2,143 research outputs found
The Laplace-Jaynes approach to induction
An approach to induction is presented, based on the idea of analysing the
context of a given problem into `circumstances'. This approach, fully Bayesian
in form and meaning, provides a complement or in some cases an alternative to
that based on de Finetti's representation theorem and on the notion of infinite
exchangeability. In particular, it gives an alternative interpretation of those
formulae that apparently involve `unknown probabilities' or `propensities'.
Various advantages and applications of the presented approach are discussed,
especially in comparison to that based on exchangeability. Generalisations are
also discussed.Comment: 38 pages, 1 figure. V2: altered discussion on some points, corrected
typos, added reference
Numerical Bayesian quantum-state assignment for a three-level quantum system. II. Average-value data with a constant, a Gaussian-like, and a Slater prior
This paper offers examples of concrete numerical applications of Bayesian
quantum-state assignment methods to a three-level quantum system. The
statistical operator assigned on the evidence of various measurement data and
kinds of prior knowledge is computed partly analytically, partly through
numerical integration (in eight dimensions) on a computer. The measurement data
consist in the average of outcome values of N identical von Neumann projective
measurements performed on N identically prepared three-level systems. In
particular the large-N limit will be considered. Three kinds of prior knowledge
are used: one represented by a plausibility distribution constant in respect of
the convex structure of the set of statistical operators; another one
represented by a prior studied by Slater, which has been proposed as the
natural measure on the set of statistical operators; the last prior is
represented by a Gaussian-like distribution centred on a pure statistical
operator, and thus reflecting a situation in which one has useful prior
knowledge about the likely preparation of the system. The assigned statistical
operators obtained with the first two kinds of priors are compared with the one
obtained by Jaynes' maximum entropy method for the same measurement situation.
In the companion paper the case of measurement data consisting in absolute
frequencies is considered.Comment: 10 pages, 4 figures. V2: added "Post scriptum" under Conclusions,
slightly changed Acknowledgements, and corrected some spelling error
Numerical Bayesian state assignment for a three-level quantum system. I. Absolute-frequency data; constant and Gaussian-like priors
This paper offers examples of concrete numerical applications of Bayesian
quantum-state-assignment methods to a three-level quantum system. The
statistical operator assigned on the evidence of various measurement data and
kinds of prior knowledge is computed partly analytically, partly through
numerical integration (in eight dimensions) on a computer. The measurement data
consist in absolute frequencies of the outcomes of N identical von Neumann
projective measurements performed on N identically prepared three-level
systems. Various small values of N as well as the large-N limit are considered.
Two kinds of prior knowledge are used: one represented by a plausibility
distribution constant in respect of the convex structure of the set of
statistical operators; the other represented by a Gaussian-like distribution
centred on a pure statistical operator, and thus reflecting a situation in
which one has useful prior knowledge about the likely preparation of the
system.
In a companion paper the case of measurement data consisting in average
values, and an additional prior studied by Slater, are considered.Comment: 23 pages, 14 figures. V2: Added an important note concerning
cylindrical algebraic decomposition and thanks to P B Slater, corrected some
typos, added reference
Unpolarized light in quantum optics
We present a new derivation of the unpolarized quantum states of light, whose
general form was first derived by Prakash and Chandra [Phys. Rev. A 4, 796
(1971)]. Our derivation makes use of some basic group theory, is
straightforward, and offers some new insights.Comment: 3 pages, REVTeX, presented at ICQO'200
Tunable effective g-factor in InAs nanowire quantum dots
We report tunneling spectroscopy measurements of the Zeeman spin splitting in
InAs few-electron quantum dots. The dots are formed between two InP barriers in
InAs nanowires with a wurtzite crystal structure grown by chemical beam
epitaxy. The values of the electron g-factors of the first few electrons
entering the dot are found to strongly depend on dot size and range from close
to the InAs bulk value in large dots |g^*|=13 down to |g^*|=2.3 for the
smallest dots. These findings are discussed in view of a simple model.Comment: 4 pages, 3 figure
Interest Rates and Information Geometry
The space of probability distributions on a given sample space possesses
natural geometric properties. For example, in the case of a smooth parametric
family of probability distributions on the real line, the parameter space has a
Riemannian structure induced by the embedding of the family into the Hilbert
space of square-integrable functions, and is characterised by the Fisher-Rao
metric. In the nonparametric case the relevant geometry is determined by the
spherical distance function of Bhattacharyya. In the context of term structure
modelling, we show that minus the derivative of the discount function with
respect to the maturity date gives rise to a probability density. This follows
as a consequence of the positivity of interest rates. Therefore, by mapping the
density functions associated with a given family of term structures to Hilbert
space, the resulting metrical geometry can be used to analyse the relationship
of yield curves to one another. We show that the general arbitrage-free yield
curve dynamics can be represented as a process taking values in the convex
space of smooth density functions on the positive real line. It follows that
the theory of interest rate dynamics can be represented by a class of processes
in Hilbert space. We also derive the dynamics for the central moments
associated with the distribution determined by the yield curve.Comment: 20 pages, 3 figure
Quantum limits on phase-shift detection using multimode interferometers
Fundamental phase-shift detection properties of optical multimode
interferometers are analyzed. Limits on perfectly distinguishable phase shifts
are derived for general quantum states of a given average energy. In contrast
to earlier work, the limits are found to be independent of the number of
interfering modes. However, the reported bounds are consistent with the
Heisenberg limit. A short discussion on the concept of well-defined relative
phase is also included.Comment: 6 pages, 3 figures, REVTeX, uses epsf.st
Two-photon imaging and quantum holography
It has been claimed that ``the use of entangled photons in an imaging system
can exhibit effects that cannot be mimicked by any other two-photon source,
whatever strength of the correlations between the two photons'' [A. F.
Abouraddy, B. E. A. Saleh, A. V. Sergienko, and M. C. Teich, Phys. Rev. Lett.
87, 123602 (2001)]. While we believe that the cited statement is true, we show
that the method proposed in that paper, with ``bucket detection'' of one of the
photons, will give identical results for entangled states as for appropriately
prepared classically correlated states.Comment: 4 pages, 2 figures, REVTe
Measuring the Mermin-Peres magic square using an online quantum computer
We have implemented the six series of three commuting measurement of the
Mermin-Peres magic square on an online, five qubit, quantum computer. The magic
square tests if the measurements of the system can be described by physical
realism (in the EPR sense) and simultaneously are non-contextual. We find that
our measurement results violate any realistic and non-contextual model by
almost 28 standard deviations. We also find that although the quantum computer
we used for the measurements leaves much to be desired in producing accurate
and reproducible results, the simplicity, the ease of re-running the
measurement programs, and the user friendliness compensates for this fact.Comment: 7 pages, 2 figures, 5 table
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