Difference between revisions of "Entropy"
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Entropy is a data structure that embodies the notion of [[time]]. In other words, it is a [[time-like structure]]. Entropy is directly related to the notion of [[ | Entropy is a data structure that embodies the notion of [[time]]. In other words, it is a [[time-like structure]]. Entropy is directly related to the notion of measure of possible states. Therefore, [[entropy]] should be defined as a measure of [[unpredictability]], or [[randomness]]. It should not be described as a measure of disorder<ref>[[Entropy is not about disorder]]</ref>. | ||
=Entropy is time, and time is money= | =Entropy is time, and time is money= | ||
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=Category Theorists' view on Entropy= | =Category Theorists' view on Entropy= | ||
[[Tai-Danae Bradley]] has a video<ref>{{:Video/A New Perspective of Entropy}}</ref> called:[[Video/A New Perspective of Entropy|A New Perspective of Entropy]]. She also mentioned [[John Baez]] blog<ref> | [[Tai-Danae Bradley]] has a video<ref>{{:Video/A New Perspective of Entropy}}</ref> called:[[Video/A New Perspective of Entropy|A New Perspective of Entropy]]. She also mentioned [[John Baez]] blog<ref>{{:Web/Entropy as a Functor}}</ref> on [https://ncatlab.org/johnbaez/show/Entropy+as+a+functor Entropy as a Functor], which are summarized in a few papers<ref>{{:Paper/A Characterization of Entropy in Terms of Information Loss}}</ref><ref>{{:Paper/Renyi Entropy and Free Energy}}</ref>. | ||
=Entropy and its applications= | =Entropy and its applications= | ||
One of the most direct applications of entropy math is information compression algorithm development. Take a look at the following artciles: | One of the most direct applications of entropy math is information compression algorithm development. Take a look at the following artciles: | ||
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==Related Pages== | ==Related Pages== | ||
*[[Definition::聚寶盆]] | *[[Definition::聚寶盆]] | ||
[[Category:Randomness]] | |||
[[Category:Resource]] | |||
[[Category:Freedom]] | [[Category:Freedom]] | ||
</noinclude> | </noinclude> | ||
Latest revision as of 02:49, 24 May 2022
Entropy is a data structure that embodies the notion of time. In other words, it is a time-like structure. Entropy is directly related to the notion of measure of possible states. Therefore, entropy should be defined as a measure of unpredictability, or randomness. It should not be described as a measure of disorder[1].
Entropy is time, and time is money
It was Bitcoin and its mining mechanism/blockchain as a time-like structure show that it is possible to use time as a way to issue currency with physical grounded phenomenon.
Category Theorists' view on Entropy
Tai-Danae Bradley has a video[2] called:A New Perspective of Entropy. She also mentioned John Baez blog[3] on Entropy as a Functor, which are summarized in a few papers[4][5].
Entropy and its applications
One of the most direct applications of entropy math is information compression algorithm development. Take a look at the following artciles:
References
Anderson, Walter. Study of Entropy. local page. Retrieved Sep 24, 2021.
Hardy, Seth (May 20, 2004). Pseudorandom Number Generation, Entropy Harvesting, and Provable Security in Linux (PDF). tsumego foundation. Retrieved Sep 24, 2021.
- ↑ Entropy is not about disorder
- ↑ Bradley, Tai-Danae (Oct 3, 2018). A New Perspective of Entropy. local page.
- ↑ Baez, John (June 22, 2016). "Entropy as a Functor". local page: John Baez.
- ↑ Baez, John; Fritz, Tobias; Leinster, Tom (Nov 18, 2011). "A Characterization of Entropy in Terms of Information Loss" (PDF). local page: Springer, Lecture Notes in Physics.
- ↑ Baez, John (June 7, 2011). "Renyi Entropy and Free Energy" (PDF). local page: arXiv.