Virtual Monte Carlo Research Articles

New Developments in the VMC Project

Virtual Monte Carlo (VMC) provides a unified interface to different detector simulation transport engines such as GEANT3 and GEANT4. Since recently all the VMC packages (the VMC core library, also included in ROOT, and the GEANT3 and GEANT4 VMC) are distributed via the VMC Project GitHub organization. In addition to these VMC related packages, the VMC project also includes the Virtual Geometry Model (VGM), which is optionally used in GEANT4 VMC for conversion between GEANT4 and ROOT TGeo geometry models.In this contribution we will present the new organization of the VMC project at GitHub and new developments in the VMC interfaces and the VMC packages. We will cover the introduction of the sensitive detector interface in the VMC core and both GEANT3 and GEANT4 VMC and the new GEANT4-related developments.GEANT4 VMC 3.0 with the integration of multithreading processing was presented at CHEP in 2015. In this presentation we will report on new features included since this version: the improved support for magnetic fields, the integration of fast simulation, Garfield physics, GEANT4 transition radiation and monopole physics. Five new VMC examples demonstrating these new features, and serving also for tests, will be also discussed. Finally we will mention the work towards the code quality and improvements in testing, documentation and automated code formatting.

Using multiple engines in the Virtual Monte Carlo package

The Virtual Monte Carlo (VMC) package provides a unified interface to different detector simulation transport engines such as GEANT3 and GEANT4. It has been in production use in various experiments but so far the simulation of one event was restricted to the usage of a single chosen engine. We introduce here the possibility to mix multiple engines within the simulation of a single event. Depending on user conditions the simulation is partitioned among the chosen engines, for instance to profit from each of their advantages or specific capabilities. Such conditions can depend on phase space, geometry, particle type or an arbitrary combination. As a main achievement, this development allows for the implementation of fast simulation kernels at the VMC level which can be used stand-alone or together with full simulation engines. This capability is crucial to cope with largely increasing data expected in future LHC runs.

FairRoot and ALICE O2 Multithreading Simulation

To address the challenges of the major upgrade of the experiment, the ALICE simulations must be able to make efficient use of computing and opportunistic supercomputing resources available on the GRID. The Geant4 transport package, the performance of which has been demonstrated in a hybrid multithreading (MT) and multiprocessing (MPI) environment with up to 1/4 million threads, is therefore of a particular interest. The O2 simulation framework is based on FairRoot, which itself is based on the Virtual Monte Carlo (VMC). The integration of multithreading into the VMC design and its impact on the Geant4 VMC were presented at CHEP 2014. Geant4 VMC multithreading and the scaling behaviour of the computing time with the number of cores have then been tested using a simplified but realistic multithreaded simulation application. The focus was then put on the integration of multithreading in FairRoot classes as the necessary step towards multithreading in the FairRoot-based experimental frameworks. The new O2 framework is the first one of which the migration to multithreading is achieved for all actually included detectors. In this paper we present the progress with the integration of multithreading in FairRoot classes, the work for thread-safety in the O2 simulation classes and the experience with the integration of the multithreading mode in testing. We will also discuss plans for the further developments.

A scalable and asynchronous detector simulation system based on ALFA

In the context of the common online-offline computing infrastructure for Run3 (ALICE-O2), ALICE is reorganizing its detector simulation software to be based on FairRoot, offering a common toolkit to implement simulation based on the Virtual-Monte-Carlo (VMC) scheme. Recently, FairRoot has been augmented by ALFA, a software framework developed in collaboration between ALICE and FAIR, offering portable building blocks to construct message-based and loosely-coupled multiprocessing systems. We will report here on the implementation of a scalable and asynchronous de-tector simulation system which is based on ALFA. The system offers paral-lelization at the primary-track level, going beyond the usual inter-event parallelism of Geant4-MT, and the possibility to asynchronously and simultaneously process simulation data for the purpose of digitization and clusterization. Core advantages of our implementation are an ideal reduction of the processing time per event as well as a reduction of the memory footprint, allowing us to make significantly better use of opportunistic resources, such as HPC backfills. Moreover, the track-level parallelism opens up the interesting possibility to use different simulation engines (such as Geant4 and Fluka) concurrently, based on simple selection filters on the primary particles. The integration of fast MC processes, such as machine learning kernels running on a dedicated GPU, are a natural extension to the system.

Geant4 VMC 3.0

Virtual Monte Carlo (VMC) [1] provides an abstract interface into Monte Carlo transport codes. A user VMC based application, independent from the specific Monte Carlo codes, can be then run with any of the supported simulation programs. Developed by the ALICE Offline Project and further included in ROOT [2], the interface and implementations have reached stability during the last decade and have become a foundation for other detector simulation frameworks, the FAIR facility experiments framework being among the first and largest.Geant4 VMC [3], which provides the implementation of the VMC interface for Geant4 [4], is in continuous maintenance and development, driven by the evolution of Geant4 on one side and requirements from users on the other side. Besides the implementation of the VMC interface, Geant4 VMC also provides a set of examples that demonstrate the use of VMC to new users and also serve for testing purposes. Since major release 2.0, it includes the G4Root navigator package, which implements an interface that allows one to run a Geant4 simulation using a ROOT geometry.The release of Geant4 version 10.00 with the integration of multithreading processing has triggered the development of the next major version of Geant4 VMC (version 3.0), which was released in November 2014. A beta version, available for user testing since March, has helped its consolidation and improvement. We will review the new capabilities introduced in this major version, in particular the integration of multithreading into the VMC design, its impact on the Geant4 VMC and G4Root packages, and the introduction of a new package, MTRoot, providing utility functions for ROOT parallel output in independent files with necessary additions for thread-safety. Migration of user applications to multithreading that preserves the ease of use of VMC will be also discussed. We will also report on the introduction of a new CMake [5] based build system, the migration to ROOT major release 6 and the improvement of the testing suites.

The Geant4 Virtual Monte Carlo

The Virtual Monte Carlo (VMC) [1] provides the abstract interface to the Monte Carlo transport codes: GEANT 3.21 [2], Geant4 [3], and FLUKA [4]. The user VMC based application, independent from the specific Monte Carlo codes, can be then run with all supported simulation programs. VMC has been developed by the ALICE Offline Project and it has drawn attention in other experimental frameworks.Since its first release in 2002, the implementation of the VMC for Geant4 (Geant4 VMC) has been continuously maintained and developed, driven by the evolution of Geant4 on one side and the requirements from users on the other side. In this paper we report on new features in this tool, we present its development multi-threading version based on the Geant4 MT prototype [5] as well as the time comparisons of equivalent native Geant4 and VMC test applications.

The PandaRoot framework for simulation, reconstruction and analysis

The PANDA experiment at the future facility FAIR will study anti-proton proton and anti-proton nucleus collisions in a beam momentum range from 2 GeV/c up to 15 GeV/c. The PandaRoot framework is part of the FairRoot project, a common software framework for the future FAIR experiments, and is currently used to simulate detector performances and to evaluate different detector concepts. It is based on the packages ROOT and Virtual MonteCarlo with Geant3 and Geant4. Different reconstruction algorithms for tracking and particle identification are under development and optimization, in order to achieve the performance requirements of the experiment. In the central tracker a first track fit is performed using a conformal map transformation based on a helix assumption, then the track is used as input for a Kalman Filter (package genfit), using GEANE as track follower. The track is then correlated to the pid detectors (e.g. Cerenkov detectors, EM Calorimeter or Muon Chambers) to evaluate a global particle identification probability, using a Bayesian approach or multivariate methods. Further implemented packages in PandaRoot are: the analysis tools framework Rho, the kinematic fitter package for vertex and mass constraint fits, and a fast simulation code based upon parametrized detector responses. PandaRoot was also tested on an Alien-based GRID infrastructure. The contribution will report about the status of PandaRoot and show some example results for analysis of physics benchmark channels.

The Geant4 virtual Monte Carlo

The Virtual Monte Carlo (VMC) [1] provides an abstract interface into the Monte Carlo transport codes: Geant3, Geant4 and Fluka. The user VMC based application, independent from the specific Monte Carlo codes, can then be run with all three simulation programs. The VMC has been developed by the ALICE Offline Project and since then it has been adopted in other experimental frameworks.Since its first release in 2002, the implementation of the VMC for Geant4 (Geant4 VMC) [2] is in continuous maintenance and development, mostly driven by the requirements from new, non ALICE, users. In this presentation we will give an overview and the present status of this interface. We will report on new features, such as support for user defined Geant4 classes (the physics list, detector construction class) or support for Root TGeo geometry definition and G4Root navigation. We will also discuss the aspects specific to Geant4 and comment on the strong and weak points of the VMC approach.

Use of GEANE for tracking in virtual Monte Carlo

The concept of Virtual Monte Carlo (VMC) allows to use different Monte Carlo programs to simulate particle physics detectors without changing the geometry definition and the detector response simulation. In this context, to study the reconstruction capabilities of a detector, the availability of a tool to extrapolate the track parameters and their associated errors due to magnetic field, straggling in energy loss and Coulomb multiple scattering plays a central role: GEANE is an old program written in Fortran 15 years ago that performs this task through dense materials and that is still succesfully used by many modern experiments in its native form. Among its features there is the capability to read directly the geometry and the magnetic field map from the simulation and to use different track representations. In this work we have ‘rediscovered’ GEANE in the context of the Virtual Monte Carlo: we will show how GEANE has been integrated in the FairROOT framework, firmly based on the VMC, by keeping the old features in the new ROOT geometry modeler. Moreover new features have been added to GEANE that allow one to use it also for low density materials, i.e. for gaseous detectors, and preliminary results will be shown and discussed. The tool is now used by the PANDA and CBM collaborations at GSI as the first step for the global reconstruction algorithms, based on a Kalman filter which is currently under development.

An interface for GEANT4 simulation using ROOT geometry navigation

The ROOT geometry modeller (TGeo) offers powerful tools for detector geometry description. The package provides several functionalities like: navigation, geometry checking, enhanced visualization, geometry editing GUI and many others, using ROOT I/O. A new interface module g4root was recently developed to take advantage of ROOT geometry navigation optimizations in the context of GEANT4 simulation. The interface can be used either by native GEANT4-based simulation applications or in the more general context of the Virtual Monte Carlo (VMC) framework developed by ALICE offline and ROOT teams. The latter allows running GEANT3, GEANT4 and FLUKA simulations without changing either the geometry description or the user code. The interface was tested and stressed in the context of ALICE simulation framework. A description of the interface, its usage as well as recent results in terms of reliability and performance will be presented. Some benchmarks will be compared for ROOT-TGeo or GEANT4 based navigation.