Lifeboat Foundation: Safeguarding Humanity
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Greenhouse gas emissions need to be significantly reduced to avoid potentially catastrophic effects of climate change, with access to clean and affordable energy needed to eliminate our reliance on fossil fuels. Many researchers and companies are working to address this issue and replace fossil fuels through the use of hydrogen, a storable fuel.

When used in a fuel cell, hydrogen does not emit any greenhouse gasses at the point of use and can help decarbonize sectors such as shipping and transportation, where it can be used as a fuel, as well as in manufacturing industries. However, most hydrogen produced today is almost entirely supplied from natural gas and coal, producing greenhouse gases. And therefore, green hydrogen production is urgently needed.

New research led by the University of Strathclyde suggests that solar energy can be accessed and converted into hydrogen – a clean and renewable fuel.

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The James Webb Space Telescope dima_zel/ iStock

Between May 23 and 25, the James Webb Space Telescope (JWST) was hit by a micrometeoroid that has impacted one of its primary mirror segments, NASA said in a recent update on its website. The telescope continues to function at levels exceeding mission requirements.

A meteoroid is a fragment of an asteroid and can be either large or small. A micrometeoroid, though, is a microscopic fragment of a meteoroid and is smaller than a grain of sand. NASA estimates that millions of meteoroids and micrometeoroids strike the Earth’s atmosphere every day but most burn up due to the friction.

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The Silurian Hypothesis contemplates how long the ruins of a civilization would be detectable, on Earth or even other worlds, and if we could ever know if a world had once been inhabited by a technological civilization.

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A team of researchers affiliated with multiple institutions in the U.S., including Google Quantum AI, and a colleague in Australia, has developed a theory suggesting that quantum computers should be exponentially faster on some learning tasks than classical machines. In their paper published in the journal Science, the group describes their theory and results when tested on Google’s Sycamore quantum computer. Vedran Dunjko with Leiden University City has published a Perspective piece in the same journal issue outlining the idea behind combining quantum computing with machine learning to provide a new level of computer-based learning systems.

Machine learning is a system by which computers trained with datasets make informed guesses about new data. And quantum computing involves using sub-atomic particles to represent qubits as a means for conducting applications many times faster than is possible with . In this new effort, the researchers considered the idea of running machine-learning applications on quantum computers, possibly making them better at learning, and thus more useful.

To find out if the idea might be possible, and more importantly, if the results would be better than those achieved on classical computers, the researchers posed the problem in a novel way—they devised a task that would learn via experiments repeated many times over. They then developed theories describing how a quantum system could be used to conduct such experiments and to learn from them. They found that they were able to prove that a quantum could do it, and that it could do it much better than a classical system. In fact, they found a reduction in the required number of experiments needed to learn a concept to be four orders of magnitude lower than for classical systems. The researchers then built such a system and tested it on Google’s Sycamore quantum computer and confirmed their theory.

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Nuclear fusion is a widely studied process through which atomic nuclei of a low atomic number fuse together to form a heavier nucleus, while releasing a large amount of energy. Nuclear fusion reactions can be produced using a method known as inertial confinement fusion, which entails the use of powerful lasers to implode a fuel capsule and produce plasma.

Researchers at Massachusetts Institute of Technology (MIT), University of Delaware, University of Rochester, the Lawrence Livermore National Laboratory, Imperial College London, and University of Rome La Sapienza have recently showed what happens to this implosion when one applies a strong to the fuel capsule used for . Their paper, published in Physical Review Letters, demonstrates that strong magnetic fields flatten the shape of inertial fusion implosions.

“In inertial confinement fusion, a millimeter-size spherical capsule is imploded using high-power lasers for ,” Arijit Bose, one of the researchers who carried out the study, told Phys.org. “Applying a magnetic field to the implosions can strap the charged plasma particles to the B-field and improve their chances of fusion. However, since magnetic field can restrict plasma particle motion only in the direction across the field lines and not in the direction along the applied field lines, this can introduce differences between the two directions that affect the implosion shape.”

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USC scientists have found evidence that the Earth’s inner core oscillates, contradicting previously accepted models that suggested it consistently rotates at a faster rate than the planet’s surface.

Their study, published today in Science Advances, shows that the inner core changed direction in the six-year period from 1969–74, according to the analysis of seismic data. The scientists say their model of inner core movement also explains the variation in the length of day, which has been shown to oscillate persistently for the past several decades.

“From our findings, we can see the Earth’s surface shifts compared to its inner core, as people have asserted for 20 years,” said John E. Vidale, co-author of the study and Dean’s Professor of Earth Sciences at USC Dornsife College of Letters, Arts and Sciences. “However, our latest observations show that the inner core spun slightly slower from 1969–71 and then moved the other direction from 1971–74. We also note that the length of day grew and shrank as would be predicted.

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Researchers at Duke University and the University of Maryland have used the frequency of measurements on a quantum computer to get a glimpse into the quantum phenomena of phase changes—something analogous to water turning to steam.

By measuring the number of operations that can be implemented on a quantum computing system without triggering the collapse of its quantum state, the researchers gained insight into how other systems—both natural and computational—meet their tipping points between phases. The results also provide guidance for working to implement that will eventually enable quantum computers to achieve their full potential.

The results appeared online June 3 in the journal Nature Physics.

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A major campaign of domino-toppling simulations yields new insights into the effects of friction.

Despite the apparent simplicity of toppling dominoes, physicists still don’t have a complete model of the phenomenon. But new numerical simulations get a step closer by untangling the influence of two types of friction—one between neighboring dominoes and the other between each domino and the surface beneath it [1]. The researchers found that, in some cases, these two friction coefficients play competing roles in determining the speed of the domino cascade. They also found that one of the coefficients behaves similar to friction in granular systems such as piles of sand or pharmaceutical pills, suggesting that the domino simulations may provide insights into other situations where friction is important.

A YouTube video by engineer Destin Sandlin (on his channel Smarter Every Day) inspired David Cantor of Montreal Polytechnic and Kajetan Wojtacki of the Polish Academy of Sciences in Warsaw to study dominoes. Sandlin recorded a series of domino toppling experiments with a high-speed camera and quickly discovered just how complex the problem is. He determined that the wave of falling dominoes moves slightly faster on felt than on a slippery hardwood floor. He also saw surprising anomalies, such as cases where the train of toppling dominoes would abruptly stop.

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Noise in an electronic circuit is a nuisance that can scramble information or reduce a detector’s sensitivity. But noise also offers a way to learn about the microscopic quantum mechanisms at play in a material or device. By measuring a circuit’s “shot noise,” a form of white noise, researchers have previously shed light on conduction in quantum Hall and spintronic systems, for instance. Now, a collaboration led by Oren Tal at the Weizmann Institute of Science, Israel, and by Dvira Segal at the University of Toronto, Canada, has shown that an easier-to-measure form of noise, called “flicker noise,” can also be a powerful probe of quantum effects [1].

Flicker noise is a type of pink noise, whose spectrum is dominated by low frequencies—the kind of noise associated with light rainfall. Flicker noise also appears in electrical circuits, but its connection to microscopic transport channels remains poorly understood. To investigate this connection, the team studied an atomic-scale junction between two wires. They modeled the electrons passing through the junction as coherent quantum-mechanical waves that scatter off fluctuating defects located near the junction. These fluctuations can represent the trapping and releasing of electrons by static defects, the movement of charged impurities between lattice sites, and the fluctuations of atoms and molecules adsorbed on surfaces.

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