Researchers at IBM and the University of California are questioning whether a closely watched experimental computer used by Google actually relies on quantum mechanics as its manufacturer, D-Wave, claims.
At the heart of the battle is a question about the validity of quantum computing, which some predict may offer a road forward after Intel and other chip manufacturers exhaust "and reach the physical limits" of how powerful they can make their processors.
IBM questions Google quantum computing claims
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D-Wave is a closely watched company in that it is perhaps the most advanced in terms of commercializing quantum computing, though even its founders acknowledge that they exploit only a subset of quantum mechanics, called quantum annealing.
Quantum computing is the practice of harnessing the laws of quantum mechanics, or how matter behaves at the subatomic level. Advocates claim quantum computing could be more powerful than standard silicon processing in that its small scale of operations can simulate problems too large to be represented in traditional computing systems.
Williams said the charge from IBM and University of California is a pretty common one for D-Wave. Researchers will typically try to match the results of a quantum computer to what could be achieved by using classical physics. However, they usually just confine their study to one aspect of quantum computing.
"Based on these results, we conclude that classical models for the D-Wave machine are not ruled out," the paper stated. In other words, while D-Wave claims its computer is based on quantum mechanics, it is possible that the results it gets can be achieved using only standard classical physics.
Google engineers had suggested that performance will improve as D-Wave continues to double the number of qubits on its processors. A qubit, or quantum bit, is the basic unit of information for quantum computing. Unlike a regular binary bit, a qubit is able to hold two states at a single time, an effect called superposition that could be a key element to powerful quantum computers.
1) The model should be checked experimentally for 5-10-15-20-25 qubits (Actually, in my 2018 paper I noted that that this already gives strong positive or negative support for quantum supremacy claims. It is certainly necessary.)
Wade Roush: But the math of quantum computing actually says that when a qubit is in a state of superposition, you have to describe it with a kind of smear of probabilities between 0 and 1.
Gideon Lichfield: Yes, they did. And pretty much everybody in the quantum computing world that you speak to, except the people at IBM, will agree that this meant something, that there was a significant milestone achieved.
In a blog post published today, Google asserts that it has demonstrated quantum supremacy in an experiment using its 54-qubits 'Sycamore' based processor system (though only 53-qubits worked). Spreading the news, Google CEO Sundar Pichai Tweeted that he is "very proud that our @GoogleAI team has achieved a big breakthrough in quantum computing known as quantum supremacy after over a decade of work," and went on to thank Google collaborators in the research community.
IBM suggests that Google has broadly misinterpreted quantum supremacy but with fairness says its experiment is nonetheless "an excellent demonstration of the progress in superconducting-based quantum computing".
If I am interpreting Gil Kalai correctly, he alluded to the possibility in one of the comments of his blog that the number n=53 is too small for asymptotic results like this to apply. See -computers-amazing-progress-google-ibm-and-extraordinary-but-probably-false-supremacy-claims-google/#comment-61122
The controversy is the latest example of major technology companies trying to one-up each other in quantum computing, a futuristic realm with no clear winner yet. Microsoft and Intel have also been working actively in the area.
"This dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy for this specific computational task, heralding a much-anticipated computing paradigm."
"For quantum to positively impact society, the task ahead is to continue to build and make widely accessible ever more powerful programmable quantum computing systems that can implement, reproducibly and reliably, a broad array of quantum demonstrations, algorithms and programs. This is the only path forward for practical solutions to be realized in quantum computers," they wrote.
Whether you are a researcher who wants to push the boundaries of what's available for NISQ computers, a software engineer, a technical writer, or a student who is excited about quantum computing, we welcome your contributions to our open source code available on GitHub.
Google's paper noted that its Sycamore quantum processor is forward compatible and should support error-correction algorithms that the company may create in the future. Google expects to be able to create scalable and more powerful versions of Sycamore well into the future. It claimed that its processor is fully programmable and can run general quantum computing algorithms (unlike the quantum annealing D-Wave computer, for instance).
With the potential to significantly speed up drug discovery, give trading algorithms a big boost, break some of the most commonly used encryption methods, and much more, quantum computing could help solve some of the most complex problems industries face. But how does it work?
Cambridge Quantum Computing is the most well-funded startup focused primarily on quantum computing software. The company has raised $95M in disclosed funding from investors including IBM, Honeywell, and more. It offers a platform to help enterprises build out quantum computing applications in areas like chemistry, finance, and machine learning.
For example, Google is developing its own quantum computing hardware and has hit several key milestones, including the first claims of quantum supremacy and simulating a chemical reaction using a quantum computer. Google entities have also invested in startups in the space, including IonQ, ProteinQure, and Kuano.
Quantum-resistant blockchains may not fully emerge until post-quantum cryptography standards are more firmly established in the coming years. In the meantime, those running blockchain projects will likely be keeping a nervous eye on quantum computing advancements.
Eventually, quantum computing may even help create AI systems that act in a more human-like way. For example, enabling robots to make optimized decisions in real-time and more quickly adapt to changing circumstances or new situations.
Given the extreme complexities and variables involved in international shipping routes and orchestrating supply chains, quantum computing could be well-placed to help tackle daunting logistics challenges.
In 2019, Google announced that it had used a quantum computer to complete a task much more quickly than a classical counterpart could manage. Though the specific problem solved is not of much practical use, it marks an important milestone for the nascent quantum computing industry.
Despite this momentum, the space faces a number of hurdles. Significant technical barriers must be surmounted around critical issues like error correction and stability, tools to help more businesses develop software for quantum computers will need to become established, and companies sizing up quantum computing might need to start hiring for brand new skill sets from a small pool of talent.
Washington cares about quantum computing for some big reasons. In theory, a quantum computer could decipher codes that are used to encrypt a lot of modern communications, like those that enable secure web browsing. That makes quantum computing a huge national security risk, or opportunity, depending who gets there first. Quantum computers also could potentially simulate the behavior of molecules to design everything from more effective drugs to more efficient solar cells.
The House competitiveness bill tacks on even more provisions related to quantum research, some with much bigger price tags. It includes the Department of Energy Science for the Future Act, which would set aside $500 million over five years for research into distributed quantum computing systems, quantum communication technologies and new quantum-enabled sensing and measurement tools. It would also direct DOE to develop a Quantum User Expansion for Science and Technology (QUEST) program, granting the department $340 million over five years to give U.S.-based researchers access to advanced quantum computing tools.
During 2021, IBM said it plans to extend its Qiskit execution environment to increase the capacity to run more circuits at a much faster rate, and adding the capability to store quantum programs so that other users can run them as a service. This could pave the way to making quantum computing available as a service within enterprises.
By 2023, IBM said it plans to offer entire families of pre-built runtimes, callable from a cloud-based application programming interface (API) using a variety of common development frameworks to apply quantum computing to tackle industry-specific problems.
The developments from companies like IBM and Microsoft illustrate how the industry will deliver quantum computing to the enterprise software market. But a new short film, Quantum ethics, highlights the risks.
The experts featured in the film warn that society needs to think through the implication of what it means to solve problems that were previously insoluble and what regulatory framework needs to be in place to prevent misuse or exploiting quantum computing for malicious intent.
The best way to learn is by doing. Qiskit allows users to run experiments on state-of-the-art quantum devices from the comfort of their homes. The textbook teaches not only theoretical quantum computing but the experimental quantum physics that realises it. 2ff7e9595c
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