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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.

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.

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 optical lattice, 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.’”.

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 quantum physics: 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.

A team of physicists and engineers at Lawrence Berkeley National Laboratory (Berkeley Lab) successfully demonstrated the feasibility of low-cost and high-performance radio frequency modules for qubit controls at room temperature. They built a series of compact radio frequency (RF) modules that mix signals to improve the reliability of control systems for superconducting quantum processors. Their tests proved that using modular design methods reduces the cost and size of traditional RF control systems while still delivering superior or comparable performance levels to those commercially available.

Their research, featured as noteworthy in the Review of Scientific Instruments and selected as a Scilight by the American Institute of Physics, is open source and has been adopted by other quantum information science (QIS) groups. The team expects the RF modules’ compact design is suitable for adaptation to the other qubit technologies as well. The research was conducted at the Advanced Quantum Testbed (AQT) at Berkeley Lab, a collaborative research program funded by the U.S. Department of Energy’s Office of Science.