scholarly journals Next-to-leading-order QCD corrections and parton-shower effects for weakino+squark production at the LHC

2021 ◽  
Vol 2021 (12) ◽  
Author(s):  
Julien Baglio ◽  
Gabriele Coniglio ◽  
Barbara Jäger ◽  
Michael Spira
Keyword(s):  
Production Process ◽  
Parton Shower ◽  
Leading Order ◽  
Hadron Colliders ◽  
Perturbative Calculations ◽  
The Real ◽  
Decay Products ◽  
Production Processes ◽  
Fixed Order ◽  
Real Emission

Abstract We present a calculation of the next-to-leading order QCD corrections to weakino+squark production processes at hadron colliders and their implementation in the framework of the POWHEG-BOX, a tool for the matching of fixed-order perturbative calculations with parton-shower programs. Particular care is taken in the subtraction of on-shell resonances in the real-emission corrections that have to be assigned to production processes of a different type. In order to illustrate the capabilities of our code, representative results are shown for selected SUSY parameter points in the pMSSM11. The perturbative stability of the calculation is assessed for the pp →$$ {\tilde{\upchi}}_1^0{\tilde{d}}_L $$ χ ˜ 1 0 d ˜ L process. For the squark+chargino production process pp →$$ {\upchi}_1^{-}{\tilde{u}}_L $$ χ 1 − u ˜ L distributions of the chargino’s decay products are provided with the help of the decay feature of PYTHIA 8.

scholarly journals Fixed-order and merged parton-shower predictions for WW and WWj production at the LHC including NLO QCD and EW corrections

2020 ◽  
Vol 2020 (10) ◽  
Author(s):  
Stephan Bräuer ◽  
Ansgar Denner ◽  
Mathieu Pellen ◽  
Marek Schönherr ◽  
Steffen Schumann
Keyword(s):  
Cross Sections ◽  
Parton Shower ◽  
Higher Order ◽  
Order Effects ◽  
Leading Order ◽  
Combined Analysis ◽  
Fixed Order ◽  
Higher Order Effects ◽  
Inclusive Sample ◽  
Electroweak Corrections

Abstract First, we present a combined analysis of pp $$ \to {\mu}^{+}{v}_{\mu }{\mathrm{e}}^{-}{\overline{v}}_{\mathrm{e}} $$ → μ + v μ e − v ¯ e and pp $$ \to {\mu}^{+}{v}_{\mu }{\mathrm{e}}^{-}{\overline{v}}_{\mathrm{e}}\mathrm{j} $$ → μ + v μ e − v ¯ e j at next-to-leading order, including both QCD and electroweak corrections. Second, we provide all-order predictions for pp $$ \to {\mu}^{+}{v}_{\mu }{\mathrm{e}}^{-}{\overline{v}}_{\mathrm{e}}+ $$ → μ + v μ e − v ¯ e + jets using merged parton-shower simulations that also include approximate EW effects. A fully inclusive sample for WW production is compared to the fixed-order computations for exclusive zero- and one-jet selections. The various higher-order effects are studied in detail at the level of cross sections and differential distributions for realistic experimental set-ups. Our study confirms that merged predictions are significantly more stable than the fixed-order ones in particular regarding ratios between the two processes.

scholarly journals A Positive Resampler for Monte Carlo events with negative weights

2020 ◽  
Vol 80 (11) ◽  
Author(s):  
Jeppe R. Andersen ◽  
Christian Gütschow ◽  
Andreas Maier ◽  
Stefan Prestel
Keyword(s):  
Parton Shower ◽  
State Of The Art ◽  
General Purpose ◽  
Leading Order ◽  
Hadron Colliders ◽  
Correct Description ◽  
Multiple Jets ◽  
Positive Weights ◽  
Sizeable Number ◽  
Processing Steps

AbstractWe propose the Positive Resampler to solve the problem associated with event samples from state-of-the-art predictions for scattering processes at hadron colliders typically involving a sizeable number of events contributing with negative weight. The proposed method guarantees positive weights for all physical distributions, and a correct description of all observables. A desirable side product of the method is the possibility to reduce the size of event samples produced by General Purpose Event Generators, thus lowering the resource demands for subsequent computing-intensive event processing steps. We demonstrate the viability and efficiency of our approach by considering its application to a next-to-leading order + parton shower merged prediction for the production of a W boson in association with multiple jets.

scholarly journals $${t {{\bar{t}}}H}$$ production at NNLO: the flavour off-diagonal channels

2021 ◽  
Vol 81 (6) ◽  
Author(s):  
Stefano Catani ◽  
Ignacio Fabre ◽  
Massimiliano Grazzini ◽  
Stefan Kallweit
Keyword(s):  
Transverse Momentum ◽  
Perturbative Expansion ◽  
Complete Agreement ◽  
Leading Order ◽  
Hadron Colliders ◽  
Fully Differential ◽  
Associated Production ◽  
Fixed Order ◽  
Heavy Quark Pair ◽  
First Time

AbstractWe consider QCD radiative corrections to the associated production of a heavy-quark pair ($$Q{{\bar{Q}}}$$ Q Q ¯ ) with a generic colourless system F at hadron colliders. We discuss the resummation formalism for the production of the $$Q{{\bar{Q}}}F$$ Q Q ¯ F system at small values of its total transverse momentum $$q_T$$ q T . We present the results of the corresponding resummation coefficients at next-to-leading and, partly, next-to-next-to-leading order. The perturbative expansion of the resummation formula leads to the explicit ingredients that can be used to apply the $$q_T$$ q T subtraction formalism to fixed-order calculations for this class of processes. We use the $$q_T$$ q T subtraction formalism to perform a fully differential perturbative computation for the production of a top-antitop quark pair and a Higgs boson. At next-to-leading order we compare our results with those obtained with established subtraction methods and we find complete agreement. We present, for the first time, the results for the flavour off-diagonal partonic channels at the next-to-next-to-leading order.

scholarly journals Jet angularities in Z+jet production at the LHC

2021 ◽  
Vol 2021 (7) ◽  
Author(s):  
Simone Caletti ◽  
Oleh Fedkevych ◽  
Simone Marzani ◽  
Daniel Reichelt ◽  
Steffen Schumann ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Transverse Momentum ◽  
Parton Shower ◽  
Phenomenological Study ◽  
State Of The Art ◽  
Leading Order ◽  
Associate Production ◽  
Fixed Order ◽  
The Impact ◽  
Logarithmic Accuracy

Abstract We present a phenomenological study of angularities measured on the highest transverse-momentum jet in LHC events that feature the associate production of a Z boson and one or more jets. In particular, we study angularity distributions that are measured on jets with and without the SoftDrop grooming procedure. We begin our analysis exploiting state-of-the-art Monte Carlo parton shower simulations and we quantitatively assess the impact of next-to-leading order (NLO) matching and merging procedures. We then move to analytic resummation and arrive at an all-order expression that features the resummation of large logarithms at next-to-leading logarithmic accuracy (NLL) and is matched to the exact NLO result. Our predictions include the effect of soft emissions at large angles, treated as a power expansion in the jet radius, and non-global logarithms. Furthermore, matching to fixed-order is performed in such a way to ensure what is usually referred to as NLL′ accuracy. Our results account for realistic experimental cuts and can be easily compared to upcoming measurements of jet angularities from the LHC collaborations.

scholarly journals MiNNLO$$_{\text {PS}}$$: optimizing $$2\rightarrow 1$$ hadronic processes

2020 ◽  
Vol 80 (11) ◽  
Author(s):  
Pier Francesco Monni ◽  
Emanuele Re ◽  
Marius Wiesemann
Keyword(s):  
Parton Shower ◽  
Neutral Current ◽  
Leading Order ◽  
Fixed Order ◽  
Formula Method

AbstractWe consider the MiNNLO$$_\mathrm{PS}$$ PS method to consistently combine next-to-next-to-leading order (NNLO) QCD calculations with parton-shower simulations. We identify the main sources of differences between MiNNLO$$_\mathrm{PS}$$ PS and fixed-order NNLO predictions for inclusive observables due to corrections beyond NNLO accuracy and present simple prescriptions to either reduce or remove them. Refined predictions are presented for Higgs, charged- and neutral-current Drell Yan production. The agreement with fixed-order NNLO calculations is considerably improved for inclusive observables and scale uncertainties are reduced. The codes are released within the POWHEG-BOX.

scholarly journals Addendum to: A theoretical study of top-mass measurements at the LHC using NLO+PS generators of increasing accuracy

2019 ◽  
Vol 79 (10) ◽  
Author(s):  
Silvia Ferrario Ravasio ◽  
Tomáš Ježo ◽  
Paolo Nason ◽  
Carlo Oleari
Keyword(s):  
Parton Shower ◽  
Theoretical Study ◽  
Leading Order ◽  
Hadron Colliders ◽  
Mass Measurements ◽  
Link Type ◽  
The Impact ◽  
Top Mass ◽  
C 78

Abstract This paper is a follow-up of Ref. Ferrario Ravasio et al. (Eur Phys J C 78:458, 2018. arXiv:1801.03944), where we studied the impact of next-to-leading order calculations merged with parton shower generators (NLO+PS) of increasing accuracy in the extraction of the top mass at hadron colliders. Here we examined results obtained with the older (fortran-based) shower generators and . Our findings are in line with what we found in Ref. Ferrario Ravasio et al. (2018) with the new, c++-based, generators and .

МODERNIZATION TECHNOLOGY REPAIRING ACENTRIFUGAL WATER PUMP

2018 ◽  
pp. 48-51
Author(s):  
Sh.U. Yuldashev ◽  
D.T. Abdumuminova
Keyword(s):  
Production Process ◽  
Technological Process ◽  
Energy Efficient ◽  
Technical Support ◽  
Ultrasonic Processing ◽  
Water Pump ◽  
The Real ◽  
Technological Processes ◽  
Efficient Management ◽  
Pump Shaft

The article provides an overview of the principle of the pump D630-90, as well as methods for studying the real conditions of technical support to improve maintainability and optimize technological processes and systems. A technological process for the restoration of the shaft of a centrifugal water pump has been developed and an algorithm for managing it has been proposed, on the basis of which the system for energy-efficient management of the recovery area has been implemented. Also in the article some questions of use, metal-filled compound SK812, and also application of ultrasonic processing of a surface of a shaft of the centrifugal water pump of mark D630-90 are mentioned and considered. The developed technological process of pump shaft restoration showed that it is characterized by simplicity, it fits well into the production process of repair and can be widely used in repair shops.

scholarly journals Application of the Deep CNN-Based Method in Industrial System for Wire Marking Identification

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3659
Author(s):  
Andrzej Szajna ◽  
Mariusz Kostrzewski ◽  
Krzysztof Ciebiera ◽  
Roman Stryjski ◽  
Waldemar Woźniak
Keyword(s):  
Production Process ◽  
Process Development ◽  
Process Time ◽  
Industrial System ◽  
Assembly Process ◽  
Production Environment ◽  
Deep Convolutional Neural Networks ◽  
Control Cabinet ◽  
Production Processes ◽  
The Wire

Industry 4.0, a term invented by Wolfgang Wahlster in Germany, is celebrating its 10th anniversary in 2021. Still, the digitalization of the production environment is one of the hottest topics in the computer science departments at universities and companies. Optimization of production processes or redefinition of the production concepts is meaningful in light of the current industrial and research agendas. Both the mentioned optimization and redefinition are considered in numerous subtopics and technologies. One of the most significant topics in these areas is the newest findings and applications of artificial intelligence (AI)—machine learning (ML) and deep convolutional neural networks (DCNNs). The authors invented a method and device that supports the wiring assembly in the control cabinet production process, namely, the Wire Label Reader (WLR) industrial system. The implementation of this device was a big technical challenge. It required very advanced IT technologies, ML, image recognition, and DCNN as well. This paper focuses on an in-depth description of the underlying methodology of this device, its construction, and foremostly, the assembly industrial processes, through which this device is implemented. It was significant for the authors to validate the usability of the device within mentioned production processes and to express both advantages and challenges connected to such assembly process development. The authors noted that in-depth studies connected to the effects of AI applications in the presented area are sparse. Further, the idea of the WLR device is presented while also including results of DCNN training (with recognition results of 99.7% although challenging conditions), the device implementation in the wire assembly production process, and its users’ opinions. The authors have analyzed how the WLR affects assembly process time and energy consumption, and accordingly, the advantages and challenges of the device. Among the most impressive results of the WLR implementation in the assembly process one can be mentioned—the device ensures significant process time reduction regardless of the number of characters printed on a wire.

scholarly journals Forward dijets in proton-nucleus collisions at next-to-leading order: the real corrections

2021 ◽  
Vol 2021 (3) ◽  
Author(s):  
Edmond Iancu ◽  
Yair Mulian
Keyword(s):  
Cross Section ◽  
Soft Gluon ◽  
Effective Theory ◽  
Dglap Evolution ◽  
Leading Order ◽  
Final State ◽  
Dijet Production ◽  
The Real ◽  
First Case ◽  
Subsequent Publication

Abstract Using the CGC effective theory together with the hybrid factorisation, we study forward dijet production in proton-nucleus collisions beyond leading order. In this paper, we compute the “real” next-to-leading order (NLO) corrections, i.e. the radiative corrections associated with a three-parton final state, out of which only two are being measured. To that aim, we start by revisiting our previous results for the three-parton cross-section presented in [1]. After some reshuffling of terms, we deduce new expressions for these results, which not only look considerably simpler, but are also physically more transparent. We also correct several errors in this process. The real NLO corrections to inclusive dijet production are then obtained by integrating out the kinematics of any of the three final partons. We explicitly work out the interesting limits where the unmeasured parton is either a soft gluon, or the product of a collinear splitting. We find the expected results in both limits: the B-JIMWLK evolution of the leading-order dijet cross-section in the first case (soft gluon) and, respectively, the DGLAP evolution of the initial and final states in the second case (collinear splitting). The “virtual” NLO corrections to dijet production will be presented in a subsequent publication.

scholarly journals The real-time big data processing method based on LSTM or GRU for the smart job shop production process

2020 ◽  
Vol 14 ◽  
pp. 174830262096239 ◽  
Author(s):  
Chuang Wang ◽  
Wenbo Du ◽  
Zhixiang Zhu ◽  
Zhifeng Yue
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Production Process ◽  
Real Time ◽  
Job Shop ◽  
Production Data ◽  
Time Data ◽  
Big Data Processing ◽  
The Real ◽  
Data Processing Method

With the wide application of intelligent sensors and internet of things (IoT) in the smart job shop, a large number of real-time production data is collected. Accurate analysis of the collected data can help producers to make effective decisions. Compared with the traditional data processing methods, artificial intelligence, as the main big data analysis method, is more and more applied to the manufacturing industry. However, the ability of different AI models to process real-time data of smart job shop production is also different. Based on this, a real-time big data processing method for the job shop production process based on Long Short-Term Memory (LSTM) and Gate Recurrent Unit (GRU) is proposed. This method uses the historical production data extracted by the IoT job shop as the original data set, and after data preprocessing, uses the LSTM and GRU model to train and predict the real-time data of the job shop. Through the description and implementation of the model, it is compared with KNN, DT and traditional neural network model. The results show that in the real-time big data processing of production process, the performance of the LSTM and GRU models is superior to the traditional neural network, K nearest neighbor (KNN), decision tree (DT). When the performance is similar to LSTM, the training time of GRU is much lower than LSTM model.

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