66,138 research outputs found
Computation in Classical Mechanics
There is a growing consensus that physics majors need to learn computational
skills, but many departments are still devoid of computation in their physics
curriculum. Some departments may lack the resources or commitment to create a
dedicated course or program in computational physics. One way around this
difficulty is to include computation in a standard upper-level physics course.
An intermediate classical mechanics course is particularly well suited for
including computation. We discuss the ways we have used computation in our
classical mechanics courses, focusing on how computational work can improve
students' understanding of physics as well as their computational skills. We
present examples of computational problems that serve these two purposes. In
addition, we provide information about resources for instructors who would like
to include computation in their courses.Comment: 6 pages, 3 figures, submitted to American Journal of Physic
A practical guide to computer simulations
Here practical aspects of conducting research via computer simulations are
discussed. The following issues are addressed: software engineering,
object-oriented software development, programming style, macros, make files,
scripts, libraries, random numbers, testing, debugging, data plotting, curve
fitting, finite-size scaling, information retrieval, and preparing
presentations.
Because of the limited space, usually only short introductions to the
specific areas are given and references to more extensive literature are cited.
All examples of code are in C/C++.Comment: 69 pages, with permission of Wiley-VCH, see http://www.wiley-vch.de
(some screenshots with poor quality due to arXiv size restrictions) A
comprehensively extended version will appear in spring 2009 as book at
Word-Scientific, see http://www.worldscibooks.com/physics/6988.htm
A Data Science Course for Undergraduates: Thinking with Data
Data science is an emerging interdisciplinary field that combines elements of
mathematics, statistics, computer science, and knowledge in a particular
application domain for the purpose of extracting meaningful information from
the increasingly sophisticated array of data available in many settings. These
data tend to be non-traditional, in the sense that they are often live, large,
complex, and/or messy. A first course in statistics at the undergraduate level
typically introduces students with a variety of techniques to analyze small,
neat, and clean data sets. However, whether they pursue more formal training in
statistics or not, many of these students will end up working with data that is
considerably more complex, and will need facility with statistical computing
techniques. More importantly, these students require a framework for thinking
structurally about data. We describe an undergraduate course in a liberal arts
environment that provides students with the tools necessary to apply data
science. The course emphasizes modern, practical, and useful skills that cover
the full data analysis spectrum, from asking an interesting question to
acquiring, managing, manipulating, processing, querying, analyzing, and
visualizing data, as well communicating findings in written, graphical, and
oral forms.Comment: 21 pages total including supplementary material
Genetic programming for the automatic design of controllers for a surface ship
In this paper, the implementation of genetic programming (GP) to design a contoller structure is assessed. GP is used to evolve control strategies that, given the current and desired state of the propulsion and heading dynamics of a supply ship as inputs, generate the command forces required to maneuver the ship. The controllers created using GP are evaluated through computer simulations and real maneuverability tests in a laboratory water basin facility. The robustness of each controller is analyzed through the simulation of environmental disturbances. In addition, GP runs in the presence of disturbances are carried out so that the different controllers obtained can be compared. The particular vessel used in this paper is a scale model of a supply ship called CyberShip II. The results obtained illustrate the benefits of using GP for the automatic design of propulsion and navigation controllers for surface ships
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