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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Forward Physics Facility at the High-Luminosity LHC

High energy collisions at the High-Luminosity Large Hadron Collider (LHC) produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located several hundred meters from the ATLAS interaction point and shielded by concrete and rock, will host a suite of experiments to probe standard model (SM) processes and search for physics beyond the standard model (BSM). In this report, we review the status of the civil engineering plans and the experiments to explore the diverse physics signals that can be uniquely probed in the forward region. FPF experiments will be sensitive to a broad range of BSM physics through searches for new particle scattering or decay signatures and deviations from SM expectations in high statistics analyses with TeV neutrinos in this low-background environment. High statistics neutrino detection will also provide valuable data for fundamental topics in perturbative and non-perturbative QCD and in weak interactions. Experiments at the FPF will enable synergies between forward particle production at the LHC and astroparticle physics to be exploited. We report here on these physics topics, on infrastructure, detector, and simulation studies, and on future directions to realize the FPF’s physics potential.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Development and demonstration of next generation technology for Nb_3Sn accelerator magnets with lower cost, improved performance uniformity, and higher operating point in the 12-14 T range

The scope of the proposal outlined in this white paper is the development and demonstration of the technology needed for next generation of Nb_3Sn accelerator magnets in the 12-14 T range. The main goal is to cut magnet cold-mass cost by a factor 2 or higher with respect to the Nb_3Sn magnets produced by the US Accelerator Upgrade Project (AUP) for the High-Luminosity Large Hadron Collider (HL-LHC). This goal will be achieved by significant reduction of labor hours, higher operating point, and improved performance uniformity. A key factor will be automation that will be achieved through industry involvement and benefitting from the experience gained in US national laboratories through the production of the AUP magnets. This partnership will enable the development of a technology that will be easily transferable to industry for mid- and large-scale production of Nb_3Sn accelerator magnets in the 12-14 T range. This step is essential to enable next generation of colliders such as the FNAL-proposed Muon Collider, FCC and other HEP hadron colliders. This is a Directed R&D where direction is given by the field range and industry involvement for high-automation and industry-ready technology. The plan includes ten milestones, to be achieved in 6-8 years at the cost of 5-7 $M/year.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Time-resolved synchrotron light source X-ray detection with Low-Gain Avalanche Diodes

Low Gain Avalanche Diodes (LGADs) represent the state-of-the-art in timing measurements and will instrument future timing detectors at the High Luminosity Large Hadron Collider (HL-LHC) experiments. While conceived as a sensor for charged particles, the intrinsic gain of LGADs makes it possible to detect low energy X-rays with good energy resolution and excellent timing (tens of picoseconds). Here, using the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC, several LGADs designs were characterized with energies from 5 to 35 keV. The SSRL provides 10 ps pulsed X-ray bunches separated by 2.1 ns intervals, and with an energy dispersion (ΔE/E) of 1 X 10 -4 . LGADs fabricated by Hamamatsu Photonics (HPK) and Brookhaven National Laboratory (BNL) with different thicknesses ranging from 20 µm to 50 µm and different gain layer designs were read out a two stage fast amplification circuit and digitized with a high bandwidth, high sampling rate oscilloscope. PIN devices from HPK were characterized as well. A systematic and detailed characterization of the devices’ energy linearity, resolution and timing resolution as a function of X-ray energy was performed for different biasing voltages at room temperature

Charge multiplication↗
DOE OSTI2025

Leveraging the Run 3 experience for the evolution of the ATLAS software-based readout towards HL-LHC

The High-Luminosity Large Hadron Collider (HL-LHC), scheduled to start operating in 2030, aims to increase the instantaneous luminosity by a factor of 10 compared to the LHC. To match this increase, the ATLAS experiment has been implementing a major upgrade program divided into two phases. The first phase (Phase-I), completed in 2022, introduced new trigger and detector systems that have been used during the Run 3 data taking period which began in July 2022. These systems have been used in conjunction with the new Data Acquisition (DAQ) Readout system, based on a software application called Software Readout Driver (SW ROD). SW ROD receives and aggregates data from the front-end electronics via the Front-End Link eXchange (FELIX) system and passes aggregated data fragments to the High-Level Trigger (HLT) system. During Run 3, SW ROD operates in parallel with the legacy Readout System (ROS) at an input rate of 100 kHz. For the Phase-II, the legacy ROS will be completely replaced with a new system based on the next generation of FELIX and an evolution of the SW ROD application called Data Handler. Data Handler has the same functional requirements as SW ROD but must be able to operate at an input rate of 1 MHz. To facilitate this evolution the SW ROD has been implemented using plugin architecture. This contribution presents the design and implementation of the SW ROD application for Run 3, along with the strategy for its evolution to the Phase-II Readout system. It discusses the lessons learned during Run 3 and describes the challenges that have been addressed to accomplish the demanding performance requirements of HL-LHC.

Kolos, Serguei [Univ. of California, Irvine, CA (U↗
DOE OSTI2024

Distilling particle knowledge for fast reconstruction at high-energy physics experiments

Knowledge distillation is a form of model compression that allows artificial neural networks of different sizes to learn from one another. Its main application is the compactification of large deep neural networks to free up computational resources, in particular on edge devices. In this article, we consider proton-proton collisions at the High-Luminosity Large Hadron Collider (HL-LHC) and demonstrate a successful knowledge transfer from an event-level graph neural network (GNN) to a particle-level small deep neural network (DNN). Our algorithm, DistillNet, is a DNN that is trained to learn about the provenance of particles, as provided by the soft labels that are the GNN outputs, to predict whether or not a particle originates from the primary interaction vertex. The results indicate that for this problem, which is one of the main challenges at the HL-LHC, there is minimal loss during the transfer of knowledge to the small student network, while improving significantly the computational resource needs compared to the teacher. This is demonstrated for the distilled student network on a CPU, as well as for a quantized and pruned student network deployed on a field programmable gate array. Our study proves that knowledge transfer between networks of different complexity can be used for fast artificial intelligence (AI) in high-energy physics that improves the expressiveness of observables over non-AI-based reconstruction algorithms. Such an approach can become essential at the HL-LHC experiments, e.g. to comply with the resource budget of their trigger stages.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The High Luminosity LHC interaction region magnets towards series production

The High Luminosity Large Hadron Collider (HL-LHC) is the new flagship project of CERN. First endorsed in 2013 and approved in 2016, HL-LHC is an upgrade of the accelerator aiming to increase by a factor of ten the statistics of the LHC collisions at the horizon of 2035-2040. HL-LHC relies on cutting edge technologies: among them, large aperture superconducting magnets will replace the present hardware to allow a smaller beam size in two interaction points (IPs). The project involves the construction of about 150 magnets of six different types: the quadrupole triplet, two main dipoles and three orbit correctors. The triplet, manufactured at CERN and in the USA, will consist of 30 magnets based on Nb3Sn technology, with an operational peak field of 11.4 T. These will be the first quadrupole Nb3Sn magnets installed in a particle accelerator. The other five types of magnets, all relying on Nb-Ti technology, present non-trivial challenges in the design and construction; they will be manufactured as part of in-kind contribution under the responsibility of institutes in Japan, China, Spain, and Italy. The project is now in the phase of transition between qualification through short models and prototypes and the beginning of the series construction. In this paper we review the magnet requirements, the reasons for selecting the design, the technological challenges with respect to previous projects, and we summarize the steps that have been taken to validate the baseline.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Testing CP properties of the Higgs boson coupling to τ leptons with heterogeneous graphs

In this paper we explore the possibility of utilizing Deep Learning in measuring the CP properties of the coupling of Higgs boson to τ leptons at the High Luminosity Large Hadron Collider. We employ three Deep Learning (DL) networks, Multi-Layer Perceptron (MLP), Graph Convolution Network (GCN), and Graph Transformer Network (GTN) to enhance signal-to-background separation. The angle between τ lepton decay planes at the detector level is CP-sensitive observables, and we develop Heterogeneous Graphs that integrate diverse node and edge structures to incorporate the CP-sensitive observable efficiently. Using simplified detector simulations we estimate the reconstruction accuracy of the angle between τ lepton planes at the detector level, considering hadronic τ decay modes and standard model backgrounds. With $\sqrt{s}$ = 14 TeV and $\mathcal{L}$ = 100 fb -1 , MLP excludes CP mixing angles above 20° at 68% confidence level (CL), while GCN and GTN achieve exclusions at 90% CL and 95% CL, respectively. The networks also achieve a 3σ significance in excluding a pure CP-odd state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Modeling of surface-state induced inter-electrode isolation of n -on- p devices in mixed-field and γ -irradiation environments

Position sensitive n-on-p silicon sensors will be utilized in the tracker and in the High Granularity Calorimeter (HGCAL) of the Compact Muon Solenoid (CMS) experiment at High Luminosity Large Hadron Collider (HL-LHC). The detrimental effect of the radiation-induced accumulation of positive net oxide charge on position resolution in n-on-p sensors has typically been countered by the application of isolation implants like p-stop or p-spray between n + -electrodes. In addition to the positively charged layer inside the oxide and close to the Si/SiO 2 -interface, surface damage introduced by ionizing radiation in SiO 2 -passivated silicon particle detectors includes the accumulation of trapped-oxide-charge and interface traps. A previous study of either n/γ (mixed field)- or γ-irradiated Metal-Oxide-Semiconductor (MOS) capacitors showed evidence of substantially higher introduction rates of acceptor- and donor-type deep interface traps (N it,acc/don ) in mixed-field environment. Here, in this work, an inter-pad and -strip resistance (or resistivity (ρ int )) simulation study of n-on-p sensors with and without p-stop isolation implants was conducted for both irradiation types. Higher levels of ρint showed correlation to higher densities of deep N it,acc/don , with the inter-pad isolation performance of the mixed-field irradiated sensors becoming independent of the presence of p-stop implant between the n + - electrodes up to about 100 kGy. The low introduction rates of deep N it,acc/don in γ-irradiated sensors resulted in high sensitivity of ρ int to the presence and peak doping of p-stop above the lowest dose of about 7 kGy in the study. As a consequence of the advantageous influence of radiation-induced accumulation of deep N it on the inter-electrode isolation, position sensitive n-on-p sensors without isolation implants may be considered for future HEP-experiments where the radiation is largely due to hadrons.

Akchurin, N. [Texas Tech Univ., Lubbock, TX (Unite↗
DOE OSTI2021

Charged particle tracking with quantum annealing optimization

Abstract At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for physics analysis will need to be upgraded to scale with track density. Quantum annealing has shown promise in its ability to solve combinatorial optimization problems amidst an ongoing effort to establish evidence of a quantum speedup. As a step towards exploiting such potential speedup, we investigate a track reconstruction approach by adapting the existing geometric Denby-Peterson (Hopfield) network method to the quantum annealing framework for HL-LHC conditions. We develop additional techniques to embed the problem onto existing and near-term quantum annealing hardware. Results using simulated annealing and quantum annealing with the D-Wave 2X system on the TrackML open dataset are presented, demonstrating the successful application of a quantum annealing algorithm to the track reconstruction challenge. We find that combinatorial optimization problems can effectively reconstruct tracks, suggesting possible applications for fast hardware-specific implementations at the HL-LHC while leaving open the possibility of a quantum speedup for tracking.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC

The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine-Learning (ML) techniques to explore WIMP radiative decays into a Dark Matter (DM) candidate in a supersymmetric framework. The minimal supersymmetric WIMP sector includes the lightest neutralino that can provide the observed DM relic density through its co-annihilation with the second lightest neutralino and lightest chargino. Moreover, the direct DM detection cross section rates fulfill current experimental bounds and provide discovery targets for the same region of model parameters in which the radiative decay of the second lightest neutralino into a photon and the lightest neutralino is enhanced. This strongly motivates the search for radiatively decaying neutralinos which, however, suffers from strong backgrounds. We investigate the LHC reach in the search for these radiatively decaying particles by means of cut-based and ML methods and estimate its discovery potential in this well-motivated, new physics scenario. We demonstrate that using ML techniques would enable access to most of the parameter space unexplored by other searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Upper bound on Parity breaking scale for doublet WIMP dark matter

A bstract We consider weakly interacting massive particle (WIMP) dark matter in a Parity solution to the strong CP problem. The WIMP phenomenology can be drastically affected by the presence of Parity partners of the WIMP and electroweak gauge bosons. We focus on a Parity extension of SU(2) L -doublet fermion dark matter, identify the viable parameter space, and derive the predictions of the theory. We find that the Parity symmetry breaking scale is bounded from above, with the bound given by 25–60 TeV, depending on whether or not dark matter and its Parity partner coannihilate with each other. The High-Luminosity Large Hadron Collider, future colliders, and direct and indirect detection experiments can probe the parameter space further, with correlated signal rates.

Baldwin, Matthew J. [University of Chicago; Univer↗
DOE OSTI2020

Design and evaluation of large area strip sensor prototypes for the ATLAS Inner Tracker detector

The ATLAS community is facing the last stages prior to the production of the upgraded silicon strip Inner Tracker for the High-Luminosity Large Hadron Collider. An extensive Market Survey was carried out in order to evaluate the capability of different foundries to fabricate large area silicon strip sensors, satisfying the ATLAS specifications. The semiconductor manufacturing company, Infineon Technologies AG, was one of the two foundries, along with Hamamatsu Photonics K.K., that reached the last stage of the evaluation for the production of the new devices. The full prototype wafer layout for the participation of Infineon, called ATLAS17LS-IFX, was designed using a newly developed Python-based Automatic Layout Generation Tool, able to rapidly design sensors with different characteristics and dimensions based on a few geometrical and technological input parameters. Here we present the layout design process and the results obtained from the evaluation of the new Infineon large area sensors before and after proton and neutron irradiations, up to fluences expected in the inner layers of the future ATLAS detector.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors

Abstract Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event reconstruction in electron-positron collisions based on a full detector simulation. Particle-flow reconstruction can be formulated as a supervised learning task using tracks and calorimeter clusters. We compare a graph neural network and kernel-based transformer and demonstrate that we can avoid quadratic operations while achieving realistic reconstruction. We show that hyperparameter tuning significantly improves the performance of the models. The best graph neural network model shows improvement in the jet transverse momentum resolution by up to 50% compared to the rule-based algorithm. The resulting model is portable across Nvidia, AMD and Habana hardware. Accurate and fast machine-learning based reconstruction can significantly improve future measurements at colliders.

Physics↗
DOE OSTI2022

Prototype hardware design and testing of the global common module for the global trigger subsystem of the ATLAS phase-II upgrade

We report the High-Luminosity Large Hadron Collider (HL-LHC) will deliver more than ten times the integrated luminosity of the previous runs combined. Meeting its stricter throughput requirements poses new challenges to the Trigger and Data Acquisition (TDAQ) systems of the LHC experiments. Introduced in the framework of the ATLAS experiment’s HL upgrade, the Global Trigger (GT) is a new subsystem which will perform offline-like algorithms on full-granularity calorimeter data. The implementation of the GT’s functionality is firmware-focused and is composed of three layers: multiplexing (or data aggregating), global event processing, and demultiplexing interface to the central trigger processor. Each layer will be composed of several, similar nodes, hosted on replicas of identical hardware, the Global Common Module (GCM), an ATCA front board which is designed to be adopted throughout the entire GT subsystem. This article proceeds from the TWEPP 2021 conference and presents the GCM hardware design, performed in 2020, and focuses on some key results of its extensive testing performed in 2021.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

System design and prototyping for the CMS Level-1 Trigger at the High-Luminosity LHC

For the High-Luminosity Large Hadron Collider, the trigger and data acquisition system of the CMS experiment will be entirely replaced. Novel design choices have been explored, including ATCA prototyping platforms with SoC controllers and newly available interconnect technologies with serial optical links with data rates up to 28 Gb/s. Trigger analyses will be performed through sophisticated algorithms, including widespread use of Machine Learning, in large FPGAs, such as the Xilinx Ultrascale family. The system will process over 50 Tb/s of detector data with an event rate of 750 kHz. Here, we describe system design and prototyping and review trigger algorithm exemplars.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Construction of precision sMDT detector for the ATLAS Muon Spectrometer upgrade

Here, this paper describes the small-diameter monitored drift-tube detector construction at the University of Michigan as a contribution to the ATLAS Muon Spectrometer upgrade for the high-luminosity Large Hadron Collider at CERN. Measurements of the first 30 chambers built at Michigan show that the drift tube wire position accuracy meets the specification of 20 μm. The positions of the platforms for alignment and magnetic field sensors are all installed well within the required precision. The cosmic ray test measurements show single wire tracking resolution of 100 ± 7 μm with an average detection efficiency above 99%. The infrastructure, tooling, techniques, and procedures for chamber production are described in detail. The results from the chamber quality control tests of the first 30 constructed chambers are reported.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

The COLUTA ADC ASIC and the ATLAS HL-LHC Liquid Argon Front-End Readout

Abstract The upgraded High-Luminosity Large Hadron Collider (HL-LHC) requires a new radiation tolerant ATLAS Liquid Argon (LAr) Calorimeter readout operating at 40 MHz with 16-bit dynamic range. The Front-End Board 2 (FEB2) will provide the front-end readout for the calorimeter, and will interface a series of custom ASICs due to radiation tolerance requirements of the HL-LHC. The COLUTA is a 65 nm CMOS custom 8-channel 15-bit 40 MSPS ADC ASIC developed for this application. This contribution will present performance results of the final prototype of the COLUTA, surpassing specifications at >11.5 ENOB for relevant frequencies, as well as non-linearity and radiation requirements. Preliminary integration results of the front-end readout components will also be described by means of the FEB2 Pre-Prototype, the “Slice Testboard”.

Instruments & Instrumentation↗
DOE OSTI2023

Hardware design and testing of the generic rear transition module for the global trigger subsystem of ATLAS Phase-II Upgrade

Abstract In the framework of the ATLAS experiment’s Phase-II Upgrade at the High-Luminosity Large Hadron Collider (HL-LHC), new and improved trigger hardware and algorithms will be implemented onto a single-level, 10 μs-latency architecture. The Global Trigger is a new subsystem which will bring event-filter capabilities by performing offline-like algorithms on full-granularity calorimeter data. The implementation of the functionality is firmware-focused and composed of several processing nodes, which are hosted on identical hardware, made up of an Advanced Telecommunications Computing Architecture (ATCA) front board, called Global Common Module (GCM), and a rear transition module (RTM), called Generic RTM (GRM). The GRM, which was developed to mitigate the risks deriving from the complex design and power management of the GCM, features an advanced Xilinx Versal Prime system-on-chip and can handle communication with the GCM and Front-End Link eXchange (FELIX) subsystem and trigger processors through 124 25.8 Gb/s transceiver links, for readout and control. Additionally, the GRM mounts a Low-Power GigaBit Transceiver (lpGBT) chip which enables emulation of the detector front-ends for integration tests. This paper presents the GRM hardware design and its testing.

Instruments & Instrumentation↗