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Related Concept Videos

Entropy02:39

Entropy

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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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Entropy and the Second Law of Thermodynamics01:20

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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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Third Law of Thermodynamics02:38

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A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
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The Second Law of Thermodynamics01:14

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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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Interference and Decay01:16

Interference and Decay

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Forgetting is a complex cognitive phenomenon influenced by several factors, among which interference and decay are particularly prominent. These processes explain why individuals often struggle to retrieve specific information from memory, leading to lapses in recall that can be observed in everyday situations.
Interference occurs when competing memories hinder the retrieval of particular information. It can be classified into two types: proactive and retroactive interference. Proactive...
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Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

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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.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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Memory and Entropy.

Carlo Rovelli1,2,3

  • 1Aix Marseille University, Université de Toulon, CNRS, CPT, 13288 Marseille, France.

Entropy (Basel, Switzerland)
|July 27, 2022
PubMed
Summary
This summary is machine-generated.

Physical traces are created by system separation, temperature differences, and long thermalization times. This thermodynamic process converts low entropy into macroscopic information, explaining ubiquitous traces in the universe.

Keywords:
information.metastable systemstraces

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Area of Science:

  • Thermodynamics
  • Information Theory
  • Statistical Mechanics

Background:

  • Macroscopic traces, or evidence of past events, are common in the universe.
  • The physical conditions necessary for trace formation are not fully understood.
  • Understanding trace formation is key to understanding information storage in physical systems.

Purpose of the Study:

  • To identify the fundamental physical conditions required for the creation of macroscopic traces.
  • To quantify the thermodynamic principles governing memory formation and information storage.
  • To establish a link between low entropy states and the origin of macroscopic information.

Main Methods:

  • Investigated the role of system separation, temperature gradients, and thermalization times in trace formation.
  • Developed a quantitative thermodynamic framework to describe memory and information storage.
  • Derived an expression for the maximum information content of traces based on thermodynamic parameters.

Main Results:

  • Demonstrated that system separation, temperature differences, and long thermalization times are sufficient for macroscopic trace production.
  • Quantified the thermodynamic conditions necessary for memory formation.
  • Derived a formula for maximum stored information as a function of thermodynamic variables, showing a transformation of low entropy into available information.

Conclusions:

  • The physical conditions identified are ubiquitous in the universe, explaining the prevalence of traces.
  • Macroscopic information storage is fundamentally linked to past low-entropy states.
  • This work provides a thermodynamic basis for understanding information in the physical world.