Lifeboat Foundation

Top quarks and antiquarks produced in the Large Hadron Collider are entangled, a study shows.

A summary of an argumentative paper by Litt, Eliasmith, Kroon, Weinstein and Thagard.

In recent years, a community of researchers from various universities and institutes across Europe and the United States set out to explore the physics of micro-and nano-mechanical devices coupled to light. The initial focus of these investigations was on demonstrating and exploiting uniquely quantum effects in the interaction of light and mechanical motion, such as quantum superposition, where a mechanical oscillator occupies two places simultaneously. The scope of this work quickly broadened as it became clear that these so-called optomechanical devices would open the door to a broad range of new applications.

Hybrid Optomechanical Technologies (HOT) is a research and innovation action funded by the European Commission’s FET Proactive program that supports future and emerging technologies at an early stage. HOT is laying the foundation for a new generation of devices that bring together several nanoscale platforms in a single hybrid system. It unites researchers from thirteen leading academic groups and four major industrial companies across Europe working to bring technologies to market that exploit the combination of light and motion.

One key set of advances made in the HOT consortium involves a family of non-reciprocal optomechanical devices, including optomechanical circulators. Imagine a device that acts like a roundabout for light or microwaves, where a signal input from one port emerges from a second port, and a signal input from that second port emerges from a third one, and so on. Such a device is critical to signal processing chains in radiofrequency or optical systems, as it allows efficient distribution of information among sources and receivers and protection of fragile light sources from unwanted back-reflections. It has however proven very tricky to implement a circulator at small scales without involving strong magnetic fields to facilitate the required unidirectional flow of signals.

In recent years, these technological limitations have become far more pressing. Deep neural networks have radically expanded the limits of artificial intelligence—but they have also created a monstrous demand for computational resources, and these resources present an enormous financial and environmental burden. Training GPT-3, a text predictor so accurate that it easily tricks people into thinking its words were written by a human, costs $4.6 million and emits a sobering volume of carbon dioxide—as much as 1,300 cars, according to Boahen.

With the free time afforded by the pandemic, Boahen, who is faculty affiliate at the Wu Tsai Neurosciences Institute at Stanford and the Stanford Institute for Human-Centered AI (HAI), applied himself single mindedly to this problem. “Every 10 years, I realize some blind spot that I have or some dogma that I’ve accepted,” he says. “I call it ‘raising my consciousness.’”

This time around, raising his consciousness meant looking toward dendrites, the spindly protrusions that neurons use to detect signals, for a completely novel way of thinking about computer chips. And, as he writes in Nature, he thinks he’s figured out how to make chips so efficient that the enormous GPT-3 language prediction neural network could one day be run on a cell phone. Just as Feynman posited the “quantum supremacy” of quantum computers over traditional computers, Boahen wants to work toward a “neural supremacy.”

Even those of us who aren’t physicists have an intuitive understanding of classical physics — we can predict what will happen when we throw a ball, use a salad spinner, or ease up on the gas pedal.

But atomic and subatomic particles don’t follow these ordinary rules of reality. “It turns out that at really small scales there are a different set of rules called quantum physics,” said Travis Nicholson. “These rules are bizarre and interesting.” (Think Schrodinger’s cat and Einstein’s “spooky action at a distance.”)

Nicholson is an assistant professor with joint appointments in Physics and Electrical and Computer Engineering. The physicist in him likes doing experiments to advance our knowledge of quantum mechanics; the engineer in him likes figuring out how to harness that knowledge to build quantum computers that will be vastly more powerful than today’s computers.

MIT physicists and colleagues have created a new material with unusual superconducting and metallic properties, thanks to wavy layers of atoms only billionths of a meter thick that repeat themselves over and over to create a macroscopic sample that can be manipulated by hand. The large size of the sample makes it much easier to explore its quantum behavior, or interactions at the atomic scale that give rise to its properties.

The topological quantum computer still exists only in theory but, if possible, would be the most stable and powerful computing machine in the world. However, it requires a special type of qubit (quantum bit) that has yet to be realized and manipulated.

Analysis suggests that the two pioneers of quantum mechanics, Niels Bohr and John von Neumann, may have had more similar views than previously thought regarding the nature of quantum systems, and the classical apparatus used to measure them.

Quantum entanglement is a fascinating feature of quantum physics—the theory of the very small. If two particles are quantum-entangled, the state of one particle is tied to that of the other, no matter how far apart the particles are. This mind-bending phenomenon, which has no analog in classical physics, has been observed in a wide variety of systems and has found several important applications, such as quantum cryptography and quantum computing.