Google’s New Quantum Chip, the Willow Chip, Crosses Error-Correction Milestone in Quantum Computing

     I won’t pretend to know much about quantum computing, so I am mostly parroting and copying relevant quotes in this post. Google Quantum AI was founded in 2012 to build a large-scale quantum computer in order to “benefit society by advancing scientific discovery, developing helpful applications, and tackling some of society's greatest challenges.” Correcting errors has been one major challenge of quantum computing and Google claims to have made significant progress on that front with their new Willow Chip. The chip demonstrated the ability to correct errors “below threshold” — being able to drive errors down while scaling up the number of qubits.” Another part of the accomplishment is the speed of error correction, in real-time. Google Quantum AI founder Hartmut Neven noted:

“As the first system below threshold, this is the most convincing prototype for a scalable logical qubit built to date. It’s a strong sign that useful, very large quantum computers can indeed be built. Willow brings us closer to running practical, commercially-relevant algorithms that can’t be replicated on conventional computers.”

     Neven described the two major achievements as follows:

·        The first is that Willow can reduce errors exponentially as we scale up using more qubits. This cracks a key challenge in quantum error correction that the field has pursued for almost 30 years.

·        Second, Willow performed a standard benchmark computation in under five minutes that would take one of today’s fastest supercomputers 10 septillion (that is, 1025) years — a number that vastly exceeds the age of the Universe.

     The researchers created a silicon chip with 105 qubits.  The performance metrics for Willow are shown below:

     The most difficult benchmark for a quantum computer thus far is random circuit sampling (RCS). Neven explains:

“On the one hand, we’ve run the RCS benchmark, which measures performance against classical computers but has no known real-world applications. On the other hand, we’ve done scientifically interesting simulations of quantum systems, which have led to new scientific discoveries but are still within the reach of classical computers. Our goal is to do both at the same time — to step into the realm of algorithms that are beyond the reach of classical computers and that are useful for real-world, commercially relevant problems.”

     The quantum computing roadmap below shows that the new milestone in quantum error correction is milestone 2 in a roadmap that has 6 milestones laid out. It took about 12 years or more to hit milestone 2 so I wonder how long it will take to hit the last 4 milestones.

     At the end of his blog post, Neven explains why he thinks quantum computing will be revolutionary:

“My colleagues sometimes ask me why I left the burgeoning field of AI to focus on quantum computing. My answer is that both will prove to be the most transformational technologies of our time, but advanced AI will significantly benefit from access to quantum computing. This is why I named our lab Quantum AI. Quantum algorithms have fundamental scaling laws on their side, as we’re seeing with RCS. There are similar scaling advantages for many foundational computational tasks that are essential for AI. So quantum computation will be indispensable for collecting training data that’s inaccessible to classical machines, training and optimizing certain learning architectures, and modeling systems where quantum effects are important. This includes helping us discover new medicines, designing more efficient batteries for electric cars, and accelerating progress in fusion and new energy alternatives. Many of these future game-changing applications won’t be feasible on classical computers; they’re waiting to be unlocked with quantum computing.”

     The milestone in quantum error correction (QEC) was explained by Google AI researchers in a December paper in Nature where I note two relevant descriptions from the abstract:

“Our system maintains below-threshold performance when decoding in real time, …”

“Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms.”

Thus, that seems to be the goal that was reached: “large scale fault-tolerant quantum algorithms.”

    Dan Garisto for Scientific American explains QEC and its potential implications:

“If physicists could quell quantum errors caused by noise on a large enough quantum computer, they could perform some computations, such as exact simulations of molecules, that are intractable for classical computers.”

In a sense, quantum computers can enable us to reach into computational probability at a much deeper level than classical supercomputers can. But there are still many issues to overcome. Getting ahead of the errors is an important milestone.

“As you make a bigger and bigger system, you get better at correcting errors, but you’re also causing more errors,” says Daniel Gottesman, a quantum information theorist at the University of Maryland, who was not involved with the study. “When you pass this transition, where you can correct errors faster than they’re caused, is when making bigger and bigger systems makes it better.”

     Even though the current error rate is still magnitudes higher than for classical computers, that may not matter since the errors can be corrected quickly.

“The logical qubit lasted more than twice as long as any individual qubit it was composed of, and it had a one-in-1,000 chance of error per cycle of computation. (For comparison, the rate of error in a typical classical computer is about one in 1,000,000,000,000,000,000—essentially zero.)”

“Really good qubits are the thing that enables quantum error correction,” says Julian Kelly, director of quantum hardware at Google

     Google is not alone in making QEC progress as the joint venture of Microsoft and Quantinuum announced an error rate of 1 in 500 a few months ago.

“…using qubits made from ions trapped by lasers, they could encode 12 logical qubits that had a two-in-1,000 error rate.”

     Garisto also has a more sobering account of the immediate implications:

“Even with advances in error correction, practical applications for quantum computers are unlikely in the near term. Estimates vary, but consensus among many researchers is that to solve useful algorithms or perform robust simulations of chemistry, a quantum computer would need hundreds of logical qubits with error rates below about one in a million.”

     Wiilow is a hardware implementation. It has more cubits, 105 compared to its predecessor Sycamore’s 72. However, Sycamore was unable to get below threshold on its error rate.

“Willow’s qubits are more robust than Sycamore’s: they maintain their delicate quantum state five times as long and having lower error rates.”

     Increasing performance with increasing size is the part of the breakthrough that allows for scale up. Above threshold means more qubits = more uncorrected errors. Below threshold means more qubits = less uncorrected errors. Thus, it now seems possible that hundreds of logical qubits with lower error rates can happen.

     According to an article in PC Magazine:

“In 2019, Google previously did a quantum computation in 200 seconds that would have taken the fastest supercomputer at that time 10,000 years. But IBM dismissed its claims, arguing that a classical computer could do the same calculation with greater "fidelity" in 2.5 days and argued that "quantum supremacy" had yet to be achieved.”

     My question is when will that assumed “quantum supremacy” come about and how would we measure it?

     It is speculated that quantum computing will eventually threaten Bitcoin since it apparently has the potential to hack Bitcoin’s encryption. That makes one wonder a bit since China is far along in both quantum computing and hacking.

 

 

References:

 

Meet Willow, our state-of-the-art quantum chip. Hartmut Neven, Founder and Lead, Google Quantum AI. December 7, 2024. Meet Willow, our state-of-the-art quantum chip

Elon Musk is wowed by Google’s new quantum chip, which it claims ‘cracks a key challenge’ that’s existed for almost 3 decades. Dave Smith. Fortune. Elon Musk is wowed by Google’s new quantum chip, which it claims ‘cracks a key challenge’ that’s existed for almost 3 decades

Google’s Quantum Computer Makes a Major Breakthrough in Error Correction. Dan Garisto. Scientific American. December 9, 2024. Google Makes a Major Quantum Computing Breakthrough | Scientific American

Google's Quantum Chip Can Do in 5 Minutes What Would Take Other Computers 10 Septillion Years. Kate Irwin. PC Magazine. December 10, 2024. Google's Quantum Chip Can Do in 5 Minutes What Would Take Other Computers 10 Septillion Years

Google's 'Willow' chip is a big threat to Bitcoin: Eric Jackson. Fox Business, December 6, 2024. Google's 'Willow' chip is a big threat to Bitcoin: Eric Jackson | Watch

Quantum error correction below the surface code threshold. Google Quantum AI and Collaborators, Nature (December 9, 2024). Quantum error correction below the surface code threshold | Nature