Level Trigger Research Articles

World Experience in Rationing the Content of Chemical Elements in the Soil

Timely development of standards for soil quality is a prerequisite for environmental management. In Russia, the content in the soil of chemical elements (CE) is insufficiently studied, which is one of the reasons for the small number of developed not only maximum permissible, but also approximately permissible concentrations of CE in the soil. To solve the problem of rationing soil quality in Russia, the experience of such countries as Holland, Finland, Canada, and Germany can be adapted to domestic realities. So, to justify the production and economic standards, Finnish guideline values and Dutch intervention levels can be used; for soil assessment of playgrounds and residential areas – trigger levels of Germany, for residential and park areas and farmland – the relevant Canadian standards.

Search for pair-produced three-jet resonances in proton-proton collisions at s=13 TeV

A search has been performed for pair-produced resonances decaying into three jets. The proton-proton collision data used for this analysis were collected with the CMS detector in 2016 at a center-of-mass energy of 13 TeV and correspond to an integrated luminosity of 35.9 fb$^{-1}$. The mass range from 200 to 2000 GeV is explored in four separate mass regions. The observations show agreement with standard model expectations. The results are interpreted within the framework of $R$-parity violating SUSY, where pair-produced gluinos decay to a six quark final state. Gluino masses below 1500 GeV are excluded at 95% confidence level. An analysis based on data with multijet events reconstructed at the trigger level extends the reach to masses as low as 200 GeV. Improved analysis techniques have led to enhanced sensitivity, allowing the most stringent limits to date to be set on gluino pair production.

Particle Flow reconstruction in the CMS Level-1 Trigger For The HL-LHC

With the planned addition of the tracking information in the Level-1 trigger in CMS for the High-Luminosity Large Hadron Collider (HL-LHC), the algorithms for the Level-1 trigger can be completely reconceptualized. Following the example for offline reconstruction in CMS to use complementary subsystem information and mitigate pileup, we explore the feasibility of using Particle Flow-like and pileup-per-particle identification techniques at the hardware trigger level. We present the challenges of adapting these algorithm to the timing and resource constraints of the Level-1 trigger, the first prototype implementations, and the expected performance on physics object reconstruction.

Simultaneous usage of the LHCb HLT farm for Online and Offline processing workflows

LHCb is one of the 4 LHC experiments and continues to revolutionise data acquisition and analysis techniques. Already two years ago the concepts of “online” and “offline” analysis were unified: the calibration and alignment processes take place automatically in real time and are used in the triggering process such that Online data are immediately available offline for physics analysis (Turbo analysis), the computing capacity of the HLT farm has been used simultaneously for different workflows : synchronous first level trigger, asynchronous second level trigger, and Monte-Carlo simulation. Thanks to the same software environment, LHCb can switch seamlessly and fast from Online to Offline workflows, run them simultaneously and thus maximize the usage of the HLT farm computing resources.

Design and performance of the CMS High Granularity Calorimeter Level 1 trigger

The high luminosity (HL) LHC will pose significant detector challenges for radiation tolerance and event pileup, especially for forward calorimetry, and this will provide a benchmark for future hadron colliders. The CMS experiment has chosen a novel high granularity calorimeter (HGCAL) for the forward region as part of its planned Phase 2 upgrade for the HL-LHC. Based largely on silicon sensors, the HGCAL features unprecedented transverse and longitudinal readout segmentation, which will be exploited in the upgraded Level 1 (L1) trigger system. Together with the tracking information, which will also be available at L1, this will open the possibility of pioneering particle-flow-based techniques in the L1 trigger. The high channel granularity results in around one million trigger channels in total and so presents a significant challenge in terms of data manipulation and processing for the trigger, to be compared with the 2000 channels in the endcaps of the current detector. In addition, the high luminosity will result in an average of 140 interactions per bunch crossing that give a huge background rate in the forward region and these will need to be efficiently rejected by the trigger algorithms. Furthermore, 3-dimensional reconstruction of the HGCAL clusters, which will be used for particle-flow, in events with high hit rates is also a complex computational problem for the trigger, unprecedented with the 2-dimensional reconstruction in the current CMS calorimeter trigger. The status of the trigger architecture and design, as well as the concepts for the algorithms needed in order to tackle these major issues and their impact on trigger object performance, are presented here.

Operational experience with the new CMS DAQ-Expert

The data acquisition (DAQ) system of the Compact Muon Solenoid (CMS) at CERN reads out the detector at the level-1 trigger accept rate of 100 kHz, assembles events with a bandwidth of 200 GB/s, provides these events to the high level-trigger running on a farm of about 30k cores and records the accepted events. Comprising custom-built and cutting edge commercial hardware and several 1000 instances of software applications, the DAQ system is complex in itself and failures cannot be completely excluded. Moreover, problems in the readout of the detectors,in the first level trigger system or in the high level trigger may provoke anomalous behaviour of the DAQ systemwhich sometimes cannot easily be differentiated from a problem in the DAQ system itself. In order to achieve high data taking efficiency with operators from the entire collaboration and without relying too heavily on the on-call experts, an expert system, the DAQ-Expert, has been developed that can pinpoint the source of most failures and give advice to the shift crew on how to recover in the quickest way. The DAQ-Expert constantly analyzes monitoring data from the DAQ system and the high level trigger by making use of logic modules written in Java that encapsulate the expert knowledge about potential operational problems. The results of the reasoning are presented to the operator in a web-based dashboard, may trigger sound alerts in the control room and are archived for post-mortem analysis - presented in a web-based timeline browser. We present the design of the DAQ-Expert and report on the operational experience since 2017, when it was first put into production.

Upgrade of the ATLAS Tile Calorimeter for the High Luminosity LHC

The Tile Calorimeter (TileCal) is the hadronic calorimeter covering the central region of the ATLAS experiment. TileCal is a sampling calorimeter with steel as absorber and scintillators as active medium. The scintillators are read-out by wavelength shifting fibers coupled to photomultiplier tubes (PMTs). The analogue signals from the PMTs are amplified, shaped, digitized by sampling the signal every 25 ns and stored on detector until a trigger decision is received. The High-Luminosity phase of LHC (HL-LHC) expected to begin data taking in 2026 requires readout electronics suitable for a 1 MHz trigger rate, higher ambient radiation, and for better performance under high pileup. Both the on- and off-detector TileCal electronics will be replaced during the shutdown of 2024-2025. PMT signals from every TileCal cell will be digitized and sent directly to the back-end electronics, where the signals are reconstructed, stored, and sent to the first trigger level at a rate of 40 MHz. This will provide better precision of the calorimeter signals used by the trigger system and will allow the development of more complex trigger algorithms. Changes to the electronics will also enhance the data integrity and reliability of the system. Three front-end board options were built and investigated both in laboratory and in several beam test campaigns. The final version has been chosen after evaluating the results. A hybrid Demonstrator for the new readout architecture and compatible with the present system has been developed, adopting the new chosen front-end option. The Demonstrator is undergoing extensive testing and is planned for future insertion in ATLAS.

New method of out-of-time energy subtraction for the CMS hadronic calorimeter

The CMS hadronic calorimeter employs plastic scintillator active material in the barrel and endcap (HBHE). In Run 2, the LHC operates at 13 TeV center-of-mass energy with up to 50 simultaneous collisions per bunch crossing (pileup) and a 25 ns bunch spacing. The HBHE scintillator light pulse is only 60% contained in a 25 ns window, resulting in significant pulse overlap for consecutive events (out-of-time pileup). This talk presents a novel algorithm that will be used in 2018 for subtracting out-of-time pileup in HBHE both online in the software trigger and offline. The algorithm includes methods for both the barrel with hybrid photodiode photosensors and QIE8 digitizers, and the endcap with silicon photomultipliers and QIE11 digitizers, including the challenging charge-dependent pulse shaping effects of the QIEs. The on-detector pulse shape measurement method and results are also shown. The new algorithm is five-to-ten times faster than the previous one, and for the first time CMS will use the offline method at the trigger level.

Trigger Rate Monitoring Tools at CMS

One of the major challenges for the Compact Muon Solenoid (CMS)experiment, is the task of reducing event rate from roughly 40 MHz down to a more manageable 1 kHz while keeping as many interesting physics events as possible. This is accomplished through the use of a Level-1 (L1) hardware based trigger as well as a software based High-Level Trigger (HLT). Monitoring and understanding the output rates of the L1 and HLT triggers is of key importance for determining the overall performance of the trigger system and is intimately tied to what type of data is being recorded for physics analyses. We present here a collection of tools used by CMS to monitor the L1 and HLT trigger rates. One of these tools is a script (run in the CMS control room) that gives valuable real-time feedback of trigger rates to the shift crew. Another useful tool is a plotting library, that is used for observing how trigger rates vary over a range of beam and detector conditions, in particular how the rates of individual triggers scale with event pile-up.

Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm

The Simulation at Point1 (Sim@P1) project was established in 2013 to take advantage of the Trigger and Data Acquisition High Level Trigger (HLT) farm of the ATLAS experiment at the LHC. The HLT farm is a significant compute resource, which is critical to ATLAS during data taking. This large compute resource is used to generate and process simulation data for the experiment when ATLAS is not recording data. The Sim@P1 system uses virtual machines, deployed by OpenStack, in order to isolate the resources from the ATLAS technical and control network. During the upcoming long shutdown in 2019 (LS2), the HLT farm including the Sim@P1 infrastructure will be upgraded. A previous paper on the project emphasized the need for “simple, reliable, and efficient tools” to quickly switch between data acquisition operation and offline processing. In this contribution we assess various options for updating and simplifying the provisional tools. Cloudscheduler is a tool for provisioning cloud resources for batch computing that has been managing cloud resources in HEP offline computing since 2012. We present the argument for choosing Cloudscheduler, and describe technical details regarding optimal utilization of the Sim@P1 re-sources.

Run Control Software For The Upgrade Of The Atlas Muon To Central Trigger Processor Interface (MUCTPI)

The Muon to Central Trigger Processor Interface (MUCTPI) of the ATLAS experiment at the Large Hadron Collider(LHC) at CERN is being upgraded for the next run of the LHC in order to use optical inputs and to provide full-precision information for muon candidates to the topological trigger processor (L1TOPO) of the Level-1 trigger system. The new MUCTPI is implemented as a single ATCA blade with high-end processing FPGAs which eliminate doublecounting of muon candidates in overlapping regions, send muon candidates to L1TOPO, and muon multiplicities tothe Central Trigger Processor (CTP), as well as readout data to the data acquisition system of the experiment. A Xilinx Zynq System-on-Chip (SoC) with a programmable logic part and a processor part is used for the communication to the processing FPGAs and the run control system. The processor part, based on ARM processor cores, is running embedded Linux prepared using the framework of the Linux Foundation's Yocto project. The ATLAS run control software was ported to the processor part and a run control application was developed which receives, at configuration, all data necessary for the overlap handling and candidate counting of the processing FPGAs. During running, the application provides ample monitoring of the physics data and of the operation of the hardware. *

The ATLAS High-Level Calorimeter Trigger in Run-2

The ATLAS Experiment uses a two-level triggering system to identify and record proton-proton collision events containing a wide variety of physics signatures. It reduces the event rate from the bunch crossing rate of 40 MHz to an average recording rate of 1 kHz, whilst maintaining high efficiency for interesting collision events. It is composed of an initial hardware-based level-1 trigger followed by a software-based high-level trigger. A central component of the high-level trigger is the calorimeter trigger. This is responsible for processing data from the electromagnetic and hadronic calorimeters in order to identify electrons, photons, taus, jets and missing transverse energy. This paper presents the performance of the high-level calorimeter trigger in Run-2, noting the improvements that have been made in response to the challenges of operating at high luminosity.

The Impact of Applying Wildcards to Disabled Modules for Ftk Pattern Banks on Efficiency and Data Flow

Online selection is an essential step to collect the most relevant collisions from the very large number of collisions inside the ATLAS detector at the Large Hadron Collider (LHC). The Fast TracKer (FTK) is a hardware based track finder, built to greatly improve the ATLAS trigger system capabilities for identifying interesting physics processes through track-based signatures. The FTK is reconstructing after each Level-1 trigger all tracks with pT > 1 GeV, such that the high-level trigger system gains access to track information at an early stage. FTK track reconstruction starts with a pattern recognition step. Patterns are found with hits in seven out of eight possible detector layers. Disabled detector modules, as often encountered during LHC operation, lead to efficiency losses. To recover efficiency, WildCards (WC) algorithms are implemented in the FTK system. The WC algorithm recovers inefficiency but also causes high combinatorial background and thus increased data volumes in the FTK system, possibly exceeding hardware limitations. To overcome this, a refined algorithm to select patterns is developed and investigated in this article.

Evolution of the ALICE Software Framework for Run 3

ALICE is one of the four major LHC experiments at CERN. When the accelerator enters the Run 3 data-taking period, starting in 2021, ALICE expects almost 100 times more Pb-Pb central collisions than now, resulting in a large increase of data throughput. In order to cope with this new challenge, the collaboration had to extensively rethink the whole data processing chain, with a tighter integration between Online and Offline computing worlds. Such a system, code-named ALICE O2, is being developed in collaboration with the FAIR experiments at GSI. It is based on the ALFA framework which provides a generalized implementation of the ALICE High Level Trigger approach, designed around distributed software entities coordinating and communicating via message passing. We will highlight our efforts to integrate ALFA within the ALICE O2 environment. We analyze the challenges arising from the different running environments for production and development, and conclude on requirements for a flexible and modular software framework. In particular we will present the ALICE O2 Data Processing Layer which deals with ALICE specific requirements in terms of Data Model. The main goal is to reduce the complexity of development of algorithms and managing a distributed system, and by that leading to a significant simplification for the large majority of the ALICE users.

Design of the CMS calorimeter trigger upgrade from Phase I to Phase II of the LHC

The CMS experiment implements a sophisticated two-level triggering system composed of the Level-1, instrumented by custom-design hardware boards, and the software High Level Trigger. In 2017, the LHC delivered proton-proton collisions at a centre-of-mass energy of 13 TeV with a peak instantaneous luminosity larger than 2×1034 cm−2s−1, more than twice the peak luminosity reached during Run I and far larger than the design value. The CMS Level-1 calorimeter trigger was upgraded during the long shutdown 1 between 2013 and 2015, to improve its performance at high luminosity and large number of simultaneous inelastic collisions per crossing (pile-up). All the electronic boards have been replaced, tested and commissioned with data. Smarter, more sophisticated, and innovative algorithms are now the core of the first decision layer of CMS: the upgraded trigger system implements dynamic clustering techniques, pile-up subtraction and isolation requirements for electrons and tau leptons. In addition, the new global trigger is capable of computing complex variables such as those involving the invariant mass of trigger objects. The trigger selections used for a wide variety of physics signals during Run II are presented, ranging from simple single-object selections to more sophisticated algorithms combining different objects and applying analysis-level reconstruction and selection. The design and operation of the Phase I calorimeter trigger will be reviewed. The technological choices made influenced the path towards the Phase II upgrade system necessary for the LHC run at a center-of mass energy of 14 TeV with luminosity of 5−7×1034 cm−2s−1, corresponding to 140-200 pile-up events. The addition of the tracker information at Level-1 and the enhanced calorimeter granularity will be used to maintain the trigger object thresholds at a similar level as the present system.

Implementation Of The Atlas Trigger Within The Multithreaded Athenamt Framework

We present an implementation of the ATLAS High Level Trigger (HLT) that provides parallel execution of trigger algorithms within the ATLAS multithreaded software framework, AthenaMT. This development will enable the HLT to meet future challenges from the evolution of computing hardware and upgrades of the Large Hadron Collider (LHC) and ATLAS Detector. During the LHC data-taking period starting in 2021, luminosity will reach up to three times the original design value. In the following data-taking period (2026) upgrades to the ATLAS trigger architecture will increase the HLT input rate by a factor of 4-10, while the luminosity will increase by a further factor of 2-3. AthenaMT provides a uniform interface for offine and trigger algorithms, facilitating the use of offine code in the HLT. Trigger-specific optimizations provided by the framework include early event rejection and reconstruction within restricted geometrical regions. We report on the current status, including experience of migrating trigger selections to this new framework,and present the next steps towards a full implementation of the redesigned ATLAS trigger.

Experience with dynamic resource provisioning of the CMS online cluster using a cloud overlay

The primary goal of the online cluster of the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is to build event data from the detector and to select interesting collisions in the High Level Trigger (HLT) farm for offline storage. With more than 1500 nodes and a capacity of about 850 kHEPSpecInt06, the HLT machines represent similar computing capacity of all the CMS Tier1 Grid sites together. Moreover, it is currently connected to the CERN IT datacenter via a dedicated 160 Gbps network connection and hence can access the remote EOS based storage with a high bandwidth. In the last few years, a cloud overlay based on OpenStack has been commissioned to use these resources for the WLCG when they are not needed for data taking. This online cloud facility was designed for parasitic use of the HLT, which must never interfere with its primary function as part of the DAQ system. It also allows to abstract from the different types of machines and their underlying segmented networks. During the LHC technical stop periods, the HLT cloud is set to its static mode of operation where it acts like other grid facilities. The online cloud was also extended to make dynamic use of resources during periods between LHC fills. These periods are a-priori unscheduled and of undetermined length, typically of several hours, once or more a day. For that, it dynamically follows LHC beam states and hibernates Virtual Machines (VM) accordingly. Finally, this work presents the design and implementation of a mechanism to dynamically ramp up VMs when the DAQ load on the HLT reduces towards the end of the fill.

Alice Overwatch: Online Monitoring and Data Quality Assurance Using Hlt Data

ALICE Overwatch is a project started in late 2015 to provide augmented online monitoring and data quality assurance utilizing time-stamped QA histograms produced by the ALICE High Level Trigger. The system receives the data via ZeroMQ, stores it for later review, enriches it with detector specific functionality, and visualizes it via a web application. These provided capabilities are complementary to the existing Data Quality Monitoring system. In addition to basic visualization, additional processing options are accessible to the user, including requests for data within a particular time range or reprocessing of a particular run with different processing parameters. For example, the first ten minutes of a particular run could be investigated for a transient hot trigger channel.Due to similarities between the Overwatch architecture and that which will be used for Quality Control (QC) in LHC Run 3 and beyond, Overwatch will also be utilized to develop and test various QC components during LHC Run 2. Some of the areas of QC development include a new trending and alarm framework. We report on the project᠙s design, development, and status.

Analysis of ELVES at the Pierre Auger Observatory

In the last six years, the Fluorescence Detector (FD) of the Auger Observatory has been exploited for the study of transient luminous events occuring high above thunderstorms at large distances (250 to more than 1000 km) from the Observatory. The first ELVES candidate was discovered during a night shift in 2005, and further studies based on auxiliary subtriggers allowed to modify the third level trigger of the observatory in order to acquire them with reasonable efficiency. This report aims to briefly review the studies underway on the >4000 ELVES triggers harvested in the years 2013-18 by the Observatory.

LHCb High Level Trigger in remote IT datacentre

In 2017 the CERN IT department and the major LHC experiments reviewed the possibility to build a common High Level Trigger facility, to share costs and for a more efficient utilization of computing resources. This paper describes a Proof-of-Concept built by the CERN IT-CS group and the LHCb online and offline teams to demonstrate the feasibility of the proposal: the dedicated, high speed connection between the LHCb detector and the IT data-centre, the setup of the servers and how they were used for offline simulation and online data taking, the different technologies considered and used, the challenges encountered and how they were tackled. The Proof of Concept exceed expectations and the remote servers were used for real data taking for more than two months during the summer 2018.