Correlation-powered Information Engines and the Thermodynamics of Self-Correction

Information engines can use structured environments as a resource to generate work by randomizing ordered inputs and leveraging the increased Shannon entropy to transfer energy from a thermal reservoir to a work reservoir. We give a broadly applicable expression for the work production of an information engine, generally modeled as a memoryful channel that communicates inputs to outputs as it interacts with an evolving environment. The expression establishes that an information engine must have more than one memory state in order to leverage input environment correlations. To emphasize this functioning, we designed an information engine powered solely by temporal correlations and not by statistical biases, as employed by previous engines. Key to this is the engine's ability to synchronize---the engine automatically returns to a desired dynamical phase when thrown into an unwanted, dissipative phase by corruptions in the input---that is, by unanticipated environmental fluctuations. This self-correcting mechanism is robust up to a critical level of corruption, beyond which the system fails to act as an engine. We give explicit analytical expressions for both work and critical corruption level and summarize engine performance via a thermodynamic-function phase diagram over engine control parameters. The results reveal a new thermodynamic mechanism based on nonergodicity that underlies error correction as it operates to support resilient engineered and biological systems.Comment: 22 pages, 13 figures; http://csc.ucdavis.edu/~cmg/compmech/pubs/tos.ht

Identifying Functional Thermodynamics in Autonomous Maxwellian Ratchets

We introduce a family of Maxwellian Demons for which correlations among information bearing degrees of freedom can be calculated exactly and in compact analytical form. This allows one to precisely determine Demon functional thermodynamic operating regimes, when previous methods either misclassify or simply fail due to approximations they invoke. This reveals that these Demons are more functional than previous candidates. They too behave either as engines, lifting a mass against gravity by extracting energy from a single heat reservoir, or as Landauer erasers, consuming external work to remove information from a sequence of binary symbols by decreasing their individual uncertainty. Going beyond these, our Demon exhibits a new functionality that erases bits not by simply decreasing individual-symbol uncertainty, but by increasing inter-bit correlations (that is, by adding temporal order) while increasing single-symbol uncertainty. In all cases, but especially in the new erasure regime, exactly accounting for informational correlations leads to tight bounds on Demon performance, expressed as a refined Second Law of Thermodynamics that relies on the Kolmogorov-Sinai entropy for dynamical processes and not on changes purely in system configurational entropy, as previously employed. We rigorously derive the refined Second Law under minimal assumptions and so it applies quite broadly---for Demons with and without memory and input sequences that are correlated or not. We note that general Maxwellian Demons readily violate previously proposed, alternative such bounds, while the current bound still holds.Comment: 13 pages, 9 figures, http://csc.ucdavis.edu/~cmg/compmech/pubs/mrd.ht

Thermodynamic Machine Learning through Maximum Work Production

Adaptive systems -- such as a biological organism gaining survival advantage, an autonomous robot executing a functional task, or a motor protein transporting intracellular nutrients -- must model the regularities and stochasticity in their environments to take full advantage of thermodynamic resources. Analogously, but in a purely computational realm, machine learning algorithms estimate models to capture predictable structure and identify irrelevant noise in training data. This happens through optimization of performance metrics, such as model likelihood. If physically implemented, is there a sense in which computational models estimated through machine learning are physically preferred? We introduce the thermodynamic principle that work production is the most relevant performance metric for an adaptive physical agent and compare the results to the maximum-likelihood principle that guides machine learning. Within the class of physical agents that most efficiently harvest energy from their environment, we demonstrate that an efficient agent's model explicitly determines its architecture and how much useful work it harvests from the environment. We then show that selecting the maximum-work agent for given environmental data corresponds to finding the maximum-likelihood model. This establishes an equivalence between nonequilibrium thermodynamics and dynamic learning. In this way, work maximization emerges as an organizing principle that underlies learning in adaptive thermodynamic systems.Comment: 29 pages, 10 figures, 6 appendices; http://csc.ucdavis.edu/~cmg/compmech/pubs/tml.ht

Information engine in a nonequilibrium bath

Information engines can convert thermal fluctuations of a bath at temperature $T$ into work at rates of order $k_\mathrm{B}T$ per relaxation time of the system. We show experimentally that such engines, when in contact with a bath that is out of equilibrium, can extract much more work. We place a heavy, micron-scale bead in a harmonic potential that ratchets up to capture favorable fluctuations. Adding a fluctuating electric field increases work extraction up to ten times, limited only by the strength of applied field. Our results connect Maxwell's demon with energy harvesting and an estimate of efficiency shows that information engines in nonequilibrium baths can greatly outperform conventional engines.Comment: 14 pages, 9 figure

Development of track-walking DNA nanomotors

Ph.DDOCTOR OF PHILOSOPH

The Devil Made Her Do It: Three Horror Film Case Studies in the Exorcism Subgenre

Although interest in exorcism has spiked in real world and fictional filmic contexts, scholars have yet to fully identify the exorcism film as a subgenre of the horror film. Following Anne Rothe’s (2011) argument that representation of trauma in popular culture may function like “a discursive knot in contemporary culture due to its vast associative powers of generating interactions between disparate ideas” (p. 4), this study recognizes exorcism as a discursive knot that deserves further attention. Utilizing a case study approach, this dissertation focuses on three exorcism films: The Exorcism of Emily Rose (2005), The Last Exorcism (2010), and The Conjuring (2013). Results concluded that although filmmakers utilize a distinct formula of narrative stages and signature characters to represent contemporary exorcism, such elements were negotiated through each film’s construction. Additionally, this study utilizes Lowenstein’s (2010) concept of “spectacle horror” to highlight dynamic elements of the exorcism film including: bodily contortions, film-viewer relationships, and intertextuality. Based on the analysis, gender stands as a significant theme in the exorcism film’s content and in conceptualizing its constitution. Exorcism films portray women as inescapably connected to men, but rebellious performances of possession provide liberatory possibilities for new symbolic orders. This study also indicates that representation of exorcism itself is gendered and draws attention to the distinct strategies characters utilize. Finally, this dissertation finds the mother-daughter relationship as a crucial site of stability (and horror) in the exorcism film

The role of Fabiana Aziza Cunningham in Stephen Adly Guirgis\u27 The Last Days of Judas Iscariot: a production thesis in acting

This thesis will follow the experience of Leigh-Erin Balmer in creating the role of Fabiana Aziza Cunningham, a character written by Stephen Adly Guirgis in his play, The Last Days of Judas Iscariot. The role of Cunningham is the topic of this production thesis in acting, which will be submitted to the Graduate School of Louisiana State University in partial fulfillment of the requirements for graduation with the Master of Fine Arts degree in Theatre. The thesis contains an introduction; textual analysis and research (regarding author and original production history as well as other text materials); a character study, including a discussion of physical preparation for the role, as well as an investigation of the character relationship between Cunningham and Satan; Balmer’s rehearsal journal which demonstrates growth in implementing research in rehearsal and exhibits performance preparation with detailed scene breakdowns; performance analysis, including written critical feedback; and a conclusion. It will detail Balmer’s approach to the role of Cunningham and decisions regarding Cunningham’s identity, appearance, and character purpose. Finally, the thesis will present a critique of Balmer’s successes in the utilization of different acting methods