A summary of measurements of the fragmentation of charm quarks into a specific hadron is given. Measurements performed in photoproduction and deep inelastic scattering in
e
±
p
,
pp
and
e
+
e
-
...collisions are compared, using up-to-date branching ratios. Within uncertainties, all measurements agree, supporting the hypothesis that fragmentation is independent of the specific production process. Averages of the fragmentation fractions over all measurements are presented. The average has significantly reduced uncertainties compared to individual measurements.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We consider a method for determining the QCD strong coupling constant using fits of perturbative predictions for event shape averages to data collected at the LEP, PETRA, PEP and TRISTAN colliders. ...To obtain highest accuracy predictions we use a combination of perturbative
O
(
α
S
3
)
calculations and estimations of the
O
(
α
S
4
)
perturbative coefficients from data. We account for non-perturbative effects using modern Monte Carlo event generators and analytic hadronization models. The obtained results show that the total precision of the
α
S
determination cannot be improved significantly with the higher-order perturbative QCD corrections alone, but primarily requires a deeper understanding of the non-perturbative effects.
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Deeply learning deep inelastic scattering kinematics Diefenthaler, Markus; Farhat, Abdullah; Verbytskyi, Andrii ...
The European physical journal. C, Particles and fields,
11/2022, Volume:
82, Issue:
11
Journal Article
Peer reviewed
Open access
We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use ...simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables
Q
2
and
x
. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection of a training set, the neural networks sufficiently surpass all classical reconstruction methods on most of the kinematic range considered. Rapid access to large samples of simulated data and the ability of neural networks to effectively extract information from large data sets, both suggest that deep learning techniques to reconstruct DIS kinematics can serve as a rigorous method to combine and outperform the classical reconstruction methods.
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A
bstract
We present state-of-the-art extractions of the strong coupling based on N
3
LO+NNLL accurate predictions for the two-jet rate in the Durham clustering algorithm at
e
+
e
−
collisions, as ...well as a simultaneous fit of the two- and three-jet rates taking into account correlations between the two observables. The fits are performed on a large range of data sets collected at the LEP and PETRA colliders, with energies spanning from 35 GeV to 207 GeV. Owing to the high accuracy of the predictions used, the perturbative uncertainty is considerably smaller than that due to hadronization. Our best determination at the
Z
mass is
α
s
(
M
Z
) = 0
.
11881 ± 0
.
00063(exp
.
) ± 0
.
00101(hadr
.
) ± 0
.
00045(ren
.
) ± 0
.
00034(res
.
), which is in agreement with the latest world average and has a comparable total uncertainty.
Abstract We present a comparison of the computation of energy–energy correlation in $$e^{+}e^{-}$$ e+e- collisions in the back-to-back region at next-to-next-to-leading logarithmic accuracy matched ...with the next-to-next-to-leading order perturbative prediction to LEP, PEP, PETRA, SLC and TRISTAN data. With these predictions we perform an extraction of the strong coupling constant taking into account non-perturbative effects modelled with Monte Carlo event generators. The final result at NNLO+NNLL precision is $$\alpha _{S}(M_{Z})= 0.11750\pm 0.00018 {\text{( } exp.)}\pm 0.00102{\text{( }hadr.)}\pm 0.00257{\text{( }ren.)}\pm 0.00078{\text{( }res.)}$$ αS(MZ)=0.11750±0.00018(exp.)±0.00102(hadr.)±0.00257(ren.)±0.00078(res.) .
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In this proceedings we discuss a prescription to extract the QCD
strong coupling constant at
N^{3}LO
N
3
L
O
precision in perturbative QCD using a combination of
{{O}}(\alpha_{S}^{3})
O
(
α
S
3
)
...calculations in pQCD and estimations of the
{{O}}(\alpha_{S}^{4})
O
(
α
S
4
)
corrections from the data. The method is applied to a set of event shape
averages measured in experiments at the LEP, PETRA, PEP and TRISTAN
colliders. In our analysis we account for hadronization effects with
models from modern Monte Carlo event generators and analytic
hadronization models. We conclude that the precision of the
\alpha_{S}
α
S
extraction cannot be improved significantly only with pQCD predictions
of higher orders, and further progress in these studies requires a
significant advances in the studies and modeling of hadronization
process.
A summary of measurements of the fragmentation of charm quarks into a specific hadron is given. Measurements performed in photoproduction and deep inelastic scattering in e± p, pp and e+e‒ collisions ...are compared, using up-to-date branching ratios. Within uncertainties, all measurements agree, supporting the hypothesis that fragmentation is independent of the specific production process. Averages of the fragmentation fractions over all measurements are presented. The average has significantly reduced uncertainties compared to individual measurements.
Full text
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
We study jet production in e+e− annihilation to hadrons with data recorded by the OPAL experiment at LEP at centre-of-mass energies between 91 GeV and 209 GeV. The jet production rates were measured ...with Durham and for the first time with the anti-kt and SISCone jet clustering algorithms. We compare the data with predictions by modern Monte Carlo event generators.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
The installation and maintenance of scientific software for research in experimental, phenomenological, and theoretical High Energy Physics (HEP) requires a considerable amount of time and ...expertise. While many tools are available to make the task of installation and maintenance much easier, many of these tools require maintenance on their own, have little documentation and very few are used outside of HEP community.
For the installation and maintenance of the software, we rely on the well tested, extensively documented, and reliable stack of software management tools with the RPM Package Manager (RPM) at its core. The precompiled HEP software packages can be deployed easily and without detailed Linux system knowledge and are kept up-to-date through the regular system update process. The precompiled packages were tested on multiple installations of openSUSE, RHEL clones, and Fedora. As the RPM infrastructure is adopted by many Linux distributions, the approach can be used on more systems.
In this contribution, we discuss our approach to software deployment in detail, present the software repositories for multiple RPM-based Linux distributions to a wider public and call for a collaboration for all the interested parties.
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