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Applying Quantum Tomography to Hadronic Interactions

A proper description of inclusive reactions is expressed with density matrices. Quantum tomography reconstructs density matrices from experimental observables. We review recent work that applies quantum tomography to practical experimental data analysis. Almost all field-theoretic formalism and modeling used in a traditional approach is circumvented with great efficiency. Tomographically-determined density matrices can express information about quantum systems which cannot in principle be expressed with distributions defined by classical probability. Topics such as entanglement and von Neumann entropy can be accessed using the same natural language where they are defined. A deep relation exists between separability, as defined in quantum information science, and factorization, as defined in high energy physics. Factorization acquires a non-perturbative definition when expressed in terms of a conditional form of separability. An example illustrates how to go from data for momentum 4-vectors to a density matrix while bypassing almost all the formalism of the Standard Model.

Martens, J. C.↗

Search for heavy resonances decaying to ZZ or ZW and axion-like particles mediating nonresonant ZZ or ZH production at $\sqrt{s}$ = 13 TeV

A search has been performed for heavy resonances decaying to ZZ or ZW and for axion-like particles (ALPs) mediating nonresonant ZZ or ZH production, in final states with two charged leptons (ℓ = e, μ) produced by the decay of a Z boson, and two quarks produced by the decay of a Z, W, or Higgs boson H. The analysis is sensitive to resonances with masses in the range 450 to 2000 GeV. Two categories are defined corresponding to the merged or resolved reconstruction of the hadronically decaying boson. The search is based on data collected during 2016–2018 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb -1 . No significant excess is observed in the data above the standard model background expectation. Upper limits on the production cross section of heavy, narrow spin-2 and spin-1 resonances are derived as functions of the resonance mass, and exclusion limits on the production of bulk graviton particles and W' bosons are calculated in the framework of the warped extra dimensions and heavy vector triplet models, respectively. In addition, upper limits on the ALP-mediated diboson production cross section and ALP couplings to standard model particles are obtained in the framework of linear and chiral effective field theories. These are the first limits on nonresonant ALP-mediated ZZ and ZH production obtained by the LHC experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Speeding up particle track reconstruction using a parallel Kalman filter algorithm

One of the most computationally difficult problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is determining the trajectory of charged particles during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material effects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filter-based methods for highly parallel, many-core SIMD architectures that are now prevalent in high-performance hardware. In this paper, we discuss the design and performance of the improved tracking algorithm, referred to as mkFit. A key piece of the algorithm is the Matriplex library, containing dedicated code to optimally vectorize operations on small matrices. The physics performance of the mkFit algorithm is comparable to the nominal CMS tracking algorithm when reconstructing tracks from simulated proton-proton collisions within the CMS detector. We study the scaling of the algorithm as a function of the parallel resources utilized and find large speedups both from vectorization and multi-threading. mkFit achieves a speedup of a factor of 6 compared to the nominal algorithm when run in a single-threaded application within the CMS software framework.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.

97 MATHEMATICS AND COMPUTING↗

Experimental Measurements of the Wake of a Sphere at Subcritical Reynolds Numbers

This work experimentally investigated the flow phenomena and vortex structures in the wake of a sphere located in a water loop at Reynolds numbers of Re = 850, 1,250, and 1,700. Velocity fields in the wake region were obtained by applying the time-resolved stereoscopic particle image velocimetry (TR-SPIV) technique. From the acquired TR-SPIV velocity vector fields, the statistical values of mean and fluctuating velocities were computed. Spectral analysis, two-point velocity–velocity cross-correlation, proper orthogonal decomposition (POD) and vortex identification analyses were also performed. The velocity fields show a recirculation region that decreases in length with an increase of Reynolds numbers. The power spectra from the spectral analysis had peaks corresponding to a Strouhal number of St = 0.2, which is a value commonly found in the literature studies of flow over a sphere. The two-point cross-correlation analysis revealed elliptical structures in the wake, with estimated integral length scales ranging between 12% and 63% of the sphere diameter. The POD analysis revealed the statistically dominant flow structures that captured the most flow kinetic energy. It is seen that the flow kinetic energy captured in the smaller scale flow structures increased as Reynolds number increased. The POD modes contained smaller structure as the Reynolds number increased and as mode order increased. In addition, spectral analysis performed on the POD temporal coefficients revealed peaks corresponding to St = 0.2, similar to the spectral analysis on the fluctuating velocity. The ability of POD to produce low-order reconstructions of the flow was also utilized to facilitate vortex identification analysis, which identified average vortex sizes of 0.41D for Re1, 0.33D for Re2, and 0.32D for Re3.

Engineering↗

Universal Monte Carlo Event Generator

With the Jefferson Lab 12 GeV physics program underway and plans for the future Electron-Ion Collider (EIC), the nuclear physics community is entering a new era of exploration of QCD phenomena involving extensive data taking and event-level processing. This brings with it the potential for unprecedented access to multidimensional particle momentum distributions (PMDs) that can be connected to various theoretical frameworks by unfolding the emergent quantum mechanical properties of QCD using the PMDs. In practice, the PMDs are rendered as discretized histograms (typically one- or two-dimensional projections), and detector effects must be taken into account to unfold the pure detector effect-free PMDs that can be connected with theory. One of the challenges in this new era is obtaining faithful reconstructions of the multidimensional PMDs that preserve all of the inherent particle correlations. In this LDRD project we developed a novel approach using machine learning (ML) that solves this challenge, by avoiding entirely the need to use histograms as the main numerical technique to obtain the detector effect-free PMDs. The new approach is, moreover, scalable to higher dimensional PMDs. The central idea involves training neural networks (NNs) to generate synthetic event-level data (momenta 4-vectors of final state particles) to preserve all correlations among the particles. This is achieved by converting the trial synthetic vertex-level events to detector-level events using detector simulators. The NNs are then tuned using a specialized distance metric between the synthetic detector events and the real detector events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Machine learning-assisted upscaling analysis of reservoir rock core properties based on micro-computed tomography imagery

Optimum solutions for geologic modeling and reservoir simulation in industries such as oil and gas recovery and carbon capture and storage require accurate characterization of reservoir properties, which are often heterogeneous. In this study, high-quality micro-computed tomography (CT) images (1.475-μm/pixel resolution) of a sandstone core acquired from the Bell Creek oil field, USA, were used to provide nondestructive analysis of pore- and core-scale heterogeneity across measurement scales of 94–566 μm. In addition to characterizing the as-received sample, the core sample was flooded with brine to evaluate the capacity of the core sample to receive injected fluids. The micro-CT images were systematically segmented into pore spaces and grains via machine learning (ML) steps including image preprocessing, label creation using a traditional ML method based on limited manual image annotation, and finally U-Net segmentation. The segmented image stacks were reconstructed into digital cubes of various scales of voxel lengths. The 3D porosity values were calculated for all the digital cubes, and the fractal dimensions of the cubes were estimated using a box-counting method. The results showed that smaller cubes had greater heterogeneity and that the porosity values could be accurately estimated by fractal dimension and voxel lengths using ML models. For the core sample with brine flooding, the ratio of pores filled by brine to the total pore space was related to the porosity and could also be accurately estimated by porosity, fractal dimension, and voxel lengths using ML models. In conclusion, the results of this study demonstrate that the concept of fractal dimension can be a useful vector to perform upscaling analysis of sandstone rock heterogeneity from the pore to core scale and that fractal dimensions can be used to estimate porosity values and pore space-filling capacity across those scales.

58 GEOSCIENCES↗

SEARCHING FOR MESONIC DARK MATTER WITH THE HEAVY PHOTON SEARCH EXPERIMENT

Several highly-sensitive astrophysical experiments over the past couple of decades have demonstrated that the current abundance of visible Standard Model matter cannot explain galactic rotation curves, the expansion history of the Universe, or the apparent warping of light in empty space. Instead, one finds strong agreement with this body of experimental results upon positing the existence of an invisible particulate field, dark matter. Namely, a cold, weakly interacting dark matter component can explain all these phenomena. A number of accelerator-based experiments have been developed to search for the weak couplings/interactions of these particles, many of them concentrating on particle models with masses of tens to thousands of GeV. A relatively new, well-motivated model is a dark sector coupled to the Standard Model via a dark photon. The current abundance of dark matter can be obtained if one assumes that dark matter is coupled to light by a MeV to GeV particle with a U(1) symmetry. The parameter space of these models remains largely unexplored because they are difficult to probe experimentally. In this thesis, I analyze data from the Heavy Photon Search (HPS) detector, whose two detector halves closely surround the electron beam, providing acceptance to far-forward boosted interactions. This forward acceptance to highly boosted particles yields unprecedented sensitivity to MeV-scale invariant masses. I exhaustively optimize the offline reconstruction of the HPS detector. Each reconstruction object, from Silicon Vertex Tracker hits to tracks, is studied to maximize acceptance of dark matter events. I then use the 2021 run data to search for one model of dark-photon-mediated matter, the Strongly Interacting Massive Particle (SIMP). SIMP models provide self-interacting dark matter candidates that can form bound states resembling dark mesons. HPS can detect SIMPs through the decay of a dark vector boson (either a dark ¿ or ¿) into e+e- pairs. I obtain exclusion contours for SIMPs using both an optimized cuts-based selection and a machine-learning-based selection, advancing our knowledge of the nature of dark matter.

O'Dwyer, Rory [Stanford Univ., CA (United States).↗

Evidence of pair production of longitudinally polarised vector bosons and study of CP properties in ZZ → 4ℓ events with the ATLAS detector at $ \sqrt{s} $ = 13 TeV

A study of the polarisation and CP properties in ZZ production is presented. The used data set corresponds to an integrated luminosity of 140 fb –1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. The ZZ candidate events are reconstructed using two same-flavour opposite-charge electron or muon pairs. The production of two longitudinally polarised Z bosons is measured with a significance of 4.3 standard deviations, and its cross-section is measured in a fiducial phase space to be 2.45 ± 0.60 fb, consistent with the next-to-leading-order Standard Model prediction. The inclusive differential cross-section as a function of a CP-sensitive angular observable is also measured. The results are used to constrain anomalous CP-odd neutral triple gauge couplings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Efficient ptychographic phase retrieval via a matrix-free Levenberg-Marquardt algorithm

The phase retrieval problem, where one aims to recover a complex-valued image from far-field intensity measurements, is a classic problem encountered in a range of imaging applications. Modern phase retrieval approaches usually rely on gradient descent methods in a nonlinear minimization framework. Calculating closed-form gradients for use in these methods is tedious work, and formulating second order derivatives is even more laborious. Additionally, second order techniques often require the storage and inversion of large matrices of partial derivatives, with memory requirements that can be prohibitive for data-rich imaging modalities. We use a reverse-mode automatic differentiation (AD) framework to implement an efficient matrix-free version of the Levenberg-Marquardt (LM) algorithm, a longstanding method that finds popular use in nonlinear least-square minimization problems but which has seen little use in phase retrieval. Furthermore, we extend the basic LM algorithm so that it can be applied for more general constrained optimization problems (including phase retrieval problems) beyond just the least-square applications. Since we use AD, we only need to specify the physics-based forward model for a specific imaging application; the first and second-order derivative terms are calculated automatically through matrix-vector products, without explicitly forming the large Jacobian or Gauss-Newton matrices typically required for the LM method. We demonstrate that this algorithm can be used to solve both the unconstrained ptychographic object retrieval problem and the constrained “blind” ptychographic object and probe retrieval problems, under the popular Gaussian noise model as well as the Poisson noise model. We compare this algorithm to state-of-the-art first order ptychographic reconstruction methods to demonstrate empirically that this method outperforms best-in-class first-order methods: it provides excellent convergence guarantees with (in many cases) a superlinear rate of convergence, all with a computational cost comparable to, or lower than, the tested first-order algorithms.

36 MATERIALS SCIENCE↗

Search for single production of a vector-like T quark decaying to a top quark and a Z boson in the final state with jets and missing transverse momentum at $ \sqrt{s} $ = 13 TeV

A search is presented for single production of a vector-like T quark with charge 2/3 e, in the decay channel featuring a top quark and a Z boson, with the top quark decaying hadronically and the Z boson decaying to neutrinos. The search uses data collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb -1 recorded at the CERN LHC in 2016–2018. The search is sensitive to a T quark mass between 0.6 and 1.8 TeV with decay widths ranging from negligibly small up to 30% of the T quark mass. Reconstruction strategies for the top quark are based on the degree of Lorentz boosting of its final state. At 95% confidence level, the upper limit on the product of the cross section and branching fraction for a T quark of small decay width varies between 15 and 602 fb, depending on its mass. For a T quark with decay widths between 10 and 30% of its mass, this upper limit ranges between 16 and 836 fb. For most of the studied range, the results provide the best limits to date. This is the first search for single T quark production based on the full Run 2 data set of the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Primary track recovery in high-definition gas time projection chambers

Abstract We develop and validate a new algorithm called primary track recovery () that effectively deconvolves known physics and detector effects from nuclear recoil tracks in gas time projection chambers (TPCs) with high-resolution readout. This gives access to the primary track charge, length, and vector direction (helping to resolve the “head-tail” ambiguity). Additionally, provides a measurement of the transverse and longitudinal diffusion widths, which can be used to determine the absolute position of tracks in the drift direction for detector fiducialization. Using simulated helium recoils in an atmospheric pressure TPC with a 70:30 mixture of $$\hbox {He:CO}_2$$ He:CO 2 we compare the performance of to traditional methods for all key track variables. We find that the algorithm reduces reconstruction errors, including those caused by charge integration, for tracks with mean length-to-width ratios 1.4 and above, corresponding to recoil energies of 20 keV and above in the studied TPCs. We show that improves on existing methods for head-tail disambiguation, particularly for highly inclined tracks, and improves the determination of the absolute position of recoils on the drift axis via transverse diffusion. We find that can partially recover charge structure integrated out by the detector in the z direction, but that its determination of energy and length have worse resolution compared to existing methods. We use experimental data to qualitatively verify these findings and discuss implications for future directional detectors at the low-energy frontier.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Leptonic cascade decays of a heavy Higgs boson through vectorlike leptons at the LHC

We demonstrate the potential of fully leptonic cascade decays of a heavy neutral Higgs boson through vectorlike leptons as a simultaneous probe for extended Higgs sectors and extra matter particles at the LHC. The processes we explore are unique in that their event topologies lead to di-boson-like leptonic final states with a lepton pair which does not reconstruct the mass of a gauge boson. By recasting existing $2\ell$ + $E^{\text{miss}}_{R}$ and $3/4\ell$ searches channels using run2 data from the LHC we obtain model independent bounds on the masses of heavy scalars and vectorlike leptons and use these results to explore future prospects at the HL-LHC. Our results can be directly applied to any kind of new physics scenarios sharing the final states and the event topology. For concreteness, we apply our results to a benchmark scenario: a two Higgs doublet model type-II augmented with vectorlike leptons. Remarkably, even with current data the sensitivity of our analysis shows a reach for masses of a heavy neutral Higgs and vectorlike leptons up to 2 TeV and 1.5 TeV, respectively. Even for low tan β ≳ 1, the analysis retains sensitivity to heavy Higgs masses slightly above 1 TeV. The future sensitivities at the HL-LHC extend the reach for heavy Higgses and new leptons to 2.7 TeV and 2 TeV, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Advancing Artificial Intelligence with Liquid Argon Neutrino Experiments (Technical Report)

The grant allowed two main contributions: 1) The development of a first successful demonstration of the employment of Optimal Transport in liquid argon time projection chamber neutrino detectors. Optimal Transport, used in other contexts and specifically with LHC calorimetric data, was adapted to address a key particle identification challenge in LArTPCs: the separation of pi0 backgrounds from single-electrons produced in charged-current electron neutrino interactions. The work, leveraging ML methods such as k-nearest-neighbor (kNN) and support-vector-machine (SVM), showed an increase in background rejection of a factor of two or more. Work is now ongoing to incorporate this development in physics analyses for LArTPC experiments and more broadly expand the use of OT in LArTPC detectors including DUNE. This work was done in collaboration with the phenomenology group led by Nathaniel Craig at UCSB. 2) The deployment of NuGraph2, a graph neural network developed for LArTPC reconstruction, in the MicroBooNE experiment. NuGraph2 uses novel graph-neural-network methods on the rather simple LArTPC inputs of reconstructed hits, greatly simplifying the workflow compared to the use of waveform or signal-deconvolved wire ROIs. The network performed particle classification and was shown to address many challenging problems in LArTPC imaging including track-shower separation and the identification of protons and charged pions from primary muons. Our group collaborated with Giuseppe Cerati (FNAL scientist) who is one of the core developers of NuGraph2 to integrate this tool in MicroBooNE’s analysis framework. This consisted in tow key contributions: a) Studying performance on real data, which came with several months of iterations because the MC-trained version of the network was found to show significant bias that our group investigated and addressed. b) Integrating the output hit labeling of NuGraph2 into the existing particle tracking and shower reconstruction code. As a result of this work led by our team NuGraph2 is now enabling a suite of new analyses which benefit from enhanced capabilities and thus broader physics reach. The grant supported primarily the salary of UCSB graduate student Chuyue “Michaelia” Fang as well as partial summer salary support for PI Caratelli. Some funds were used for travel by Michaelia to ML related schools and conferences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Study of WH production through vector boson scattering and extraction of the relative sign of the W and Z couplings to the Higgs boson in proton-proton collisions at $\sqrt{s} = 13$ TeV

A search for the production of a W boson and a Higgs boson through vector boson scattering (VBS) is presented, using CMS data from proton-proton collisions at $\sqrt{s} = 13$ TeV collected from 2016 to 2018. The integrated luminosity of the data sample is 138 fb −1 . Selected events must be consistent with the presence of two jets originating from VBS, the leptonic decay of the W boson to an electron or muon, possibly also through an intermediate τ lepton, and a Higgs boson decaying into a pair of b quarks, reconstructed as either a single merged jet or two resolved jets. A measurement of the process as predicted by the standard model (SM) is performed alongside a study of beyond-the-SM (BSM) scenarios. The SM analysis sets an observed (expected) 95% co­fidence level upper limit of 14.3 (9.9) on the ratio of the measured VBS WH cross section to that expected by the SM. The BSM analysis, conducted within the so-called 𝜅 framework, excludes all scenarios with 𝜆 WZ < 0 that are consistent with current measurements, where 𝜆 WZ = 𝜅 W ∕𝜅 Z and 𝜅 W and 𝜅 Z are the HWW and HZZ coupling mod­fiers, respectively. The significance of the exclusion is beyond 5 standard deviations, and it is consistent with the SM expectation of 𝜆 WZ = 1.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for a heavy resonance decaying to a top quark and a W boson at $\sqrt{s}$ = 13 TeV in the fully hadronic final state

A search for a heavy resonance decaying to a top quark and a W boson in the fully hadronic final state is presented. The analysis is performed using data from proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb -1 recorded by the CMS experiment at the LHC. The search is focused on heavy resonances, where the decay products of each top quark or W boson are expected to be reconstructed as a single, large-radius jet with a distinct substructure. The production of an excited bottom quark, b*, is used as a benchmark when setting limits on the cross section for a heavy resonance decaying to a top quark and a W boson. The hypotheses of b* quarks with left-handed, right-handed, and vector-like chiralities are excluded at 95% confidence level for masses below 2.6, 2.8, and 3.1 TeV, respectively. These are the most stringent limits on the b* quark mass to date, extending the previous best limits by almost a factor of two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for heavy resonances decaying into a Z or W boson and a Higgs boson in final states with leptons and b -jets in 139 fb –1 of pp collisions at $ \sqrt{s} $ = 13 TeV with the ATLAS detector

This article presents a search for new resonances decaying into a Z or W boson and a 125 GeV Higgs boson h, and it targets the $ν\bar{ν}b\bar{b}, l^{+} l^{-} b\bar{b}$, or $ll^{±} νb\bar{b}$ final states, where $\ell$ = e or µ, in proton-proton collisions at $\sqrt{s}$ = 13 TeV. The data used correspond to a total integrated luminosity of 139 fb –1 collected by the ATLAS detector during Run 2 of the LHC at CERN. The search is conducted by examining the reconstructed invariant or transverse mass distributions of Zh or W h candidates for evidence of a localised excess in the mass range from 220 GeV to 5 TeV. No significant excess is observed and 95% confidence-level upper limits between 1.3 pb and 0.3 fb are placed on the production cross section times branching fraction of neutral and charged spin-1 resonances and CP-odd scalar bosons. These limits are converted into constraints on the parameter space of the Heavy Vector Triplet model and the two-Higgs-doublet model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗