Level Trigger Research Articles

Data-driven design of the Belle II track segment finder

The Belle II experiment relies on a level-1 trigger system to reduce noise background and preselect events of interest for particle physics. The Central Drift Chamber is the main track detector which makes its trigger system important for online track reconstruction. To improve its hit efficiency, an extension of the track segment finder for low angle tracks is proposed. By combining hardware and software development flows, an automated data-driven pipeline is created and three different-sized hardware concepts are implemented. The operation point is adjustable to balance hit efficiency against hit purity in the trigger system.

Commissioning LHCb’s GPU high level trigger

From 2022 onward, the upgraded LHCb experiment will use a triggerless readout system collecting data at an event rate of 30 MHz. A software-only High Level Trigger will enable unprecedented flexibility for trigger selections. During the first stage (HLT1), a sub-set of the full offline track reconstruction for charged particles is run to select particles of interest based on single or two-track selections. This includes decoding the raw data, clustering of hits, pattern recognition, as well as track fitting, ghost track rejection with machine learning techniques and finally event selections. HLT1 will be processed entirely on O(100) GPUs. We will present the integration of the GPU HLT1 into LHCb’s data acquisition system in preparation for data taking in 2022.

Online Event Selection and GPU-based Waveform Compression at the High Level Trigger of the KOTO Experiment

The Data Acquisition (DAQ) system of the KOTO experiment is currently undergoing a major upgrade, following an also ongoing accelerator’s beam intensity upgrade. The throughput of the current DAQ is limited by the hardware, and different prescalings have to be applied to reduce the data rate to a manageable level. The DAQ upgrade aims to remove the hardware bottleneck, increasing the amount of data that reaches the high level trigger system. The new high level trigger will make use of parallelization over CPU and GPU threads to perform event reconstruction, selection, and compression, to eventually allow for more variate physics searches in KOTO.

CMS High Level Trigger performance comparison on CPUs and GPUs

At the start of the upcoming LHC Run-3, CMS will deploy a heterogeneous High Level Trigger (HLT) farm composed of x86 CPUs and NVIDIA GPUs. In order to guarantee that the HLT can run on machines without any GPU accelerators - for example as part of the large scale Monte Carlo production running on the grid, or when individual developers need to optimise specific triggers - the HLT reconstruction has been implemented both for NVIDIA GPUs and for traditional CPUs. This contribution will describe how the CMS software used online and offline (CMSSW) can transparently switch between the two implementations, and compare their performance on GPUs and CPUs from different architectures, vendors and generations.

Performance portability for the CMS Reconstruction with Alpaka

For CMS, Heterogeneous Computing is a powerful tool to face the computational challenges posed by the upgrades of the LHC, and will be used in production at the High Level Trigger during Run 3. In principle, to offload the computational work on non-CPU resources, while retaining their performance, different implementations of the same code are required. This would introduce code-duplication which is not sustainable in terms of maintainability and testability of the software. Performance portability libraries allow to write code once and run it on different architectures with close-to-native performance. The CMS experiment is evaluating performance portability libraries for the near term future.

Data Acquisition Upgrade at KOTO

KOTO is building a new data acquisition system which is a pyramid style architecture, composed of all new homemade optical fiber centers modules with high-speed ports that gather and build the event from over 4000 channels. It will be able to handle up to 30,000 triggers per second with minimal loss in the near future, which is a factor of six more than current rates. This will allow KOTO to handle a higher intensity KL beam, as well as open up the possibility of adding new physics triggers such as one for KL → π 0 e + e −. Additionally, the new architecture simplifies our data handling and allows for greater flexibility in adding late level trigger conditions since the event building is done before the data is sent to the server. This system is robust, flexible and easily scalable in the future and provides a foundation for moving forward to KOTO II.

Developing GPU-compliant algorithms for CMS ECAL local reconstruction during LHC Run 3 and Phase 2

The higher LHC luminosities foreseen in Run 3 (2022+) and during the Phase 2 of the LHC (2029+), and the consequently larger number of simultaneous proton-proton collisions per event, pose significant challenges for the CMS event reconstruction. In particular maintaining the strict time budget for reconstruction algorithms at the CMS software high level trigger will not be possible considering only the expected increase of processing power from conventional CPUs. Therefore, CMS is investigating the use of heterogeneous architectures, including GPU accelerators, to satisfy the needs of the Phase 2 reconstruction. The local reconstruction algorithm of the CMS electromagnetic calorimeter (ECAL) is among the first to be implemented on heterogeneous platforms for LHC Run 3. This article discusses the necessary changes to the CMS software framework that support the execution of code on accelerators. The current development status of the ECAL local reconstruction algorithm is described and first performance results of GPU enabled code are presented.

Restrictive blood transfusion and 1-year mortality in patients undergoing open abdominal surgery: A retrospective propensity score-matched cohort study.

The importance of patient blood management is increasingly recognized in surgery patients. This study aimed to examine the effect of perioperative restrictive blood transfusion on 1-year mortality and blood transfusion rate in open abdominal surgery. We retrospectively studied 452 consecutive patients who underwent open abdominal surgery before (liberal group: 233 patients) and after (restrictive group: 219 patients) implementing intraoperative restrictive transfusion of red blood cell. The trigger levels of hemoglobin were less than 9-10g/dL in the liberal group and less than 7-8g/dL in the restrictive group. All-cause mortality at 1-year as the primary outcome and the transfusion rate of any allogeneic blood products as secondary outcome were compared between the liberal group and the restrictive group by the propensity-score matching. Among a total of 452 patients (69±11yr., 70.5% men), overall mortality at 1year was 8.4% and the proportion of patients who received any allogeneic blood products was 19.6%. Compared with 155 propensity-score matched patients of the liberal group, 155 matched patients of the restrictive group had significantly lower 1-year mortality (4 [2.5%] versus 18 [11.6%], p=0.003, percent absolute risk reduction [%ARR]; 9.0, 95% confidential interval [CI], 3.1-14.7) and had significantly lower proportion of patients who received any allogeneic blood products (21 [13.5%] versus 41 [26.4%], p=0.006, %ARR; 12.9, 95% CI, 3.9-21.5). The results of this study indicate that intraoperative restrictive blood transfusion reduces 1-year mortality and the transfusion rate of allogeneic blood products.

Contingent Convertible Obligations and Financial Stability

This paper investigates whether a financial system can be made more stable if financial institutions share risk by exchanging contingent convertible (CoCo) debt obligations. The question is framed in a financial network model of debt and equity interlinkages with the addition of a variant of the CoCo that converts continuously when a bank’s equity–debt ratio drops to a trigger level. The main theoretical result is a complete characterization of the clearing problem for the interbank debt and equity at the maturity of the obligations. We then introduce stylized networks to study when introducing CoCo bonds improves financial stability, as well as specific networks for which CoCo bonds do not provide uniformly improved system performance. To return to the main question, we examine the European Union financial network at the time of the 2011 European Banking Authority stress test to do comparative statics to study the implications of CoCo debt on financial stability. It is found that by replacing all unsecured interbank debt by standardized CoCo interbank debt securities, systemic risk in the European Union will decrease and bank shareholder value will increase.

Orientational deformations leading to temperature-induced structural phase transition in Prehnite using Raman, Infrared, and Terahertz spectroscopy

Understanding molecular and structural properties of naturally extracted minerals under varying thermodynamic parameters such as pressure (P) and temperature (T) helps us to explore vital information regarding various geological processes. Here, we present the comprehensive results of Raman, infrared (IR), and Terahertz (THz) spectroscopic investigations on Prehnite (Ca2Al(AlSi3O10)(OH)2) mineral from ambient (25 °C) to 1000 °C in the 6.6 – 4000 cm−1 wide spectral range. The results indicate a substantial distortion in orientation between AlO6 octahedron and SiO4 tetrahedron layer leads to the strengthening of hydrogen bonds (HBs) in the Prehnite structure around 800 °C. Consequently, the disappearance of Raman active modes and abrupt change in frequency (ω) of Far-IR modes (obtained using THz spectroscopy) around 800 °C are spectral signatures of symmetry change in the structure. Eventually, these orientational changes at the molecular level trigger structural phase transition around 800 °C, supported by X-ray diffraction (XRD) measurements. Thus, the present study depicts the pivotal role of inter- and intra-molecular interactions in Prehnite, which determines its bonding and structural characteristics and hence its physicochemical properties under diverse environments.

Particle flow reconstruction for the CMS Phase-II Level-1 Trigger

The upgrade of the CMS detector for the high-luminosity LHC will include track-finding for the first time in the Level-1 trigger, enabling Particle Flow reconstruction of every event in addition to comprehensive pileup mitigation. The Correlator trigger will reconstruct isolated leptons and photons, hadronic jets, and energy sums, assisted in many cases by machine learning to benefit from the complete particle-level event record. We present the logic of these algorithms, possible implementations using large FPGAs and their demonstration in prototype hardware, in addition to the expected physics performance.

System design and prototyping for the CMS Level-1 Trigger at the High-Luminosity LHC

For the High-Luminosity Large Hadron Collider, the trigger and data acquisition system of the CMS experiment will be entirely replaced. Novel design choices have been explored, including ATCA prototyping platforms with SoC controllers and newly available interconnect technologies with serial optical links with data rates up to 28 Gb/s. Trigger analyses will be performed through sophisticated algorithms, including widespread use of Machine Learning, in large FPGAs, such as the Xilinx Ultrascale family. The system will process over 50 Tb/s of detector data with an event rate of 750 kHz. We describe system design and prototyping and review trigger algorithm exemplars.

Architecture and prototype of the CMS Global Level-1 Trigger for Phase-2

We present the architecture and current state of prototype firmware of the CMS Level-1 Global Trigger, the final stage of the new Level-1 trigger for Phase-2 of the LHC. Based on high-precision inputs from the muon, calorimeter, track and particle flow triggers, the Global Trigger evaluates O(1000) cut-based and neural-net-based algorithms in a system of up to thirteen Xilinx Ultrascale+ based ATCA processing boards interconnected by 25 Gb/s optical links. In order to optimize the usage of resources, the main algorithms, including the DSP-based calculation of invariant masses, are implemented at 480 MHz.

Multivariate Time Series Clustering of Groundwater Quality Data to Develop Data-Driven Monitoring Strategies in a Historically Contaminated Urban Area

As groundwater quality monitoring networks have been expanded over the last decades, significant time series are now available. Therefore, a scientific effort is needed to explore innovative techniques for groundwater quality time series exploitation. In this work, time series exploratory analysis and time series cluster analysis are applied to groundwater contamination data with the aim of developing data-driven monitoring strategies. The study area is an urban area characterized by several superimposing historical contamination sources and a complex hydrogeological setting. A multivariate time series cluster analysis was performed on PCE and TCE concentrations data over a 10 years time span. The time series clustering was performed based on the Dynamic Time Warping method. The results of the clustering identified 3 clusters associated with diffuse background contamination and 7 clusters associated with local hotspots, characterized by specific time profiles. Similarly, a univariate time series cluster analysis was applied to Cr(VI) data, identifying 3 background clusters and 7 hotspots, including 4 singletons. The clustering outputs provided the basis for the implementation of data-driven monitoring strategies and early warning systems. For the clusters associated with diffuse background contaminations and those with constant trends, trigger levels were calculated with the 95° percentile, constituting future threshold values for early warnings. For the clusters with pluriannual trends, either oscillatory or monotonous, specific monitoring strategies were proposed based on trends’ directions. Results show that the spatio-temporal overview of the data variability obtained from the time series cluster analysis helped to extract relevant information from the data while neglecting measurements noise and uncertainty, supporting the implementation of a more efficient groundwater quality monitoring.

Diabetes mellitus — metabolic preconditioning in protecting the heart from ischemic damage?

The negative impact of diabetes mellitus (DM) on the cardiovascular system has been confirmed by numerous clinical studies. However, there are experimental studies that show an increase in the resistance of the heart to ischemic and reperfusion damage in animals with DM. This phenomenon is characterized by a smaller size of the infarct zone, better preservation of the contractile function of the myocardium, and a lower incidence of ischemic and reperfusion arrhythmias. It is assumed that at a certain stage in the development of DM, a “metabolic window” is formed, in which metabolic alterations at the cellular level trigger adaptive mechanisms that increase the viability of cardiomyocytes. Published data confirm that the magnitude of the protective effect induced by DM is comparable to, and in some cases even exceeds, the effect of the preconditioning phenomenon. It is recognized that the mechanisms that protect the heart from ischemic and reperfusion damage against the background of DM are universal and are associated with the modulation of the antioxidant system, apoptosis factors, pro-inflammatory cytokines, and signaling systems that ensure cell survival. The one of the main pathogenic factor in DM is hyperglycemia, but under stress it plays the role of an adaptive mechanism aimed at meeting the increased energy demand in pathological conditions. Probably, at a certain stage of DM, hyperglycemia becomes a trigger for the development of protective effects and activates not only signaling pathways, but also the restructuring of energy metabolism, which makes it possible to maintain ATP production at a sufficient level to maintain the vital activity of heart cells under ischemia/reperfusion conditions. It is possible that an increased level of glucose, accompanied by the activation of insulin-independent mechanisms of its entry into cells, as well as the availability of this energy substrate, will contribute to a better restoration of energy production in heart cells after a infarction, which, in turn, will significantly reduce the degree of myocardial damage and will help preserve the contractile function of the heart. Identification of the conditions and mechanisms of the cardioprotective phenomenon induced by DM will make it possible to simulate the metabolic state in which the protection of cardiomyocytes from damaging factors is realized.

Profitability Assessment of Sprinkler Irrigated Maize Production in Semi-Arid area of Maiduguri, Borno State, Nigeria

Water has been identified as one of the scarce inputs, which can severely restrict agricultural production and productivity unless it is carefully conserved and managed. Increasing the adoption of irrigation technology is an important requirement for increasing Nigeria’s agricultural productivity. Farmers use the furrow irrigation method and fixed irrigation interval schedule for maize production in this region. The irrigation method used by the farmers has become unsustainable due to low yield, low water use efficiency, low quality of maize kernels and low net farm income. Thus, there is a growing gap between the demand for maize and its production to meet the food requirement for the growing population. The aim of this study was to determine the profitability of sprinkler irrigation method for maize production in semi-arid environment of Nigeria. Two field experiments were conducted in the 2014 and 2015 seasons at the Teaching and Research Farm of Ramat Polytechnic Maiduguri, Borno State which is located in the semi-arid region of Northern Nigeria. The sprinkler irrigation system used consisted of a reservoir, mainline and six laterals spaced 12 meters apart. Each treatment was irrigated using two laterals and each lateral has a control valve for regulating the flow of water. Each lateral consisted of three double nozzle sprinklers spaced 6 meters apart along the lateral. The diameters of the mainline and the laterals were 101.6 and 31.75mm respectively. The area irrigated by the sprinkler system was cleared and marked out into plots of sizes 12m2. Scheduling was on the use of tensiometer, pan evaporation and fixed irrigation interval. Irrigation was conducted in the plots monitored by the tensiometer whenever the trigger level of 30cb is reached. The crops were irrigated at 1.0 IW/CPE ratio for optimum yield based on the evaporation pan method. The profitability analysis result revealed that Sprinkler irrigation was found to be a profitable irrigation method for maize production with net farm income of $460.8 and benefit cost ratio of 1.99. Based on the results, it is recommended that farmers in the semi-arid region of Nigeria should use the sprinkler irrigation method for improved maize production.

Design and initial performance of the prototype for the BEACON instrument for detection of ultrahigh energy particles

The Beamforming Elevated Array for COsmic Neutrinos (BEACON) is a planned neutrino telescope designed to detect radio emission from upgoing air showers generated by ultrahigh energy tau neutrino interactions in the Earth. This detection mechanism provides a measurement of the tau flux of cosmic neutrinos. We have installed an 8-channel prototype instrument at high elevation at Barcroft Field Station, which has been running since 2018, and consists of 4 dual-polarized antennas sensitive between 30–80 MHz, whose signals are filtered, amplified, digitized, and saved to disk using a custom data acquisition system (DAQ). The BEACON prototype is at high elevation to maximize effective volume and uses a directional beamforming trigger to improve rejection of anthropogenic background noise at the trigger level. Here we discuss the design, construction, and calibration of the BEACON prototype instrument. We also discuss the radio frequency environment observed by the instrument, and categorize the types of events seen by the instrument, including a likely cosmic ray candidate event.

Charged particle tracking in real-time using a full-mesh data delivery architecture and associative memory techniques

We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1 triggers) in collider physics experiments. The method described here is based on a full-mesh architecture for data distribution and relies on the Associative Memory approach to implement a pattern recognition algorithm that quickly identifies and organizes hits associated to trajectories of particles originating from particle collisions. We describe a successful implementation of a demonstration system composed of several innovative hardware and algorithmic elements. The implementation of a full-size system relies on the assumption that an Associative Memory device with the sufficient pattern density becomes available in the future, either through a dedicated ASIC or a modern FPGA. We demonstrate excellent performance in terms of track reconstruction efficiency, purity, momentum resolution, and processing time measured with data from a simulated LHC-like tracking detector.

The Event Timing Finder for the Central Drift Chamber Level-1 Trigger at the Belle II experiment

The level-1 trigger system of the Belle II experiment is designed to select physics events of interest with almost 100% efficiency for hadronic events. In terms of event timing decision, the level-1 trigger is required to have an accuracy of less than 10 ns. The Central Drift Chamber (CDC) level-1 trigger provides the event timing information as one of the level-1 timing sources. We developed the new algorithm to measure the event timing with an accuracy of about 10 ns based on the CDC hit timing. Two-dimensional charged track reconstruction by Hough transformation was utilized to reduce high background hits. We used a new-developed general-purpose FPGA board (Universal Trigger board 4) for this module for the first time. We report the performance of the new algorithm using e + e − collision data collected in 2020.

ECAL trigger performance in Run 2 and improvements for Run 3

The CMS electromagnetic calorimeter (ECAL) is a high resolution crystal calorimeter operating at the CERN LHC. It is read out at 40 MHz (the proton-proton collision rate) in order to provide information to the hardware-level (Level-1) trigger system, which decides whether the full CMS detector must be read out for each collision. The ECAL trigger performance achieved during LHC Run 2 (2015-2018) will be presented. The increased luminosity with respect to the LHC Run 1 has required frequent calibrations during LHC operation to account for radiation-induced changes in crystal and photodetector response. Further improvements in the energy and time reconstruction of the CMS ECAL trigger primitives are being explored for LHC Run 3 (2022-24), using additional features implemented in the on-detector readout. In this presentation, we will review the ECAL trigger performance during LHC Run 2 and present improvements to the ECAL trigger system for LHC Run 3.