Lifeboat Foundation

A team of researchers from Tri Alpha Energy Inc. and Google has developed an algorithm that can be used to speed up experiments conducted with plasma. In their paper published in the journal Scientific Reports, the group describes how they plan to use the algorithm in nuclear fusion research.

As research into harnessing nuclear fusion has progressed, scientists have found that some of its characteristics are too complex to be solved in a reasonable amount of time using current technology. So they have increasingly turned to computers to help. More specifically, they want to adjust certain parameters in a device created to achieve fusion in a reasonable way. Such a device, most in the field agree, must involve the creation of a certain type of plasma that is not too hot or too cold, is stable, and has a certain desired density.

Finding the right parameters that meet these conditions has involved an incredible amount of trial and error. In this new effort, the researchers sought to reduce the workload by using a computer to reduce some of the needed trials. To that end, they have created what they call the “optometrist’s algorithm.” In its most basic sense, it works like an optometrist attempting to measure the visual ability of a patient by showing them images and asking if they are better or worse than other images. The idea is to use the crunching power of a computer with the intelligence of a human being—the computer generates the options and the human tells it whether a given option is better or worse.

MIT physicists and colleagues have demonstrated an exotic form of superconductivity in a new material the team synthesized only about a year ago. Although predicted in the 1960s, until now this type of superconductivity has proven difficult to stabilize. Further, the scientists found that the same material can potentially be manipulated to exhibit yet another, equally exotic form of superconductivity.

The work was reported in the Nov. 3 issue of the journal Nature.

The demonstration of finite momentum superconductivity in a layered crystal known a natural superlattice means that the material can be tweaked to create different patterns of superconductivity within the same sample. And that, in turn, could have implications for quantum computing and more.

Today, the greatest mysteries facing astronomers and cosmologists are the roles gravitational attraction and cosmic expansion play in the evolution of the Universe.

To resolve these mysteries, astronomers and cosmologists are taking a two-pronged approach. These consist of directly observing the cosmos to observe these forces at work while attempting to find theoretical resolutions for observed behaviors – such as dark matter and dark energy.

In between these two approaches, scientists model cosmic evolution with computer simulations to see if observations align with theoretical predictions. The latest of which is AbacusSummit, a simulation suite created by the Flatiron Institute’s Center for Computational Astrophysics (CCA) and the Harvard-Smithsonian Center for Astrophysics (CfA).

Squeezing more data density into the 3.5-inch hard drive form factor.

It is a major step towards commercial quantum computers outperforming traditional machines.

Researchers demonstrated new variation of Rowhammer attack affecting all DRAM chips that bypasses currently deployed mitigations.

How are chemical elements produced in our Universe? Where do heavy elements like gold and uranium come from? Using computer simulations, a research team from the GSI Helmholtzzentrum für Schwerionenforschung in Darmstadt, together with colleagues from Belgium and Japan, shows that the synthesis of heavy elements is typical for certain black holes with orbiting matter accumulations, so-called accretion disks. The predicted abundance of the formed elements provides insight into which heavy elements need to be studied in future laboratories — such as the Facility for Antiproton and Ion Research (FAIR), which is currently under construction — to unravel the origin of heavy elements. The results are published in the journal Monthly Notices of the Royal Astronomical Society.

All heavy elements on Earth today were formed under extreme conditions in astrophysical environments: inside stars, in stellar explosions, and during the collision of neutron stars. Researchers are intrigued with the question in which of these astrophysical events the appropriate conditions for the formation of the heaviest elements, such as gold or uranium, exist. The spectacular first observation of gravitational waves and electromagnetic radiation originating from a neutron star merger in 2017 suggested that many heavy elements can be produced and released in these cosmic collisions. However, the question remains open as to when and why the material is ejected and whether there may be other scenarios in which heavy elements can be produced.

Promising candidates for heavy element production are black holes orbited by an accretion disk of dense and hot matter. Such a system is formed both after the merger of two massive neutron stars and during a so-called collapsar, the collapse and subsequent explosion of a rotating star. The internal composition of such accretion disks has so far not been well understood, particularly with respect to the conditions under which an excess of neutrons forms. A high number of neutrons is a basic requirement for the synthesis of heavy elements, as it enables the rapid neutron-capture process or r-process. Nearly massless neutrinos play a key role in this process, as they enable conversion between protons and neutrons.

It seems evaporated glass, chains of ions, and quantum stability go hand in hand.

IonQ has replaced the typical silicon with a fused glass-based chip, allowing for unprecedented levels of scaling for the company’s trapped-ion approach to quantum computing.

A group of scientists at the U.S. Department of Energy’s Ames Laboratory has developed computational quantum algorithms that are capable of efficient and highly accurate simulations of static and dynamic properties of quantum systems. The algorithms are valuable tools to gain greater insight into the physics and chemistry of complex materials, and they are specifically designed to work on existing and near-future quantum computers.

Scientist Yong-Xin Yao and his research partners at Ames Lab use the power of advanced computers to speed discovery in condensed matter physics, modeling incredibly complex quantum mechanics and how they change over ultra-fast timescales. Current high performance computers can model the properties of very simple, small quantum systems, but larger or more complex systems rapidly expand the number of calculations a computer must perform to arrive at an accurate model, slowing the pace not only of computation, but also discovery.

“This is a real challenge given the current early-stage of existing quantum computing capabilities,” said Yao, “but it is also a very promising opportunity, since these calculations overwhelm classical computer systems, or take far too long to provide timely answers.”