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Dark Matter and Track Triggering with the CMS Experiment (Final Report)

This report summarizes the progress from DOE Early Career Award entitled “Dark Matter and Track Triggering with the CMS Experiment”. The first major goal of the project was to establish a sensitive Dark Matter (DM) search program for the CMS experiment in Run-2 of the LHC. Two related strategies were developed to accomplish this goal. First, we designed and executed searches for DM produced in association with heavy flavor quark pairs, top/anti-top (ttbar) and bottom/anti-bottom (bbbar). In addition, we sought to maximize the power of Run-2 DM searches through the development of a statistical combination of all major search channels within a consistent theoretical framework. The results of these aspects of the project are detailed in Section 1. The second major goal of the project was to develop a real-time “Level-1” tracking trigger system for the high-luminosity LHC (HL-LHC) CMS upgrade. Charged particle tracking in the first stage of the CMS trigger will be crucial for surviving the high-pileup environment expected at the HL-LHC. The L1 tracking trigger must process all front-end hit data sent from the inner Tracker and will have just 4us to output track primitives to the downstream L1 trigger without data loss. Our development of the CMS tracking trigger is described in Section 2. The team supported by the award is given in Section 3. The project resulted in 10 peer reviewed publications, a graduate student thesis, and contributions to the CMS Phase-2 Tracker Technical Design Report, as is detailed in Section 4. Our development work for the CMS tracking trigger has been integrated in the backend system architecture for the Tracker upgrade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Design of a Level-1 Long-Lived Particle Trigger in the CMS Hadron Calorimeter

The Hadron Calorimeter (HCAL) in the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) was recently upgraded for Run 3 to introduce depth segmentation and online timing measurements, expanding the physics capabilities. In particular, the augmentation of the calorimeter information at the hardware trigger level enables quick identification and recording of long-lived particle decays using lower thresholds on energy-based event quantities. The depth segmentation and online timing capabilities are utilized in novel HCAL-based hardware-level triggers to identify displaced and delayed long-lived particles (LLPs), either decaying inside the calorimeter volume or arriving at a delayed time. This increases the sensitivity to LLP decays occurring up to almost 6 m from the collision point. This two-pronged calorimeter trigger approach leverages the new capabilities of the CMS HCAL to expand the phase space accessible in ongoing LLP searches. These triggers were deployed for Run 3 of the LHC, beginning data-taking in 2022, and we review the trigger implementation and calibration.

Kopp, Gillian Baron [Princeton University, NJ (Uni↗

The Cosmic Ray Electron Excess

This slide presentation reviews the possible sources for the apparent excess of Cosmic Ray Electrons. The presentation reviews the Advanced Thin Ionization Calorimeter (ATIC) instrument, the various parts, how cosmic ray electrons are measured, and shows graphs that review the results of the ATIC instrument measurement. A review of Cosmic Ray Electrons models is explored, along with the source candidates. Scenarios for the excess are reviewed: Supernova remnants (SNR) Pulsar Wind nebulae, or Microquasars. Each of these has some problem that mitigates the argument. The last possibility discussed is Dark Matter. The Anti-Matter Exploration and Light-nuclei Astrophysics (PAMELA) mission is to search for evidence of annihilations of dark matter particles, to search for anti-nuclei, to test cosmic-ray propagation models, and to measure electron and positron spectra. There are slides explaining the results of Pamela and how to compare these with those of the ATIC experiment. Dark matter annihilation is then reviewed, which represent two types of dark matter: Neutralinos, and kaluza-Kline (KK) particles, which are next explained. The future astrophysical measurements, those from GLAST LAT, the Alpha Magnetic Spectrometer (AMS), and HEPCAT are reviewed, in light of assisting in finding an explanation for the observed excess. Also the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) could help by revealing if there are extra dimensions.

Chang, J.↗

Two-step electroweak symmetry-breaking: theory meets experiment

We study the phenomenology of a hypercharge-zero SU(2) triplet scalar whose existence is motivated by two-step electroweak symmetry-breaking. We consider both the possibility that the triplets are stable and contribute to the dark matter density, or that they decay via mixing with the standard model Higgs boson. The former is constrained by disappearing charged track searches at the LHC and by dark matter direct detection experiments, while the latter is constrained by existing multilepton collider searches. We find that a two-step electroweak phase transition involving a stable triplet with a negative quadratic term is ruled out by direct detection searches, while an unstable triplet with a mass less than 230 GeV is excluded at 95% confidence level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Probing an MeV-scale scalar boson in association with a TeV-Scale top-quark partner at the LHC

Searches for new low-mass matter and mediator particles have actively been pursued at fixed target experiments and at e + e - colliders. It is challenging at the CERN LHC, but they have been searched for in Higgs boson decays and in B meson decays by the ATLAS and CMS Collaborations, as well as in a low transverse momentum phenomena from forward scattering processes (e.g., FASER). We propose a search for a new scalar particle in association with a heavy vector-like quark. We consider the scenario in which the top quark (t) couples to a light scalar φ' and a heavy vector-like top quark T. We examine single and pair production of T in pp collisions, resulting in a final state with a top quark that decays purely hadronically, a T which decays semileptonically (T → W + b → ℓ ν b), and a φ' that is very boosted and decays to a pair of collimated photons which can be identified as a merged photon system. The proposed search is expected to achieve a discovery reach with signal significance greater than 5σ (3σ) for m(T) as large as 1.8 (2) TeV and m(φ') as small as 1 MeV, assuming an integrated luminosity of 3000 fb -1 . This search can expand the reach of T, and demonstrates that the LHC can probe low-mass, MeV-scale particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Operation and performance of the CMS silicon strip tracker with proton-proton collisions at the CERN LHC

Salient aspects of the commissioning, calibration, and performance of the CMS silicon strip tracker are discussed, drawing on experience during operation with proton-proton collisions delivered by the CERN LHC. The data were obtained with a variety of luminosities. The operating temperature of the strip tracker was changed several times during this period and results are shown as a function of temperature in several cases. Details of the system performance are presented, including occupancy, signal-to-noise ratio, Lorentz angle, and single-hit spatial resolution. Saturation effects in the APV25 readout chip preamplifier observed during early Run 2 are presented, showing the effect on various observables and the subsequent remedy. Studies of radiation effects on the strip tracker are presented both for the optical readout links and the silicon sensors. The observed effects are compared to simulation, where available, and they generally agree well with expectations.

47 OTHER INSTRUMENTATION↗

Porting HEP Parameterized Calorimeter Simulation Code to GPUs

The High Energy Physics (HEP) experiments, such as those at the Large Hadron Collider (LHC), traditionally consume large amounts of CPU cycles for detector simulations and data analysis, but rarely use compute accelerators such as GPUs. As the LHC is upgraded to allow for higher luminosity, resulting in much higher data rates, purely relying on CPUs may not provide enough computing power to support the simulation and data analysis needs. As a proof of concept, we investigate the feasibility of porting a HEP parameterized calorimeter simulation code to GPUs. We have chosen to use FastCaloSim, the ATLAS fast parametrized calorimeter simulation. While FastCaloSim is sufficiently fast such that it does not impose a bottleneck in detector simulations overall, significant speed-ups in the processing of large samples can be achieved from GPU parallelization at both the particle (intra-event) and event levels; this is especially beneficial in conditions expected at the high-luminosity LHC, where extremely high per-event particle multiplicities will result from the many simultaneous proton-proton collisions. We report our experience with porting FastCaloSim to NVIDIA GPUs using CUDA. A preliminary Kokkos implementation of FastCaloSim for portability to other parallel architectures is also described.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

First results of AUP Nb3Sn quadrupole horizontal tests

The Large Hadron Collider will soon undergo an upgrade to increase its luminosity by a factor of ~10 [1]. A crucial part of this upgrade will be replacement of the NbTi focusing magnets with Nb3Sn magnets that achieve a ~50% increase in the field strength. This will be the first ever large-scale implementation of Nb3Sn magnets in a particle accelerator. The High-Luminosity LHC Upgrade, HL-LHC is a CERN project with a world-wide collaboration. It is under construction and utilizes Nb3Sn Magnets (named MQXF) as key ingredients to increase tenfold the integrated luminosity delivered to the CMS and ATLAS experiments in the next decade. The HL-LHC AUP is the US effort to contribute approximately 50% of the low-beta focusing magnets and crab cavities for the HL-LHC. This paper will present the program to fabricate the Nb3Sn superconducting magnets. We are reporting the status of the HL-LHC AUP project present the results from horizontal tests of the first fully assembled cryo-assembly.

43 PARTICLE ACCELERATORS↗

Calibration of the CMS hadron calorimeters using proton-proton collision data at √ s = 13 TeV

Methods are presented for calibrating the hadron calorimeter system of the CMS detector at the LHC. The hadron calorimeters of the CMS experiment are sampling calorimeters of brass and scintillator, and are in the form of one central detector and two endcaps. These calorimeters cover pseudorapidities |η| < 3 and are positioned inside the solenoidal magnet. An outer calorimeter, outside the magnet coil, covers |η| < 1.26, and a steel and quartz-fiber Cherenkov forward calorimeter extends the coverage to |η| < 5.19. The initial calibration of the calorimeters was based on results from test beams, augmented with the use of radioactive sources and lasers. The calibration was improved substantially using proton-proton collision data collected at √ s = 7 , 8, and 13 TeV, as well as cosmic ray muon data collected during the periods when the LHC beams were not present. The present calibration is performed using the 13 TeV data collected during 2016 corresponding to an integrated luminosity of 35.9 fb -1 . The intercalibration of channels exploits the approximate uniformity of energy collection over the azimuthal angle. The absolute energy scale of the central and endcap calorimeters is set using isolated charged hadrons. The energy scale for the electromagnetic portion of the forward calorimeters is set using Z→ ee data. The energy scale of the outer calorimeters has been determined with test beam data and is confirmed through data with high transverse momentum jets. In this paper, we present the details of the calibration methods and accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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↗

SymbolFit: Automatic Parametric Modeling with Symbolic Regression

We introduce SymbolFit (API: https://github.com/hftsoi/symbolfit), a framework that automates parametric modeling by using symbolic regression to perform a machine-search for functions that fit the data while simultaneously providing uncertainty estimates in a single run. Traditionally, constructing a parametric model to accurately describe binned data has been a manual and iterative process, requiring an adequate functional form to be determined before the fit can be performed. The main challenge arises when the appropriate functional forms cannot be derived from first principles, especially when there is no underlying true closed-form function for the distribution. In this work, we develop a framework that automates and streamlines the process by utilizing symbolic regression, a machine learning technique that explores a vast space of candidate functions without requiring a predefined functional form because the functional form itself is treated as a trainable parameter, making the process far more efficient and effortless than traditional regression methods. We demonstrate the framework in high-energy physics experiments at the CERN Large Hadron Collider (LHC) using five real proton-proton collision datasets from new physics searches, including background modeling in resonance searches for high-mass dijet, trijet, paired-dijet, diphoton, and dimuon events. We show that our framework can flexibly and efficiently generate a wide range of candidate functions that fit a nontrivial distribution well using a simple fit configuration that varies only by random seed, and that the same fit configuration, which defines a vast function space, can also be applied to distributions of different shapes, whereas achieving a comparable result with traditional methods would have required extensive manual effort.

Tsoi, Ho Fung [Univ. of Pennsylvania, Philadelphia↗

Performance of the CMS Zero Degree Calorimeters in pPb collisions at the LHC

The two Zero Degree Calorimeters (ZDCs) of the CMS experiment are located at ± 140 m from the collision point and detect neutral particles in the |η| > 8.3 pseudorapidity region. This paper presents a study on the performance of the ZDC in the 2016 pPb run. The response of the detectors to ultrarelativistic neutrons is studied using in-depth Monte Carlo simulations. A method of signal extraction based on template fits is presented, along with a dedicated calibration procedure. A deconvolution technique for the correction of overlapping collision events is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Octopus processor for the CMS L1 muon trigger for High Luminosity LHC

The upgraded L1 muon trigger system of the CMS experiment in the High Luminosity Large Hadron Collider is based on custom processors featuring large Field Programmable Gate Arrays (FPGAs) connected by large numbers of optical links. These provide the I/O bandwidth and power necessary to process the complex algorithms used during the collection of physics data. The design and performance requirements of these processors creates significant challenges in signal integrity, power delivery, and thermal management. In this paper we describe the Octopus processor, featuring a large Xilinx Virtex Ultrascale+ FPGA and up to 128 links interfaced to optics through high quality twin-ax copper cables. Results on signal integrity at 25 Gb/s and the first demonstration of 50+ Gb/s links with pluggable optics in CMS are also shown, demonstrating bit error rates below 10 –15 at a 95% confidence level. The thermal performance is measured inside an Advanced-TCA crate with acceptable thermal margins up to 200 W of chip power. Future improvements are mentioned, potentially allowing operation at up to 300 W.

Instruments & Instrumentation↗

RD53 pixel readout integrated circuits for ATLAS and CMS HL-LHC upgrades

The RD53 collaboration has since 2013 developed new hybrid pixel detector chips with 50 × 50 μm2 pixels for the HL-LHC upgrades of the ATLAS and CMS experiments at CERN. A common architecture, design and verification framework has been developed to enable final pixel chips of different sizes to be designed, verified and tested to handle extreme hit rates of 3 GHz/cm2 (up to 12 GHz per chip) together with an increased trigger rate of 1 MHz and efficient readout of up to 5.12 Gbits/s per pixel chip. Tolerance to an extremely hostile radiation environment with 1 Grad over 10 years and induced SEU (Single Event Upset) rates of up to 100 upsets per second per chip have been major challenges to make reliable pixel chips. Three generations of pixel chips, and many specific mixed signal building blocks and radiation test chips, have been submitted and extensively tested to get to final production chips. The large, complex and high rate pixel chips have been developed with a strong emphasis on low power consumption together with a concurrent development and qualification of novel serial powering at chip, module and system level, to minimize detector material budget.

Alimonti, G↗

Search for dark matter produced in association with a single top quark and an energetic W boson in $\sqrt{s}=$ 13 TeV $pp$ collisions with the ATLAS detector

This paper presents a search for dark matter, $χ$, using events with a single top quark and an energetic W boson. The analysis is based on proton–proton collision data collected with the ATLAS experiment at $\sqrt{s}=$ 13 TeV during LHC Run 2 (2015–2018), corresponding to an integrated luminosity of 139 fb -1 . The search considers final states with zero or one charged lepton (electron or muon), at least one $b$-jet and large missing transverse momentum. In addition, a result from a previous search considering two-charged-lepton final states is included in the interpretation of the results. The data are found to be in good agreement with the Standard Model predictions and the results are interpreted in terms of 95% confidence-level exclusion limits in the context of a class of dark matter models involving an extended two Higgs-doublet sector together with a pseudoscalar mediator particle. The search is particularly sensitive to on-shell pro duction of the charged Higgs boson state, $H$ ± , arising from the two-Higgs-doublet mixing, and its semi-invisible decays via the mediator particle, $a$: $H$ ± → $W$ ± $a$(→ $χ$ $χ$). Signal models with $H$ ± masses up to 1.5 TeV and a masses up to 350 GeV are excluded assuming a tan $β$ value of 1. For masses of a of 150 (250) GeV, tan $β$ values up to 2 are excluded for $H$ ± masses between 200 (400) GeV and 1.5 TeV. Signals with tan $β$ values between 20 and 30 are excluded for $H$ ± masses between 500 and 800 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Physics motivation and detector upgrades for the new era of the ATLAS experiment

The ATLAS experiment at CERN’s Large Hadron Collider (LHC) will be upgraded in two stages to prepare first for the Run~3 data-taking campaign, during which the integrated luminosity will roughly double, and then for the High-Luminosity LHC program with an ultimate integrated luminosity of up to 4 ab ^{{-1}} − 1 . These upgrades and high-statistics datasets will allow ATLAS to perform searches and precision measurements to constrain the Standard Model in yet-unexplored phase spaces and in the Higgs sector. This contribution summarizes the ATLAS detector upgrades and selected physics prospects for Run~3 and the HL-LHC.

Nielsen, Jason↗

"Experimental Research at the Energy Frontier in High Energy Physics" (Final Technical Report)

Recent developments in particle physics and cosmology raise the exciting prospect that we are on the threshold of a major step forward in our understanding of the universe. This proposal describes a research program at the University of Illinois in experimental high-energy physics on the ATLAS experiment at CERN’s Large Hadron Collider (LHC). Our group actively collaborates with the Theory Group and other experimental efforts within the Office of Science frontiers (energy, intensity, and cosmic) to search broadly in the ATLAS data to maximize our potential for scientifc discovery. The thrust of this proposal is to search for new physics using ATLAS data. Emphasis is placed on novel use of the Higgs boson as a tool to search for new particles and interactions and development of fast particle tracking systems for use in triggering. We propose to continue our strong role in FTK commissioning and operations. To maximize the impact and vitality of the proposed physics program through the HL-LHC running, we will lead firmware efforts in the HWTT Phase-II TDAQ upgrade, leveraging our expertise acquired through development of fast tracking hardware and firmware for the FTK system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗