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Journal articles on the topic 'Monte Carlo event generators'

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Published: 4 June 2021
Last updated: 11 February 2022

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1

Gieseke, Stefan. "Monte Carlo Event Generators." Nuclear Physics B - Proceedings Supplements 222-224 (January 2012): 174–86. http://dx.doi.org/10.1016/j.nuclphysbps.2012.03.018.

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2

Webber, Bryan. "Parton shower Monte Carlo event generators." Scholarpedia 6, no. 12 (2011): 10662. http://dx.doi.org/10.4249/scholarpedia.10662.

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3

Collins, John C. "Spin correlations in Monte Carlo event generators." Nuclear Physics B 304 (January 1988): 794–804. http://dx.doi.org/10.1016/0550-3213(88)90654-2.

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4

Schönherr, Marek. "Recent developments in Monte-Carlo Event Generators." EPJ Web of Conferences 120 (2016): 05002. http://dx.doi.org/10.1051/epjconf/201612005002.

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5

Verbytskyi, Andrii, Andy Buckley, David Grellscheid, Dima Konstantinov, James William Monk, Leif Lönnblad, Tomasz Przedzinski, and Witold Pokorski. "HepMC3 Event Record Library for Monte Carlo Event Generators." Journal of Physics: Conference Series 1525 (April 2020): 012017. http://dx.doi.org/10.1088/1742-6596/1525/1/012017.

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6

Buckley, Andy, Philip Ilten, Dmitri Konstantinov, Leif Lönnblad, James Monk, Witold Pokorski, Tomasz Przedzinski, and Andrii Verbytskyi. "The HepMC3 event record library for Monte Carlo event generators." Computer Physics Communications 260 (March 2021): 107310. http://dx.doi.org/10.1016/j.cpc.2020.107310.

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7

Collins, John C., and Xiaomin Zu. "Parton distribution functions suitable for Monte-Carlo event generators." Journal of High Energy Physics 2002, no. 06 (June 10, 2002): 018. http://dx.doi.org/10.1088/1126-6708/2002/06/018.

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8

Krishnamoorthy, Mohan, Holger Schulz, Xiangyang Ju, Wenjing Wang, Sven Leyffer, Zachary Marshall, Stephen Mrenna, Juliane Müller, and James B. Kowalkowski. "Apprentice for Event Generator Tuning." EPJ Web of Conferences 251 (2021): 03060. http://dx.doi.org/10.1051/epjconf/202125103060.

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APPRENTICE is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.
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9

Galoyan, A. S., and V. V. Uzhinsky. "Monte Carlo event generators for NICA/MPD and CBM experiments." Bulletin of the Russian Academy of Sciences: Physics 80, no. 3 (March 2016): 333–37. http://dx.doi.org/10.3103/s1062873816030138.

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10

Winter, Jan, Peter Z. Skands, and Bryan R. Webber. "Monte Carlo event generators & the top quark forward-backward asymmetry." EPJ Web of Conferences 49 (2013): 17001. http://dx.doi.org/10.1051/epjconf/20134917001.

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11

Sato, Yo, Sam Cunliffe, Frank Meier, and Anze Zupanc. "Monte Carlo matching in the Belle II software." EPJ Web of Conferences 251 (2021): 03021. http://dx.doi.org/10.1051/epjconf/202125103021.

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The Belle II experiment is an upgrade to the Belle experiment, and is located at the SuperKEKB facility in KEK, Tsukuba, Japan. The Belle II software is completely new and is used for everything from triggering data, generation of Monte Carlo events, tracking, clustering, to high-level analysis. One important feature is the matching between the combinations of reconstructed objects which form particle candidates and the underlying simulated particles from the event generators. This is used to study detector effects, analysis backgrounds, and efficiencies. This document describes the algorithm that is used by Belle II.
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12

Chekanov, S. V. "HepSim: A Repository with Predictions for High-Energy Physics Experiments." Advances in High Energy Physics 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/136093.

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A file repository for calculations of cross sections and kinematic distributions using Monte Carlo generators for high-energy collisions is discussed. The repository is used to facilitate effective preservation and archiving of data from theoretical calculations and for comparisons with experimental data. The HepSim data library is publicly accessible and includes a number of Monte Carlo event samples with Standard Model predictions for current and future experiments. The HepSim project includes a software package to automate the process of downloading and viewing online Monte Carlo event samples. Data streaming over a network for end-user analysis is discussed.
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13

Collins, John. "Subtraction method for NLO corrections in Monte-Carlo event generators for leptoproduction." Journal of High Energy Physics 2000, no. 05 (May 2, 2000): 004. http://dx.doi.org/10.1088/1126-6708/2000/05/004.

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14

SCHENKE, BJÖRN, SANGYONG JEON, and CHARLES GALE. "MONTE-CARLO SIMULATION OF HEAVY-ION COLLISIONS." International Journal of Modern Physics E 20, no. 07 (July 2011): 1588–93. http://dx.doi.org/10.1142/s0218301311019921.

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Results from the Modular Algorithm for Relativistic Treatment of heavy IoN Interactions (MARTINI) are presented. This comprehensive event generator for the hard and penetrating probes in high energy nucleus-nucleus collisions employs a time evolution model for the soft background, PYTHIA 8.1 and the McGill-AMY parton evolution scheme including radiative as well as elastic processes. It generates full event configurations in the high pT region, allowing to perform the same processing as with experimental data, such as multi-particle correlation analyses and full jet reconstruction.
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15

Montagna, Guido, Oreste Nicrosini, and Fulvio Piccinini. "NUNUGPV — A Monte Carlo event generator for events at LEP." Computer Physics Communications 98, no. 1-2 (October 1996): 206–14. http://dx.doi.org/10.1016/0010-4655(96)00081-1.

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16

JIAXIN, DU, LI NA, and LIU LIANSHOU. "ON THE RELATION BETWEEN THE WIDTH OF CHARGE BALANCE FUNCTION AND HADRONIZATION TIME IN RELATIVISTIC HEAVY ION COLLISION." International Journal of Modern Physics E 16, no. 10 (November 2007): 3355–62. http://dx.doi.org/10.1142/s0218301307009336.

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A Monte Carlo study on the charge balance function in high energy hadron-hadron and relativistic heavy ion collisions are carried out using the Monte Carlo generators PYTHIA and AMPT, respectively. A strong dependence of the width of balance function on multiplicity is found in both cases. Using the mean parton-freeze-out time of a heavy-ion-collision event as the characteristic hadronization time for the event, it is found that for a fixed multiplicity interval the width of balance function is consistent with being independent of hadronization time.
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17

TANAKA, HIDEKAZU, and TOMO MUNEHISA. "COMPARISON OF ALGORITHMS FOR SINGLET PARTON GENERATIONS IN DEEP INELASTIC SCATTERING." Modern Physics Letters A 13, no. 14 (May 10, 1998): 1085–94. http://dx.doi.org/10.1142/s0217732398001157.

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Algorithms for parton shower models are examined for singlet partons in deep inelastic scattering. We compare two different types of models: (i) based on evolution of particle number distributions as conventionally used in Monte–Carlo event generators, (ii) based on evolution of momentum distributions which has not been studied in the practical event generators. Features of these two models are qualitatively studied in order to understand the properties of these models.
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18

Jadach, S. "Foam: A general-purpose cellular Monte Carlo event generator." Computer Physics Communications 152, no. 1 (April 2003): 55–100. http://dx.doi.org/10.1016/s0010-4655(02)00755-5.

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19

Iaselli, G. "A fast Monte Carlo event generator for particle physics." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 248, no. 2-3 (August 1986): 488–90. http://dx.doi.org/10.1016/0168-9002(86)91037-5.

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20

Amoroso, Simone, Sascha Caron, Adil Jueid, Roberto Ruiz de Austri, and Peter Skands. "Estimating QCD uncertainties in Monte Carlo event generators for gamma-ray dark matter searches." Journal of Cosmology and Astroparticle Physics 2019, no. 05 (May 7, 2019): 007. http://dx.doi.org/10.1088/1475-7516/2019/05/007.

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21

Collins, John C., and Francesco Hautmann. "Soft gluons and gauge-invariant subtractions in NLO parton-shower Monte Carlo event generators." Journal of High Energy Physics 2001, no. 03 (March 12, 2001): 016. http://dx.doi.org/10.1088/1126-6708/2001/03/016.

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22

Chen, Yujun, John Collins, and Nadiya Tkachuk. "Subtraction method for NLO corrections in Monte-Carlo event generators for Z boson production." Journal of High Energy Physics 2001, no. 06 (June 6, 2001): 015. http://dx.doi.org/10.1088/1126-6708/2001/06/015.

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23

Brugger, C., S. Weithoffer, C. de Schryver, U. Wasenmüller, and N. Wehn. "On parallel random number generation for accelerating simulations of communication systems." Advances in Radio Science 12 (November 10, 2014): 75–81. http://dx.doi.org/10.5194/ars-12-75-2014.

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Abstract. Powerful compute clusters and multi-core systems have become widely available in research and industry nowadays. This boost in utilizable computational power tempts people to run compute-intensive tasks on those clusters, either for speed or accuracy reasons. Especially Monte Carlo simulations with their inherent parallelism promise very high speedups. Nevertheless, the quality of Monte Carlo simulations strongly depends on the quality of the employed random numbers. In this work we present a comprehensive analysis of state-of-the-art pseudo random number generators like the MT19937 or the WELL generator used for parallel stream generation in different settings. These random number generators can be realized in hardware as well as in software and help to accelerate the analysis (or simulation) of communications systems. We show that it is possible to generate high-quality parallel random number streams with both generators, as long as some configuration constraints are met. We furthermore depict that distributed simulations with those generator types are viable even to very high degrees of parallelism.
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24

Yevick, David. "Accelerated rare event sampling." International Journal of Modern Physics C 27, no. 04 (February 23, 2016): 1650041. http://dx.doi.org/10.1142/s0129183116500418.

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25

ALVER, BURAK. "A METHOD FOR MEASURING ELLIPTIC FLOW FLUCTUATIONS WITH THE PHOBOS DETECTOR." International Journal of Modern Physics E 16, no. 07n08 (August 2007): 1852–58. http://dx.doi.org/10.1142/s0218301307007106.

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We have performed the first measurement of elliptic flow (v2) fluctuations in nucleus-nucleus collisions. In this paper, we describe the analysis method we have developed for this measurement. In this method, v2 is determined event-by-event by a maximum likelihood fit. The non-statistical fluctuations are determined by unfolding the contribution of statistical fluctuations and detector effects using Monte Carlo simulations. Application of this method to measure dynamical fluctuations in events from a different Monte Carlo event generator is presented.
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26

Shokr, E., A. H. El-Farrash, A. De Roeck, and M. A. Mahmoud. "Study of charged-particle multiplicity fluctuations in pp collisions with Monte Carlo event generators at the LHC." International Journal of Modern Physics E 29, no. 09 (September 2020): 2050074. http://dx.doi.org/10.1142/s0218301320500743.

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Proton–Proton ([Formula: see text]) collisions at the Large Hadron Collider (LHC) are simulated in order to study events with a high local density of charged particles produced in narrow pseudorapidty windows of [Formula: see text] = 0.1, 0.2, and 0.5. The [Formula: see text] collisions are generated at center of mass energies of [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] TeV, i.e., the energies at which the LHC has operated so far, using PYTHIA and HERWIG event generators. We have also studied the average of the maximum charged-particle density versus the event multiplicity for all events, using the different pseudorapidity windows. This study prepares for the multi-particle production background expected in a future search for anomalous high-density multiplicity fluctuations using the LHC data.
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27

Borrelli, Arianna. "Program FAKE: Monte Carlo Event Generators as Tools of Theory in Early High Energy Physics." NTM Zeitschrift für Geschichte der Wissenschaften, Technik und Medizin 27, no. 4 (October 18, 2019): 479–514. http://dx.doi.org/10.1007/s00048-019-00223-w.

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28

Kawabata, S. "A new Monte Carlo event generator for high energy physics." Computer Physics Communications 41, no. 1 (July 1986): 127–53. http://dx.doi.org/10.1016/0010-4655(86)90025-1.

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29

Monk, J., and A. Pilkington. "ExHuME 1.3: A Monte Carlo event generator for exclusive diffraction." Computer Physics Communications 175, no. 3 (August 2006): 232–39. http://dx.doi.org/10.1016/j.cpc.2006.04.005.

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30

Varga, Zoltán, Róbert Vértesi, and Gergely Gábor Barnaföldi. "Multiplicity Dependence of the Jet Structures in pp Collisions at LHC Energies." Proceedings 10, no. 1 (April 4, 2019): 3. http://dx.doi.org/10.3390/proceedings2019010003.

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We study the charged event multiplicity dependence of the jet structure in pp collisions.We present evidence for jet shape modification due to multi-parton interactions using PYTHIAand HIJING++ Monte Carlo (MC) event generators as an input to our analysis. We introducea characteristic jet size measure which is independent of the choice of simulation parameters,parton distribution functions, jet reconstruction algorithms and even of the presence or absenceof multi-parton interactions. We also investigate heavy-flavor jets and show the sensitivity of themultiplicity-differential jet structure to flavor-dependent fragmentation.
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31

Shtejer, K. "Prediction of the particle production in pp collisions with the MPD detector at NICA collider." EPJ Web of Conferences 204 (2019): 07005. http://dx.doi.org/10.1051/epjconf/201920407005.

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The proton-proton collisions have been extensively used as a baseline reference for nucleus-nucleus collisions. In this work, Monte Carlo simulations of inelastic head-on pp interactions at $\sqrt s = 6 - 25\,{\rm{GeV}}$ were performed to study the possibilities of the Multi–Purpose Detector (MPD) to register data from small systems at the energy range of NICA. For that purpose the Monte Carlo models EPOS 1.99 and UrQMD 3.4 were used as event generators to analyse the charge particle yield from pp collisions in the framework of MpdRoot. The production of protons, pions and kaons from pp collisions was studied through their mean multiplicity, rapidity spectra and particle ratios as function of the collision energy. The yield of Λ hyperons was also estimated by means of pure Monte Carlo and the reconstruction of the simulated data in MPD. The comparison with recent data from NA61/SHINE experiment is presented.
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32

Ciappina, M. F., M. Schulz, and T. Kirchner. "Monte Carlo event generators in atomic physics: A new tool to tackle the few-body dynamics." Journal of Physics: Conference Series 388, no. 8 (November 5, 2012): 082016. http://dx.doi.org/10.1088/1742-6596/388/8/082016.

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33

Ciappina, M. F., T. Kirchner, and M. Schulz. "Monte Carlo event generators in atomic collisions: A new tool to tackle the few-body dynamics." Computer Physics Communications 181, no. 4 (April 2010): 813–20. http://dx.doi.org/10.1016/j.cpc.2009.12.014.

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34

Hoang, André H. "What Is the Top Quark Mass?" Annual Review of Nuclear and Particle Science 70, no. 1 (October 19, 2020): 225–55. http://dx.doi.org/10.1146/annurev-nucl-101918-023530.

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This review provides an overview of the conceptual issues regarding the interpretation of so-called direct top quark mass measurements, which are based on the kinematic reconstruction of top quark decay products at the Large Hadron Collider (LHC). These measurements quote the top mass parameter [Formula: see text] of Monte Carlo event generators with current uncertainties of around 0.5 GeV. The problem of finding a rigorous relation between [Formula: see text] and top mass renormalization schemes defined in field theory is unresolved to date and touches perturbative as well as nonperturbative aspects and the limitations of state-of-the-art Monte Carlo event generators. I review the status of LHC top mass measurements, illustrate how conceptual limitations enter the picture, and explain a controversy that has permeated the community in the context of the interpretation problem related to [Formula: see text]. I then summarize recent advances in acquiring first principles insights and outline what else has to be understood to fully resolve the issue. I conclude with recommendations on how to deal with the interpretation problem for the time being when making top mass–dependent theoretical predictions.
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35

Varga, Zoltán, Róbert Vértesi, and Gergely Gábor Barnaföldi. "Jet Structure Studies in Small Systems." Universe 5, no. 5 (May 27, 2019): 132. http://dx.doi.org/10.3390/universe5050132.

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A study investigating a possible jet shape dependence on the charged event multiplicity was performed on collision samples generated by Monte–Carlo (MC) event generators Pythia and Hijing++. We calculated the integral jet shape and found a significant modification caused by multiple-parton interactions. By interchanging and enabling different model ingredients in the simulations and analyzing the results in several p T bins and event multiplicity classes, we found a characteristic jet size measure that was independent of the chosen tunes, settings, and jet reconstruction algorithms.
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36

Caffo, M., and H. Czyż. "BHAGEN-1PH: a Monte Carlo event generator for radiative Bhabha scattering." Computer Physics Communications 100, no. 1-2 (February 1997): 99–118. http://dx.doi.org/10.1016/s0010-4655(96)00134-8.

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37

Jadach, Stanislaw, and B. F. L. Ward. "Multiphoton Monte Carlo event generator for Bhabha scattering at small angles." Physical Review D 40, no. 11 (December 1, 1989): 3582–89. http://dx.doi.org/10.1103/physrevd.40.3582.

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38

Czyż, Henryk, and Patrycja Kisza. "EKHARA 3.0: An update of the EKHARA Monte Carlo event generator." Computer Physics Communications 234 (January 2019): 245–55. http://dx.doi.org/10.1016/j.cpc.2018.07.021.

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39

ENE, Alexandru Cătălin, Alexandru JIPA, and Lavinia-Elena GIUBEGA. "Study of Monte Carlo event generators for proton-proton collisions at LHC energies in the forward region." Chinese Physics C 43, no. 8 (July 16, 2019): 083001. http://dx.doi.org/10.1088/1674-1137/43/8/083001.

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40

Jadach, Stanislaw, and B. F. L. Ward. "Exponentiation of soft photons in Monte Carlo event generators: The case of the Bonneau-Martin cross section." Physical Review D 38, no. 9 (November 1, 1988): 2897–903. http://dx.doi.org/10.1103/physrevd.38.2897.

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41

FUKS, BENJAMIN. "BEYOND THE MINIMAL SUPERSYMMETRIC STANDARD MODEL: FROM THEORY TO PHENOMENOLOGY." International Journal of Modern Physics A 27, no. 07 (March 20, 2012): 1230007. http://dx.doi.org/10.1142/s0217751x12300074.

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Thanks to the latest development in the field of Monte Carlo event generators and satellite programs allowing for a straightforward implementation of any beyond the Standard Model theory in those tools, studying the property of any softly-broken supersymmetric theory is become an easy task. We illustrate this statement in the context of two nonminimal supersymmetric theories, namely the Minimal Supersymmetric Standard Model with R-parity violation and the Minimal R-symmetric Supersymmetric Standard Model and choose to probe interaction vertices involving a nonstandard color structure and the sector of the top quark. We show how to efficiently implement these theories in the MATHEMATICA package FEYNRULES and use its interfaces to Monte Carlo tools for phenomenological studies. For the latter, we employ the latest version of the MADGRAPH program.
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42

SALAM, GAVIN P. "DEVELOPMENTS IN PERTURBATIVE QCD." International Journal of Modern Physics A 21, no. 08n09 (April 10, 2006): 1778–91. http://dx.doi.org/10.1142/s0217751x06032757.

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A brief review of key recent developments and ongoing projects in perturbative QCD theory, with emphasis on conceptual advances that have the potential for impact on LHC studies. Topics covered include: twistors and new recursive calculational techniques; automation of one-loop predictions; developments concerning NNLO calculations; the status of Monte Carlo event generators and progress in matching to fixed order; analytical resummation including the push to NNLL, automation and gap between jets processes; and progress in the understanding of saturation at small x.
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43

Zhang, Chuan Cheng, Cui Hui Yan, Sai Dai, Dan Xu, Yi Zhu, and Wei Dong. "Improved Probabilistic Load Flow Method to Consider Random Generator Outages." Advanced Materials Research 962-965 (June 2014): 2783–88. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.2783.

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In conventional cumulant method of probabilistic load flow (PLF), random generator outages are usually simulated by discrete distributions of nodal power injections, but that will lead to significant error in AC load flow model. An improved PLF method base on AC model is proposed in this paper, which considers random generator outages and loads uncertainties. Cumulant and Gram-Charlier series expansion were applied to deal with the random variations of loads, instead of convolution calculations. According to the characteristics and focused aspects of power grid, certain generators were selected to form event group of generator outages and each event was analysed by exact load flow.Then total probability theorem was introduced to obtain the probabilistic distributions of node voltages and line flows that considered random factors of loads and generators.The case study of IEEE 39-bus system shows that the random generator outages remarkably affect the probabilistic distributions of state variables. The proposed method can avoid the error caused by generator outages in conventional cumulant method. Furthermore, the result of proposed method is consistent with that of Monte Carlo simulation, while computation speed is much faster.
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44

Jadach, Stanislaw, and B. F. L. Ward. "Erratum: Exponentiation of soft photons in Monte Carlo event generators: The case of the Bonneau-Martin cross section." Physical Review D 39, no. 5 (March 1, 1989): 1472. http://dx.doi.org/10.1103/physrevd.39.1472.2.

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45

Varga, Zoltán, Róbert Vértesi, and Gergely Gábor Barnaföldi. "Modification of Jet Structure in High-Multiplicity pp Collisions due to Multiple-Parton Interactions and Observing a Multiplicity-Independent Characteristic Jet Size." Advances in High Energy Physics 2019 (March 18, 2019): 1–12. http://dx.doi.org/10.1155/2019/6731362.

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We study the multiplicity dependence of jet structures in pp collisions using Monte Carlo event generators. We give predictions for multiplicity-differential jet structures and present evidence for a nontrivial jet shape dependence on charged hadron event multiplicity that can be used as a sensitive tool to experimentally differentiate between equally well-preforming simulation tunes. We also propose a way to validate the presence and extent of effects such as multiple-parton interactions (MPI) or color reconnection (CR), based on the detection of nontrivial jet shape modification in high-multiplicity events at high pT. Using multiplicity-dependent jet structure observables in various pT windows might also help understanding the interplay between jet particles and the underlying event (UE). We introduce a multiplicity-independent characteristic jet size measure and use a simplistic model to aid its physical interpretation.
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46

Carloni Calame, Carlo M., Guido Montagna, Oreste Nicrosini, and Fulvio Piccinini. "Status of the BabaYaga event generator." EPJ Web of Conferences 218 (2019): 07004. http://dx.doi.org/10.1051/epjconf/201921807004.

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The Monte Carlo event generator BabaYaga has been developed for high precision simulation of QED processes (e+e−→ e+ e− , e+e−→ µ+µ− and e+e−→ γγ) at flavour factories, chiefly for luminometry purposes, with an estimated theoretical accuracy at the 0.1% level or better. QED radiative corrections are included by means of a Parton Shower in QED matched with exact next-to-leading order corrections to reach the required accuracy. The latter is assessed by means of consistent comparisons to independent calculations and an estimate of the size of missing higher-order corrections. The main theoretical framework is overviewed and the status of the generator is summarized.
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47

Jadach, S., B. F. L. Ward, and Z. Wa̧s. "The precision Monte Carlo event generator for two-fermion final states in collisions." Computer Physics Communications 130, no. 3 (August 2000): 260–325. http://dx.doi.org/10.1016/s0010-4655(00)00048-5.

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48

Pan, Jicai. "A Monte Carlo event generator for high energy hadron-hadron collisions - ECCO 2.0." Computer Physics Communications 78, no. 1-2 (December 1993): 190–98. http://dx.doi.org/10.1016/0010-4655(93)90154-5.

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49

Accomando, Elena, Alessandro Ballestrero, and Ezio Maina. "PHASE, a Monte Carlo event generator for six-fermion physics at the LHC." Journal of High Energy Physics 2005, no. 07 (July 8, 2005): 016. http://dx.doi.org/10.1088/1126-6708/2005/07/016.

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50

Revuelta-Acosta, Josept D., Dennis C. Flanagan, and Bernard A. Engel. "Development of a Stochastic Storm Generator Using High-Resolution Precipitation Records." Applied Engineering in Agriculture 35, no. 4 (2019): 461–73. http://dx.doi.org/10.13031/aea.13259.

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Abstract.Sophisticated field and watershed scale environmental models for runoff, erosion control, environmental, and global-change investigations require detailed continuous temporal and spatial inputs of precipitation to drive the hydrologic processes. For accurate estimates of these processes, the resolution of the input data must allow the representation of the variability of precipitation as it represents a major source of variability in the model outputs. Currently, the use of stochastic weather generators is widespread to generate continuous series of meteorological data at gauged and ungauged locations. These weather simulators are designed to replicate the statistical properties of real weather data at monthly or daily time resolutions. However, daily values of precipitation do not represent the variability of storm parameters within a day, which is assumed to significantly influence the predictions of environmental or agricultural models where processes are sensitive to sub-daily values. This research proposes a parsimonious stochastic storm generator based on 5-min time resolution and correlated non-normal Monte Carlo-based numerical simulation. The model considers correlated non-normal random rainstorm characteristics such as time between storms, duration, and amount of precipitation, as well as the storm intensity structure. The accuracy of the model was verified by comparing the generated rainfall with rainfall data from a randomly selected 5-min weather station in North Carolina. Current results have shown that the proposed storm generator can capture the essential statistical features of rainstorms as well as their patterns followed by their intensities, preserving the first four moments of monthly storm events, good annual extreme event correspondence, and the correlation structure within each storm. Finally, as the proposed model depends on statistical properties at a site, this may allow the use of the synthetic storms in ungauged locations provided relevant information from a regional analysis is available. Keywords: Monte Carlo, Stochastic storm generator, Storm distribution.
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