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On the Role of Consciousness in Random Physical Processes

  • Robert G. Jahn
  • Brenda Dunne
Part of the Fundamental Theories of Physics book series (FTPH, volume 24)

Abstract

Extensive data from a variety of man/machine experiments indicate that human operators can influence random device output distributions in accordance with pre-stated intentions. Deviations of these output distribution mean values from theoretical expectations or calibration data accumulate in individually characteristic and repli- cable patterns of achievement, many of which achieve high statistical significance. Despite wide variations in individual performance, the composite data base for 33 operators also departs substantially from chance expectation. Histograms of the deviations achieved in 87 separate experimental series confirm the significant mean shifts in the intended directions, and in addition distribute with greater than chance variance. In contrast, the histogram of baseline deviations, obtained under null intentions of the operators, centers on the appropriate chance mean, but with a variance considerably smaller than chance. When all such baseline and directional mean deviations are combined in an appropriately balanced mixture, a normal chance histogram is reconstituted. Such behavior raises the possibility that the basic combinatorial processes undergirding classical or quantum statistical mechanics may reflect, at least to a marginal degree, some processes of human consciousness. This hypothesis, along with the empirical data on which it is based, is consistent with a quantum wave mechanical model of the interactions of consciousness with its physical environment that predicts experiential eigenfunctions indexed by appropriate quantum numbers of both the consciousness and the physical system, and influenced by the degree of resonance between them, in much the same fashion as the Heitler-London treatment of molecular bonds.

Keywords

Output Distribution Quantum Statistical Mechanic High Statistical Significance Cumulative Deviation Full Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Kluwer Academic Publishers 1989

Authors and Affiliations

  • Robert G. Jahn
    • 1
  • Brenda Dunne
    • 1
  1. 1.School of Engineering and Applied SciencePrinceton UniversityPrincetonUSA

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