LHC Data-taking Research Articles

Triggering On Hadronic Signatures In The Atlas Experiment-Developments For 2017 And 2018

Hadronic signatures are critical to the ATLAS physics program, and are used extensively for both the StandardModel measurements and searches for new physics. These signatures include generic quark and gluon jets, as well as jets originating from b-quarks or the decay of massive particles (such as electroweak bosons or top quarks). Additionally, missing transverse momentum from non-interacting particles provides an interesting probe in the search for new physics beyond the Standard Model. Developing trigger selections that target these events is a hugechallenge at the LHC due to the enormous rates associated with hadronic signatures. This challenge is exacerbated by the amount of pile-up activity, which continues to grow. In order to address these challenges, several new techniques were developed to significantly improve the potential of the 2017 dataset. An overview of how we triggeron hadronic signatures at the ATLAS experiment is presented, outlining the challenges of hadronic object triggering and describing the improvements performed over the course of the Run 2 LHC data-taking program. The performance in Run 2 data is shown, including demonstrations of the new techniques being used in 2017. We also discuss further critical developments implemented for the rest of Run 2 and their performance in early 2018 data.

Performance of the ATLAS Tile Calorimeter

The ATLAS Tile hadronic calorimeter (TileCal) provides highly-segmented energy measurements of incoming particles. It is a key detector for the measurement of hadrons, jets, tau leptons and missing transverse energy. It is also useful for identification and reconstruction of muons due to good signal to noise ratio. The calorimeter consists of thin steel plates and 460,000 scintillating tiles configured into 5000 cells, each viewed by two photomultipliers. The calorimeter response and its readout electronics is monitored to better than 1% using radioactive source, laser and charge injection systems. The calibration and performance of the calorimeter have been established through test beam measurements, cosmic ray muons and the large sample of proton-proton collisions acquired in 2011 and 2012. Results on the calorimeter performance are presented, including the absolute energy scale, timing, noise and associated stabilities. The results demonstrate that the Tile Calorimeter has performed well within the design requirements and it has given essential contribution to reconstructed objects and physics results. In addition, the data quality procedures used during the LHC data-taking are described and the outcome of the detector consolidation in the maintenance period is also presented.

Performance of the ATLAS Tile Calorimeter in pp collisions at the LHC

The Tile Calorimeter is the central section of the ATLAS hadronic calorimeter at the Large Hadron Collider. This detector is instrumented for the measurements of hadrons, jets, tau leptons and missing transverse energy. Scintillation light produced in the tiles is transmitted by wavelength shifting fibers to photomultiplier tubes (PMTs). The resulting electronic signals from approximately 10000 PMTs are measured and digitized before being transferred to off- detector data-acquisition systems. After an initial setting of the absolute energy scale in test beams with particles of well-defined momentum, the calibrated scale is transferred to the rest of the detector via the response to radioactive sources. The calibrated scale is validated in situ with muons and single hadrons whereas the timing performance is checked with muons and jets. The data quality procedures used during the LHC data-taking and the evolution of the detector status during the LHC Run 1 are presented. The energy and the time reconstruction performance of the digitized signals is summarized and the calorimeter response to hadrons is investigated with collision data.

Performance of the ATLAS Tile Hadronic Calorimeter at LHC in Run 1 and planned upgrades

The Tile Calorimeter (TileCal) is the central section of the ATLAS hadronic calorimeter at the Large Hadron Collider, a key detector for the measurements of hadrons, jets, tau leptons and missing transverse energy. Scintillation light produced in the tiles is transmitted by wavelength shifting fibres to photomultiplier tubes (PMTs). The resulting electronic signals from approximately 10000 PMTs are digitized before being transferred to off-detector data-acquisition systems. The data quality procedures used during the LHC data-taking and the evolution of the detector status are explained in the presentation. The energy and the time reconstruction performance of the digitized signals is presented and the noise behaviour and its improvement during the detector consolidation in maintenance periods are shown. A set of calibration systems allow monitoring and equalization of the calorimeter channels responses via signal sources that act at every stage of the signal path, from scintillation light to digitized signal. These partially overlapping systems are described in detail, their individual performance is discussed as well as the comparative results from measurements of the evolution of the calorimeter response with time during the full LHC data-taking period. The TileCal upgrade aims at replacing the majority of the on- and off-detector electronics so that all calorimeter signals will be directly digitized and sent to the off-detector electronics in the counting room. To achieve the required reliability, redundancy has been introduced at different levels. For the off-detector electronics a special pre-processor board is being developed, which will take care of the initial trigger processing, while the main data are temporarily stored in the pipeline and de-randomiser memories.

Algorithms, performance, development of the ATLAS High-Level trigger

The ATLAS trigger system has been used for the online event selection for three years of LHC data-taking and is preparing for the next run. The trigger system consists of a hardware level-1 and a software high-level trigger (HLT) which is implemented in a region-of-interest based level-2 stage and a event filter operating after event building with offline-like software. During the past three years, the luminosity and pile-up (number of collisions per beam crossing) has increased significantly placing escalating demands on the rejection and timing performance. The HLT algorithms advanced during this period to maintain and even improve performance. Also discussed is the work towards the merging of the two HLT levels in to a single level HLT.

Studies on the upgrade of the muon system in the forward region of the CMS experiment at LHC with GEMs

The LHC data-taking will resume in 2015 with energy of 13–14 TeV and luminosity of 2÷5 × 1034 cm−2 s−1. At those energies, a considerable fraction of the particles produced propagate in the high pseudo-rapidity regions. The proposal for the upgrade of the CMS muon forward system involves Gas Electron Multiplier (GEM) chambers to be installed during the second LHC Long Shutdown (LS2) covering the pseudorapidity range 1.5 < |η| < 2.2. This detector is able to handle the extreme particle rates expected in this region when the LHC will be running at higher luminosity. The GEM is an excellent choice, as its high spatial resolution (order of 100 μm) allows to combine tracking and triggering capabilities, which will improve the CMS muon High Level Trigger, the muon identification and the track reconstruction. Intense R&D has been going on since 2009 and it has lead to the development of several GEM prototypes and associated detector electronics. These GEM prototypes have been subjected to extensive tests in the laboratory and in test beams at the CERN Super Proton Synchrotron (SPS). This contribution will review the status of the CMS upgrade project with GEMs, discussing also the trigger performance.

Operational Experience with the Frontier System in CMS

The Frontier framework is used in the CMS experiment at the LHC to deliver conditions data to processing clients worldwide, including calibration, alignment, and configuration information. Each central server at CERN, called a Frontier Launchpad, uses tomcat as a servlet container to establish the communication between clients and the central Oracle database. HTTP-proxy Squid servers, located close to clients, cache the responses to queries in order to provide high performance data access and to reduce the load on the central Oracle database. Each Frontier Launchpad also has its own reverse-proxy Squid for caching. The three central servers have been delivering about 5 million responses every day since the LHC startup, containing about 40 GB data in total, to more than one hundred Squid servers located worldwide, with an average response time on the order of 10 milliseconds. The Squid caches deployed worldwide process many more requests per day, over 700 million, and deliver over 40 TB of data. Several monitoring tools of the tomcat log files, the accesses of the Squids on the central Launchpad servers, and the availability of remote Squids have been developed to guarantee the performance of the service and make the system easily maintainable. Following a brief introduction of the Frontier framework, we describe the performance of this highly reliable and stable system, detail monitoring concerns and their deployment, and discuss the overall operational experience from the first two years of LHC data-taking.

Evolution of the ATLAS PanDA Production and Distributed Analysis System

The PanDA (Production and Distributed Analysis) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at LHC data processing scale. PanDA has performed well with high reliability and robustness during the two years of LHC data-taking, while being actively evolved to meet the rapidly changing requirements for analysis use cases. We will present an overview of system evolution including automatic rebrokerage and reattempt for analysis jobs, adaptation for the CernVM File System, support for the multi-cloud model through which Tier-2 sites act as members of multiple clouds, pledged resource management and preferential brokerage, and monitoring improvements. We will also describe results from the analysis of two years of PanDA usage statistics, current issues, and plans for the future.

Overview of ATLAS PanDA Workload Management

The Production and Distributed Analysis System (PanDA) plays a key role in the ATLAS distributed computing infrastructure. All ATLAS Monte-Carlo simulation and data reprocessing jobs pass through the PanDA system. We will describe how PanDA manages job execution on the grid using dynamic resource estimation and data replication together with intelligent brokerage in order to meet the scaling and automation requirements of ATLAS distributed computing. PanDA is also the primary ATLAS system for processing user and group analysis jobs, bringing further requirements for quick, flexible adaptation to the rapidly evolving analysis use cases of the early datataking phase, in addition to the high reliability, robustness and usability needed to provide efficient and transparent utilization of the grid for analysis users. We will describe how PanDA meets ATLAS requirements, the evolution of the system in light of operational experience, how the system has performed during the first LHC data-taking phase and plans for the future.

Alignment and calibration experience under LHC data-taking conditions in the CMS experiment

Full achievement of the physics potential of the detector and timely preparation of results for conferences require a fast turnaround of alignment and calibration workflows. The CMS experiment has set up a powerful framework and infrastructure for alignment and calibration, which is based on dedicated skims providing a highly compact specific input for the various workflows computing the constants, and includes a prompt calibration concept which allows determination of highly time-dependent constants on the fly. The CMS alignment and calibration model has been commissioned step by step with cosmic muons and passed a main challenge with the first LHC high energy run and the preparation of physics results for the 2010 summer conferences. This article reviews detailed experience from this extended operation, including results from selected workflows.

ATLAS: Status and First Results

Recent results from the ATLAS experiment at the CERN Large Hadron Collider are presented. The experiment has been functioning with high efficiency since the start of LHC data-taking, at proton-proton centre-of-mass energies of 900 GeV and 2.36 TeV (2009) and 7 TeV (2010). This paper provides a brief overview of the highlights of recent detector performance and physics measurements.

Relational databases for conditions data and event selection in ATLAS

The ATLAS experiment at LHC will make extensive use of relational databases in both online and offline contexts, running to O(TBytes) per year. Two of the most challenging applications in terms of data volume and access patterns are conditions data, making use of the LHC conditions database, COOL, and the TAG database, that stores summary event quantities allowing a rapid selection of interesting events. Both of these databases are being replicated to regional computing centres using Oracle Streams technology, in collaboration with the LCG 3D project. Database optimisation, performance tests and first user experience with these applications will be described, together with plans for first LHC data-taking and future prospects.

Preparation for WLCG production from a Tier-1 viewpoint

The GRIDPP Tier-1 Centre at RAL is one of 10 Tier-1 centres worldwide preparing for the start of LHC data taking in late 2007. The RAL Tier-1 is expected to provide a reliable grid-based computing service running thousands of simultaneous batch jobs with access to a multi-petabyte CASTOR-managed disk storage pool and tape silo, and will support the ATLAS, CMS and LHCb experiments as well as many other experiments already taking or analysing data. The RAL Tier-1 is already well advanced towards readiness for LHC data-taking. We describe some of the reliability and performance issues encountered with various generations of storage hardware in use at RAL and how the problems were addressed. We also describe the networking challenges for shipping large volumes of data into and out of the Tier-1 storage systems, and system to system within the Tier-1, and the changes made to accommodate the expected data volumes. We describe the scalability and reliability issues encountered with the grid-services and the various strategies used to minimise the impact of problems, including multiplying the number of service hosts, splitting services across a number of hosts, and upgrading services to more resilient hardware.