerating progress in the field of thermonuclear energy and new energy alternatives.
Source: The Verge
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