Lifeboat Foundation

A massive hole opened up in the Sun’s atmosphere over the weekend, measuring more than 60 times the diameter of the Earth across at its peak.

Coronal holes like this one, imaged by NASA’s Solar Dynamics Observatory, occur when the Sun’s magnetic field suddenly allows a huge stream of the star’s upper atmosphere to pour out in the form of solar wind.

Over a short period of time, these highly energized particles can eventually make their way to us and — if powerful enough — wreak havoc on satellites in the Earth’s orbit. In rare instances, they can even mess with the electrical grid back on the ground.

As someone who never lived in the extreme northern latitudes of Earth, I always found it exciting when I heard auroras might be visible farther south. I would always crane my eyes skyward, hoping I could see those ghostly dancing lights, almost trying to wish them into existence. Alas, I was never that lucky. Though as we approach solar maximum in 2025, we ought not to only get excited about seeing auroras, but perhaps also ask: What could a powerful geomagnetic storm do to our technological infrastructure?

Geomagnetic storms can be triggered by either coronal mass ejections, giant bubbles of plasma erupting from the surface of the sun, or very powerful solar flares. It’s because these events can accelerate particles to extremely fast speeds. And when some of those particles hit the Earth’s magnetic field, this generates what we see as brilliant auroras — however, those particles can also damage satellite equipment and even harm astronauts in orbit.

A truly gigantic magnetic storm has not affected the Earth in well over one hundred years — and since then, technology has changed quite significantly. Satellite communications, air travel and the power grid have been brought into existence, and they all can be impacted by these events. Yet, scientists aren’t quite sure what, exactly, would happen to the integral technological components of society if a major solar storm shrouded Earth with charged particle showers.

Physicists at the University of Regensburg have found a way to manipulate the quantum state of individual electrons using a microscope with atomic resolution. The results of the study have now been published in the journal Nature.

We, and everything around us, consist of molecules. The molecules are so tiny that even a speck of dust contains countless numbers of them. It is now routinely possible to precisely image such molecules with an atomic force microscope, which works quite differently from an optical microscope: it is based on sensing tiny forces between a tip and the molecule under study.

Using this type of microscope, one can even image the internal structure of a molecule. Although one can watch the molecule this way, this does not imply knowing all its different properties. For instance, it is already very hard to determine which kind of atoms the molecule consists of.

A radical theory that consistently unifies gravity and quantum mechanics while preserving Einstein’s classical concept of spacetime is announced today in two papers published simultaneously by UCL (University College London) physicists.

Modern physics is founded upon two pillars: quantum theory on the one hand, which governs the smallest particles in the universe, and Einstein’s theory of general relativity on the other, which explains gravity through the bending of spacetime. But these two theories are in contradiction with each other and a reconciliation has remained elusive for over a century.

Challenging the status quo: a new theoretical approach.

The field of attosecond physics was established with the mission of exploring light–matter interactions at unprecedented time resolutions. Recent advancements in this field have allowed physicists to shed new light on the quantum dynamics of charge carriers in atoms and molecules.

A technique that has proved particularly valuable for conducting research in this field is RABBITT (i.e., the Reconstruction of Attosecond Beating By Interference of Two-photon Transitions). This promising tool was initially used to characterize ultrashort laser pulses, as part of a research effort that won this year’s Nobel Prize, yet it has since also been employed to measure other ultrafast physical phenomena.

Researchers at East China Normal University and Queen’s University Belfast recently built on the RABBITT technique to distinctly measure individual contributions in photoionization. Their paper, published in Physical Review Letters, introduces a new highly promising method for conducting attosecond physics research.

Researchers have precisely measured the electrical-transport properties of a highly ordered Wigner solid—a crystalline state formed of electrons rather than atoms.

When Emiliano Cortés goes hunting for sunlight, he doesn’t use gigantic mirrors or sprawling solar farms. Quite the contrary, the professor of experimental physics and energy conversion at LMU dives into the nanocosmos.

“Where the high-energy particles of sunlight, the photons, meet atomic structures is where our research begins,” Cortés says. “We are working on material solutions to capture and use solar energy more efficiently.”

His findings have great potential as they enable novel solar cells and photocatalysts. The industry has high hopes for the latter because they can make light energy accessible for chemical reactions—bypassing the need to generate electricity. But there is one major challenge to using sunlight, which solar cells also have to contend with, Cortés knows: “Sunlight arrives on Earth ‘diluted,’ so the energy per area is comparatively low.” Solar panels compensate for this by covering large areas.

Long before the Deep Underground Neutrino Experiment takes its first measurements in an effort to expand our understanding of the universe, a prototype for one of the experiment’s detectors is blazing new trails in neutrino detection technology.

DUNE, currently under construction, will be a massive experiment that spans more than 800 miles. A beam of neutrinos originating at the U.S. Department of Energy’s Fermi National Accelerator Laboratory will pass through a particle detector located on the Fermilab site, then travel through the ground to a huge detector at the Sanford Underground Research Facility in South Dakota.

The near detector consists of a set of particle detection systems. One of them, known as the ND-LAr, will feature a liquid-argon time projection chamber to record particle tracks; it will be placed inside a container full of liquid argon. When a neutrino collides with one of the particles that make up argon atoms, the collision generates more particles. As each particle created in the collision travels out of the nucleus, it interacts with nearby atoms, stripping off some of their electrons, leading to the production of detectable signals in the form of light and charge.

A first-principles model accounts for the wide range of critical temperatures (T_c’s) for four materials and suggests a parameter that determines T_c in any high-temperature superconductor.

Since the first high-temperature superconducting materials, known as the cuprates, were discovered in 1986, researchers have struggled to explain their properties and to find materials with even higher superconducting transition temperatures (T_c’s). One puzzle has been the cuprates’ wide variation in T_c, ranging from below 10 K to above 130 K. Now Masatoshi Imada of Waseda University in Japan and his colleagues have used first-principles calculations to determine the order parameters—which measure the density of superconducting electrons—for four cuprate materials and have predicted the T_c’s based on those order parameters [1]. The researchers have also found what they believe is the fundamental parameter that determines T_c in a given material, which they hope will lead to the development of higher-temperature superconductors.

For each material, Imada and his colleagues applied the basic principles of quantum mechanics, focusing on the planes of copper and oxygen atoms that are known to host the superconducting electrons. They used a combination of numerical techniques, including one supplemented by machine learning, and did not require any adjustable parameters.