There are two main theoretical frameworks in statistical mechanics, one associated with Boltzmann and the other with Gibbs. Despite their well-known differences, there is a prevailing view that equilibrium values calculated in both frameworks coincide. We show that this is wrong. There are important cases in which the Boltzmannian and Gibbsian equilibrium concepts yield different outcomes. Furthermore, the conditions under which equilibriums exists are different for Gibbsian and Boltzmannian statistical mechanics. There are, however, special circumstances under which it is true (...) that the equilibrium values coincide. We prove a new theorem providing sufficient conditions for this to be the case. (shrink)

A popular view in contemporary Boltzmannian statistical mechanics is to interpret the measures as typicality measures. In measure-theoretic dynamical systems theory measures can similarly be interpreted as typicality measures. However, a justification why these measures are a good choice of typicality measures is missing, and the paper attempts to fill this gap. The paper first argues that Pitowsky's (2012) justification of typicality measures does not fit the bill. Then a first proposal of how to justify typicality measures is presented. The (...) main premises are that typicality measures are invariant and are related to the initial probability distribution of interest (which are translation-continuous or translation-close). The conclusions are two theorems which show that the standard measures of statistical mechanics and dynamical systems are typicality measures. There may be other typicality measures, but they agree about judgements of typicality. Finally, it is proven that if systems are ergodic or epsilon-ergodic, there are uniqueness results about typicality measures. (shrink)

Kevin Davey claims that the justification of the second law of thermodynamics as it is conveyed by the “standard story” of statistical mechanics, roughly speaking, that lowentropy microstates tend to evolve to high-entropy microstates, is “unhelpful at best and wrong at worst.” In reply, I demonstrate that Davey’s argument for rejecting the standard story commits him to a form of skepticism that is more radical than the position he claims to be stating and that Davey places unreasonable demands on the (...) notion of justification in the physical sciences. (shrink)

We often use symmetries to infer outcomes’ probabilities, as when we infer that each side of a fair coin is equally likely to come up on a given toss. Why are these inferences successful? I argue against answering this with an a priori indifference principle. Reasons to reject that principle are familiar, yet instructive. They point to a new, empirical explanation for the success of our probabilistic predictions. This has implications for indifference reasoning in general. I argue that a priori (...) symmetries need never constrain our probability attributions, even when it comes to our initial credences. (shrink)

The relationship between statistical mechanics and population genetics has a long history. Both take advantage of statistics to address the behavior of large groups of entities. The main objective of this article is to assess the obstacles population genetics is meeting in its claim to explain biological phenomena from the conceptual apparatus of statistical mechanics according to two recent articles. Several tools available to the latter are missing in the former. Thus, in the absence of an adequate justification of the (...) relevance of the analogy and without the satisfaction of certain basic assumptions, I argue that the explanatory strategy of the analogously based model is seriously compromised. La relation entre mécanique statistique et génétique des populations a une longue histoire. À l’instar de la première, la seconde tire profit des statistiques afin de traiter le comportement des grands ensembles d’entités. L’objectif principal du présent article est d’identifier les obstacles que rencontre la génétique des populations dans sa prétention d’explication des phénomènes biologiques à partir de l’appareillage conceptuel de la mécanique statistique selon deux articles récents. Or, plusieurs outils dont dispose cette dernière manque à la première. Ainsi, en l’absence d’une justification adéquate de la pertinence de l’analogie et sans la satisfaction de certaines hypothèses fondamentales, je soutiens que la stratégie explicative du modèle analogue est sérieusement compromise. (shrink)

In many ways, entropy and probability are two concepts that complement each other. But it has been argued that there is no ‘straightforward connection’ between them with a no-go thesis from Kevin D...

The laws of nature are central to our understanding of the world. And while there is often broad agreement about the technical formulations of the laws, there can be sharp disagreement about the metaphysical nature of the laws. For instance, the Newtonian laws of nature can be stated and analyzed by appealing to a set of possible worlds. Yet, some philosophers argue the worlds are mere notational devices, while others take them to be robust, concrete entities in their own right. (...) In this paper, I use a recent view of laws called the Mentaculus as a case study to illustrate the wide variety of metaphysical pictures that can accompany such a view. I conclude that the technical features of the laws -- typically (though not always) given to us by practicing scientists -- are compatible with many different metaphysical foundations. (shrink)

A gas relaxing into equilibrium is often taken to be a process in which a system moves from an “improbable” to a “probable” state. Given that the thermodynamic entropy increases during such a process, it is natural to conjecture that the thermodynamic entropy is a measure of the probability of a macrostate. For nonideal classical gases, however, I claim that there is no clear sense in which the thermodynamic entropy of a macrostate measures its probability. We must therefore reject the (...) idea that thermodynamic entropy and probability are connected in a deep and general way. (shrink)

Entropy is ubiquitous in physics, and it plays important roles in numerous other disciplines ranging from logic and statistics to biology and economics. However, a closer look reveals a complicated picture: entropy is defined differently in different contexts, and even within the same domain different notions of entropy are at work. Some of these are defined in terms of probabilities, others are not. The aim of this chapter is to arrive at an understanding of some of the most important notions (...) of entropy and to clarify the relations between them, After setting the stage by introducing the thermodynamic entropy, we discuss notions of entropy in information theory, statistical mechanics, dynamical systems theory and fractal geometry. (shrink)

I defend the idea that the fact that no system is entirely isolated can be used to explain the successful use of the microcanonical distribution in statistical mechanics. The argument turns on claims about what is needed for an adequate explanation of this fact: I argue in particular that various competing explanations do not meet reasonable conditions of adequacy, and that the most striking lacuna in Interventionism – its failure to explain the ‘arrow of time’ – is no real defect.