With increasing instantaneous luminosity at the LHC come additional reconstruction challenges. At high luminosity, many collisions occur simultaneously within one proton-proton bunch crossing. The isolation of an interesting collision from the additional "pileup" collisions is needed for effective physics performance. In the CMS Collaboration, several techniques capable of mitigating the impact of these pileup collisions have been developed. Such methods include charged-hadron subtraction, pileup jet identification, isospin-based neutral particle "$δβ$" correction, and, most recently, pileup per particle identification. This paper surveys the performance of these techniques for jet and missing transverse momentum reconstruction, as well as muon isolation. The analysis makes use of data corresponding to 35.9 fb$^{-1}$ collected with the CMS experiment in 2016 at a center-of-mass energy of 13 TeV. The performance of each algorithm is discussed for up to 70 simultaneous collisions per bunch crossing. Significant improvements are found in the identification of pileup jets, the jet energy, mass, and angular resolution, missing transverse momentum resolution, and muon isolation when using pileup per particle identification.
The performance of missing transverse momentum reconstruction algorithms is presented using 8 TeV pp collision data collected with the CMS detector, corresponding to an integrated luminosity of $12.2 \pm 0.5$ $\mathrm{fb^{-1}}$. The scale and resolution of missing transverse momentum and the effects of multiple proton-proton interactions (pileup), are measured using events with an identified Z boson or isolated photon. They are in general well described by the simulation. Advanced missing transverse momentum reconstruction algorithms are also developed specifically to mitigate the effects of l…
With the planned addition of tracking information to the Compact Muon Solenoid (CMS) Level-1 trigger for the High-Luminosity Large Hadron Collider (HL-LHC), the trigger algorithms can be completely reconceptualized. We explore the feasibility of using particle flow-like reconstruction and pileup per particle identification (PUPPI) pileup mitigation at the hardware trigger level. This represents a new type of multi-subdetector pattern recognition challenge for the HL-LHC. We present proof-of-principle studies on both physics and hardware-resource performance of a prototype algorithm for use by …
The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and re…
The performance of missing transverse energy reconstruction algorithms is presented using sqrt(s) = 8 TeV proton-proton (pp) data collected with the CMS detector. Events with anomalous missing transverse energy are studied, and the performance of algorithms used to identify and remove these events is presented. The scale and resolution for missing transverse energy, including the effects of multiple pp interactions (pileup), are measured using events with an identified Z boson or isolated photon, and are found to be well described by the simulation. Novel missing transverse energy reconstructi…
The High Luminosity LHC (HL-LHC) will integrate 10 times more luminosity than the LHC, posing significant challenges for radiation tolerance and event pileup on detectors, especially for forward calorimetry, and hallmarks the issue for future colliders. As part of its HL-LHC upgrade program, the CMS collaboration is designing a High Granularity Calorimeter to replace the existing endcap calorimeters. It features unprecedented transverse and longitudinal segmentation for both electromagnetic (ECAL) and hadronic (HCAL) compartments. This will facilitate particle-flow calorimetry, where the fine …
The High Luminosity LHC (HL-LHC) will integrate 10 times more luminosity than the LHC, posing significant challenges for radiation tolerance and event pileup on detectors, especially for forward calorimetry, and hallmarks the issue for future colliders. As part of its HL-LHC upgrade program, the CMS collaboration is designing a High Granularity Calorimeter to replace the existing endcap calorimeters. It features unprecedented transverse and longitudinal segmentation for both electromagnetic (ECAL) and hadronic (HCAL) compartments. This will facilitate particle-flow calorimetry, where the fine …
University of Cambridge（剑桥大学）；California Institute of Technology（加州理工学院）；CERN（欧洲核子研究组织）
At the Large Hadron Collider, the high transverse-momentum events studied by experimental collaborations occur in coincidence with parasitic low transverse-momentum collisions, usually referred to as pileup. Pileup mitigation is a key ingredient of the online and offline event reconstruction as pileup affects the reconstruction accuracy of many physics observables. We present a classifier based on Graph Neural Networks, trained to retain particles coming from high-transverse-momentum collisions, while rejecting those coming from pileup collisions. This model is designed as a refinement of the …
Pileup involves the contamination of the energy distribution arising from the primary collision of interest (leading vertex) by radiation from soft collisions (pileup). We develop a new technique for removing this contamination using machine learning and convolutional neural networks. The network takes as input the energy distribution of charged leading vertex particles, charged pileup particles, and all neutral particles and outputs the energy distribution of particles coming from leading vertex alone. The PUMML algorithm performs remarkably well at eliminating pileup distortion on a wide ran…
The high instantaneous luminosity of the CERN Large Hadron Collider leads to multiple proton-proton interactions in the same or nearby bunch crossings (pileup). Advanced pileup mitigation algorithms are designed to remove this noise from pileup particles and improve the performance of crucial physics observables. This study implements a semi-supervised graph neural network for particle-level pileup noise removal, by identifying individual particles produced from pileup. The graph neural network is firstly trained on charged particles with known labels, which can be obtained from detector measu…
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 $\times$ 10$^{34}$ cm$^{-2}$ s$^{-1}$, 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 th…
To maximise the potential for new measurements and discoveries at the LHC, the machine delivers as high as possible collision rates. As a consequence, multiple proton-proton collisions occur whenever two bunches cross. Interesting high-energy (hard) collisions are therefore contaminated by several soft, zero-bias, ones. This effect known as pileup pollutes the final state of the collision. It complicates the reconstruction of the objects in this final state, resulting in increased experimental uncertainties. To reduce these uncertainties, and improve the quality and precision of LHC measuremen…
The High-Luminosity LHC is expected to deliver proton-proton collisions every 25 ns with an estimated 140-200 pileup interactions per bunch crossing. Ultrafast track finding is vital for handling Level 1 trigger rates in such conditions. An FPGA-based track trigger system, capable of finding tracks with momenta above 2 GeV, is presented.
The CMS experiment has been designed with a two-level trigger system: the Level-1 Trigger, implemented on custom-designed electronics, and the High Level Trigger, a streamlined version of the CMS offline reconstruction software running on a computer farm. During its second phase the LHC will reach a luminosity of $7.5\times10^{34}\,\textrm{cm}^{-2}\,\textrm{s}^{-1}$ with a pileup of 200 collisions, producing integrated luminosity greater than 3000 fb$^{-1}$ over the full experimental run. To fully exploit the higher luminosity, the CMS experiment will introduce a more advanced Level-1 Trigger …
The foreseen upgrade of the LHC to its high luminosity phase (HL-LHC), will maximize the physics potential of the facility. The upgrade is expected to increase the instantaneous luminosity by a factor of 5 and deliver an integrated luminosity of 3000 fb-1 after 10 years of operation. As a result of the corresponding increase in radiation and pileup, the electromagnetic calorimetry in the CMS endcaps will sustain maximum integrated doses of 1.5 MGy and neutron fluences above 1e16 neq/cm2, necessitating their replacement for HL-LHC operation. The CMS collaboration has decided to replace the exis…
The use of charged pileup tracks in a jet to predict the neutral pileup component in that same jet could potentially lead to improved pileup removal techniques, provided there is a strong local correlation between charged and neutral pileup. In Monte Carlo simulation we find that the correlation is however moderate, a feature that we attribute to characteristics of the underlying non-perturbative dynamics. Consequently, `neutral-proportional-to-charge' (NpC) pileup mitigation approaches do not outperform existing, area-based, pileup removal methods. This finding contrasts with the arguments ma…
The CMS muon system has played a key role for many physics results obtained from the LHC Run-1 data. During the Long Shutdown (2013-2014) significant upgrades have been carried out on the muon detectors and on the L1 muon trigger. In parallel the algorithms for muon reconstruction and identification have been improved for both the High-Level Trigger and the offline reconstruction. Results of studies performed on data and Monte Carlo simulations will be presented, with focus on the improvements aiming to ensure an excellent performance in conditions of multiplicity of pileup events and bunch sp…
As part of the Phase II upgrade program, the Compact Muon Solenoid (CMS) detector will incorporate a new timing layer designed to measure minimum ionizing particles (MIPs) with a time resolution of $\sim$30 ps. Precision timing will mitigate the impact of the challenging levels of pileup expected at the High Luminosity LHC. The time information assigned to each track will enable the use of 4D-vertexing which will render a 5-fold pile-up reduction, thus recovering the current conditions. Precision timing will also enable new time-based isolations and improved $b$-tagging algorithms. All of this…
The CMS experiment makes use of a large variety of algorithms to identify the origin of particle jets measured in the detector. Through the study of jet substructure properties, jets originating from quarks, gluons, W/Z/Higgs bosons, top quarks and pileup interactions are identified and categorized. We present new techniques based on machine learning approaches developed for the analysis of the data collected during the LHC Run 2 that significantly surpass the performances of classical taggers.
We propose a new method for pileup mitigation by implementing "pileup per particle identification" (PUPPI). For each particle we first define a local shape $α$ which probes the collinear versus soft diffuse structure in the neighborhood of the particle. The former is indicative of particles originating from the hard scatter and the latter of particles originating from pileup interactions. The distribution of $α$ for charged pileup, assumed as a proxy for all pileup, is used on an event-by-event basis to calculate a weight for each particle. The weights describe the degree to which particles ar…
We investigate how a Generative Adversarial Network could be used to generate a list of particle four-momenta from LHC proton collisions, allowing one to define a generative model that could abstract from the irregularities of typical detector geometries. As an example of application, we show how such an architecture could be used as a generator of LHC parasitic collisions (pileup). We present two approaches to generate the events: unconditional generator and generator conditioned on missing transverse energy. We assess generation performances in a realistic LHC data-analysis environment, with…
In planning for the Phase II upgrades of CMS and ATLAS major considerations are: 1)being able to deal with degradation of tracking and calorimetry up to the radiation doses to be expected with an integrated luminosity of 3000 $fb^{-1}$ and 2)maintaining physics performance at a pileup level of ~140. Here I report on work started within the context of the CMS Forward Calorimetry Task Force and continuing in an expanded CERN RD52 R$&$D program integrating timing (i.e. measuring the time-of-arrival of physics objects) as a potential tool for pileup mitigation and ideas for Forward Calorimetry. Fo…
Measurements of jet energy scale (JES) and resolution (JER) are presented, based on the legacy reconstruction of 13 TeV proton-proton collision data collected by the CMS experiment during the LHC Run 2 period from 2016-2018. Precision measurement of JES is of the utmost importance for the vast majority of physics measurements and searches at CMS. The high pileup, a harsh radiation environment, and time-dependent variations in detector response and calibration, all make precision JES measurement a challenging task. We present in-situ derivations of JES and JER based on CMS Run 2 data, as well a…
A search for central exclusive production of top quark pairs ($\mathrm{t}\bar{\mathrm{t}}$) is presented using collision data collected by CMS and the CMS-TOTEM Precision Proton Spectrometer in 2017. A data-driven method to estimate the background from coincidences of inclusive events and pileup protons is described, as well as the development of a Boosted Decision Tree classifier to separate the exclusive $\mathrm{t}\bar{\mathrm{t}}$ signal from the inclusive $\mathrm{t}\bar{\mathrm{t}}$ background. The first-ever upper limits on the cross section of exclusive $\mathrm{t}\bar{\mathrm{t}}$ are…
The High-Luminosity LHC (HL-LHC) will usher in a new era in high-energy physics. The HL-LHC experimental conditions entail an instantaneous luminosity of up to $7.5 \times 10^{34}$ cm$^{-2}$ s$^{-1}$ and up to 200 simultaneous collisions per bunch crossing (pileup). To cope with those conditions, the CMS detector will undergo a series of improvements, in what is known as the Phase-2 upgrade. In particular, the upgrade of the Data Acquisition and of the High-Level Trigger (DAQ-HLT) will have to address a much higher event rate and more complex events. In this paper, we will discuss the aspects …
The performance of missing transverse momentum (${\vec p}_{\mathrm{T}}^\mathrm{miss}$) reconstruction algorithms for the CMS experiment is presented, using proton-proton collisions at a center-of-mass energy of 13 TeV, collected at the CERN LHC in 2016. The data sample corresponds to an integrated luminosity of 35.9 fb$^{-1}$. The results include measurements of the scale and resolution of ${\vec p}_{\mathrm{T}}^\mathrm{miss}$, and detailed studies of events identified with anomalous ${\vec p}_{\mathrm{T}}^\mathrm{miss}$. The performance is presented of a ${\vec p}_{\mathrm{T}}^\mathrm{miss}$ …
The LHC is undergoing a high luminosity upgrade, which is set to increase the instantaneous luminosity by at least a factor of five, resulting in a higher muon flux rate in the forward region, which will overwhelm the current trigger system of the CMS experiment. The ME0, a gas electron multiplier detector, is proposed for the Phase-2 Muon System Upgrade to help increase the muon acceptance and to control the Level 1 muon trigger rate. To lower the probability of HV discharges, the ME0 was designed with GEM foils that are segmented on both sides. Initial testing of the ME0 showed substantial c…
Jets are one of the most prominent physics signatures of high energy proton proton (p-p) collisions at the Large Hadron Collider (LHC). They are key physics objects for precision measurements and searches for new phenomena. This review provides an overview of the reconstruction and calibration of jets at the LHC during its first Run. ATLAS and CMS developed different approaches for the reconstruction of jets, but use similar methods for the energy calibration. ATLAS reconstructs jets utilizing input signals from their calorimeters and use charged particle tracks to refine their energy measurem…
Improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 inverse-femtobarns collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented. The corrections as a function of pseudorapidity eta and transverse momentum pT are extracted from data and simulated events combining several channels and methods. They account successively for the effects of pileup, uniformity of the detector response, and residual data-simulation jet energy scale differences. Further corrections, depending on the jet fl…
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material effects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filter-based methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant…
Building particle tracks is the most computationally intense step of event reconstruction at the LHC. With the increased instantaneous luminosity and associated increase in pileup expected from the High-Luminosity LHC, the computational challenge of track finding and fitting requires novel solutions. The current track reconstruction algorithms used at the LHC are based on Kalman filter methods that achieve good physics performance. By adapting the Kalman filter techniques for use on many-core SIMD architectures such as the Intel Xeon and Intel Xeon Phi and (to a limited degree) NVIDIA GPUs, we…
At hadron colliders, top quarks are dominantly produced in pairs ($t\bar{t}$), a production mechanism that was discovered more than twenty years ago at the Tevatron in Fermilab. Although the \ttbar process has already entered the domain of "precision" physics, especially with the advent of the multi-TeV energies at the CERN LHC, there still remains room for dedicated experimental measurements of the top quark in the "gap" of energies between Tevatron and LHC. Hence, in the study presented here the total inclusive cross section for pair production at a center-of-mass energy of 5.02 TeV is measu…
We explore the metric space of jets using public collider data from the CMS experiment. Starting from 2.3/fb of 7 TeV proton-proton collisions collected at the Large Hadron Collider in 2011, we isolate a sample of 1,690,984 central jets with transverse momentum above 375 GeV. To validate the performance of the CMS detector in reconstructing the energy flow of jets, we compare the CMS Open Data to corresponding simulated data samples for a variety of jet kinematic and substructure observables. Even without detector unfolding, we find very good agreement for track-based observables after using c…
During the upcoming High Luminosity phase of the Large Hadron Collider (HL-LHC), the integrated luminosity of the accelerator will increase to 3000 fb$^{-1}$. The expected experimental conditions in that period in terms of background rates, event pileup, and the probable aging of the current detectors present a challenge for all the existing experiments at the LHC, including the Compact Muon Solenoid (CMS) experiment. To ensure a highly performing muon system for this period, several upgrades of the Resistive Plate Chamber (RPC) system of the CMS are currently being implemented. These include …
High Multiplicity Trigger for Long-Lived Particles in CMS detector
University of California, Davis（加州大学戴维斯分校）；Rice University（莱斯大学）；California Institute of Technology（加州理工学院）；Fermi National Accelerator Laboratory（费米国家加速器实验室）；University of Florida（佛罗里达大学）；Northeastern University（东北大学）；Institute of Experimental Physics, Faculty of Physics, University of Warsaw（华沙大学物理学院实验物理研究所）；University of California, Santa Barbara（加州大学圣塔芭芭拉分校）；University of California, Los Angeles（加州大学洛杉矶分校）；Institute of High Energy Physics（高能物理研究所）；University of California, Riverside（加州大学河滨分校）；The Ohio State University（俄亥俄州立大学）；CERN, European Organization for Nuclear Research（欧洲核子研究组织（CERN））；University of Wisconsin--Madison（威斯康星大学麦迪逊分校）；Boston University（波士顿大学）；Riga Technical University（里加技术大学）；Institute of High Energy Physics of the Austrian Academy of Sciences（奥地利科学院高能物理研究所）；Seoul National University（首尔国立大学）；University of Nebraska-Lincoln（内布拉斯加大学林肯分校）
Bose-Einstein correlations of charged hadrons are measured over a broad multiplicity range, from a few particles up to about 250 reconstructed charged hadrons in proton-proton collisions at $\sqrt{s} =$ 13 TeV. The results are based on data collected using the CMS detector at the LHC during runs with a special low-pileup configuration. Three analysis techniques with different degrees of dependence on simulations are used to remove the non-Bose-Einstein background from the correlation functions. All three methods give consistent results. The measured lengths of homogeneity are studied as functi…
Progress towards an improved particle flow algorithm at CMS with machine learning
University of California San Diego（加州大学圣地亚哥分校）；NICPB（国家化学物理与生物物理研究所）；European Organization for Nuclear Research (CERN)（欧洲核子研究组织）；California Institute of Technology（加州理工学院）
Manchester Metropolitan University（曼彻斯特城市大学）；CERN（欧洲核子研究组织）；Florida State University（佛罗里达州立大学）；Massachusetts Institute of Technology（麻省理工学院）；Staffordshire University（斯塔福德郡大学）
We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular calorimeters similar to that foreseen for the high-luminosity upgrade of the CMS detector. The algorithm exploits a distance-weighted graph neural network, trained with object condensation, a graph segmentation technique. Through a single-shot approach, the reconstruction task is paired with energy regression. We describe the reconstruction performance in terms of efficiency as well as in terms of energy resolution. In addition, we show the jet reconstruction performanc…
Recent interest in pile-up mitigation through fast timing at the HL-LHC has focused attention on technologies that now achieve minimum ionising particle (MIP) time resolution of 30 picoseconds or less. The constraints of technical maturity and radiation tolerance narrowed the options in this rapidly developing field for the ATLAS and CMS upgrades to low gain avalanche detectors and silicon photomultipliers. In a variety of applications where occupancies and doses are lower, devices with pixel elements of order 1 cm$^2$, nevertheless achieving 30 ps, would be attractive. In this paper, deep dif…
Jet substructure has provided new opportunities for searches and measurements at the LHC, and has seen continuous development since the optimization of the large-radius jet definition used by ATLAS was performed during Run 1. A range of new inputs to jet reconstruction, pile-up mitigation techniques and jet grooming algorithms motivate an optimisation of large-radius jet reconstruction for ATLAS. In this paper, this optimisation procedure is presented, and the performance of a wide range of large-radius jet definitions is compared. The relative performance of these jet definitions is assessed …
Jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how…
