UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

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Author: search.filters.author.Parker, DanielSubject: search.filters.subject.History of Science

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    Thermodynamics, Reversibility and Jaynes' Approach to Statistical Mechanics
    (2006-07-25) Parker, Daniel; Bub, Jeffrey; Philosophy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation contests David Albert's recent arguments that the proposition that the universe began in a particularly low entropy state (the "past hypothesis") is necessary and sufficient to ground the thermodynamic asymmetry against the reversibility objection, which states that the entropy of thermodynamic systems was previously larger than it is now. In turn, it argues that this undermines Albert's suggestion that the past hypothesis can underwrite other temporal asymmetries such as those of records and causation. This thesis thus concerns the broader philosophical problem of understanding the interrelationships among the various temporal asymmetries that we find in the world, such as those of thermodynamic phenomena, causation, human agency and inference. The position argued for is that the thermodynamic asymmetry is nothing more than an inferential asymmetry, reflecting a distinction between the inferences made towards the past and the future. As such, it cannot be used to derive a genuine physical asymmetry. At most, an inferential asymmetry can provide evidence for an asymmetry not itself forthcoming from the formalism of statistical mechanics. The approach offered here utilises an epistemic, information-theoretic interpretation of thermodynamics applied to individual "branch" systems in order to ground irreversible thermodynamic behaviour (Branch systems are thermodynamic systems quasi-isolated from their environments for short periods of time). I argue that such an interpretation solves the reversibility objection by treating thermodynamics as part of a more general theory of statistical inference supported by information theory and developed in the context of thermodynamics by E.T. Jaynes. It is maintained that by using an epistemic interpretation of probability (where the probabilities reflect one's knowledge about a thermodynamic system rather than a property of the system itself), the reversibility objection can be disarmed by severing the link between the actual history of a thermodynamic system and its statistical mechanical description. Further, novel and independent arguments to ground the veracity of records in the face of the reversibility objection are developed. Additionally, it is argued that the information-theoretic approach offered here provides a clearer picture of the reduction of the thermodynamic entropy to its statistical mechanical basis than other extant proposals.