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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

HL-LHC Beam Dynamics with Hollow Electron Lenses

Each of the two proton beams in the High-Luminosity Large Hadron Collider (HL-LHC) will carry a total energy of 720 MJ. One concern for machine protection is the energy stored in the transverse beam tails, estimated to potentially reach up to 5% of the total stored energy. Several failure scenarios could drive these tails into the collimators, potentially causing damage and therefore severely affecting operational efficiency. Hollow Electron Lenses (HEL) were integrated in the HL-LHC baseline to mitigate this risk by depleting the tails in a controlled way. A hollow-shaped electron beam runs co-axially to the hadron beam over about 3 m, such that halo particles at large amplitudes become unstable, while core particles ideally remain undisturbed. Residual fields from e-beam asymmetries can, however, induce emittance growth of the beam core. Various options for the pulsing of the HEL are considered and are compared using two figures of merit: halo depletion efficiency and core emittance growth. This contribution presents simulations for these two effects with different HEL pulsing modes using the final HL-LHC optics, that was optimized at the location of the lenses.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

CMS Physics Results in the LHC Runs 2,3

The Large hadron Collider at CERN and four scientific collaborations: Alice, ATLAS, CMS, LHCb are in operation since September 2008. The accelerator delivered and the experiments processed trillions of events of proton-proton and heavy ions collisions and provided useful data for thousands of physics analyses and publications. The jewel of the published data is a discovery in 2012 of the long anticipated Higgs boson. During the operation time the regular acquisition of data was interleaved with two periods of maintenance, Long-shutdown-1 (2013-2015) and Long-shutdown-2 (2018-2022), which resulted in several improvements to the machine and the experiments. The CMS collaboration recorded to date two large physics datasets of pp collision data. The first dataset, called Run 2, was recorded between 2015 and 2018 with 140fb-1 of integrated luminosity taken at 13TeV of center of mass energy. The second dataset, called Run 3, has just started in 2022 and it has been recording pp collision data at 13.6 TeV of center of mass energy, with 80 fb-1 of data collected till the end of July 2023.For my presentation I selected the most recent results produced by CMS from Run2 and Run 3 which are covering the topics of Higgs boson properties, searches for new particles and additional scalars, top quark production and properties, and I am discussing other interesting models e.g. using SM particles as portals to the Dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Ultra-low magnetization and hysteresis loss in APC Nb 3 Sn superconductors

For the accelerator magnets of the next hadron collider, reducing superconductor persistent-current magnetization is not only important for achieving the desired field quality, but also crucial for its sustainability because the magnetization loss is the major heat load to the magnet cold mass. For conventional Nb 3 Sn conductors this requires reduction of effective subelement size (D eff ). For the restacked-rod-process (RRP ® ) conductors a physical subelement size (D sub ) as small as 35 µm (corresponding to a D eff close to 45 µm) can be reached, but at a significant price in J c . Another way to reduce the magnetization is by introducing artificial pinning centers (APC) using the internal oxidation approach. APC conductors outperform conventional Nb 3 Sn wires in two aspects: 1) higher J c at high fields, and 2) much lower J c and magnetization at low fields (e.g. below 5 T). Here, in this work we explored the fabricability of APC wires with small D sub . A 180-stack APC wire was produced and drawn to 0.7- and 0.5 mm diameters with good quality, with D sub s of 34 and 24 µm (D eff s of 36 and 25 µm), respectively. For the 34 µm-D sub wire, its non-Cu J c is higher than that of an RRP ® wire used for the High-Luminosity Large Hadron Collider (HL-LHC) project above 13 T (e.g. 36% higher at 4.2 K, 18 T), while its non-Cu magnetization at 1 T, ΔM(1 T), is only 29% of the RRP ® wire. Its non-Cu hysteresis loss for a cycle between 1 and 14 T, Q h (1–14 T), is 37% of the RRP ® wire. For the 24 µm-D sub wire, its non-Cu J c surpasses the HL-LHC RRP ® wire above 17.5 T, while its ΔM(1 T) and Q h (1–14 T) are only 17% and 23% of the RRP® wire, respectively. Its non-Cu Q h (±3 T) even meets the specification of the International Thermonuclear Experimental Reactor project.

Xu, X [Fermi National Accelerator Laboratory (FNAL↗
DOE OSTI2022

Precision QCD, Hadronic Structure & Forward QCD, Heavy Ions: Report of Energy Frontier Topical Groups 5, 6, 7 submitted to Snowmass 2021

This report was prepared on behalf of three Energy Frontier Topical Groups of the Snowmass 2021 Community Planning Exercise. It summarizes the status and implications of studies of strong interactions in high-energy experiments and QCD theory. We emphasize the rich landscape and broad impact of these studies in the decade ahead. Hadronic interactions play a central role in the high-luminosity Large Hadron Collider (LHC) physics program, and strong synergies exist between the (HL-)LHC and planned or proposed experiments at the U.S. Electron-Ion Collider, CERN forward physics experiments, high-intensity facilities, and future TeV-range lepton and hadron colliders. Prospects for precision determinations of the strong coupling and a variety of nonperturbative distribution and fragmentation functions are examined. We also review the potential of envisioned tests of new dynamical regimes of QCD in high-energy and high-density scattering processes with nucleon, ion, and photon initial states. The important role of the high-energy heavy-ion program in studies of nuclear structure and the nuclear medium, and its connections with QCD involving nucleons are summarized. We address ongoing and future theoretical advancements in multi-loop QCD computations, lattice QCD, jet substructure, and event generators. Cross-cutting connections between experimental measurements, theoretical predictions, large-scale data analysis, and high-performance computing are emphasized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Search for resonant leptoquark production via lepton-jet signatures in pp collisions at $\sqrt{s}=13$ TeV and $\sqrt{s}=13.6$ TeV with the ATLAS detector

This paper presents a search for physics beyond the Standard Model targeting a heavy resonance visible in the invariant mass of the lepton-jet system. The analysis focuses on final states with a high-energy lepton and jet, and is optimised for the resonant production of leptoquarks — a novel production mode mediated by the lepton content of the proton originating from quantum fluctuations. Four distinct and orthogonal final states are considered: e+light jet, μ+light jet, e+b-jet, and μ+b-jet, constituting the first search at the Large Hadron Collider for resonantly produced leptoquarks with couplings to electrons and muons. Events with an additional same-flavour lepton, as expected from higher-order diagrams in the signal process, are also included in each channel. The search uses proton-proton collision data from the full Run 2, corresponding to an integrated luminosity of 140 fb −1 at a centre-of-mass energy of $\sqrt{s}=13$ TeV, and from a part of Run 3 (2022–2023), corresponding to 55 fb −1 at $\sqrt{s}=13.6$ TeV. No significant excess over Standard Model predictions is observed. The results are interpreted as exclusion limits on scalar leptoquark ($\tilde{S}$ 1 ) production, substantially improving upon previous ATLAS constraints from leptoquark pair production for large coupling values. The excluded $\tilde{S}$ 1 $\tilde{S}$ 1 mass ranges depend on the coupling strength, reaching up to 3.4 TeV for quark-lepton couplings y de = 1.0, and up to 4.3 TeV, 3.1 TeV, and 2.8 TeV for y sμ , y be , and y bμ couplings set to 3.5, respectively.

Hadron-Hadron Scattering↗
DOE OSTI2024

Distributed Machine Learning Workflow with PanDA and iDDS in LHC ATLAS

Machine Learning (ML) has become one of the important tools for High Energy Physics analysis. As the size of the dataset increases at the Large Hadron Collider (LHC), and at the same time the search spaces become bigger and bigger in order to exploit the physics potentials, more and more computing resources are required for processing these ML tasks. In addition, complex advanced ML workflows are developed in which one task may depend on the results of previous tasks. How to make use of vast distributed CPUs/GPUs in WLCG for these big complex ML tasks has become a popular research area. In this paper, we present our efforts enabling the execution of distributed ML workflows on the Production and Distributed Analysis (PanDA) system and intelligent Data Delivery Service (iDDS). First, we describe how PanDA and iDDS deal with large-scale ML workflows, including the implementation to process workloads on diverse and geographically distributed computing resources. Next, we report real-world use cases, such as HyperParameter Optimization, Monte Carlo Toy confidence limits calculation, and Active Learning. Finally, we conclude with future plans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Efficient emulation of relativistic heavy ion collisions with transfer learning

Measurements from the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) can be used to study the properties of quark-gluon plasma. Systematic constraints on these properties must combine measurements from different collision systems and methodically account for experimental and theoretical uncertainties. Such studies require a vast number of costly numerical simulations. While computationally inexpensive surrogate models (“emulators”) can be used to efficiently approximate the predictions of heavy ion simulations across a broad range of model parameters, training a reliable emulator remains a computationally expensive task. We use transfer learning to map the parameter dependencies of one model emulator onto another, leveraging similarities between different simulations of heavy ion collisions. By limiting the need for large numbers of simulations to only one of the emulators, this technique reduces the numerical cost of comprehensive uncertainty quantification when studying multiple collision systems and exploring different models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Enhanced production of strange baryons in high-energy nuclear collisions from a multiphase transport model

Here, we introduce additional coalescence factors for the production of strange baryons in a multiphase transport (AMPT) model in order to describe the enhanced production of multistrange hadrons observed in Pb + Pb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV at the Large Hadron Collider (LHC) and Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV at Relativistic Heavy-Ion Collider (RHIC). This extended AMPT model is found to also give a reasonable description of the multiplicity dependence of the strangeness enhancement observed in high multiplicity events in $\textit{pp}$ collisions at $\sqrt{s}$ = 7 TeV and $\textit{p}$-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV. We find that the coalescence factors depend on the system size but not much on whether the system is produced from A + A or $\textit{p}$ + A collisions. Here, the extended AMPT model thus provides a convenient way to model the mechanism underlying the observed strangeness enhancement in collisions of both small and large systems at RHIC and LHC energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

ATLAS ITk strip sensor quality control procedures and testing site qualification

Abstract The high-luminosity upgrade of the Large Hadron Collider, scheduled to become operational in 2029, requires the replacement of the ATLAS Inner Detector with a new all-silicon Inner Tracker. Radiation hard n + -in-p micro-strip silicon sensors were developed by the ATLAS Inner Tracker strip collaboration and are produced by Hamamatsu Photonics K.K. Production of the total amount of 22000 strip sensors has started in 2020 and will continue until 2025. The ATLAS strip sensor collaboration has the responsibility to monitor the quality of the fabricated devices by performing detailed measurements of individual sensor characteristics and by comparing the obtained results with the tests done by the manufacturer. Dedicated Quality Control procedures were developed to check whether the delivered large-format sensors adhere to the ATLAS specifications. The institutes performing the Quality Control testing of the pre-production and production ATLAS ITk strip sensors had to initially be qualified for multiple high-throughput tests by successfully completing the Site Qualification process. The Quality Control procedures and the qualification process are described in this paper.

Instruments & Instrumentation↗
DOE OSTI2023

Measurement of Sequential ϒ Suppression in Au + Au Collisions at $\sqrt{s_{NN}}$ = 200 GeV with the STAR Experiment

We report on measurements of sequential ϒ suppression in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV with the STAR detector at the Relativistic Heavy Ion Collider (RHIC) through both the dielectron and dimuon decay channels. In the 0%–60% centrality class, the nuclear modification factors (𝑅 𝐴⁢𝐴 ), which quantify the level of yield suppression in heavy-ion collisions compared to 𝑝 + 𝑝 collisions, for ϒ⁡(1⁢𝑆) and ϒ⁡(2⁢𝑆) are 0.40 ± 0.03⁢(stat) ± 0.03⁢(sys) ± 0.09⁢(norm) and 0.26 ± 0.08⁢(stat) ± 0.02⁢(sys) ± 0.06⁢(norm), respectively, while the upper limit of the ϒ⁡(3⁢𝑆) 𝑅 𝐴⁢𝐴 is 0.17 at a 95% confidence level. This provides experimental evidence that the ϒ⁡(3⁢𝑆) is significantly more suppressed than the ϒ⁡(1⁢𝑆) at RHIC. The level of suppression for ϒ⁡(1⁢𝑆) is comparable to that observed at the much higher collision energy at the Large Hadron Collider. Furthermore, these results point to the creation of a medium at RHIC whose temperature is sufficiently high to strongly suppress excited ϒ states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Precise measurements of W - and Z -boson transverse momentum spectra with the ATLAS detector using pp collisions at $\sqrt{s} = 5.02$ TeV and 13 TeV

This paper describes measurements of the transverse momentum spectra of W and Z bosons produced in proton–proton collisions at centre-of-mass energies of $\sqrt{s}$ = 5.02 TeV and $\sqrt{s}$ = 13 TeV with the ATLAS experiment at the Large Hadron Collider. Measurements are performed in the electron and muon channels, W → $\ell$$v$ and Z → $\ell$$\ell$ ($\ell$ = e or μ), and for W events further separated by charge. The data were collected in 2017 and 2018, in dedicated runs with reduced instantaneous luminosity, and correspond to 255 and 338 pb -1 at $\sqrt{s}$ = 5.02 TeV and 13 TeV, respectively. These conditions optimise the reconstruction of the W-boson transverse momentum. The distributions observed in the electron and muon channels are unfolded, combined, and compared to QCD calculations based on parton shower Monte Carlo event generators and analytical resummation. The description of the transverse momentum distributions by Monte Carlo event generators is imperfect and shows significant differences largely common to W - , W + and Z production. The agreement is better at $\sqrt{s}$ = 5.02 TeV, especially for predictions that were tuned to Z production data at $\sqrt{s}$ = 7 TeV. Higher-order, resummed predictions based on DYTurbo generally match the data best across the spectra. Distribution ratios are also presented and test the understanding of differences between the production processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Anomaly detection search for new resonances decaying into a Higgs boson and a generic new particle $X$ in hadronic final states using $\sqrt{s}$ = 13 TeV $pp$ collisions with the ATLAS detector

A search is presented for a heavy resonance $Y$ decaying into a Standard Model Higgs boson $H$ and a new particle $X$ in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at $\sqrt{s}$ = 13 TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139 fb –1 . The search targets the high $Y$-mass region, where the $H$ and $X$ have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted $X$ particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark $X$ decay into two quarks, covering topologies where the $X$ is reconstructed as either a single large-radius jet or two smallradius jets. The analysis selects Higgs boson decays into $b$$\overline{b}$, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section $σ$ ($pp$ → $Y$ → $XH$ → $q$$\overline{q}$$b$$\overline{b}$) for signals with $m_Y$ between 1.5 and 6 TeV and $m_X$ between 65 and 3000 GeV

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Generative machine learning for detector response modeling with a conditional normalizing flow

In this paper, we explore the potential of generative machine learning models as an alternative to the computationally expensive Monte Carlo (MC) simulations commonly used by the Large Hadron Collider (LHC) experiments. Our objective is to develop a generative model capable of efficiently simulating detector responses for specific particle observables, focusing on the correlations between detector responses of different particles in the same event and accommodating asymmetric detector responses. Here, we present a conditional normalizing flow model ($\mathcal{CNF}$) based on a chain of Masked Autoregressive Flows, which effectively incorporates conditional variables and models high-dimensional density distributions. We assess the performance of the $\mathcal{CNF}$ model using a simulated sample of Higgs boson decaying to diphoton events at the LHC. We create reconstruction-level observables using a smearing technique. We show that conditional normalizing flows can accurately model complex detector responses and their correlation. This method can potentially reduce the computational burden associated with generating large numbers of simulated events while ensuring that the generated events meet the requirements for data analyses. We make our code available at https://github.com/allixu/normalizing_flow_for_detector_response

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Color-octet scalars in Dirac gaugino models with broken R symmetry

In this work we study the collider phenomenology of color-octet scalars ( sgluons ) in supersymmetric models with Dirac gaugino masses that feature an explicitly broken R symmetry ( R - broken models ). We construct such models by augmenting minimal R -symmetric models with a fairly general set of supersymmetric and softly supersymmetry-breaking operators that explicitly break R symmetry. We then compute the rates of all significant two-body decays and highlight new features that appear as a result of R symmetry breaking, including enhancements to extant decay rates, novel tree- and loop-level decays, and improved cross sections of single sgluon production. We demonstrate in some detail how the familiar results from minimal R -symmetric models can be obtained by restoring R symmetry. In parallel to this discussion, we explore constraints on these models from the Large Hadron Collider. We find that, in general, R symmetry breaking quantitatively affects existing limits on color-octet scalars, perhaps closing loopholes for light CP-odd (pseudoscalar) sgluons while opening one for a light CP-even (scalar) particle. Qualitatively, however, we find that — much as for minimal R -symmetric models, despite stark differences in phenomenology — scenarios with broken R symmetry and two sgluons below the TeV scale can be accommodated by existing searches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Anomaly detection in collider physics via factorized observables

To maximize the discovery potential of high-energy colliders, experimental searches should be sensitive to unforeseen new physics scenarios. This goal has motivated the use of machine learning for unsupervised anomaly detection. In this paper, we introduce a new anomaly detection strategy called : factorized observables for regressing conditional expectations. Our approach is based on the inductive bias of factorization, which is the idea that the physics governing different energy scales can be treated as approximately independent. Assuming factorization holds separately for signal and background processes, the appearance of nontrivial correlations between low- and high-energy observables is a robust indicator of new physics. Under the most restrictive form of factorization, a machine-learned model trained to identify such correlations will in fact converge to the optimal new physics classifier. We test on a benchmark anomaly detection task for the Large Hadron Collider involving collimated sprays of particles called jets. By teasing out correlations between the kinematics and substructure of jets, our method can reliably extract percent-level signal fractions. This strategy for uncovering new physics adds to the growing toolbox of anomaly detection methods for collider physics with a complementary set of assumptions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2020

Disentangling contributions to small-system collectivity via scans of light nucleus-nucleus collisions

The observation of multiparticle azimuthal correlations in high-energy small-system collisions has led to intense debate on its origin and the possible coexistence from two competing theoretical scenarios: one based on initial-state intrinsic momentum anisotropy, and the other based on final-state interaction model (FSM) collective response to the collision geometry. To complement the previous scan of asymmetric collision systems ( p +Au, d +Au, and He+Au), we propose a scan of small symmetric collision systems at the Brookhaven National Laboratory Relativistic Heavy Ion Collider, such as C+C, O+O, Al+Al, and Ar+Ar$\sqrt{s_\text{NN}}$ = 0.2 TeV , to provide further insights in disentangling contributions from these two scenarios. These symmetric small systems have the advantage of providing a better controlled initial geometry dominated by the average shape of the overlap region as opposed to fluctuation-driven geometries in asymmetric systems. In this work, a transport model is employed to investigate the expected geometry response in the FSM scenario. Different trends of elliptic flow with increasing charge particle multiplicity are observed between symmetric and asymmetric systems, whereas triangular flow appears to show a similar behavior. Furthermore, a comparison of O+O collisions at $\sqrt{s_\text{NN}}$ = 0.2 TeV and at $\sqrt{s_\text{NN}}$ = 2.76 ₋ 7 TeV as proposed at the CERN Large Hadron Collider, provides a unique opportunity to disentangle the collision geometry effects at the nucleon level from those arising from subnucleon fluctuations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

On-Demand Column Joining for High Energy Physics

As the Large Hadron Collider (LHC) transitions into the High-Luminosity LHC (HL-LHC) era, the volume of data to be processed is expected to increase significantly. The CMS Experiment currently utilizes various data formats, including AOD, MiniAOD, and NanoAOD, each with different levels of detail and storage requirements. This paper addresses the challenges of data duplication and storage inefficiencies in high-energy physics (HEP) analyses by proposing an on-demand column-joining solution. This approach aims to reduce data duplication by enabling the dynamic combination of NanoAOD data with auxiliary information from larger data tiers, such as MiniAOD. The proposed solution leverages Trino, a high-performance distributed SQL query engine, to perform efficient and scalable data joins. Benchmarks using CMS OpenData demonstrate the feasibility of this approach, showing that it can handle large datasets with low latency. Integration with the scikit-hep ecosystem and the coffea analysis framework is also discussed, highlighting the potential for seamless end-to-end data processing and analysis. Ongoing and future work focuses on expanding benchmarks, integrating ServiceX for data transformation, and exploring the use of native object storage solutions.

Manganelli, Nicholas [Northeastern U.]↗
DOE OSTI2023

IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics

The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. CERN's Large Hadron Collider (LHC) represents a huge step forward in this quest. The discovery of the Higgs boson, the observation of exceedingly rare decays of $B$ mesons, and stringent constraints on many viable theories of physics beyond the Standard Model (SM) demonstrate the great scientific value of the LHC physics program. The next phase of this global scientific project will be the High-Luminosity LHC (HL-LHC) which will collect data starting circa 2029 and continue through the 2030s. The primary science goal is to search for physics beyond the SM and, should it be discovered, to study its implications. In the HL-LHC era, the ATLAS and CMS experiments will record around 100 times as many collisions as were used to discover the Higgs boson (and at twice the energy). Both NSF and DOE are making large detector upgrade investments so the HL-LHC can operate in this high-rate environment. Similar investment in software R&D for acquiring, managing, processing and analyzing HL-LHC data is critical to maximize the return-on-investment in the upgraded accelerator and detectors. This report presents a strategic plan for a possible second 5-year funded phase (2023 through 2028) for the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) which will close remaining software and computing gaps to deliver HL-LHC science.

43 PARTICLE ACCELERATORS↗