Lifeboat Foundation

CERN Courier

Jennifer Ngadiuba and Maurizio Pierini describe how ‘unsupervised’ machine learning could keep watch for signs of new physics at the LHC that have not yet been dreamt up by physicists.

In the 1970s, the robust mathematical framework of the Standard Model ℠ replaced data observation as the dominant starting point for scientific inquiry in particle physics. Decades-long physics programmes were put together based on its predictions. Physicists built complex and highly successful experiments at particle colliders, culminating in the discovery of the Higgs boson at the LHC in 2012.

Continue reading “Hunting anomalies with an AI trigger” »

There are eight known planets in the Solar System (ever since Pluto was booted from the club), but for a while, there has been some evidence that there might be one more.

A hypothetical Planet 9 lurking on the outer edge of our Solar System. So far this world has eluded discovery, but a new study has pinned down where it should be. The evidence for Planet 9 comes from its gravitational pull on other bodies. If the planet exists, its gravity will affect the orbits of other planets.

So if something seems to be tugging on a planet, just do a bit of math to find the source. This is how Neptune was discovered when John Couch Adams and Urbain Le Verrier noticed independently that Uranus seemed to be tugged by an unseen planet.

Integrated Information Theory is one of the leading models of consciousness. It aims to describe both the quality and quantity of the conscious experience of a physical system, such as the brain, in a particular state. In this contribution, we propound the mathematical structure of the theory, separating the essentials from auxiliary formal tools. We provide a definition of a generalized IIT which has IIT 3.0 of Tononi et al., as well as the Quantum IIT introduced by Zanardi et al. as special cases. This provides an axiomatic definition of the theory which may serve as the starting point for future formal investigations and as an introduction suitable for researchers with a formal background.

Integrated Information Theory (IIT), developed by Giulio Tononi and collaborators [5, 45–47], has emerged as one of the leading scientific theories of consciousness. At the heart of the latest version of the theory [19, 25 26, 31 40] is an algorithm which, based on the level of integration of the internal functional relationships of a physical system in a given state, aims to determine both the quality and quantity (‘Φ value’) of its conscious experience.

The Bernese theoretical astrophysicist Kevin Heng has achieved a rare feat: On paper, he has derived novel solutions to an old mathematical problem needed to calculate light reflections from planets and moons. Now, data can be interpreted in a simple way to understand planetary atmospheres, for example. The new formulae will likely be incorporated into future textbooks.

For millennia, humanity has observed the changing phases of the Moon. The rise and fall of sunlight reflected off the Moon, as it presents its different faces to us, is known as a “phase curve.” Measuring phase curves of the Moon and Solar System planets is an ancient branch of astronomy that goes back at least a century. The shapes of these phase curves encode information on the surfaces and atmospheres of these celestial bodies. In modern times, astronomers have measured the phase curves of exoplanets using space telescopes such as Hubble, Spitzer, TESS

Launched on April 18 2018, aboard a SpaceX Falcon 9 rocket, NASA’s Transiting Exoplanet Survey Satellite (TESS) is a mission to search nearby stars for undiscovered worlds with a gold of discovering thousands of exoplanets around nearby bright stars.

Three reasons why it falls short.

Isaac Newton invented physics as we know it. And one of the ways he did so was that he formalized the initial condition problem into calculus — the mathematics of change.

Researchers from Skoltech, KTH Royal Institute of Technology, and Uppsala University have predicted the existence of antichiral ferromagnetism, a nontrivial property of some magnetic crystals that opens the door to a variety of new magnetic phenomena. The paper was published in the journal Physical Review B.

Chirality, or handedness, is an extremely important fundamental property of objects in many fields of physics, mathematics, chemistry and biology; a chiral object cannot be superimposed on its mirror image in any way. The simplest chiral objects are human hands, hence the term itself. The opposite of chiral is achiral: a circle or a square are simple achiral objects.

Chirality can be applied to much more complex entities; for instance, competing internal interactions in a magnetic system can lead to the appearance of periodic magnetic textures in the structure that differ from their mirror images—this is called chiral ferromagnetic ordering. Chiral crystals are widely considered promising candidates for magnetic data storage and processing device realization as information can be encoded via their nontrivial magnetic textures.

A team of Swiss researchers from Graubuenden University of Applied Sciences has broken the record for calculating the mathematical constant pi. It is now known to an incredible level of exactitude, hitting 62.8 trillion figures thanks to the work of a supercomputer.

Pi represents the ratio between the radius of a circle and its circumference. You may recognize the first 10 digits, π=3.141592653, though there is an infinite number of digits that follow that decimal point.

To write all of the digits for the new record out on A4 paper, you would need almost 35 billion sheets, equivalent to about 52 percent of the mass of the Empire State Building. Putting those pieces of paper head to toe they would extend for over 10 million kilometers (6.5 million miles).

Summary: Study reveals how the brain analyzes different types of speech which may be linked to how we comprehend sentences and calculate mathematical equations.

Source: SfN

Separate math and language networks segregate naturally when listeners pay attention to one type over the other, according to research recently published in Journal of Neuroscience.

Determining if particular extreme hot or cold spells were caused by climate change could be made easier by a new mathematical method.

The statistical method, developed by physicists at the University of Reading and Uppsala University in Sweden, looks at the characteristics, or “fingerprints,” of a specific extreme weather event of interest, like a heatwave, in order to ascertain whether it can be attributed to natural climate variability of the climate or is a unique product of global warming.

The method also allows predictions to be made about how likely extreme climate events will be in the future.