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Analysing pendulum videos, the artificial intelligence tool identified variables not present in current mathematics.


An artificial intelligence tool has examined physical systems and not surprisingly, found new ways of describing what it found.

How do we make sense of the universe? There’s no manual. There’s no prescription.

At its most basic, physics helps us understand the relationships between “observable” variables – these are things we can measure. Velocity, energy, mass, position, angles, temperature, charge. Some variables like acceleration can be reduced to more fundamental variables. These are all variables in physics which shape our understanding of the world.

In February 2020, four distinguished astrophysicists — Jonathan Carroll-Nellenback, Adam Frank, Jason Wright, Caleb Scharf suggested that Earth may have remained unvisited by space-faring civilizations all the while existing in a galaxy of interstellar civilizations seeded by moving stars that spread alien life, offering a solution to the perplexing Fermi paradox. They concluded that a planet-hopping civilization could populate the Milky Way in as little as 650,000 years.

“It’s possible that the Milky Way is partially settled, or intermittently so; maybe explorers visited us in the past, but we don’t remember, and they died out,” says Jonathan Carroll-Nellenback, an astronomer at the University of Rochester and his collaborators in a 2019 study that suggests it wouldn’t take as long as thought for a space-faring civilization to planet-hop across the galaxy, because the orbits of stars can help distribute life, offering a new solution to the Fermi paradox. “The solar system may well be amid other settled systems; it’s just been unvisited for millions of years.”

While driven by the desire to pursue curiosity, fundamental investigations are the crucial first step to innovation.


When scientists announced their discovery of gravitational waves in 2016, it made headlines all over the world. The existence of these invisible ripples in space-time had finally been confirmed.

It was a momentous feat in basic research, the curiosity-driven search for fundamental knowledge about the universe and the elements within it. Basic (or “blue-sky”) research is distinct from applied research, which is targeted toward developing or advancing technologies to solve a specific problem or to create a new product.

But the two are deeply connected.

Potential applications include pressure-monitoring bandages, shade-shifting fabrics.


The bright iridescent colors in butterfly wings or beetle shells don’t come from any pigment molecules but from how the wings are structured—a naturally occurring example of what physicists call photonic crystals. Scientists can make their own structural colored materials in the lab, but it can be challenging to scale up the process for commercial applications without sacrificing optical precision.

Scientists at the Lawrence Livermore National Laboratory (LLNL) Energetic Materials Center and Purdue University Materials Engineering Department have used simulations performed on the LLNL supercomputer Quartz to uncover a general mechanism that accelerates chemistry in detonating explosives critical to managing the nation’s nuclear stockpile. Their research is featured in the July 15 issue of the Journal of Physical Chemistry Letters.

Insensitive high explosives based on TATB (1,3,5-triamino-2,4,6-trinitrobenzene) offer enhanced safety properties over more conventional explosives, but physical explanations for these safety characteristics are not clear. Explosive initiation is understood to arise from hotspots that are formed when a shockwave interacts with microstructural defects such as pores. Ultrafast compression of pores leads to an intense localized spike in temperature, which accelerates chemical reactions needed to initiate burning and ultimately . Engineering models for insensitive high explosives—used to assess safety and performance—are based on the hotspot concept but have difficulty in describing a wide range of conditions, indicating missing physics in those models.

Using large-scale atomically resolved reactive molecular dynamics supercomputer simulations, the team aimed to directly compute how hotspots form and grow to better understand what causes them to react.