The Operational Intelligence (OpInt) project is a joint effort from
various WLCG communities aimed at increasing the level of automation
in computing operations and reducing human interventions. The currently deployed systems have proven to be mature and capable of meeting the experiments goals, by allowing timely delivery of scientific results. However, a substantial number of interventions...
sPHENIX is a high energy nuclear physics experiment under construction at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The primary physics goals of sPHENIX are to measure jets, their substructure, and the upsilon resonances in $p$$+$$p$, $p$+Au, and Au+Au collisions. sPHENIX will collect approximately 200 PB of data over three run periods utilizing a finite-sized...
The High Energy Physics (HEP) experiments, such as those at theLarge Hadron Collider (LHC), traditionally consume large amounts of CPUcycles for detector simulations and data analysis, but rarely use compute accel-erators such as GPUs. As the LHC is upgraded to allow for higher luminosity,resulting in much higher data rates, purely relying on CPUs may not provideenough computing...
The physics reach of the HL-LHC will be limited by how efficiently the experiments can use the available computing resources, i.e. affordable software and computing are essential. The development of novel methods for charged particle reconstruction at the HL-LHC incorporating machine learning techniques or based entirely on machine learning is a vibrant area of research. In the past two years,...
A major upgrade of the ALICE experiment is ongoing aiming to a high-rate data taking during LHC Run 3 (2022-2024).
The LHC interaction rate at Point 2 will be increased to $50\ \mathrm{kHz}$ kHz in Pb-Pb collisions and $1\ \mathrm{MHz}$ in pp collisions. ALICE experiment will be able to readout full interaction rate leading to an increase of the collected luminosity up a factor of about 100...
CORSIKA is a standard software for simulations of air showers induced by cosmic rays. It has been developed in Fortran 77 continuously over the last thirty years. So it becomes very difficult to add new physics features to CORSIKA 7. CORSIKA 8 aims to be the future of the CORSIKA project. It is a framework in C++17 which uses modern concepts in object oriented programming for an efficient...
We report the latest development in ROOT/TMVA, a new system that takes trained ONNX deep learning models and emits C++ code that can be easily included and invoked for fast inference of the model, with minimal dependency. We present an overview of the current solutions for conducting inference in C++ production environment, discuss the technical details and examples of the generated code, and...
Daisy (Data Analysis Integrated Software System) has been designed for the analysis and visualization of the X-ray experiments. To address an extensive range of Chinese radiation facilities community’s requirements from purely algorithmic problems to scientific computing infrastructure, Daisy sets up a cloud-native platform to support on-site data analysis services with fast feedback and...
The DUNE detector is a neutrino physics experiment that is expected to take data starting from 2028. The data acquisition (DAQ) system of the experiment is designed to sustain several TB/s of incoming data which will be temporarily buffered while being processed by a software based data selection system.
In DUNE, some rare physics processes (e.g. Supernovae Burst events) require storing the...
The ATLAS experiment at the Large Hadron Collider (LHC) op- erated very successfully in the years 2008 to 2018, in two periods identified as Run 1 and Run 2. ATLAS achieved an overall data-taking efficiency of 94%, largely constrained by the irreducible dead-time introduced to accommodate the limitations of the detector read-out electronics. Out of the 6% dead-time only about 15% could be...
Synchrotron radiation sources are widely used in various fields, among which computed tomography (CT) is one of the most important fields. The amount of effort expended by the operator varies depending on the subject. If the number of angles needed to be used can be greatly reduced under the condition of similar imaging effects, the working time and workload of the experimentalists will be...
The ATLAS experiment will undergo a major upgrade to take advantage of the new conditions provided by the upgraded High-Luminosity LHC. The Trigger and Data Acquisition system (TDAQ) will record data at unprecedented rates: the detectors will be read out at 1 MHz generating around 5 TB/s of data. The Dataflow system (DF), component of TDAQ, introduces a novel design: readout data are buffered...
During the LHC Long Shutdown 2, the ALICE experiment has undergone numerous upgrades to cope with the large amount of data expected in Run3. Among all new elements integrated into ALICE, the experiment counts with a new Inner Tracking System (ITS), equipped with innovative pixel sensors that will substantially improve the performance of the system. The new detector is equipped with a complex...
With the LHC continuing to collect more data and experimental analyses becoming increasingly complex, tools to efficiently develop and execute
these analyses are essential. The bamboo framework defines a domain-specific
language, embedded in python, that allows to concisely express the analysis
logic in a functional style. The implementation based on ROOT’s RDataFrame
and cling C++ JIT...
Full detector simulation is known to consume a large proportion of computing resources available to the LHC experiments, and reducing time consumed by simulation will allow for more profound physics studies. There are many avenues to exploit, and in this work we investigate those that do not require changes in the GEANT4 simulation suite. In this study, several factors affecting the full...
We report status of the CMS full simulation for Run-3. During the long shutdown of the LHC a significant update has been introduced to the CMS code for simulation. CMS geometry description is reviewed. Several important modifications were needed. CMS detector description software is migrated to the DD4Hep community developed tool. We will report on our experience obtained during the process of...
This paper presents an overview and features of an Analysis Description Language (ADL) designed for HEP data analysis. ADL is a domain-specific, declarative language that describes the physics content of an analysis in a standard and unambiguous way, independent of any computing frameworks. It also describes infrastructures that render ADL executable, namely CutLang, a direct runtime...
The ATLAS detector requires a huge infrastructure consisting of numerous interconnected systems forming a complex mesh which requires constant maintenance and upgrades. The ATLAS Technical Coordination Expert System provides, by the means of a user interface, a quick and deep understanding of the infrastructure, which helps to plan interventions by foreseeing unexpected consequences, and to...
The usefulness and valuableness of Multi-step ML, where a task is organized into connected sub-tasks with known intermediate inference goals, as opposed to a single large model learned end-to-end without intermediate sub-tasks, is presented. Pre-optimized ML models are connected and better performance is obtained by re-optimizing the connected one. The selection of a ML model from several...
The modelling of Cherenkov based detectors is traditionally done using Geant4 toolkit. In this work, we present another method based on Python programming language and Numba high performance compiler to speed up the simulation. As an example we take one of the Forward Proton Detectors at the CERN LHC - ATLAS Forward Proton (AFP) Time-of-Flight, which is used to reduce the background from...
The Large Hadron Collider and the ATLAS experiment at CERN will explore new frontiers in physics in Run 3 starting in 2022. In the Run 3 ATLAS Level-1 endcap muon trigger, new detectors called New Small Wheel and additional Resistive Plate Chambers will be installed to improve momentum resolution and to enhance the rejection of fake muons. The Level-1 endcap muon trigger algorithm will be...
Starting from the next LHC run, the upgraded LHCb High Level Trigger will process events at the full LHC collision rate (averaging 30 MHz). This challenging goal, tackled using a large and heterogeneous computing farm, can be eased addressing lowest-level, more repetitive tasks at the earliest stages of the data acquisition chain. FPGA devices are very well-suited to perform with a high degree...
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...
We proposed a disk-based custodial storage as an alternative to tape for the ALICE experiment at CERN to preserve its raw data.
The proposed storage system relies on RAIN layout -- the implementation of erasure coding in the EOS storage suite, which is developed by CERN -- for data protection and takes full advantage of high-density JBOD enclosures to maximize storage capacity as well as to...
The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino experiment with a broad physical program. The main goals of JUNO are the determination of the neutrino mass ordering and high precision investigation of neutrino oscillation properties. The precise reconstruction of the event energy is crucial for the success of the experiment.
JUNO is equiped with 17 612 + 25 600 PMT...
The traditional approach in HEP analysis software is to loop over every event and every object via the ROOT framework. This method follows an imperative paradigm, in which the code is tied to the storage format and steps of execution. A more desirable strategy would be to implement a declarative language, such that the storage medium and execution are not included in the abstraction model....
The optimization of reconstruction algorithms has become a key aspect in LHCb as it is currently undergoing a major upgrade that will considerably increase the data processing rate. Aiming to accelerate the second most time consuming reconstruction process of the trigger, we propose an alternative reconstruction algorithm for the Electromagnetic Calorimeter of LHCb. Together with the use of...
The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. iDDS has been designed to intelligently orchestrate workflow and data management systems, decoupling data pre-processing, delivery, and main processing in various workflows. It is an experiment-agnostic service around a workflow-...
This paper evaluates the real-time distribution of data over Ethernet for the upgraded LHCb data acquisition cluster at CERN. The total estimated throughput of the system is 32 Terabits per second. After the events are assembled, they must be distributed for further data selection to the filtering farm of the online trigger. High-throughput and very low overhead transmissions will be an...
The SuperKEKB/Belle II experiment expects to collect 50 $\mathrm{ab}^{-1}$ of collision data during the next decade. Study of this data requires monumental computing resources to process and to generate the required simulation events necessary for physics analysis. At the core of the Belle II simulation library is the Geant4 toolkit. To use the available computing resources more efficiently,...
The GeoModel class library for detector description has recently been released as an open-source package and extended with a set of tools to allow much of the detector modeling to be carried out in a lightweight development environment, outside of large and complex software frameworks. These tools include the mechanisms for creating persistent representation of the geometry, an interactive 3D...
The HIBEAM/NNBAR program is a proposed two-stage experiment for the European Spallation Source focusing on searches for baryon number violation via processes in which neutrons convert to anti-neutrons. This paper outlines the computing and detector simulation framework for the HIBEAM/NNBAR program. The simulation is based on predictions of neutron flux and neutronics together with signal and...
Simulation is one of the key components in high energy physics. Historically it relies on the Monte Carlo methods which require a tremendous amount of computation resources. These methods may have difficulties with the expected High Luminosity Large Hadron Collider need, so the experiment is in urgent need of new fast simulation techniques. The application of Generative Adversarial Networks is...
The High Luminosity Large Hadron Collider provides a data challenge. The amount of data recorded from the experiments and transported to hundreds of sites will see a thirty fold increase in annual data volume. A systematic approach to contrast the performance of different Third Party Copy (TPC) transfer protocols arises. Two contenders, XRootD-HTTPS and the GridFTP are evaluated in their...
The High Luminosity upgrade to the LHC, which aims for a ten-fold increase in the luminosity of proton-proton collisions at an energy of 14 TeV, is expected to start operation in 2028/29, and will deliver an unprecedented volume of scientific data at the multi-exabyte scale. This amount of data has to be stored and the corresponding storage system must ensure fast and reliable data delivery...
CMS tuned its simulation program and chose a specific physics model of Geant4 by comparing the simulation results with dedicated test beam experiments. Test beam data provide measurements of energy response of the calorimeter as well as resolution for well identified charged hadrons over a large energy region. CMS continues to validate the physics models using the test beam data as well as...
This document is devoted to the description of advances in the generation of high-quality random numbers for CORSIKA 8, which is being developed in modern C++17 and is designed to run on modern multi-thread processors and accelerators. CORSIKA 8 is a Monte Carlo simulation framework to model ultra-high energy secondary particle cascades in astroparticle physics. The aspects associated with...
The dCache project provides open-source software deployed internationally to satisfy ever more demanding storage requirements. Its multifaceted approach provides an integrated way of supporting different use-cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters and long term data persistence on a tertiary...
Accurate and fast simulation of particle physics processes is crucial for the high-energy physics community. Simulating particle interactions with the detector is both time consuming and computationally expensive. With its proton-proton collision energy of 13 TeV, the Large Hadron Collider is uniquely positioned to detect and measure the rare phenomena that can shape our knowledge of new...
The management of separate memory spaces of CPUs and GPUs brings an additional burden to the development of software for GPUs. To help with this, CUDA unified memory provides a single address space that can be accessed from both CPU and GPU. The automatic data transfer mechanism is based on page faults generated by the memory accesses. This mechanism has a performance cost, that can be with...
The ATLAS experiment relies heavily on simulated data, requiring the production on the order of billions of Monte Carlo-based proton-proton collisions every run period. As such, the simulation of collisions (events) is the single biggest CPU resource consumer. ATLAS's finite computing resources are at odds with the expected conditions during the High Luminosity LHC era, where the increase in...
Upon its restart in 2022, the LHCb experiment at the LHC will run at higher instantaneous luminosity and utilize an unprecedented full-software trigger, promising greater physics reach and efficiency. On the flip side, conforming to offline data storage constraints becomes far more challenging. Both of these considerations necessitate a set of highly optimised trigger selections. We therefore...
Infrastructures supporting distributed scientific collaborations must address competing goals in both providing high-performance access to resources while simultaneously securing the infrastructure against security threats. The NetBASILISK project is attempting to improve the security of such infrastructures while not adversely impacting their performance. This paper will present our work to...
Based on the fact that showers in calorimeters depend on the type of particle, this note attempts to perform a particle classifier for electromagnetic and hadronic particles on an electromagnetic calorimeter, based on the energy deposit of individual cells. Using data from a Geant4 simulation of a proposal of a Crystal Fiber Calorimeter (SPACAL), foreseen for a future upgrade of the LHCb...
Programming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, and development of new algorithms would be daunting if it had to be repeated many times. Fortunately there are several portability technologies on the market such as Alpaka, Kokkos, and SYCL. These technologies aim to...
Tape storage remains the most cost-effective system for safe long-term storage of petabytes of data and reliably accessing it on demand. It has long been widely used by Tier-1 centers in WLCG. GridKa uses tape storage systems for LHC and non-LHC HEP experiments. The performance requirements on the tape storage systems are increasing every year, creating an increasing number of challenges in...
Detector simulation in high energy physics experiments is a key yet computationally expensive step in the event simulation process. There has been much recent interest in using deep generative models as a faster alternative to the full Monte Carlo simulation process in situations in which the utmost accuracy is not necessary. In this work we investigate the use of conditional Wasserstein...
Future operation of the CBM detector requires ultra-fast analysis of the continuous stream of data from all subdetector systems. Determining the inter-system time shifts among individual detector systems in the existing prototype experiment Mini-CBM is an essential step for data processing and in particular for stable data taking. Based on the input of raw measurements from all detector...
We present the porting to heterogeneous architectures of the algorithm used for applying linear transformations of raw energy deposits in the CMS High Granularity Calorimeter (HGCAL). This is the first heterogeneous algorithm to be fully integrated with HGCAL’s reconstruction chain. After introducing the latter and giving a brief description of the structural components of HGCAL relevant for...
Given the anticipated increase in the amount of scientific data, it is widely accepted that primarily disk based storage will become prohibitively expensive. Tape based storage, on the other hand, provides a viable and affordable solution for the ever increasing demand for storage space. Coupled with a disk caching layer that temporarily holds a small fraction of the total data volume to allow...
The SARS COV 2 virus, the cause of the better known COVID-19 disease, has greatly altered our personal and professional lives. Many people are now expected to work from home but this is not always possible and, in such cases, it is the responsibility of the employer to implement protective measures. One simple such measure is to require that people maintain a distance of 2 metres but this...
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...
A major goal of future dCache development will be to allow users to define file Quality of Service (QoS) in a more flexible way than currently available. This will mean implementing what might be called a QoS rule engine responsible for registering and managing time-bound QoS transitions for files or storage units. In anticipation of this extension to existing dCache capabilities, the...
The lepton–proton collisions produced at the HERA collider represent a unique high energy physics data set. A number of years after the end of collisions, the data collected by the H1 experiment, as well as the simulated events and all software needed for reconstruction, simulation and data analysis were migrated into a preserved operational mode at DESY. A recent modernisation of the H1...
Within the Phase-II upgrade of the LHC, the readout electronics of the ATLAS LAr Calorimeters is prepared for high luminosity operation expecting a pile-up of up to 200 simultaneous pp interactions. Moreover, the calorimeter signals of up to 25 subsequent collisions are overlapping, which increases the difficulty of energy reconstruction. Real-time processing of digitized pulses sampled at 40...
Quantum computers have the potential for significant speed-ups of certain computational tasks. A possibility this opens up within the field of machine learning is the use of quantum features that would be inefficient to calculate classically. Machine learning algorithms are ubiquitous in particle physics and as advances are made in quantum machine learning technology, there may be a similar...
The EDM4hep project aims to design the common event data model for the Key4hep project and is generated via the podio toolkit. We present the first version of EDM4hep and discuss some of its use cases in the Key4hep project. Additionally, we discuss recent developments in podio, like the updates of the automatic code generation and also the addition of a second I/O backend based on SIO. We...
In recent years a Muon Collider has attracted a lot of interest in the High-Energy Physics community thanks to its ability of achieving clean inter- action signatures at multi-TeV collision energies in the most cost-effective way. Estimation of the physics potential of such an experiment must take into account the impact of beam-induced background on the detector performance, which has to be...
The HEPiX Benchmarking Working Group has been developing a benchmark based on actual software workloads of the High Energy Physics community. This approach, based on container technologies, is designed to provide a benchmark that is better correlated with the actual throughput of the experiment production workloads. It also offers the possibility to separately explore and describe the...
Dirac and Rucio are two standard pieces of software widely used in the HEP domain. Dirac provides Workload and Data Management functionalities, among other things, while Rucio is a dedicated, advanced Distributed Data Management system. Many communities that already use Dirac express their interest in using Dirac for workload management in combination with Rucio for the Data management part....
As part of the FAIR Phase-0 program, the fast FLES (First-Level Event Selection) package algorithms developed for the CBM experiment (FAIR/GSI, Germany) has been adapted for online and offline processing in the STAR experiment (BNL, USA). Using the same algorithms creates a bridge between online and offline modes. This allows combining online and offline resources for data processing.
Thus,...
We present BAT.jl 2.0, the next generation of the Bayesian Analysis Toolkit. BAT.jl is a highly efficient and easy to use software package for Bayesian Inference. It's predecessor, BAT 1.0 in C++, has been very successful over the years with a large number of citations. Our new incarnation of BAT was rewritten from scratch in Julia and we recently released the long-term stable version...
To optimise the performance of distributed compute, smaller lightweight storage caches are needed which integrate with existing grid computing workflows. A good solution to provide lightweight storage caches is to use an XRootD-proxy cache. To support distributed lightweight XRootD proxy services across GridPP we have developed a centralised monitoring framework.
With the v5 release of...
The High Luminosity phase of the LHC, which aims for a ten-fold increase in the luminosity of proton-proton collisions is expected to start operation in eight years. An unprecedented scientific data volume at the multi-exabyte scale will be delivered to particle physics experiments at CERN. This amount of data has to be stored and the corresponding technology must ensure fast and...
Processing and scientific analysis of the data taken by the ATLAS experiment requires reliable information describing the event data recorded by the detector or generated in software. ATLAS event processing applications store such descriptive metadata information in the output data files along with the event information.
To better leverage the available computing resources during LHC Run3...
The European-funded ESCAPE project (Horizon 2020) aims to address computing challenges in the context of the European Open Science Cloud. The project targets Particle Physics and Astronomy facilities and research infrastructures, focusing on the development of solutions to handle Exabyte-scale datasets. The science projects in ESCAPE are in different phases of evolution and count a variety of...
We present an ongoing R&D activity for machine-learning-assisted navigation through detectors to be used for track reconstruction. We investigate different approaches of training neural networks for surface prediction and compare their results. This work is carried out in the context of the ACTS tracking toolkit.
One of the biggest challenges in the High-Luminosity LHC (HL- LHC) era will be the significantly increased data size to be recorded and an- alyzed from the collisions at the ATLAS and CMS experiments. ServiceX is a software R&D project in the area of Data Organization, Management and Access of the IRIS- HEP to investigate new computational models for the HL- LHC era. ServiceX is an...
The PANDA experiment at FAIR (Facility for Antiproton and Ion
Research) in Darmstadt is currently under construction. In order to reduce the
amount of data collected during operation, it is essential to find all true tracks
and to be able to distinguish them from false tracks. Part of the preparation
for the experiment is therefore the development of a fast online track finder.
This work...
To sustain the harsher conditions of the high-luminosity LHC, the CMS collaboration is designing a novel endcap calorimeter system. The new calorimeter will predominantly use silicon sensors to achieve sufficient radiation tolerance and will maintain highly-granular information in the readout to help mitigate the effects of pileup. In regions characterised by lower radiation levels, small...
Anomaly detection in the CERN OpenStack cloud is a challenging task due to the large scale of the computing infrastructure and, consequently, the large volume of monitoring data to analyse. The current solution to spot anomalous servers in the cloud infrastructure relies on a threshold-based alarming system carefully set by the system managers on the performance metrics of each...
The Time Projection Chamber (TPC) of the ALICE experiment at the CERN LHC was upgraded for Run 3 and Run 4. Readout chambers based on Gas Electron Multiplier (GEM) technology and a new readout scheme allow continuous data taking at the highest interaction rates expected in Pb-Pb collisions. Due to the absence of a gating grid system, a significant amount of ions created in the multiplication...
The CERN IT Storage Group ensures the symbiotic development
and operations of storage and data transfer services for all CERN physics data,
in particular the data generated by the four LHC experiments (ALICE, ATLAS,
CMS and LHCb).
In order to accomplish the objectives of the next run of the LHC (Run-3), the
Storage Group has undertaken a thorough analysis of the experiments’...
Machine learning algorithms are gaining ground in high energy physics for applications in particle and event identification, physics analysis, detector reconstruction, simulation and trigger. Currently, most data-analysis tasks at LHC experiments benefit from the use of machine learning. Incorporating these computational tools in the experimental framework presents new challenges.
This...
Across the years, being the backbone of numerous data management solutions used within the WLCG collaboration, the XRootD framework and protocol became one of the most important building blocks for storage solutions in the High Energy Physics (HEP) community. The latest big milestone for the project, release 5, introduced multitude of architectural improvements and functional enhancements,...
The CMS experiment at CERN employs a distributed computing infrastructure to satisfy its data processing and simulation needs. The CMS Submission Infrastructure team manages a dynamic HTCondor pool, aggregating mainly Grid clusters worldwide, but also HPC, Cloud and opportunistic resources. This CMS Global Pool, which currently involves over 70 computing sites worldwide and peaks at 300k CPU...
The alignment of the Belle II tracking system composed of a pixel and strip vertex detectors and central drift chamber is described by approximately 60,000 parameters. These include internal local alignment: positions, orientations and surface deformations of silicon sensors and positions of drift chamber wires as well as global alignment: relative positions of the sub-detectors and larger...
The cabinetry library provides a Python-based solution for building and steering binned template fits. It tightly integrates with the pythonic High Energy Physics ecosystem, and in particular with pyhf for statistical inference. cabinetry uses a declarative approach for building statistical models, with a JSON schema describing possible configuration choices. Model building instructions can...
Effective selection of muon candidates is the cornerstone of the LHC physics programme. The ATLAS experiment uses the two-level trigger system for real-time selections of interesting events. The first-level hardware trigger system uses the Resistive Plate Chamber detector (RPC) for selecting muon candidates in the central (barrel) region of the detector. With the planned upgrades, the entirely...
This talk summarises the main changes to the ATLAS experiment’s Inner Detector Track reconstruction software chain in preparation of LHC Run 3 (2022-2024). The work was carried out to ensure that the expected high-activity collisions with on average 50 simultaneous proton-proton interactions per bunch crossing (pile-up) can be reconstructed promptly using the available computing resources....
CERNBox is the cloud collaboration hub at CERN. The service has more than 37,000 user accounts. The backup of user and project data is critical for the service. The underlying storage system hosts over a billion files which amount to 12PB of storage distributed over several hundred disks with a two-replica RAIN layout. Performing a backup operation over this vast amount of data is a...
The CORSIKA 8 project is an international collaboration of scientists working together to deliver the most modern, flexible, robust and efficient framework for the simulation of ultra-high energy secondary particle cascades in matter. The main application is for cosmic ray air shower simulations, but is not limited to that. Besides a comprehensive collection of physics models and algorithms...
We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as...
Network utilisation efficiency can, at least in principle, often be improved by dynamically re-configuring routing policies to better distribute on-going large data transfers. Unfortunately, the information necessary to decide on an appropriate reconfiguration---details of on-going and upcoming data transfers such as their source and destination and, most importantly, their volume and...
The IceCube Neutrino Observatory is a cubic kilometer neutrino detector located at the geographic South Pole designed to detect high-energy astrophysical neutrinos. To thoroughly understand the detected neutrinos and their properties, the detector response to signal and background has to be modeled using Monte Carlo techniques. An integral part of these studies are the optical properties of...
High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form $\Delta \chi^2$ is often...
The Hall-D Online Skim System (HOSS) was developed to simultaneously solve two issues for the high intensity GlueX experiment. One was to parallelize the writing of raw data files to disk in order to improve bandwidth. The other was to distribute the raw data across multiple compute nodes in order to produce calibration \textit{skims} of the data online. The highly configurable system employs...
The locations of proton-proton collision points in LHC experiments
are called primary vertices (PVs). Preliminary results of a hybrid deep learning
algorithm for identifying and locating these, targeting the Run 3 incarnation
of LHCb, have been described at conferences in 2019 and 2020. In the past
year we have made significant progress in a variety of related areas. Using
two newer...
The distributed computing of the ATLAS experiment at LHC is using computing resources of the Czech national HPC center IT4Innovations for several years. The submission system is based on ARC-CEs installed at the Czech LHC Tier2 site (praguelcg2). Recent improvements of this system will be discussed here. First, there was migration of the ARC-CE from version 5 to 6 which improves the...
HPC resources will help meet the future challenges of HL-LHC in terms of CPU requirements. The Spanish HPC centers have been used recently by implementing all the necessary edge services to integrate the resources into the LHC experiments workflow management system. Since it not always possible to install the edge services on HPC premises, we opted to set up a dedicated ARC-CE and interact...
The LZ collaboration aims to directly detect dark matter by using a liquid xenon Time Projection Chamber (TPC). In order to probe the dark matter signal, observed signals are compared with simulations that model the detector response. The most computationally expensive aspect of these simulations is the propagation of photons in the detector’s sensitive volume. For this reason, we propose to...
This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar reconstruction tasks in the LHC. In this paper, a multihead attention message passing network is used to classify the relationship...
Apache Spark is one of the predominant frameworks in the big data space, providing a fully-functional query processing engine, vendor support for hardware accelerators, and performant integrations with scientific computing libraries. One difficulty in adopting conventional big data frameworks to HEP workflows is the lack of support for the ROOT file format in these frameworks. Laurelin...
An effort is underway to develop streaming readout data acquisition system for the CLAS12 detector in Jefferson Lab's experimental Hall-B. Successful beam tests were performed in the spring and summer of 2020 using a 10GeV electron beam from Jefferson Lab's CEBAF accelerator. The prototype system combined elements of the TriDAS and CODA data acquisition systems with the JANA2...
While deep learning techniques are becoming increasingly more popular in high-energy and, since recently, neutrino experiments, they are less confidently used in direct dark matter searches based on dual-phase noble gas TPCs optimized for low-energy signals from particle interactions.
In the present study, application of modern deep learning methods for event ver- tex reconstruction is...
Thanks to its RDataFrame interface, ROOT now supports the execution of the same physics analysis code both on a single machine and on a cluster of distributed resources. In the latter scenario, it is common to read the input ROOT datasets over the network from remote storage systems, which often increases the time it takes for physicists to obtain their results. Storing the remote files much...
In this proceedings we present MadFlow, a new framework for the automation of Monte Carlo (MC) simulation on graphics processing units (GPU) for particle physics processes. In order to automate MC simulation for a generic number of processes, we design a program which provides to the user the possibility to simulate custom processes through the MG5_aMC@NLO framework. The pipeline includes a...
This paper presents the experience in providing CERN users with
direct online access to their EOS/CERNBox-powered user storage from Win-
dows. In production for about 15 months, a High-Available Samba cluster is
regularly used by a significant fraction of the CERN user base, following the
migration of their central home folders from Microsoft DFS in the context of
CERN’s strategy to move...
The Gamma Ray Energy Tracking Array (GRETA) is a state of the art gamma-ray spectrometer being built at Lawrence Berkeley National Laboratory to be first sited at the Facility for Rare Isotope Beams (FRIB) at Michigan State University. A key design requirement for the spectrometer is to perform gamma-ray tracking in near real time. To meet this requirement we have used an inline, streaming...
Future analysis of ATLAS data will involve new small-sized analysis
formats to cope with the increased storage needs. The smallest of
these, named DAOD_PHYSLITE, has calibrations already applied
to allow fast downstream analysis and avoid the need for further
analysis-specific intermediate formats. This allows for application
of the "columnar analysis" paradigm where operations are...
Computational science, data management and analysis have been key factors in the success of Brookhaven National Laboratory's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source (NSLS-II), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, Lattice Quantum Chromodynamics (LQCD) and...
Triggered data acquisition systems provide only limited possibilities of triggering methods. In our paper, we propose a novel approach that completely removes the hardware trigger and its logic. It introduces an innovative free-running mode instead, which provides unprecedented possibilities to physics experiments. We would like to present such system, which is being developed for the AMBER...
Metadata management is one of three major areas and parts of functionality of scientific data management along with replica management and workflow management. Metadata is the information describing the data stored in a data item, a file or an object. It includes the data item provenance, recording conditions, format and other attributes. MetaCat is a metadata management database designed and...
Celeritas is a new computational transport code designed for high-performance
simulation of high-energy physics detectors. This work describes some of its
current capabilities and the design choices that enable the rapid development
of efficient on-device physics. The abstractions that underpin the code design
facilitate low-level performance tweaks that require no changes to the
...
Over the last decades, several data preservation efforts have been undertaken by the HEP community, as experiments are not repeatable and consequently their data considered unique. ARCHIVER is a European Commission (EC) co-funded Horizon 2020 pre-commercial procurement project procuring R&D combining multiple ICT technologies including data-intensive scalability, network, service...
File formats for generic data structures, such as ROOT, Avro, and Parquet, pose a problem for deserialization: it must be fast, but its code depends on the type of the data structure, not known at compile-time. Just-in-time compilation can satisfy both constraints, but we propose a more portable solution: specialized virtual machines. AwkwardForth is a Forth-driven virtual machine for...
The Rutherford Appleton Laboratory (RAL) runs the UK Tier-1 which supports all four LHC experiments, as well as a growing number of others in HEP, Astronomy and Space Science. In September 2020, RAL was provided with funds to upgrade its network. The Tier-1 not only wants to meet the demands of LHC Run 3, it also wants to ensure that it can take an active role in data lake development and...
The Front-End Link eXchange (FELIX) system is an interface between the trigger and detector electronics and commodity switched networks for the ATLAS experiment at CERN. In preparation for the LHC Run 3, to start in 2022, the system is being installed to read out the new electromagnetic calorimeter, calorimeter trigger, and muon components being installed as part of the ongoing ATLAS upgrade...
The increasing number of high-performance computing centers around the globe is providing physicists and other researchers access to heterogeneous systems -- comprising multiple central processing units and graphics processing units per node -- with various platforms. However, it is more often than not the case that domain scientists have limited resources such that writing multiple...
Over the last two decades, ROOT TTree has been used for storing over one exabyte of High-Energy Physics (HEP) events. The TTree columnar on-disk layout has been proved to be ideal for analyses of HEP data that typically require access to many events, but only a subset of the information stored for each of them. Future accelerators, and particularly HL-LHC, will bring an increase of at least...
Array operations are one of the most concise ways of expressing common filtering and simple aggregation operations that is the hallmark of the first step of a particle physics analysis: selection, filtering, basic vector operations, and filling histograms. The High Luminosity run of the Large Hadron Collider (HL-LHC), scheduled to start in 2026, will require physicists to regularly skim...
Modern experiments in high energy physics analyze millions of events recorded in particle detectors to select the events of interest and make measurements of physics parameters. These data can often be stored as tabular data in files with detector information and reconstructed quantities. Current techniques for event selection in these files lack the scalability needed for high performance...
Data analysis in HEP has often relied on batch systems and event loops; users are given a non-interactive interface to computing resources and consider data event-by-event. The "Coffea-casa" prototype analysis facility is an effort to provide users with alternate mechanisms to access computing resources and enable new programming paradigms. Instead of the command-line interface and...
Generative machine learning models offer a promising way to efficiently amplify classical Monte Carlo generators' statistics for event simulation and generation in particle physics. Given the already high computational cost of simulation and the expected increase in data in the high-precision era of the LHC and at future colliders, such fast surrogate simulators are urgently needed.
This...
Given the increasing data collection capabilities and limited computing resources of future collider experiments, interest in using generative neural networks for the fast simulation of collider events is growing. In our previous study, the Bounded Information Bottleneck Autoencoder (BIB-AE) architecture for generating photon showers in a high-granularity calorimeter showed a high accuracy...
EsbRootView is an event display for the detectors of ESSnuSB able to exploit natively all the nice devices that we have in hands today; desktop, laptops but also smartphones and tablets.
There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to make the best use of near-term quantum devices. We introduce two separate ideas for circuit optimization and combine them in a multi-tiered quantum circuit optimization protocol called AQCEL. The first ingredient is a...
The CERN ATLAS Experiment successfully uses a worldwide distributed computing Grid infrastructure to support its physics programme at the Large Hadron Collider (LHC). The Grid workflow system PanDA routinely manages up to 700'000 concurrently running production and analysis jobs to process simulation and detector data. In total more than 500 PB of data is distributed over more than 150 sites...
CloudVeneto is a private cloud implemented as the result of merging two existing cloud infrastructures: the INFN Cloud Area Padovana, and a private cloud owned by 10 departments of University of Padova.
This infrastructure is a full production facility, in continuous growth, both in terms of users, and in terms of computing and storage resources.
Even if the usage of CloudVeneto is not...
Education & outreach is an important part of HEP experiments. With outreach & education, experiments can have an impact on the public, students and their teachers, as well as policymakers and the media. The tools and methods for visualization enable to represent the detectors' facilities, explaining their purpose, functionalities, development histories, and participant institutes. In addition,...
In recent years, machine learning methods have become increasingly important for the experiments of the Large Hadron Collider (LHC). They are utilized in everything from trigger systems to reconstruction to data analysis. The recent UCluster method is a general model providing unsupervised clustering of particle physics data, that can be easily modified for a variety of different tasks. In...
Generative Models, and Generative Adversarial Networks (GAN) in particular, are being studied as possible alternatives to Monte Carlo. Meanwhile, it has also been proposed that, in certain circumstances, simulation using GANs can itself be sped-up by using quantum GANs (qGANs).
Our work presents an advanced prototype of qGAN, that we call the dual-Parameterized Quantum Circuit (PQC) GAN,...
The ATLAS Tile Calorimeter (TileCal) is the central part of the hadronic calorimeter of the ATLAS experiment and provides important information for reconstruction of hadrons, jets, hadronic decays of tau leptons and missing transverse energy. The readout is segmented into nearly 10000 channels that are calibrated by means of Cesium source, laser, charge injection, and integrator-based...
Abstract. The vast amounts of data generated by scientific research pose enormous challenges for capturing, managing and processing this data. Many trials have been made in different projects (such as HNSciCloud and OCRE), but today, commercial cloud services do not yet play a major role in the production computing environments of the publicly funded research sector in Europe. Funded by...
The Belle II detector began collecting data from $e^+e^-$ collisions at the SuperKEKB electron-positron collider in March 2019 and has already exceeded the Belle instantaneous luminosity. The result is an unprecedented amount of incoming raw data that must be calibrated promptly prior to data reconstruction. To fully automate the calibration process a Python plugin package, b2cal, had been...
Visualising HEP experiment event data and geometry is vital for physicists trying to debug their reconstruction software, their detector geometry or their physics analysis, and also for outreach and publicity purposes. Traditionally experiments used in-house applications that required installation (often as part of a much larger experiment specific framework). In recent years, web-based...
With the increasing number of Machine and Deep Learning applications in High Energy Physics, easy access to dedicated infrastructure represents a requirement for fast and efficient R&D. This work explores different types of cloud services to train a Generative Adversarial Network (GAN) in a parallel
environment, using Tensorflow data parallel strategy. More specifically, we parallelize the...
We have developed two quantum classifier models for the $t\bar{t}H$ classification problem, both of which fall into the category of hybrid quantum-classical algorithms for Noisy Intermediate Scale Quantum devices (NISQ). Our results, along with other studies, serve as a proof of concept that Quantum Machine Learning (QML) methods can have similar or better performance, in specific cases of low...
The LHCb detector at the LHC is currently undergoing a major upgrade to increase full detector read-out rate to 30 MHz. In addition to the detector hardware modernisation, the new trigger system will be software-only. The code base of the new trigger system must be thoroughly tested for data flow, functionality and physics performance. Currently, the testing procedure is based on a system of...
Following the outbreak of the COVID-19 pandemic, the ATLAS experiment considered how it could most efficiently contribute using its distributed computing resources. After considering many suggestions, examining several potential projects and following the advice of the CERN COVID Task Force, it was decided to engage in the Folding@Home initiative, which provides payloads that perform protein...
The inclusion of opportunistic resources, for example from High Performance Computing (HPC) centers or cloud providers, is an important contribution to bridging the gap between existing resources and future needs by the LHC collaborations, especially for the HL-LHC era. However, the integration of these resources poses new challenges and often needs to happen in a highly dynamic manner. To...
The high-luminosity upgrade of the LHC will come with unprecedented physics and computing challenges. One of these challenges is the accurate reconstruction of particles in events with up to 200 simultaneous proton-proton interactions. The planned CMS High Granularity Calorimeter offers fine spatial resolution for this purpose, with more than 6 million channels, but also poses unique...
Computing resource needs are expected to increase drastically in the future. The HEP experiments ATLAS and CMS foresee an increase of a factor of 5-10 in the volume of recorded data in the upcoming years. The current infrastructure, namely the WLCG, is not sufficient to meet the demands in terms of computing and storage resources.
The usage of non HEP specific resources is one way to reduce...
During the second long shutdown (LS2) of the CERN Large Hadron Collider (LHC), the Detector Control System (DCS) of the Compact Muon Solenoid (CMS) Electromagnetic Calorimeter (ECAL) is undergoing a large software upgrade at various levels. The ECAL DCS supervisory system has been reviewed and extended to migrate the underlying software toolkits and platform technologies to the latest...
High Energy Photon Source (HEPS) has the characteristic of large amount of data, high timeliness, and diverse requirements for scientific data analysis. Generally, researchers need to spend a lot of time in the configuration of the experimental environment. In response to the above problems, we introduce a remote data analysis system for HEPS. The platform provides users a web-based...
Particle physics experiments rely extensively on computing and data services, making e-infrastructure an integral part of the research collaboration. Constructing and operating distributed computing can however be challenging for a smaller-scale collaboration.
The Light Dark Matter eXperiment (LDMX) is a planned small-scale accelerator-based experiment to search for dark matter in the...
The ATLAS experiment’s software production and distribution on the grid benefits from a semi-automated infrastructure that provides up-to-date information about software usability and availability through the CVMFS distribution service for all relevant systems. The software development process uses a Continuous Integration pipeline involving testing, validation, packaging and installation...
The processing needs for the High Luminosity (HL) upgrade for the LHC require the CMS collaboration to harness the computational power available on non-CMS resources, such as High-Performance Computing centers (HPCs). These sites often limit the external network connectivity of their computational nodes. In this paper we describe a strategy in which all network connections of CMS jobs inside a...
The precise simulation of particle transport through detectors is a key element for the successful interpretation of high energy physics results.
However, Monte Carlo based simulation is extremely demanding in terms of computing resources. This challenge motivates investigations of faster, alternative approaches for replacing the standard Monte Carlo approach.
We apply Generative...
Developing an Open Source Software application is a challenge. Mainly because there are commercial alternatives that have an army of expert developers behind them, experienced supporters and well-established business processes in their development and promotion.
Nevertheless, web-based applications, that securely handle the users' personal data are an area of freedom and ease of use,...
The CMS experiment at the CERN LHC (Large Hadron Collider) relies on a distributed computing infrastructure to process the multi-petabyte datasets where the collision and simulated data are stored. A scalable and reliable monitoring system is required to ensure efficient operation of the distributed computing services, and to provide a comprehensive set of measurements of the system...
In High Energy Physics facilities that provide High Performance Computing environments provide an opportunity to efficiently perform the statistical inference required for analysis of data from the Large Hadron Collider, but can pose problems with orchestration and efficient scheduling. The compute architectures at these facilities do not easily support the Python compute model, and the...
CMS is tackling the exploitation of CPU resources at HPC centers where compute nodes do not have network connectivity to the Internet. Pilot agents and payload jobs need to interact with external services from the compute nodes: access to the application software (cmvfs) and conditions data (Frontier), management of input and output data files (data management services), and job management...
A large scientific computing infrastructure must offer versatility to host any kind of experiment that can lead to innovative ideas. The ATLAS experiment offers wide access possibilities to perform intelligent algorithms and analyze the massive amount of data produced in the Large Hadron Collider at CERN. The BigPanDA monitoring is a component of the PanDA (Production ANd Distributed Analysis)...
We reframe common tasks in jet physics in probabilistic terms, including jet reconstruction, Monte Carlo tuning, matrix element – parton shower matching for large jet multiplicity, and efficient event generation of jets in complex, signal-like regions of phase space. We also introduce Ginkgo, a simplified, generative model for jets, that facilitates research into these tasks with techniques...
Dirac and Rucio are two standard pieces of software widely used in the HEP domain. Dirac provides Workload and Data Management functionalities, among other things, while Rucio is a dedicated, advanced Distributed Data Management system. Many communities that already use Dirac express their interest in using Dirac for workload management in combination with Rucio for the Data management part....
The deployment of analysis pipelines has been tightly related and conditioned to the scientific facility’s computer infrastructure or academic institution where it is carried on. Nowadays, Software as a Service (SaaS) and Infrastructure as a Service (IaaS) have reshaped the industry of data handling, analysis, storage, and sharing. The sector of science does not escape those changes. This...
GlideinWMS is a pilot framework to provide uniform and reliable HTCondor clusters using heterogeneous and unreliable resources. The Glideins are pilot jobs that are sent to the selected nodes, test them, set them up as desired by the user jobs, and ultimately start an HTCondor schedd to join an elastic pool. These Glideins collect information that is very useful to evaluate the health and...
We present a novel algorithm to identify potential dispersed signals of new physics in the slew of published LHC results. It employs a random walk algorithm to introduce sets of new particles, dubbed “proto-models”, which are tested against simplified-model results from ATLAS and CMS (exploiting the SModelS software framework). A combinatorial algorithm identifies the set of analyses and/or...
The challenges proposed by the HL-LHC era are not limited to the sheer amount of data to be processed: the capability of optimizing the analyser's experience will also bring important benefits for the LHC communities, in terms of total resource needs, user satisfaction and in the reduction of end time to publication. At the Italian National Institute for Nuclear Physics (INFN) a portable...
Since 2017, the Worldwide LHC Computing Grid (WLCG) has been working towards enabling token based authentication and authorisation throughout its entire middleware stack. Following the publication of the WLCG v1.0 Token Schema in 2019, middleware developers have been able to enhance their services to consume and validate OAuth2.0 tokens and process the authorization information they convey....
The infrastructure behind [home.cern][1] and 1000 other Drupal websites serves more than 15,000 unique visitors daily. To best serve the site owners, a small engineering team needs development speed to adapt to their evolving needs and operational velocity to troubleshoot emerging problems rapidly. We designed a new Web Frameworks platform by extending Kubernetes to replace the ageing physical...
The ATLAS Experiment at the LHC generates petabytes of data that is distributed among 160 computing sites all over the world and is processed continuously by various central production and user analysis tasks. The popularity of data is typically measured as the number of accesses and plays an important role in resolving data management issues: deleting, replicating, moving between tapes, disks...
The WLCG is modernizing its security infrastructure, replacing X.509 client authentication with the newer industry standard of JSON Web Tokens (JWTs) obtained through the Open ID Connect (OIDC) protocol. There is a wide variety of software available using the standards, but most of it is for Web browser-based applications and doesn’t adapt well to the command line-based software used heavily...
The CMS experiment at CERN has released research-quality data from particle collisions at the LHC since 2014. Almost all data from the first LHC run in 2010--2012 with the corresponding simulated samples are now in the public domain, and several scientific studies have been performed using these data. This paper summarizes the available data and tools, reviews the challenges in using them in...
With more applications and services deployed in BNL SDCC that rely on authentication services, adoption of Multi-factor Authentication (MFA) became inevitable. While web applications can be protected by Keycloak (a open source Single sign-on solution directed by Red Hat) with its MFA feature, other service components within the facility rely on FreeIPA (an open source identity management...
CERN uses the world's largest scientific computing grid, WLCG, for distributed data storage and processing. Monitoring of the CPU and storage resources is an important and essential element to detect operational issues in its systems, for example in the storage elements, and to ensure their proper and efficient function. The processing of experiment data depends strongly on the data access...
Consistent, efficient software builds and deployments are a common concern for all HEP experiments. These proceedings describe the evolution of the usage of the Spack package manager in HEP in the context of the LCG stacks and the current Spack-based management of Key4hep software. Whereas previously Key4hep software used spack only for a thin layer of FCC experiment software on top of the LCG...
We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation of the high-energy collision event. In this study, we use low-level detector...
The High Luminosity LHC project at CERN, which is expected to deliver a ten-fold increase in the luminosity of proton-proton collisions over LHC, will start operation towards the end of this decade and will deliver an unprecedented scientific data volume of multi-exabyte scale. This vast amount of data has to be processed and analyzed, and the corresponding computing facilities must ensure...
The File Transfer Service (FTS3) is a data movement service developed at CERN which is used to distribute the majority of the Large Hadron Collider's data across the Worldwide LHC Computing Grid (WLCG) infrastructure. At Fermilab, we have deployed FTS3 instances for Intensity Frontier experiments (e.g. DUNE) to transfer data in America and Europe, using a container-based strategy. In this...
Recent changes to the ATLAS offline data quality monitoring system are described. These include multithreaded histogram filling and subsequent postprocessing, improvements in the responsiveness and resource use of the automatic check system, and changes to the user interface to improve the user experience.
The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their...
The Exa.TrkX project has applied geometric learning concepts such as metric learning and graph neural networks to HEP particle tracking. The Exa.TrkX tracking pipeline clusters detector measurements to form track candidates and selects track candidates with competitive efficiency and purity. The pipeline, originally developed using the TrackML dataset (a simulation of an LHC-like tracking...
We have deployed a central monitoring and logging system based on Prometheus, Loki and Grafana that collects, aggregates and displays metrics and logs from the Tier-2 ScotGrid cluster at Glasgow. Bespoke dashboards built on Prometheus metrics give a quick overview of cluster performance and make it easy to identify issues. Logs from all nodes and services are collected to a central Loki server...
The DUNE experiment will begin running in the late 2020’s. The goals of the experiment include 1) studying neutrino oscillations using a beam of neutrinos from Fermilab in Illinois to the Sanford Underground Research Facility, 2) studying astrophysical neutrino sources and rare processes and 3) understanding the physics of neutrino interactions in matter. The DUNE Far Detector, consisting of...
ATLAS is one of the largest experiments at the Large Hadron Collider. Its broad physics program ranges from precision measurements to the discovery of new interactions, requiring gargantuan amount of simulated Monte Carlo events. However, a detailed detector simulation with Geant4 is often too slow and requires too many CPU resources. For more than 10 years, ATLAS has developed and utilized...
Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade. Meeting this sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required...
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well-suited to address a variety of recon- struction problems in HEP. In particular, tracker events are naturally repre- sented as graphs by identifying hits as nodes and track segments as edges; given a set of hypothesized edges, edge-classifying GNNs predict which rep- resent real track...
