The quantum realm is full of theories and concepts that are impossible for most people to understand, and numbers both very large and very small that are equally difficult for our minds to grasp. Google’s latest groundbreaking announcement reflects all these angles and does not disappoint in any of these “head-turning” categories. Last week, they announced that their new quantum AI had solved an equation in just five minutes that would require a septillion years of continuous operation of a normal computer.

A septillion is a 1 followed by 24 zeros. So it looks like this: 1 000 000 000 000 000 000 000 000

However, if you tried to count to a septillion, you would need billions of years, much longer than the age of the universe.

Why is this so important?

Quantum computing, no matter how cool and advanced it sounds, has always struggled with instability. Tiny particles do not obey the rules of regularity that apply to everyday objects, and even the most perfect chip can fail as their fragile state is disrupted at the slightest intervention. Researchers have spent decades exploiting this elusive behavior, hoping to use it to perform calculations that ordinary machines could never complete. Many promises have been made, but every initiative faces the same stumbling block. Bugs pile up too quickly for everyone to fix, slowing down progress.

Google plays in the quantum world

Quantum error correction offered a possible solution, but it had its complications. This requires propagating information across multiple qubits, the fundamental units of quantum data. While it may seem simple in theory, it creates a juggling act in practice. With too many qubits involved, it becomes difficult to keep the error rate below a critical threshold.

Until recently, no one had been able to show that the error rate could drop below this critical point, especially in code designed to scale. This changed with the demonstration of the new quantum chip architecture. This achievement was shared by quantum scientist and founder of the Google Quantum AI laboratory, Hartmut Neven.

Access to parallel universes?

Neven called Willow’s performance “wonderful”. He added that his high-speed results “confirm the idea that quantum computing occurs in many parallel universes.” Neven praised Oxford University physicist David Deutsch for proposing the idea that the successful development of quantum computers could support the “many worlds interpretation” of quantum mechanics and the existence of a multiverse. Since the 1970s, Deutsch has been pioneering quantum computing not for the technology itself but to test the theory of the multiverse.

What is a parallel universe?

Parallel universes, also known as alternative or multiple universes, are the idea that other realities may exist besides our own. Think of our universe as a single bubble within a vast cosmic foam; Here, each bubble is a separate universe, with its own unique laws of physics, history, and even versions of ourselves.

Scientists are exploring this concept with theories such as the multiverse, which posits that countless other universes may exist, each with their own unique possibilities. Although we have yet to find concrete evidence for the existence of parallel universes, the idea sparks fascinating discussions about the nature of reality and what might lie beyond what we can currently see and understand.

A private opinion but praise nonetheless

However, astrophysicist-turned-writer Ethan Siegel disagreed with Google’s view. He accused them of “mixing up unrelated concepts that Neven should also know.” Siegel explained that Neven confused the mathematical field in which quantum mechanics operates with the idea of ​​parallel universes and multiverses.

According to Siegel, even if quantum computers are successful, they will not prove the existence of parallel universes. Despite their differences, Siegel praised the progress Google has made with Willow, calling it “a really big step forward in the world of quantum computing.” He believes this breakthrough could help solve some of Earth’s biggest challenges, such as the discovery of new drugs, the development of better batteries for electric cars, and the development of fusion and new energy sources.

Neven echoed this optimism, saying: “Many of these game-changing programs will not be possible to run on classical computers; “They are waiting to be unlocked by the quantum computer.”

Google Willow quantum chip

chip Willow It is the latest superconducting processor developed by Google’s Quantum AI team. Unlike older devices that struggle to deal with errors, Willow takes performance into a new realm that leverages techniques that aim to truly deliver on the promise of quantum error correction. This system conforms to a special approach known as surface code. Previous attempts have run into difficulties as more qubits are added, but Willow breaks down that hurdle here.

Coding Distances and the Google Quantum Chip

Quantum error correction frameworks often refer to something called code distance. In simple terms, this means how many qubits are used to secure a piece of quantum data. Longer distances, such as going a code distance from three to five to seven, are expected to reduce the overall probability of failure if certain conditions are met.

In this new device, each step in distance cuts the logic error rate in half. This type of development has long been an important goal for quantum computing researchers. According to the published findings, quantum scientist and founder of Google’s Quantum AI Laboratory, Hartmut Neven, said, “Willow performed in less than five minutes a standard benchmark calculation that would take one of today’s fastest supercomputers 10 septillion years.”

Slow and steady marathon pace

Running the test for only a few cycles may not reveal the full stability story of the system. Google’s new quantum chip overcomes this problem by increasing performance to one million cycles. The device keeps its performance below the threshold for a period of time that would normally cause other systems to run out of air. Maintaining real-time decoding accuracy over such a long period of time is no small feat.

The team behind Willow has organized their work so that fixes can be made instantly. This approach ensures that the chip does not go astray.

“We see Willow as an important step towards building a useful quantum computer,” said Google CEO Sundar Pichai.

Looking beyond classic bottlenecks

Traditional supercomputers solve complex tasks using billions of tiny switches that operate in well-understood ways.

Quantum computers, on the contrary, connect to phenomena that cannot be reduced to classical labels. The challenge so far has been keeping delicate quantum states alive long enough to complete meaningful calculations. With Willow, the team shows that qubits can cooperate in ways that drive errors out of control. The demonstration suggests that quantum chips may be on the path to computing that could surpass anything a classical system could handle.

Why does Google want a quantum chip?

Relying on hardware that can pass these stringent reliability tests shows that quantum computing isn’t stuck in the toy problem phase forever. Increasing the distance of the code without losing the ability to correct errors suggests that one day large collections of qubits could use algorithms applied to real-world tasks.

Examples include accelerating complex simulations, improving drug discovery pipelines, and investigating new materials for energy storage. Willow’s success in achieving sub-threshold error rates over long periods of time could spur work in industries awaiting convincing evidence that quantum hardware will be a reliable tool.

When fixing mistakes becomes routine

Quantum error correction has never been about completely eliminating errors. The idea is to make it rare enough that the machine can complete the calculation. If future projects build on Willow’s stability and scalability features, the day may come when such fixes will happen behind the scenes, invisible to users.

Achieving this level of fault tolerance could allow quantum computers to handle workloads that classical hardware cannot reach. This opens up a practical way to expand these incredible machines.

Scaling fault tolerance with quantum microcircuits

The efforts of Google Quantum AI and other groups around the world do not occur in a vacuum. The field of quantum error correction has attracted the attention of many researchers seeking a path to practical devices.

Research over the last decade has demonstrated the importance of specific lattice designs and logic qubits arranged in careful patterns. Willow now shows that thresholds can be exceeded with the right chip architecture and error correction schemes. It moves the entire industry closer to producing machines that solve useful problems. Although the journey is not over, an important piece of the puzzle has fallen into place.