The new process for noise separation and thermalization

The new process for noise separation and thermalization

Figure 1. Graphical display of the model Unitary Circuit Map. (a) The black flower on the right shows the direction of time as the fragments grew, indicated by small blue circles. The yellow dots indicate the transition to join the dots. The green squares show nonlinear changes that cause chaos. (b) Depending on the sections selected, the joints between the sections may be either short (left) or long (right). This applies to emerging timelines of chaotic dynamics. Available: Institute for Basic Science

Another notable example of abuse is the baby hurricane – a baby can flap its wings over the Atlantic Ocean and create a tornado in Colorado. This fascinating story shows how the complex nature of the dynamics of chaotic systems can give different results despite the small differences of the initial conditions. The fundamental laws of nature that govern the dynamics of physical systems are linear, often leading to turbulence and subsequent thermalization.

However, one might ask why the hurricanes in Colorado did not increase so much because the insects were more vulnerable to global activities, such as global warming? This is because physical activity, while chaotic, can exhibit stable conditions. One example is the stability of our solar system – it obeys the nonlinear laws of physics, which can cause chaos in the system.

The reason for this stability is based on the fact that weak chaotic systems exhibit ordered time dynamics that can last for millions of years. This knowledge was discovered in the 1950s by the great mathematicians Kolmogorov, Arnold, and Moser. Their view is that it only deals with the issue of systems with a small number of stakeholders. If the system has many constituent parts, then its effect is not very clear.

Researchers from the Center for Theoretical Physics of Complex Systems (PCS) within the Institute for Basic Science (IBS), South Korea recently published a report to show weak chaotic dynamics in complex systems. which consists of a large number of constituent parts. To accomplish this, they used an example based on quantum computing – Unitary Circuits Map – to simulate turbulence.

Finding time scales of chaoticity is a difficult task, requiring accurate numerical methods. The Unitary Circuit Map model implemented in this study addresses this requirement. “The model that states can communicate well and seamlessly over time,” explains Merab Malishava, “is important for comparing the weakest chaoticity to large -scale systems. in our company. “

As a result, they were able to distinguish the dynamics within the system by observing the time and length scales that emerge with a very slow thermalization. The researchers found that if the constituent segments are related to a long -range system (LRN) (for example in the whole), then the thermalization dynamics are characterized by a single independent time, called the Lyapunov time. However, if the connection is of a short circuit (SRN) type (e.g. close neighbor) then a new long -term scale will emerge that is associated with the drying of large parts of the system over long periods of time. with uncomplicated thighs.

Typically, studies on such critical dynamics are conducted using the techniques of observing the behavior of observers. These technologies began in the 1950s when the first experiments on chaoticity and thermalization were performed. The authors discovered a new way of looking at it – by researching Lyapunov spectrum scaling.

Merab Malishava says: “Previous methods are likely to have ambiguous results. You choose thermalization to be visible and perceived and you think the dynamics are chaotic… Change, that is, no thermalization. ’This is the ambiguity, which we have overcome.’ The Lyapunov spectrum is a sequence of time that represents full and complete dynamics.

The results are not only interesting from a basic point of view. They have the power to illuminate the concepts of quantum computers. Quantum numbering requires coherent dynamics, i.e., no thermalization. In the present work, a significant delay of thermal dynamics with quasi-conserved values ​​has been studied. The calculation of this case can explain various factors such as the localization of many bodies, which is one of the main reasons for preventing thermalization in quantum computers.

Another positive aspect of the study is that the effects are related to most physical features from simple oscillator networks to complex spin network dynamics. Dr. Sergej Flach, leader of the research team and director of PCS, explained: “We have been working for five years on developing a model to separate weak chaotic dynamics from macroscopic systems, which has resulted in The lessons recorded in each case are designed to develop a more confident thinking and focus on a large number of physical knowledge. We do not end our work here. , we look forward to advancing science with more advanced ideas. “

This research is published in Physical inspection messages.


Melting by heating: The role of dynamical glass


More information:
ʻO Merab Malishava et al, Lyapunov Spectrum Scaling for Classical Many-Body Dynamics Close to Integrability, Physical inspection messages (2022). DOI: 10.1103 / PhysRevLett.128.134102

Presented by the Institute for Basic Science

Directions: The new framework for noise separation and thermalization (2022, April 5) downloaded on 5 April 2022 from https://phys.org/news/2022-04-framework-chaos -thermalization.html

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