Lifeboat Foundation

As pervasive as they are in everyday uses, like encryption and security, randomly generated digital numbers are seldom truly random.

So far, only bulky, relatively slow quantum random number generators (QRNGs) can achieve levels of randomness on par with the basic laws of quantum physics, but researchers are looking to make these devices faster and more portable.

In Applied Physics Letters, scientists from China present the fastest real-time QRNG to date to make the devices quicker and more portable. The device combines a state-of-the-art photonic integrated chip with optimized real-time postprocessing for extracting randomness from quantum entropy source of vacuum states.

Quantum mechanics deals with the behavior of the Universe at the super-small scale: atoms and subatomic particles that operate in ways that classical physics can’t explain. In order to explore this tension between the quantum and the classical, scientists are attempting to get larger and larger objects to behave in a quantum-like way.

In the case of this particular study, the object in question is a tiny glass nanosphere, 100 nanometers in diameter – about a thousand times smaller than the thickness of a human hair. To our minds that’s very, very small, but in terms of quantum physics, it’s actually rather huge, made up to 10 million atoms.

Pushing such a nanosphere into the realm of quantum mechanics is actually a huge achievement, and yet that’s exactly what physicists have now accomplished.

A potentially life-saving treatment for heart attack victims has been discovered from a very unlikely source — the venom of one of the world’s deadliest spiders.

A drug candidate developed from a molecule found in the venom of the Fraser Island (K’gari) funnel web spider can prevent damage caused by a heart attack and extend the life of donor hearts used for organ transplants. The discovery was made by a team led by Dr Nathan Palpant and Professor Glenn King from The University of Queensland (UQ) and Professor Peter Macdonald from the Victor Chang Cardiac Research Institute.

Dr Palpant, from UQ’s Institute for Molecular Bioscience (IMB), said the drug candidate worked by stopping a ‘death signal’ sent from the heart in the wake of an attack.

An 18-year-old is about to become the youngest person in space, rocketing away with an aviation pioneer who will become the oldest at age 82.

Blue Origin announced Thursday that instead of a $28 million auction winner launching with founder Jeff Bezos on Tuesday, the Dutch son of another bidder will be on board. The company said Oliver Daemen will be the first paying customer, but did not disclose the price of his ticket. A family spokesperson said it will be considerably less than the winning bid.

Daemen snagged the fourth and last seat on the space capsule after the auction winner stepped aside because of a scheduling conflict. The offer came in a surprise phone call from Blue Origin last week, he said.

Scientists have waited months for access to highly accurate protein structure prediction since DeepMind presented remarkable progress in this area at the 2020 Critical Assessment of Structure Prediction, or CASP14, conference. The wait is now over.

Researchers at the Institute for Protein Design at the University of Washington School of Medicine in Seattle have largely recreated the performance achieved by DeepMind on this important task. These results will be published online by the journal Science on Thursday, July 15.

Unlike DeepMind, the UW Medicine team’s method, which they dubbed RoseTTAFold, is freely available. Scientists from around the world are now using it to build protein models to accelerate their own research. Since July, the program has been downloaded from GitHub by over 140 independent research teams.

Users are rattled after learning their devices and networks were exposed.

A collaborative research team, led by the University of Liverpool, has discovered a new inorganic material with the lowest thermal conductivity ever reported. This discovery paves the way for the development of new thermoelectric materials that will be critical for a sustainable society.

Reported in the journal Science, this discovery represents a breakthrough in the control of heat flow at the atomic scale, achieved by materials design. It offers fundamental new insights into the management of energy. The new understanding will accelerate the development of new materials for converting waste heat to power and for the efficient use of fuels.

The research team, led by Professor Matt Rosseinsky at the University’s Department of Chemistry and Materials Innovation Factory and Dr. Jon Alaria at the University’s Department of Physics and Stephenson Institute for Renewable Energy, designed and synthesized the new material so that it combined two different arrangements of atoms that were each found to slow down the speed at which heat moves through the structure of a solid.

Electronic circuits that compute and store information contain millions of tiny switches that control the flow of electric current. A deeper understanding of how these tiny switches work could help researchers push the frontiers of modern computing.

Now scientists have made the first snapshots of atoms moving inside one of those switches as it turns on and off. Among other things, they discovered a short-lived state within the switch that might someday be exploited for faster and more energy-efficient computing devices.

The research team from the Department of Energy’s SLAC National Accelerator Laboratory, Stanford University, Hewlett Packard Labs, Penn State University and Purdue University described their work in a paper published in Science today.

The Google Quantum AI team has found that adding logical qubits to the company’s quantum computer reduced the logical qubit error rate exponentially. In their paper published in the journal Nature, the group describes their work with logical qubits as an error correction technique and outline what they have learned so far.

One of the hurdles standing in the way of the creation of usable quantum computers is figuring out how to either prevent errors from occurring or fixing them before they are used as part of a computation. On traditional computers, the problem is mostly solved by adding a parity bit—but that approach will not work with quantum computers because of the different nature of qubits—attempts to measure them destroy the data. Prior research has suggested that one possible solution to the problem is to group qubits into clusters called logical qubits. In this new effort, the team at AI Quantum has tested this idea on Google’s Sycamore quantum computer.

Sycamore works with 54 physical qubits, in their work, the researchers created logical qubits of different sizes ranging from five to 21 qubits to see how each would work. In so doing, they found that adding qubits reduced error rates exponentially. They were able to measure the extra qubits in a way that did not involve collapsing their state, but that still provided enough information for them to be used for computations.