Lifeboat Foundation

Nanoscale machinery has many uses, including drug delivery, single-atom transistor technology, or memory storage. However, the machinery must be assembled at the nanoscale, which is a considerable challenge for researchers.

For nanotechnology engineers the ultimate goal is to be able to assemble functional machinery part-by-part at the nanoscale. In the macroscopic world, we can simply grab items to assemble them. It is not impossible to “grab” single molecules anymore, but their quantum nature makes their response to manipulation unpredictable, limiting the ability to assemble molecules one by one. This prospect is now a step closer to reality, thanks to an international effort led by the Research Centre Jülich of the Helmholtz society in Germany, including researchers from the Department of Chemistry at the University of Warwick.

In the paper, “The stabilization potential of a standing molecule,” published today, 10 November 2021 in the journal Science Advances, an international team of researchers has been able to reveal the generic stabilization mechanism of a single standing molecule, which can be used in the rational design and construction of three-dimensional molecular devices at surfaces.

IBM has created a quantum processor able to process information so complex the work can’t be done or simulated on a traditional computer, CEO Arvind Krishna told “Axios on HBO” ahead of a planned announcement.

Why it matters: Quantum computing could help address problems that are too challenging for even today’s most powerful supercomputers, such as figuring out how to make better batteries or sequester carbon emissions.

Driving the news: IBM says its new Eagle processor can handle 127 qubits, a measure of quantum computing power. In topping 100 qubits, IBM says it has reached a milestone that allows quantum to surpass the power of a traditional computer.

What kinds of ‘particles’ are allowed by nature? The answer lies in the theory of quantum mechanics, which describes the microscopic world.

In a bid to stretch the boundaries of our understanding of the quantum world, UC Santa Barbara researchers have developed a device that could prove the existence of non-Abelian anyons, a quantum particle that has been mathematically predicted to exist in two-dimensional space, but so far not conclusively shown. The existence of these particles would pave the way toward major advances in topological quantum computing.

In a study that appears in the journal Nature, physicist Andrea Young, his graduate student Sasha Zibrov and their colleagues have taken a leap toward finding conclusive evidence for non-Abelian anyons. Using graphene, an atomically thin material derived from graphite (a form of carbon), they developed an extremely low-defect, highly tunable device in which non-Abelian anyons should be much more accessible. First, a little background: In our three-dimensional universe, elementary particles can be either fermions or bosons: think electrons (fermions) or the Higgs (a boson).

Scientists demonstrate how quantum entanglement can be witnessed in the quasi-1D Heisenberg antiferromagnet.

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This instructs qsim to make use of its cuQuantum integration, which provides improved performance on NVIDIA GPUs. If you experience issues with this option, please file an issue on the qsim repository.

After you finish, don’t forget to stop or delete your VM on the Compute Instances dashboard to prevent further billing.

Continue reading “GPU-based quantum simulation on Google Cloud” »

A team of researchers led by an Institute for Quantum Computing (IQC) faculty member performed the first-ever simulation of baryons—fundamental quantum particles—on a quantum computer.

With their results, the team has taken a step towards more complex quantum simulations that will allow scientists to study neutron stars, learn more about the earliest moments of the universe, and realize the revolutionary potential of quantum computers.

Continue reading “Researchers achieve first quantum simulation of baryons” »

The first ever simulation of baryons on a quantum computer is reported by the University of Waterloo.

Do you know what a computer can do in that time?

Scientists created an intelligent material that acts as a brain by physically changing when it learns. This is an important step toward a new generation of computers that could dramatically increase computing power while using less energy.

Artificial intelligence imitates human intelligence by recognizing patterns and learning new things. Currently, it is run on machine learning software. But the “smarter” computers get, the more computing power they require. This can lead to a sizable energy footprint, which could destabilize the computer.

In the last seven years, computer usage has increased by 300,000-fold. Since 2012 the amount of computing power used to train the largest AI models has doubled every 3.4 months, the MIT Technology Review reports. And, the escalating costs of deep learning, can have environmental costs too. Researchers at the University of Massachusetts, Amherst, found that a common large AI model emits more than 626,000 pounds of carbon dioxide in its lifetime, nearly five times that of the average American car.