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Register a new userStable algorithm for event detection in event-driven particle dynamics: logical states
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Following the recent development of a stable event-detection algorithm for hard-sphere systems, the implications of more complex interaction models are examined. The relative location of particles leads to ambiguity when it is used to determine the interaction state of a particle in stepped potentials, such as the square-well model. To correctly predict the next event in these systems, the concept of an additional state that is tracked separately from the particle position is introduced and integrated into the stable algorithm for event detection.
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This work presents novel discrete event-based simulation algorithms based on the Quantized State System (QSS) numerical methods. QSS provides attractive features for particle transportation processes, in particular a very efficient handling of discontinuities in the simulation of continuous systems. We focus on High Energy Physics (HEP) particle tracking applications that typically rely on discrete time-based methods, and study the advantages of adopting a discrete event-based numerical approach that resolves efficiently the crossing of geometry boundaries by a traveling particle. For this purpose we follow two complementary strategies. First, a new co-simulation technique connects the Geant4 simulation toolkit with a standalone QSS solver. Second, a new native QSS numerical stepper is embedded into Geant4. We compare both approaches against the latest Geant4 default steppers in different HEP setups, including a complex real scenario (the CMS particle detector at CERN). Our techniques achieve relevant simulation speedups in a wide range of scenarios, particularly when the intensity of discrete-event handling dominates performance in the solving of the continuous laws of particle motion.
A novel Stochastic Event-Driven Molecular Dynamics (SEDMD) algorithm is developed for the simulation of polymer chains suspended in a solvent. The polymers are represented as chains of hard spheres tethered by square wells and interact with the solvent particles with hard core potentials. The algorithm uses Event-Driven Molecular Dynamics (EDMD) for the simulation of the polymer chain and the interactions between the chain beads and the surrounding solvent particles. The interactions between the solvent particles themselves are not treated deterministically as in event-driven algorithms, rather, the momentum and energy exchange in the solvent is determined stochastically using the Direct Simulation Monte Carlo (DSMC) method. The coupling between the solvent and the solute is consistently represented at the particle level, however, unlike full MD simulations of both the solvent and the solute, the spatial structure of the solvent is ignored. The algorithm is described in detail and applied to the study of the dynamics of a polymer chain tethered to a hard wall subjected to uniform shear. The algorithm closely reproduces full MD simulations with two orders of magnitude greater efficiency. Results do not confirm the existence of periodic (cycling) motion of the polymer chain.
Monte Carlo event generators (MCEGs) are the indispensable workhorses of particle physics, bridging the gap between theoretical ideas and first-principles calculations on the one hand, and the complex detector signatures and data of the experimental community on the other hand. All collider physics experiments are dependent on simulated events by MCEG codes such as Herwig, Pythia, Sherpa, POWHEG, and MG5_aMC@NLO to design and tune their detectors and analysis strategies. The development of MCEGs is overwhelmingly driven by a vibrant community of academics at European Universities, who also train the next generations of particle phenomenologists. The new challenges posed by possible future collider-based experiments and the fact that the first analyses at Run II of the LHC are now frequently limited by theory uncertainties urge the community to invest into further theoretical and technical improvements of these essential tools. In this short contribution to the European Strategy Update, we briefly review the state of the art, and the further developments that will be needed to meet the challenges of the next generation.
A Monte Carlo study of identified particle ratio fluctuations at LHC energies is carried out in the frame work of hij model using the fluctuation variable $ u_{dyn}$. The simulated events for Pb-Pb collisions at $sqrt{s}_{NN}$ = 2.76 and 5.02 TeV and Xe-Xe collisions at $sqrt{s}_{NN}$ = 5.44 TeV are analyzed. From this study, it is observed that the values of $[pi,K]$, $[p,K]$ and $[pi,p]$ follow the similar trends of energy dependence as observed in the most central collision data by NA49, STAR and ALICE experiments. It is also observed that $ u_{dyn}$ for all the three combinations of particles for semi-central and central collisions, the model predicted values of $ u_{dyn}[A,B]$ for Pb-Pb collisions at $sqrt{s}_{NN}$ = 2.76 TeV agree fairly well with those observed in ALICE experiment. For peripheral collisions, however, the model predicted values of $ u_{dyn}[pi,K]$ are somewhat smaller, whereas for $[p,K]$ and $[pi,p]$ it predicts larger values as compared to the corresponding experimental values. The possible reasons for the observed differences are discussed. The $ u_{dyn}$ values scaled with charged particle density when plotted against $langle$N$_{part}$$rangle$, exhibit a flat behaviour, as expected from the independent particle emission sources. For $[p,K]$ and $[pi,p]$ combinations, a departure from the flat trend is, however, observed in central collisions in the case of low p$_{T}$ window when effect of jet quenching or resonances are considered. Furthermore, the study of $ u_{dyn}[A,B]$ dependence on particle density for various collision systems (including proton-proton collisions) suggests that at LHC energies $ u_{dyn}$ values for a given particle pair is simply a function of charged particle density, irrespective of system size, beam energy and collision centrality.
The dynamics of dissipative soft-sphere gases obeys Newtons equation of motion which are commonly solved numerically by (force-based) Molecular Dynamics schemes. With the assumption of instantaneous, pairwise collisions, the simulation can be accelerated considerably using event-driven Molecular Dynamics, where the coefficient of restitution is derived from the interaction force between particles. Recently it was shown, however, that this approach may fail dramatically, that is, the obtained trajectories deviate significantly from the ones predicted by Newtons equations. In this paper, we generalize the concept of the coefficient of restitution and derive a numerical scheme which, in the case of dilute systems and frictionless interaction, allows us to perform highly efficient event-driven Molecular Dynamics simulations even for non-instantaneous collisions. We show that the particle trajectories predicted by the new scheme agree perfectly with the corresponding (force-based) Molecular Dynamics, except for a short transient period whose duration corresponds to the duration of the contact. Thus, the new algorithm solves Newtons equations of motion like force-based MD while preserving the advantages of event-driven simulations.
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