Monte Carlo Generator Research Articles

Comparison of Fragmentation Functions for Jets Dominated by Light Quarks and Gluons from pp and Pb+Pb Collisions in ATLAS.

Charged-particle fragmentation functions for jets azimuthally balanced by a high-transverse-momentum, prompt, isolated photon are measured in 25 pb^{-1} of pp and 0.49 nb^{-1} of Pb+Pb collision data at 5.02TeV per nucleon pair recorded with the ATLAS detector at the Large Hadron Collider. The measurements are compared to predictions of MonteCarlo generators and to measurements of inclusively selected jets. In pp collisions, a different jet fragmentation function in photon-tagged events from that in inclusive jet events arises from the difference in fragmentation between light quarks and gluons. The ratios of the fragmentation functions in Pb+Pb events to that in pp events are used to explore the parton color-charge dependence of jet quenching in the hot medium. In relatively peripheral collisions, fragmentation functions exhibit a similar modification pattern for photon-tagged and inclusive jets. However, photon-tagged jets are observed to have larger modifications than inclusive jets in central Pb+Pb events.

BSM constraints from model-independent measurements: A Contur Update

Particle-level measurements, especially of differential cross-sections, made in fiducial regions of phase-space have a high degree of model-independence and can therefore be used to give information about a wide variety of Beyond the Standard Model (BSM) physics implemented in Monte Carlo generators, using a broad range of final states. The Contur package is used to make such comparisons. We summarise a snapshot of current results for a number of BSM scenarios; a UV complete model in which the global Baryon-number minus Lepton-number symmetry is gauged; several Dark Matter simplified models, and two generic light scalar models.

Documentation of TauSpinner approach for electroweak corrections in LHC Z rightarrow ll observables

The LHC Standard Model Z-boson couplings measurements approach the LEP legacy precision. The calculations of electroweak (EW) corrections available for the Monte Carlo generators become of relevance. Predictions of Z-boson production and decay require classes of QED/EW/QCD corrections and separatly from the production process QCD dynamics. At the LEP time electroweak form-factors and Improved Born Approximation were introduced for non QED genuine weak and line-shape corrections. This formalism was well suited for observables, so-called doubly-deconvoluted the Z-pole region where initial- and final-state QED real and virtual emissions were treated separately or were integrated over. The approach was convenient for implementation into Monte Carlo programs for LEP, Belle-BaBar and other future e^+e^- colliders and for invariant mass of outgoing lepton pair from a few GeV to well above WW and even t{bar{t}} threshold. We attempt now to profit from that, for the LHC pp and 70–150 GeV window for the outgoing lepton pair invariant mass. Our technical focus is on the EW corrections for LHC Z rightarrow ell ell observables. For this purpose the TauSpinner package, for the reweighting of previously generated events, is enriched with the genuine EW corrections (QED effects subtracted) of the Dizet electroweak library, taken from the LEP era KKMC Monte Carlo. Complete genuine EW O(alpha ) weak loop corrections and dominant higher-order terms are taken into account. For the efficiency and numerical stability look-up tables are used. For LHC observables: the Z-boson line-shape, the outgoing leptons forward-backward asymmetry, the effective leptonic weak mixing angles and finally for the spherical harmonic expansion coefficients of the lepton distributions, corrections are evaluated. Simplified calculations of Effective Born of modified EW couplings are compared with of Improved Born Approximation of complete set of EW form-factors. Approach uses LEP precision tests definitions and thus offers consistency checks. The package can be useful to evaluate of observables precision limits and to determine which corrections are then important for LHC and FCC projects phenomenology.

Influence of Backside Energy Leakages from Hadronic Calorimeters on Fluctuation Measures in Relativistic Heavy-Ion Collisions

The phase diagram of the strongly interacting matter is the main research subject for different current and future experiments in high-energy physics. System size and energy scan programs aim to find a possible critical point. One of such programs was accomplished by the fixed-target NA61/SHINE experiment in 2018. It includes six beam energies and six colliding systems: p + p, Be + Be, Ar + Sc, Xe + La, Pb + Pb and p + Pb. In this study, we discuss how the efficiency of centrality selection by forward spectators influences multiplicity and fluctuation measures and how this influence depends on the size of colliding systems. We use SHIELD and EPOS Monte-Carlo (MC) generators along with the wounded nucleon model, introduce a probability to lose a forward spectator and spectator energy loss. We show that for light colliding systems such as Be or Li even a small inefficiency in centrality selection has a dramatic impact on multiplicity scaled variance. Conversely, heavy systems such as Ar + Sc are much less prone to the effect.

Study of Jet Shape Observables in Au+Au Collisions at s N N = 200 GeV with JEWEL

Nuclear–nuclear collisions at energies attainable at the large accelerators RHIC and the LHC are an ideal environment to study nuclear matter under extreme conditions of high temperature and energy density. One of the most important probes of such nuclear matter is the study of production of jets. In this article, several jet shape observables in Au+Au collisions at the center of mass energy per nucleon–nucleon pair of s N N = 200 GeV simulated in the Monte Carlo generator JEWEL are presented. Jets were reconstructed using the anti- k T algorithm and their shapes were studied as a function of the jet-resolution parameter R, transverse momentum p T and collision centrality.

Estimating QCD uncertainties in Monte Carlo event generators for gamma-ray dark matter searches

Motivated by the recent galactic center gamma-ray excess identified in the Fermi-LAT data, we perform a detailed study of QCD fragmentation uncertainties in the modeling of the energy spectra of gamma-rays from Dark-Matter (DM) annihilation. When Dark-Matter particles annihilate to coloured final states, either directly or via decays such as W(*)→ qq̄′, photons are produced from a complex sequence of shower, hadronisation and hadron decays. In phenomenological studies their energy spectra are typically computed using Monte Carlo event generators. These results have however intrinsic uncertainties due to the specific model used and the choice of model parameters, which are difficult to asses and which are typically neglected. We derive a new set of hadronisation parameters (tunes) for the PYTHIA 8.2 Monte Carlo generator from a fit to LEP and SLD data at the Z peak. For the first time we also derive a conservative set of uncertainties on the shower and hadronisation model parameters. Their impact on the gamma-ray energy spectra is evaluated and discussed for a range of DM masses and annihilation channels. The spectra and their uncertainties are also provided in tabulated form for future use. The fragmentation-parameter uncertainties may be useful for collider studies as well.

A fresh look at ALP searches in fixed target experiments

A significant number of high power proton beams are available or will go online in the near future. This provides exciting opportunities for new fixed target experiments and the search for new physics in particular. In this note we will survey these beams and consider their potential to discover new physics in the form of axion-like particles, identifying promising locations and set ups. To achieve this, we present a significantly improved calculation of the production of axion-like particles in the coherent scattering of protons on nuclei, valid for lower ALP masses and/or beam energies. We also provide a new publicly available tool for this process: the Alpaca Monte Carlo generator. This will impact ongoing and planned searches based on this process.

Impact of QCD Jets and Heavy-quark Production in Cosmic-Ray Proton Atmospheric Showers up to 1020eV

AbstractThepythia 6 Monte Carlo (MC) event generator, commonly used in collider physics, is interfaced for the first time with a fast transport simulation of a hydrogen atmosphere, with the same density as air, in order to study the properties of extended atmospheric showers (EAS) produced by cosmic-ray protons with energies–1020 eV. At variance with the hadronic MC generators (epos-lhc,qgsjet, andsibyll) commonly used in cosmic-ray physics,pythiaincludes the generation of harder hadronic jets and heavy (charm and bottom) quarks, thereby producing higher transverse momentum final particles, that could explain several anomalies observed in the data. The electromagnetic, hadronic, and muonic properties of EAS generated with various settings ofpythia 6, tuned to proton–proton data measured at the LHC, are compared to those fromepos-lhc,qgsjet 01,qgsjet-ii-04, andsibyll 2.1. Despite their different underlying parton dynamics, the characteristics of the EAS generated withpythia 6 are in between those predicted by the rest of the MC generators. The only exceptions are the muonic components at large transverse distances from the shower axis, wherepythiapredicts more activity than the rest of the models. Heavy-quark production, as implemented in this study for a hydrogen atmosphere, does not seem to play a key role in the EAS muon properties, pointing to nuclear effects as being responsible for the muon anomalies observed in the air-shower data.

Removal energies and final state interaction in lepton nucleus scattering

We investigate the binding energy parameters that should be used in modeling electron and neutrino scattering from nucleons bound in a nucleus within the framework of the impulse approximation. We discuss the relation between binding energy, missing energy, removal energy (epsilon ), spectral functions and shell model energy levels and extract updated removal energy parameters from hbox {ee}^{prime }p spectral function data. We address the difference in parameters for scattering from bound protons and neutrons. We also use inclusive e-A data to extract an empirical parameter U_{FSI}( (varvec{q}_3+varvec{k})^2) to account for the interaction of final state nucleons (FSI) with the optical potential of the nucleus. Similarly we use V_{eff} to account for the Coulomb potential of the nucleus. With three parameters epsilon , U_{FSI}( (varvec{q}_3+varvec{k})^2) and V_{eff} we can describe the energy of final state electrons for all available electron QE scattering data. The use of the updated parameters in neutrino Monte Carlo generators reduces the systematic uncertainty in the combined removal energy (with FSI corrections) from ± 20 to ± 5 MeV.

Hadronization from color interactions * * Supported in part by National Natural Science Foundation of China (11435004, 11375069), the Ministry of Science and Technology of China (2015CB56901), and the Programme of Introducing Talents of Discipline to Universities (B08033)

A quark coalescence model, based on semi-relativistic molecular dynamics with color interactions among quarks, is presented and applied to pp collisions. A phenomenological potential with two tunable parameters is introduced to describe the color interactions between quarks and antiquarks. The interactions drive the process of hadronization that finally results in different color neutral clusters, which can be identified as hadrons based on some criteria. A Monte Carlo generator PYTHIA is used to generate quarks in the initial state of hadronization, and different values of tunable parameters are used to study the final state distributions and correlations. Baryon-to-meson ratio, transverse momentum spectra, pseudorapidity distributions and forward-backward multiplicity correlations of hadrons produced in the hadronization process, obtained from this model with different parameters, are compared with those from PYTHIA.

Ensemble Bayesian forecasting system Part II: Experiments and properties

A typical deficiency of ensemble forecasts is the lack of calibration; e.g., ensemble members are under-dispersed and, consequently, probabilities estimated from them cannot be taken at their face values. Self-calibration is one of the unique theoretic properties of the Bayesian forecasting system, BFS. Its ensemble version, EBFS, inherits this property, provided the ensemble size is large enough. That requirement motivated the version with randomization, EBFSR, presented in part I. Its unique advantage is the operational feasibility of generating a hydrologic ensemble forecast of large size, M (having hundreds or even thousands of members), from a meteorologic input ensemble forecast of small size, MI (having only tens or hundreds of members): MI<M, with M=MIR, where R stands for randomization factor (R>1 and integer). This R-fold enlargement of the ensemble size is achieved through a Monte Carlo generator (sans extra runs of the hydrologic model) and, therefore, requires little extra effort or computing time. But what are the statistical implications?The objective of this part II is to identify experimentally the sampling properties of the EBFSR so that its advantage can be properly harnessed in operational forecasting. The core matter to understand and to quantify is the tradeoff between the computing efficiency and the statistical efficiency of the EBFSR. This is so because the user must specify (i) the largest acceptable sampling error [measured in terms of the average expected maximum absolute difference, E¯(MAD), between the true but unknown predictive distribution function of the forecasted variate and the empirical distribution function estimated from a sample of size m, a fraction of the ensemble size M], and (ii) the tradeoff between MI and R. Critical to deciding this tradeoff are two relationships: E¯MAD=ξ(m) and ME=τ(MP,R), where MP is the size of the input sub-ensemble with positive precipitation amounts, and ME is the effective sample size of the output sub-ensemble of size MPR. In terms of output/input ensemble sizes, the computing efficiency is M/MI=R>1, and the statistical efficiency is ME/MPR<1 because MP<ME<MPR.Based on results of large numerical experiments, general parametric forms of ξ and τ are identified, and the dependence of the parameter values is established on factors such as the forecast type (probabilistic river stage forecast, probabilistic stage transition forecast, probabilistic flood forecast), the forecast lead time, the magnitude of the precipitation input uncertainty, and the informativeness of the deterministic hydrologic model employed by the EBFSR. Finally, two algorithms are formulated to aid the user in specifying the values of M and R, such that E¯(MAD) does not exceed the largest acceptable value and that operational constraints are satisfied (e.g., constraints regarding the input ensemble size MI or the feasible number of runs of the hydrologic model).

Monte Carlo, fitting and Machine Learning for Tau leptons

Status of \tauτ lepton decay Monte Carlo generator TAUOLA, and its main recent applications are reviewed. It is underlined, that in recent efforts on development of new hadronic currents, the multi-dimensional nature of distributions of the experimental data must be taken with a great care. Studies for H \to \tau\tau ; \tau \to hadronsH→ττ;τ→hadrons indeed demonstrate that multi-dimensional nature of distributions is important and available for evaluation of observables where \tauτ leptons are used to constrain experimental data. For that part of the presentation, use of the TAUOLA program for phenomenology of HH and ZZ decays at LHC is discussed, in particular in the context of the Higgs boson parity measurements with the use of Machine Learning techniques. Some additions, relevant for QED lepton pair emission and electroweak corrections are mentioned as well.

Infrared safety of a neural-net top tagging algorithm

Neural network-based algorithms provide a promising approach to jet classification problems, such as boosted top jet tagging. To date, NN-based top taggers demonstrated excellent performance in Monte Carlo studies. In this paper, we construct a top-jet tagger based on a Convolutional Neural Network (CNN), and apply it to parton-level boosted top samples, with and without an additional gluon in the final state. We show that the jet observable defined by the CNN obeys the canonical definition of infrared safety: it is unaffected by the presence of the extra gluon, as long as it is soft or collinear with one of the quarks. Our results indicate that the CNN tagger is robust with respect to possible mis-modeling of soft and collinear final-state radiation by Monte Carlo generators.

JUNIPR: a framework for unsupervised machine learning in particle physics

In applications of machine learning to particle physics, a persistent challenge is how to go beyond discrimination to learn about the underlying physics. To this end, a powerful tool would be a framework for unsupervised learning, where the machine learns the intricate high-dimensional contours of the data upon which it is trained, without reference to pre-established labels. In order to approach such a complex task, an unsupervised network must be structured intelligently, based on a qualitative understanding of the data. In this paper, we scaffold the neural network’s architecture around a leading-order model of the physics underlying the data. In addition to making unsupervised learning tractable, this design actually alleviates existing tensions between performance and interpretability. We call the framework Junipr: “Jets from UNsupervised Interpretable PRobabilistic models”. In this approach, the set of particle momenta composing a jet are clustered into a binary tree that the neural network examines sequentially. Training is unsupervised and unrestricted: the network could decide that the data bears little correspondence to the chosen tree structure. However, when there is a correspondence, the network’s output along the tree has a direct physical interpretation. Junipr models can perform discrimination tasks, through the statistically optimal likelihood-ratio test, and they permit visualizations of discrimination power at each branching in a jet’s tree. Additionally, Junipr models provide a probability distribution from which events can be drawn, providing a data-driven Monte Carlo generator. As a third application, Junipr models can reweight events from one (e.g. simulated) data set to agree with distributions from another (e.g. experimental) data set.

Fragmentation of J/ψ in jets in pp collisions at [formula omitted

The fragmentation of jets containing a J/ψ meson is studied in s=5.02TeV pp data using an integrated luminosity of L=27.39pb−1. The fraction of the jet transverse momentum pT,jet carried by the J/ψ is measured for prompt J/ψ and J/ψ coming from b hadron decays, named nonprompt. Whereas the fragmentation function of nonprompt J/ψ is well-modeled by simulations using a Monte Carlo generator, the prompt J/ψ are found to be accompanied by a larger level of jet activity. The fraction of J/ψ mesons that are produced inside a jet is also reported, and found to be larger in data than in simulation, for both prompt and nonprompt J/ψ.

The evolution of the near-side peak in two-particle number and transverse momentum correlations in Pb–Pb collisions from ALICE

Two-particle number and transverse momentum correlations are powerful tools for studying the medium produced in heavy-ion collisions. Correlations in the angular separation of pairs of hadrons can provide information on the medium transport characteristics. In particular, the transverse momentum correlations are sensitive to momentum currents, and provide information about the system life time, the shear viscosity over entropy density ratio (η/s) and the system relaxation time (τπ). Furthermore, the interaction of the jets produced in the initial stages of a collision can be studied using number correlations, by observing the medium-induced modification of the near-side jet peak. Measurements of both sets of correlations from Pb–Pb collisions are reported as a function of centrality. Theoretical interpretations and results from Monte Carlo generators are then confronted with the experimental data.

Measurement of anisotropic flow in XeXe collisions at 5.44 TeV with the CMS experiment

New measurements of anisotropic flow in XeXe collisions at a center-of-mass energy of 5.44 TeV per nucleon pair, collected by the CMS experiment at the LHC, are presented. The ν2, ν3 and ν4 Fourier coefficients of the anisotropic azimuthal distribution are obtained employing three different analysis techniques: two-particle correlations, the scalar product method, and multiparticle cumulants, which have different sensitivities to non-flow and flow fluctuation effects. The results are shown as a function of transverse momentum (pT) for various centrality selections, and compared with corresponding results from PbPb collisions. These new measurements in a smaller nucleus-nucleus system than PbPb provide additional insights into the system-size dependence of the collective flow induced by the dominant collision geometry and its fluctuations. In particular, these results, compared to theoretical predictions and Monte Carlo generators, will provide important details on the system size dependence of the medium response in heavy ion collisions. They also offer a unique opportunity to study the onset of flow from small to large systems.

Measuring the Weizsäcker-Williams distribution of linearly polarized gluons at an electron-ion collider through dijet azimuthal asymmetries

The production of a hard dijet with small transverse momentum imbalance in semi-inclusive DIS probes the conventional and linearly polarized Weizsaecker-Williams (WW) Transverse Momentum Dependent (TMD) gluon distributions. The latter, in particular, gives rise to an azimuthal dependence of the dijet cross-section. In this paper we analyze the feasibility of a measurement of these TMDs through dijet production in DIS on a nucleus at an Electron-Ion Collider. We introduce the MCDijet Monte-Carlo generator to sample quark-antiquark dijet configurations based on leading order parton level cross-sections with WW gluon distributions that solve the non-linear small-x QCD evolution equations. These configurations are fragmented to hadrons using PYTHIA, and final state jets are reconstructed. We report on background studies and on the effect of kinematic cuts introduced to remove beam jet remnants. We estimate that with an integrated luminosity of 20 fb^{-1}/A one can determine the distribution of linearly polarized gluons with a statistical accuracy of approximately 5%.

Demonstration of MeV-scale physics in liquid argon time projection chambers using ArgoNeuT

MeV-scale energy depositions by low-energy photons produced in neutrino-argon interactions have been identified and reconstructed in ArgoNeuT liquid argon time projection chamber (LArTPC) data. ArgoNeuT data collected on the NuMI beam at Fermilab were analyzed to select isolated low-energy depositions in the TPC volume. The total number, reconstructed energies and positions of these depositions have been compared to those from simulations of neutrino-argon interactions using the FLUKA Monte Carlo generator. Measured features are consistent with energy depositions from photons produced by de-excitation of the neutrino's target nucleus and by inelastic scattering of primary neutrons produced by neutrino-argon interactions. This study represents a successful reconstruction of physics at the MeV-scale in a LArTPC, a capability of crucial importance for detection and reconstruction of supernova and solar neutrino interactions in future large LArTPCs.

Building, testing and distributing common software for the LHC experiments

Building, testing and deploying of coherent large software stacks is very challenging, in particular when they consist of the diverse set of packages required by the LHC experiments, the CERN Beams Department and data analysis services such as SWAN. These software stacks include several packages (Grid middleware, Monte Carlo generators, Machine Learning tools, Python modules) all available for a large number of compilers, operating systems and hardware architectures. To address this challenge, we developed an infrastructure around a tool called lcgcmake. Dedicated modules are responsible for building the packages, con-trolling the dependencies in a reliable and scalable way. The distribution relies on a robust and automatic system, responsible for building and testing the packages, installing them on CernVM-FS and packaging the binaries in RPMs and tarballs. This system is orchestrated through Jenkins on build machines provided by the CERN Openstack facility. The results are published through user-friendly web pages. In this paper we will present an overview of these infrastructure tools and policies. We also discuss the role of this effort within the HEP Software Foundation (HSF). Finally we will discuss the evolution of the infrastructure towards container (Docker) technologies and the future directions and challenges of the project.