Lifeboat Foundation

A new methodology for analyzing the 3D distribution of galaxies borrows techniques from the study of colloids and other disordered materials.

A study of the electron excitation response of DNA to proton radiation has elucidated mechanisms of damage incurred during proton radiotherapy.

Radiobiology studies on the effects of ionizing radiation on human health focus on the deoxyribonucleic acid (DNA) molecule as the primary target for deleterious outcomes. The interaction of ionizing radiation with tissue and organs can lead to localized energy deposition large enough to instigate double strand breaks in DNA, which can lead to mutations, chromosomal aberrations, and changes in gene expression. Understanding the mechanisms behind these interactions is critical for developing radiation therapies and improving radiation protection strategies. Christopher Shepard of the University of North Carolina at Chapel Hill and his colleagues now use powerful computer simulations to show exactly what part of the DNA molecule receives damaging levels of energy when exposed to charged-particle radiation (Fig. 1) [1]. Their findings could eventually help to minimize the long-term radiation effects from cancer treatments and human spaceflight.

The interaction of radiation with DNA’s electronic structure is a complex process [2, 3]. The numerical models currently used in radiobiology and clinical radiotherapy do not capture the detailed dynamics of these interactions at the atomic level. Rather, these models use geometric cross-sections to predict whether a particle of radiation, such as a photon or an ion, crossing the cell volume will transfer sufficient energy to cause a break in one or both of the DNA strands [4– 6]. The models do not describe the atomic-level interactions but simply provide the probability that some dose of radiation will cause a population of cells to lose their ability to reproduce.

Strongly correlated systems are systems made of particles that strongly interact with one another, to such an extent that their individual behavior depends on the behavior of all other particles in the system. In states that are far from equilibrium, these systems can sometimes give rise to fascinating and unexpected physical phenomena, such as many-body localization.

Many-body localization occurs when a system made of interacting particles fails to reach thermal equilibrium even at high temperatures. In many-body localized systems, particles thus remain in a state of non-equilibrium for long periods of time, even when a lot of energy is flowing through them.

Theoretical predictions suggest that the instability of the many-body localized phase is caused by small thermal inclusions in the strongly interacting system that act as a bath. These inclusions prompt the delocalization of the entire system, through a mechanism that is known as avalanche propagation.

Graph neural networks (GNNs) are promising machine learning architectures designed to analyze data that can be represented as graphs. These architectures achieved very promising results on a variety of real-world applications, including drug discovery, social network design, and recommender systems.

As graph-structured data can be highly complex, graph-based machine learning architectures should be designed carefully and effectively. In addition, these architectures should ideally be run on efficient hardware that support their computational demands without consuming too much power.

Continue reading “A system integrating echo state graph neural networks and analogue random resistive memory arrays” »

Water makes up 71% of Earth’s surface, but no one knows how or when such massive quantities of water arrived on Earth.

A new study published in the journal Nature brings scientists one step closer to answering that question. Led by University of Maryland Assistant Professor of Geology Megan Newcombe, researchers analyzed melted meteorites that had been floating around in space since the solar system’s formation 4 1/2 billion years ago. They found that these meteorites had extremely low water content—in fact, they were among the driest extraterrestrial materials ever measured.

These results, which let researchers rule them out as the primary source of Earth’s water, could have important implications for the search for water—and life—on other planets. It also helps researchers understand the unlikely conditions that aligned to make Earth a habitable planet.

Micron-sized “bow ties,” self-assembled from nanoparticles, form a variety of different curling shapes that can be precisely controlled, a research team led by the University of Michigan has shown.

The development opens the way for easily producing materials that interact with twisted light, providing new tools for machine vision and producing medicines.

While biology is full of twisted structures like DNA, known as chiral structures, the degree of twist is locked in—trying to change it breaks the structure. Now, researchers can engineer the degree of twist.

Most people only encounter turbulence as an unpleasant feature of air travel, but it’s also a notoriously complex problem for physicists and engineers. The same forces that rattle planes are swirling in a glass of water and even in the whorl of subatomic particles. Because turbulence involves interactions across a range of distances and timescales, the process is too complicated to be solved through calculation or computational modeling—there’s simply too much information involved.

Scientists have attempted to tackle the issue by studying the turbulence that occurs in superfluids, which is formed by tiny identical whirls called quantized vortices. A key question is how turbulence happens on the quantum scale and how is it linked to turbulence at larger scales.

Researchers at Aalto University have brought that goal closer with a new study of quantum wave turbulence. Their findings, published in Nature Physics, demonstrate a new understanding of how wave-like motion transfers energy from macroscopic to microscopic length scales, and their results confirm a theoretical prediction about how the energy is dissipated at small scales.

Physicists were surprised by the 2022 discovery that electrons in magnetic iron-germanium crystals could spontaneously and collectively organize their charges into a pattern featuring a standing wave. Magnetism also arises from the collective self-organization of electron spins into ordered patterns, and those patterns rarely coexist with the patterns that produce the standing wave of electrons physicists call a charge density wave.

In a study published this week in Nature Physics, Rice University physicists Ming Yi and Pengcheng Dai, and many of their collaborators from the 2022 study, present an array of experimental evidence that shows their charge density wave discovery was rarer still, a case where the magnetic and electronic orders don’t simply coexist but are directly linked.

“We found magnetism subtly modifies the landscape of electron energy states in the material in a way that both promotes and prepares for the formation of the charge density wave,” said Yi, a co-corresponding author of the study.

A quantum device fabricated by Zhejiang University researchers could help to advance the design of quantum computers as it offers topological control over the units that store information within them. The team’s results were published in Science in December 2022.

Since their discovery around 2007, quantum materials, known as topological insulators, have been generating a lot of excitement due to their intriguing properties. For example, they are insulating in their interior, but conducting on their surfaces. This property stems from the topological nature of these materials, which makes them robust to deformations, so electrons moving along their surfaces resist any obstacles that might obstruct their flow.

Continue reading “A quantum playground for exploring light topology” »