Latest news with #OskarPainter
Yahoo
09-03-2025
- Science
- Yahoo
Google, Microsoft, and others are racing to crack open quantum computing. Here's how their breakthroughs stack up.
Tech giants Amazon, Google, IBM, and Microsoft are racing to develop a functional quantum computer. Each has released a prototype quantum chip with different approaches and potential applications. The field is rapidly evolving, but major hurdles remain before it becomes commercially useful. The quantum race is heating up. Tech titans Amazon, Google, IBM, and Microsoft each recently announced advancements in their prototype chips, tightening the race to develop a commercially useful quantum computer that could solve some of the universe's stickiest problems faster than a classical computer ever could. Quantum computing is a rapidly evolving — though still largely theoretical and deeply technical — field. But cracking it open could help discover new drugs, develop new chemical compounds, or break encryption methods, among other outcomes, researchers say. Naturally, each of the major players in Big Tech wants to be the one to take quantum computing mainstream. "You're hearing a lot about it because this is a real tipping point," Oskar Painter, the director of quantum hardware at Amazon Web Services, told Business Insider in late February, following the company's announcement of its Ocelot chip. Stick with us — here's where it gets complicated. Where classical computing uses binary digits — 0s and 1s, called bits — to represent information, quantum computing relies on a foundation built from the quantum equivalent of bits, called qubits. When they behave predictably at a large enough scale, qubits allow quantum computers to quickly calculate equations with multiple solutions and perform advanced computations that would be impossible for classical computers. However, qubits are unstable, and their behavior is unpredictable. They require specific conditions, such as low light and extremely cold environments, to reduce errors. When the number of qubits is increased, the error rate goes up — making advancement in the field slowgoing. Small-scale quantum computers already exist, but the race is on to scale them up and make them useful to a wider audience rather than just scientists. Recently, Amazon, Google, and Microsoft have announced new prototype chips, and IBM has made strides in its existing quantum road map. Each company is using unique approaches to solve the error reduction and scalability problems that have long plagued the field and make useful quantum computing a reality. Here's how each approach stacks up. Approach to quantum: Topological qubits Most powerful machine: Majorana 1 In February, Microsoft unveiled its new quantum chip, Majorana 1. The aim is for the chip to speed up the development of large-scale quantum computers from decades to years. Microsoft said the chip uses a new state of matter to produce "topological" qubits that are less prone to errors and more stable. Essentially, this is a qubit based on a topological state of matter, which isn't a liquid, gas, or solid. As a result, these quantum particles could retain a "memory" of their position over time and move around each other. Information, therefore, could be stored across the whole qubit, so if any parts fail, the topological qubit could still hold key pieces of information and become more fault-resistant. "Microsoft's progress is the hardest to get an idea about because it's very niche," said Tom Darras, founder of quantum computing startup Welinq. "Even experts in the industry find it difficult to assess the quality of these results." Quantum experts agree that Microsoft still has many roadblocks to overcome, and its peer-reviewed Nature paper only demonstrates aspects of what its researchers have claimed to achieve — but some in the quantum ecosystem see it as a promising outcome. Approach to quantum: Superconducting qubits Most powerful machine: Willow In December, Google announced Willow, its newest quantum chip, which the company claims takes just five minutes to solve a problem that would take the world's fastest supercomputer 10 septillion years. Perhaps more impressive was Google's breakthrough in how quantum computers scale. Historically, the more qubits that are added, and the more powerful the computer becomes, the more prone it is to errors. With Willow, Google's researchers said that adding more physical qubits to a quantum processor actually made it less error-prone, reversing the typical phenomenon. Known as "below threshold," the accomplishment marks a significant milestone by cracking a problem that has been around since the 1990s. In a study published in Nature, Google's researchers posit this breakthrough could finally offer a way to build a useful large-scale quantum computer. However, much of this is still theoretical, and now Google will need to prove it in practice. Approach to quantum: Superconducting qubits Most powerful machine: Ocelot In late February, Amazon Web Services announced its Ocelot chip, a prototype designed to advance the company's focus on cloud-based quantum computing. An Amazon spokesperson told Business Insider the Ocelot prototype demonstrated the potential to increase efficiency in quantum error correction by up to 90% compared to conventional approaches. The chip leverages a unique architecture that integrates cat qubit technology — named for the famous Schrödinger's cat thought experiment — and additional quantum error correction components that can be manufactured using processes borrowed from the electronics industry. Troy Nelson, a computer scientist and the chief technology officer at Lastwall, a cybersecurity provider of quantum resilient technology, told Business Insider that Amazon's Ocelot chip is another building block that the industry will use to build a functioning quantum computer. However, its error rate needs to be substantially lowered, and its chips would require more qubit density before they're useful. "There's lots of challenges ahead. What Amazon gained in error correction was a trade-off for the complexity and the sophistication of the control systems and the readouts from the chip," Nelson said. "We're still in prototype days, and we still have multiple years to go, but they've made a great leap forward." Approach to quantum: Superconducting qubits Most powerful machine: Condor IBM has been a quantum frontrunner for some time, with several different prototype chips and its development of Q System One, the first circuit-based commercial quantum computer, unveiled in January 2019. IBM's Condor chip is the company's most powerful in terms of its number of qubits. However, since its development, IBM has focused its approach on the quality of its gate operations and making its newer quantum chips modular so multiple smaller, less error-prone chips can be combined to make more powerful quantum computing machines. Condor, the second-largest quantum processor ever made, was unveiled at the IBM Quantum Summit 2023 on December 4, 2023. At the same time, IBM debuted its Heron chip, a 133-qubit processor with a lower error rate. Rob Schoelkopf, cofounder and chief scientist of Quantum Circuits, told Business Insider that IBM has prioritized "error mitigation" over traditional error correction approaches. While IBM has so far been successful in what Schoelkopf calls "brute force scaling" with this approach, he said the methodology will need to be modified in the long run for efficiency. Sankar Das Sarma, a theoretical condensed matter physicist at the University of Maryland, told Business Insider that the Amazon Web Services Ocelot chip, Google's Willow, and IBM's Condor use a "more conventional" superconducting approach to quantum development compared to other competitors. By contrast, Microsoft's approach is based on topological Majorana zero modes, which also have a superconductor, but in "a radically different manner," he said. If the Majorana 1 chip works correctly, Das Sarma added, it is protected topologically with minimal need for error correction, compared to claims from other tech companies that they have improved conventional error correction methods. Still, each company's approach is "very different," Das Sarma said. "It is premature to comment on who is ahead since the whole subject is basically in the initial development phase." Big Tech companies should be cautious about "raising expectations when promoting results," said Georges-Olivier Reymond, CEO of quantum computing startup Pasqal. "Otherwise, you could create disillusionment." Reymond's sentiment was echoed by IBM's VP of quantum adoption and business development, Scott Crowder, who told Business Insider he is concerned "over-hype" could lead people to discount quantum technology before its promise can be realized. "We think we are on the cusp of demonstrating quantum advantage," said Crowder, referring to when a quantum computer outperforms classical machines. "But the industry is still a few years from a fully fault-tolerant quantum computer." Read the original article on Business Insider
Al Bawaba
03-03-2025
- Business
- Al Bawaba
Amazon Web Services announces new quantum computing chip
Amazon Web Services (AWS) has announced Ocelot, a new quantum computing chip that can reduce the costs of implementing quantum error correction by up to 90%, compared to current approaches. Developed by the team at the AWS Center for Quantum Computing at the California Institute of Technology, Ocelot represents a breakthrough in the pursuit to build fault-tolerant quantum computers capable of solving problems of commercial and scientific importance that are beyond the reach of today's conventional computers. AWS used a novel design for Ocelot's architecture, building error correction in from the ground up and using the 'cat qubit'. Cat qubits–named after the famous Schrödinger's cat thought experiment–intrinsically suppress certain forms of errors, reducing the resources required for quantum error correction. Through this new approach with Ocelot, AWS researchers have, for the first time, combined cat qubit technology and additional quantum error correction components onto a microchip that can be manufactured in a scalable fashion using processes borrowed from the microelectronics industry. History shows that important advancements in computing have been made by fundamentally rethinking hardware components, as this can have a significant impact on cost, performance, and even the feasibility of a new technology. The computer revolution truly took off when the transistor replaced the vacuum tube, enabling room-sized computers to be shrunk down into today's compact and much more powerful, reliable, and lower-cost laptops. Choosing the right building block to scale is critical, and today's announcement represents an important step in developing efficient means to scaling up to practical, fault-tolerant quantum computers. 'With the recent advancements in quantum research, it is no longer a matter of if, but when practical, fault-tolerant quantum computers will be available for real-world applications. Ocelot is an important step on that journey,' said Oskar Painter, AWS director of Quantum Hardware. 'In the future, quantum chips built according to the Ocelot architecture could cost as little as one-fifth of current approaches, due to the drastically reduced number of resources required for error correction. Concretely, we believe this will accelerate our timeline to a practical quantum computer by up to five years.' AWS researchers have published their findings in a peer-reviewed research paper in Nature. The major challenge with quantum computing: One of the biggest challenges with quantum computers is that they're incredibly sensitive to the smallest changes, or 'noise' in their environment. Vibrations, heat, electromagnetic interference from cell phones and Wi-Fi networks, or even cosmic rays and radiation from outer space, can all knock qubits out of their quantum state, causing errors in the quantum computation being performed. This has historically made it extremely challenging to build quantum computers that can perform reliable, error-free calculations of any significant complexity. 'The biggest challenge isn't just building more qubits,' said Painter. 'It's making them work reliably.' To solve this problem, quantum computers rely on quantum error correction that uses special encodings of quantum information across multiple qubits—in the form of 'logical' qubits—to shield quantum information from the environment. This also enables the detection and correction of errors as they occur. Unfortunately, given the sheer number of qubits required to get accurate results, current approaches to quantum error correction have come at a huge, and therefore prohibitive, cost. A new approach to quantum error correction: To address the current problems associated with quantum error correction, researchers at AWS developed Ocelot. Ocelot was designed from the ground up with error correction 'built in.' 'We looked at how others were approaching quantum error correction and decided to take a different path,' said Painter. 'We didn't take an existing architecture and then try to incorporate error correction afterwards. We selected our qubit and architecture with quantum error correction as the top requirement. We believe that if we're going to make practical quantum computers, quantum error correction needs to come first.' In fact, according to Painter, his team estimates that scaling Ocelot to a 'fully-fledged quantum computer capable of transformative societal impact would require as little as one-tenth of the resources associated with standard quantum error correcting approaches.' One way to think about quantum correction is in the context of quality control in manufacturing, and the difference between needing one inspection point to catch all defects, instead of 10 inspection points. In other words, it offers the same result, but with fewer resources and an overall improved manufacturing process. By reducing the amount of resources needed through approaches such as with Ocelot, quantum computers can be built smaller, more reliably, and at lower cost. All of this accelerates the path to applying quantum computing to future applications in the real-world, such as faster drug discovery and development, the production of new materials, the ability to make more accurate predictions about risk and investment strategies in financial markets, and many more. Making science fiction science fact:While today's announcement is a promising start, Ocelot is still a prototype and AWS is committed to continuing to invest in quantum research and refining its approach. In the same way it took many years of development and learnings of running x86 systems (a widely used computer architecture for central processing units) reliably and securely at scale to build Graviton into one of the leading chips in the cloud, AWS is taking a similar approach to quantum computing. 'We're just getting started and we believe we have several more stages of scaling to go through,' said Painter. 'It's a very tough problem to tackle, and we will need to continue investing in basic research, while staying connected to, and learning from, important work being done in academia. Right now, our task is to keep innovating across the quantum computing stack, to keep examining whether we're using the right architecture, and to incorporate these learnings into our engineering efforts. It's a flywheel of continuous improvement and scaling.'How to get started with quantum computing: Customers can get started exploring quantum computing today with Amazon Braket on AWS. Amazon Braket is a full-managed quantum computing service that allows scientists, developers, and students to work with a range of third-party quantum computing hardware, high-performance simulators, and a suite of software tools that make it easy to get started in quantum computing.
Channel Post MEA
28-02-2025
- Business
- Channel Post MEA
Amazon Unveils Quantum Computing Chip Ocelot
Amazon Web Services (AWS) has announced Ocelot, a new quantum computing chip that can reduce the costs of implementing quantum error correction by up to 90%, compared to current approaches. Developed by the team at the AWS Center for Quantum Computing at the California Institute of Technology, Ocelot represents a breakthrough in the pursuit to build fault-tolerant quantum computers capable of solving problems of commercial and scientific importance that are beyond the reach of today's conventional computers. AWS used a novel design for Ocelot's architecture, building error correction in from the ground up and using the 'cat qubit'. Cat qubits–named after the famous Schrödinger's cat thought experiment–intrinsically suppress certain forms of errors, reducing the resources required for quantum error correction. Through this new approach with Ocelot, AWS researchers have, for the first time, combined cat qubit technology and additional quantum error correction components onto a microchip that can be manufactured in a scalable fashion using processes borrowed from the microelectronics industry. History shows that important advancements in computing have been made by fundamentally rethinking hardware components, as this can have a significant impact on cost, performance, and even the feasibility of a new technology. The computer revolution truly took off when the transistor replaced the vacuum tube, enabling room-sized computers to be shrunk down into today's compact and much more powerful, reliable, and lower-cost laptops. Choosing the right building block to scale is critical, and today's announcement represents an important step in developing efficient means to scaling up to practical, fault-tolerant quantum computers. 'With the recent advancements in quantum research, it is no longer a matter of if, but when practical, fault-tolerant quantum computers will be available for real-world applications. Ocelot is an important step on that journey,' said Oskar Painter, AWS director of Quantum Hardware. 'In the future, quantum chips built according to the Ocelot architecture could cost as little as one-fifth of current approaches, due to the drastically reduced number of resources required for error correction. Concretely, we believe this will accelerate our timeline to a practical quantum computer by up to five years.' AWS researchers have published their findings in a peer-reviewed research paper in Nature. The major challenge with quantum computing: One of the biggest challenges with quantum computers is that they're incredibly sensitive to the smallest changes, or 'noise' in their environment. Vibrations, heat, electromagnetic interference from cell phones and Wi-Fi networks, or even cosmic rays and radiation from outer space, can all knock qubits out of their quantum state, causing errors in the quantum computation being performed. This has historically made it extremely challenging to build quantum computers that can perform reliable, error-free calculations of any significant complexity. 'The biggest challenge isn't just building more qubits,' said Painter. 'It's making them work reliably.' To solve this problem, quantum computers rely on quantum error correction that uses special encodings of quantum information across multiple qubits—in the form of 'logical' qubits—to shield quantum information from the environment. This also enables the detection and correction of errors as they occur. Unfortunately, given the sheer number of qubits required to get accurate results, current approaches to quantum error correction have come at a huge, and therefore prohibitive, cost. A new approach to quantum error correction: To address the current problems associated with quantum error correction, researchers at AWS developed Ocelot. Ocelot was designed from the ground up with error correction 'built in.' 'We looked at how others were approaching quantum error correction and decided to take a different path,' said Painter. 'We didn't take an existing architecture and then try to incorporate error correction afterwards. We selected our qubit and architecture with quantum error correction as the top requirement. We believe that if we're going to make practical quantum computers, quantum error correction needs to come first.' In fact, according to Painter, his team estimates that scaling Ocelot to a 'fully-fledged quantum computer capable of transformative societal impact would require as little as one-tenth of the resources associated with standard quantum error correcting approaches.' One way to think about quantum correction is in the context of quality control in manufacturing, and the difference between needing one inspection point to catch all defects, instead of 10 inspection points. In other words, it offers the same result, but with fewer resources and an overall improved manufacturing process. By reducing the amount of resources needed through approaches such as with Ocelot, quantum computers can be built smaller, more reliably, and at lower cost. All of this accelerates the path to applying quantum computing to future applications in the real-world, such as faster drug discovery and development, the production of new materials, the ability to make more accurate predictions about risk and investment strategies in financial markets, and many more. Making science fiction science fact: While today's announcement is a promising start, Ocelot is still a prototype and AWS is committed to continuing to invest in quantum research and refining its approach. In the same way it took many years of development and learnings of running x86 systems (a widely used computer architecture for central processing units) reliably and securely at scale to build Graviton into one of the leading chips in the cloud, AWS is taking a similar approach to quantum computing. 'We're just getting started and we believe we have several more stages of scaling to go through,' said Painter. 'It's a very tough problem to tackle, and we will need to continue investing in basic research, while staying connected to, and learning from, important work being done in academia. Right now, our task is to keep innovating across the quantum computing stack, to keep examining whether we're using the right architecture, and to incorporate these learnings into our engineering efforts. It's a flywheel of continuous improvement and scaling.' How to get started with quantum computing: Customers can get started exploring quantum computing today with Amazon Braket on AWS. Amazon Braket is a full-managed quantum computing service that allows scientists, developers, and students to work with a range of third-party quantum computing hardware, high-performance simulators, and a suite of software tools that make it easy to get started in quantum computing. Ocelot: Fast facts Ocelot is a prototype quantum computing chip, designed to test the effectiveness of AWS's quantum error correction architecture. It consists of two integrated silicon microchips. Each chip has an area of roughly 1cm2. They are bonded one on top of the other in an electrically-connected chip stack. On the surface of each silicon microchip are thin layers of superconducting materials that form the quantum circuit elements. The Ocelot chip is composed of 14 core components: five data qubits (the cat qubits), five 'buffer circuits' for stabilizing the data qubits, and four additional qubits for detecting errors on the data qubits. The cat qubits store the quantum states used for computation. To do so, they rely on components called oscillators, which generate a repetitive electrical signal with steady timing. Ocelot's high-quality oscillators are made from a thin film of superconducting material called Tantalum. AWS material scientists have developed a specific way of processing Tantalum on the silicon chip to boost oscillator performance. How do quantum computers work? Quantum computers have the potential to drive major advances in society and technology, from cryptography to engineering novel materials. The main difference between the conventional or 'classical' computers we use today, and quantum computers, is that classical computers use bits—usually represented as a digital value of 1 or 0 —as their most basic unit of information. But quantum computers use quantum bits, or 'qubits'—usually elementary particles such as electrons or photons—to make calculations. Scientists can apply precisely timed and tuned electromagnetic pulses to manipulate what's called the 'quantum state' of the qubit, where it can be both 1 and 0 at the same time. This mind-bending behavior, when performed across many qubits, allows a quantum computer to solve some important problems exponentially faster than a classical computer ever could. 0 0
Tahawul Tech
28-02-2025
- Science
- Tahawul Tech
Amazon Web Services announces new quantum computing chip
Recently, Amazon Web Services (AWS) announced Ocelot, a new quantum computing chip that can reduce the costs of implementing quantum error correction by up to 90%, compared to current approaches. Developed by the team at the AWS Centre for Quantum Computing at the California Institute of Technology, Ocelot represents a breakthrough in the pursuit to build fault-tolerant quantum computers capable of solving problems of commercial and scientific importance that are beyond the reach of today's conventional computers. AWS used a novel design for Ocelot's architecture, building error correction in from the ground up and using the 'cat qubit'. Cat qubits–named after the famous Schrödinger's cat thought experiment–intrinsically suppress certain forms of errors, reducing the resources required for quantum error correction. Through this new approach with Ocelot, AWS researchers have, for the first time, combined cat qubit technology and additional quantum error correction components onto a microchip that can be manufactured in a scalable fashion using processes borrowed from the microelectronics industry. History shows that important advancements in computing have been made by fundamentally rethinking hardware components, as this can have a significant impact on cost, performance, and even the feasibility of a new technology. The computer revolution truly took off when the transistor replaced the vacuum tube, enabling room-sized computers to be shrunk down into today's compact and much more powerful, reliable, and lower-cost laptops. Choosing the right building block to scale is critical, and today's announcement represents an important step in developing efficient means to scaling up to practical, fault-tolerant quantum computers. 'With the recent advancements in quantum research, it is no longer a matter of if, but when practical, fault-tolerant quantum computers will be available for real-world applications. Ocelot is an important step on that journey', said Oskar Painter, AWS director of Quantum Hardware. 'In the future, quantum chips built according to the Ocelot architecture could cost as little as one-fifth of current approaches, due to the drastically reduced number of resources required for error correction. Concretely, we believe this will accelerate our timeline to a practical quantum computer by up to five years'. AWS researchers have published their findings in a peer-reviewed research paper in Nature. The major challenge with quantum computing: One of the biggest challenges with quantum computers is that they're incredibly sensitive to the smallest changes, or 'noise' in their environment. Vibrations, heat, electromagnetic interference from cell phones and Wi-Fi networks, or even cosmic rays and radiation from outer space, can all knock qubits out of their quantum state, causing errors in the quantum computation being performed. This has historically made it extremely challenging to build quantum computers that can perform reliable, error-free calculations of any significant complexity. 'The biggest challenge isn't just building more qubits,' said Painter. 'It's making them work reliably.' To solve this problem, quantum computers rely on quantum error correction that uses special encodings of quantum information across multiple qubits—in the form of 'logical' qubits—to shield quantum information from the environment. This also enables the detection and correction of errors as they occur. Unfortunately, given the sheer number of qubits required to get accurate results, current approaches to quantum error correction have come at a huge, and therefore prohibitive, cost. A new approach to quantum error correction: To address the current problems associated with quantum error correction, researchers at AWS developed Ocelot. Ocelot was designed from the ground up with error correction 'built in'. 'We looked at how others were approaching quantum error correction and decided to take a different path', said Painter. 'We didn't take an existing architecture and then try to incorporate error correction afterwards. We selected our qubit and architecture with quantum error correction as the top requirement. We believe that if we're going to make practical quantum computers, quantum error correction needs to come first'. In fact, according to Painter, his team estimates that scaling Ocelot to a 'fully-fledged quantum computer capable of transformative societal impact would require as little as one-tenth of the resources associated with standard quantum error correcting approaches'. One way to think about quantum correction is in the context of quality control in manufacturing, and the difference between needing one inspection point to catch all defects, instead of 10 inspection points. In other words, it offers the same result, but with fewer resources and an overall improved manufacturing process. By reducing the amount of resources needed through approaches such as with Ocelot, quantum computers can be built smaller, more reliably, and at lower cost. All of this accelerates the path to applying quantum computing to future applications in the real-world, such as faster drug discovery and development, the production of new materials, the ability to make more accurate predictions about risk and investment strategies in financial markets, and many more. Making science fiction science fact: While today's announcement is a promising start, Ocelot is still a prototype and AWS is committed to continuing to invest in quantum research and refining its approach. In the same way it took many years of development and learnings of running x86 systems (a widely used computer architecture for central processing units) reliably and securely at scale to build Graviton into one of the leading chips in the cloud, AWS is taking a similar approach to quantum computing. 'We're just getting started and we believe we have several more stages of scaling to go through', said Painter. 'It's a very tough problem to tackle, and we will need to continue investing in basic research, while staying connected to, and learning from, important work being done in academia. Right now, our task is to keep innovating across the quantum computing stack, to keep examining whether we're using the right architecture, and to incorporate these learnings into our engineering efforts. It's a flywheel of continuous improvement and scaling'. How to get started with quantum computing: Customers can get started exploring quantum computing today with Amazon Braket on AWS. Amazon Braket is a full-managed quantum computing service that allows scientists, developers, and students to work with a range of third-party quantum computing hardware, high-performance simulators, and a suite of software tools that make it easy to get started in quantum computing. Ocelot: Fast facts Ocelot is a prototype quantum computing chip, designed to test the effectiveness of AWS's quantum error correction architecture. It consists of two integrated silicon microchips. Each chip has an area of roughly 1cm 2 . They are bonded one on top of the other in an electrically-connected chip stack. . They are bonded one on top of the other in an electrically-connected chip stack. On the surface of each silicon microchip are thin layers of superconducting materials that form the quantum circuit elements. The Ocelot chip is composed of 14 core components: five data qubits (the cat qubits), five 'buffer circuits' for stabilizing the data qubits, and four additional qubits for detecting errors on the data qubits. The cat qubits store the quantum states used for computation. To do so, they rely on components called oscillators, which generate a repetitive electrical signal with steady timing. Ocelot's high-quality oscillators are made from a thin film of superconducting material called Tantalum. AWS material scientists have developed a specific way of processing Tantalum on the silicon chip to boost oscillator performance. How do quantum computers work? Quantum computers have the potential to drive major advances in society and technology, from cryptography to engineering novel materials. The main difference between the conventional or 'classical' computers we use today, and quantum computers, is that classical computers use bits—usually represented as a digital value of 1 or 0 —as their most basic unit of information. But quantum computers use quantum bits, or 'qubits'—usually elementary particles such as electrons or photons—to make calculations. Scientists can apply precisely timed and tuned electromagnetic pulses to manipulate what's called the 'quantum state' of the qubit, where it can be both 1 and 0 at the same time. This mind-bending behaviour, when performed across many qubits, allows a quantum computer to solve some important problems exponentially faster than a classical computer ever could. Image Credit: Amazon Web Services
Yahoo
28-02-2025
- Business
- Yahoo
Amazon joins the quantum computing race, announcing new 'Ocelot' chip
Amazon Web Services on Thursday debuted its new quantum computing chip, a prototype called Ocelot. The company says the Ocelot represents a breakthrough in error correction and scalability. The quantum computing field is heating up with recent advancements from Google and Microsoft. Amazon Web Services on Thursday debuted its prototype quantum chip, the Ocelot, making headway in the race to develop functional quantum computers. "What makes Ocelot different and special is the way it approaches the fundamental challenge we have with quantum computers, and that is the errors that they're susceptible to," Oskar Painter, the director of quantum hardware at AWS told Business Insider. Amazon, in research published in the peer-reviewed journal Nature, says the Ocelot represents a breakthrough in error correction and scalability — two key issues that have long slowed advancement in the field. The Ocelot prototype demonstrated the potential to increase efficiency in quantum error correction by up to 90% compared to conventional approaches, the company says. "And that efficiency is something on the order of a factor of five to 10x so it's a pretty significant reduction," Painter said. "We still have about a factor of a billion to reduce the error rate — so that it's a huge gap — but it turns out that quantum error correction is up to the challenge, and it turns out that we eventually can bridge this massive gap." Quantum computing is a growing field of technology that combines computer science, math, and quantum mechanics. It relies on units of information called qubits rather than the binary bits used in classical computing. Qubits hold more information than binary bits and can exist in multiple states simultaneously. However, they are unstable, difficult to measure, and require specific conditions — such as low light or extremely cold environments — to reliably replicate results without errors, which has slowed progress in the field for years. But when they behave predictably at a large enough scale, qubits enable quantum computers to solve more complex calculations more quickly than classical computers can. Researchers in the field agree that computations solvable through quantum computing could help discover new drugs, promote sustainable food growth in harsh climates, develop new chemical compounds, or break our current encryption methods, among other outcomes. Amazon said the Ocelot chip uses a kind of qubit technology called cat qubits, named after the famous Schrödinger's cat thought experiment. This technology intrinsically suppresses certain forms of errors, simplifying and reducing the quantum error correction required to build a full-fledged quantum computer, a spokesperson said. An Amazon spokesperson told Business Insider the chip has a unique architecture that integrates the cat qubit technology and additional quantum error correction components into the chip that can be manufactured using processes borrowed from the electronics industry. Before fully-fledged and functional quantum computers can become commercially useful, Painter and other quantum researchers agree they must make more progress in error reduction and scalability. While Amazon's new chip doesn't mean commercially useful quantum computers are in production now, it's the latest in a series of recent advancements in the field that has galvanized the industry and suggests commercial adoption will come sooner than expected. Rob Schoelkopf, cofounder and chief scientist of Quantum Circuits, said Amazon's research results "highlight how more efficient error correction is key to ensuring viable quantum computing. " He described the company's progress as "a good step toward exploring and preparing for future roadmaps" in further developing quantum technology. Amazon's announcement comes about a week after Microsoft unveiled its quantum chip, the Majorana 1. Microsoft says its chip is powered by a new state of matter and allows for more stable, scalable, and simplified quantum computing. Similarly, Google in December announced its quantum chip, Willow, which the company says can perform a standard benchmark computation in under five minutes. It's a task that would take the current fastest supercomputers 10 septillion years to complete — a timeframe that exceeds the age of the universe. "We really are at a very exciting time in quantum computing, and you're hearing a lot about it because this is a real tipping point," Painter said. Sankar Das Sarma, a theoretical condensed matter physicist at the University of Maryland's Joint Quantum Institute, told Business Insider Amazon's Ocelot chip is a "more conventional superconducting chip, perhaps similar to the ones developed by Google and IBM," than the one recently unveiled by Microsoft — though he added it's too soon to say which company is ahead in their findings. "The MSFT work is based on topological Majorana zero modes, which also has a superconductor, but in a radically different manner," Das Sarma wrote in an email to BI. "In particular, the MSFT device, if it works correctly, is protected topologically with minimal need for error correction, whereas the AWS claim seems to be that they have made some improvement in the conventional error correction schemes. The two approaches are very different." Researchers in the field are closely monitoring Amazon's and other companies' advancements, hoping to prove that quantum technology will become commercially viable sooner than anticipated. In January, Nvidia CEO Jensen Huang suggested we were still 20 years away from the technology being "very useful," sending quantum stocks tumbling. Troy Nelson, the chief technology officer at Lastwall, a cybersecurity provider of quantum resilient technology, told Business Insider that each company's announcement represents another building block that the industry will use along the way to a functioning quantum computer. "There's lots of challenges ahead. What Amazon gained in error correction — and it has led to some new scientific knowledge and discoveries in error correction — was a trade-off for the complexity and the sophistication of the control systems and the readouts from the chip," Nelson said. "We're still in prototype days, and we still have multiple years to go, but they've made a great leap forward." Read the original article on Business Insider
