Skip to main content

The Evolution of our Probability Image for the Spin Orientation of a Spin — 1/2 — Ensemble as Measurements are Made on Several Members of the Ensemble — Connections with Information Theory and Bayesian Statistics

  • Chapter
Maximum Entropy and Bayesian Methods

Part of the book series: Fundamental Theories of Physics ((FTPH,volume 43))

Abstract

An analysis is made of the information acquired when measurements are made, of the component of spin along an arbitrarily chosen axis, (Θ, Φ), of each of several or many spin 1/2 systems, each prepared in the same way. Since the probability p↑ of the observed value of the spin being “up” is a unique function of the relative orientation of the axis of measurement, (Θ, Φ), and the quantization axis, (θ, φ), of the state into which the system was prepared, this probability function, p↑(θ, φ; Θ, Φ), may be interpreted as a likelihood function for the orientation, (θ, φ), of the state into which the system is prepared, conditioned by its having been measured with “up” spin along the axis with orientation (Θ, Φ). If one assumes that the preparation procedure prepares each system into the same unknown pure state, and further assumes that, a priori, each equal infinitisimal solid angle is equally likely to contain the orientation of this pure state, the likelihood function for the orientation, via Bayes’ theorem, becomes the (unnormalized) probability density function for the orientation of the pure state. Thus, from an ensemble of spin 1/2 systems, each prepared in the pure state with quantization axis (θ, φ), the probability for realizing n “up” values and m = N—n “down” values, in some specified order, in a sequence of N measurement events for the spin component along the (Θ, Φ) axis, is given by Π(θ, φ; Θ, Φ) = p n(1-p )m = p n(1-p ])N-n, (as in the Bernoulli coin-tossing problem). By the above arguments Π(θ, φ; Θ, Φ) dΩ, becomes, for fixed (Θ, Φ,n,N), the (unnormalized) probability for the system being prepared in the spin state whose direction is aligned to within dΩ of (θ, φ), conditioned by the measurement events which determined Π. If we take the density operator corresponding to this distribution function to be ρ = [∫dΩ,ρ0(θ, φ)Π(θ, φ; Θ, Φ)]/[∫dΩΠ(θ, φ; Θ, Φ)], where ρ0(θ, φ) is the density operator corresponding to the pure state aligned along (θ, φ), one finds that the probability of measuring “up” spin along (Θ, Φ), conditioned by a measurement of n “up” values in N trials is given by (n+1)/(N+2), which is Laplace’s rule of succession. Also presented is a geometrical parametrization of the density operator for a spin 1/2 system. The density operator for the pure state with spin orientation (θ, φ) is represented as the corresponding point on the unit sphere. Each point in the interior of the sphere represents a non-idempotent density operator, diagonal in the coordinate system in which the radial line to the representative point lies on the +2 axis, and such that the radius is equal to (σz) = λ — λ. A measurement of n “up” values in TV trials, with a prior probability distribution that is uniform over the volume of this sphere, leads to (n+2)/(N+4) for the probability of measuring “up” spin; a more “cautious” rule of succession than that of Laplace.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Von Neumann, J.: 1943, Math. Grundlagen der Quantenmechanik, Dover, New York, 41.

    Google Scholar 

  2. Messiah, A.: 1962, Quantum Mechanics, North-Holland, Amsterdam Chaps. 5 and 7.

    MATH  Google Scholar 

  3. Löwdin, P.O.: 1964, Linear Algebra and the Fundamentals of Quantum Theory, Technical Note 125, Uppsala Quantum Chemistry Group, unpublished.

    Google Scholar 

  4. Löwdin, P.O.: 1987, ‘Some Comments about the Historical Development of Reduced Density Matrices’, Density Matrices and Density Functionals, Proceedings of the A. John Coleman Symposium, R.E. Erdahl and V.H. Smith (eds.), D. Reidel.

    Google Scholar 

  5. Fano, U.: 1957, ‘Description of States in Quantum Mechanics by Density Matrix and Operator Techniques’, Rev. Mod. Phys. 29, 74.

    Article  MathSciNet  MATH  Google Scholar 

  6. Coleman, A.J.: 1987, ‘Reduced Density Matrices from 1930 to 1989’, Density Matrices and Density Functionals, Proceedings of the A. John Coleman Symposium), R.E. Erdahl and V.H. Smith (eds.), D. Reidel, Dordrecht.

    Google Scholar 

  7. McWeeny, R.: 1960, ‘Some Recent Advances in Density Matrix Theory’, Rev. Mod. Phys. 32, 335.

    Article  MathSciNet  MATH  Google Scholar 

  8. Larson, E.G.: 1987, ‘Reduced Density Operators, Their Related von Neumann Density Operators, Close Cousins of These, and Their Physical Interpretation’, Density Matrices and Density Functionals, Proceedings of the A. John Coleman Symposium), R.E. Erdahl and V.H. Smith (eds.), D. Reidel, Dordrecht, 249.

    Chapter  Google Scholar 

  9. Shannon, C.E.: 1948, ‘A Mathematical Theory of Communication’, Bell System Tech. J. 27, 379, 623.

    MathSciNet  MATH  Google Scholar 

  10. Jaynes, E.T.: 1963, ‘Information Theory and Statistical Mechanics’, Statistical Physics, 1962 Brandeis Lectures 3, Benjamin, New York, 181.

    Google Scholar 

  11. Katz, A.: 1967, Principles of Statistical Mechanics — The Information Theory Approach, W.H. Freeman and Co., San Francisco, Chaps. 2 and 4.

    Google Scholar 

  12. Larson, E.G.: 1973, Int. J. Quantum Chem. 7, 853.

    Article  Google Scholar 

  13. Dukes, P.R. and E.G. Larson: 1991, ‘Assignment of Prior Expectation Values and a More Efficient Means of Maximizing —Trρlnρ Constrained to Measured Expectation Values for Quantum Systems with Total Angular Momentum J’, elsewhere in this proceedings.

    Google Scholar 

  14. Wooters, W. Kent: 1980, The Acquisition of Information from Quantum Measurements, Ph.D. Dissertation, University of Texas at Austin.

    Google Scholar 

  15. Jaynes, E.T.: 1983, Papers on Probability, Statistics, and Statistical Physics, D. Reidel.

    Google Scholar 

  16. Jaynes, E.T.: 1990, Probability Theory — The Logic of Science, in press, Chaps. 4 and 13.

    Google Scholar 

  17. Fisher, R.A.: 1973, Statistical Methods and Scientific Inference, Third Edition, Hafner Press, New York, 11, 12, 24, 56, 115, and 133.

    MATH  Google Scholar 

  18. Rosenkranz, R.D.: 1977, Inference, Method and Decision, D. Reidel, 48, 52, and 62.

    Google Scholar 

  19. de Laplace, P.S.: 1820, Theorie Analytique des Probabilitié, 3rd Edition, Paris, 178.

    Google Scholar 

  20. Pólya, G.: 1954, Patterns of Plausible Inference, Princeton Univ. Press, 132–139.

    Google Scholar 

  21. Carnap, R.: 1952, The Continuum of Inductive Methods, Univ. of Chicago Press.

    Google Scholar 

  22. Cyranski, J.F.: 1986, ‘The Probability of a Probability’, in Maximum Entropy and Bayesian Methods in Applied Statistics, Proceedings of the Fourth Maximum Entropy Workshop, Univ. of Calgary, 1984, J.H. Justice (ed.), Cambridge Univ. Press, 101–116.

    Google Scholar 

  23. Hua, L.K.: 1963, Harmonic Analysis of Functions of Several Complex Varibles in the Classical Domains, Amer. Math. Soc., Providence.

    Google Scholar 

  24. Fröhner, F.H.: 1989, Applications of the Maximum Entropy Principle in Nuclear Physics, Kernforschungszentrum, Karlsruh GmbH, 1989, 16 and 17.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Larson, E.G., Dukes, P.R. (1991). The Evolution of our Probability Image for the Spin Orientation of a Spin — 1/2 — Ensemble as Measurements are Made on Several Members of the Ensemble — Connections with Information Theory and Bayesian Statistics. In: Grandy, W.T., Schick, L.H. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 43. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-3460-6_17

Download citation

  • DOI: https://doi.org/10.1007/978-94-011-3460-6_17

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-5531-4

  • Online ISBN: 978-94-011-3460-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics