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Battlemage!
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Many scientists believe information is conserved, but it seems that in an isolated system entropy isn't. These two things seem incompatible to me. Would anyone care to enlighten me about this? Thank you.
While entropy is a measure of disorder or randomness in a system, information refers to the organization and structure of that system. When entropy increases, it means that there is a decrease in the amount of usable energy in the system, but this does not necessarily mean that information is lost. In fact, as entropy increases, information can become more concentrated and organized in certain areas of the system.
The second law of thermodynamics states that entropy in a closed system will always increase over time. This is because energy will naturally disperse and become less organized. However, this law does not apply to open systems, where energy and matter can enter and exit. In these systems, information can be conserved even as entropy increases.
Negentropy, or negative entropy, is a concept that refers to the process of creating order and reducing entropy in a system. This is often seen in living organisms, where energy is used to maintain order and complexity. In these systems, information can be conserved even as entropy increases, as the energy used to maintain order is constantly replenished.
No, information cannot be destroyed or lost in a closed system. This is because information is not a physical entity, but rather a concept that describes the organization of a system. While entropy can increase, causing changes in the physical state of the system, the information that describes the system's organization remains intact.
In information theory, entropy is used to measure the uncertainty or randomness of a system. As the amount of information in a system increases, the entropy also increases. However, this does not mean that information is lost or destroyed, as the information can still be retrieved and organized in a meaningful way. In this sense, the conservation of information still applies in information theory.