Lifeboat Foundation

Computer simulations have struggled to capture the impact of elusive particles called neutrinos on the formation and growth of the large-scale structure of the universe. But now, a research team from Japan has developed a method that overcomes this hurdle.

In a study published this month in the Astrophysical Journal, researchers led by the University of Tsukuba present simulations that accurately depict the role of neutrinos in the evolution of the universe.

Why are these simulations important? One key reason is that they can set constraints on a currently unknown quantity: the neutrino mass. If this quantity is set to a particular value in the simulations and the simulation results differ from observations, that value can be ruled out. However, the constraints can be trusted only if the simulations are accurate, which was not guaranteed in previous work. The team behind this latest research aimed to address this limitation.

Researchers are a step closer to realizing a new kind of memory that works according to the principles of spintronics which is analogous to, but different from, electronics. Their unique gallium arsenide-based ferromagnetic semiconductor can act as memory by quickly switching its magnetic state in the presence of an induced current at low power. Previously, such current-induced magnetization switching was unstable and drew a lot of power, but this new material both suppresses the instability and lowers the power consumption too.

The field of quantum computing often gets covered in the technical press; however, another emerging field along similar lines tends to get overlooked, and that is spintronics. In a nutshell, spintronic devices could replace some electronic devices and offer greater performance at far low power levels. Electronic devices use the motion of electrons for power and communication. Whereas spintronic devices use a transferable property of stationary electrons, their angular momentum, or spin. It’s a bit like having a line of people pass on a message from one to the other rather than have the person at one end run to the other. Spintronics reduces the effort needed to perform computational or memory functions.

Spintronic-based memory devices are likely to become common as they have a useful feature in that they are nonvolatile, meaning that once they are in a certain state, they maintain that state even without power. Conventional computer memory, such as DRAM and SRAM made of ordinary semiconductors, loses its state when it’s powered off. At the core of experimental spintronic memory devices are magnetic materials that can be magnetized in opposite directions to represent the familiar binary states of 1 or 0, and this switching of states can occur very, very quickly. However, there has been a long and arduous search for the best materials for this job, as magnetizing spintronic materials are no simple matter.

Researchers identify Brown-Zak fermions in superlattices made from the carbon sheet.

Researchers at the University of Manchester in the UK have identified a new family of quasiparticles in superlattices made from graphene sandwiched between two slabs of boron nitride. The work is important for fundamental studies of condensed-matter physics and could also lead to the development of improved transistors capable of operating at higher frequencies.

In recent years, physicists and materials scientists have been studying ways to use the weak (van der Waals) coupling between atomically thin layers of different crystals to create new materials in which electronic properties can be manipulated without chemical doping. The most famous example is graphene (a sheet of carbon just one atom thick) encapsulated between another 2D material, hexagonal boron nitride (hBN), which has a similar lattice constant. Since both materials also have similar hexagonal structures, regular moiré patterns (or “superlattices”) form when the two lattices are overlaid.

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Faster, smaller, smarter and more energy-efficient chips for everything from consumer electronics to big data to brain-inspired computing could soon be on the way after engineers at The University of Texas at Austin created the smallest memory device yet. And in the process, they figured out the physics dynamic that unlocks dense memory storage capabilities for these tiny devices.

The research published recently in Nature Nanotechnology builds on a discovery from two years ago, when the researchers created what was then the thinnest memory storage device. In this new work, the researchers reduced the size even further, shrinking the cross section area down to just a single square nanometer.

Getting a handle on the physics that pack dense memory storage capability into these devices enabled the ability to make them much smaller. Defects, or holes in the material, provide the key to unlocking the high-density memory storage capability.

Dogmatic individuals tend to form less accurate judgements thanks to a generic resistance to seeking out additional information, according to new research published in the Proceedings of the National Academy of Sciences (PNAS). The findings shed new light on the cognitive underpinnings of dogmatic worldviews.

“We have never been so free to decide if we have enough evidence about something or whether we should seek out further information from a reliable source before believing it,” explained study author Lion Schulz, a doctoral researcher in the Department of Computational Neuroscience at the Max Planck Institute for Biological Cybernetics.

“In turn, if we don’t check on quick and uncertain judgements, this can leave us quite vulnerable to misinformation. Understanding the mechanism behind such decisions and how different people approach them is therefore important when we try to understand the current societal climate.”

Amazon acknowledged that the system failure was exacerbated by the co-dependencies its various services have on one another. The company had been trying to add capacity to its Amazon Kinesis service that customers use to process real-time data including video, audio and application logs. To resolve the issue, Amazon needed to restart a piece of its system it described as “many thousands of servers,” a lengthy process that had to be done gradually. But because other Amazon cloud services rely on Kinesis, including its Cognito authentication offering, they failed as well.

Synthetic biology tools used to engineer T cells that work like living computers and recognize antigen combinations in solid tumors.

Silica-Rich Soil in Gusev Crater.

Physicists propose using time crystals to bring about a quantum computing revolution.