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Category: quantum physics

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 world, UC Santa Barbara researchers have developed a device that could prove the existence of non-Abelian anyons, a 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).

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O,.o woah!

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.

You are now ready to run your own large simulations on Google Cloud. For sample code of a large circuit, see the Simulate a large circuit tutorial.

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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.

“This is an important step forward—it is the first of baryons on a quantum ever,” Christine Muschik, an IQC faculty member, said. “Instead of smashing particles in an accelerator, a quantum computer may one day allow us to simulate these interactions that we use to study the origins of the universe and so much more.”

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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.

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Sandia National Laboratories is developing an avocado-sized vacuum chamber made out of titanium and sapphire that could one day use quantum mechanical sensors to provide GPS-grade navigation without the need for satellites.

In only a few short decades, GPS has gone from a military technology to finding so many everyday applications that modern society is now dependent on it. However, GPS is not always available in places like high polar latitudes or in deep mountain valleys, and it can be jammed or spoofed.

The vulnerability of GPS and similar systems lies in their dependence on constellations of satellites that orbit the Earth. These satellites emit time-stamped signals that are synced to atomic clocks. Using these signals, a GPS receiver in something as small as a wristwatch can use the Doppler effect on the satellite signals as they pass overhead to make an extremely precise fix on the receiver’s position and velocity. If these signals are interrupted or corrupted, the system fails.

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When sound was first incorporated into movies in the 1920s, it opened up new possibilities for filmmakers such as music and spoken dialogue. Physicists may be on the verge of a similar revolution, thanks to a new device developed at Stanford University that promises to bring an audio dimension to previously silent quantum science experiments.

In particular, it could bring sound to a common quantum science setup known as an , which uses a crisscrossing mesh of laser beams to arrange atoms in an orderly manner resembling a crystal. This tool is commonly used to study the fundamental characteristics of solids and other phases of matter that have repeating geometries. A shortcoming of these lattices, however, is that they are silent.

“Without sound or vibration, we miss a crucial degree of freedom that exists in real materials,” said Benjamin Lev, associate professor of applied physics and of physics, who set his sights on this issue when he first came to Stanford in 2011. “It’s like making soup and forgetting the salt; it really takes the flavor out of the quantum ‘soup.’”.

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A new phase of matter, thought to be understandable only using quantum physics, can be studied with far simpler classical methods.

Researchers from the University of Cambridge used computer modeling to study potential new phases of matter known as prethermal discrete time crystals (DTCs). It was thought that the properties of prethermal DTCs were reliant on : the strange laws ruling particles at the subatomic scale. However, the researchers found that a simpler approach, based on classical physics, can be used to understand these mysterious phenomena.

Understanding these new phases of matter is a step forward towards the control of complex many-body systems, a long-standing goal with various potential applications, such as simulations of complex quantum networks. The results are reported in two joint papers in Physical Review Letters and Physical Review B.

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