Trigger Rate Research Articles

Data Acquisition System for the Calorimeter of the Belle II Detector

The electromagnetic CsI(Tl) calorimeter is one of the key systems in the Belle II detector. The calorimeter is aimed primarily at efficiently detecting photons over a wide energy range from several tens of MeV units to $$7$$ GeV. A highly efficient data acquisition system is required for a continuous readout of signal events at a trigger rate corresponding to the maximum collider luminosity. Problems solved by such a system for the calorimeter of the Belle II detector are described.

Trigger Performance Monitoring and Rate Predictions Preparation for Run 3 at ATLAS Experiment

Bespoke Cost Monitoring software collates data on the performance of all aspects of the ATLAS experiment's High Level Trigger software. These data are exported for subsequent analysis offline, and are used to understand the resource usage of the individual trigger selections in terms of the amount of CPU time and the amount of raw detector data which was required to perform the selection. For the LHC's Run 3, the ATLAS High Level Trigger is re-implemented in a multi-threaded framework with both intra-event and inter-event algorithm parallelism. We will describe some of the complications and considerations which arise from monitoring event metrics in a highly parallel environment.

Implementation and Evaluation of an Electronic Maternal Early Warning Trigger Tool to Reduce Maternal Morbidity.

We compare maternal morbidity and clinical care metrics before and after the electronic implementation of a maternal early warning trigger (MEWT) tool. This is a study of maternal morbidity and clinical care within three linked hospitals comparing 1 year before and after electronic MEWT implementation. We compare severe maternal morbidity overall as well as within the subcategories of hemorrhage, hypertension, cardiopulmonary, and sepsis in addition to relevant process metrics in each category. We describe the MEWT trigger rate in addition to MEWT sensitivity and specificity for morbidity overall and by morbidity type. The morbidity rate ratio increased from 1.6 per 100 deliveries in the pre-MEWT period to 2.06 per 100 deliveries in the post-MEWT period (incidence rate ratio = 1.28, p = 0.018); however, in cases of septic morbidity, time to appropriate antibiotics decreased (pre-MEWT: 1.87 hours [1.11-2.63] vs. post-MEWT: 0.75 hours [0.31-1.19], p = 0.036) and in cases of hypertensive morbidity, the proportion of cases treated with appropriate antihypertensive medication within 60 minutes improved (pre-MEWT: 62% vs. post-MEWT: 83%, p = 0.040). The MEWT trigger rate was 2.3%, ranging from 0.8% in the less acute centers to 2.9% in our tertiary center. The MEWT sensitivity for morbidity overall was 50%; detection of hemorrhage morbidity was lowest (30%); however, it ranged between 69% for septic morbidity, 74% for cardiopulmonary morbidity, and 82% for cases of hypertensive morbidity. Overall, maternal morbidity did not decrease after implementation of the MEWT system; however, important clinical metrics such as time to antibiotics and antihypertensive care improved. We suspect increased morbidity was related to annual variation and unexpected lower morbidity in the pre-MEWT comparison year. Because MEWT sensitivity for hemorrhage was low, and because hemorrhage dominates administrative metrics of morbidity, process metrics around sepsis, hypertension, and cardiopulmonary morbidity are important to track as markers of MEWT efficacy. · MEWT was not associated with a decrease in maternal morbidity.. · MEWT was associated with improvements in some clinical care metrics.. · MEWT is more sensitive in detecting septic, hypertensive, and cardiopulmonary morbidities than hemorrhage morbidity..

The ATLAS Muon Spectrometer upgrade for High-Luminosity LHC

The muon spectrometer of the ATLAS detector will undergo a major upgrade in order to cope with the operational conditions at the high-luminosity LHC. The trigger and readout system will need to support Level-0 trigger rates of 1 MHz and a latency of 10 μs. The readout electronics of all the trigger and precision chambers will be replaced and the precision chambers, currently not included in the hardware trigger, will be integrated into the Level-0 trigger in order to sharpen the momentum threshold and increase the system redundancy. New-generation RPC chambers will be installed in the inner barrel layer to increase the acceptance and robustness of the trigger. Some of the MDT chambers in the inner barrel layer will be replaced with new small-diameter MDTs. New TGC triplet chambers will replace the current TGC doublets in the barrel-endcap transition region to enhance the suppression of fake triggers in this region. A major upgrade of the power system is also planned. In this presentation the main detector technology developments of the project will be presented.

Fast convolutional neural networks for identifying long-lived particles in a high-granularity calorimeter

We present a first proof of concept to directly use neural network based pattern recognition to trigger on distinct calorimeter signatures from displaced particles, such as those that arise from the decays of exotic long-lived particles. The study is performed for a high granularity forward calorimeter similar to the planned high granularity calorimeter for the high luminosity upgrade of the CMS detector at the CERN Large Hadron Collider. Without assuming a particular model that predicts long-lived particles, we show that a simple convolutional neural network, that could in principle be deployed on dedicated fast hardware, can efficiently identify showers from displaced particles down to low energies while providing a low trigger rate.

The Risk of Subclinical Breast Cancer-Related Lymphedema by the Extent of Axillary Surgery and Regional Node Irradiation: A Randomized Controlled Trial

To compare the risk of subclinical breast cancer-related lymphedema (sBCRL) using bioimpedance spectroscopy (BIS) or tape measure (TM) by the extent of axillary surgery and regional nodal irradiation (RNI). Patients were randomized to surveillance with TM or BIS. A BIS ≥6.5 L-Dex units or TM volume change ≥5 and <10% above presurgical baselines "triggered" sBCRL. The incidence of sBCRL by sentinel node biopsy or axillary lymph node dissection (ALND) with or without RNI was examined for 484 patients. Radiation was categorized as "limited RNI" (axilla level I/II only) or "extensive RNI" (axilla level III or supraclavicular fossa with or without level I/II). At a median follow-up of 20.5 months, 109 of 498 patients (21.9%) triggered sBCRL (BIS 13.5% vs TM 25.6%; P <.001). In patients not receiving RNI, BIS triggered 12.9% of patients undergoing SNB and 25.0% undergoing ALND (P = .18). Extensive RNI significantly increased triggering with BIS versus no RNI after sentinel node biopsy (SNB; 33.3% vs 12.9%; P = .03) but not ALND (30.8% vs 25.0%; P = .69). Triggering by TM was greater than 25% for most subgroups and was inferior to BIS in discriminating the risk of sBCRL by utilization of RNI or axillary surgery. The lower triggering rates with BIS and its better discrimination of the risk of sBCRL by receipt and type of RNI compared with TM support its use for posttreatment surveillance to detect sBCRL and to initiate early intervention. The risk of sBCRL increased with more extensive axillary treatment. Patients having ALND or extensive RNI require close surveillance for BCRL. Longer follow-up is required to determine rates of progression to clinical lymphedema.

The GlueX beamline and detector

The GlueX experiment at Jefferson Lab has been designed to study photoproduction reactions with a 9-GeV linearly polarized photon beam. The energy and arrival time of beam photons are tagged using a scintillator hodoscope and a scintillating fiber array. The photon flux is determined using a pair spectrometer, while the linear polarization of the photon beam is determined using a polarimeter based on triplet photoproduction. Charged-particle tracks from interactions in the central target are analyzed in a solenoidal field using a central straw-tube drift chamber and six packages of planar chambers with cathode strips and drift wires. Electromagnetic showers are reconstructed in a cylindrical scintillating fiber calorimeter inside the magnet and a lead-glass array downstream. Charged particle identification is achieved by measuring energy loss in the wire chambers and using the flight time of particles between the target and detectors outside the magnet. The signals from all detectors are recorded with flash ADCs and/or pipeline TDCs into memories allowing trigger decisions with a latency of 3.3 μs. The detector operates routinely at trigger rates of 40 kHz and data rates of 600 megabytes per second. We describe the photon beam, the GlueX detector components, electronics, data-acquisition and monitoring systems, and the performance of the experiment during the first three years of operation.

Prognostic relevance of GRACE risk score in Takotsubo syndrome.

Takotsubo syndrome is an increasingly recognised cardiac condition that clinically mimics an acute coronary syndrome, but data regarding its prognosis remain controversial. It is currently unknown whether acute coronary syndrome risk scores could effectively be applied to Takotsubo syndrome patients. This study aims to assess whether the Global Registry of Acute Coronary Events (GRACE) score can predict clinical outcome in Takotsubo syndrome and to compare the prognosis with matched acute coronary syndrome patients. A total of 561 Takotsubo syndrome patients was included in this prospective registry. According to the GRACE score, the population was divided into quartiles. The primary endpoint was all-cause mortality and the secondary endpoints were cardiocerebrovascular events (a composite of all-cause mortality, cardiovascular death, recurrence of Takotsubo syndrome and stroke). The median GRACE risk score was 139±27. Takotsubo syndrome patients with a higher GRACE risk score mostly have a higher rate of physical triggers and lower left ventricular ejection fraction on admission. During long-term follow-up, all-cause mortality rates were 5%, 11%, 12% and 22%, respectively, in the first, second, third and fourth quartile (P<0.001). After multivariate analysis, the GRACE risk score was found to be a strong predictor of all-cause mortality (odds ratio (OR) 1.68, 95% confidence interval (CI) 1.28-2.20; P=0.001) and cardiocerebrovascular events (OR 1.63, 95% CI 1.26-2.11; P=0.001). Moreover, all-cause mortality in Takotsubo syndrome patients was comparable with the matched acute coronary syndrome cohort. In Takotsubo syndrome, the GRACE risk score allows us to predict all-cause mortality and cardiocerebrovascular events at long-term follow-up.

The FAIR Phase 0 program of the CBM TOF

In order to provide particle identification (PID) of charged hadrons at the future high-rate Compressed Baryonic Matter (CBM) experiment, the TOF group has developed a large-area Time-of-Flight (ToF) wall equipped with Multi-gap Resistive Plate Chambers (MRPC) capable to operate at incident particle fluxes of up to 30 kHz/cm2. Prior to its destined operation at the Facility for Antiproton and Ion Research (FAIR)—starting in 2025—this high-rate timing MRPC technology will be used for physics research at two scientific pillars of the FAIR Phase-0 program: the end-cap TOF upgrade of the STAR experiment at RHIC and the mini-TOF (mTOF) wall of the mini-CBM (mCBM) experiment at Schwerionensynchrotron18 (SIS18). At STAR, the fixed-target program of the Beam Energy Scan II (BES-II) will rely on 108 CBM MRPC detectors for forward PID at trigger rates of up to 2 kHz. At mCBM, high-performance benchmark runs of Lambda-baryon production at top SIS18 energies and CBM design interaction rates of 10 MHz will become feasible with a PID backbone consisting of 25 CBM MRPC detectors. Apart from the physics perspective, these pre-FAIR involvements will help gathering experience in operating the final CBM TOF wall comprising about 1500 MRPC detectors and 110,000 readout channels. The status of the FAIR phase 0 program will be discussed.

Performance of the CMS Level-1 trigger in proton-proton collisions at √s = 13 TeV

At the start of Run 2 in 2015, the LHC delivered proton-proton collisions at a center-of-mass energy of 13\\TeV. During Run 2 (years 2015–2018) the LHC eventually reached a luminosity of 2.1× 1034 cm-2s-1, almost three times that reached during Run 1 (2009–2013) and a factor of two larger than the LHC design value, leading to events with up to a mean of about 50 simultaneous inelastic proton-proton collisions per bunch crossing (pileup). The CMS Level-1 trigger was upgraded prior to 2016 to improve the selection of physics events in the challenging conditions posed by the second run of the LHC. This paper describes the performance of the CMS Level-1 trigger upgrade during the data taking period of 2016–2018. The upgraded trigger implements pattern recognition and boosted decision tree regression techniques for muon reconstruction, includes pileup subtraction for jets and energy sums, and incorporates pileup-dependent isolation requirements for electrons and tau leptons. In addition, the new trigger calculates high-level quantities such as the invariant mass of pairs of reconstructed particles. The upgrade reduces the trigger rate from background processes and improves the trigger efficiency for a wide variety of physics signals.

Establishment of a pediatric trigger tool based on Global Trigger Tool to identify adverse drug events of children: experience in a Chinese hospital

BackgroundThe Global Trigger Tool (GTT),which is a method using “triggers” to review medical record retrospectively to identify possible adverse events. Several studies showed that the GTT was effective. However, there were only a few localized trigger tools that had been established to detect pediatric adverse drug events (ADEs) in China. This study aimed to establish a pediatric trigger tool based on GTT, to examine the performance by detecting pediatric inpatients ADEs in a Chinese hospital (a retrospective review), and to investigate the factors associating with the occurrence of ADEs.MethodsThe triggers were established by three steps including literature search, triggers extraction and revision, and experts investigation. A retrospective cohort study was conducted to detect ADEs by using 200 pediatric inpatient records of Sichuan Provincial People’s Hospital.ResultsThirty-three preliminary triggers were established, and 2 rounds of experts investigation were conducted. Finally, 33 triggers were established. In the retrospective review, the positive trigger rate was 64.0%, while the positive predictive value (PPV) was 24.9%. The occurrence of inpatients with ADEs was 20.5%. ADEs/100 admissions were 49.0. ADEs/1000 patient days were 46.89. The most common ADE categories were leukocyte disorders, skin disorders and platelet disorders. The severity of 39 ADEs was grade 1, 55 ADEs was grade 2, 4 ADEs was grade 3. The highest frequency of ADE-related drugs was antineoplastic, followed by antibacterial. The length of stay and the leukemia in the diagnosed diseases were positively correlated with ADEs.ConclusionsThe 33 pediatric triggers may detect ADEs effectively, but still need to be optimized. This study may provide some references for further research in order to improve the rationality and safety of medication.

Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array

ABSTRACTDistributed acoustic sensing is a growing technology that enables affordable downhole recording of strain wavefields from microseismic events with spatial sampling down to ∼1 m. Exploiting this high spatial information density motivates different detection approaches than typically used for downhole geophones. A new machine learning method using convolutional neural networks is described that operates on the full strain wavefield. The method is tested using data recorded in a horizontal observation well during hydraulic fracturing in the Eagle Ford Shale, Texas, and the results are compared to a surface geophone array that simultaneously recorded microseismic activity. The neural network was trained using synthetic microseismic events injected into real ambient noise, and it was applied to detect events in the remaining data. There were 535 detections found and no false positives. In general, the signal‐to‐noise ratio of events recorded by distributed acoustic sensing was lower than the surface array and 368 of 933 surface array events were found. Despite this, 167 new events were found in distributed acoustic sensing data that had no detected counterpart in the surface array. These differences can be attributed to the different detection threshold that depends on both magnitude and distance to the optical fibre. As distributed acoustic sensing data quality continues to improve, neural networks offer many advantages for automated, real‐time microseismic event detection, including low computational cost, minimal data pre‐processing, low false trigger rates and continuous performance improvement as more training data are acquired.

Mobilisation alarm triggers, response times and utilisation before and after the introduction of policy for alarm reduction or elimination: A descriptive and comparative analysis

BackgroundMobilisation alarms are a falls prevention strategy used in hospitals to alert staff when an at risk patient is attempting to mobilise. Mobilisation alarms have an estimated annual cost of $AUD58MIL in Australia. There is growing evidence from randomised controlled trials indicating mobilisation alarms are unlikely to prevent falls. AimThe primary aim of this study was to describe the rate of mobilisation alarm false triggers and staff response time across different health services. The secondary aim was to compare pre to post mobilisation alarm utilisation following the introduction of policy to reduce or eliminate mobilisation alarms. MethodsThis descriptive and comparative study was conducted through Monash Partners Falls Alliance across six health services in Melbourne, Australia. This study described true and false alarm triggers and trigger response times across three health services and usual care mobilisation alarm utilisation across six health services; and then compared alarm utilisation across two health services following the introduction of policy to reduce (<2.5%) or eliminate (0.0%) mobilisation alarms in the acute and rehabilitation settings. ResultsThe most frequent observation was a false alarm (n = 74, 52%), followed by a true alarm (n = 67, 47%) and no alarm (n = 3, 2%). Time to respond to the true and false alarms was an average of 37 seconds (SD 92) and this included 61 occasions of 0 seconds as a member of staff was present when the alarm triggered. If the 61 occasions of staff being present when the alarm triggered were removed, the average time to respond was 65 seconds (SD114). Usual care mobilisation alarm utilisation in acute was 7% (n = 171/2,338) and in rehabilitation was 11% (n = 286/2,623). Introducing policy for reduced and eliminated mobilisation alarm conditions was successful with a reduced utilisation rate of 1.8% (n = 11/609) and an eliminated utilisation rate of 0.0% (n = 0/521). ConclusionHalf of mobilisation alarm triggers are false and when alarms trigger without staff present, staff take about a minute to respond. While usual care has one in fourteen patients in acute and one in nine patients in rehabilitation using a mobilisation alarm, it is possible to introduce policy which will change practice to reduce or eliminate the use of mobilisation alarms, providing evidence of feasibility for future disinvestment effectiveness studies that it is feasible to disinvest in the alarms.

The Phase-2 Upgrade of the Hardware Trigger of CMS at the LHC

The CMS experiment uses a two-level triggering system consisting of the Level-1, instrumented by custom-design hardware boards, and the High Level Trigger, a streamlined version of the offline reconstruction software running on a computer farm. The upgrade of the collider to the “High-Luminosity LHC”, which will deliver a luminosity of 5−7.5 × 1034 cm−2s−1, corresponding to 140–200 pileup events, also necessitates a complete upgrade of the trigger system to make optimal use of the data. An important difference from the present system will be the fact that after the upgrade, information from the silicon strip tracker will be available already for the Level-1 Trigger. This will allow CMS to use so-called “particle flow” objects, i.e. signals seen not only in one subdetector but put together from all available subdetectors, resulting in much sharper efficiency turn-on curves for trigger objects. Also, trigger rates will rise both at Level-1 (from 100 kHz to 750 kHz) and at the High-Level Trigger (from 1 kHz to 7.5 kHz). At the same time, more sophisticated algorithms will be available at Level-1. To make this possible, the latency—the processing time available for arriving at the Level-1 trigger decision—will increase significantly. Machine-learning techniques such as Boosted Decision Trees have already started to be implemented in the trigger electronics and will occupy a more important place in the future. The use of High-Level Synthesis (HLS) tools will allow physicists to formulate trigger requirements in a language closer to that of data analysis. To avoid missing unexpected signatures from New Physics, studies are underway to employ anomaly detection using autoencoders.

Triggering long-lived particles in HL-LHC and the challenges in the first stage of the trigger system

Triggering long-lived particles (LLPs) at the first stage of the trigger system is very crucial in LLP searches to ensure that we do not miss them at the very beginning. The future High Luminosity runs of the Large Hadron Collider will have increased number of pile-up events per bunch crossing. There will be major upgrades in hardware, firmware and software sides, like tracking at level-1 (L1). The L1 trigger menu will also be modified to cope with pile-up and maintain the sensitivity to physics processes. In our study we found that the usual level-1 triggers, mostly meant for triggering prompt particles, will not be very efficient for LLP searches in the 140 pile-up environment of HL-LHC, thus pointing to the need to include dedicated L1 triggers in the menu for LLPs. We consider the decay of the LLP into jets and develop dedicated jet triggers using the track information at L1 to select LLP events. We show in our work that these triggers give promising results in identifying LLP events with moderate trigger rates.

The Phase-2 Upgrade of the CMS Outer Tracker

The Large Hadron Collider(LHC), at CERN will undergo major upgrades to be able to deliver peak instantaneous luminosities of about 5−7.5×1034cm−2s−1 by 2027. This High Luminosity upgrade of the LHC (HL-LHC) is expected to deliver a total of about 3000−4000fb−1 during ten years of operation. At the nominal instantaneous luminosity of the HL-LHC, a single bunch crossing will produce 140−200 proton–proton collisions. The current CMS strip tracker and the CMS Phase-1 pixel detector will not be able to survive the harsh operating conditions of the HL-LHC period. The CMS experiment will install a new silicon tracker for the HL-LHC. The Phase-2 Outer Tracker(OT) will feature increased radiation hardness, higher granularity and track separation and compatibility with higher data rates and a longer trigger latency. In addition, the OT will provide tracking information to the Level-1 trigger, allowing trigger rates to be kept at a sustainable level without sacrificing physics potential. To achieve this, the OT will be made up of modules with two closely spaced sensors read out by a single ASIC. The ASIC will correlate data from both sensors to form short track segments called stubs, to be used in tracking at Level-1. In this contribution, the design of the CMS Phase-2 OT, the technological choices and highlights of the research and development activities will be reported.

Electronics performance of the ATLAS New Small Wheel Micromegas wedges at CERN

A series of upgrades are planned for the LHC accelerator to increase its instantaneous luminosity to 7.5 × 1034 cm−2s−1. The luminosity increase drastically impacts the ATLAS trigger and readout data rates. The present ATLAS small wheel muon detector will be replaced with a New Small Wheel (NSW) detector which is expected to be installed in the ATLAS underground cavern by the end of the Long Shutdown 2 of the LHC . With the final micromegas (MM) quadruplets (modules) already produced the activities concerning the integration of the modules into the final, fully equipped MM wedges, that will then be installed on the wheel structure on surface, are currently in full swing at CERN. One crucial part of the integration procedure concerns the installation, testing and validation of the on-detector electronics and readout chain for a very large system with more than 2.1 millions electronic channels in total. These include ∼4 thousands MM Front-End Boards (MMFE8), custom printed circuit boards each one housing eight 64-channel VMM Application Specific Integrated Circuits (ASICs) that interface with the ATLAS Trigger and Data Acquisition (TDAQ) system through ∼1 thousands data-driver cards (ADDC & L1DDC, respectively). The readout chain is based on optical link technology (GigaBit Transceiver links) connecting the back-end to the front-end electronics via the Front-End LInk eXchange (FELIX), a newly developed system that will serve as the next generation readout driver for ATLAS. Experience and performance results from the first large-scale electronics integration tests performed at CERN on final MM wedges, including system validation with cosmic-rays, are presented.

Data acquisition system for Belle II electromagnetic calorimeter

Since 2018, the Belle II experiment has been running at KEK, at the SuperKEKB B-factory, with all detector subsystems taking data. One of the important detector systems is an electromagnetic calorimeter (ECL) that includes 8736 counters based on CsI(Tl) scintillation crystals. This report describes the data acquisition (DAQ) system that has been developed for ECL. Front-end electronics of ECL DAQ consist of several hundred highly configurable FPGA-controlled modules that utilize pipeline readout architecture and are able to handle a trigger rate up to 30 kHz. ECL front end electronics are initialized, configured and monitored by ECL DAQ software. The initialization library can work with several transport protocols, internally optimize requests to the electronics and perform caching of the configuration data. Configuration software manages and monitors more than 105 electronics parameters and updates them based on the calibrations. Continuous monitoring of ECL data quality is also implemented.

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 responsible for the identification and precise reconstruction of electrons and photons in CMS, which were crucial in the discovery and subsequent characterization of the Higgs boson. It also contributes to the reconstruction of tau leptons, jets, and calorimeter energy sums, which are vital components of many CMS physics analyses. The ECAL trigger system employs fast digital signal processing algorithms to precisely measure the energy and timing information of ECAL energy deposits recorded during LHC collisions. These trigger primitives are transmitted to the Level-1 trigger system at the LHC collision rate of 40 MHz. These energy deposits are then combined with information from other CMS sub-detectors to determine whether the event should trigger the readout of the data from CMS to be transmitted to the High-Level Trigger and eventually to permanent storage. This note will summarize the ECAL trigger performance achieved during LHC Run 2 (2015–2018). It will describe the methods that are used to provide frequent calibrations of the ECAL trigger primitives during LHC operation. These are needed to account for radiation-induced changes in crystal and photodetector response and to maintain stable trigger rates and efficiencies up to 0|η|=3.. They also minimize the spurious triggering on direct signals in the photodetectors used in the barrel region (|η|<1.48). Both of these effects have increased relative to LHC Run 1 (2009–2012), due to the higher luminosities experienced in Run 2. Further improvements in the energy and time reconstruction of the CMS ECAL trigger primitives are being explored for LHC Run 3 (2021–2023), using additional features implemented in the on-detector readout. These are particularly focused on improving the performance at the highest instantaneous luminosities (which will reach or exceed 2⋅ 1034 cm−2 s−1 in Run 3) and in the most forward regions of the calorimeter (|η|>2.5), where the effects of detector aging will be the greatest. The main features of these improved algorithms will be described and preliminary estimates of the expected performance gains will be presented.

Detector Control System for the GE1/1 slice test

Gas Electron Multiplier (GEM) technology, in particular triple-GEM, was selected for the upgrade of the CMS endcap muon system following several years of intense effort on R&D. The triple-GEM chambers (GE1/1) are being installed at station 1 during the second long shutdown with the goal of reducing the Level-1 muon trigger rate and improving the tracking performance in the harsh radiation environment foreseen in the future LHC operation [1]. A first installation of a demonstrator system started at the beginning of 2017: 10 triple-GEM detectors were installed in the CMS muon system with the aim of gaining operational experience and demonstrating the integration of the GE1/1 system into the trigger. In this context, a dedicated Detector Control System (DCS) has been developed, to control and monitor the detectors installed and integrating them into the CMS operation. This paper presents the slice test DCS, describing in detail the different parts of the system and their implementation.