Why Physicists Believe Geometry Holds the Key to All Theories

Can you envision the impression a 4D hexagon might create as it travels through a 3D kitchen table? It might seem implausible, yet some individuals can perceive it.

One such individual was mathematician Alicia Bourstott, daughter of logician George Bourg. In the early 20th century, she devised models of shapes while moving through three-dimensional objects. Years later, when mathematicians could verify her work with computer programs, they found that Stott had an uncanny ability to accurately depict these shapes.

This narrative is part of our special concept, uncovering how specialists ponder some of science’s most astonishing ideas. Click here for further details

For many of us, geometry recalls images of pencils, rulers, triangles, and circles. It evokes the complex questions posed in school involving parallel lines and angles. However, as Boole Stott’s experience illustrates, scholars have been expanding the scope of geometry for some time.

Geometry can transcend the conventional realm of 2D and 3D shapes. A prime example is Albert Einstein’s theory of gravity, known as general relativity, which intertwines with time to form a four-dimensional stage where the universe unfolds.

Moreover, geometry can also explore dimensions that defy physical reality. Take meteorology, for example. Atmospheric data encompasses multiple “dimensions” such as latitude, longitude, temperature, pressure, wind speed, and more.

Researchers visualize these dimensions as shapes extending into higher dimensions, aiding in understanding atmospheric behavior. “From this, we can implement mathematical models to explain what occurs. [those properties] In numerous dimensions,” states mathematician Snezana Lawrence of Middlesex University in London.

For theoretical physicists, extra dimensions appear to be essential for a complete understanding of the universe, with some suggesting that our reality might be a “projection” from a higher dimension. While this idea might sound peculiar, under certain simplified assumptions, physicists can perform calculations related to fundamental particles and black holes.

Some physicists have even proposed the concept of “all theories,” a curious geometric idea that may lead to a unified explanation of the universe and everything within it. One of these concepts is the “amplituhedron,” introduced by Jaroslav Trnka from the University of California, Davis, and Nima Arkani Hamed at the Institute for Advanced Study in New Jersey. Imagine it as an abstract, multidimensional crystal that offers an alternative perspective on the fundamentals of particle physics.

Another concept is “causal dynamic triangulation,” developed by Renate Roll at Radboud University in the Netherlands. This approach stitches together various geometric shapes to craft an explanation of space-time that seems to embody characteristics of both quantum mechanics and general relativity—two concepts that are traditionally seen as incompatible. She asserts that it serves as a testable reflection of both abstract geometric theories and true properties of the universe, as observed in the cosmic microwave background radiation.

Neither of these ideas has yet been universally accepted in all theories. However, some believe that a fresh perspective on physics is essential for progress. There is a growing consensus that this perspective may be expressed through the language of geometry. While the truth of this notion remains to be seen, it is evident that geometry encompasses far more than just hexagons.

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DeepMind’s AI successfully tackles challenging geometry problems for Math Olympiad

Geometric problems involve proving facts about angles and lines in complex shapes

Google Deep Mind

Google DeepMind's AI can solve some International Mathematics Olympiad (IMO) problems in geometry almost as well as the best human contestants.

“AlphaGeometry's results are surprising and breathtaking,” says IMO Chairman Gregor Driner. “It looks like AI will be winning his IMO gold medal much sooner than was thought a few months ago.”

IMO is one of the most difficult math competitions in the world for middle school students. Answering questions correctly requires mathematical creativity, something AI systems have long struggled with. For example, GPT-4, who has shown remarkable reasoning ability in other areas, gets his 0% score on IMO geometry problems, and even a specialized AI can answer them just as well as an average contestant. I'm having a hard time.

This is partly due to the difficulty of the problem, but also due to the lack of training data. This contest has been held annually since 1959, and each round consists of only six questions. However, some of the most successful AI systems require millions or even billions of data points. In particular, geometry problems, which account for one or two out of six questions and require proving facts about angles or lines in complex shapes, are particularly difficult to convert into a computer-friendly format.

Thanh Luong Google's DeepMind and his colleagues got around this problem by creating a tool that can generate hundreds of millions of machine-readable geometric proofs. Using this data he trained an AI called AlphaGeometry and when he tested it on 30 of his IMO geometry questions, the IMO gold medalist's estimated score based on his score in the contest was 25.9, whereas the AI answered 25 of them correctly.

“our [current] AI systems still struggle with capabilities such as deep reasoning. There you have to plan many steps in advance and understand the big picture. That's why mathematics is such an important benchmark and test set in our explorations. to artificial general intelligence,” Luong said at a press conference.

AlphaGeometry is made up of two parts, which Luong likens to different thinking systems in the brain. One system is fast and intuitive, the other is slower and more analytical. The first intuitive part is a language model called GPT-f, similar to the technology behind ChatGPT. It is trained on millions of generated proofs and suggests which theorems and arguments to try next for your problem. Once the next step is proposed, a slower but more careful “symbolic reasoning” engine uses logical and mathematical rules to fully construct the argument proposed by GPT-f. The two systems then work together and switch between each other until the problem is resolved.

While this method has been very successful in solving IMO geometry problems, Luong says the answers it constructs tend to be longer and less “pretty” than human proofs. However, it can also find things that humans overlook. For example, a better and more general solution was discovered for the question from his IMO in 2004 than the one listed in the official answer.

I think it's great that you can solve IMO geometry problems in this way. Yang Hui He However, IMO problems must be solvable using theorems taught at undergraduate level and below, so this system inherently limits the mathematics that can be used. Expanding the amount of mathematical knowledge that AlphaGeometry can access could improve the system and even help make new mathematical discoveries, he says.

It's also interesting to see how AlphaGeometry deals with situations where you don't know what you need to prove, since mathematical insight often comes from exploring theorems that have no fixed proof. Yes, he says. “If I don't know what an endpoint is, can I find it in all sets?” [mathematical] Are there any new and interesting theorems? ”

Last year, algorithmic trading firm XTX Markets Total prize money: $10 million For AI math models, the first publicly shared AI model to earn an IMO gold medal will receive a $5 million grand prize, with small progress awards for major milestones.

“Solving the IMO geometry problem is one of the planned advancement awards supported by the $10 million AIMO Challenge Fund,” said Alex Gerko of XTX Markets. “Even before we announce all the details of this Progress Award, we are excited to see the progress we are making towards this goal, including making our models and data openly available and , which involves solving real geometry problems during a live IMO contest.”

DeepMind declined to say whether it plans to use AlphaGeometry in live IMO contests or extend the system to solve other IMO problems that are not based on geometry. However, DeepMind previously entered a public protein folding prediction competition to test the AlphaFold system.

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Source: www.newscientist.com