Monday, February 7, 2022

Increasing the accuracy of atomic force calculations with the space-warp coordinate transformation

Atomic forces are primarily responsible for the motion of atoms and their versatile arrangement patterns, which is unique for different types of materials. Atomic simulation methods are a popular choice for the calculation of these forces, the understanding of which can vastly enhance existing knowledge on how to improve a material's function at an atomic level.

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Friday, February 4, 2022

LHC experiments are stepping up their data processing game

Analyzing as many as one billion proton collisions per second or tens of thousands of very complex lead collisions is not an easy job for a traditional computer farm. With the latest upgrades of the LHC experiments due to come into action next year, their demand for data processing potential has significantly increased. As their new computational challenges might not be met using traditional central processing units (CPUs), the four large experiments are adopting graphics processing units (GPUs).

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Thursday, February 3, 2022

A mathematical model may help explain how blood circulates in the brain

Research carried out by the Universidad Carlos III de Madrid (UC3M) may help us better understand oscillations in blood flow that occur in the cerebrovascular network, thanks to a theoretical model that allows the flow and accumulation of fluid (in this case, blood) to be taken into account.

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Wednesday, February 2, 2022

Novel method simulates tens of thousands of bubbles in foamy flows

Bubbles aren't just for bath time. Bubbles, specifically bubbles in foamy flows, are critical for many industrial processes, including the production of food and cosmetics and drug development and delivery. But the behavior of these foamy flows is notoriously difficult to compute because of the sheer number of bubbles involved.

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Assessing and optimizing the quality of sensor networks

Rather than using a single, centralized sensor to gather data, many experiments deploy multiple sensors in complex networks. This offers numerous advantages: including higher sensitivities and resolutions in experimental measurements, and the ability to catch and correct errors more effectively. Yet with all the complexities involved in managing each sensor, and collecting all of their data streams at once, it can be extremely challenging to determine how the sensors should be arranged to obtain optimal results. Through new research published in EPJ D, Joseph Smiga at Johannes Gutenberg University Mainz proposes a new way to quantify the quality of sensor networks, and uses his methods to suggest improvements to existing experiments.

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Tuesday, February 1, 2022

Dark matter travelling through stars could produce potentially detectable shock waves

Dark matter, a hypothetical material that does not absorb, emit or reflect light, is thought to account for over 80 percent of the matter in the universe. While many studies have indirectly hinted at its existence, so far, physicists have been unable to directly detect dark matter and thus to confidently determine what it consists of.

from General Physics News - Science News, Physics News, Physics, Material Sciences, Science https://ift.tt/LlHuwJUeO

The impact of learning from ancestors on the rate of natural selection

Researchers from the Institute of Industrial Science, The University of Tokyo studied the impact of learning from ancestors on the rate of natural selection, and found that the evolutionary process can be accelerated, which may assist in the design of future evolutionary algorithms.

from General Physics News - Science News, Physics News, Physics, Material Sciences, Science https://ift.tt/Bc4dk8epb