普朗克曾说:“熵和概率之间的对数关系是由玻尔兹曼在他的气体动力学理论中首次提出的”。<ref>Max Planck, p. 119.</ref> 也就是著名的熵公式:<ref>The concept of [[entropy]] was introduced by Rudolf Clausius in 1865. He was the first to enunciate the second law of thermodynamics by saying that "entropy always increases".</ref><ref>An alternative is the information entropy definition introduced in 1948 by [[Claude Elwood Shannon|Claude Shannon]].[https://archive.is/20070503225307/http://cm.bell-labs.com/cm/ms/what/shannonday/paper.html] It was intended for use in communication theory, but is applicable in all areas. It reduces to Boltzmann's expression when all the probabilities are equal, but can, of course, be used when they are not. Its virtue is that it yields immediate results without resorting to factorials or Stirling's approximation. Similar formulas are found, however, as far back as the work of Boltzmann, and explicitly in Gibbs (see reference).</ref><math> S = k_B \ln W </math>,其中''k<sub>B</sub>'' 是玻尔兹曼常数,''W'' 代表德文中宏观状态出现的概率,<ref>{{cite book|last=Pauli| first=Wolfgang| title=Statistical Mechanics|publisher=MIT Press|location=Cambridge|year=1973|isbn=978-0-262-66035-8}}, p. 21</ref>更准确一些来说,是对应于系统宏观状态的可能微观状态的数量——在一个系统的(可观察的)热力学状态下的(不可观测的)“方式”的数量,可以通过分配不同的位置和动量给不同的分子来实现。玻尔兹曼的范式是N个相同粒子的理想气体,其中Ni处于第i个微观位置和动量条件(范围)。''W'' 可以用排列公式计算:<math> W = N! \prod_i \frac{1}{N_i!} </math>,其中''i'' 的范围包含所有可能的分子状态,<math>!</math>代表阶乘。分母中的“修正”解释了相同条件下难以区分的粒子。 | 普朗克曾说:“熵和概率之间的对数关系是由玻尔兹曼在他的气体动力学理论中首次提出的”。<ref>Max Planck, p. 119.</ref> 也就是著名的熵公式:<ref>The concept of [[entropy]] was introduced by Rudolf Clausius in 1865. He was the first to enunciate the second law of thermodynamics by saying that "entropy always increases".</ref><ref>An alternative is the information entropy definition introduced in 1948 by [[Claude Elwood Shannon|Claude Shannon]].[https://archive.is/20070503225307/http://cm.bell-labs.com/cm/ms/what/shannonday/paper.html] It was intended for use in communication theory, but is applicable in all areas. It reduces to Boltzmann's expression when all the probabilities are equal, but can, of course, be used when they are not. Its virtue is that it yields immediate results without resorting to factorials or Stirling's approximation. Similar formulas are found, however, as far back as the work of Boltzmann, and explicitly in Gibbs (see reference).</ref><math> S = k_B \ln W </math>,其中''k<sub>B</sub>'' 是玻尔兹曼常数,''W'' 代表德文中宏观状态出现的概率,<ref>{{cite book|last=Pauli| first=Wolfgang| title=Statistical Mechanics|publisher=MIT Press|location=Cambridge|year=1973|isbn=978-0-262-66035-8}}, p. 21</ref>更准确一些来说,是对应于系统宏观状态的可能微观状态的数量——在一个系统的(可观察的)热力学状态下的(不可观测的)“方式”的数量,可以通过分配不同的位置和动量给不同的分子来实现。玻尔兹曼的范式是N个相同粒子的理想气体,其中Ni处于第i个微观位置和动量条件(范围)。''W'' 可以用排列公式计算:<math> W = N! \prod_i \frac{1}{N_i!} </math>,其中''i'' 的范围包含所有可能的分子状态,<math>!</math>代表阶乘。分母中的“修正”解释了相同条件下难以区分的粒子。 |