High Pile-up Environment Research Articles

The development of a laser system for use in the timing performance measurements of CMS HGCAL silicon modules

For optimal operations in the high radiation and pileup environment of the HL-LHC, the CMS-HGCAL requires precise timing information at the level of 30 ps (RMS) for a particle shower. The time measurement in silicon detector modules is performed using a per-channel time-of-arrival discriminator coupled with charge measurement to correct for the time-walk. The module design includes access holes in the PCB and in the sensor passivation to enable infrared laser light to be injected directly into the sensor cells. We present the calibration and timing-in of the system used to perform measurements.

Design of the CMS High Granularity Calorimeter trigger primitive generator system

The High Luminosity phase of the LHC (HL-LHC) is planned to begin data taking in 2029, with the instantaneous luminosity expected to increase to 4 times its current value and the average number of particle interactions per bunch crossing increasing by approximately 3.5 times its current value. The current endcap calorimeters in the CMS detector will be replaced by a novel high granularity calorimeter (HGCAL) that will have fine segmentation in both the transverse and longitudinal directions and will be the first such calorimeter specifically optimised for particle flow reconstruction to operate at a colliding-beam experiment. The Level 1 trigger of the CMS experiment will combine the calorimeter data with tracking information to allow particle-flow techniques to be used. The high granularity of the calorimeter leads to about six million readout channels in total, concentrated in one million trigger cells, sampled for the L1 trigger at a rate of 40 MHz. The trigger data volumes will be an order of magnitude above those currently handled in CMS, posing significant challenges for data manipulation and processing. In addition, the trigger algorithms must be able to efficiently reject the huge background rate in the forward region of the detector due to the high pileup environment. The status of the HGCAL trigger architecture and design, as well as the algorithms developed in order to tackled these major issues, is presented here. The data flow is described from the formation and preselection of trigger cells on detector to the generation of two types of trigger primitives off detector, projective towers of energy in the (η, ϕ) plane and three-dimensional clusters of particles. Particle flow will use these 3D clusters, and their formation is described and followed by recent developments in the optimization of their transverse size.

The CMS Level-1 Calorimeter Trigger for the HL-LHC

The High-Luminosity LHC (HL-LHC) provides an opportunity for a pioneering physics program to harness an integrated luminosity of 4000 fb−1 of ten years of operations. This large volume of collision data will help in high precision measurements of the Standard Model (SM) and the search for new and rare physics phenomena. The harsh environment of 200 proton–proton interactions poses a substantial challenge in the collection of these large datasets. The HL-LHC CMS Level-1 (L1) trigger, including the calorimeter trigger, will receive a massive upgrade to tackle the challenge of a high-bandwidth and high pileup environment. The L1 trigger is planned to handle a very high bandwidth (∼63 Tb/s) with an output rate of 750 kHz, and the desired latency budget is 12.5 μs. The calorimeter trigger aims to process the high-granular information from the new end-cap detector called the high-granularity calorimeter (HGCAL) and the barrel calorimeter. The HL-LHC trigger prototyped boards are equipped with large modern-day FPGAs and high-speed optical links (∼28 Gb/s), which helps in the parallel and rapid computation of the calorimeter trigger algorithms. This article discusses the proposed design and expected performance of the upgraded CMS Level-1 calorimeter trigger system.

MLPF: efficient machine-learned particle-flow reconstruction using graph neural networks

In general-purpose particle detectors, the particle-flow algorithm may be used to reconstruct a comprehensive particle-level view of the event by combining information from the calorimeters and the trackers, significantly improving the detector resolution for jets and the missing transverse momentum. In view of the planned high-luminosity upgrade of the CERN Large Hadron Collider (LHC), it is necessary to revisit existing reconstruction algorithms and ensure that both the physics and computational performance are sufficient in an environment with many simultaneous proton–proton interactions (pileup). Machine learning may offer a prospect for computationally efficient event reconstruction that is well-suited to heterogeneous computing platforms, while significantly improving the reconstruction quality over rule-based algorithms for granular detectors. We introduce MLPF, a novel, end-to-end trainable, machine-learned particle-flow algorithm based on parallelizable, computationally efficient, and scalable graph neural network optimized using a multi-task objective on simulated events. We report the physics and computational performance of the MLPF algorithm on a Monte Carlo dataset of top quark–antiquark pairs produced in proton–proton collisions in conditions similar to those expected for the high-luminosity LHC. The MLPF algorithm improves the physics response with respect to a rule-based benchmark algorithm and demonstrates computationally scalable particle-flow reconstruction in a high-pileup environment.

Performance of the upgraded PreProcessor of the ATLAS Level-1 Calorimeter Trigger

The PreProcessor of the ATLAS Level-1 Calorimeter Trigger prepares the analogue trigger signals sent from the ATLAS calorimeters by digitising, synchronising, and calibrating them to reconstruct transverse energy deposits, which are then used in further processing to identify event features. During the first long shutdown of the LHC from 2013 to 2014, the central components of the PreProcessor, the Multichip Modules, were replaced by upgraded versions that feature modern ADC and FPGA technology to ensure optimal performance in the high pile-up environment of LHC Run 2. This paper describes the features of the new Multichip Modules along with the improvements to the signal processing achieved.

Precision timing calorimetry with the CMS HGCAL

The existing CMS endcap calorimeters will be replaced with a High Granularity Calorimeter (HGCAL) for operation at the High Luminosity (HL) LHC . Radiation hardness and excellent physics performance will be achieved by utilising silicon pad sensors and SiPM-on-scintillator tiles with high longitudinal and transverse segmentation. One of the major challenges of the HL-LHC will be the high pileup environment, with interaction vertices spread not only in position, but also in time. In order to efficiently reject particles originating from pileup, precision timing information of the order of 30 ps will be of great benefit. In order to meet such performance goals, the HGCAL will provide timing measurements for individual hits with signals above 12 fC (equivalent to 3–10 MIPs), such that clusters resulting from particles with pT > 5 GeV should have a timing resolution better than 30 ps. Given the complexity and size of the system, this poses a particular challenge to the readout electronics as well as to the calibration and reconstruction procedures. We present the challenges for the front-end electronics design, results from prototype tests in laboratory and beam environments, as well as anticipated timing performance from simulation.

The Phase-I upgrade of the ATLAS Level-1 calorimeter trigger

The ATLAS Level-1 calorimeter trigger (L1Calo) is a hardware-based system that identifies events containing calorimeter-based physics objects, including electrons, photons, taus, jets, and missing transverse energy. In preparation for Run 3, when the LHC will run at higher energy and instantaneous luminosity, L1Calo is currently implementing a significant programme of planned upgrades. The existing hardware will be replaced by a new system of feature extractor (FEX) modules, which will process finer-granularity information from the calorimeters and execute more sophisticated algorithms to identify physics objects; these upgrades will permit better performance in a challenging high-luminosity and high-pileup environment.

Reconstruction in an imaging calorimeter for HL-LHC

The CMS endcap calorimeter upgrade for the High Luminosity LHC in 2027 uses silicon sensors to achieve radiation tolerance, with the further benefit of a very high readout granularity. Small scintillator tiles with individual SiPM readout are used in regions permitted by the radiation levels. A reconstruction framework is being developed to fully exploit the granularity and other significant features of the detector like precision timing, especially in the high pileup environment of HL-LHC . An iterative clustering framework (TICL) has been put in place, and is being actively developed. The framework takes as input the clusters of energy deposited in individual calorimeter layers delivered by the CLUE algorithm, which has recently been revised and tuned. Mindful of the projected extreme pressure on computing capacity in the HL-LHC era, the algorithms are being designed with modern parallel architectures in mind. Important speedup has recently been obtained for the clustering algorithm by running it on GPUs. Machine learning techniques are being developed and integrated into the reconstruction framework. This paper will describe the approaches being considered and show first results.

LHC searches for Dark Matter in compressed mass scenarios: challenges in the forward proton mode

We analyze in detail the LHC prospects at the center-of-mass enery of sqrt{s} = 14 TeV for charged electroweakino searches, decaying to leptons, in compressed supersymmetry scenarios, via exclusive photon-initiated pair production. This provides a potentially increased sensitivity in comparison to inclusive channels, where the background is often overwhelming. We pay particular attention to the challenges that such searches would face in the hostile high pile-up environment of the LHC, giving close consideration to the backgrounds that will be present. The signal we focus on is the exclusive production of same-flavour muon and electron pairs, with missing energy in the final state, and with two outgoing intact protons registered by the dedicated forward proton detectors installed in association with ATLAS and CMS. We present results for slepton masses of 120–300 GeV and slepton-neutralino mass splitting of 10–20 GeV, and find that the relevant backgrounds can be controlled to the level of the expected signal yields. The most significant such backgrounds are due to semi-exclusive lepton pair production at lower masses, with a proton produced in the initial proton dissociation system registering in the forward detectors, and from the coincidence of forward protons produced in pile-up events with an inclusive central event that mimics the signal. We also outline a range of potential methods to further suppress these backgrounds as well as to enlarge the signal yields.

Comparison of two hardware-based hit filtering methods for trackers in high-pileup environments

As experiments in high energy physics aim to measure increasingly rare processes, the experiments continually strive to increase the expected signal yields. In the case of the High Luminosity upgrade of the LHC, the luminosity is raised by increasing the number of simultaneous proton-proton interactions, so-called pile-up. This increases the expected yields of signal and background processes alike. The signal is embedded in a large background of processes that mimic that of signal events. It is therefore imperative for the experiments to develop new triggering methods to effectively distinguish the interesting events from the background. We present a comparison of two methods for filtering detector hits to be used for triggering on particle tracks: one based on a pattern matching technique using Associative Memory (AM) chips and the other based on the Hough transform. Their efficiency and hit rejection are evaluated for proton-proton collisions with varying amounts of pile-up using a simulation of a generic silicon tracking detector. It is found that, while both methods are feasible options for a track trigger with single muon efficiencies around 98–99%, the AM based pattern matching produces a lower number of hit combinations with respect to the Hough transform whilst keeping more of the true signal hits. We also present the effect on the two methods of increasing the amount of support material in the detector and of introducing inefficiencies by deactivating detector modules. The increased support material has negligable effects on the efficiency for both methods, while dropping 5% (10%) of the available modules decreases the efficiency to about 95% (87%) for both methods, irrespective of the amount of pile-up.

Challenges of Particle Flow reconstruction in the CMS High-Granularity Calorimeter at the High-Luminosity LHC

The challenges of the High-Luminosity LHC (HL-LHC) are driven by the large number of overlapping proton-proton collisions (pileup) in each bunch-crossing and the extreme radiation dose to detectors at high pseudorapidity. To overcome this challenge CMS is developing an endcap electromagnetic+hadronic sampling calorimeter employing silicon sensors in the electromagnetic and front hadronic sections, comprising over 6 million channels, and highly-segmented plastic scintillators in the rear part of the hadronic section. This High- Granularity Calorimeter (HGCAL) will be the first of its kind used in a colliding beam experiment. Clustering deposits of energy over many cells and layers is a complex and challenging computational task, particularly in the high-pileup environment of HL-LHC. Baseline detector performance results are presented for electromagnetic and hadronic objects, and studies demonstrating the advantages of fine longitudinal and transverse segmentation are explored.

A Characterisation of the ATLAS ITk High Rapidity Modules in AllPix and EUTelescope

The upgrade of the LHC to the high luminosity LHC (HL-LHC) will result in far more collisions occurring per bunch crossing, in turn producing more particles per second. Consequently, the current detectors will need to be upgraded to accommodate the large increase in radiation and data acquisition as well as a need to improve the tracking efficiency for the high pile-up environment. One of the main upgrades to the ATLAS detector is the complete overhaul of the inner detector (ID) by replacing it with an all silicon Inner Tracker (ITk). A simulation of the ITk will be required for performance predictions as well as for testing sample sensors in testbeams. The current testbeam software of Allpix and EUTelescope are written completely using Cartesian definitions, however some of the geometries in the ITk have radial definitions. In particular, the R0 geometry of the strip end-cap is in need of a radial description. Presented is the work behind creating a radial geometry for the R0 module in Allpix (using Geant4 descriptions) and EUTelescope (using TGeo descriptions).

Primary vertex reconstruction with the ATLAS detector

Efficient and precise reconstruction of the primary vertex in a LHC collision is essential for determining the full kinematic properties of a hard-scatter event and of soft interactions as a measure of the amount of pile-up. The reconstruction of primary vertices in the busy, high pile-up environment of Run-2 of the LHC is a challenging task. The algorithms developed by the ATLAS experiments to reconstruct multiple vertices with small spatial separation are presented.

Boosting Higgs pair production in the [Formula: see text] final state with multivariate techniques.

The measurement of Higgs pair production will be a cornerstone of the LHC program in the coming years. Double Higgs production provides a crucial window upon the mechanism of electroweak symmetry breaking and has a unique sensitivity to the Higgs trilinear coupling. We study the feasibility of a measurement of Higgs pair production in the bbar{b}bbar{b} final state at the LHC. Our analysis is based on a combination of traditional cut-based methods with state-of-the-art multivariate techniques. We account for all relevant backgrounds, including the contributions from light and charm jet mis-identification, which are ultimately comparable in size to the irreducible 4b QCD background. We demonstrate the robustness of our analysis strategy in a high pileup environment. For an integrated luminosity of {mathcal {L}}=3 ab^{-1}, a signal significance of S/sqrt{B}simeq 3 is obtained, indicating that the bbar{b}bbar{b} final state alone could allow for the observation of double Higgs production at the High Luminosity LHC.

CMS muon system towards LHC Run 2 and beyond

The CMS muon system has played a key role for many physics results obtained from the LHC Run 1 data. The LHC will increase the beam energy as well as progressively increase the peak instantaneous luminosity in Run 2 and in the following years. Significant consolidation and upgrade activities are ongoing, in order to improve the CMS muon detectors and trigger performance and robustness. With LHC and then HL-LHC running beyond 2030, the large accumulated radiation dose, the high pileup environment, and the ageing of several detector and electronics components become challenges that can only be met with further development and upgrade work. We will introduce the CMS muon system and present the consolidation work in preparation for LHC Run 2. We will then describe the main constraints and the solutions proposed for the upgrade of the muon detector system towards HL-LHC.

The ATLAS jet trigger performance in LHC Run I and Run II updates

The Large Hadron Collider (LHC) provides proton-proton collisions with a nominal rate of 40 MHz, and the ATLAS trigger performs the first event selections online during data- taking. The ATLAS jet trigger is an important element of the ATLAS trigger system, selecting collision events containing high transverse energy jets, to provide data samples for studies ranging from Standard Model physics to searches for new physics at the LHC. During LHC Run I, the first LHC operation period from 2010 to 2012, the ATLAS jet trigger system improved as experience developed with triggering in a high luminosity and high event pileup environment. For the next LHC operation period, Run II, the system is being updated for further improved performance and stability. In this contribution, performance and improvements of the ATLAS jet trigger in Run I are presented. Updates for Run II are also shown.

The study of QCD in high pile-up environments: Higgs boson and Drell-Yan production

In the forthcoming high-luminosity phase of the LHC many of the most interesting measurements for precision QCD studies are hampered by large pile-up conditions, especially at not very high transverse momenta. However, with the recently discovered Higgs boson, which couples in the heavy top limit directly to gluons, we have access to a novel production process to probe QCD by a colour-singlet current. In this study we compare observables in Higgs boson and Drell-Yan production and investigate whether measuring ratios or subtractions can yield results that are stable in high pile-up environments, and yet sensitive to (small-p T ) QCD physics in gluon fusion processes. We present results of Monte Carlo event generator calculations for a few specific examples.

Silicon sensors with various pixel geometries adapted for a common readout ASIC

ATLAS is proposing to replace the entire tracking system for HL-LHC operation. The ``Letter of Intent'' baseline pixel size at higher radii was 50 × 250μm2 (φ × η), based on the FE-I4 readout chip, and this was optimized for the central barrel region. The detector tracking performance in the end-cap pixel disks can benefit from enhanced resolution in the radial direction to improve the impact parameter resolution in z-coordinate (along the beam line) for high η tracks, which is critical in the high pile-up environment of the HL-LHC. So called ``strixel'' geometries, with long narrow pixels, can be proposed at higher z in the barrel where tracks pass through at large angles. Larger pixels may also be considered for an additional pixel layer if this could reduce the requirements, and therefore costs, for the outer part of the tracker.While ATLAS pixel upgrade plans are evolving, the demonstration of providing a variety of sensor pixel shapes and sizes for a common ASIC pixel geometry will be of general application, whatever the final ASIC design.This paper will report on the development and testing of pixel sensors with several different dimensions assembled into modules with the FE-I4 readout chip. Some of these were irradiated (with protons, 1015 neq/cm2) and evaluated at the DESY test beam. These, together with the test beam results with non-irradiated sensors, will be shown, as well as the results from laboratory characterization.

The design and performance of the ATLAS jet trigger

The ATLAS jet trigger is an important element of the event selection process, providing data samples for studies of Standard Model physics and searches for new physics at the LHC. The ATLAS jet trigger system has undergone substantial modifications over the past few years of LHC operations, as experience developed with triggering in a high luminosity and high event pileup environment. In particular, the region-of-interest based strategy has been replaced by a full scan of the calorimeter data at the third trigger level, and by a full scan of the level-1 trigger input at level-2 for some specific trigger chains. Hadronic calibration and cleaning techniques are applied in order to provide improved performance and increased stability in high luminosity data taking conditions. In this note we discuss the implementation and operational aspects of the ATLAS jet trigger during 2011 and 2012 data taking periods at the LHC.

Pileup Subtraction for Jet Shapes

Jets in high energy hadronic collisions often contain the fingerprints of the particles that produced them. Those fingerprints, and thus the nature of the particles that produced the jets, can be read off with the help of quantities known as jet shapes. Jet shapes are, however, severely affected by pileup, the accumulation in the detector of the residues of the many simultaneous collisions taking place in the Large Hadron Collider (LHC). We introduce a method to correct for pileup effects in jet shapes. Relative to earlier, limited approaches, the key advance resides in its full generality, achieved through a numerical determination, for each jet, of a given shape's susceptibility to pileup. The method rescues the possibility of using jet shapes in the high pileup environment of current and future LHC running, as we show with examples of quark-gluon discrimination and top tagging.