Computational Thinking, Between Papert and Wing
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Advances in Theoretical & Computational Physics
ISSN: 2639-0108 Review Article Advances in Theoretical & Computational Physics Cosmology: Preprogrammed Evolution (The problem of Providence) Besud Chu Erdeni Unified Theory Lab, Bayangol disrict, Ulan-Bator, Mongolia *Corresponding author Besud Chu Erdeni, Unified Theory Lab, Bayangol disrict, Ulan-Bator, Mongolia. Submitted: 25 March 2021; Accepted: 08 Apr 2021; Published: 18 Apr 2021 Citation: Besud Chu Erdeni (2021) Cosmology: Preprogrammed Evolution (The problem of Providence). Adv Theo Comp Phy 4(2): 113-120. Abstract This is continued from the article Superunification: Pure Mathematics and Theoretical Physics published in this journal and intended to discuss the general logical and philosophical consequences of the universal mathematical machine described by the superunified field theory. At first was mathematical continuum, that is, uncountably infinite set of real numbers. The continuum is self-exited and self- organized into the universal system of mathematical harmony observed by the intelligent beings in the Cosmos as the physical Universe. Consequently, cosmology as a science of evolution in the Uni- verse can be thought as a preprogrammed natural phenomenon beginning with the Big Bang event, or else, the Creation act pro- (6) cess. The reader is supposed to be acquinted with the Pythagoras’ (Arithmetization) and Plato’s (Geometrization) concepts. Then, With this we can derive even the human gene-chromosome topol- the numeric, Pythagorean, form of 4-dim space-time shall be ogy. (1) The operator that images the organic growth process from nothing is where time is an agorithmic (both geometric and algebraic) bifur- cation of Newton’s absolute space denoted by the golden section exp exp e. -
Journal of Computational Physics
JOURNAL OF COMPUTATIONAL PHYSICS AUTHOR INFORMATION PACK TABLE OF CONTENTS XXX . • Description p.1 • Audience p.2 • Impact Factor p.2 • Abstracting and Indexing p.2 • Editorial Board p.2 • Guide for Authors p.6 ISSN: 0021-9991 DESCRIPTION . Journal of Computational Physics has an open access mirror journal Journal of Computational Physics: X which has the same aims and scope, editorial board and peer-review process. To submit to Journal of Computational Physics: X visit https://www.editorialmanager.com/JCPX/default.aspx. The Journal of Computational Physics focuses on the computational aspects of physical problems. JCP encourages original scientific contributions in advanced mathematical and numerical modeling reflecting a combination of concepts, methods and principles which are often interdisciplinary in nature and span several areas of physics, mechanics, applied mathematics, statistics, applied geometry, computer science, chemistry and other scientific disciplines as well: the Journal's editors seek to emphasize methods that cross disciplinary boundaries. The Journal of Computational Physics also publishes short notes of 4 pages or less (including figures, tables, and references but excluding title pages). Letters to the Editor commenting on articles already published in this Journal will also be considered. Neither notes nor letters should have an abstract. Review articles providing a survey of particular fields are particularly encouraged. Full text articles have a recommended length of 35 pages. In order to estimate the page limit, please use our template. Published conference papers are welcome provided the submitted manuscript is a significant enhancement of the conference paper with substantial additions. Reproducibility, that is the ability to reproduce results obtained by others, is a core principle of the scientific method. -
Computational Science and Engineering
Computational Science and Engineering, PhD College of Engineering Graduate Coordinator: TBA Email: Phone: Department Chair: Marwan Bikdash Email: [email protected] Phone: 336-334-7437 The PhD in Computational Science and Engineering (CSE) is an interdisciplinary graduate program designed for students who seek to use advanced computational methods to solve large problems in diverse fields ranging from the basic sciences (physics, chemistry, mathematics, etc.) to sociology, biology, engineering, and economics. The mission of Computational Science and Engineering is to graduate professionals who (a) have expertise in developing novel computational methodologies and products, and/or (b) have extended their expertise in specific disciplines (in science, technology, engineering, and socioeconomics) with computational tools. The Ph.D. program is designed for students with graduate and undergraduate degrees in a variety of fields including engineering, chemistry, physics, mathematics, computer science, and economics who will be trained to develop problem-solving methodologies and computational tools for solving challenging problems. Research in Computational Science and Engineering includes: computational system theory, big data and computational statistics, high-performance computing and scientific visualization, multi-scale and multi-physics modeling, computational solid, fluid and nonlinear dynamics, computational geometry, fast and scalable algorithms, computational civil engineering, bioinformatics and computational biology, and computational physics. Additional Admission Requirements Master of Science or Engineering degree in Computational Science and Engineering (CSE) or in science, engineering, business, economics, technology or in a field allied to computational science or computational engineering field. GRE scores Program Outcomes: Students will demonstrate critical thinking and ability in conducting research in engineering, science and mathematics through computational modeling and simulations. -
Agent-Based Modeling with Netlogo
Agent-Based Modeling with NetLogo Uri Wilensky Center for Connected Learning and Computer-Based Modeling Northwestern Institute on Complex Systems Departments of Computer Science & Learning Sciences Northwestern University Agent-Based Modeling in NetLogo SFI MOOC, Summer 2016 1 History: Roman to Hindu-Arabic Europe – at the turn of the first millenium • Before widespread adoption of Hindu-Arabic, very few could do multiplication/division • Scientists recognized superiority immediately • But widespread adoption took a very long time • Was in surreptitious use, but not official 2 Restructurations Structurations -- the encoding of the knowledge in a domain as a function of the representational infrastructure used to express the knowledge Restructurations -- A change from one structuration of a domain to another resulting from a change in representational infrastructure --- Wilensky & Papert 2006;2010 What is important and hard for people today? Similar to numeracy importance for science but difficulties in understanding, today we need to make sense of complex systems yet we find it difficult. What are Complex Systems? • Systems with a large number of interacting parts, evolving over time • Decentralized decisions vs. centralized control • Emergent global patterns from local interactions and decisions • Examples: ecosystems, economies, immune systems, molecular systems, minds, stock market, democratic government... Emergent Phenomena • Structure (Rules) at Micro- level leads to pattern at Macro- level • Order without Design • No leader or orchestrator -
COMPUTER PHYSICS COMMUNICATIONS an International Journal and Program Library for Computational Physics
COMPUTER PHYSICS COMMUNICATIONS An International Journal and Program Library for Computational Physics AUTHOR INFORMATION PACK TABLE OF CONTENTS XXX . • Description p.1 • Audience p.2 • Impact Factor p.2 • Abstracting and Indexing p.2 • Editorial Board p.2 • Guide for Authors p.4 ISSN: 0010-4655 DESCRIPTION . Visit the CPC International Computer Program Library on Mendeley Data. Computer Physics Communications publishes research papers and application software in the broad field of computational physics; current areas of particular interest are reflected by the research interests and expertise of the CPC Editorial Board. The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered. -
A Simplified Introduction to Virus Propagation Using Maple's Turtle Graphics Package
E. Roanes-Lozano, C. Solano-Macías & E. Roanes-Macías.: A simplified introduction to virus propagation using Maple's Turtle Graphics package A simplified introduction to virus propagation using Maple's Turtle Graphics package Eugenio Roanes-Lozano Instituto de Matemática Interdisciplinar & Departamento de Didáctica de las Ciencias Experimentales, Sociales y Matemáticas Facultad de Educación, Universidad Complutense de Madrid, Spain Carmen Solano-Macías Departamento de Información y Comunicación Facultad de CC. de la Documentación y Comunicación, Universidad de Extremadura, Spain Eugenio Roanes-Macías Departamento de Álgebra, Universidad Complutense de Madrid, Spain [email protected] ; [email protected] ; [email protected] Partially funded by the research project PGC2018-096509-B-100 (Government of Spain) 1 E. Roanes-Lozano, C. Solano-Macías & E. Roanes-Macías.: A simplified introduction to virus propagation using Maple's Turtle Graphics package 1. INTRODUCTION: TURTLE GEOMETRY AND LOGO • Logo language: developed at the end of the ‘60s • Characterized by the use of Turtle Geometry (a.k.a. as Turtle Graphics). • Oriented to introduce kids to programming (Papert, 1980). • Basic movements of the turtle (graphic cursor): FD, BK RT, LT. • It is not based on a Cartesian Coordinate system. 2 E. Roanes-Lozano, C. Solano-Macías & E. Roanes-Macías.: A simplified introduction to virus propagation using Maple's Turtle Graphics package • Initially robots were used to plot the trail of the turtle. http://cyberneticzoo.com/cyberneticanimals/1969-the-logo-turtle-seymour-papert-marvin-minsky-et-al-american/ 3 E. Roanes-Lozano, C. Solano-Macías & E. Roanes-Macías.: A simplified introduction to virus propagation using Maple's Turtle Graphics package • IBM Logo / LCSI Logo (’80) 4 E. -
Computational Complexity for Physicists
L IMITS OF C OMPUTATION Copyright (c) 2002 Institute of Electrical and Electronics Engineers. Reprinted, with permission, from Computing in Science & Engineering. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the discussed products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by sending a blank email message to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. COMPUTATIONALCOMPLEXITY FOR PHYSICISTS The theory of computational complexity has some interesting links to physics, in particular to quantum computing and statistical mechanics. This article contains an informal introduction to this theory and its links to physics. ompared to the traditionally close rela- mentation as well as the computer on which the tionship between physics and mathe- program is running. matics, an exchange of ideas and meth- The theory of computational complexity pro- ods between physics and computer vides us with a notion of complexity that is Cscience barely exists. However, the few interac- largely independent of implementation details tions that have gone beyond Fortran program- and the computer at hand. Its precise definition ming and the quest for faster computers have been requires a considerable formalism, however. successful and have provided surprising insights in This is not surprising because it is related to a both fields. -
Viewpoint Do We Really Need Computational Thinking?
viewpoints VDOI:10.1145/3231587 Enrico Nardelli Viewpoint Do We Really Need Computational Thinking? Considering the expression “computational thinking” as an entry point to understand why the fundamental contribution of computing to science is the shift from solving problems to having problems solved. CONFESS UPFRONT, the title of this Viewpoint is meant to attract readers’ attention. As a com- puter scientist, I am convinced we need the concept of compu- Itational thinking, interpreted as “being able to think like a computer scientist and being able to apply this competence to every field of human endeavor.” The focus of this Viewpoint is to dis- cuss to what extent we need the expres- sion “computational thinking” (CT). The term was already known through the work of Seymour Papert,13 many com- putational scientists,5 and a recent pa- per15 clarifies both its historical devel- opment and intellectual roots. After the widely cited Communications Viewpoint by Jeannette Wing,19 and thanks to her role at NSF,6 an extensive discussion opened with hundreds of subsequent papers dissecting the expression. There is not yet a commonly agreed definition of CT—what I consider in this View- Wing discussed CT to argue it is im- Forsythe, a former ACM president and point is whether we really need a defini- portant every student is taught “how one of the founding fathers of computer tion and for which goal. a computer scientist thinks,”19 which science education in academia, in 1968 To anticipate the conclusion, we I interpret to mean it is important to wrote: “The most valuable acquisition probably need the expression as an in- teach computer science to every stu- in a scientific or technical education are strument, as a shorthand reference to dent. -
Computational Complexity: a Modern Approach
i Computational Complexity: A Modern Approach Sanjeev Arora and Boaz Barak Princeton University http://www.cs.princeton.edu/theory/complexity/ [email protected] Not to be reproduced or distributed without the authors’ permission ii Chapter 10 Quantum Computation “Turning to quantum mechanics.... secret, secret, close the doors! we always have had a great deal of difficulty in understanding the world view that quantum mechanics represents ... It has not yet become obvious to me that there’s no real problem. I cannot define the real problem, therefore I suspect there’s no real problem, but I’m not sure there’s no real problem. So that’s why I like to investigate things.” Richard Feynman, 1964 “The only difference between a probabilistic classical world and the equations of the quantum world is that somehow or other it appears as if the probabilities would have to go negative..” Richard Feynman, in “Simulating physics with computers,” 1982 Quantum computing is a new computational model that may be physically realizable and may provide an exponential advantage over “classical” computational models such as prob- abilistic and deterministic Turing machines. In this chapter we survey the basic principles of quantum computation and some of the important algorithms in this model. One important reason to study quantum computers is that they pose a serious challenge to the strong Church-Turing thesis (see Section 1.6.3), which stipulates that every physi- cally reasonable computation device can be simulated by a Turing machine with at most polynomial slowdown. As we will see in Section 10.6, there is a polynomial-time algorithm for quantum computers to factor integers, whereas despite much effort, no such algorithm is known for deterministic or probabilistic Turing machines. -
COMPUTATIONAL SCIENCE 2017-2018 College of Engineering and Computer Science BACHELOR of SCIENCE Computer Science
COMPUTATIONAL SCIENCE 2017-2018 College of Engineering and Computer Science BACHELOR OF SCIENCE Computer Science *The Computational Science program offers students the opportunity to acquire a knowledge in computing integrated with knowledge in one of the following areas of study: (a) bioinformatics, (b) computational physics, (c) computational chemistry, (d) computational mathematics, (e) environmental science informatics, (f) health informatics, (g) digital forensics and cyber security, (h) business informatics, (i) biomedical informatics, (j) computational engineering physics, and (k) computational engineering technology. Graduates of this program major in computational science with a concentration in one of the above areas of study. (Amended for clarification 12/5/2018). *Previous UTRGV language: Computational science graduates develop emphasis in two major fields, one in computer science and one in another field, in order to integrate an interdisciplinary computing degree applied to a number of emerging areas of study such as biomedical-informatics, digital forensics, computational chemistry, and computational physics, to mention a few examples. Graduates of this program are prepared to enter the workforce or to continue a graduate studies either in computer science or in the second major. A – GENERAL EDUCATION CORE – 42 HOURS Students must fulfill the General Education Core requirements. The courses listed below satisfy both degree requirements and General Education core requirements. Required 020 - Mathematics – 3 hours For all -
Down with School! up with Logoland!
NEW SCIENTIST REVIEW Down with School! Up with Logoland! The Children's Machine: Rethinking in the classroom, with mixed results. large and small, designed to implement his School in the Age of the Computer I was one of them. About ten years ago, ideas, and has received a wealth of feed by Seymour Papert, Basic Books, New York, I was part of a team that developed and back, much of it deeply discouraging. But HarperCollins in Britain, pp 241, £22·50 taught an introductory course in computer one can learn even more from "mistakes" science aimed at universirv students who than from a string of successes-that is a Daniel Dennett hated and feared computers but whose central tenet of Papert's vision of learning, parents, in many cases, had said "You must and he practices what he preaches. So this IN 1956, the mathematician John McCarthy learn about computers before you gradu sequel engagingly recounts what he has coined the term "artificial intelligence" ate." These students were seasoned veter learned, and especially the mistakes he for a new discipline that was emerging ans of what Paperr calls School-experts at made along the way. His own thinking from some of the more has undergone a transforma imaginative and playful tion; he is still an infectiously explorations of that new optimistic visionary, but a mind-tool, the computer. A wiser one. few years later he devel Logo has nowjoined forces oped a radically new sort of with Lego, the plastic build programming language, ing blocks, and a new wave Lisp, which became the of delectable settings for lingua franca of AI. -
Papert's Microworld and Geogebra: a Proposal to Improve Teaching Of
Creative Education, 2019, 10, 1525-1538 http://www.scirp.org/journal/ce ISSN Online: 2151-4771 ISSN Print: 2151-4755 Papert’s Microworld and Geogebra: A Proposal to Improve Teaching of Functions Carlos Vitor De Alencar Carvalho1,4, Lícia Giesta Ferreira De Medeiros2, Antonio Paulo Muccillo De Medeiros3, Ricardo Marinho Santos4 1State University Center of Western, Rio de Janeiro, RJ, Brazil 2CEFET/RJ, Valença, RJ, Brazil 3Rio de Janeiro Federal Institute (IFRJ), Pinheiral, RJ, Brazil 4Vassouras University, Vassouras, RJ, Brazil How to cite this paper: De Alencar Car- Abstract valho, C. V., De Medeiros, L. G. F., De Me- deiros, A. P. M., & Santos, R. M. (2019). This paper discusses how to improve teaching of Mathematics in Brazilian Papert’s Microworld and Geogebra: A Pro- schools, based on Seymour Papert’s Constructionism associated with Infor- posal to Improve Teaching of Functions. mation Technology tools. Specifically, this work introduces the construction- Creative Education, 10, 1525-1538. https://doi.org/10.4236/ce.2019.107111 ist microworld, a digital environment where students are able to build their knowledge interactively, in this case, using dynamic mathematics software Received: June 6, 2019 GeoGebra. Accepted: July 14, 2019 Published: July 17, 2019 Keywords Copyright © 2019 by author(s) and Microworld, GeoGebra, Seymour Papert, Information Technologies in Scientific Research Publishing Inc. Education This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access 1. Introduction This research’s main goal is to present a proposal to help Brazilian teachers im- prove their educational practices.