Google solves a major quantum computing problem, gets closer to practical quantum computers

Google has made a big breakthrough in quantum computing that could bring practical quantum computers closer to reality. The company says it has found a way to reduce errors in its Willow quantum chip, the processor it uses for quantum computing, by around 40 times. In simple terms, this could help quantum computers solve complex problems more reliably, without wasting so much of their computing power on correcting errors.Sharing the findings on X, CEO Sundar Pichai says the breakthrough is another step towards building quantum computers that can solve complex problems that even today's most powerful computers struggle with. “ Some magical progress towards "magic state" in quantum! Our GoogleQuantumAI team has demonstrated "magic state cultivation" on physical hardware for the first time. The result is a 40x error reduction on our Willow processor vs. previous methods, achieving a state-of-the-art 99.99% logical fidelity,” he wrote.“It's another step towards useful, error-corrected quantum computers to help solve the hardest problems. The result is published in Science today, watch the video below to see how it works.” So, what exactly has Google achieved, and why does it matter. Lets break it down. What is the problem Google is trying to solve?Quantum computers work differently from regular computers. They use tiny units of information called qubits, which are highly sensitive and can easily develop errors. This makes it difficult for quantum computers to carry out complex calculations accurately. Researchers are trying to reduce these errors so that quantum computers can solve real-world problems reliably.One challenge is creating what scientists call “magic states”. These help quantum computers perform complex calculations. But each state is used up during a calculation, and any errors in it can affect the final result. Until now, scientists have used a process called “distillation” to make these states more reliable by combining several imperfect ones. But this takes up a lot of computing power. According to Google some estimates suggest that producing these states could use up as much as 95 per cent of a quantum computer’s capacity, leaving little room for actual calculations.However, Google has now demonstrated another approach, called “magic state cultivation”, on its quantum hardware. Researchers Craig Gidney, Noah Shutty and Cody Jones developed the idea in 2024. Instead of relying on conventional distillation, this technique uses a series of checks to identify errors and reject faulty attempts, helping produce more reliable quantum states.The process works a bit like a filter. It starts with an imperfect quantum state in a small area of the chip. The computer then runs a series of checks to identify errors and discard faulty attempts. States that pass these checks can be expanded across more qubits to create larger, more reliable states.According to Google, getting the technique to work on real hardware took months of testing. Its researcher Emma Rosenfeld and her team found that changes in temperature and electrical equipment were interfering with their measurements. After fixing the issue, the team tested the technique using 54 of the 105 qubits in its Willow chip. Google says this reduced errors by around 40 times, with the resulting quantum states achieving 99.99 per cent logical fidelity. However, the process still rejected 92 per cent of attempts, meaning more work is needed before it can be used on a larger scale.So, how will this help build real-world quantum computers? The idea is simple: if quantum computers can make reliable quantum states using fewer resources, they will have more computing power left to solve actual problems. This could eventually help researchers build larger quantum computers that can tackle complex tasks, such as studying molecules and developing new medicines, which are difficult for conventional computers to handle.However, there is still a long way to go. Google says it still needs to show that the technique works on a much larger scale and that it can reduce errors enough for demanding calculations. For now, the breakthrough solves one important part of the puzzle, bringing the company a step closer to its goal of building quantum computers that can solve real-world problems.- Ends