Lifeboat Foundation

A pressing quest in the field of nanoelectronics is the search for a material that could replace silicon. Graphene has seemed promising for decades. But its potential has faltered along the way, due to damaging processing methods and the lack of a new electronics paradigm to embrace it. With silicon nearly maxed out in its ability to accommodate faster computing, the next big nanoelectronics platform is needed now more than ever.

Walter de Heer, Regents’ Professor in the School of Physics at the Georgia Institute of Technology, has taken a critical step forward in making the case for a successor to silicon. De Heer and his collaborators have developed a new nanoelectronics platform based on graphene —a single sheet of carbon atoms. The technology is compatible with conventional microelectronics manufacturing, a necessity for any viable alternative to silicon.

In the course of their research, published in Nature Communications, the team may have also discovered a new quasiparticle. Their discovery could lead to manufacturing smaller, faster, more efficient and more sustainable computer chips, and has potential implications for quantum and high-performance computing.

In physics, weak microwave signals can be amplified with minimal added noise. For instance, artificial quantum systems based on superconducting circuits can amplify and detect single microwave patterns, although at millikelvin temperatures. Researchers can use natural quantum systems for low-noise microwave amplification via stimulated emission effects; however, they generate a higher noise at functionalities greater than 1 Kelvin.

In this new work, published in the journal Science Advances, Alexander Sherman and a team of scientists in chemistry at the Technical-Israel Institute of Technology, Haifa, used electron spins in diamond as a quantum microwave amplifier to function with quantum-limited internal noise above liquid nitrogen temperatures. The team reported details of the amplifier’s design, gain, bandwidth, saturation power and noise to facilitate hitherto unavailable applications in quantum science, engineering and physics.

For decades, physicists have been hunting for a quantum-gravity model that would unify quantum physics, the laws that govern the very small, and gravity. One major obstacle has been the difficulty in testing the predictions of candidate models experimentally. But some of the models predict an effect that can be probed in the lab: a very small violation of a fundamental quantum tenet called the Pauli exclusion principle, which determines, for instance, how electrons are arranged in atoms.

A project carried out at the INFN underground laboratories under the Gran Sasso mountains in Italy, has been searching for signs of radiation produced by such a violation in the form of atomic transitions forbidden by the Pauli exclusion principle.

In two papers appearing in the journals Physical Review Letters (published on September 19, 2022) and Physical Review D (accepted for publication on December 7, 2022) the team reports that no evidence of violation has been found, thus far, ruling out some quantum-gravity models.

Quantum telepathy, laser-based time crystals, a glow from empty space and an “unreal” universe—these are the most awesome (and awfully hard to understand) results from the subatomic realm we encountered in 2022.

How a century of research culminated in the first lab-built wormhole linking classical physics and the quantum world.

We are aware of how skewed our perception of reality is. How we see the world is shaped by our senses, our societies, and our knowledge.

And you may want to rethink your belief that science will always provide you with an objective reality.

Water has puzzled scientists for decades. For the last 30 years or so, they have theorized that when cooled down to a very low temperature like-100C, water might be able to separate into two liquid phases of different densities. Like oil and water, these phases don’t mix and may help explain some of water’s other strange behavior, like how it becomes less dense as it cools.

It’s almost impossible to study this phenomenon in a lab, though, because water crystallizes into ice so quickly at such low temperatures. Now, new research from the Georgia Institute of Technology uses machine learning models to better understand water’s phase changes, opening more avenues for a better theoretical understanding of various substances. With this technique, the researchers found strong computational evidence in support of water’s liquid-liquid transition that can be applied to real-world systems that use water to operate.

“We are doing this with very detailed quantum chemistry calculations that are trying to be as close as possible to the real physics and physical chemistry of water,” said Thomas Gartner, an assistant professor in the School of Chemical and Biomolecular Engineering at Georgia Tech. “This is the first time anyone has been able to study this transition with this level of accuracy.”

In spin-based quantum processors, each quantum dot of a qubit is populated by exactly one electron, which requires careful tuning of each gate voltage such that it lies inside the charge-stability region (the “Coulomb diamond’‘) associated with the dot array. However, mapping the boundary of a multidimensional Coulomb diamond by traditional dense raster scanning would take years, so the authors develop a sparse acquisition technique that autonomously learns Coulomb-diamond boundaries from a small number of measurements. Here we have hardware-triggered line searches in the gate-voltage space of a silicon quadruple dot, with smart search directions proposed by an active-learning algorithm.

A single particle has no temperature. It has a certain energy or a certain speed—but it is not possible to translate that into a temperature. Only when dealing with random velocity distributions of many particles does a well-defined temperature emerge.

How can the laws of thermodynamics arise from the laws of quantum physics? This is a topic that has attracted growing attention in recent years. At TU Wien (Vienna), this question has now been pursued with computer simulations, which showed that chaos plays a crucial role: Only where chaos prevails do the well-known rules of thermodynamics follow from quantum physics.