Entropy is not directly dependent on time. It is a measure of the disorder or randomness in a system and is associated with the number of microstates that correspond to a particular macrostate. In simple terms, it quantifies the degree of uncertainty or lack of information about the state of a system.
Entropy can increase or remain constant over time in an isolated system, following the second law of thermodynamics, which states that the entropy of a closed system tends to increase over time. However, the concept of entropy can still be applied to systems even in the absence of time.
Even if time were to be absent or not exist, the concept of entropy could still be meaningful within a static system. For example, a system with particles in various positions and velocities can have different levels of disorder or entropy, even without any temporal progression. In such a scenario, entropy would measure the randomness or uncertainty within the system.
It is worth noting that our understanding of entropy and its relationship with time is based on the framework of classical and statistical physics, which assumes the existence of time as a fundamental dimension. In other words, the laws of thermodynamics, including the increase of entropy, are formulated within a framework that includes the concept of time.