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Related Concept Videos

Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

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The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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Entropy02:39

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Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
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Types of Damping01:20

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If the amount of damping in a system is gradually increased, the period and frequency start to become affected because damping opposes, and hence slows, the back and forth motion (the net force is smaller in both directions). If there is a very large amount of damping, the system does not even oscillate; instead, it slowly moves toward equilibrium. In brief, an overdamped system moves slowly towards equilibrium, whereas an underdamped system moves quickly to equilibrium but will oscillate about...
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Entropy Change in Reversible Processes01:10

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In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
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Dynamical noise can enhance high-order statistical structure in complex systems.

Patricio Orio1,2, Pedro A M Mediano3,4, Fernando E Rosas5,6,7,8

  • 1Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, 2360103 Valparaíso, Chile.

Chaos (Woodbury, N.Y.)
|December 4, 2023
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Summary
This summary is machine-generated.

Dynamical noise can enhance high-order interdependencies in complex systems, contrary to previous beliefs. This research shows noise can improve statistical regularities and alter interdependencies, offering insights into their emergence.

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Area of Science:

  • Complex Systems
  • Information Theory
  • Statistical Physics

Background:

  • High-order interdependencies are crucial for complex systems' information processing.
  • Previous research suggested these interdependencies are fragile and difficult to harness.

Purpose of the Study:

  • To challenge the notion that high-order interdependencies are easily disrupted.
  • To investigate the impact of stochastic perturbations on high-order interdependencies.

Main Methods:

  • Utilized elementary cellular automata as a testbed.
  • Analyzed the effects of dynamical noise on system dynamics and interdependencies.

Main Results:

  • Demonstrated that high-order interdependencies can be robust to and even enhanced by stochastic perturbations.
  • Showcased dynamical noise's capacity to improve statistical regularities between agents.
  • Observed noise altering the character of interdependencies, linked to the structure of local rules.

Conclusions:

  • High-order interdependencies can emerge and be strengthened in systems interacting with noisy environments.
  • Findings deepen understanding of the origin and function of high-order interdependencies in systems like the brain.