Google's Quantum Echoes Algorithm: A Leap Towards Practical Quantum Computing

Google claims 'quantum advantage' again -- but researchers are sceptical

Google researchers have made a fresh claim of quantum advantage -- the ability of quantum computers to radically speed up calculations compared with their classical counterparts. This is not the company's first such claim. But the researchers say their latest algorithm -- dubbed quantum echoes -- has the potential to solve scientific problems, including deriving the structures of molecules. It could also, in theory, be replicated on another quantum computer. "This algorithm offers the opportunity for real-world applications," said Hartmut Neven, who heads Google's quantum-computing lab, in Santa Barbara, California, at a briefing for journalists ahead of the announcement. The firm is optimistic that in five years there will be practical uses for quantum computers, he added. But some researchers are cautious of the claim of quantum advantage, published in Nature on 22 October. "The burden of proof should be high," says Dries Sels, a quantum physicist at New York University in New York City. And although the paper does a "serious job" of testing various classical algorithms, there is no proof that an efficient one doesn't exist. "Personally I don't think that's enough to make such a big claim," he says. Others say that the promise of practical use so soon is premature. The technical advance is impressive, says James Whitfield, a quantum physicist at Dartmouth College in Hanover, New Hampshire, but it is "a bit of a stretch to think how this is going to suddenly solve some economically viable problem". Google researchers and their collaborators fleshed out how they could apply the algorithm to simple molecules in a preprint study that they have submitted to arXiv. They were able to predict certain features of the molecules' structures using quantum simulations, and confirm their findings with nuclear magnetic resonance (NMR) measurements. But so far, they can only apply the method to molecules that can already be efficiently simulated classically, such as the aromatic liquid toluene. Applying the quantum echoes algorithm to more complex systems will require less noisy hardware or methods to correct for errors that are still being worked on, said Tom O'Brien, a research scientist at Google Quantum AI in Munich, Germany, at the briefing. The demonstrations used Google's Willow chip, which harnesses 105 tiny superconducting circuits to store information as quantum bits, or qubits -- the quantum equivalent of classical bits of information. Google's algorithm is able to detect subtle quantum links between distant parts of the computer, which otherwise get scrambled and lost owing to interactions between the device's many quantum parts. The team likened their method to mapping a cave using echoes; it involves running a series of operations, perturbing a qubit, then running the operations in reverse. Measurements reveal traces of the single qubit's interactions throughout the system. To apply the algorithm to molecules, researchers make qubits simulate 'spins' of atomic nuclei, the quantum property that makes each nucleus act like a tiny bar magnet. By measuring how these spins interact magnetically, NMR reveals a molecule's structure, but the technique fails when the nuclei are too far apart. By simulating spins using qubits, the quantum echoes algorithm can tease out long-distance interactions to give more structural information than is possible using NMR alone, said O'Brien. "So far these demonstrations have been on relatively small molecules, but we are optimistic that similar ideas could eventually be extended to much larger systems -- potentially even proteins -- in the future," says Ashok Ajoy, a quantum chemist at the University of California, Berkeley. Claims of quantum advantage are fraught and often contested. Google's first claim in 2019 involved a task with no practical applications, and other researchers soon showed that the same calculations were also possible using classical computers. In March, D-Wave, a quantum-computing company in Palo Alto, California, claimed to have solved the first problem of scientific relevance with a quantum processor, which was similarly challenged by improved classical algorithms. Google says its quantum echoes algorithm runs on the firm's quantum processor 13,000 times faster than the best classical competitor. The team spent the equivalent of ten years of a researchers' time 'red teaming' -- stress testing the gap by improving the classical equivalent as much as possible, and researchers who spoke to Nature's news team say that Google's result appears robust. "Certainly, it throws down the gauntlet for any sceptics to try to reproduce their results classically," says Scott Aaronson, a computer scientist at the University of Texas at Austin. But a 13,000-fold improvement is not a big buffer to have and Sels says he already sees potential strategies that could boost the speed of a classical algorithm. A big advantage of Google's claim, says Aaronson, is that, because the result the computer delivers is a definitive number, the results can be verified on another quantum computer. When the algorithm is used to predict real molecular structures, the team can also compare its results with experimental measurements, says Neven. Previous claims of quantum advantage often used probabilistic algorithms in which no two outputs would be expected to match. Verifiable quantum advantage is "one of the biggest challenges of the field for the past several years, so I'm thrilled that Google and others are making clear progress directly on that", says Aaronson. But getting from this demonstration to anything commercially useful, or to a scalable computer that can run large computations despite the presence of errors, will present "additional big challenges", he adds.

Google's breakthrough 'Quantum Echoes' algorithm pushes us closer to useful quantum computing -- running 13,000 times faster than on a supercomputer

The new algorithm is inspired by the way that sonar works, and scientists used it to solve real-world problems. (Image credit: Google Quantum AI) Google scientists have created a new algorithm that can solve problems on a quantum processor 13,000 times faster than the world's fastest supercomputers. They say it brings us one step closer to using quantum computers in drug discovery, materials science and many other scientific applications. The researchers say the new algorithm, dubbed Quantum Echoes, is a breakthrough because it achieves quantum advantage while being the first such algorithm that can be verified independently by running it on another quantum computer. The Quantum Echoes algorithm achieved its superfast result in a benchmarking experiment run on Google's Willow quantum processing unit (QPU). The researchers outlined how the algorithm works in a new study published Oct. 22 in the journal Nature. "Quantum algorithms tell the quantum computer how to solve problems in the most efficient manner, analogous to software developments in classical computing," Xiao Mi, a Google Quantum AI research scientist who oversaw the completion of this work, told Live Science in an email. "Both the software and hardware elements have to exist and work together in order for either classical or quantum computing to help solve problems in the future." While the scientists demonstrated the new algorithm's quantum advantage in the first study, they also wanted to show that it could be used to address a practical problem. In a second study, published Oct. 22 in the arXiv preprint database, the same team designed a quantum circuit to mimic the dynamics of molecules in a nuclear magnetic resonance (NMR) spectroscopy laboratory. In doing so, they discovered previously unknown details of the atomic spacing and structures of two molecules with 15 and 28 atoms respectively -- [4-C]-toluene and [1-C]-3',5'-dimethylbiphenyl (DMBP). The system used in this experiment was small (15 qubits), but future work will enable researchers to simulate molecules that are four times larger -- a scale that's impossible for classical simulations, the team said in the study. The new research has built on decades of work that began in the 1980s with research by Michel Devoret, professor of physics at the University of California and Google Quantum AI's chief scientist of quantum hardware. Devoret was the joint winner of the 2025 Nobel Prize in physics for the work and is a co-author of the study. "Today, we are announcing this breakthrough algorithm that actually marks another milestone in which the computation is done, the quantity of which is verifiable. So if another quantum computer would do the same calculation, the result would be the same. So this marks a new step towards full-scale quantum computations," Devoret said in a press briefing. "This Quantum Echoes algorithm is not only verifiable, so that its result can be obtained by another similar quantum computer, but it presents a quantum advantage; it realizes a computation that would take much longer than with classical hardware." The Quantum Echoes algorithm works in several stages, amounting to a highly advanced echo in which a signal is sent into the quantum system and then reversed to listen for the "echo" that comes back, all amplified by constructive interference (a phenomenon in which quantum waves compound to become stronger). First, scientists ran a series of operations, or quantum gates, on an entangled 105-qubit array on the Willow QPU. Next, one qubit was perturbed, or deviated, before they ran the same exact operations in reverse. The result was a curious "butterfly effect" that could be used to reveal information about the quantum system. The scientists then used this algorithm to measure distances between atoms in the two molecules. To confirm the performance of the algorithm on Willow versus on classical supercomputers, the scientists conducted rigorous "red-teaming" tests, borrowing from cybersecurity methods to verify the robustness of the results. These tests ran for the equivalent of 10 years. "Certainly, it throws down the gauntlet for any skeptics to try to reproduce their results classically," Scott Aaronson, chair of computer science at The University of Texas at Austin told Live Science. "Compared to previous quantum supremacy demonstrations, the big advantage here is that the output is a single number rather than a sample from a distribution, and therefore is in principle, efficiently verifiable -- if not using a classical computer, then at least using a second quantum computer." Aaronson added that verifiable quantum supremacy is one of the biggest challenges in the field. He noted that Google's goal across both new studies was not to solve a commercially useful problem but to get a clear advantage over a classical computer and enable another quantum computer to verify the answer independently. Google launched the Willow quantum computing chip in December last year. The new processor demonstrated that as the number of qubits are scaled up, the errors that occur reduce exponentially, marking a key milestone in quantum computing research. But hardware improvements are not enough on their own -- even if the machines could be scaled the millions of qubits required to beat classical computing. That's because the software and hardware components need to work together to find the most efficient route to solving a problem, as Mi noted. Google scientists claim that we will begin to see practical applications that are only possible with quantum computers in as little as five years. However, we would still need to scale up the hardware so that machines can operate with millions of qubits -- something which is difficult to imagine today because the most powerful quantum computers only have 100s or 1,000s of qubits.

13,000x faster: Google's chip delivers first verifiable quantum edge

Google's Quantum AI team claims its latest algorithm could move quantum computing closer to real-world impact. The new method, called Quantum Echoes, may one day help scientists design better drugs, catalysts, polymers, and batteries. Although the early experiments have not yet demonstrated a "quantum advantage," researchers believe the results mark a turning point toward practical benefits. Quantum computers rely on qubits, components that can process information exponentially faster than classical bits. The more qubits connected, the greater the system's potential power.

Google demonstrates verifiable quantum simulation that reveals molecular shapes - SiliconANGLE

Google demonstrates verifiable quantum simulation that reveals molecular shapes Google LLC's quantum division just released research showing that its Willow quantum chip can provide elegant and accurate simulations about the physical properties of molecules much faster than classical computers. Furthermore, the algorithm the team developed is verifiable, which means that the same algorithm can be run on a similarly powerful computer and get the same answer. Google Quantum AI Principal Scientist ‪Vadim Smelyanskiy said this new algorithm offers "a valuable tool to understand the nature of quantum systems from molecules, to magnets, to potentially black holes." Just published in Nature, the Google team demonstrated what it says is the first-ever verifiable capability by a quantum computer, outperforming the ability of classical computers, for a problem known as the out-of-time-order correlator, which the company calls Quantum Echoes. Quantum Echoes is a new quantum-computing algorithm developed by Google's Quantum AI team that works a bit like playing a piece of music forwards and then backwards in an echo chamber to reveal hidden harmonics. In this case, the "music" is the simulation of quantum motions of molecules, and the "echo" is a clever reversal of those motions inside the quantum processor so that software can pick out the subtle quantum effects. Imagine you have a gigantic orchestra playing in a symphony, but you can only listen to one instrument at a time. Classical computers operate by focusing on instrument to instrument and piecing the final picture together afterward. A quantum computer, capable of massively parallel calculations, can pick up many instruments at once and discover patterns in ways classical computers would find extremely slow. This kind of simulation can be applied to data from nuclear magnetic resonance experiments, a scientific technique that uses strong magnetic fields and radio waves to probe the nuclei of atoms. NMR works by putting molecules into a magnetic field, forcing atomic nuclei to align either with or against it; then radio waves are used to "flip" the atoms to a higher energy state. When the atoms "flip back," they release energy that can be measured. The types of atomic nuclei and the surrounding nuclei change how each atom is affected by different frequencies of radio waves, thus providing a spectrum of data that provides clues to a molecule's structure. Google's Quantum Echoes algorithm effectively recreates that process inside a quantum computer, simulating how a molecule's atomic nuclei would behave in an NMR experiment. Researchers then compared their quantum simulations with real NMR data, confirming that the quantum model reproduced the same underlying atomic interactions observed in the laboratory. Because the method is verifiable -- meaning the quantum machine's answer can be checked -- it offers a trusted way to explore complex molecular systems that could one day help in materials design or drug discovery. To verify the accuracy of its new algorithm, Google ran a proof-of-principle experiment in partnership with the University of California, Berkley. In the experiment, the research team studied two molecules, one with 15 atoms and one with 28 atoms. The company said the results of the experiment matched those of traditional NMR and unveiled information not normally accessible to NMR. This finding is significant because, while classical computers can model the structure and quantum interactions within molecules, their accuracy quickly breaks down as molecular size and complexity grow. Google's team believes that with continued progress, quantum computers could one day provide direct, verifiable insights into the structure and behavior of much larger and more intricate molecules. Google said this validated that quantum-enhanced NMR could become a prevailing tool for drug discovery and materials science. In these fields, the specific structure of molecules helps describe how they will interact with one another and other materials. This can lead to the discovery of novel drug interactions and characterize new materials such as polymers, battery components or materials to construct quantum bits -- the fundamental component that makes up quantum computer logic. "The shape of molecules is critical in determining how they work," said Nicholas Rubin, chief quantum chemist at Google Quantum AI. "Our hope is that we could use the Quantum Echoes algorithm to augment what's already possible with traditional NMR." The company said its quantum chip ran the algorithm 13,000 times faster than the world's fastest supercomputer. Google's Willow chip, unveiled in October 2024, represents the company's state-of-the-art in quantum computing with key capabilities that solve challenges with error correction at a large scale. Although quantum chips are powerful, they have a problem: errors caused by external noise. This "noise" can be virtually anything from microvibrations, heat fluctuations, errant radio waves and cosmic rays. Even slightly perturbed by noise, a qubit can have its information destroyed. The larger that quantum chips get, the more errors they face. To tackle this, Google came up with a specialized architecture that cut error rates by half each time the number of qubits was increased. This allowed the company to build and release a 105-qubit processor, almost double the 59 housed in the previous Sycamore chip released in 2019.

Google says it has developed landmark quantum computing algorithm

Google has created a new quantum algorithm named Quantum Echoes. This algorithm runs on Google's quantum chip and is significantly faster than current supercomputers. It promises to unlock practical uses for quantum computing. The algorithm could help in drug discovery and material science. It may also generate unique data for artificial intelligence training, especially in fields lacking sufficient datasets. Google said it has developed a computer algorithm that points the way to practical applications for quantum computing and will be able to generate unique data for use with artificial intelligence. The new algorithm called Quantum Echoes, which runs on the company's quantum chip, is 13,000 times faster than the most sophisticated classical computing algorithm on supercomputers, Google said. In the future, the Quantum Echoes algorithm may be able to help measure molecular structure in molecules which could aid in drug discovery and help material science through identifying new types of materials, company executives told a media briefing last week. Alphabet's Google is among several major tech firms including Amazon and Microsoft investing in quantum computing - which promises to speed up computing and solve problems out of reach for today's machines. Last year, Google unveiled its quantum chip, Willow, that the company said is able to overcome a crucial problem with "qubits", the building blocks of quantum computing. The development of the algorithm was roughly equivalent in significance to the chip, the executives said. The algorithm is also verifiable with other quantum computers or through experiments. Verifiable data means that it can lead to practical applications. "If I can't tell you the data is correct, if I can't prove to you the data is correct, how can I do anything with it?" Google staff research scientist Tom O'Brien said. For artificial intelligence, Google's engineers hope to be able to use the algorithm to help create new data sets for uses in areas such as life sciences where good data sets do not exist to train AI models with. Google published details about the Quantum Echoes algorithm in the scientific journal Nature on Wednesday.

Google reaches a milestone in quantum computing with an algorithm that is 13,000 times faster

Alphabet unveiled Quantum Echoes on Wednesday, a new quantum computing algorithm that, according to the company, outperforms the best classical algorithms by up to 13,000 times. Developed to run on its Willow quantum chip, unveiled in 2023, this tool marks a major step forward in the transition of quantum computing from the experimental stage to practical applications, particularly in artificial intelligence, materials science, and pharmaceutical research. The algorithm could simulate complex molecular structures, paving the way for the discovery of new drugs and the design of next-generation materials. One of its strengths is its verifiability: the results can be confirmed by other quantum machines or by physical tests, a crucial criterion according to Google researchers. Published Wednesday in Nature, Quantum Echoes could also be used to generate new data to train AI models in areas where data is scarce, reinforcing Google's ambitions in quantum computing against rivals such as Microsoft and Amazon.

Google says it has developed landmark quantum computing algorithm

SAN FRANCISCO (Reuters) -Google said it has developed a computer algorithm that points the way to practical applications for quantum computing and will be able to generate unique data for use with artificial intelligence. The new algorithm called Quantum Echoes, which runs on the company's quantum chip, is 13,000 times faster than the most sophisticated classical computing algorithm on supercomputers, Google said. In the future, the Quantum Echoes algorithm may be able to help measure molecular structure in molecules which could aid in drug discovery and help material science through identifying new types of materials, company executives told a media briefing last week. Alphabet's Google is among several major tech firms including Amazon and Microsoft investing in quantum computing - which promises to speed up computing and solve problems out of reach for today's machines. Last year, Google unveiled its quantum chip, Willow, that the company said is able to overcome a crucial problem with "qubits", the building blocks of quantum computing. The development of the algorithm was roughly equivalent in significance to the chip, the executives said. The algorithm is also verifiable with other quantum computers or through experiments. Verifiable data means that it can lead to practical applications. "If I can't tell you the data is correct, if I can't prove to you the data is correct, how can I do anything with it?" Google staff research scientist Tom O'Brien said. For artificial intelligence, Google's engineers hope to be able to use the algorithm to help create new data sets for uses in areas such as life sciences where good data sets do not exist to train AI models with. Google published details about the Quantum Echoes algorithm in the scientific journal Nature on Wednesday. (Reporting by Max A. Cherney in San Francisco; Editing by Edwina Gibbs)