A determination of αs from scaling violations with truncated moments

Forte, Stefano; Latorre, José I.; Magnea, Lorenzo; Piccione, Andrea

doi:10.1016/s0920-5632(03)01810-3

Cited by 2 publications

(4 citation statements)

References 11 publications

(21 reference statements)

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“…In this approach, QCD evolution equations are directly expressed in terms of the scale dependence of the contribution to moments of structure functions from the experimentally accessible region. A precision determination of the strong coupling α s based on these techniques will be presented in a companion paper [19].…”

Section: Discussionmentioning

confidence: 99%

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Neural network parametrization of deep-inelastic structure functions

Forte

Garrido

Latorre

et al. 2002

J. High Energy Phys.

195

330

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We construct a parametrization of deep-inelastic structure functions which retains information on experimental errors and correlations, and which does not introduce any theoretical bias while interpolating between existing data points. We generate a Monte Carlo sample of pseudo-data configurations and we train an ensemble of neural networks on them. This effectively provides us with a probability measure in the space of structure functions, within the whole kinematic region where data are available. This measure can then be used to determine the value of the structure function, its error, point-to-point correlations and generally the value and uncertainty of any function of the structure function itself. We apply this technique to the determination of the structure function F 2 of the proton and deuteron, and a precision determination of the isotriplet combination F 2 [p-d]. We discuss in detail these results, check their stability and accuracy, and make them available in various formats for applications.April 2002

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Section: Discussionmentioning

confidence: 99%

“…The key issue here is the choice of a suitable error function Eq. (19). A possibility would be to use the simplest unweighted form Eq.…”

Section: Neural Structure Functions 41 General Strategymentioning

confidence: 99%

Neural network parametrization of deep-inelastic structure functions

Forte

Garrido

Latorre

et al. 2002

J. High Energy Phys.

195

330

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“…We add the following examples. From truncated moments (but with a limited set of proton data and NLO kernels) [14]: α s (m Z ) = 0.122 ± 0.006; from proton data with Nachtmann moments (which take into account some higher twist terms) including effects from soft gluon resummation [15]: α s (m Z ) = 0.1188 ± 0.0017(exp). A combination of measurements at HERA by H1 and ZEUS, also including final state jet observables, leads to α s (m Z ) = 0.1186 ± 0.0051 [16], most of the error being theoretical.…”

Section: Dis 2009mentioning

confidence: 99%

DIS 2009 Concluding Talk: Outlook and Perspective

Altarelli¹

2009

Proceedings of the XVII International Workshop on Deep-Inelastic Scattering and Related Topics

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I will present here my perception on the status of Deep Inelastic Scattering physics, as I have further developed it during this Workshop, together with a number of comments on the results that have impressed me most during this week. I will emphasize a number of open problems and of critical areas. Finally I conclude with some projections and auspices for the future of the field. RM3-TH/09-14CERN-PH-TH/2009-114 * Dedicated to the memory of Wu-Ki Tung, a leading scientist in the field of deep inelastic scattering.

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“…We add the following examples. From truncated moments (but with a limited set of proton data and NLO kernels) [91]: α s (m Z ) = 0.122 ±0.006, from Nachtmann moments (which take into account some higher twist terms) and proton data [92]: α s (m Z ) = 0.1188 ± 0.0017. A combination of measurements at HERA by H1 and Zeus, also including final state jet observables, leads to α s (m Z ) = 0.1186 ± 0.0051 [93], most of the error being theoretical.…”

Section: α S From Deep Inelastic Scatteringmentioning

confidence: 99%