The Observer Interpretation Evolution and Collapse Determination in a Single 2-D Space

Abstract Full-Text HTML XML Download Download as PDF (Size:366KB) PP. 53-58
DOI: 10.4236/apm.2014.42008    2,249 Downloads   3,375 Views   Citations

ABSTRACT

We present a complete interpretation theory in the following sense: we observe that each measuring device represents a concept set (such as the set of locations) while the measurement activity associates the measured object with an appropriate member from the concepts set. In that sense, the measurement process is the only interpretation of reality. In this article, we deal with the evolution of this interpreting measuring device for a 2-d Hilbert space. It is shown that nonlinear recursive maps give rise to a unique projective operator accompanied with the collapse ability and consequently to a measuring device. Our formalism can be easily interpreted as a single brain signal.

Cite this paper

Y. Roth, "The Observer Interpretation Evolution and Collapse Determination in a Single 2-D Space," Advances in Pure Mathematics, Vol. 4 No. 2, 2014, pp. 53-58. doi: 10.4236/apm.2014.42008.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Y. G. Roth, “Bifurcation and Pattern Recognition,” Journal of Modern Physics, Vol. 4, No. 1, 2013, pp. 25-29.
http://dx.doi.org/10.4236/jmp.2013.41005
[2] Y. G. Roth, “Single Measurement of Figures,” Journal of Modern Physics, Vol. 4, No. 6, 2013, pp. 812-817.
[3] S. S. Ge, C. C. Hang and T. Zhang, “Systems, Man, and Cybernetics, Part B,” Cybernetics, Vol. 29, No. 6, 1999, pp. 818-828.
[4] Y. G. Roth, “The Evolution of Quantum Measuring Devices,” Accepted for Publication at the IC-MSQUARE Conference Proceedings Book, 2013.
[5] R. Penrose, “The Road to Reality: A Complete Guide to the Laws of the Universe, Ch. 2, Vintage Books,” 2004.
[6] G. C. Ghirardi, A. Rimini and T. Weber, “Unified Dynamics for Microscopic and Macroscopic Systems,” Physical Review D, Vol. 34, No. 2, 1986, pp. 470-491. http://dx.doi.org/10.1103/PhysRevD.34.470
[7] D. J. Amit and H. Gutfreund, “Spin-Glass Models of Neural Networks,” Physical Review A, Vol. 32, No. 2, 1985, pp. 1007-1018.
[8] A. Wolf, J. B. Swift, H. L. Swinney and J. A. Vastano, “Determining Lyapunov Exponents from a Time Series,” Physica D, Vol. 16, No. 3, 1985, pp. 285-317. http://dx.doi.org/10.1016/0167-2789(85)90011-9
[9] D. L. Stein and C. M. Newman, “Spin Glasses and Complexity (Primers in Complex Systems), Ch. 1,” Princeton University, Princeton, 2013.
[10] A. Bassi, “Dynamical Reduction Models: Present Status and Future Developments,” Journal of Physics: Conference Series, Vol. 67, 2007, Article ID: 012013.
[11] A. Bassi and D. G. M. Salvetti, “The Quantum Theory of Measurement within Dynamical Reduction Models,” Journal of Physics A: Mathematical Theory, Vol. 40, No. 32, 2007, p. 9859. http://dx.doi.org/10.1088/1751-8113/40/32/011
[12] W. H. Zurek, “Decoherence and the Transition from Quantum to Classical,” Physics Today, Vol. 44, No. 10, 1991, pp. 36-44.
http://dx.doi.org/10.1063/1.881293
[13] S. L. Adler and A. Bassi, “Collapse Models with Non-White Noises,” Journal of Physics A: Mathematical Theory, Vol. 40, No. 50, 2007, pp. 15083-15098. http://dx.doi.org/10.1088/1751-8113/40/50/012

  
comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.