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Visual Analysis of Quantum Physics Data

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Quantum Dynamic Imaging

Abstract

During the past two decades data visualization has matured as an own sub-discipline in computer science. Its methods are successfully applied in almost all areas of science, engineering, and medicine, in order to depict and visually analyze data—both from experiment and simulation. The goal of data visualization is to achieve a better understanding of data by intuitive, perceptually efficient and interactively steerable depictions of the data. For this specific data analysis methods are combined with visualization techniques that utilize modern computer graphics. Quantum physics, however, so far remained largely omitted as application area, in particular due to the high dimensionality of the phenomena. However, the situation is not hopeless; on the contrary, there are many ways to visualize quantum mechanical phenomena. In this paper, this will be demonstrated by means of visualizations of simulation data from quantum chemistry and high-harmonic generation.

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References

  1. S. Brandt, H.D. Dahmen, The Picture Book of Quantum Mechanics, 3rd edn. (Springer, New York, 2001)

    Google Scholar 

  2. B. Thaller, Visual Quantum Mechanics (Springer, New York, 2000)

    Google Scholar 

  3. B. Thaller, Advanced Visual Quantum Mechanics (Springer, New York, 2005)

    Google Scholar 

  4. D.T. Smithey, M. Beck, M.G. Raymer, A. Faridani, Phys. Rev. Lett. 70, 1244 (1993)

    Article  ADS  Google Scholar 

  5. J. Itatani, J. Levesque, D. Zeidler, H. Niikura, H. PĂ©pin, J.C. Kieffer, P.B. Corkum, D.M. Villeneuve, Nature 432, 867 (2004)

    Article  ADS  Google Scholar 

  6. S. Haessler, J. Caillat, W. Boutu, C. Giovanetti-Teixeira, T. Ruchon, T. Auguste, Z. Diveki, P. Breger, A. Maquet, B. Carr´e, R. TaĂ¯eb, P. Salières, Nature Phys. 6, 200 (2010)

    Google Scholar 

  7. C. Figueira de Morisson Faria, B.B. Augstein, Phys. Rev. A 81, 043409 (2010)

    Google Scholar 

  8. H. Niikura, N. Dudovich, D.M. Villeneuve, P.B. Corkum, Phys. Rev. Lett. 105, 053003 (2010)

    Article  ADS  Google Scholar 

  9. J. Meyer, J. Thomas, S. Diehl, B. Fisher, D.A. Keim, in Scientific Visualization: Advanced Concepts, Dagstuhl Follow-Ups, vol. 1, ed. by H. Hagen (Schloss Dagstuhl—Leibniz-Zentrum f¨ur Informatik, Dagstuhl, 2010), pp. 227–245. URL http://drops.dagstuhl.de/opus/volltexte/2010/2707

  10. C.D. Hansen, C.R. Johnson, The Visualization Handbook (Academic Press, Orlando, FL, 2005)

    Google Scholar 

  11. A.C. Telea, Data Visualization (A K Peters Ltd, London, 2007)

    Google Scholar 

  12. J.L. Moreland, A. Gramada, O.V. Buzko, Q. Zhang, P.E. Bourne, BMC Bioinformatics 6, 21 (2005)

    Article  Google Scholar 

  13. S.J. Lee, H.Y. Chung, K.S. Kim, Bull. Kor. Chem. Soc. 25, 1061 (2004)

    Article  Google Scholar 

  14. J.D. Gans, D. Shalloway, J. Mol. Graph. Model. 19, 557 (2001)

    Article  Google Scholar 

  15. J. Schmidt-Ehrenberg, D. Baum, H.C. Hege, in VIS ’02—Proceedings of the conference on Visualization ’02 (IEEE, Washington, DC, 2002), pp. 235–242

    Google Scholar 

  16. F.W. Young, P. Rheingans, IBM J. Res. Develop. 35, 97 (1991)

    Article  Google Scholar 

  17. E.A. Rundensteiner, M.O.Ward, J. Yang, P.R. Doshi, in SIGMOD ’02 Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data (ACM, New York, 2002), p. 631

    Google Scholar 

  18. P.E. Hoffman, G.G. Grinstein, in Information Visualization in Data Mining and Knowledge Discovery, ed. by U. Fayyad, G.G. Grinstein, A. Wierse (Morgan Kaufmann, San Francisco, CA, 2001), pp. 47–82

    Google Scholar 

  19. J.A. Walter, H. Ritter, in KDD ’02 - Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM, New York, 2002), pp. 123–132

    Google Scholar 

  20. A. Hinneburg, D.A. Keim, M. Wawryniuk, IEEE Comput. Graphics Appl. 19(5), 22 (1999)

    Article  Google Scholar 

  21. K. Engel,M. Hadwiger, J.M. Kniss, C. Rezk-Salama, Real-Time Volume Graphics (A K Peters Ltd, London, 2006)

    Google Scholar 

  22. H.C. Hege, T. Höllerer, D. Stalling, Volume rendering—mathematical models and algorithmic aspects. Tech. Rep. 93–07, ZIB (1993)

    Google Scholar 

  23. L. Noodleman, J.G. Norman, J.H. Osborne, A. Aizman, D.A. Case, J. Am. Chem. Soc. 107(12), 3418 (1985)

    Article  Google Scholar 

  24. T.S. Newman, H. Yi, Computers & Graphics 30, 854 (2006)

    Article  Google Scholar 

  25. W.E. Lorensen, H.E. Cline, in SIGGRAPH ’87—Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, ed. by M.C. Stone (ACM, New York, 1987), pp. 163–169

    Google Scholar 

  26. J. Chambers, W. Cleveland, B. Kleiner, P. Tukey, Graphical Methods for Data Analysis (Wadsworth, Monterey, CA, 1983)

    Google Scholar 

  27. N. Elmqvist, P. Dragicevic, J.D. Fekete, IEEE Trans. Vis. Comput. Graph. 14(6), 1141 (2008)

    Article  Google Scholar 

  28. A. Inselberg, B. Dimsdale, in Visualization ’90—Proceedings of the 1st Conference on Visualization (IEEE, Washington, DC, 1990), pp. 361–378

    Google Scholar 

  29. A. Inselberg, Parallel Coordinates—Visual Multidimensional Geometry and Its Applications (Springer, New York, 2009)

    Google Scholar 

  30. J. Blaas, C.P. Botha, F.H. Post, IEEE Trans. Vis. Comput. Graph. 14(6), 1436 (2008)

    Article  Google Scholar 

  31. D. Asimov, SIAM J. Sci. Statist. Comput. 6, 128 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  32. H. Hauser, F. Ledermann, H. Doleisch, in INFOVIS ’02 Proceedings of the IEEE Symposium on Information Visualization (IEEE, Washington, DC, 2002), pp. 127–130

    Google Scholar 

  33. D. Stalling, M. Westerhoff, H.C. Hege, in The Visualization Handbook, ed. by C.D. Hansen, C.R. Johnson (Academic Press, Orlando, FL, 2005), chap. 38, pp. 749–767

    Google Scholar 

  34. I. Barth, H.C. Hege, H. Ikeda, A. Kenfack, M. Koppitz, J. Manz, F. Marquardt, G.K. Paramonov, Chem. Phys. Lett. 481, 118 (2009)

    Article  ADS  Google Scholar 

  35. J. Caillat, J. Zanghellini,M. Kitzler, O. Koch,W. Kreuzer, A. Scrinzi, Phys. Rev. A 71, 012712 (2005)

    Article  ADS  Google Scholar 

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Correspondence to Hans-Christian Hege .

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Hege, HC., Koppitz, M., Marquardt, F., McDonald, C., Mielack, C. (2011). Visual Analysis of Quantum Physics Data. In: Bandrauk, A., Ivanov, M. (eds) Quantum Dynamic Imaging. CRM Series in Mathematical Physics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9491-2_6

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