Gibbs vs Boltzmann Entropies

By E. T. Jaynes. 1965

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Citations in the corpus

Algorithmic independence of initial condition and dynamical law in thermodynamics and causal inference (2015, background): “macroscopic states –which becomes problematic on the mesoscopic scale– like the Boltzmann entropy [24].”
On the Entropy Production of Time Series with Unidirectional Linearity (2009, background): “nal linearity in time series To study the implications and the diﬀerent versions of the thermodynamic arrow of time has attracted interest of theoretical physicists and philosophers since a long time [1, 2, 3, 4, 5, 6, 7]. More speciﬁcly, it is the question how the diﬀerence between time reversibili”
The evolutionary approach to entropy: Reconciling Georgescu-Roegen's natural philosophy with the maximum entropy framework (2011, unknown): “As Jaynes (1965) has demonstrated forcefully, entropy – in Searle’s notation – is an observer relative magnitude, because it depends on the setting of macrostates and the constraints.”
Stochastic Time Evolution, Information Geometry, and the Cramér-Rao Bound (2018, background): “Thus, it is not surprising that there exists a strong connection between thermodynamics and information theory, which, despite dating back all the way to Gibbs and Boltzmann [6], has recently received much attention [7– 16].”
Time-Reversal and Entropy (2002, methodology): “ to the level of distributions on ˆΓ. Another application of the Gibbs variational formula (3.6) concerns the change of entropy under the Hamiltonian dynamics. This was emphasized by Jaynes, see e.g. [10]. Suppose the system is initially (at 7 time t0 = 0) prepared with density ˆν× ρ(i.e., microcano”