Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: physics – Page 173

Physicists make most precise measurement yet of magnetic moment of an electron

A combined team of physicists from Harvard University and Northwestern University has found the most precise value yet for the magnetic moment of an electron. In their paper published in the journal Physical Review Letters, the group describes the methods they used to measure properties of an electron and implications of the new precision.

The of an electron, also known as the electron , results from its electric and spin properties. Of all the elementary properties that have been studied, it is the one that has been the most precisely measured, and also the most accurately verified.

Measuring the magnetic moment of an electron to ever higher standards of accuracy is important because physicists believe that at some point, such measurements will help to complete the standard model of physics. In this new effort, the research group has measured the magnetic moment to a precision twice that of any other effort—the last best effort was 14 years ago.

David Wallace: Thermodynamics as control theory

I explore the reduction of thermodynamics to statistical mechanics by treating the former as a control theory: a theory of which transitions between states can be induced on a system (assumed to obey some known underlying dynamics) by means of operations from a fixed list. I recover the results of standard thermodynamics in this framework on the assumption that the available operations do not include measurements which affect subsequent choices of operations. I then relax this assumption and use the framework to consider the vexed questions of Maxwell’s demon and Landauer’s principle. Throughout I assume rather than prove the basic irreversibility features of statistical mechanics, taking care to distinguish them from the conceptually distinct assumptions of thermodynamics proper.

Annual UWO Philosophy of Physics Conference.
Thermodynamics as a Resource Theory: Foundational and Philosophical Implications.
June 20–22, 2018
http://philphysics.uwo.ca.
David Wallace, University of Southern California.

Visit the Rotman website for more information on applications, events, project descriptions, and openings. http://www.rotman.uwo.ca.

Follow The Rotman Institute on Twitter: https://twitter.com/rotmanphilo.

Like The Rotman Institute on Facebook: https://www.facebook.com/rotmanphilosophy.

Neutron Stars Create ‘Perfect’ Explosion in Space, Forming Senseless Symmetrical Sphere

Two neutron stars collided which caused a huge explosion but with an unusually flawless form, baffling scientists. Usually, a collision between neutron stars would lead to a flattened cloud but the recently observed explosion formed a perfectly spherical shape, SpaceAcademy.org reports.

It is still unclear how this is possible, but a new study may shed light on the fundamental physics involved and help scientists calculate the universe’s age. Astrophysicists from the Universe of Copenhagen discovered the kilonova and described it in full in their study, titled “Spherical Symmetry in the Kilonova At2017gfo/GW170817,” which was published in the journal Nature.

The Planck Temperature: How hot can the Universe get?

The Planck Temperature – Absolute Hot: What is the hottest temperature possible.

Today I’m going to look at the Planck Temperature and it’s about to get very strange. Let’s find out more.

Planck temperature is what we think is the highest temperature possible. It is the temperature at which our understanding of the universe breaks.
In this video we’re going to try to imagine just how hot that is, and what the implications of this value are. In order to do this, we’re going to look at some other very hot things to compare.

Cup of tea image by TerriC
https://pixabay.com/photos/tea-cup-vintage-tea-cup-tea-cup-2107599/

Desert image by photo-graphe.
https://pixabay.com/photos/desert-landscape-sunset-dune-sand-2774945/

LHC tunnel image by Maximilien Brice at CERN, used under creative commons CC 4.0

Continue reading “The Planck Temperature: How hot can the Universe get?” | >

Scientists observe high-speed star formation

Gas clouds in the Cygnus X Region, a region where stars form, are composed of a dense core of molecular hydrogen (H2) and an atomic shell. These ensembles of clouds interact with each other dynamically in order to quickly form new stars. That is the result of observations conducted by an international team led by scientists at the University of Cologne’s Institute of Astrophysics and at the University of Maryland.

Until now, it was unclear how this process precisely unfolds. The Cygnus X region is a vast luminous cloud of gas and dust approximately 5,000 light years from Earth. Using observations of spectral lines of ionized carbon (CII), the scientists showed that the clouds have formed there over several million years, which is a fast process by astronomical standards. The results of the study, “Ionized carbon as a tracer for the assembly of interstellar clouds,” will appear in the next issue of Nature Astronomy.

The observations were carried out in an international project led by Dr. Nicola Schneider at the University of Cologne and Prof Alexander Tielens at the University of Maryland as part of the FEEDBACK program on board the flying observatory SOFIA (Stratospheric Observatory for Infrared Astronomy). The new findings modify previous perceptions that this specific process of star formation is quasi-static and quite slow. The dynamic formation process now observed would also explain the formation of particularly massive stars.

Engineers finally peeked inside a deep neural network

Say you have a cutting-edge gadget that can crack any safe in the world—but you haven’t got a clue how it works. What do you do? You could take a much older safe-cracking tool—a trusty crowbar, perhaps. You could use that lever to pry open your gadget, peek at its innards, and try to reverse-engineer it. As it happens, that’s what scientists have just done with mathematics.

Researchers have examined a deep neural network—one type of artificial intelligence, a type that’s notoriously enigmatic on the inside—with a well-worn type of mathematical analysis that physicists and engineers have used for decades. The researchers published their results in the journal PNAS Nexus on January 23. Their results hint their AI is doing many of the same calculations that humans have long done themselves.

The paper’s authors typically use deep neural networks to predict extreme weather events or for other climate applications. While better local forecasts can help people schedule their park dates, predicting the wind and the clouds can also help renewable energy operators plan what to put into the grid in the coming hours.

/* */