A neural network discovered Copernicus’ heliocentricity on its own

Can neural networks help scientists discover laws about more complex phenomena, like quantum mechanics?

A neural network discovered Copernicus’ heliocentricity on its own
  • Scientists trained a neural network to predict the movements of Mars and the Sun.
  • In the process, the network generated formulae that place the Sun at the center of our solar system.
  • The case suggests that machine-learning techniques could help reveal new laws of physics.


A neural network was able to rediscover one of the most important paradigm shifts in scientific history: Earth and other planets revolve around the Sun. The accomplishment suggests machine-learning techniques could someday help to reveal new laws of physics, maybe even within the complex realm of quantum mechanics.

The results are set to appear in the journal Physical Review Letters, according to Nature.

The neural network — a machine-learning algorithm called SciNetwas shown measurements of how the Sun and Mars appear from Earth against the fixed-star background of the night sky. SciNet's task, assigned by a team of scientists at the Swiss Federal Institute of Technology, was to predict where the Sun and Mars would be at future points in time.

Copernicus-style formulae

In the process, SciNet generated formulas that place the Sun at the center of our solar system. Remarkably, SciNet accomplished this in a way similar to how astronomer Nicolaus Copernicus discovered heliocentricity.

"In the 16th century, Copernicus measured the angles between a distant fixed star and several planets and celestial bodies and hypothesized that the Sun, and not the Earth, is in the centre of our solar system and that the planets move around the Sun on simple orbits," the team wrote in a paper published on the preprint repository arXiv. "This explains the complicated orbits as seen from Earth."

The team "encouraged" SciNet to come up with ways to predict the movements of the Sun and Mars in the simplest way possible. To do that, SciNet passes information back and forth between two sub-networks. One network "learns" from data, and the other uses that knowledge to make predictions and test their accuracy. These networks are connected to each other by only a few links, so when they communicate, information is compressed, resulting in "simpler" representations.

Renner et al.

SciNet decided that the simplest way to predict the movements of celestial bodies was through a model that places the Sun at the center of our solar system. So, the neural network didn't necessarily "discover" heliocentricity, but rather described it through mathematics that humans can interpret.

Building humanlike AI

In 2017, data scientist Brenden Lake and his colleagues wrote a paper describing what it will take to build machines that learn and think like people. One benchmark for doing so would be artificial intelligence that can describe the physical world. At the time, they said it "remains to be seen" whether "deep networks trained on physics-related data" could discover laws of physics on their own. In a narrow sense, SciNet passes this test.

"To summarize, the main aim of this work is to show that neural networks can be used to discover physical concepts without any prior knowledge," the SciNet team wrote. "To achieve this goal, we introduced a neural network architecture that models the physical reasoning process. The examples illustrate that this architecture allows us to extract physically relevant data from experiments, without imposing further knowledge about physics or mathematics."

U.S. Navy controls inventions that claim to change "fabric of reality"

Inventions with revolutionary potential made by a mysterious aerospace engineer for the U.S. Navy come to light.

U.S. Navy ships

Credit: Getty Images
Surprising Science
  • U.S. Navy holds patents for enigmatic inventions by aerospace engineer Dr. Salvatore Pais.
  • Pais came up with technology that can "engineer" reality, devising an ultrafast craft, a fusion reactor, and more.
  • While mostly theoretical at this point, the inventions could transform energy, space, and military sectors.
Keep reading Show less

China's "artificial sun" sets new record for fusion power

China has reached a new record for nuclear fusion at 120 million degrees Celsius.

Credit: STR via Getty Images
Technology & Innovation

This article was originally published on our sister site, Freethink.

China wants to build a mini-star on Earth and house it in a reactor. Many teams across the globe have this same bold goal --- which would create unlimited clean energy via nuclear fusion.

But according to Chinese state media, New Atlas reports, the team at the Experimental Advanced Superconducting Tokamak (EAST) has set a new world record: temperatures of 120 million degrees Celsius for 101 seconds.

Yeah, that's hot. So what? Nuclear fusion reactions require an insane amount of heat and pressure --- a temperature environment similar to the sun, which is approximately 150 million degrees C.

If scientists can essentially build a sun on Earth, they can create endless energy by mimicking how the sun does it.

If scientists can essentially build a sun on Earth, they can create endless energy by mimicking how the sun does it. In nuclear fusion, the extreme heat and pressure create a plasma. Then, within that plasma, two or more hydrogen nuclei crash together, merge into a heavier atom, and release a ton of energy in the process.

Nuclear fusion milestones: The team at EAST built a giant metal torus (similar in shape to a giant donut) with a series of magnetic coils. The coils hold hot plasma where the reactions occur. They've reached many milestones along the way.

According to New Atlas, in 2016, the scientists at EAST could heat hydrogen plasma to roughly 50 million degrees C for 102 seconds. Two years later, they reached 100 million degrees for 10 seconds.

The temperatures are impressive, but the short reaction times, and lack of pressure are another obstacle. Fusion is simple for the sun, because stars are massive and gravity provides even pressure all over the surface. The pressure squeezes hydrogen gas in the sun's core so immensely that several nuclei combine to form one atom, releasing energy.

But on Earth, we have to supply all of the pressure to keep the reaction going, and it has to be perfectly even. It's hard to do this for any length of time, and it uses a ton of energy. So the reactions usually fizzle out in minutes or seconds.

Still, the latest record of 120 million degrees and 101 seconds is one more step toward sustaining longer and hotter reactions.

Why does this matter? No one denies that humankind needs a clean, unlimited source of energy.

We all recognize that oil and gas are limited resources. But even wind and solar power --- renewable energies --- are fundamentally limited. They are dependent upon a breezy day or a cloudless sky, which we can't always count on.

Nuclear fusion is clean, safe, and environmentally sustainable --- its fuel is a nearly limitless resource since it is simply hydrogen (which can be easily made from water).

With each new milestone, we are creeping closer and closer to a breakthrough for unlimited, clean energy.

The science of sex, love, attraction, and obsession

The symbol for love is the heart, but the brain may be more accurate.

Videos
  • How love makes us feel can only be defined on an individual basis, but what it does to the body, specifically the brain, is now less abstract thanks to science.
  • One of the problems with early-stage attraction, according to anthropologist Helen Fisher, is that it activates parts of the brain that are linked to drive, craving, obsession, and motivation, while other regions that deal with decision-making shut down.
  • Dr. Fisher, professor Ted Fischer, and psychiatrist Gail Saltz explain the different types of love, explore the neuroscience of love and attraction, and share tips for sustaining relationships that are healthy and mutually beneficial.

Sex & Relationships

There never was a male fertility crisis

A new study suggests that reports of the impending infertility of the human male are greatly exaggerated.

Quantcast