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At least 415 records · Page 23

Search for new physics in final states with low transverse energy photon and missing transverse energy in proton-proton collisions at $\sqrt{s} = 8$ TeV

With the recent discovery of the Higgs boson at the Large Hadron Collider (LHC), the next set of goals for the Compact Muon Solenoid (CMS) experiment includes characterizing the newly discovered particle and probing for new physics beyond the Standard Model. Results from a search for new physics in the final state with a low transverse energy photon and missing transverse energy, using a data set corresponding to an integrated luminosity of 7.3/fb collected in proton-proton collisions at 8 TeV with the CMS detector is presented. Due to the large background rate for this final state, a novel strategy was used to collect this dataset from August through December of 2012. Such final state can arise from models involving dark matter production or exotic decays of the Higgs boson in low-scale supersymmetry breaking scenarios. In the absence of deviations from the Standard Model predictions, limits are set on the probability of an exotic decay of the Higgs boson. The phase space consisting of a photon with a transverse energy of at least 45 GeV and significant missing transverse energy was further examined in a model independent way by varying the selection requirements on the missing transverse energy and the transverse mass of the system. Upper limits at the 95% confidence level on production cross section of possible processes resulting in this final state were set. Additional and complementary results from a search for new physics in the final states containing a high-energy photon and missing transverse energy are also presented, using the data set corresponding to an integrated luminosity of 19.6/fb collected in proton-proton collisions at 8 TeV. In the absence of any significant deviation from the Standard Model predictions, improved limits are set on dark matter production and on the parameters of a model with large extra dimensions. Upper limits at a 95% confidence level on the production cross section of possible processes resulting in the final state with the photon transverse momentum greater than 145 GeV and missing transverse energy greater than 140 GeV were set.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CLUSTERED CEPHEID VARIABLES 90 KILOPARSECS FROM THE GALACTIC CENTER

Distant regions close to the plane of our Galaxy are largely unexplored by optical surveys as they are hidden by dust. We have used near-infrared data (which minimizes dust obscuration) from the ESO Public survey VISTA Variables of the Via Lactea to search for distant stars at low latitudes. We have discovered four Cepheid variables within an angular extent of 1° centered at a Galactic longitude of l = −27.°4 and a Galactic latitude of b = −1.°08. We use the tightly constrained period–luminosity relationship that these pulsating stars obey to derive distances. We infer an average distance to these Cepheid variables of 90 kpc. The Cepheid variables are highly clustered in angle (within 1°) and in distance (the standard deviation of the distances is 12 kpc). These young (∼100 Myr old), pulsating stars are unexpected at such large distances from the Galactic disk, which terminates at ∼15 kpc. The highly clustered nature in distance and angle of the Cepheid variables suggests that the stars may be associated with a dwarf galaxy; its location and mass were earlier predicted by a dynamical analysis. The Cepheids are at an average distance of ∼2 kpc from the plane and their maximum projected separation is ∼1 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗

Automated Assembly Progress Monitoring in Modular Construction Factories Using Computer Vision-Based Instance Segmentation

Modular construction has recently gained interest as a transformative construction method. In this method, a large portion of the construction is performed inside factories, where processes are fast-paced and interdependent; therefore, any deviation from the schedule can delay the production. Such deviations are frequent in modular factories due to the labor-intensive nature of the tasks. This propagation of delays can be mitigated by continuously monitoring each process; however, current manual monitoring methods are laborious, and recently proposed contact sensor-based methods are intrusive to the work. In addition, recent computer vision-based monitoring methods inside factories are limited to detection algorithms that fail to provide the pixel-level accuracy required for assembly progress monitoring in highly occluded factory scenes, and they require a large number of manual annotations. Therefore, this paper proposes a method to monitor the installation of subassemblies in modular construction factories using mask R-CNN instance segmentation and improves the data efficiency of the model using a copy-paste augmentation method. This method was validated on the CCTV videos captured from a modular construction factory in the US, resulting in a 9% mAP improvement in segmentation.

computer vision↗

Optimization-Based Calibration of FAST.Farm Parameters Against SOWFA

FAST.Farm is a medium-delity wind farm modeling tool that can be used to assess power and loads contributions of wind turbines in a wind farm. The objective of this paper is to undertake a calibration procedure to set the user parameters of FAST.Farm to accurately represent results from large-eddy simulations. The results provide an in- depth analysis of the comparison of FAST.Farm and large-eddy simulations before and after calibration. The comparison of FAST.Farm and large-eddy simulation results are presented with respect to streamwise and radial velocity components as well as wake-meandering statistics (mean and standard deviation) in the lateral and vertical directions under different atmospheric and turbine operating conditions.

17 WIND ENERGY↗

Planck intermediate results: LI. Features in the cosmic microwave background temperature power spectrum and shifts in cosmological parameters

We present that the six parameters of the standard ΛCDM model have best-fit values derived from the Planck temperature power spectrum that are shifted somewhat from the best-fit values derived from WMAP data. These shifts are driven by features in Planck the Planck temperature power spectrum at angular scales that had never before been measured to cosmic-variance level precision. We have investigated these shifts to determine whether they are within the range of expectation and to understand their origin in the data. Taking our parameter set to be the optical depth of the reionized intergalactic medium Τ, the baryon density ω b , the matter density ω m , the angular size of the sound horizon θ&lowast; the spectral index of the primordial power spectrum, n s , and A s e -2τ (where A s is the amplitude of the primordial power spectrum), we have examined the change in best-fit values between a WMAP-like large angular-scale data set (with multipole moment < 800 in the Planck temperature power spectrum) and an all angular-scale data set (< 2500 Planck temperature power spectrum), each with a prior on τ of 0.07 ± 0.02. We find that the shifts, in units of the 1σ expected dispersion for each parameter, are { Δτ,ΔA s e - 2τ ,Δn s ,Δω m ,Δω b ,Δθ&lowast; } = { -1.7,-2.2,1.2,-2.0,1.1,0.9 }, with a χ2 value of 8.0. We find that this χ2 value is exceeded in 15% of our simulated data sets, and that a parameter deviates by more than 2.2σ in 9% of simulated data sets, meaning that the shifts are not unusually large. Comparing &ell; < 800 instead to &ell; > 800, or splitting at a different multipole, yields similar results. We examined the &ell; < 800 model residuals in the &ell; > 800 power spectrum data and find that the features there that drive these shifts are a set of oscillations across a broad range of angular scales. Although they partly appear similar to the effects of enhanced gravitational lensing, the shifts in ΛCDM parameters that arise in response to these features correspond to model spectrum changes that are predominantly due to non-lensing effects; the only exception is Τ, which, at fixed A s e -2τ , affects the &ell; > 800 temperature power spectrum solely through the associated change in A s and the impact of that on the lensing potential power spectrum. We also ask, "what is it about the power spectrum at &ell; < 800 that leads to somewhat different best-fit parameters than come from the full range?" We find that if we discard the data at &ell; < 30, where there is a roughly 2σ downward fluctuation in power relative to the model that best fits the full range, the &ell; < 800 best-fit parameters shift significantly towards the &ell; < 2500 best-fit parameters. In contrast, including &ell; < 30, this previously noted "low-deficit" drives n s up and impacts parameters correlated with n s , such as ω m and H 0 . As expected, the &ell; < 30 data have a much greater impact on the &ell; < 800 best fit than on the &ell; < 2500 best fit. So although the shifts are not very significant, we find that they can be understood through the combined effects of an oscillatory-like set of high-residuals and the deficit in low-power, excursions consistent with sample variance that happen to map onto changes in cosmological parameters. Finally, we examine agreement between PlanckTT data and two other CMB data sets, namely the Planck lensing reconstruction and the TT power spectrum measured by the South Pole Telescope, again finding a lack of convincing evidence of any significant deviations in parameters, suggesting that current CMB data sets give an internally consistent picture of the ΛCDM model.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimization-Based Calibration of FAST.Farm Parameters Against SOWFA: Preprint

FAST.Farm is a medium-delity wind farm modeling tool that can be used to assess power and loads contributions of wind turbines in a wind farm. The objective of this paper is to undertake a calibration procedure to set the user parameters of FAST.Farm to accurately represent results from large-eddy simulations. The results provide an in- depth analysis of the comparison of FAST.Farm and large-eddy simulations before and after calibration. The comparison of FAST.Farm and large-eddy simulation results are presented with respect to streamwise and radial velocity components as well as wake-meandering statistics (mean and standard deviation) in the lateral and vertical directions under different atmospheric and turbine operating conditions.

17 WIND ENERGY↗

Constraints on Large Extra Dimensions from the MINOS Experiment

We report new constraints on the size of large extra dimensions from data collected by the MINOS experiment between 2005 and 2012. Our analysis employs a model in which sterile neutrinos arise as Kaluza-Klein states in large extra dimensions and thus modify the neutrino oscillation probabilities due to mixing between active and sterile neutrino states. Using Fermilab’s Neutrinos at the Main Injector beam exposure of 10.56×1020 protons on target, we combine muon neutrino charged current and neutral current data sets from the Near and Far Detectors and observe no evidence for deviations from standard three-flavor neutrino oscillations. The ratios of reconstructed energy spectra in the two detectors constrain the size of large extra dimensions to be smaller than 0.45 μm at 90% C.L. in the limit of a vanishing lightest active neutrino mass. Stronger limits are obtained for nonvanishing masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Designer Metasurfaces for Antireflective Applications Enabled by Advanced Nanoparticle Technology

Optic processing advances have shifted system limitations, with current constraints consisting of antireflective (AR) coatings applied to optics and the inability to reduce size, weight, and price. Metasurfaces, and more broadly metaoptics, provide an avenue to overcome these limitations. The ability to generate substrate-engraved metasurfaces that can be tailored is demonstrated within a broad design space to satisfy large-area AR applications for bandpass or broadband needs, demonstrating an optically equivalent surface roughness standard deviation of only 5 Å. Using an advanced nanoparticle masking approach, two metasurfaces are fabricated: 1) vertical sidewall nanofeature metasurface (MS) for AR applications at 351 nm, and 2) sloped sidewall MS designed for broadband AR applications. For the 351 nm MS, the reflectance is measured to be 0.127%. In the case of the sloped sidewall MS, the reflectance is measured to be <0.25% over 400–700 nm and <1% over 400–1100 nm. To the best of the authors’ knowledge, this is the first demonstration of a broadband AR capable of this performance. The tunability of these structures, with a parameter space spanning even more remarkable designs such as broader bands and acceptance angles, coupled with high laser-induced damage durability and mechanical robustness, displays the strength of metasurfaces for AR applications.

36 MATERIALS SCIENCE↗

Rescuing a black hole in the large- q coupled SYK model

In this paper, we develop a general effective theory for two copies of the Sachdev-Ye-Kitaev (SYK) model with a time-dependent bilinear coupling. For a quantum quench problem with an initial state of the thermofield double state, we show how the evolution of the system is described by a complex reparametrization field with a classical Hamiltonian. We study correlation functions in this system and compare the large-q theory with the bulk low energy effective theory. In particular, we study the special case of a “rescued black hole”, which describes how a time-evolved thermofield double state can evolve to the ground state of a coupled SYK model by a carefully tuned time-dependent coupling. In the low energy region, there is a holographic dual interpretation, which is a geometry that crosses over from an eternal black hole to a global AdS2 vacuum. This family of geometries allow us to access the bulk region that would be the black hole interior without the rescue process. By comparing the large-q and low energy theory, we find that even in the low energy region the deviation from the low energy theory cannot be neglected if the rescue process starts late. This provides evidence that the low energy effective theory of the bulk fails near the inner horizon of the black hole. We note the possibility of a connection to a two-dimensional analog of the higher-dimensional black hole singularity.

2D Gravity↗

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and the AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.

97 MATHEMATICS AND COMPUTING↗

Distinct evolutionary lineages of Schistocephalus parasites infecting co-occurring sculpin and stickleback fishes in Alaska

Sculpins (coastrange and slimy) and sticklebacks (ninespine and threespine) are widely distributed fishes cohabiting 2 south-central Alaskan lakes (Aleknagik and Iliamna), and all these species are parasitized by cryptic diphyllobothriidean cestodes in the genus Schistocephalus. The goal of this investigation was to test for host-specific parasitic relationships between sculpins and sticklebacks based upon morphological traits (segment counts) and sequence variation across the NADH1 gene. A total of 446 plerocercoids was examined. Large, significant differences in mean segment counts were found between cestodes in sculpin (mean = 112; standard deviation [S.D.] = 15) and stickleback (mean = 86; S.D. = 9) hosts within and between lakes. Nucleotide sequence divergence between parasites from sculpin and stickleback hosts was 20.5%, and Bayesian phylogenetic analysis recovered 2 well-supported clades of cestodes reflecting intermediate host family (i.e. sculpin, Cottidae vs stickleback, Gasterosteidae). Our findings point to the presence of a distinct lineage of cryptic Schistocephalus in sculpins from Aleknagik and Iliamna lakes that warrants further investigation to determine appropriate evolutionary and taxonomic recognition.

59 BASIC BIOLOGICAL SCIENCES↗

Graphene nanoribbons initiated from molecularly derived seeds

Abstract Semiconducting graphene nanoribbons are promising materials for nanoelectronics but are held back by synthesis challenges. Here we report that molecular-scale carbon seeds can be exploited to initiate the chemical vapor deposition (CVD) synthesis of graphene to generate one-dimensional graphene nanoribbons narrower than 5 nm when coupled with growth phenomena that selectively extend seeds along a single direction. This concept is demonstrated by subliming graphene-like polycyclic aromatic hydrocarbon molecules onto a Ge(001) catalyst surface and then anisotropically evolving size-controlled nanoribbons from the seeds along $$\left\langle 110\right\rangle$$ 110 of Ge(001) via CH 4 CVD. Armchair nanoribbons with mean normalized standard deviation as small as 11% (3 times smaller than nanoribbons nucleated without seeds), aspect ratio as large as 30, and width as narrow as 2.6 nm (tunable via CH 4 exposure time) are realized. Two populations of nanoribbons are compared in field-effect transistors (FETs), with off-current differing by 150 times because of the nanoribbons’ different widths.

36 MATERIALS SCIENCE↗

Effect of water on structure and dynamics of [BMIM][PF{sub 6}] ionic liquid: An all-atom molecular dynamics simulation investigation

Composition dependent structural and dynamical properties of aqueous hydrophobic 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF{sub 6}]) ionic liquid (IL) have been investigated by using all-atom molecular dynamics simulation. We observe that addition of water does not increase significant number of dissociated ions in the solution over the pure state. As a consequence, self-diffusion coefficient of the cation and anion is comparable to each other at all water concentration similar to that is observed for the pure state. Voronoi polyhedra analysis exhibits strong dependence on the local environment of IL concentration. Void and neck distributions in Voronoi tessellation are approximately Gaussian for pure IL but upon subsequent addition of water, we observe deviation from the Gaussian behaviour with an asymmetric broadening with long tail of exponential decay at large void radius, particularly at higher water concentrations. The increase in void space and neck size at higher water concentration facilitates ionic motion, thus, decreasing dynamical heterogeneity and IL reorientation time and increases self-diffusion coefficient significantly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Loss tangent fluctuations due to two-level systems in superconducting microwave resonators

Superconducting microwave resonators are critical to quantum computing and sensing technologies. Additionally, they are common proxies for superconducting qubits when determining the effects of performance-limiting loss mechanisms such as from two-level systems (TLSs). The extraction of these loss mechanisms is often performed by measuring the internal quality factor Qi as a function of power or temperature. In this work, we investigate large temporal fluctuations of Qi at low powers over periods of 12–16 h (relative standard deviation σQi/Qi=13%). These fluctuations are ubiquitous across multiple resonators, chips, and cooldowns. We are able to attribute these fluctuations to variations in the TLS loss tangent due to two main indicators. First, measured fluctuations decrease as power and temperature increase. Second, for interleaved measurements, we observe correlations between low- and medium-power Qi fluctuations and an absence of correlations with high-power fluctuations. Agreement with the TLS loss tangent mean is obtained by performing measurements over a time span of a few hours. We hypothesize that, in addition to decoherence, due to coupling to individual near-resonant TLS, superconducting qubits are affected by these observed TLS loss tangent fluctuations.

Vallières, André [Northwestern U.; Fermilab] (ORCI↗

Regular instantons in the Eddington-inspired-Born-Infeld gravity: Lorentzian wormholes from bubble nucleations

The O(4)-symmetric regular instanton solutions are studied within the framework of the Eddington-inspired-Born-Infeld gravity (EiBI). Here we find that the behavior of the solution would deviate from that in Einstein gravity when the kinetic energy of the scalar field is sufficiently large. The tunneling probability is calculated numerically in different parameter space. We find that the tunneling probability would increase with the Born-Infeld coupling constant, which is assumed to be positive in this paper. Furthermore, we discover a neck feature in the physical instanton solutions when the kinetic energy of the scalar field is sufficiently large. This feature can be interpreted as a Lorentzian time-like wormhole geometry formed during the bubble materialization.

79 ASTRONOMY AND ASTROPHYSICS↗

What drives the scatter of local star-forming galaxies in the BPT diagrams? A Machine Learning based analysis

ABSTRACT We investigate which physical properties are most predictive of the position of local star forming galaxies on the BPT diagrams, by means of different Machine Learning (ML) algorithms. Exploiting the large statistics from the Sloan Digital Sky Survey (SDSS), we define a framework in which the deviation of star-forming galaxies from their median sequence can be described in terms of the relative variations in a variety of observational parameters. We train artificial neural networks (ANN) and random forest (RF) trees to predict whether galaxies are offset above or below the sequence (via classification), and to estimate the exact magnitude of the offset itself (via regression). We find, with high significance, that parameters primarily associated to variations in the nitrogen-over-oxygen abundance ratio (N/O) are the most predictive for the [N ii]-BPT diagram, whereas properties related to star formation (like variations in SFR or EW(H α)) perform better in the [S ii]-BPT diagram. We interpret the former as a reflection of the N/O–O/H relationship for local galaxies, while the latter as primarily tracing the variation in the effective size of the S+ emitting region, which directly impacts the [S ii] emission lines. This analysis paves the way to assess to what extent the physics shaping local BPT diagrams is also responsible for the offsets seen in high redshift galaxies or, instead, whether a different framework or even different mechanisms need to be invoked.

79 ASTRONOMY AND ASTROPHYSICS↗

Linear magnetoresistance caused by mobility fluctuations in n -doped Cd 3 As 2

Cd 3 As 2 is a candidate three-dimensional Dirac semimetal which has exceedingly high mobility and nonsaturating linear magnetoresistance that may be relevant for future practical applications. We report magnetotransport and tunnel diode oscillation measurements on Cd 3 As 2 , in magnetic fields up to 65 T and temperatures between 1.5 and 300 K. We find that the nonsaturating linear magnetoresistance persists up to 65 T and it is likely caused by disorder effects, as it scales with the high mobility rather than directly linked to Fermi surface changes even when approaching the quantum limit. As a result of the observed quantum oscillations, we determine the bulk three-dimensional Fermi surface having signatures of Dirac behavior with a nontrivial Berry phase shift, very light effective quasiparticle masses, and clear deviations from the band-structure predictions. In very high fields we also detect signatures of large Zeeman spin splitting (g~16).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability

Purpose: To determine the variation in tumor contrast between different MRI sequences and between patients for the purpose of MRI-based treatment planning. Methods: Multiple MRI scans of 11 patients with cancer(s) in the liver were included in this IRB-approved study. Imaging sequences consisted of T1W MRI, Contrast-Enhanced T1W MRI, T2W MRI, and T2*/T1W MRI. MRI images were acquired on a 1.5T GE Signa scanner with a four-channel torso coil. We calculated the tumor-to-tissue contrast to noise ratio (CNR) for each MR sequence by contouring the tumor and a region of interest (ROI) in a homogeneous region of the liver using the Eclipse treatment planning software. CNR was calculated (I-Tum-I-ROI)/SD-ROI, where I-Tum and I-ROI are the mean values of the tumor and the ROI respectively, and SD-ROI is the standard deviation of the ROI. The same tumor and ROI structures were used in all measurements for different MR sequences. Inter-patient Coefficient of variation (CV), and inter-sequence CV was determined. In addition, mean and standard deviation of CNR were calculated and compared between different MR sequences. Results: Our preliminary results showed large inter-patient CV (range: 37.7% to 88%) and inter-sequence CV (range 5.3% to 104.9%) of liver tumor CNR, indicating great variations in tumor CNR between MR sequences and between patients. Tumor CNR was found to be largest in CE-T1W (8.5±7.5), followed by T2W (4.2±2.4), T1W (3.4±2.2), and T2*/T1W (1.7±0.6) MR scans. The inter-patient CV of tumor CNR was also the largest in CE-T1W (88%), followed by T1W (64.3%), T1W (56.2%), and T2*/T1W (37.7) MR scans. Conclusion: Large inter-sequence and inter-patient variations were observed in liver tumor CNR. CE-T1W MR images on average provided the best tumor CNR. Efforts are needed to optimize tumor contrast and its consistency for MRI-based treatment planning of cancer in the liver. This project is supported by NIH grant: 1R21CA165384.

60 APPLIED LIFE SCIENCES↗