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The Quantum Formalism in Social Science: A Brief Excursion

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Structural Changes and their Econometric Modeling (TES 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 808))

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Abstract

This contribution discusses several examples on how social science problems can begin to be re-interpreted with the aid of elements of the formalism of quantum mechanics.

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Notes

  1. 1.

    Econophysics is a movement which has endeavoured to apply statistical mechanics concepts mostly to finance but also to economics.

  2. 2.

    And even less in finance!.

  3. 3.

    Those sort of arguments I hear often. They are expected but they also show that when individuals make those statements, they problably will not have read much of the mainstream literature on the interface of quantum mechanics and social science.

  4. 4.

    Think of an operator as an instruction. A Hermitian operator expressed in matrix form will essentially say this: if you take the transpose of a matrix (and you multiply each element with its complex conjugate), then if that yields the original matrix, the matrix is Hermitian.

  5. 5.

    The Hamiltonian is the sum of potential and kinetic energy. In a quantum mechanical context, when the Hamiltonian becomes an operator, this forms a key part in the rendering of the so called Schrödinger partial differential equation (PDE). This PDE describes the undisturbed evolution of a state (in time dependent or time independent fashion). It is a central equation in quantum mechanics.

  6. 6.

    Many textbooks exist which introduce quantum physics. A great book to consider is Bowman [10].

  7. 7.

    No Planck constant occurs in the macroscopic version of this potential!.

  8. 8.

    If you are not sure what those expected utility frameworks are, a great book to consider the intricacies is by Kreps [14].

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Haven, E. (2019). The Quantum Formalism in Social Science: A Brief Excursion. In: Kreinovich, V., Sriboonchitta, S. (eds) Structural Changes and their Econometric Modeling. TES 2019. Studies in Computational Intelligence, vol 808. Springer, Cham. https://doi.org/10.1007/978-3-030-04263-9_8

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