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At least 1,045 records · Page 58
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DOE OSTI2018

Symmetry realization via a dynamical inverse Higgs mechanism

The Ward identities associated with spontaneously broken symmetries can be saturated by Goldstone bosons. However, when space-time symmetries are broken, the number of Goldstone bosons necessary to non-linearly realize the symmetry can be less than the number of broken generators. The loss of Goldstones may be due to a redundancy or the generation of a gap. In either case the associated Goldstone may be removed from the spectrum. This phenomena is called an Inverse Higgs Mechanism (IHM) and its appearance has a well defined mathematical condition. However, there are cases when a Goldstone boson associated with a broken generator does not appear in the low energy theory despite the lack of the existence of an associated IHM. In this paper we will show that in such cases the relevant broken symmetry can be realized, without the aid of an associated Goldstone, if there exists a proper set of operator constraints, which we call a Dynamical Inverse Higgs Mechanism (DIHM). We consider the spontaneous breaking of boosts, rotations and conformal transformations in the context of Fermi liquids, finding three possible paths to symmetry realization: pure Goldstones, no Goldstones and DIHM, or some mixture thereof. We show that in the two dimensional degenerate electron system the DIHM route is the only consistent way to realize spontaneously broken boosts and dilatations, while in three dimensions these symmetries could just as well be realized via the inclusion of non-derivatively coupled Goldstone bosons. We present the action, including the leading order non-linearities, for the rotational Goldstone (angulon), and discuss the constraint associated with the possible DIHM that would need to be imposed to remove it from the spectrum. Finally we discuss the conditions under which Goldstone bosons are non-derivatively coupled, a necessary condition for the existence of a Dynamical Inverse Higgs Constraint (DIHC), generalizing the results for Vishwanath and Wantanabe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Implications of the XENON1T excess on the dark matter interpretation

The dark matter interpretation for a recent observation of excessive electron recoil events at the XENON1T detector seems challenging because its velocity is not large enough to give rise to recoiling electrons of O(keV). Fast-moving or boosted dark matter scenarios are receiving attention as a remedy for this issue, rendering the dark matter interpretation a possibility to explain the anomaly. We investigate various scenarios where such dark matter of spin 0 and 1/2 interacts with electrons via an exchange of vector, axial-vector, pseudo-scalar, or scalar mediators. We find parameter values not only to reproduce the excess but to be consistent with existing bounds. Our study suggests that the scales of mass and coupling parameters preferred by the excess can be mostly affected by the type of mediator, and that significantly boosted dark matter can explain the excess depending on the mediator type and its mass choice. The method proposed in this work is general, and hence readily applicable to the interpretation of observed data in the dark matter direct detection experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Geometric entropies and their Hamiltonian flows

In holographic theories, the Hubeny-Rangamani-Takayanagi (HRT) area operator plays a key role in our understanding of the emergence of semiclassical Einstein-Hilbert gravity. When higher derivative corrections are included, the role of the area is instead played by a more general functional known as the geometric entropy. It is thus of interest to understand the flow generated by the geometric entropy on the classical phase space. In particular, the fact that the associated flow in Einstein-Hilbert or Jackiw-Teitelboim (JT) gravity induces a relative boost between the left and right entanglement wedges is deeply related to the fact that gravitational dressing promotes the von Neumann algebra of local fields in each wedge to type II. This relative boost is known as a boundary-condition-preserving (BCP) kink-transformation. In a general theory of gravity (with arbitrary higher-derivative terms), it is straightforward to show that the flow continues to take the above geometric form when acting on a spacetime where the HRT surface is the bifurcation surface of a Killing horizon. However, the form of the flow on other spacetimes is less clear. In this paper, we use the manifestly-covariant Peierls bracket to explore such flows in two-dimensional theories of JT gravity coupled to matter fields with higher derivative interactions. The results no longer take a purely geometric form and, instead, demonstrate new features that should be expected of such flows in general higher derivative theories. We also show how to obtain the above flows using Poisson brackets.

AdS-CFT correspondence↗
DOE OSTI2014

High precision predictions for exclusive VH production at the LHC

We present a resummation-improved prediction for pp → VH + 0 jets at the Large Hadron Collider. We focus on highly-boosted final states in the presence of jet veto to suppress the tt¯ background. In this case, conventional fixed-order calculations are plagued by the existence of large Sudakov logarithms α n s log m (p veto T /Q) for Q ~ m V + m H which lead to unreliable predictions as well as large theoretical uncertainties, and thus limit the accuracy when comparing experimental measurements to the Standard Model. In this work, we show that the resummation of Sudakov logarithms beyond the next-to-next-to-leading-log accuracy, combined with the next-to-next-to-leading order calculation, reduces the scale uncertainty and stabilizes the perturbative expansion in the region where the vector bosons carry large transverse momentum. Thus, our result improves the precision with which Higgs properties can be determined from LHC measurements using boosted Higgs techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Search for vector-like T quarks decaying to top quarks and Higgs bosons in the all-hadronic channel using jet substructure

We performed a search for a vector-like heavy T quark that is produced in pairs and that decays to a top quark and a Higgs boson. The data analysed correspond to an integrated luminosity of 19.7 fb -1 collected with the CMS detector in proton-proton collisions at √s=8 TeV. For T quarks with large mass values the top quarks and Higgs bosons can have significant Lorentz boosts, so that their individual decay products often overlap and merge. Methods are applied to resolve the substructure of such merged jets. We also derived upper limits on the production cross section of a T quark with mass between 500 and 1000 GeV/c 2 . If the T quark decays exclusively to tH, the observed (expected) lower limit on the mass of the T quark is 745 (773) GeV/c 2 at 95% confidence level. For the first time an algorithm is used for tagging boosted Higgs bosons that is based on a combination of jet substructure information and b tagging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Search for pair production of up-type vector-like quarks and for four-top-quark events in final states with multiple b-jets with the ATLAS detector

A search for pair production of up-type vector-like quarks ( T ) with a significant branching ratio into a top quark and either a Standard Model Higgs boson or a Z boson is presented. The same analysis is also used to search for four-top-quark production in several new physics scenarios. The search is based on a dataset of pp collisions at $\sqrt{s}$ =13 TeV recorded in 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb -1 . Data are analysed in the lepton+jets final state, characterised by an isolated electron or muon with high transverse momentum, large missing transverse momentum and multiple jets, as well as the jets + E T miss final state, characterised by multiple jets and large missing transverse momentum. The search exploits the high multiplicity of jets identified as originating from b -quarks, and the presence of boosted, hadronically decaying top quarks and Higgs bosons reconstructed as large-radius jets, characteristic of signal events. No significant excess above the Standard Model expectation is observed, and 95% CL upper limits are set on the production cross sections for the different signal processes considered. These cross-section limits are used to derive lower limits on the mass of a vector-like T quark under several branching ratio hypotheses assuming contributions from T → W b , Zt , Ht decays. The 95% CL observed lower limits on the T quark mass range between 0 . 99 TeV and 1 . 43 TeV for all possible values of the branching ratios into the three decay modes considered, significantly extending the reach beyond that of previous searches. Additionally, upper limits on anomalous four-top-quark production are set in the context of an effective field theory model, as well as in an universal extra dimensions model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Measurements of b -jet tagging efficiency with the ATLAS detector using $t\overline{t}$ events at $\sqrt{s}=13$ TeV

The efficiency to identify jets containing b-hadrons (b-jets) is measured using a high purity sample of dileptonic top quark-antiquark pairs ($t\bar{t}$) selected from the 36.1 fb -1 of data collected by the ATLAS detector in 2015 and 2016 from proton-proton collisions produced by the Large Hadron Collider at a centre-of-mass energy $\sqrt{s}=13$ TeV. Two methods are used to extract the efficiency from $t\bar{t}$ events, a combinatorial likelihood approach and a tag-and-probe method. A boosted decision tree, not using b-tagging information, is used to select events in which two b-jets are present, which reduces the dominant uncertainty in the modelling of the flavour of the jets. The efficiency is extracted for jets in a transverse momentum range from 20 to 300 GeV, with data-to-simulation scale factors calculated by comparing the efficiency measured using collision data to that predicted by the simulation. In conclusion, the two methods give compatible results, and achieve a similar level of precision, measuring data-to-simulation scale factors close to unity with uncertainties ranging from 2% to 12% depending on the jet transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Evidence for the charge asymmetry in $pp$ → $t\bar{t}$ production at $\sqrt{s}$ = 13 TeV with the ATLAS detector

Inclusive and differential measurements of the top–antitop ($t\bar{t}$) charge asymmetry ${A}_{C}^{t\bar{t}}$ and the leptonic asymmetry ${A}_{C}^{\ell\bar{\ell}}$ are presented in proton–proton collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS experiment at the CERN Large Hadron Collider. The measurement uses the complete Run 2 dataset, corresponding to an integrated luminosity of 139 fb –1 , combines data in the single-lepton and dilepton channels, and employs reconstruction techniques adapted to both the resolved and boosted topologies. A Bayesian unfolding procedure is performed to correct for detector resolution and acceptance effects. The combined inclusive $t\bar{t}$ charge asymmetry is measured to be ${A}_{C}^{t\bar{t}}$ = 0.0068 ± 0.0015, which differs from zero by 4.7 standard deviations. Differential measurements are performed as a function of the invariant mass, transverse momentum and longitudinal boost of the $t\bar{t}$ system. Both the inclusive and differential measurements are found to be compatible with the Standard Model predictions, at next-to-next-to-leading order in quantum chromodynamics perturbation theory with next-to-leading-order electroweak corrections. The measurements are interpreted in the framework of the Standard Model effective field theory, placing competitive bounds on several Wilson coefficients.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Search for supersymmetry in proton-proton collisions at $\sqrt{s} =$ 13 TeV in events with high-momentum Z bosons and missing transverse momentum

A search for new physics in events with two highly Lorentz-boosted Z bosons and large missing transverse momentum is presented. The analyzed proton-proton collision data, corresponding to an integrated luminosity of 137 fb$^{−1}$, were recorded at $ \sqrt{s} $ = 13 TeV by the CMS experiment at the CERN LHC. The search utilizes the substructure of jets with large radius to identify quark pairs from Z boson decays. Backgrounds from standard model processes are suppressed by requirements on the jet mass and the missing transverse momentum. No significant excess in the event yield is observed beyond the number of background events expected from the standard model. For a simplified supersymmetric model in which the Z bosons arise from the decay of gluinos, an exclusion limit of 1920 GeV on the gluino mass is set at 95% confidence level. This is the first search for beyond-standard-model production of pairs of boosted Z bosons plus large missing transverse momentum.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Jet charge and machine learning

Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For example, they have demonstrated effectiveness at boosted top or W boson identification or for quark/gluon discrimination. We explore these methods for the purpose of classifying jets according to their electric charge. We find that both neural networks that incorporate distance within the jet as an input and boosted decision trees including radial distance information can provide significant improvement in jet charge extraction over current methods. Specifically, convolutional, recurrent, and recursive networks can provide the largest improvement over traditional methods, in part by effectively utilizing distance within the jet or clustering history. Furthermore, the advantages of using a fixed-size input representation (as with the CNN) or a small input representation (as with the RNN) suggest that both convolutional and recurrent networks will be essential to the future of modern machine learning at colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

New angles on energy correlation functions

Jet substructure observables, designed to identify specific features within jets, play an essential role at the Large Hadron Collider (LHC), both for searching for signals beyond the Standard Model and for testing QCD in extreme phase space regions. In this paper, we systematically study the structure of infrared and collinear safe substructure observables, defining a generalization of the energy correlation functions to probe n-particle correlations within a jet. These generalized correlators provide a flexible basis for constructing new substructure observables optimized for specific purposes. Focusing on three major targets of the jet substructure community — boosted top tagging, boosted W/Z/H tagging, and quark/gluon discrimination — we use power-counting techniques to identify three new series of powerful discriminants: M i , N i , and U i . The Mi series is designed for use on groomed jets, providing a novel example of observables with improved discrimination power after the removal of soft radiation. The N i series behave parametrically like the N -subjettiness ratio observables, but are defined without respect to subjet axes, exhibiting improved behavior in the unresolved limit. Finally, the U i series improves quark/gluon discrimination by using higher-point correlators to simultaneously probe multiple emissions within a jet. Taken together, these observables broaden the scope for jet substructure studies at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Fuel Property Effects on Knock Propensity and Thermal Efficiency in a Direct-Injection Spark-Ignition Engine

Engine knock remains one of the major barriers to further improvement in thermal efficiency of Direct-Injection Spark-Ignition (DISI) engines. While Research Octane Number and Motor Octane Number are often used as standard rating methods for knock resistance of fuels, the impacts of other fuel properties on knock propensity in modern engines such as heat of vaporization (HoV) and laminar flame speed (LFS) require better understanding in order to co-optimize fuels and engine designs to achieve higher thermal efficiency and lower CO2 emission. In the present study, computational fluid dynamics (CFD) is used to model a boosted DISI engine with a focus on knock prediction and fuel property effects. A level-set G-equation model is employed to capture turbulent premixed combustion, and is coupled with a transported Livengood-Wu (L-W) integral approach to predict autoignition in the unburnt region. A criterion associated with the L-W integral is developed to accurately predict knock onset and knock-limited spark-advance. This model is then applied to a sensitivity analysis of HoV and LFS on knock tendency and thermal efficiency. The pressure-temperature trajectory framework is applied and extended to study the fuel effects on auto-ignition process in the engine. An existing efficiency-based merit function, which is derived from experiments for boosted SI engines, is evaluated and improved based on the current CFD results.

DISI↗
DOE OSTI2020

A novel improved model for building energy consumption prediction based on model integration

Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Constantly improving the performance of prediction models is the key to ensuring the efficient operation of energy systems. Moreover, accuracy is no longer the only factor in revealing model performance, it is more important to evaluate the model from multiple perspectives, considering the characteristics of engineering applications. Based on the idea of model integration, this paper proposes a novel improved integration model (stacking model) that can be used to forecast building energy consumption. The stacking model combines advantages of various base prediction algorithms and forms them into “meta-features” to ensure that the final model can observe datasets from different spatial and structural angles. Two cases are used to demonstrate practical engineering applications of the stacking model. A comparative analysis is performed to evaluate the prediction performance of the stacking model in contrast with existing well-known prediction models including Random Forest, Gradient Boosted Decision Tree, Extreme Gradient Boosting, Support Vector Machine, and K-Nearest Neighbor. The results indicate that the stacking method achieves better performance than other models, regarding accuracy (improvement of 9.5%–31.6% for Case A and 16.2%–49.4% for Case B), generalization (improvement of 6.7%–29.5% for Case A and 7.1%-34.6% for Case B), and robustness (improvement of 1.5%–34.1% for Case A and 1.8%–19.3% for Case B). The proposed model enriches the diversity of algorithm libraries of empirical models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A novel machine learning based identification of potential adopter of rooftop solar photovoltaics

With the proliferation of rooftop solar photovoltaic installations, there is a need to proactively predict consumer potential for solar photovoltaic adoption, for improved electric utility planning and operation. Traditional analytical modeling approaches are limited to a few survey features and a larger part of the survey would remain untouched by the decision model. This article presents a novel, data-driven modeling approach that strategically prunes a large set of consumer profile features using a machine learning framework to train a model for predicting potential solar adoption. The approach utilizes the Gradient Boosting Decision Tree model through a Light Gradient Boosting framework that improves significantly over the poor prediction accuracy of the existing approaches. Model training using focal-loss based supervision is used to overcome the difficulty in identifying the potential adopters that is inherent in conventional data-driven models. In addition, to overcome possible data sparsity in a limited survey sample, a Generative Adversarial Network is presented to create synthetic user samples and its effectiveness on model performance is assessed. A Bayesian optimization approach is used to systematically arrive at the hyperparameters of the proposed model. Validation of the presented approach on a survey data collected by the National Rural Electric Cooperative Association in Virginia in 2018 demonstrates the excellent predictive capability of the machine learning based approach to modeling solar adoption reliably.

14 SOLAR ENERGY↗
DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗
DOE OSTI2016

ESAT6 inhibits autophagy flux and promotes BCG proliferation through MTOR

In recent years, increasing studies have found that pathogenic Mycobacterium tuberculosis (Mtb) inhibits autophagy, which mediates the anti-mycobacterial response, but the mechanism is not clear. We previously reported that secretory acid phosphatase (SapM) of Mtb can negatively regulate autophagy flux. Recently, another virulence factor of Mtb, early secretory antigenic target 6 (ESAT6), has been found to be involved in inhibiting autophagy, but the mechanism remains unclear. In this study, we show that ESAT6 hampers autophagy flux to boost bacillus Calmette-Guerin (BCG) proliferation and reveals a mechanism by which ESAT6 blocks autophagosome-lysosome fusion in a mammalian target of rapamycin (MTOR)-dependent manner. In both Raw264.7 cells and primary macrophages derived from the murine abdominal cavity (ACM), ESAT6 repressed autophagy flux by interfering with the autophagosome-lysosome fusion, which resulted in an increased load of BCG. Impaired degradation of LC3Ⅱ and SQSTM1 by ESAT6 was related to the upregulated activity of MTOR. Contrarily, inhibiting MTOR with Torin1 removed the ESAT6-induced autophagy block and lysosome dysfunction. Furthermore, in both Raw264.7 and ACM cells, MTOR inhibition significantly suppressed the survival of BCG. In conclusion, our study highlights how ESAT6 blocks autophagy and promotes BCG survival in a way that activates MTOR. - Highlights: • A mechanism for disruping autophagy flux induced by ESAT6. • ESAT6-inhibited autophagy is MTOR-dependent. • ESAT6-boosted BCG is MTOR-dependent.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Short-term culture with IL-2 is beneficial for potent memory chimeric antigen receptor T cell production

Interleukin-2 (IL-2) has been extensively used to boost the body's immune cells, especially T cells. IL-2 is a cytokine that for many years was used to activate and amplify T cells. Due to its potent T cell growth-inducing functions in vitro, for many years, IL-2 was used for the culture and expansion of various T cell products, including tumor-infiltrating lymphocytes (TIL), T cell receptors T cells (TCR T), or genetically engineered cells with chimeric antigen receptors T cells (CAR T). Despite its positive effect on T cell production, the side-effect is not well studied. Here, we reported that long-term culture with IL-2 promotes terminal differentiation and impairs rather than boosts the function of chimeric antigen receptor T cells. However, short-term culture with IL-2 predominantly generates memory CAR T cell favorable for cancer treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Knockdown of long noncoding RNA XIST alleviates oxidative low-density lipoprotein-mediated endothelial cells injury through modulation of miR-320/NOD2 axis

Highlights: • lncRNA XIST was upregulated in HUVECs stimulated by ox-LDL. • Knockdown of XIST boosted cell viability and suppressed cell apoptosis. • XIST regulated the expression of NOD2 by sponging miR-320. • XIST exerts its role via modulation of miR-320/NOD2 axis in ox-LDL-treated HUVECs. Atherosclerosis remains to be one of the most common vascular disorders resulting in morbidity and mortality in the world. Recent studies suggested that endothelial cells (ECs) injury caused by oxidative low-density lipoprotein (ox-LDL) is an early marker for atherosclerosis. Nevertheless, the mechanisms of ox-LDL-induced ECs injury are complicated and largely unknown. Here, we found lncRNA XIST (X-inactive specific transcript) was upregulated in human umbilical vein endothelial cells (HUVECs) stimulated by ox-LDL. Knockdown of XIST boosted the cell viability and suppressed cell apoptosis under ox-LDL stimuli. Further experiments identified XIST regulated the expression of Nucleotide-Binding Oligomerization Domain 2 (NOD2) by sponging miR-320. XIST silencing exerted a protective effect on ox-LDL-induced HUVECs injury via miR-320/NOD2 regulatory network. Our data provide insight into the role of the lncRNA XIST in ox-LDL mediated ECs injury, which can aid in developing new therapeutic strategies for the treatment of atherosclerosis.

60 APPLIED LIFE SCIENCES↗