2016
DOI: 10.1007/s11467-016-0558-5
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Uncertainty relations for general phase spaces

Abstract: We describe a setup for obtaining uncertainty relations for arbitrary pairs of observables related by a Fourier transform. The physical examples discussed here are the standard position and momentum, number and angle, finite qudit systems, and strings of qubits for quantum information applications. The uncertainty relations allow for an arbitrary choice of metric for the outcome distance, and the choice of an exponent distinguishing, e.g., absolute and root mean square deviations. The emphasis of this article … Show more

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Cited by 21 publications
(41 citation statements)
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“…Of the two metrics we only demand translation invariance d(x + z, y + z) = d(x, y), which makes sense because the domain is a group. We claim [51] that in all these cases the uncertainty regions for measurement and preparation coincide. The crucial step is to consider a special type of joint measurement, called a covariant phase space measurement.…”
Section: Results On Measurement and Preparation Uncertaintymentioning
confidence: 72%
“…Of the two metrics we only demand translation invariance d(x + z, y + z) = d(x, y), which makes sense because the domain is a group. We claim [51] that in all these cases the uncertainty regions for measurement and preparation coincide. The crucial step is to consider a special type of joint measurement, called a covariant phase space measurement.…”
Section: Results On Measurement and Preparation Uncertaintymentioning
confidence: 72%
“…There are also variants, in which the sharpness of a distribution is measured by other quantities than the usual variance [10][11][12][13], for instance entropies [14,15], or where more than two observables are considered simultaneously [16,17]. Quite different methods [18] are needed for optimal measurement uncertainty relations [10], or information-disturbance bounds [10], so we will not consider these aspects here.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, we identify the class of the approximate joint measurements with the class of the joint POVMs satisfying the same symmetry properties of their target position and momentum observables [3,23]. We are supported in this assumption by the fact that, in the discrete case [41], simmetry covariant measurements turn out to be the best approximations without any hypothesis (see also [17,19,20,29,32] for a similar appearance of covariance within MURs for different uncertainty measures).…”
Section: Introductionmentioning
confidence: 84%
“…A very rich literature on this topic flourished in the last 20 years, and various kinds of MURs have been proposed, based on distances between probability distributions, noise quantifications, conditional entropy, etc. [12,[14][15][16][17][18][19][20][21][27][28][29][30][31][32].…”
Section: Introductionmentioning
confidence: 99%