(ORDO NEWS) — To understand what can be inside a black hole and what processes are going on there, physicists use quantum computing and machine learning. What were they able to find out?
With the help of a quantum computer and a neural network, researchers were able to partially “look” inside a black hole
The University of Michigan physicist is using quantum computing and machine learning to better understand an idea called holographic duality that underpins our understanding of what goes on inside black holes.
Holographic duality is a mathematical hypothesis that connects the theory of particles and their interactions with the theory of gravity. This hypothesis assumes that the theory of gravity and the theory of particles are mathematically equivalent: what happens mathematically in the theory of gravity happens in the theory of particles, and vice versa.
Both theories describe different dimensions, but the number of dimensions they describe differs by one. For example, inside a black hole, gravity exists in three dimensions, while particle theory describes processes in two dimensions, representing processes in a flat disk.
To imagine this, think again about a black hole that warps spacetime due to its massive mass. The gravity of a black hole, which exists in three dimensions, is mathematically related to the particles moving above it in two dimensions. Therefore, the black hole exists in three-dimensional space, but we see it as a two-dimensional projection thanks to the particles.
Some scientists theorize that our entire universe is a holographic projection of particles, and this understanding could reveal quantum gravity to physicists if any convincing scientific evidence comes along.
In a study published in 2022, physicists set out to study holographic duality using quantum computing and deep learning to find the lowest energy state in quantum matrix models.
For the study, the authors used two matrix models that are simple enough to be solved by traditional methods, but have all the features of more complex matrix models used to describe black holes through holographic duality.
These matrix models are objects in string theory in which particles are represented by one-dimensional strings.
When researchers solve matrix models like this, they are trying to find a particular configuration of particles in a system, which is the lowest energy state of the system, called the ground state. Physicists have shown that it is possible to find this ground state using two different methods.
The results of the work show an important benchmark for future research conducted using quantum and machine learning algorithms. Scientists can use them to study quantum gravity using the idea of holographic duality.
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