International Journal of Theoretical Physics

, Volume 49, Issue 2, pp 304–315 | Cite as

Quantum One Go Computation and the Physical Computation Level of Biological Information Processing

  • Giuseppe Castagnoli


By extending the representation of quantum algorithms to problem-solution interdependence, the unitary evolution part of the algorithm entangles the register containing the problem with the register containing the solution. Entanglement becomes correlation, or mutual causality, between the two measurement outcomes: the string of bits encoding the problem and that encoding the solution. In former work, we showed that this is equivalent to the algorithm knowing in advance 50% of the bits of the solution it will find in the future, which explains the quantum speed up.

Mutual causality between bits of information is also equivalent to seeing quantum measurement as a many body interaction between the parts of a perfect classical machine whose normalized coordinates represent the qubit populations. This “hidden machine” represents the problem to be solved. The many body interaction (measurement) satisfies all the constraints of a nonlinear Boolean network “together and at the same time”—in one go—thus producing the solution.

Quantum one go computation can formalize the physical computation level of the theories that place consciousness in quantum measurement. In fact, in visual perception, we see, thus recognize, thus process, a significant amount of information “together and at the same time”. Identifying the fundamental mechanism of consciousness with that of the quantum speed up gives quantum consciousness, with respect to classical consciousness, a potentially enormous evolutionary advantage.

Quantum information Quantum algorithms Quantum speed up Quantum measurement Many body problem Quantum consciousness 


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  1. 1.
    Castagnoli, G.: The mechanism of quantum computation. Int. J. Theor. Phys. 47(8), 2181 (2008) MATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Castagnoli, G.: The quantum speed up as advanced cognition of the solution. Int. J. Theor. Phys. 48(3), 857 (2009) MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Castagnoli, G.: The 50% advanced information rule of the quantum algorithms. Int. J. Theor. Phys. 48(8), 2412 (2009) MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Castagnoli, G.: Quantum algorithms know in advance 50% of the solution they will find in the future. Int. J. Theor. Phys. 48(12), 3383 (2009) CrossRefMathSciNetGoogle Scholar
  5. 5.
    Castagnoli, G., Finkelstein, D.: Theory of the quantum speed up. Proc. R. Soc. Lond. A 457, 1799 (2001). arXiv:quant-ph/0010081 v1. MATHCrossRefMathSciNetADSGoogle Scholar
  6. 6.
    Castagnoli, G., Rasetti, M., Vincenzi, A.: Steady, simultaneous quantum computation: a paradigm for the investigation of nondeterministic and non-recursive computation. Int. J. Mod. Phys. C 3(4), 661 (1992) MATHCrossRefMathSciNetADSGoogle Scholar
  7. 7.
    Chalmers, D.: Facing up the problem of consciousness. J. Conscious. Stud. 2, 200–219 (1995) Google Scholar
  8. 8.
    De Faccio, A.: From an altered state of consciousness to a life long quest of a model of mind. TASTE Archives of Scientists’ Transcendent Experiences, submission N 00098. Charles T. Tart, ed. (2002)
  9. 9.
    Deutsch, D.: Quantum theory, the Church-Turing principle, and the universal quantum computer. Proc. R. Soc. Lond. A 400, 97 (1985) MATHCrossRefMathSciNetADSGoogle Scholar
  10. 10.
    Engel, G.S., Calhoun, T.R., Read, E.L., Ahn, T.K., Mencal, T., Cheng, Y.C., Blankenship, R.E., Fleming, G.R.: Evidence for wavelike energy transfer through quantum coherence in photosynthetic systems. Nature 446, 782 (2007) CrossRefADSGoogle Scholar
  11. 11.
    Finkelstein, D.R.: Generational quantum theory. Preprint, to become a Springer book (2008) Google Scholar
  12. 12.
    Fredkin, E., Toffoli, T.: Conservative logic. Int. J. Theor. Phys. 21, 219 (1982) MATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    George, F.H., Johnson, L.: Purposive Behaviour and Teleological Explanations. Studies in Cybernetic, vol. 8. Gordon and Breach, New York (1985) Google Scholar
  14. 14.
    Grover, L.K.: A fast quantum mechanical algorithm for data base search. In: Proc. 28th Ann. ACM Symp. Theory of Computing (1996) Google Scholar
  15. 15.
    Hagan, S., Hameroff, S.R., Tuszynski, J.A.: Quantum computation in brain microtubules? Decoherence and biological feasibility. Phys. Rev. E 65, 061901 (2002) CrossRefADSGoogle Scholar
  16. 16.
    Hameroff, S.R.: The brain is both neurocomputer and quantum computer. Cogn. Sci. 31, 1035–1045 (2007) Google Scholar
  17. 17.
    Hameroff, S.R.: The “conscious pilot”—dendritic synchrony moves through the brain to mediate consciousness. J. Biol. Phys.
  18. 18.
    Hameroff, S.R., Penrose, R.: Toward a science of consciousness. In: Hameroff, S.R., Kaszniak, A.W., Scott, A.C. (eds.) The First Tucson Discussions and Debates, pp. 507–540. MIT Press, Cambridge (1996) Google Scholar
  19. 19.
    Lucas, J.R.: The Godelian argument. (July, 2002)
  20. 20.
    Neven, H., Dencher, V.S., Rose, G., Macready, W.G.: Training a binary classifier with the quantum adiabatic algorithm. arXiv:0811.0416v1 [quant-ph] (2008)
  21. 21.
    Penrose, R.: Shadows of the Mind—A Search for the Missing Science of Consciousness. Oxford University Press, Oxford (1994) Google Scholar
  22. 22.
    Searle, J.R.: Mind, a Brief Introduction. Oxford University Press, Oxford (2004) Google Scholar
  23. 23.
    Shehan, D.P.: Frontiers of Time: Retrocausation—Experiment and Theory, San Diego, California, 20–22 June 2006 Google Scholar
  24. 24.
    Shülte-Herbrüggen, T., Spörl, A., Khaneja, N., Glaser, S.J.: Optimal control for generating quantum gates in open dissipative systems. arxiv:quant-ph/0609037 (2009)
  25. 25.
    Stapp, H.P.: Mind Matter and Quantum Mechanics. Springer, Berlin (2009) MATHCrossRefGoogle Scholar
  26. 26.
    Summhammer, J., Bernroider, G.: Quantum entanglement in the voltage dependent sodium channel can reproduce the salient features of neuronal action potential initiation. arXiv:0712.1474v1 [] (2007)
  27. 27.
    Trugenberger, C.A.: Quantum pattern recognition. arXiv:quant-ph/0210176v2 (2002)
  28. 28.
    Ventura, D., Martinez, T.: Quantum associative memory. Inf. Sci. 124(14), 273–296 (2000) CrossRefMathSciNetGoogle Scholar
  29. 29.
    Vitiello, G.: Coherent states, fractals, and brain waves. New Math. Nat. Comput. 5(1), 245–264 (2009) MATHCrossRefGoogle Scholar
  30. 30.
    Zhou, R., Ding, Q.: Quantum pattern recognition with probability 100%. Int J. Theor. Phys. 47(5) (2008) Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Elsag BaileyPieve LigureItaly

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