[LINK] Google Willow quantum chip

[Stephen Loosley]

Meet Willow, our state-of-the-art quantum chip

By Hartmut Neven, Founder and Lead, Google Quantum AI Dec 09, 2024
https://blog.google/technology/research/google-willow-quantum-chip/


Our new chip demonstrates error correction and performance that paves 
the way to a useful, large-scale quantum computer


Today I’m delighted to announce Willow, our latest quantum chip. Willow 
has state-of-the-art performance across a number of metrics, enabling 
two major achievements.

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 Willow chip is a major step on a journey that began over 10 years ago.

When I founded Google Quantum AI in 2012, the vision was to build a 
useful, large-scale quantum computer that could harness quantum 
mechanics — the “operating system” of nature to the extent we know it 
today — to benefit society by advancing scientific discovery, developing 
helpful applications, and tackling some of society's greatest challenges.

As part of Google Research, our team has charted a long-term roadmap, 
and Willow moves us significantly along that path towards commercially 
relevant applications.


Exponential quantum error correction — below threshold!

Errors are one of the greatest challenges in quantum computing, since 
qubits, the units of computation in quantum computers, have a tendency 
to rapidly exchange information with their environment, making it 
difficult to protect the information needed to complete a computation.

Typically the more qubits you use, the more errors will occur, and the 
system becomes classical.

Today in Nature, we published results showing that the more qubits we 
use in Willow, the more we reduce errors, and the more quantum the 
system becomes.

https://www.nature.com/articles/s41586-024-08449-y

We tested ever-larger arrays of physical qubits, scaling up from a grid 
of 3x3 encoded qubits, to a grid of 5x5, to a grid of 7x7 — and each 
time, using our latest advances in quantum error correction, we were 
able to cut the error rate in half.

https://research.google/blog/making-quantum-error-correction-work/


In other words, we achieved an exponential reduction in the error rate.

This historic accomplishment is known in the field as “below threshold” 
— being able to drive errors down while scaling up the number of qubits.

You must demonstrate being below threshold to show real progress on 
error correction, and this has been an outstanding challenge since 
quantum error correction was introduced by Peter Shor in 1995.

https://journals.aps.org/pra/abstract/10.1103/PhysRevA.52.R2493

There are other scientific “firsts” involved in this result as well. For 
example, it’s also one of the first compelling examples of real-time 
error correction on a superconducting quantum system — crucial for any 
useful computation, because if you can’t correct errors fast enough, 
they ruin your computation before it’s done.

And it’s a "beyond breakeven" demonstration, where our arrays of qubits 
have longer lifetimes than the individual physical qubits do, an 
unfakable sign that error correction is improving the system overall.

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.

As a measure of Willow’s performance, we used the random circuit 
sampling (RCS) benchmark. Pioneered by our team and now widely used as a 
standard in the field, RCS is the classically hardest benchmark that can 
be done on a quantum computer today.

You can think of this as an entry point for quantum computing — it 
checks whether a quantum computer is doing something that couldn’t be 
done on a classical computer. Any team building a quantum computer 
should check first if it can beat classical computers on RCS; otherwise 
there is strong reason for skepticism that it can tackle more complex 
quantum tasks.

We’ve consistently used this benchmark to assess progress from one 
generation of chip to the next — we reported Sycamore results in October 
2019 and again recently in October 2024.


Willow’s performance on this benchmark is astonishing: It performed a 
computation in under five minutes that would take one of today’s fastest 
supercomputers 1025 or 10 septillion years.

If you want to write it out, it’s 10,000,000,000,000,000,000,000,000 years.

This mind-boggling number exceeds known timescales in physics and vastly 
exceeds the age of the universe. It lends credence to the notion that 
quantum computation occurs in many parallel universes, in line with the 
idea that we live in a multiverse, a prediction first made by David Deutsch.

https://en.wikipedia.org/wiki/The_Fabric_of_Reality

These latest results for Willow, as shown in the plot below, are our 
best so far, but we’ll continue to make progress ... (snip..)


.. 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.

--