Methods of Nature: Landscapes from the Gettysburg College Collection

Methods of Nature: Landscapes from the Gettysburg College Collection is the third annual exhibition curated by students enrolled in the Art History Methods course. The exhibition is an exciting academic endeavor and incredible opportunity for engaged learning, research, and curatorial experience. The five student curators are Molly Chason ’17, Leah Falk ’18, Shannon Gross ’17, Bailey Harper ’19 and Laura Waters ’19. The selection of artworks in this exhibition includes the depiction of landscape in the nineteenth- and twentieth-century French, American and East Asian cultural traditions in various art forms from traditional media of paintings and prints to utilitarian artifacts of porcelain and a paper folding fan. Landscape paintings in this exhibition are inspired by nature, specific locales and literature. Each object carries a distinctive characteristic, a mood, and an ambience. Collectively, they present a multifaceted view of the landscape in the heart and mind of the artists and intended viewers. [excerpt]https://cupola.gettysburg.edu/artcatalogs/1020/thumbnail.jp

Method and Meaning: Selections from the Gettysburg College Collection

What is art historical study and how it should be carried out are fundamental questions the exhibition Method and Meaning: Selections from the Gettysburg College Collection intends to answer. This student-curated exhibition is an exciting academic endeavor of seven students of art history majors and minors in the Art History Methods course. The seven student curators are Shannon Callahan, Ashlie Cantele, Maura D’Amico, Xiyang Duan, Devin Garnick, Allison Gross and Emily Zbehlik. As part of the class assignment, this exhibition allows the students to explore various art history methods on individual case studies. The selection of the works in the exhibition reflects a wide array of student research interests including an example of 18th century Chinese jade chime stone, jade and bronze replicas of ancient Chinese bronze vessels, a piece of early 20th century Chinese porcelain, oil paintings by Pennsylvania Impressionist painter Fern Coppedge, prints by Salvador Dalí and by German artist Käthe Kollwitz, and an early 20th century wood block print by Japanese artist Kawase Hasui. [excerpt]https://cupola.gettysburg.edu/artcatalogs/1014/thumbnail.jp

Statistical mechanics of typical set decoding

The performance of ``typical set (pairs) decoding'' for ensembles of Gallager's linear code is investigated using statistical physics. In this decoding, error happens when the information transmission is corrupted by an untypical noise or two or more typical sequences satisfy the parity check equation provided by the received codeword for which a typical noise is added. We show that the average error rate for the latter case over a given code ensemble can be tightly evaluated using the replica method, including the sensitivity to the message length. Our approach generally improves the existing analysis known in information theory community, which was reintroduced by MacKay (1999) and believed as most accurate to date.Comment: 7 page

The elusive source of quantum effectiveness

We discuss two qualities of quantum systems: various correlations existing between their subsystems and the distingushability of different quantum states. This is then applied to analysing quantum information processing. While quantum correlations, or entanglement, are clearly of paramount importance for efficient pure state manipulations, mixed states present a much richer arena and reveal a more subtle interplay between correlations and distinguishability. The current work explores a number of issues related with identifying the important ingredients needed for quantum information processing. We discuss the Deutsch-Jozsa algorithm, the Shor algorithm, the Grover algorithm and the power of a single qubit class of algorithms. One section is dedicated to cluster states where entanglement is crucial, but its precise role is highly counter-intuitive. Here we see that distinguishability becomes a more useful concept.Comment: 8 pages, no figure

On Hirschman and log-Sobolev inequalities in mu-deformed Segal-Bargmann analysis

We consider a deformation of Segal-Bargmann space and its transform. We study L^p properties of this transform and obtain entropy-entropy inequalities (Hirschman) and entropy-energy inequalities (log-Sobolev) that generalize the corresponding known results in the undeformed theory.Comment: 42 pages, 3 figure

Numerical Confirmation of Late-time t^{1/2} Growth in Three-dimensional Phase Ordering

Results for the late-time regime of phase ordering in three dimensions are reported, based on numerical integration of the time-dependent Ginzburg-Landau equation with nonconserved order parameter at zero temperature. For very large systems ($700^3$) at late times, $t \ge 150,$ the characteristic length grows as a power law, $R(t) \sim t^n$, with the measured $n$ in agreement with the theoretically expected result $n=1/2$ to within statistical errors. In this time regime $R(t)$ is found to be in excellent agreement with the analytical result of Ohta, Jasnow, and Kawasaki [Phys. Rev. Lett. {\bf 49}, 1223 (1982)]. At early times, good agreement is found between the simulations and the linearized theory with corrections due to the lattice anisotropy.Comment: Substantially revised and enlarged, submitted to PR

Cracking the code of oscillatory activity

Neural oscillations are ubiquitous measurements of cognitive processes and dynamic routing and gating of information. The fundamental and so far unresolved problem for neuroscience remains to understand how oscillatory activity in the brain codes information for human cognition. In a biologically relevant cognitive task, we instructed six human observers to categorize facial expressions of emotion while we measured the observers' EEG. We combined state-of-the-art stimulus control with statistical information theory analysis to quantify how the three parameters of oscillations (i.e., power, phase, and frequency) code the visual information relevant for behavior in a cognitive task. We make three points: First, we demonstrate that phase codes considerably more information (2.4 times) relating to the cognitive task than power. Second, we show that the conjunction of power and phase coding reflects detailed visual features relevant for behavioral response-that is, features of facial expressions predicted by behavior. Third, we demonstrate, in analogy to communication technology, that oscillatory frequencies in the brain multiplex the coding of visual features, increasing coding capacity. Together, our findings about the fundamental coding properties of neural oscillations will redirect the research agenda in neuroscience by establishing the differential role of frequency, phase, and amplitude in coding behaviorally relevant information in the brai

Topological reversibility and causality in feed-forward networks

Systems whose organization displays causal asymmetry constraints, from evolutionary trees to river basins or transport networks, can be often described in terms of directed paths (causal flows) on a discrete state space. Such a set of paths defines a feed-forward, acyclic network. A key problem associated with these systems involves characterizing their intrinsic degree of path reversibility: given an end node in the graph, what is the uncertainty of recovering the process backwards until the origin? Here we propose a novel concept, \textit{topological reversibility}, which rigorously weigths such uncertainty in path dependency quantified as the minimum amount of information required to successfully revert a causal path. Within the proposed framework we also analytically characterize limit cases for both topologically reversible and maximally entropic structures. The relevance of these measures within the context of evolutionary dynamics is highlighted.Comment: 9 pages, 3 figure

cPath: open source software for collecting, storing, and querying biological pathways

BACKGROUND: Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. RESULTS: We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. CONCLUSION: cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling