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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Enriching the physics program of the CMS experiment via data scouting and data parking

Specialized data-taking and data-processing techniques were introduced by the CMS experiment in Run 1 of the CERN LHC to enhance the sensitivity of searches for new physics and the precision of standard model measurements. These techniques, termed data scouting and data parking, extend the data-taking capabilities of CMS beyond the original design specifications. The novel data-scouting strategy trades complete event information for higher event rates, while keeping the data bandwidth within limits. Data parking involves storing a large amount of raw detector data collected by algorithms with low trigger thresholds to be processed when sufficient computational power is available to handle such data. The research program of the CMS Collaboration is greatly expanded with these techniques. The implementation, performance, and physics results obtained with data scouting and data parking in CMS over the last decade are discussed in this Report, along with new developments aimed at further improving low-mass physics sensitivity over the next years of data taking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

The CMS Statistical Analysis and Combination Tool: Combine

This paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Evaluation of 3D pixel silicon sensors for the CMS Phase-2 Inner Tracker

The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R&D program, aiming at using 3D pixel silicon sensors in the innermost barrel layer of the detector, has been carried out by CMS in collaboration with the FBK (Trento, Italy) and CNM (Barcelona, Spain) foundries. The sensors will feature a pixel cell size of 25 × 100 µm 2 , with a centrally located electrode connected to the readout chip. The sensors are read out by the RD53A and CROCv1 chips, developed in 65 nm CMOS technology by the RD53 Collaboration, a joint effort between the ATLAS and CMS groups. This paper reports the results achieved in beam test experiments before and after irradiation, up to a fluence of approximately 2 . 6 × 1 0 16 n eq /cm 2 . Measurements of assemblies irradiated to a fluence of 1 × 10 16 n˙eq/cm 2 show a hit detection efficiency higher than 96% at normal incidence, with fewer than 2% of channels masked, across a bias voltage range greater than 50 V . Even after irradiation to a higher fluence of 1.6 × 10 16 n˙eq/cm 2 , similar performance is maintained over a bias voltage range of 30 V , remaining well within CMS requirements.

3D pixel↗
DOE OSTI2018

Operational Experience With the GEM Detector Assembly Lines for the CMS Forward Muon Upgrade

The CMS Collaboration has been creating large-area triple-gas electron multiplier (GEM) detectors to be installed in the muon Endcap regions of the CMS experiment in 2019 to maintain forward muon trigger and tracking performance at the High-Luminosity upgrade of the Large Hadron Collider (LHC); 10 preproduction detectors were built at CERN to commission the first assembly line and the quality controls (QCs). These were installed in the CMS detector in early 2017 and participated in the 2017 LHC run. The collaboration has prepared several additional assembly and QC lines for distributed mass production of 160 GEM detectors at various sites worldwide. In 2017, these additional production sites have optimized construction techniques and QC procedures and validated them against common specifications by constructing additional preproduction detectors. Using the specific experience from one production site as an example, we report on how the QCs make use of independent hardware and trained personnel to ensure fast and reliable production. Preliminary results on the construction status of CMS GEM detectors are presented with details of the assembly sites involvement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Triggering on New Physics with the CMS Detector

The BU CMS group led by PI Tulika Bose has made several significant contributions to the CMS trigger and to the analysis of the data collected by the CMS experiment. Group members have played a leading role in the optimization of trigger algorithms, the development of trigger menus, and the online operation of the CMS High-Level Trigger. The group’s data analysis projects have concentrated on a broad spectrum of topics that take full advantage of their strengths in jets and calorimetry, trigger, lepton identification as well as their considerable experience in hadron collider physics. Their publications cover several searches for new heavy gauge bosons, vector-like quarks as well as diboson resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

“Exploring High Energy Interactions with CMS at the LHC”

This High Energy Physics research project achieved its goal of exploring high-energy interactions with 7, 8 and 13 TeV data accumulated by CMS at the Energy Frontier. For the original hadron calorimeter (HCAL) and for its upgrade during Long Shutdown 1 (LS1), the PI helped propose and implement the upgrading the phototubes, new electronics, and fast timing of the hadronic forward (HF) and hadronic outer (HO) calorimeters of CMS, projects which he had forcefully advocated since the inception of CMS. The PI and his colleagues Prof. J. Rohlf and chief electronics engineer E. Hazen, his post-docs A. Heister and S. Girgis, and his graduate students (P. Lawson and D. Arcaro) contributed software tools used in perfecting of μTCA and Advanced Mezzanine Card (AMC13) electronics, the PC board that provides clock, timing and DAQ service for HCAL (and now many other subdetectors and central systems in the upgraded CMS detector). This Task reaped the benefits of these hardware contributions 1) to hermiticity for missing energy searches, and 2) to forward tagging jets for Vector Boson Fusion processes by analyzing and publishing early data, including that for the Higgs discovery and for exotic and supersymmetric searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Quest for a Top Quark Partner and Upgrade of the Pixel Detector Readout Chain at the CMS

After the observation of a new particle at CERN experiments, which is consistent with being the Higgs boson, the partner of the top quark is the most anticipated candidate to be discovered next. In many extensions of the standard model of particle physics the principle of naturalness dictates that the top quark partner should exist and be relatively light, at or below the TeV scale. It is hence expected to be accessible at energies and luminosities provided by the LHC machine within the next years of running. This proposal calls for supporting the effort targeting the searches for the top quark partner at the CMS experiment. We focus on scenarios and techniques that have not yet been fully explored at CMS, and that carry a large potential for new physics discovery in the immediate future. The second part of the proposal focuses on the R&D effort aiming for continuing high-quality physics program at the CMS at the high instantaneous luminosities. We propose to take one of the leading roles in the forthcoming upgrade of the Pixel detector at the CMS, and upgrade the data acquisition readout chain that would increase the data volume throughput for the new detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2018

GES DISC Long-Term Data Analysis Services Using AIRS and CMS Methane Data as an Example

NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes rich collections of data on atmospheric greenhouse gases from multiple satellite missions and model results. Among those greenhouse gases, atmospheric methane is a powerful greenhouse gas contributing ~0.5 (W/m^2) to total radiative forcing, and its concentration has increased by about 150% since 1750. Observations or estimates of methane emissions typically have sparse spatial and temporal coverage. The lack of comprehensive spatial and temporal coverage of methane source and sink observations has made analyzing atmospheric methane trends challenging. In this study the GES DISC aims to provide the community with the resources to better understand changes in atmospheric methane concentrations and the underlying causes. We will utilize methane datasets from Atmospheric Infrared Sounder (AIRS) retrieved methane concentration and three Carbon Monitoring System (CMS) methane emission datasets (in regions of North America, Canada, and Mexico) to compare AIRS methane growth with corresponding CMS regional methane emissions. Comparisons of AIRS methane growth rates and CMS methane emissions suggests wetland emissions may impact methane growth rate trends over North America. As the record for CMS methane data is extended, both datasets can be used in conjunction to better understand impacts on atmospheric methane trends. GES DISCs new anomaly tool can also be used on select datasets to further quantify trends in atmospheric greenhouse gases.

long-term data analysis↗
DOE OSTI2023

Long-lived heavy neutral leptons with a displaced shower signature at $\mathrm{CMS}$

We study the LHC discovery potential in the search for heavy neutral leptons (HNL) with a new signature: a displaced shower in the CMS muon detector, giving rise to a large cluster of hits forming a displaced shower. A new Delphes module is used to model the CMS detector response for such displaced decays. We reinterpret a dedicated CMS search for neutral long-lived particles decaying in the CMS muon endcap detectors for the minimal HNL scenario. We demonstrate that this new strategy is particularly sensitive to active-sterile mixings with τ leptons, due to hadronic τ decays. HNL masses between ~ 1–6 GeV can be accessed for mixings as low as |V τN | 2 ~10 -7 , probing unique regions of parameter space in the τ sector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its architecture, implementation, deployment, and integration with the CMS and CERN computing infrastructures, such as central HDFS and Hadoop Spark cluster. The system leverages modern technologies such as a document oriented database and the Hadoop eco-system to provide the necessary flexibility to reliably process, store, and aggregate $\mathcal{O}$(1M) documents on a daily basis. We describe the data transformation, the short and long term storage layers, the query language, along with the aggregation pipeline developed to visualize various performance metrics to assist CMS data operators in assessing the performance of the CMS computing system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Autoencoder-Based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter

The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online data quality monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. A real-time autoencoder-based anomaly detection system using semi-supervised machine learning is presented enabling the detection of anomalies in the CMS electromagnetic calorimeter data. A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. The autoencoder-based system is able to efficiently detect anomalies, while maintaining a very low false discovery rate. The performance of the system is validated with anomalies found in 2018 and 2022 LHC collision data. In addition, the first results from deploying the autoencoder-based system in the CMS online data quality monitoring workflow during the beginning of Run 3 of the LHC are presented, showing its ability to detect issues missed by the existing system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Structure–Transport Relationships of Water–Organic Solvent Co-transport in Carbon Molecular Sieve (CMS) Membranes

We explore the effects of the carbon molecular sieve (CMS) microstructure on the separation performance and transport mechanism of water–organic mixtures. Specifically, we utilize PIM-1 dense films and integrally skinned asymmetric hollow fiber membranes as polymer precursors for the CMS materials. The PIM-1 membranes were pyrolyzed under several different pyrolysis atmospheres (argon, carbon dioxide, and diluted hydrogen gas) and at multiple pyrolysis temperatures. Detailed gas physisorption measurements reveal that membranes pyrolyzed under 4% H 2 and CO 2 had broadened ultramicropore distributions (pore diameter <7 Å) compared to Ar pyrolysis, and pyrolysis under CO 2 increased ultramicropore volume and broadened micropore distributions at increased pyrolysis temperatures. Gravimetric water and p-xylene sorption and diffusion measurements reveal that the PIM-1-derived CMS materials are more hydrophilic than other CMS materials that have been previously studied, which leads to sorption-diffusion estimations showing water-selective permeation. Water permeation in the vapor phase, pervaporation, and liquid-phase hydraulic permeation reveal that the isobaric permeation modes (vapor permeation and pervaporation) are reasonably well predicted by the sorption-diffusion model, whereas the hydraulic permeation mode is significantly underpredicted (>250×). Conversely, the permeation of p-xylene is well predicted by the sorption-diffusion model in all cases. The collection of pore size analysis, vapor sorption and diffusion, and permeation in different modalities creates a picture of a combined transport mechanism in which water–under high transmembrane pressures–permeates via a Poiseuille-style mechanism, whereas p-xylene solutes in the mixture permeate via sorption-diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Current and Future Performance of the CMS Simulation

The CMS full simulation using Geant4 has delivered billions of simulated events for analysis during Runs 1 and 2 of the LHC. However, the HL-LHC dataset will be an order of magnitude larger, with a similar increase in occupancy per event. In addition, the upgraded CMS detector will be considerably more complex, with an extended silicon tracker and a high granularity calorimeter in the endcap region. Increases in conventional computing resources are subject to both technological and budgetary limitations, so novel approaches are needed to improve software efficiency and to take advantage of new architectures and heterogeneous resources. Several projects are in development to address these needs, including the vectorized geometry library Vec-Geom and the GeantV transport engine, which uses track-level parallelization. The current computing performance of the CMS simulation will be presented as a baseline, along with an overview of the various optimizations already available for Geant4. Finally, the progress and outlook for integrating VecGeom and GeantV in the CMS software framework will be discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Full Simulation of CMS for Run-3 and Phase-2

In this contribution we report the status of the CMS Geant4 simulation and the prospects for Run-3 and Phase-2. Firstly, we report about our experience during the start of Run-3 with Geant4 10.7.2, the common software package DD4hep for geometry description, and VecGeom runtime geometry library. In addition, FTFP_BERT_EMM Physics List and CMS configuration for tracking in magnetic field have been utilized. For the first time, for the Grid mass production of Monte-Carlo, this combination of components is used. Further simulation improvements are under development targeting Run-3 such as the switch to the new Geant4 11.1 in production, that provides several features important for the optimization of simulation, for example the new transportation process with built-in multiple scattering, neutron general process, custom tracking manager, G4HepEm sub-library, and others. We will present evaluation of various options, validation results, and the final choice of simulation configuration for 2023 production and beyond. The performance of the CMS full simulation for Run-2 and Run-3 will also be discussed. CMS development plan for the Phase-2 Geant4 based simulation is very ambitious, and it includes a new geometry description, physics, and simulation configurations. The progress on new detector descriptions and full simulation will be presented as well as the R&D in progress to reduce compute capacity needs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Optimization of distributed compute resources utilization in the CMS Global Pool

The CMS Submission Infrastructure is the primary system for managing computing resources for CMS workflows, including data processing, simulation, and analysis. It integrates geographically distributed resources from Grid, HPC, and cloud providers into federated pools managed by HTCondor and Glidein- WMS, for a total of around 500k CPU cores. This system dynamically manages workloads based on priorities defined by the collaboration. Additionally, CMS scheduling strategies must be flexible to handle multiple concurrent workloads while considering changing processing demands and resource availability from various providers.Efficient utilization of vast amounts of distributed compute resources is a key element for the success of the scientific programs of the LHC experiments. Optimizing the system is essential to maximize resource efficiency and fully utilize the distributed computing power. The CMS Submission Infrastructure team thus systematically investigates sources of inefficiency in workload scheduling to reduce their impact. In addition, a strategy of pilot overloading has been introduced to compensate for other inefficiency sources, thereby optimizing resource utilization and enhancing computational throughput.

Mascheroni, Marco [UC, San Diego (main)]↗
DOE OSTI2018

CMS Analysis and Data Reduction with Apache Spark

Experimental Particle Physics has been at the forefront of analyzing the world's largest datasets for decades. The HEP community was among the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems for distributed data processing, collectively called "Big Data" technologies have emerged from industry and open source projects to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and tools, promising a fresh look at analysis of very large datasets that could potentially reduce the time-to-physics with increased interactivity. Moreover these new tools are typically actively developed by large communities, often profiting of industry resources, and under open source licensing. These factors result in a boost for adoption and maturity of the tools and for the communities supporting them, at the same time helping in reducing the cost of ownership for the end-users. In this talk, we are presenting studies of using Apache Spark for end user data analysis. We are studying the HEP analysis workflow separated into two thrusts: the reduction of centrally produced experiment datasets and the end-analysis up to the publication plot. Studying the first thrust, CMS is working together with CERN openlab and Intel on the CMS Big Data Reduction Facility. The goal is to reduce 1 PB of official CMS data to 1 TB of ntuple output for analysis. We are presenting the progress of this 2-year project with first results of scaling up Spark-based HEP analysis. Studying the second thrust, we are presenting studies on using Apache Spark for a CMS Dark Matter physics search, comparing Spark's feasibility, usability and performance to the ROOT-based analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

The CMS data analysis school experience

The CMS Data Analysis School is an official event organized by the CMS Collaboration to teach students and post-docs how to perform a physics analysis. The school is coordinated by the CMS schools committee and was first implemented at the LHC Physics Center at Fermilab in 2010. As part of the training, there are a number of “short” exercises on physics object reconstruction and identification, Monte Carlo simulation, and statistical analysis, which are followed by “long” exercises based on physics analyses. Some of the long exercises go beyond the current state of the art of the corresponding CMS analyses. This paper describes the goals of the school, the preparations for a school, the structure of the training, and student satisfaction with the experience as measured by surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Stability and scalability of the CMS Global Pool: Pushing HTCondor and glideinWMS to new limits

The CMS Global Pool, based on HTCondor and glideinWMS, is the main computing resource provisioning system for all CMS workflows, including analysis, Monte Carlo production, and detector data reprocessing activities. The total resources at Tier-1 and Tier-2 grid sites pledged to CMS exceed 100,000 CPU cores, while another 50,000 to 100,000 CPU cores are available opportunistically, pushing the needs of the Global Pool to higher scales each year. These resources are becoming more diverse in their accessibility and configuration over time. Furthermore, the challenge of stably running at higher and higher scales while introducing new modes of operation such as multi-core pilots, as well as the chaotic nature of physics analysis workflows, places huge strains on the submission infrastructure. This paper details some of the most important challenges to scalability and stability that the CMS Global Pool has faced since the beginning of the LHC Run II and how they were overcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗