An international team of physicists, with the participation of the University of Augsburg, confirmed for the first time an important theoretical prediction in quantum physics. The calculations for this are so complex that they have so far proven to be very demanding, even for supercomputers. However, researchers have succeeded in simplifying it significantly using methods from the field of machine learning. The study improves understanding of the basic principles of the quantum world. It was published in the magazine science progress.
Calculating the movement of a single billiard ball is relatively simple. However, predicting the trajectories of a large number of gas molecules in a vessel that constantly collides, slows down and deflects, is a more difficult method. But what if it is not at all obvious how fast each particle is moving, so that they have infinitely possible velocities at any given time, differing only in their probabilities?
The situation is similar in the quantum world: a quantum mechanical particle can possess all possible properties simultaneously. This makes the state space for quantum mechanical systems extremely large. If you’re aiming to simulate how quantum particles interact with each other, you should consider their full state spaces.
“This is a very complex matter,” says Professor Dr. Markus Hill of the Institute of Physics at the University of Augsburg. “The computational effort increases exponentially with the number of particles. With more than 40 particles, it is already so large that even the fastest supercomputers are unable to handle it. This is one of the great challenges of quantum physics.”
Neural networks make the problem manageable
To simplify this problem, Heyl’s group used methods from the field of machine learning – artificial neural networks. With these, the state of quantum mechanics can be reformulated. “This makes it manageable by computers,” Hill explains.
Using this method, the scientists investigated an important theoretical prediction that has remained a prominent challenge so far – the quantum Kepel-Zurek mechanism. It describes the dynamic behavior of physical systems in what is called a quantum phase transition. An example of phase transition from the macroscopic world and the most intuitive is the transition from water to ice. Another example is the removal of magnets at high temperatures.
If you go in the opposite direction and cool the material, the magnet begins to form again below a certain critical temperature. However, this does not occur evenly across the entire material. Instead, many small magnets with differently aligned north and south poles are generated at the same time. Thus, the resulting magnet is actually a mosaic of many different small magnets. Physicists also say it has flaws.
The Kibble-Zurek mechanism predicts the number of such expected defects (in other words, how many mini-magnets the material will eventually form). What is particularly interesting is that the number of these defects is global and therefore independent of microscopic detail. Accordingly, many different substances behave completely identically, even if their microscopic composition is completely different.
The Kibble-Zurek Mechanism and Galaxies Formation After the Big Bang
The Kibble-Zurek mechanism was originally introduced to explain the formation of structure in the universe. After the Big Bang, the universe was initially quite homogeneous, which means that the hosted matter was completely evenly distributed. For a long time, it was not clear how galaxies, the Sun or planets could form from such a homogeneous state.
In this context, the Kepel-Zork mechanism offers an explanation. When the universe was cooling, the defects developed in a similar way to magnets. In the meantime, these processes in the macroscopic world are well understood. But there is one kind of phase transition for which it has not yet been possible to validate the mechanism – that is, the quantum phase transitions already mentioned before. “They only exist at absolute zero temperatures of -273 degrees Celsius,” Hill explains. “So the phase transition doesn’t happen during cooling, but through changes in reaction energy — you can think, perhaps, of changing the pressure.”
Scientists have now simulated such a quantum phase shift on a supercomputer. Thus, they were able to prove for the first time that the Kepel-Zurek mechanism is also applicable in the quantum world. “This was by no means an obvious result,” says the physicist Augsburg. “Our study allows us to describe the dynamics of quantum mechanics systems of many particles, and thus more accurately understand the rules that govern this strange world.”
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Marcus Schmidt et al., Quantum phase transition dynamics in a two-dimensional cross-field Ising model, science progress (2022). DOI: 10.1126 / sciadv.abl6850
Presented by the University of Augsburg
the quote: Researchers answer the fundamental question of quantum physics (2022, September 22) Retrieved September 23, 2022 from https://phys.org/news/2022-09-fundamental-quantum-physics.html
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