Results 51 to 60 of about 1,466 (260)

Associated production of a top quark pair with a heavy electroweak gauge boson at NLO+NNLL accuracy

open access: yesEuropean Physical Journal C: Particles and Fields, 2019
We perform threshold resummation of soft gluon corrections to the total cross sections and the invariant mass distributions for production of a top-antitop quark pair associated with a heavy electroweak boson $$V = W^+$$ V=W+ , $$W^-$$ W- or Z in pp ...
Anna Kulesza   +4 more
doaj   +1 more source

The light MSSM Higgs boson mass for large $$\tan \beta $$ tan β and complex input parameters

open access: yesEuropean Physical Journal C: Particles and Fields, 2020
We discuss various improvements of the prediction for the light MSSM Higgs boson mass in the hybrid framework of the public code $$\texttt {FeynHiggs}$$ FeynHiggs , which combines fixed-order and effective field theory results.
Henning Bahl   +2 more
doaj   +1 more source

Disentangling observable dependence in SCETI and SCETII anomalous dimensions: angularities at two loops

open access: yesJournal of High Energy Physics, 2021
The resummation of radiative corrections to collider jet observables using soft collinear effective theory is encoded in differential renormalization group equations (RGEs), with anomalous dimensions depending on the observable under consideration.
Christian W. Bauer   +2 more
doaj   +1 more source

Factorization and resummation for jet broadening [PDF]

open access: yesPhysics Letters B, 2011
15 pages, 4 ...
Becher Thomas   +2 more
openaire   +5 more sources

Bayesian inverse ensemble forecasting for COVID‐19

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

Small-x phenomenology at the LHC and beyond: HELL 3.0 and the case of the Higgs cross section

open access: yesEuropean Physical Journal C: Particles and Fields, 2018
Small-x resummation has been proven recently to be a crucial ingredient for describing small-x HERA data, and the inclusion of small-x resummation in parton distribution function (PDF) determination has a sizeable effect on the PDFs even at the ...
Marco Bonvini
doaj   +1 more source

Modified F‐tests for assessing tree radial growth under linear‐circular regression models with correlated errors: A comprehensive toolbox rooted in G. E. P. Box's theorems

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Annual tree growth is a complex biological process. Modelling radial growth in the trunk by linear‐circular regression with one mode and correlated errors has allowed the definition and assessment of a preferred direction for 1 and 2 years. Here, modified F$$ F $$‐tests are presented for 3 years, 1 mode/year; 1 year, 2 modes for possible main ...
Pierre Dutilleul   +2 more
wiley   +1 more source

Resummation in hot field theories [PDF]

open access: yesAnnals of Physics, 2005
82 pages, 20 figures; v2 - typos corrected, references ...
Andersen, J.O., Strickland, M.
openaire   +3 more sources

Jackknife bias‐corrected variance estimation for the generalized regression estimator

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley   +1 more source

A partial envelope approach for modelling multivariate spatial‐temporal data

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja   +3 more
wiley   +1 more source

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