Search for high-mass dilepton resonances using 139 fb(-1) of pp collision data collected at root s=13 TeV with the ATLAS detector
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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New Particle Formation and Growth to Climate-Relevant Aerosols at a Background Remote Site in the Western Himalaya
New particle formation (NPF) can influence the Earth’s radiative budget when the newly formed particles grow to climate-relevant sizes. Here, we present analysis of 21-months of continuous aerosol size distribution measurements at a background remote site in the western Himalaya and provide observational evidence that newly formed particles grow to cloud condensation nuclei (CCN)-active sizes (i.e. >20-100 nm in diameter). Out of total 55 NPF events, 38 (66%) events occurred in the pre-monsoon season (March-May). NPF events were classified into those with and without pollution influence as polluted and cleaner, respectively, using black carbon data. The analysis of air mass age, based on the ratio of number concentration of Aitken to accumulation mode aerosols, indicated that NPF occurred in the relatively cleaner air masses reaching to the site. The median formation rate of 10 nm particles and particle growth rates for cleaner events were three-fold and two-fold, respectively, higher than polluted events. We present the first estimates of the survival probability of newly formed particles to 50 nm and 100 nm size, which was not attempted in an Indian environment previously. The survival probability to 50 nm particles ranged from 44 to 98%, with a mean and standard deviation of 82 ± 18%. On average, ~60% of the particles surviving to 50 nm survived to 100 nm, making the overall survival probability of 100 nm to 53 ± 31%. This indicates that the probability of nucleated particles growing to CCN-active sizes under a large source of condensing vapor (transported from nearby lower-altitude regions) and low pre-existing particle concentrations (background mountain site) is high compared to the previous studies. These findings highlight the importance of the efficiency of nucleation events for producing CCN, which is a critical basis of aerosol indirect effects.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Search for Heavy Higgs Bosons with the ATLAS Detector
The ATLAS experiment at the Large Hadron Collider performed searches for heavy Higgs bosons, whose presence would establish the existance of new physics. Searches for charged and neutral Higgs bosons are carried out using 8 or 13 TeV data for various production modes and in many different final states. No deviations from Standard Model expectations are observed. Exclusions limits are set on the production cross section and on parameters in various benchmark models.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Significant and Inevitable End-of-Twenty-First-Century Advances in Surface Runoff Timing in California’s Sierra Nevada
Abstract Using hybrid dynamical–statistical downscaling, 3-km-resolution end-of-twenty-first-century runoff timing changes over California’s Sierra Nevada for all available global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are projected. All four representative concentration pathways (RCPs) adopted by the Intergovernmental Panel on Climate Change’s Fifth Assessment Report are examined. These multimodel, multiscenario projections allow for quantification of ensemble-mean runoff timing changes and an associated range of possible outcomes due to both intermodel variability and choice of forcing scenario. Under a “business as usual” forcing scenario (RCP8.5), warming leads to a shift toward much earlier snowmelt-driven surface runoff in 2091–2100 compared to 1991–2000, with advances of as much as 80 days projected in the 35-model ensemble mean. For a realistic “mitigation” scenario (RCP4.5), the ensemble-mean change is smaller but still large (up to 30 days). For all plausible forcing scenarios and all GCMs, the simulated changes are statistically significant, so that a detectable change in runoff timing is inevitable. Even for the mitigation scenario, the ensemble-mean change is approximately equivalent to one standard deviation of the natural variability at most elevations. Thus, even when greenhouse gas emissions are curtailed, the runoff change is climatically significant. For the business-as-usual scenario, the ensemble-mean change is approximately two standard deviations of the natural variability at most elevations, portending a truly dramatic change in surface hydrology by the century’s end if greenhouse gas emissions continue unabated.
54 ENVIRONMENTAL SCIENCES↗
Measurement of vertical betatron oscillations using the straw tracking detectors for the E989 muon g-2 experiment at Fermilab.
The measurement of the anomalous magnetic moment of electrons and muons has been an important test of the Standard Model (SM) of particle physics over many decades. This is because it can be measured experimentally and calculated theoretically to a high precision. In particular the anomalous magnetic moment of the muon, a µ , is an ideal candidate for the search of new physics due to the combination of the muons large mass and relatively long lifetime. The current world’s most precise value of aµ was measured by the E821 experiment at the Brookhaven National laboratory (BNL). This achieved a precision of 540 ppb (463 ppb stat., 283 ppb syst.) and measured a ~ 3.5 σ deviation from the SM value [1]. This motivated a new experiment: the E989 muon g–2 experiment at the Fermi National Accelerator Laboratory (Fermilab) to confirm or reject this discrepancy. This experiment aims to gather a data sample 21 times larger than the BNL experiment and improve the determination of the systematic uncertainties by a factor of three and thereby achieve a fourfold increase in precision to 140 ppb [2]. If the aµ value were to remain unchanged, this improvement in precision would establish evidence for Beyond SM (BSM) physics with a significance of more than 7 standard deviations. The Fermilab experiment has the same methodology as the BNL experiment and reuses the experiment’s storage ring magnet. New, improved experimental apparatus has been introduced to reduce the systematic uncertainty on the a µ measurement. One such improvement is the addition of two straw tracking stations. These measure the trajectory of the positrons emitted from the (positive) muon decays which allows a detailed study of the spatial and temporal motion of the beam and critical crosschecks of the calorimeter data. This thesis describes in detail the design, construction and testing of the tracking detectors which were built at the University of Liverpool. A detailed study of the vertical motion of the beam is also presented. This study provides an important correction that must be applied to the data before a µ can be determined.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Hubble Parameter and Baryon Acoustic Oscillation Measurement Constraints on the Hubble Constant, the Deviation from the Spatially Flat ΛCDM Model, the Deceleration–Acceleration Transition Redshift, and Spatial Curvature
We construct a complete collection of reliable Hubble parameter H(z) data to redshift z ≤ 2.36 and use them with the Gaussian Process approach to determine continuous H(z) functions for various data subsets. From these continuous H(z)'s, summarizing across the data subsets considered, we find H 0 ~ 67 ± 4 km s–1 Mpc–1, more consistent with the recent lower values observed using a variety of techniques. In most data subsets, we see a cosmological deceleration–acceleration transition at 2σ significance, with the data subsets transition redshifts varying over $0.33\lt {z}_{\mathrm{da}}\lt 1.0$ at 1σ significance. We discover that the flat-ΛCDM model is consistent with the H(z) data to a z of 1.5 to 2.0, depending on data subset considered, with 2σ deviations from flat-ΛCDM above this redshift range. Using the continuous H(z) with baryon acoustic oscillation distance-redshift observations, we constrain the current spatial curvature density parameter to be ${{\rm{\Omega }}}_{K0}=-0.03\pm 0.21$, consistent with a flat universe, but the large error bar does not rule out small values of spatial curvature that are now under debate.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Space Shuttle Atmospheric ascent flight dynamics
The atmospheric ascent flight phase of the mated composite booster and orbiter is discussed. The composite recoverable space shuttle booster and orbiter exhibits unique flight control characteristics. This uniqueness results from large lifting surfaces and aerodynamic and structural assymetrics. An effective load relief technique reduces aerodynamic loads on both the booster and the orbiter. Reducing aerodynamic loads permits decreasing the structural weight of the lifting and stabilizing surfaces. An orbiter payload penalty is caused by trajectory deviations resulting from load relief. However, the net effect of an effective load relief technique is an increase in payload capability. Atmospheric launch dynamics investigations have been carried out for different configuration types, which include expendable, straight wing, delta wing, and ballistic recoverable boosters.
Patha, J. T.↗
Three-dimensional position and shape of the bow shock and their variation with Alfvenic, sonic and magnetosonic Mach numbers and interplanetary magnetic field orientation
A large set of bow shock crossings (i.e., 1392) observed by 17 spacecraft has been used to explore the three-dimensional shape and location of the Earth's bow shock and its dependence on solar wind and interplanetary magnetic field (IMF) conditions. This study investigates deviations from gas dynamic flow models associated with the magnetic terms in the magnetohydrodynamic (MHD) equations. Empirical models predicting the statistical position and shape of the bow shock for arbitrary values of the solar wind pressure, IMF, and Alfvenic Mach number (M(sub A)) have been derived. The resulting data set has been used to fit three-dimensional bow shock surfaces and to explore the variations in these surfaces with sonic (M(sub S)), Alfvenic (M(sub A)) and magnetosonic (M(sub MS)) Mach numbers. Analysis reveals that among the three Mach numbers, M(sub A) provides the best ordering of the least square bow shock curves. The subsolar shock is observed to move Earthward while the flanks flare outward in response to decreasing M(sub A); the net change represents a 6-10% effect. Variations due to changes in the IMF orientation were investigated by rotating the crossings into geocentric interplanetary medium coordinates. Past studies have suggested that the north-south extent of the bow shock surface exceeds the east-west dimension due to asymmetries in the fast mode Mach cone. This study confirms such a north-south versus east-west asymmetry and quantifies its variation with M(sub S), M(sub A), M(sub MS), and IMF orientation. A 2-7% effect is measured, with the asymmetry being more pronounced at low Mach numbers. Combining the bow shock models with the magnetopause model of Roelof and Sibeck (1993), variations in the magnetosheath thickness at different local times are explored. The ratio of the bow shock size to the magnetopause size at the subpolar point is found to be 1.46; at dawn and dusk, the ratios are found to be 1.89 and 1.93, respectively. The subsolar magnetosheath thickness is used to derive the polytropic index gamma according to the empirical relation of Spreiter et al. (1966). The resulting gamma = 2.3 suggests the empirical formula is inadequate to describe the MHD interaction between the solar wind and the magnetosphere.
Peredo, M.↗
Multi-Sensor Aerosol Products Sampling System
Global and local properties of atmospheric aerosols have been extensively observed and measured using both spaceborne and ground-based instruments, especially during the last decade. Unique properties retrieved by the different instruments contribute to an unprecedented availability of the most complete set of complimentary aerosol measurements ever acquired. However, some of these measurements remain underutilized, largely due to the complexities involved in analyzing them synergistically. To characterize the inconsistencies and bridge the gap that exists between the sensors, we have established a Multi-sensor Aerosol Products Sampling System (MAPSS), which consistently samples and generates the spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of aerosol products from multiple spacebome sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Samples of satellite aerosol products are extracted over Aerosol Robotic Network (AERONET) locations as well as over other locations of interest such as those with available ground-based aerosol observations. In this way, MAPSS enables a direct cross-characterization and data integration between Level-2 aerosol observations from multiple sensors. In addition, the available well-characterized co-located ground-based data provides the basis for the integrated validation of these products. This paper explains the sampling methodology and concepts used in MAPSS, and demonstrates specific examples of using MAPSS for an integrated analysis of multiple aerosol products.
Petrenko, M.↗
Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains
Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions.
Remotely sensed soil moisture validation↗
Crystallization and Thermoelectric Transport in Semiconductor Micro- and Nanostructures Under Extreme Conditions
This project focused on thermoelectric transport in semiconductor micro and nanostructures where moderate and typical operating voltages and currents lead to extreme thermal gradients and current densities. Models that describe behavior of semiconducting materials typically assume an equilibrium condition or slight deviations from it. In these cases the generation-recombination processes are assumed to have reached a local equilibrium for a given temperature. Hence, free carrier concentrations and their mobilities, band-gap, thermal conductivity, thermoelectric properties, mobility of atoms and mechanical properties of the material, can be described as a function of temperature. In the case of PN junctions under electrical bias, carrier concentrations can change up to ~ 1020 cm-3 and a drift-diffusion approximation is typically used to obtain the carrier concentrations while assuming that the material properties do not change. In non-equilibrium conditions, the assumption that the material properties remain the same may not be valid. While the increased conduction-band electron concentration may not have a drastic effect on the material, large hole concentration is expected to soften the material as ‘a hole’ comes into existence as a broken bond in the lattice. As the hole density approaches 1022 cm-3, the number of bonds holding the lattice together is significantly reduced, making it easier to break additional bonds, reduce band-gap and inhibit phonon transport. As these holes move away from where they were generated, local properties are expected to deviate significantly from the equilibrium case. Hence, temperature alone is not sufficient to describe the behavior of the material. The behavior of the solid material close to a molten region (liquid-solid interfaces) is also expected to deviate from the equilibrium case as a function of hole injection rate, which can be drastically increased or decreased in the presence of an electric field. In the past years we have investigated the possible thermoelectric explanation of asymmetric melting of self-heated Si micro-structures using equilibrium materials’ properties that exist in the literature. We have analyzed the contribution of the electrons and the holes and identified the generation-transport-recombination of minority carriers (GTR) as the reason for an extreme change in the thermal profile in presence of strong generation and electric field. A more complete analysis required construction of models that capture the individual generation and recombination processes to understand the thermal profile as well as the possibility of electronic softening and non-equilibrium melting of the structure below melting temperature. The possibility of melting a material at a lower temperature breaks the correlation between the atomic mobility and the kinetic energy in the system for a given temperature and may allow alternative growth processes. This may also be the mechanism behind ‘amorphization-without-melting in layered structures heated with laser pulses’ that has been reported earlier. The conventional models for semiconductors are constructed for low temperature operation and their projections to higher temperatures do not yield reasonable carrier concentrations. Using these models, the free hole concentrations are calculated to be on the order of 1019 cm-3 at melting, which also do not correlate well with the latent heat of fusion. The melt is expected to correspond to broken bond concentrations on the order of the atomic density (~5x1022 cm-3 for Silicon). Hence, using conventional models the thermoelectric contribution expected from the GTR process is estimated to be much smaller than it likely is. Our work focused on improving the computational models and electrical characterization of materials and devices to better understand thermoelectric trabsport under extremen thermal gradients and current densities. Specifically, during this project, we have - Expanded our computational models to include self-consistent solution of Poisson charge equation (together with current and heat equations currently solved) for improved accuracy of role of bipolar conduction, - Developed a crystallization model incorporating experimentally determined nucleation rates and growth velocities to enable simulation of grain growth, growth-from-melt, filament formation and retention, - Performed high-temperature characterization of relevant materials (including metal contacts, interfacial and insulation layers); electrical and thermal conductivities, Seebeck coefficient, carrier mobility and concentration, - Performed High-speed device-level characterization of metastable amorphous and crystalline phases, crystallization and amorphization dynamics, melting and crystalline growth-from-melt, - Observed and characterized formation of microplasmas in electrically stressed ZnO nanoforests.
36 MATERIALS SCIENCE↗
Development of high-fidelity models for liquid fuel spray atomization and mixing processes in transportation and energy systems
Significant inadequacies of current models for multiphase flows present a major barrier to rapid development of advanced high-efficiency low-emissions combustion devices. Liquid spray atomization processes largely determine fuel-air mixture formation, which subsequently govern combustion and controls performance, emissions, and durability of a device. The current study presents a fundamentally-consistent framework to model the effects of breakup processes, liquid drop deformations, and internal flow dynamics on mass, momentum, and energy exchange functions. This framework builds on the Taylor Analogy Breakup (TAB) model which naturally quantifies local drop deformation dynamics. Real-fluid multicomponent thermodynamic property modeling and Gradient Theory simulations facilitate accurate calculations of molecular two-phase interface exchange functions, surface tensions forces, drop oscillations, and breakup processes. The analysis establishes that these drop dynamics, along with finite liquid viscosity effects, significantly alter gas-liquid exchange functions. The study quantifies these effects for the resulting drag coefficients of liquid drops and demonstrates significant deviations from the classic dynamic drag model, which is widely applied in modern simulations performed in academia and industry. This work also quantifies effects, which originate from gas-liquid coupling dynamics, on evaporation and heating rates. The analysis establishes that the consideration of these coupling dynamics modify mass and energy transfer rates even more significantly than the corresponding drag forces from momentum exchange. This physical complexity, however, is largely neglected in modern studies from academia and industry. A new set of equations is presented to improve the modeling of drop breakup processes to address the current shortcomings in the prediction of resulting drops proper- ties over the full range of relevant breakup conditions. The framework is based on a refined energy balance equation which explicitly enforces drop momentum conservation during the breakup process. The introduced modeling framework is entirely derived from conservation equations for mass, momentum, and energy and does not, as a consequence, introduce new modeling constants. The significance of the developed modeling advances to fuel injection processes is demonstrated using Large Eddy Simulation (LES) with a Lagrangian-Eulerian modeling approach.
42 ENGINEERING↗
Observation of a cross-section enhancement near the production threshold in $\sqrt{s} = 13$ TeV pp collisions with the ATLAS detector
A measurement of $t\bar{t}$ production is presented in the invariant-mass region near the pair production threshold, $m_{t\bar{t}} \sim 345$ GeV, in final states with two charged leptons and multiple jets. The measurement is based on $140\,\mathrm{fb}^{-1}$ of proton–proton collision data collected at $\sqrt{s} = 13$ TeV with the ATLAS detector at the Large Hadron Collider. The data are compared to two models of $t\bar{t}$ production: a baseline model including only perturbative quantum chromodynamics (pQCD) predictions for the hard process at approximate next-to-next-to leading order accuracy in the strong coupling, and an extended model that, in addition, incorporates non-relativistic QCD simulations that also include the formation of colour-singlet quasi-bound-states near the $t\bar{t}$ threshold. The agreement between the data and the models is quantified via a profile-likelihood fit to the reconstructed $m_{t\bar{t}}$ distributions, in bins of two angular observables sensitive to spin-correlations in the $t\bar{t}$ system. An excess of events is observed over the baseline pQCD prediction, with an observed significance over 8 standard deviations. This excess is consistent with the formation of colour-singlet and spin-singlet S-wave quasi-bound $t\bar{t}$ states, as predicted by non-relativistic QCD, and corresponds to an observed cross-section of $9.3^{+1.4}_{-1.3}$ pb.
Large Hadron Collider↗
Adaptive Data-Driven Model Predictive Control for Heat Pipe Microreactors
To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Adaptable Data Driven Model Predictive Control for Heat Pipe Microreactors
To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Symmetric Kondo Lattice States in Doped Strained Twisted Bilayer Graphene
We use the topological heavy fermion (THF) model and its Kondo lattice (KL) formulation to study the possibility of a symmetric Kondo (SK) state in twisted bilayer graphene. Via a large-N approximation, we find a SK state in the KL model at fillings v = 0,±1,±2 where a KL model can be constructed. In the SK state, all symmetries are preserved and the local moments are Kondo screened by the conduction electrons. At the mean-field level of the THF model at v = 0,±1,±2,±3 we also find a similar symmetric state that is adiabatically connected to the symmetric Kondo state. We study the stability of the symmetric state by comparing its energy with the ordered (symmetry-breaking) states found in [H. Hu et al., Phys. Rev. Lett. 131, 026502 (2023)., Z.-D. Song and B. A. Bernevig, Phys. Rev. Lett. 129, 047601 (2022).] and find the ordered states to have lower energy at v = 0,±1,±2. However, moving away from integer fillings by doping the light bands, our mean-field calculations find the energy difference between the ordered state and the symmetric state to be reduced, which suggests the loss of ordering and a tendency toward Kondo screening. In order to include many-body effects beyond the mean-field approximation, we also performed dynamical mean-field theory calculations on the THF model in the nonordered phase. The spin susceptibility follows a Curie behavior at v = 0,±1,±2 down to ~2 K where the onset of screening of the local moment becomes visible. This hints to very low Kondo temperatures at these fillings, in agreement with the outcome of our mean-field calculations. At noninteger filling v = ±0.5,±0.8,±1.2 dynamical mean-field theory shows deviations from a 1/T susceptibility at much higher temperatures, suggesting a more effective screening of local moments with doping. Lastly, we study the effect of a C 3z -rotational-symmetry-breaking strain via mean-field approaches and find that a symmetric phase (that only breaks C 3z symmetry) can be stabilized at sufficiently large strain at v = 0,±1,±2. Our results suggest that a symmetric Kondo phase is strongly suppressed at integer fillings, but could be stabilized either at noninteger fillings or by applying strain.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Axion dark matter from frictional misalignment
We study the impact of sphaleron-induced thermal friction on the axion dark-matter abundance due to the interaction of an axion-like particle (ALP) with a dark non-abelian gauge sector in a secluded thermal bath. Thermal friction can either enhance the axion relic density by delaying the onset of oscillations or suppress it by damping them. We derive an analytical formula for the frictional adiabatic invariant, which remains constant along the axion evolution and which allows us to compute the axion relic density in a general set-up. Even in the most minimal scenario, in which a single gauge group is responsible for both the generation of the ALP mass and the friction force, we find that the resulting dark-matter abundance from the misalignment mechanism deviates from the standard scenario for axion masses m a ≳ 100 eV. We also generalize our analysis to the case where the gauge field that induces friction and the gauge sector responsible for the ALP mass are distinct and their couplings to the axion have a large hierarchy as can be justified by means of alignment or clockwork scenarios. We find that it is easy to open up the ALP parameter space where the resulting axion abundance matches the observed dark-matter relic density both in the traditionally over- and underabundant regimes. This conclusion also holds for the QCD axion.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Search for long-lived heavy neutral leptons with displaced vertices in proton-proton collisions at $\sqrt{\mathrm{s}}$ =13 TeV
A search for heavy neutral leptons (HNLs), the right-handed Dirac or Majorana neutrinos, is performed in final states with three charged leptons (electrons or muons) using proton-proton collision data collected by the CMS experiment at √s = 13 TeV at the CERN LHC. The data correspond to an integrated luminosity of 138 fb -1 . The HNLs could be produced through mixing with standard model neutrinos ν. For small values of the HNL mass (<20 GeV) and the square of the HNL-ν mixing parameter (10 -7 –10 -2 ), the decay length of these particles can be large enough so that the secondary vertex of the HNL decay can be resolved with the CMS silicon tracker. The selected final state consists of one lepton emerging from the primary proton-proton collision vertex, and two leptons forming a displaced, secondary vertex. No significant deviations from the standard model expectations are observed, and constraints are obtained on the HNL mass and coupling strength parameters, excluding previously unexplored regions of parameter space in the mass range 1–20 GeV and squared mixing parameter values as low as 10 -7 .
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗