Quantum simulators are developing rapidly, opening up new opportunities for solving problems previously accessible only to theoretical physics and numerical methods. Researchers from laboratories of quantum artificial intelligence (Google Quantum ai) and their colleagues demonstrated this new potential, studying the dynamics of one-dimensional quantum magnets, in particular chains from particles from back 1/2.
Recently, they focused on one of the fundamental problems of statistical mechanics: is it possible to describe the evolution of a single quantum magnet with the same equations as the process of formation of snowballs when snow falls out? At first glance, this may seem like a strange comparison, however, in 2019, researchers from the University of Ljubljan discovered convincing numerical evidence that led them to the hypothesis that the dynamics of the spins in the Heisenberg model for spin-1/2 belongs to the universal class Kardara-Parisi-gang (kpz). This is based on the scaling of the function of correlation of the spins at endless temperature.
Using a quantum simulator, researchers from Google Quantum AI were able to confirm this hypothesis experimentally. They studied the dynamics of Heisenberg’s spin chain and found that the function of correlation of spins really demonstrates the scaling of KPZ at endless temperatures. This discovery is important, since it connects quantum dynamics with the universal grade of surface growth, characteristic of many classical systems.
Experimental data and quantum simulations
In 2022, quantum simulations began to shed light on this question thanks to Experiments with cold atoms conducted by researchers from the institute of quantum optics of Max Planck. They studied the relaxation of the initial imbalance of magnetic spins and found experimental evidence in support of this hypothesis, which was published in Science .
In order to more deeply explore the dynamics of the spins in this model, the Google team used its superconducting quantum processor, which made it possible to quickly collect a large amount of experimental data and conduct a detailed study of basic statistics. Using a chain of 46 superconducting cubes, they measured the distribution of probabilities of the number of spins crossing the center of the chain, known as transmitted magnetization. The average value and dispersion of this distribution