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  2. Entropy (statistical thermodynamics) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(statistical...

    The von Neumann entropy formula is an extension of the Gibbs entropy formula to the quantum mechanical case. It has been shown [ 1 ] that the Gibbs Entropy is equal to the classical "heat engine" entropy characterized by d S = δ Q T {\displaystyle dS={\frac {\delta Q}{T}}\!} , and the generalized Boltzmann distribution is a sufficient and ...

  3. Entropy - Wikipedia

    en.wikipedia.org/wiki/Entropy

    The statistical definition of entropy defines it in terms of the statistics of the motions of the microscopic constituents of a system — modelled at first classically, e.g. Newtonian particles constituting a gas, and later quantum-mechanically (photons, phonons, spins, etc.). The two approaches form a consistent, unified view of the same ...

  4. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    An equivalent definition of entropy is the expected value of the self-information of a variable. [1] Two bits of entropy: In the case of two fair coin tosses, the information entropy in bits is the base-2 logarithm of the number of possible outcomes ‍ — with two coins there are four possible outcomes, and two bits of entropy. Generally ...

  5. Entropy in thermodynamics and information theory - Wikipedia

    en.wikipedia.org/wiki/Entropy_in_thermodynamics...

    Despite the foregoing, there is a difference between the two quantities. The information entropy Η can be calculated for any probability distribution (if the "message" is taken to be that the event i which had probability p i occurred, out of the space of the events possible), while the thermodynamic entropy S refers to thermodynamic probabilities p i specifically.

  6. Partition function (statistical mechanics) - Wikipedia

    en.wikipedia.org/wiki/Partition_function...

    In the special case of entropy, entropy is given by ⁡ = (⁡ + ) = (⁡) = where A is the Helmholtz free energy defined as A = U − TS, where U = E is the total energy and S is the entropy, so that = = ⁡.

  7. Uncertainty coefficient - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_coefficient

    In statistics, the uncertainty coefficient, also called proficiency, entropy coefficient or Theil's U, is a measure of nominal association. It was first introduced by Henri Theil [ citation needed ] and is based on the concept of information entropy .

  8. Principle of maximum entropy - Wikipedia

    en.wikipedia.org/wiki/Principle_of_maximum_entropy

    The principle of maximum entropy states that the probability distribution which best represents the current state of knowledge about a system is the one with largest entropy, in the context of precisely stated prior data (such as a proposition that expresses testable information).

  9. Introduction to entropy - Wikipedia

    en.wikipedia.org/wiki/Introduction_to_entropy

    Thermodynamic entropy is measured as a change in entropy to a system containing a sub-system which undergoes heat transfer to its surroundings (inside the system of interest). It is based on the macroscopic relationship between heat flow into the sub-system and the temperature at which it occurs summed over the boundary of that sub-system.