Lifeboat Foundation

In February 2019, JQI Fellow Alicia Kollár, who is also an assistant professor of physics at UMD, bumped into Adrian Chapman, then a postdoctoral fellow at the University of Sydney, at a quantum information conference. Although the two came from very different scientific backgrounds, they quickly discovered that their research had a surprising commonality. They both shared an interest in graph theory, a field of math that deals with points and the connections between them.

Chapman found graphs through his work in quantum error correction —a field that deals with protecting fragile quantum information from errors in an effort to build ever-larger quantum computers. He was looking for new ways to approach a long-standing search for the Holy Grail of quantum error correction: a way of encoding quantum information that is resistant to errors by construction and doesn’t require active correction. Kollár had been pursuing new work in graph theory to describe her photon-on-a-chip experiments, but some of her results turned out to be the missing piece in Chapman’s puzzle.

Their ensuing collaboration resulted in a new tool that aids in the search for new quantum error correction schemes—including the Holy Grail of self-correcting quantum error correction. They published their findings recently in the journal Physical Review X Quantum.

Experiments have shown how the world’s hardiest microbe could endure freezing, dry and irradiated conditions on Mars.

The world wide web is not enough, because scientists have managed to transmit data at a staggering 1.84 petabits per second — nearly twice the amount of global internet traffic in the same interval.

That blows the previous record for data transmission using a single light source and optical chip of one petabit per second out the water. And to put that ridiculous amount into perspective, a petabit is equal to one million gigabits. A single gigabit, or 1,000 megabits, is about the fastest download speed money can buy for most households.

To achieve the astonishing feat, researchers from the Technical University of Denmark (DTU) and Chalmers University of Technology used a custom optical chip that can make use of a single infrared light by splitting it into hundreds of different frequencies that are evenly spaced apart. Collectively, they’re known as a frequency comb. Each frequency on the comb can discretely hold data by modulating the wave properties of light, allowing scientists to transmit far more bits than conventional methods.

The large diversity of organic molecules detected on Mars is a hint that life once existed there, but where should we search?

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Continue reading “Were Organic Molecules on Mars Made by Life?” »

Dr. Peter Fedichev, Ph.D. is the CEO of Gero (https://gero.ai/), a biotech company focused on hacking complex diseases, including aging, with AI for novel drug discovery, as well as digital biomarkers.

Gero’s models originate from the physics of complex dynamic systems, combining the potential of deep neural networks with the physical models to study dynamical processes and understand what drives diseases.

Continue reading “Dr. Peter Fedichev, PhD — CEO, Gero — Hacking Complex Diseases & Aging with AI & Digital Biomarkers” »

The objects seen on this roof are novel small-form-factor wind turbines. But read on to learn about a Bronze Age reinvention.

Two novel technologies represent innovation for those in the energy industry.

Oocytes prevent the production of reactive oxygen species by remodelling the mitochondrial electron transport chain through elimination of complex I, a strategy that enables their long-term viability.

Engineers at the SLAC National Accelerator Laboratory in California are putting the finishing touches on the world’s largest digital camera, which will be at the heart of the Vera C. Rubin Observatory.

Ultrasound sensors as small as a thumbnail can scan lithium-ion batteries to check their charge, health, and safety, a new study finds.

The findings suggest that ultrasound—that is, sound waves at frequencies higher than human hearing can detect—might one day help electric vehicles better estimate how much charge remains in their batteries. This approach might also help detect unstable batteries on the verge of disaster, quickly test battery quality during manufacturing, and identify which used batteries are healthy enough to be resold to reduce waste, says study lead author Hongbin Sun, an ultrasonic engineer at the Oak Ridge National Laboratory, in Tennessee.

Estimating how much charge is left in a commercial lithium-ion battery is currently a challenging task. For instance, electric vehicles typically experience an uncertainty of about 10 percent when estimating battery charge. This in turn reduces their driving range by about 10 percent, to ensure that they stay within their batteries’ safety margins.