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At least 1,567 records · Page 87

Spectral variability of a sample of extreme variability quasars and implications for the MgII broad-line region

We present new Gemini/GMOS optical spectroscopy of 16 extreme variability quasars (EVQs) that dimmed bymore than 1.5mag in the g band between the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey epochs (separated by a few years in the quasar rest frame). These EVQs are selected from quasars in the SDSS Stripe 82 region, covering a redshift range of 0.5 < z < 2.1. Nearly half of these EVQs brightened significantly (by more than 0.5 mag in the g band) in a few years after reaching their previous faintest state, and some EVQs showed rapid (non-blazar) variations of greater than 1-2 mag on time-scales of only months. To increase sample statistics, we use a supplemental sample of 33 EVQs with multi-epoch spectra from SDSS that cover the broad Mg II lambda 2798 line. Leveraging on the large dynamic range in continuum variability between the multi-epoch spectra, we explore the associated variations in the broad MgII line, whose variability properties have not been well studied before. The broad MgII flux varies in the same direction as the continuum flux, albeit with a smaller amplitude, which indicates at least some portion of Mg II is reverberating to continuum changes. However, the full width at half-maximum (FWHM) of Mg II does not vary accordingly as continuum changes for most objects in the sample, in contrast to the case of the broad Balmer lines. Using the width of broad MgII to estimate the black hole mass with single epoch spectra therefore introduces a luminosity-dependent bias.

79 ASTRONOMY AND ASTROPHYSICS↗

Dynamical estimate of post-main-sequence stellar masses in 47 Tucanae

We use the effects of mass segregation on the radial distribution of different stellar populations in the core of 47 Tucanae to find estimates for the masses of stars at different post-main-sequence evolutionary stages. We take samples of main-sequence (MS) stars from the core of 47 Tucanae, at different magnitudes (i.e., different masses), and use the effects of this dynamical process to develop a relation between the radial distance (RD) at which the cumulative distribution reaches the 20th and 50th percentile and stellar mass. From these relations we estimate the masses of different post-MS populations. We find that mass remains constant for stars going through the evolutionary stages from the upper MS up to the horizontal branch (HB). By comparing RDs of the HB stars with stars of lower masses, we can exclude a mass loss greater than 0.09 M{sub ⊙} during the red giant branch (RGB) stage at nearly the 3σ level. The slightly higher mass estimates for the asymptotic giant branch (AGB) are consistent with the AGB having evolved from somewhat more massive stars. The AGB also exhibits evidence of contamination by more massive stars, possibly blue straggler stars (BSSs), going through the RGB phase. We do not include the BSSs in this paper due to the complexity of these objects; instead, the complete analysis of this population is left for a companion paper. The process to estimate the masses described in this paper is exclusive to the core of 47 Tuc.

79 ASTRONOMY AND ASTROPHYSICS↗

Learning and Controlling Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy

A machine learning approach is introduced to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). This method is data-centric, leveraging data collected on a STEM. The data samples are processed and filtered to produce symbolic representations, which is used to train a neural network to predict transition probabilities. These learned transition dynamics are then leveraged to guide a single silicon atom throughout the lattice to pre-determined target destinations. Empirical analyses are presented that demonstrate the efficacy and generality of the approach.

36 MATERIALS SCIENCE↗

Characteristics of an Introduced Walleye Population with Implications for Suppression

Abstract The management of introduced fishes, including Walleye Sander vitreus, whether for control or enhancement, requires understanding of population dynamics at the invasion front. Walleye recently established in the Pend Oreille basin, Idaho, threaten the existing salmonid-based fish community and associated recreational fishery. Therefore, the objectives of this study were to describe population growth and associated life history characteristics. Walleye were sampled in October of 2011, 2014, and 2017 using a standardized gill netting survey protocol to describe trends in relative abundance and evaluate population dynamics. Relative abundance increased exponentially from 1.4 to 4.3 fish/net over the 6-year monitoring period. This population was characterized by fast somatic growth, robust body condition, and early age at maturity at or near the biological maxima for Walleye. Among the survey years, mean length at age 2 varied for female (359–441 mm) and male (358–426 mm) Walleye and relative weight varied from 91 to 98. The sampled Walleye matured at 1 to 4 years of age, and recruitment became more consistent as abundance increased. These density-dependent metrics suggest that the Walleye population is still at low density relative to carrying capacity. The information that was gained from this study was used to better understand potential risks and guide management decisions related to experimental population suppression that is now underway. Suppression under these conditions must overcome the recruitment capabilities of the population. We conclude that natural mortality is likely regulated by density-dependent processes. Therefore, at current (low) density, fishing mortality may be entirely additive and compensation is unlikely to further complicate management.

Ryan, Robert G.↗

Atmospheric Waves and Dynamics Beneath Jupiters Clouds from Radio Wavelength Observations

We observed Jupiter at wavelengths near 2 cm with the Karl G. Jansky Very Large Array (VLA) in February 2015. These frequencies are mostly sensitive to variations in ammonia abundance and probe between approx. 0.5- 2.0 bars of pressure in Jupiters atmosphere; within and below the visible cloud deck which has its base near 0.7 bars. The resultant observed data were projected into a cylindrical map of the planet with spatial resolution of approx. 1500 km at the equator. We have examined the data for atmospheric waves and observed a prominent bright belt of radio hotspot features near 10 N, likely connected to the same equatorial wave associated with the 5-m hotspots. We conducted a passive tracer power spectral wave analysis for the entire map and latitude regions corresponding to eastward and westward jets and compare our results to previous studies. The power spectra analysis revealed that the atmosphere sampled in our observation (excluding the NEB region) is in a 2-D turbulent regime and its dynamics are predominately governed by the shallow water equations. The Great Red Spot (GRS) is also very prominent and has a noticeable meridional asymmetry and we compare it, and nearby storms, with optical images. We find that the meridional radio profile has a global north-south hemisphere distinction and find correlations of it to optical intensity banding and to shear zones of the zonal wind profile over select regions of latitude. Amateur optical images taken before and after our observation complemented the radio wave- length map to investigate dynamics of the equatorial region in Jupiters atmosphere. We find that two radio hotspots at 2 cm are well correlated with optical plumes in the NEB, additionally revealing they are not the same 5 m hotspot features correlated with optical dark patches between adjacent plumes. This analysis exploits the VLAs upgraded sensitivity and explores the opportunities now possible when studying gas giants, especially atmospheric dynamics of layers beneath upper level clouds.

radio observations↗

Sequence Modulates Polypeptoid Hydration Water Structure and Dynamics

We use molecular dynamics simulations to investigate the effect of polypeptoid sequence on the structure and dynamics of its hydration waters. Polypeptoids provide an excellent platform to study small-molecule hydration in disordered polymers, as they can be precisely synthesized with a variety of sidechain chemistries. We examine water behavior near a set of peptoid oligomers in which the number and placement of nonpolar versus polar sidechains are systematically varied. To do this, we leverage a new computational workflow enabling accurate sampling of polypeptoid conformations. We find that the hydration waters are less dense, are more tetrahedral, and have slower dynamics compared to bulk water. The magnitude of these shifts increases with the number of nonpolar groups. Here, we also find that shifts in the water structure and dynamics are strongly correlated, suggesting that experimental insight into the dynamics of hydration water obtained by Overhauser dynamic nuclear polarization (ODNP) also contains information about water structural properties. We then demonstrate the ability of ODNP to probe site-specific dynamics of hydration water near these model peptoid systems.

36 MATERIALS SCIENCE↗

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

TBC↗

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

TBC↗

A Dynamic Testing Approach for Particulate Erosion–Corrosion for Gas Turbine Coatings

Particle interactions in gas turbine engines can be multicomponent, complex phenomena leading to the degradation of thermal (TBCs) and environmental barrier coatings (EBCs) meant to protect engine components. Ingestion of particles into the engine can lead to recession of coatings due to particle erosion. Similarly, these same particles can become molten, adhere to coatings and result in thermochemical corrosion of coating materials. Particle erosion testing is often carried out where the particles are injected into a gas stream, accelerated within a nozzle, and impinge on sample. Conversely, most molten particle corrosion testing is often done in static laboratory furnaces, which does not capture the dynamic nature of deposition in application. Nevertheless, these damage mechanisms are often tested separately and no single standard exists to test both erosive and corrosive particle interactions with coating materials under relevant operating conditions for gas turbine engines. Understanding the synergies of particle interactions in engines is crucial in determining operating lifetimes of potential coating materials. Such considerations emphasize the need for realistic approaches in standardizing particle interaction testing in combustion environments. The current study outlines initial efforts at NASA Glenn’s Erosion Burner Rig Facility in improving dynamic erosion/corrosion testing methods by assessing the durability of state-of-the-art (SOA) TBC material 7 wt.% yttria stabilized zirconia (7YSZ) as a function of particle deposition rate, burner temperature, and particle size. Calibration data to determine particle deposition rate will be presented, and mass and optical profilometry measurements were utilized to estimate mass/volume loss versus deposition per increment of particulate used over time. Electron microscopy analyses were then carried out to assess coating damage after testing.

burner rig↗

Metalloprotein structures at ambient conditions and in real-time: biological crystallography and spectroscopy using X-ray free electron lasers

We have studied the structure of enzymes and the chemistry at the catalytic sites, intensively and have acquired an understanding of the atomic-scale chemistry which requires a new approach beyond steady state X-ray crystallography and X-ray spectroscopy at cryogenic temperatures. Following the dynamic changes in the geometric and electronic structure of metallo-enzymes at ambient conditions, while overcoming the severe X-ray-induced changes to the redox active catalytic center, is key for deriving reaction mechanisms. Such studies become possible by the intense and ultra-short femtosecond (fs) X-ray pulses from an X-ray free electron laser (XFEL) by acquiring a signal before the sample is destroyed. Our review describes the recent and pioneering uses of XFELs to study the protein structure and dynamics of metallo-enzymes using crystallography and scattering, as well as the chemical structure and dynamics of the catalytic complexes (charge, spin, and covalency) using spectroscopy during the reaction to understand the electron-transfer processes and elucidate the mechanism.

59 BASIC BIOLOGICAL SCIENCES↗

High-response on-line gas analysis system for hydrogen-reaction combustion products

The results of testing an on-line quadrupole gas analyzer system are reported. Gas samples were drawn from the exhaust of a hydrogen-oxygen-nitrogen rocket which simulated the flow composition and dynamics at the combustor exit of a supersonic combustion ramjet engine. System response time of less than 50 milliseconds was demonstrated, with analytical accuracy estimated to be + or - 5 percent. For more complex chemical systems with interfering atom patterns, analysis would be more difficult. A cooled-gas pyrometer probe was evaluated as a total temperature indicator and as the primary mass flow measuring element for the total sample flow rate.

Metzler, A. J.↗

Considerations for quantitative in situ X-ray powder diffraction studies of solid-state reactions

The importance of sample preparation in collecting high-fidelity powder diffraction data suitable for quantitative structure and phase analysis is well established. Such powder diffraction experiments are increasingly being appliedin situ, during reactions, to explore solid-state reactivity. When appliedin situ, X-ray diffraction is widely used to gain insight into the mechanism and kinetics, and to identify dynamic intermediate states. Here, using a model ion-exchange reaction (NaFeO 2 + LiCl → LiFeO 2 + NaCl), we show that sample preparation not only influences the fidelity of powder diffraction analysis but also impacts the observed reaction progress. Specifically, we found that the observed reaction progress can differ by ∼50% depending on the capillary sample preparation. Thus, forin situdiffraction studies of solid-state reactions, packing fraction is an important and previously unrecognized consideration that impacts reproducibility and fidelity of the reaction study.

Chemistry↗

Velocity dispersion and dynamical masses for 388 galaxy clusters and groups

The second catalogue of Planck Sunyaev-Zeldovich (SZ) sources, hereafter PSZ2, represents the largest galaxy cluster sample selected by means of their SZ signature in a full-sky survey. For this work, using telescopes at the Canary Island observatories, we conducted the long-term observational program 128- MULTIPLE-16/15B (hereafter LP15), a large and complete optical follow-up campaign of all the unidentified PSZ2 sources in the northern sky, with declinations above –15° and no correspondence in the first Planck catalogue PSZ1. This paper is the third and last in the series of LP15 results, after Streblyanska et al. (2019, A&A, 628, A13) and Aguado-Barahona et al. (2019, A&A, 631, A148), and presents all the spectroscopic observations of the full program. We complement these LP15 spectroscopic results with Sloan Digital Sky Survey archival data and other observations from a previous program (ITP13-08), and present a catalogue of 388 clusters and groups of galaxies including estimates of their velocity dispersion. The majority of them (356) are optical counterparts of PSZ2 sources. A subset of 297 of those clusters are used to construct the M SZ – M dyn scaling relation based on the estimated SZ mass from Planck measurements and our dynamical mass estimates. We discuss and correct for different statistical and physical biases in the estimation of the masses, such as the Eddington bias when estimating M SZ and the aperture and the number of galaxies used to calculate M dyn . The SZ-to-dynamical mass ratio for those 297 PSZ2 clusters is (1 – B) = 0.80 ± 0.04 (stat) ± 0.05 (sys), with only marginal evidence for a possible mass dependence for this factor. Our value is consistent with previous results in the literature, but is associated with a significantly smaller uncertainty due to the use of the largest sample size for this type of study.

79 ASTRONOMY AND ASTROPHYSICS↗

Hamiltonian simulation in Zeno subspaces

Here, we investigate the quantum Zeno effect as a framework for designing and analyzing quantum algorithms for Hamiltonian simulation. We show that frequent projective measurements of an ancilla qubit register can be used to simulate quantum dynamics on a target qubit register with a circuit complexity similar to randomized approaches. The classical sampling overhead in the latter approaches is traded for ancilla qubit overhead in Zeno-based approaches. A second-order Zeno sequence is developed to improve scaling and implementations through unitary kicks are discussed. We derive rigorous error bounds that allow for identifying the associated circuit complexities for the first- and second-order Zeno sequences. We show that the circuits over the combined register can be identified as a subroutine commonly used in post-Trotter Hamiltonian simulation methods. We build on this observation to reveal connections between different Hamiltonian simulation algorithms.

Hamiltonian simulation↗

Computing equilibrium free energies through a nonequilibrium quench

Many methods to accelerate sampling of molecular configurations are based on the idea that temperature can be used to accelerate rare transitions. These methods typically compute equilibrium properties at a target temperature using reweighting or through Monte Carlo exchanges between replicas at higher temperatures. A recent paper [G. M. Rotskoff and E. Vanden-Eijnden, Phys. Rev. Lett. 122, 150602 (2019)] demonstrated that accurate equilibrium densities of states can also be computed through a nonequilibrium “quench” process, where sampling is performed at a higher temperature to encourage rapid mixing and then quenched to lower energy states with dissipative dynamics. Here, we provide an implementation of the quench dynamics in LAMMPS and evaluate a new formulation of nonequilibrium estimators for the computation of partition functions or free energy surfaces (FESs) of molecular systems. We show that the method is exact for a minimal model of N-independent harmonic springs and use these analytical results to develop heuristics for the amount of quenching required to obtain accurate sampling. We then test the quench approach on alanine dipeptide, where we show that it gives an FES that is accurate near the most stable configurations using the quench approach but disagrees with a reference umbrella sampling calculation in high FE regions. We then show that combining quenching with umbrella sampling allows the efficient calculation of the free energy in all regions. Moreover, by using this combined scheme, we obtain the FES across a range of temperatures at no additional cost, making it much more efficient than standard umbrella sampling if this information is required. Finally, we discuss how this approach can be extended to solute tempering and demonstrate that it is highly accurate for the case of solvated alanine dipeptide without any additional modifications.

Chemistry↗

Toward accurate measurement of electromagnetic field by retrieving and refining the center position of non-uniform diffraction disks in Lorentz 4D-STEM

Recent advancement in scanning transmission electron microscopy (STEM) allows the use of 4D-STEM, a technique that captures an electron diffraction pattern at each scan point in STEM, to measure electrostatic and magnetic potential and field in materials. However, accurate measurement, separation of the magnetic and electric signals, and removal of artifacts remain challenging, especially in the presence of complex non-uniform diffraction contrast within the disks. In this work, based on dynamic simulations of 4D-STEM patterns built upon superstructures consisting of millions of atoms to account for different sample thickness and edge geometries, we show how the shape and intensity distribution of the central disk are affected by multiple scattering. We propose a robust refinement procedure through iteration of the spin-sensitive peak position of the disk-center in the circular Hough transform filtered images from experimental Lorentz 4D-STEM dataset after minimizing the possible artifacts, such as those due to the change of thickness, dynamic scattering, and scanning process. We verify that caution must be taken as in practice the rigid-disk-shift model used to reconstruct induction maps can easily break down due to disk-protrusion when there exists a nonconstant phase gradient or thickness within the width of the probe. Through quantitative analysis and comparing experiment with calculation the effect of the non-spin-related intensity distribution inside the disk as well as that causes the disk shift due to the intensity-protrusion can be removed, and high-quality magnetic field mapping is possible.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Computing the binding affinity of a ligand buried deep inside a protein with the hybrid steered molecular dynamics

Computing the ligand-protein binding affinity (or the Gibbs free energy) with chemical accuracy has long been a challenge for which many methods/approaches have been developed and refined with various successful applications. False positives and, even more harmful, false negatives have been and still are a common occurrence in practical applications. Inevitable in all approaches are the errors in the force field parameters we obtain from quantum mechanical computation and/or empirical fittings for the intra- and inter-molecular interactions. These errors propagate to the final results of the computed binding affinities even if we were able to perfectly implement the statistical mechanics of all the processes relevant to a given problem. And they are actually amplified to various degrees even in the mature, sophisticated computational approaches. In particular, the free energy perturbation (alchemical) approaches amplify the errors in the force field parameters because they rely on extracting the small differences between similarly large numbers. In this paper, we develop a hybrid steered molecular dynamics (hSMD) approach to the difficult binding problems of a ligand buried deep inside a protein. Sampling the transition along a physical (not alchemical) dissociation path of opening up the binding cavity- -pulling out the ligand- -closing back the cavity, we can avoid the problem of error amplifications by not relying on small differences between similar numbers. We tested this new form of hSMD on retinol inside cellular retinol-binding protein 1 and three cases of a ligand (a benzylacetate, a 2-nitrothiophene, and a benzene) inside a T4 lysozyme L99A/M102Q(H) double mutant. In all cases, we obtained binding free energies in close agreement with the experimentally measured values. This indicates that the force field parameters we employed are accurate and that hSMD (a brute force, unsophisticated approach) is free from the problem of error amplification suffered by many sophisticated approaches in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of Time Dependent Data and PRA

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, 'extracting information' means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗