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EScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG Computational (Physics) Thinking Rubin H Landau, Founding Dir Computational Physics.

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Presentation on theme: "EScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG Computational (Physics) Thinking Rubin H Landau, Founding Dir Computational Physics."— Presentation transcript:

1 eScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG Computational (Physics) Thinking Rubin H Landau, Founding Dir Computational Physics for Undergraduates BS Degree Program @ Oregon State University Prior Support: NSF (CCLI, CI-Team/EPIC), OSU, MSR

2 eScience Workshop 12/08 eScience Workshop 12/08  CS and CP computational think differently  Edu really computational think differently  Balanced knowledge: CS +App Math + “Science”  Problems no respect discipline boundaries  Multi tools, techniques to solve problems  “What’s a good P like you talking about algorithms?”  Grow richer fields, communities (Geo Cybenko)  iff learn each other’s languages & trade in good faith  Take risks to face unknown, new  Learn multiple subjects in context  More efficient & effective Computational Physics Thinking ( Ed ) (meaningful clichés)

3 eScience Workshop 12/08 eScience Workshop 12/08 Computational Physics Thinking  Realistic not just analytic solutions  “approximate” more truthful than “exact” solutions  Complex not just simple systems  For C Physics  broader view of Science  New/excluded subjects  MD  Nonlinear science: chaos, fractals  Fluids: shocks, solitons  Signal process:  wavelets, DFT, Prin Components  Integral eqtns ( linear  libes); scattering  Space-time correlated systems; e wave packets  Many body theories  Parallel solutions require parallelizable theories  Imbued Visualization @ all stages

4 eScience Workshop 12/08 eScience Workshop 12/08 More Computational S Think  What is reality, scientific truth?  Abstracting in Math, CS, S  Group theory meets programming  Think, visualize in multiple dimensions, I  e.g. L = I ω  Complex numbers (abstract space)  Step towards intellectual maturity (Piaget)  Less abstract Ed for all needs reversal  Inclusive yet still teach what’s needed  E.g. Google  Multi-D info  Parallel files & compute clouds  No fear of compiled languages  Conversant in several  No fear of Looking inside black box  Software, algorithms, hardware  Memory hierarchy, tuning  

5 eScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG Evidence for  (Science Ed)  RHL Survey (Y&L)  CSE, CP ~ balance  Small sample  Stereotypes   PH Ed:  imbalance? PHYSPHYS CSCS MTHMTH OtherOther

6 eScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG Curriculum vs Comp Physics Curriculum O.Y. Problem solving (why do P, what P do) Learn by doing individual Projects Over-shoulder teach (lectures?) CS + Math + physics in context More efficient, effective approach to science Ed ok  # “physics” courses; yet many new subjects Compiled language see algorithm (eqtns) bare bone codes given “I am not a bigot!” (packages) equation solved (math) numerical method used code listing results (graph/table) critical discussion (meet the boss) Multi ≠ Inter

7 © Rubin Landau, CPUG Real computation across the curriculum Not 1 course, not just our view Use what’s available

8 eScience Workshop 12/08 eScience Workshop 12/08 Make into Content Map!

9 eScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG 1. Challenging for some students (intro*, multidisciplinary) 2. Unhappy with grade if just ran code, no thought, no time 3. Students often thankful when/that over (career) 4. Tears, emotion; human-C interaction = complex 5. Excitement; human-C interaction = complex, emotional 6. “This combo is what I interested in, but had to pick 1” 7. “Why have we studied fluids only in our freshman year?” 8. “Now I know what is dynamic in thermodynamics”  9. “Gave me an entirely new view of integration, series, ” 10. “Now Laplace’s equation makes sense” 11. “I was up all night.” “I was up all night.” 12. Chaotic scattering: several MS, 1 Ph D thesisChaotic scattering: 13. “MD: way I thought simulations should be” 14. Great prep  physics, astroP, CS, ocean, bioP, brain 15. Women: didn’t know liked C, problem solving  How Does this Work?

10 eScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG © Rubin Landau, CPUG Two Lower-Division Courses

11 eScience Workshop 12/08 eScience Workshop 12/08 © Rubin Landau, CPUG © Rubin Landau, CPUG Contents of Upper-Division Courses


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