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At least 19 records

Recent Standard Model measurements

A selection of recent Standard Model measurements from ATLAS, CMS, D0 and HERA Collaborations is presented. The topics include studies of QCD with jets, photons and vector bosons as well as the latest measurements of the strong coupling constant. The status and prospects of precision measurements of the $W$-boson mass, the mixing angle of the electroweak interaction and the top-quark mass are also presented followed by recent results in the top-quark sector, on multibosons produced inclusively and on the study of the vector boson fusion and scattering. These measurements and studies provide stringent tests of the Standard Model. Deviations with respect to the Standard Model predictions are valuable probes of potential New Physics effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Concurrent Inter-Model Spread of Boreal Winter Westerly Jet Meridional Positions Between the Northern and Southern Hemispheres in CMIP6 Models

Here, this study investigates the inter-model spread of climatological extratropical westerly jets in boreal winter, using the historical simulation of 52 Coupled Model Intercomparison Project phase 6 (CMIP6) models from 1851 to 2014. The results show that there is a substantial spread in the latitude of the upper-tropospheric westerly jet across models, characterised by large inter-model standard deviations to both the poleward and equatorward sides of the jet axis, although the multi-model ensemble mean (MME) performs well in simulating meridional position of westerly jets. Furthermore, we detect the consistency of inter-model jet position spread between the Northern and Southern Hemispheres, based on the inter-model empirical orthogonal function (EOF) decomposition and correlation of regional-averaged zonal winds. Specifically, the models that simulate the westerly jets poleward/equatorward relative to the MME position in one hemisphere also tend to simulate the jets poleward/equatorward in the other hemisphere. Accordingly, we define a global jet spread index to depict the concurrence of jet shift in the two hemispheres. The results of inter-model regression analyses based on this index indicate that the models positioning the jets poleward than the MME tend to simulate a wider Hadley Cell, a poleward-shifted Ferrel Cell in the Southern Hemisphere, enhanced precipitation in the subtropics and suppressed precipitation in the tropics, and warmer sea surface temperatures in the subtropics and mid-latitudes. The present results suggest that improving the simulation of jet positions in climate models requires a comprehensive consideration of thermal states in the tropics and subtropics/mid latitudes.

54 ENVIRONMENTAL SCIENCES↗

Data-assimilated time-lapse visco-acoustic full-waveform inversion: Theory and application for injected CO 2 plume monitoring

Continuous seismic monitoring for quantifying CO 2 plume migration and detection of any potential leakages in the subsurface is essential for the security of long-term anthropogenic carbon dioxide geologic storage. Traditional time-lapse full-waveform inversion (TLFWI) methods aim to map the CO 2 distribution by estimating seismic velocity changes, but recent studies find that CO 2 -induced attenuation is an important complement to seismic velocity for tracking the CO 2 plumes and even quantifying the CO 2 saturation. We have developed a novel data-assimilated TLFWI method to construct high-resolution time-lapse velocity and attenuation changes from dense time-lapse monitoring data. This method consists of two theoretical developments: visco-acoustic full-waveform inversion (QFWI) and multiparameter hierarchical matrix-powered extended Kalman filter (mHiEKF). The method is capable of (1) posing temporal constraints to retrieve time-lapse information from dense monitoring data by using mHiEKF, (2) accurately recovering high-spatial-resolution velocity and attenuation perturbations using first-order equation system-based QFWI, and (3) providing the model uncertainty by estimating their model standard deviation. With numerical examples, we first find the effectiveness of the new QFWI on estimating accurate velocity and attenuation models simultaneously. Then, a CO 2 leakage case and a realistic Frio-II CO 2 monitoring case are presented to find the advantages and applicability of our data-assimilated QFWI method for estimating time-lapse changes using dense time-lapse monitoring surveys. Here, by assimilating time-lapse seismic monitoring data over time, our data-assimilated QFWI method can improve the resolution of velocity and attenuation changes and decrease their model uncertainties.

58 GEOSCIENCES↗

Do Machine Learning Approaches Offer Skill Improvement for Short-Term Forecasting of Wind Gust Occurrence and Magnitude?

Abstract Wind gusts, and in particular intense gusts, are societally relevant but extremely challenging to forecast. This study systematically assesses the skill enhancement that can be achieved using artificial neural networks (ANNs) for forecasting of wind gust occurrence and magnitude. Geophysical predictors from the ERA5 reanalysis are used in conjunction with an autoregressive term in regression and ANN models with different predictors, and varying model complexity. Models are derived and assessed for the warm (April–September) and cold (October–March) seasons for three high passenger volume airports in the United States. Model uncertainty is assessed by deriving models for 1000 different randomly selected training (70%) and testing (30%) subsets. Gust prediction fidelity in independent test samples is critically dependent on inclusion of an autoregressive term. Gust occurrence probabilities derived using five-layer ANNs exhibit consistently higher fidelity than those from regression models and shallower ANNs. Inclusion of the autoregressive term and increasing the number of hidden layers in ANNs from 1 to 5 also improve the model performance for gust magnitudes (lower RMSE, increased correlation, and model standard deviations that more closely approximate observed values). Deeper ANNs (e.g., 20 hidden layers) exhibit higher skill in forecasting strong (17–25.7 m s −1 ) and damaging (≥25.7 m s −1 ) wind gusts. However, such deep networks exhibit evidence of overfitting and still substantially underestimate (by 50%) the frequency of strong and damaging wind gusts at the three airports considered herein. Significance Statement Improved short-term forecasting of wind gusts will enhance aviation safety and logistics and may offer other societal benefits. Here we present a rigorous investigation of the relative skill of models of wind gust occurrence and magnitude that employ different statistical methods. It is shown that artificial neural networks (ANNs) offer considerable skill enhancement over regression methods, particularly for strong and damaging wind gusts. For wind gust magnitudes in particular, application of deeper learning networks (e.g., five or more hidden layers) offers tangible improvements in forecast accuracy. However, deeper networks are vulnerable to overfitting and exhibit substantial variability with the specific training and testing data subset used. Also, even deep ANNs reproduce only half of strong and damaging wind gusts. These results indicate the need for future work to elucidate the dynamical mechanisms of intense wind gusts and advance solutions to their prediction.

54 ENVIRONMENTAL SCIENCES↗

Technical note: 3-hourly temporal downscaling of monthly global terrestrial biosphere model net ecosystem exchange

Here, the land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO 2 fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO 2 fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004–2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5° × 0.5°, 2.0° × 2.5°, and 4.0° × 5.0° (latitude × longitude).

54 ENVIRONMENTAL SCIENCES↗

The Measurement of the Anomalous Magnetic Moment of the Muon at Fermilab

The anomalous magnetic moment of the muon is one of the most precisely measured quantities in experimental particle physics. Its latest measurement at Brookhaven National Laboratory deviates from the Standard Model expectation by approximately 3.5 standard deviations. The goal of the new experiment, E989, now under construction at Fermilab, is a fourfold improvement in precision. Here in this article, we discuss the details of the future measurement and its current status.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Studies of Zγ production in association with a high-mass dijet system in pp collisions at $\sqrt{s}=8$ TeV with the ATLAS detector

The production of a Z boson and a photon in association with a high-mass dijet system is studied using 20.2 fb -1 of proton-proton collision data at a centre-of-mass energy of $\sqrt{s}$ = 8 TeV recorded with the ATLAS detector in 2012 at the Large Hadron Collider. Final states with a photon and a Z boson decaying into a pair of either electrons, muons, or neutrinos are analysed. Electroweak and total pp → Zγjj cross-sections are extracted in two fiducial regions with different sensitivities to electroweak production processes. Quartic couplings of vector bosons are studied in regions of phase space with an enhanced contribution from pure electroweak production, sensitive to vector-boson scattering processes VV → Zγ. Finally, no deviations from Standard Model predictions are observed and constraints are placed on anomalous couplings parameterized by higher-dimensional operators using effective field theory.

43 PARTICLE ACCELERATORS↗

Search for new phenomena in events with three or more charged leptons in pp collisions at $ \sqrt{s}=8 $ TeV with the ATLAS detector

A generic search for anomalous production of events with at least three charged leptons is presented. The data sample consists of pp collisions at √s=8 TeV collected in 2012 by the ATLAS experiment at the CERN Large Hadron Collider, and corresponds to an integrated luminosity of 20.3 fb -1 . Events are required to have at least three selected lepton candidates, at least two of which must be electrons or muons, while the third may be a hadronically decaying tau. Selected events are categorized based on their lepton flavour content and signal regions are constructed using several kinematic variables of interest. No significant deviations from Standard Model predictions are observed. Model-independent upper limits on contributions from beyond the Standard Model phenomena are provided for each signal region, along with prescription to re-interpret the limits for any model. Constraints are also placed on models predicting doubly charged Higgs bosons and excited leptons. For doubly charged Higgs bosons decaying to eτ or μτ, lower limits on the mass are set at 400 GeV at 95% confidence level. For excited leptons, constraints are provided as functions of both the mass of the excited state and the compositeness scale Λ, with the strongest mass constraints arising in regions where the mass equals Λ. In such scenarios, lower mass limits are set at 3.0 TeV for excited electrons and muons, 2.5 TeV for excited taus, and 1.6 TeV for every excited-neutrino flavour.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Search for Leptoquarks Coupled to Third-Generation Quarks in Proton-Proton Collisions at s = 13 TeV

Three of the most significant measured deviations from standard model predictions, the enhanced decay rate for B $\to$ D$^{(*)}\tau\nu$, hints of lepton universality violation in B $\to$ K$^{(*)}\ell\ell$ decays, and the anomalous magnetic moment of the muon, can be explained by the existence of leptoquarks (LQs) with large couplings to third-generation quarks and masses at the TeV scale. The existence of these states can be probed at the LHC in high energy proton-proton collisions. A novel search is presented for pair production of LQs coupled to a top quark and a muon using data at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb$^{-1}$, recorded by the CMS experiment. No deviation from the standard model prediction has been observed and scalar LQs decaying exclusively into t$\mu$ are excluded up to masses of 1420 GeV. The results of this search are combined with those from previous searches for LQ decays into t$\tau$ and b$\nu$, which excluded scalar LQs below masses of 900 and 1080 GeV. Vector LQs are excluded up to masses of 1190 GeV for all possible combinations of branching fractions to t$\mu$, t$\tau$ and b$\nu$. With this analysis, all relevant couplings of LQs with an electric charge of -1/3 to third-generation quarks are probed for the first time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CMB and matter power spectra with non-linear dark-sector interactions

An interaction between dark matter and dark energy, proportional to the product of their energy densities, results in a scaling behavior of the ratio of these densities with respect to the scale factor of the Robertson-Walker metric. This gives rise to a class of cosmological models which deviate from the standard model in an analytically tractable way. In particular, it becomes possible to quantify the role of potential dark-energy perturbations. We investigate the impact of this interaction on the structure formation process. Using the (modified) CAMB code we obtain the CMB spectrum as well as the linear matter power spectrum. It is shown that the strong degeneracy in the parameter space present in the background analysis is considerably reduced by considering Planck data. Our analysis is compatible with the ΛCDM model at the 2σ confidence level with a slightly preferred direction of the energy flow from dark matter to dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗

An investigation of non-canonical mixing in red giant stars using APOGEE 12 C/ 13 C ratios observed in open cluster stars

Standard stellar evolution theory poorly predicts the surface abundances of chemical species in low-mass, red giant branch (RGB) stars. Observations show an enhancement of p–p chain and CNO cycle products in red giant envelopes, which suggests the existence of non-canonical mixing that brings interior burning products to the surface of these stars. The 12 C/ 13 C ratio is a highly sensitive abundance metric used to probe this mixing. We investigate extra RGB mixing by examining: (1) how 12 C/ 13 C is altered along the RGB, and (2) how 12 C/ 13 C changes for stars of varying age and mass. Our sample consists of 43 red giants, spread over 15 open clusters from the Sloan Digital Sky Survey’s APOGEE DR17, that have reliable 12 C/ 13 C ratios derived from their APOGEE spectra. We vetted these 12 C/ 13 C ratios and compared them as a function of evolution and age/mass to the standard mixing model of stellar evolution, and to a model that includes prescriptions for RGB thermohaline mixing and stellar rotation. We find that the observations deviate from standard mixing models, implying the need for extra mixing. Additionally, some of the abundance patterns depart from the thermohaline model, and it is unclear whether these differences are due to incomplete observations, issues inherent to the model, our assumption of the cause of extra mixing, or any combination of these factors. Nevertheless, the surface abundances across our age/mass range clearly deviate from the standard model, agreeing with the notion of a universal mechanism for RGB extra mixing in low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AIC{sub c}. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. Conclusions: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.

60 APPLIED LIFE SCIENCES↗

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling↗

Effective radiative forcing and adjustments in CMIP6 models

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

54 ENVIRONMENTAL SCIENCES↗

GLAD-M35: a joint P and S global tomographic model with uncertainty quantification

We present our third and final generation joint P and S global adjoint tomography (GLAD) model, GLAD-M35, and quantify its uncertainty based on a low-rank approximation of the inverse Hessian. Starting from our second-generation model, GLAD-M25, we added 680 new earthquakes to the database for a total of 2160 events. New P-wave categories are included to compensate for the imbalance between P- and S-wave measurements, and we enhanced the window selection algorithm to include more major-arc phases, providing better constraints on the structure of the deep mantle and more than doubling the number of measurement windows to 40 million. Two stages of a Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton inversion were performed, each comprising five iterations. With this BFGS update history, we determine the model’s standard deviation and resolution length through randomized singular value decomposition.

58 GEOSCIENCES↗

Search for new physics in the final state with a single photon and large missing transverse momentum in proton-proton collisions at √𝑠 =13 TeV

A search for new physics in events featuring a single photon and missing transverse momentum is presented, using proton-proton √𝑠 =13 TeV collision data corresponding to an integrated luminosity of 101 fb −1 collected by the CMS experiment at the CERN LHC between 2017 and 2018. This analysis, combined with a previous study of 36 fb −1 of 2016 data (totaling 137 fb −1 ), reveals no significant deviations from standard model expectations. The results are then used to establish 95% confidence level limits on parameters in theoretical models involving dark matter and large extra dimensions. Compared to the 2016-only analysis, this search achieves up to a 14% improvement in exclusion reach for mediator masses in simplified dark matter models, along with 11% and 10% enhancements in the limits on the effective field theory suppression scale and the fundamental Planck scale, respectively. These results are the most stringent constraints on these parameters to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗