Classical laws precisely explain gravitational attraction on large scales. However, when it comes to the infinitely small, they fail. On the quantum scale, understanding gravity becomes crucial to explain phenomena such as the Big Bang or the interior of black holes.
The goal of researchers is to develop models capable of unifying these two scales. Johanna Erdmenger, professor at the University of Würzburg, explores this path. One of the central tools in this quest is the AdS/CFT correspondence. It connects gravitational theories in a curved space to simpler quantum theories.
AdS space, or Anti-de-Sitter, possesses a particular geometry. It is associated with a quantum theory called CFT, whose properties are invariant across all spatial scales. This correspondence, according to Erdmenger, simplifies complex gravitational processes by comparing them to more accessible mathematical models.
The main idea of this theory is that there is a relationship between what happens inside curved spacetime (such as near a black hole) and what happens outside of that space. This relationship is similar to a hologram: just as a 3D image can be created from a 2D surface, complex phenomena inside spacetime can be described by simpler equations.
To test this theory in the laboratory, the Würzburg team has designed a special electrical circuit. This circuit functions as a miniature model of spacetime. By precisely arranging the electrical components, they can mimic the curvature of spacetime and observe how electrical signals behave in this curved system. This type of simulation allows them to test how gravity might work in extreme environments like near black holes, but in a laboratory.
This is not merely a laboratory experiment. This type of circuit could have practical applications. By mimicking the curvature of space, it turns out that these circuits could stabilize the electrical signals passing through them. This means the signals would be more robust and less prone to loss or disturbance. This stability could be very useful in technologies that require reliable signals, such as artificial neural networks or other AI-based systems.
The team plans to further pursue this research to better understand gravity and explore the associated technological potentials.