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YCor
YCor
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The origin of the natural base in Statistical Mechanicsstatistical mechanics

In modern treatments of Statistical Mechanicsstatistical mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the Shannon Entropyentropy are invariant to the choice of base of the logarithm, I suspect that physicists might have careful theoretical justifications for this particular choice.

Question: Might there be a sound theory behind this convention?

So far a couple reasons occurred to me:

  1. Stirling's log-factorial approximation:

\begin{equation} \ln N! \sim N \cdot \ln N - N \tag{1} \end{equation}

which is an essential tool in Statistical Mechanicsstatistical mechanics.

  1. The exponential function diagonalises the derivative operator:

\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \cdot \exp(\lambda \cdot H) \tag{2} \end{equation}

which may be useful whenever one wants to analyse variations in the exponential of entropy. The advantage of the exponential of entropy is that it is parameterisation invariant as pointed out by Tom Leinster on a related question.

As there might be subtle reasons I have ignored, any useful references on this question are more than welcome.

References:

  1. von Neumann, John (1932). Mathematische Grundlagen der Quantenmechanik (Mathematical foundations of quantum mechanics) Princeton University Press., . ISBN 978-0-691-02893-4.

  2. Landau and Lifshitz. Statistical Physics. Butterworth-Heinemann. 1980.

  3. David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press 2003.

The origin of the natural base in Statistical Mechanics

In modern treatments of Statistical Mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the Shannon Entropy are invariant to the choice of base of the logarithm, I suspect that physicists might have careful theoretical justifications for this particular choice.

Question: Might there be a sound theory behind this convention?

So far a couple reasons occurred to me:

  1. Stirling's log-factorial approximation:

\begin{equation} \ln N! \sim N \cdot \ln N - N \tag{1} \end{equation}

which is an essential tool in Statistical Mechanics.

  1. The exponential function diagonalises the derivative operator:

\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \cdot \exp(\lambda \cdot H) \tag{2} \end{equation}

which may be useful whenever one wants to analyse variations in the exponential of entropy. The advantage of the exponential of entropy is that it is parameterisation invariant as pointed out by Tom Leinster on a related question.

As there might be subtle reasons I have ignored, any useful references on this question are more than welcome.

References:

  1. von Neumann, John (1932). Mathematische Grundlagen der Quantenmechanik (Mathematical foundations of quantum mechanics) Princeton University Press., . ISBN 978-0-691-02893-4.

  2. Landau and Lifshitz. Statistical Physics. Butterworth-Heinemann. 1980.

  3. David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press 2003.

The origin of the natural base in statistical mechanics

In modern treatments of statistical mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the Shannon entropy are invariant to the choice of base of the logarithm, I suspect that physicists might have careful theoretical justifications for this particular choice.

Question: Might there be a sound theory behind this convention?

So far a couple reasons occurred to me:

  1. Stirling's log-factorial approximation:

\begin{equation} \ln N! \sim N \cdot \ln N - N \tag{1} \end{equation}

which is an essential tool in statistical mechanics.

  1. The exponential function diagonalises the derivative operator:

\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \cdot \exp(\lambda \cdot H) \tag{2} \end{equation}

which may be useful whenever one wants to analyse variations in the exponential of entropy. The advantage of the exponential of entropy is that it is parameterisation invariant as pointed out by Tom Leinster on a related question.

As there might be subtle reasons I have ignored, any useful references on this question are more than welcome.

References:

  1. von Neumann, John (1932). Mathematische Grundlagen der Quantenmechanik (Mathematical foundations of quantum mechanics) Princeton University Press., . ISBN 978-0-691-02893-4.

  2. Landau and Lifshitz. Statistical Physics. Butterworth-Heinemann. 1980.

  3. David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press 2003.

fixed typo
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Aidan Rocke
Aidan Rocke
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In modern treatments of Statistical Mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the Shannon Entropy are invariant to the choice of base of the logarithm, I suspect that physicists might have careful theoretical justifications for this particular choice.

Question: Might there be a sound theory behind this convention?

So far a couple reasons occurred to me:

  1. Stirling's log-factorial approximation:

\begin{equation} \ln N! \sim N \cdot \ln N - N \tag{1} \end{equation}

which is an essential tool in Statistical Mechanics.

  1. The exponential function diagonalises the derivative operator:

\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \tag{2} \end{equation}\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \cdot \exp(\lambda \cdot H) \tag{2} \end{equation}

which may be useful whenever one wants to analyse variations in the exponential of entropy. The advantage of the exponential of entropy is that it is parameterisation invariant as pointed out by Tom Leinster on a related question.

As there might be subtle reasons I have ignored, any useful references on this question are more than welcome.

References:

  1. von Neumann, John (1932). Mathematische Grundlagen der Quantenmechanik (Mathematical foundations of quantum mechanics) Princeton University Press., . ISBN 978-0-691-02893-4.

  2. Landau and Lifshitz. Statistical Physics. Butterworth-Heinemann. 1980.

  3. David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press 2003.

In modern treatments of Statistical Mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the Shannon Entropy are invariant to the choice of base of the logarithm, I suspect that physicists might have careful theoretical justifications for this particular choice.

Question: Might there be a sound theory behind this convention?

So far a couple reasons occurred to me:

  1. Stirling's log-factorial approximation:

\begin{equation} \ln N! \sim N \cdot \ln N - N \tag{1} \end{equation}

which is an essential tool in Statistical Mechanics.

  1. The exponential function diagonalises the derivative operator:

\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \tag{2} \end{equation}

which may be useful whenever one wants to analyse variations in the exponential of entropy. The advantage of the exponential of entropy is that it is parameterisation invariant as pointed out by Tom Leinster on a related question.

As there might be subtle reasons I have ignored, any useful references on this question are more than welcome.

References:

  1. von Neumann, John (1932). Mathematische Grundlagen der Quantenmechanik (Mathematical foundations of quantum mechanics) Princeton University Press., . ISBN 978-0-691-02893-4.

  2. Landau and Lifshitz. Statistical Physics. Butterworth-Heinemann. 1980.

  3. David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press 2003.

In modern treatments of Statistical Mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the Shannon Entropy are invariant to the choice of base of the logarithm, I suspect that physicists might have careful theoretical justifications for this particular choice.

Question: Might there be a sound theory behind this convention?

So far a couple reasons occurred to me:

  1. Stirling's log-factorial approximation:

\begin{equation} \ln N! \sim N \cdot \ln N - N \tag{1} \end{equation}

which is an essential tool in Statistical Mechanics.

  1. The exponential function diagonalises the derivative operator:

\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \cdot \exp(\lambda \cdot H) \tag{2} \end{equation}

which may be useful whenever one wants to analyse variations in the exponential of entropy. The advantage of the exponential of entropy is that it is parameterisation invariant as pointed out by Tom Leinster on a related question.

As there might be subtle reasons I have ignored, any useful references on this question are more than welcome.

References:

  1. von Neumann, John (1932). Mathematische Grundlagen der Quantenmechanik (Mathematical foundations of quantum mechanics) Princeton University Press., . ISBN 978-0-691-02893-4.

  2. Landau and Lifshitz. Statistical Physics. Butterworth-Heinemann. 1980.

  3. David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press 2003.

Source Link
Aidan Rocke
Aidan Rocke
  • 3.9k
  • 19
  • 47

The origin of the natural base in Statistical Mechanics

In modern treatments of Statistical Mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the Shannon Entropy are invariant to the choice of base of the logarithm, I suspect that physicists might have careful theoretical justifications for this particular choice.

Question: Might there be a sound theory behind this convention?

So far a couple reasons occurred to me:

  1. Stirling's log-factorial approximation:

\begin{equation} \ln N! \sim N \cdot \ln N - N \tag{1} \end{equation}

which is an essential tool in Statistical Mechanics.

  1. The exponential function diagonalises the derivative operator:

\begin{equation} \forall \lambda \in (0,1), \frac{\partial}{\partial H} \exp(\lambda \cdot H) = \lambda \tag{2} \end{equation}

which may be useful whenever one wants to analyse variations in the exponential of entropy. The advantage of the exponential of entropy is that it is parameterisation invariant as pointed out by Tom Leinster on a related question.

As there might be subtle reasons I have ignored, any useful references on this question are more than welcome.

References:

  1. von Neumann, John (1932). Mathematische Grundlagen der Quantenmechanik (Mathematical foundations of quantum mechanics) Princeton University Press., . ISBN 978-0-691-02893-4.

  2. Landau and Lifshitz. Statistical Physics. Butterworth-Heinemann. 1980.

  3. David J.C. MacKay. Information Theory, Inference and Learning Algorithms. Cambridge University Press 2003.