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Oxford University Press eBooks

Conclusion

S. Haroche, J. M. Raimond

Published Aug 10, 2006• 0 citations
Publisher

Abstract

This chapter presents some concluding thoughts from the authors. It evokes future prospects and mentions the challenges ahead. It addresses questions such as: How far will the industry of thought experiments be carried and the quantum classical boundary pushed back? What are the odds to beat decoherence and make quantum information practical? What are the best systems to achieve these goals? Should they be reached from bottom-up, as in atomic physics, or from top-down, as in condensed matter physics?

DOI
10.1093/acprof:oso/9780198509141.003.0010

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This chapter presents some concluding thoughts from the authors. It evokes future prospects and mentions the challenges ahead. It addresses questions such as: How far will the industry of thought experiments be carried and the quantum classical boundary pushed back? What are the odds to beat decoherence and make quantum information practical? What are the best systems to achieve these goals? Should they be reached from bottom-up, as in atomic physics, or from top-down, as in condensed matter physics?
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Quantum theory has inspired many new ideas for understanding Cognition and decision making. Given the nascent state of this field, many new challenges still remain. What are the strengths and unique contributions of these ideas? What are likely next steps in its development? How can it be applied to practical problems in cognitive science? Is this a rational or an irrational system of reasoning? What, if any, are its connections to neuroscience? Should the hard problem of consciousness be considered? These are questions that we try to address in this chapter, albeit at times in a limited way. We end with a debate with a fictitious skeptic (actually previous reviewers) of these ideas. Let us start by reviewing what we have covered so far. Contributions to cognition and decision We begin by summarizing the conclusions reached in previous chapters regarding the usefulness of quantum theory for modelling phenomena in cognition and decision. Chapter 1 provided some motivation and Chapter 2 provided a theoretical introduction to quantum theory. Chapter 3 presented a quantum model to account for question order effects on survey research. An exact and parameter-free test was derived from the model, which produced surprisingly accurate predictions for results obtained from three different large Gallup poll survey studies. Chapter 4 described a quantum model of probability judgments to account for findings that produce violations of classic probability theory, including conjunction and disjunction fallacies and order effects on inference.
Quantum liquids are everywhere. This is a basic message we have tried to deliver throughout this book. But realizing the existence of quantum liquids is by no means the end of the story. An even more important issue is the fact that the various systems we have discussed in this book share common properties, precisely linked to their liquid nature. And realizing the existence of such generic trends in such different systems is a key issue by itself, as it provides a synthetic overview of whole fields of physics. In this concluding chapter, we would like to recall a few basic aspects somewhat scattered all over this book and put them again in perspective, taking for illustration a few key examples.
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320 In 1935, three physicists (Albert Einstein, Boris Podolsky, and Nathan Rosen) proposed a paradox that questioned the interpretations of quantum mechanics (QM). The fact that, apparently, quantum information had to be transmitted more rapidly than the speed of light seemed to breach of wave functions (WFs) that collapsed. Quantum systems (QS) easily entangle each other so that their WFs combine. The fact that they do or not do in phase dictates the result. Thus, quantum information can easily escape, which leads to the loss of cohesion of a quantum state (QSt). Large objects get decoherence more rapidly than smaller ones. Quantum computers (QCs) can someday succeed in substituting Si-based technologies. They can be potent enough to decode any code. They are already only prototypes and handle binary data fragments in the form of quantum bits or atomic states. Based on QM, they could exploit phenomena, for example, entanglement, in order to carry out millions calculations at the time. At supercold temperatures, some metals, alloys, and ceramics completely lose their electric resistance. Currents are free of flowing during thousands of millions years without losing any energy. The reason is QM. On matching, and with a slight shake of the cations lattice, electrons can be kept together. Feynman’s 1981 conjecture, in which QCs can be programmed to simulate any local QS, is correct. Quantum simulators are controllable QSs that could be used to simulate other QSs. Being able to tackle problems that are intractable on classical computers, quantum simulators would provide a means of exploring new physical phenomena. How may quantum simulators become a reality in the near future, as the required technologies are now within research? Quantum simulators, relying on the coherent control of neutral atoms, ions, photons, or electrons, would allow studying problems in a number of fields, for example, condensed matter physics, highenergy physics, cosmology, atomic physics, and quantum chemistry. The long-term promises of quantum simulators are far-reaching but the field needs clearly defined short-term goals.