Entropy Meaning: Definition, Examples, and Translations
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entropy
[หษntrษpi ]
Definitions
thermodynamics
Entropy is a measure of the randomness or disorder of a system. In thermodynamics, it quantifies the amount of energy in a physical system that cannot be used to do work. As entropy increases, the ability to do work decreases. This concept is essential for understanding the second law of thermodynamics, which states that the total entropy of an isolated system can never decrease over time. Essentially, entropy is a key factor in the direction of spontaneous processes and the evolution of systems towards equilibrium.
Synonyms
Examples of usage
- The entropy of the universe is constantly increasing.
- In a closed system, entropy must increase.
- Higher entropy correlates with greater disorder.
information theory
In information theory, entropy measures the uncertainty associated with a random variable. It quantifies the average amount of information produced by a stochastic source of data. The concept helps in understanding data compression and transmission. A higher entropy value indicates more unpredictability and complexity of information, while a lower value indicates more predictability.
Synonyms
information content, uncertainty measure.
Examples of usage
- Shannon's entropy is a fundamental concept in information theory.
- The entropy of a text can give insights into its complexity.
- Cryptography relies on high entropy for security.
Translations
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Origin of 'entropy'
The term 'entropy' originates from the Greek word 'entropia', meaning 'a turning towards' or 'transformation'. It was introduced in the 19th century by the German physicist Rudolph Clausius as a key concept in thermodynamics. Clausius' development of the second law of thermodynamics solidified entropy as a fundamental principle in understanding energy transfer and conversion. The use of the term later expanded into information theory in the 1940s, thanks to Claude Shannon, who formulated a mathematical representation of entropy in the context of information. This dual application of entropyโfirst in physics and later in information scienceโillustrates its broad relevance in describing systems' behavior in both natural and digital realms.