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At least 703 records · Page 39

Radiation feedback in ULIRGs: are photons movers and shakers?

We perform multidimensional radiation hydrodynamics simulations to study the impact of radiation forces on atmospheres composed of dust and gas. Our setup closely follows that of Krumholz and Thompson, assuming that dust and gas are well-coupled and that the radiation field is characterized by blackbodies with temperatures ≳ 80 K, as might be found in ultraluminous infrared galaxies (ULIRGs). In agreement with previous work, we find that Rayleigh-Taylor instabilities develop in radiation supported atmospheres, leading to inhomogeneities that limit momentum exchange between radiation and dusty gas, and eventually providing a near balance of the radiation and gravitational forces. However, the evolution of the velocity and spatial distributions of the gas differs significantly from previous work, which utilized a less accurate flux-limited diffusion (FLD) method. Our variable Eddington tensor simulations show continuous net acceleration of the gas and never reach a steady state. In contrast, our FLD results show little net acceleration of the gas and settle into a quasi-steady, turbulent state with low velocity dispersion. The discrepancies result primarily from the inability of FLD to properly model the variation of the radiation field around structures that are less than a few optical depths across. We consider the effect of varying the optical depth and study the differences between two-dimensional and three-dimensional runs. We conclude that radiation feedback remains a plausible mechanism for driving high-Mach number turbulence in ULIRGs with sufficiently high optical depths. We discuss implications for observed systems and galactic-scale numerical simulations of feedback.

79 ASTRONOMY AND ASTROPHYSICS↗

Application of a solar wind model driven by turbulence dissipation to a 2D magnetic field configuration

Although it is widely accepted that photospheric motions provide the energy source and that the magnetic field must play a key role in the process, the detailed mechanisms responsible for heating the Sun's corona and accelerating the solar wind are still not fully understood. Cranmer et al. developed a sophisticated, one-dimensional (1D), time-steady model of the solar wind with turbulence dissipation. By varying the coronal magnetic field, they obtain, for a single choice of wave properties, a realistic range of slow and fast wind conditions with a sharp latitudinal transition between the two streams. Using a 1D, time-dependent model of the solar wind of Lionello et al., which incorporates turbulent dissipation of Alfvén waves to provide heating and acceleration of the plasma, we have explored a similar configuration, obtaining qualitatively equivalent results. However, our calculations suggest that the rapid transition between slow and fast wind suggested by this 1D model may be disrupted in multidimensional MHD simulations by the requirement of transverse force balance.

79 ASTRONOMY AND ASTROPHYSICS↗

ELECTRON HEATING BY THE ION CYCLOTRON INSTABILITY IN COLLISIONLESS ACCRETION FLOWS. I. COMPRESSION-DRIVEN INSTABILITIES AND THE ELECTRON HEATING MECHANISM

In systems accreting well below the Eddington rate, such as the central black hole in the Milky Way (Sgr A*), the plasma in the innermost regions of the disk is believed to be collisionless and have two temperatures, with the ions substantially hotter than the electrons. However, whether a collisionless faster-than-Coulomb energy transfer mechanism exists in two-temperature accretion flows is still an open question. We study the physics of electron heating during the growth of ion velocity-space instabilities by means of multidimensional, fully kinetic, particle-in-cell (PIC) simulations. A background large-scale compression—embedded in a novel form of the PIC equations—continuously amplifies the field. This constantly drives a pressure anisotropy P > P {sub ∥} because of the adiabatic invariance of the particle magnetic moments. We find that, for ion plasma beta values β{sub 0i} ∼ 5-30 appropriate for the midplane of low-luminosity accretion flows (here, β{sub 0i} is the ratio of ion thermal pressure to magnetic pressure), mirror modes dominate if the electron-to-proton temperature ratio is T {sub 0e}/T {sub 0i} ≳ 0.2, whereas for T {sub 0e}/T {sub 0i} ≲ 0.2 the ion cyclotron instability triggers the growth of strong Alfvén-like waves, which pitch-angle scatter the ions to maintain marginal stability. We develop an analytical model of electron heating during the growth of the ion cyclotron instability, which we validate with PIC simulations. We find that for cold electrons (β{sub 0e} ≲ 2 m{sub e} /m{sub i} , where β{sub 0e} is the ratio of electron thermal pressure to magnetic pressure), the electron energy gain is controlled by the magnitude of the E-cross-B velocity induced by the ion cyclotron waves. This term is independent of the initial electron temperature, so it provides a solid energy floor even for electrons starting with extremely low temperatures. On the other hand, the electron energy gain for β{sub 0e} ≳ 2 m{sub e} /m{sub i} —governed by the conservation of the particle magnetic moment in the growing fields of the instability—is proportional to the initial electron temperature, and it scales with the magnetic energy of ion cyclotron waves. Our results have implications for two-temperature accretion flows as well as for solar wind and intracluster plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗

CORONAL RAIN IN MAGNETIC ARCADES: REBOUND SHOCKS, LIMIT CYCLES, AND SHEAR FLOWS

We extend our earlier multidimensional, magnetohydrodynamic simulations of coronal rain occurring in magnetic arcades with higher resolution, grid-adaptive computations covering a much longer (>6 hr) time span. We quantify how blob-like condensations forming in situ grow along and across field lines and show that rain showers can occur in limit cycles, here demonstrated for the first time in 2.5D setups. We discuss dynamical, multi-dimensional aspects of the rebound shocks generated by the siphon inflows and quantify the thermodynamics of a prominence–corona transition-region-like structure surrounding the blobs. We point out the correlation between condensation rates and the cross-sectional size of loop systems where catastrophic cooling takes place. We also study the variations of the typical number density, kinetic energy, and temperature while blobs descend, impact, and sink into the transition region. In addition, we explain the mechanisms leading to concurrent upflows while the blobs descend. As a result, there are plenty of shear flows generated with relative velocity difference around 80 km s{sup −1} in our simulations. These shear flows are siphon flows set up by multiple blob dynamics and they in turn affect the deformation of the falling blobs. In particular, we show how shear flows can break apart blobs into smaller fragments, within minutes.

79 ASTRONOMY AND ASTROPHYSICS↗

A NEW METHOD FOR DERIVING THE STELLAR BIRTH FUNCTION OF RESOLVED STELLAR POPULATIONS

We present a new method for deriving the stellar birth function (SBF) of resolved stellar populations. The SBF (stars born per unit mass, time, and metallicity) is the combination of the initial mass function (IMF), the star formation history (SFH), and the metallicity distribution function (MDF). The framework of our analysis is that of Poisson Point Processes (PPPs), a class of statistical models suitable when dealing with points (stars) in a multidimensional space (the measurement space of multiple photometric bands). The theory of PPPs easily accommodates the modeling of measurement errors as well as that of incompleteness. Our method avoids binning stars in the color–magnitude diagram and uses the whole likelihood function for each data point; combining the individual likelihoods allows the computation of the posterior probability for the population's SBF. Within the proposed framework it is possible to include nuisance parameters, such as distance and extinction, by specifying their prior distributions and marginalizing over them. The aim of this paper is to assess the validity of this new approach under a range of assumptions, using only simulated data. Forthcoming work will show applications to real data. Although it has a broad scope of possible applications, we have developed this method to study multi-band Hubble Space Telescope observations of the Milky Way Bulge. Therefore we will focus on simulations with characteristics similar to those of the Galactic Bulge.

79 ASTRONOMY AND ASTROPHYSICS↗

MAPPING THE GALAXY COLOR–REDSHIFT RELATION: OPTIMAL PHOTOMETRIC REDSHIFT CALIBRATION STRATEGIES FOR COSMOLOGY SURVEYS

Calibrating the photometric redshifts of ≳10{sup 9} galaxies for upcoming weak lensing cosmology experiments is a major challenge for the astrophysics community. The path to obtaining the required spectroscopic redshifts for training and calibration is daunting, given the anticipated depths of the surveys and the difficulty in obtaining secure redshifts for some faint galaxy populations. Here we present an analysis of the problem based on the self-organizing map, a method of mapping the distribution of data in a high-dimensional space and projecting it onto a lower-dimensional representation. We apply this method to existing photometric data from the COSMOS survey selected to approximate the anticipated Euclid weak lensing sample, enabling us to robustly map the empirical distribution of galaxies in the multidimensional color space defined by the expected Euclid filters. Mapping this multicolor distribution lets us determine where—in galaxy color space—redshifts from current spectroscopic surveys exist and where they are systematically missing. Crucially, the method lets us determine whether a spectroscopic training sample is representative of the full photometric space occupied by the galaxies in a survey. We explore optimal sampling techniques and estimate the additional spectroscopy needed to map out the color–redshift relation, finding that sampling the galaxy distribution in color space in a systematic way can efficiently meet the calibration requirements. While the analysis presented here focuses on the Euclid survey, similar analysis can be applied to other surveys facing the same calibration challenge, such as DES, LSST, and WFIRST.

79 ASTRONOMY AND ASTROPHYSICS↗

Laser–plasma interactions for fast ignition

In the electron-driven fast-ignition approach to inertial confinement fusion, petawatt laser pulses are required to generate MeV electrons that deposit several tens of kilojoules in the compressed core of an imploded DT shell. We review recent progress in the understanding of intense laser- plasma interactions (LPI) relevant to fast ignition. Increases in computational and modeling capabilities, as well as algorithmic developments have led to enhancement in our ability to perform multidimensional particle-in-cell (PIC) simulations of LPI at relevant scales. We discuss the physics of the interaction in terms of laser absorption fraction, the laser-generated electron spectra, divergence, and their temporal evolution. Scaling with irradiation conditions such as laser intensity, f-number and wavelength are considered, as well as the dependence on plasma parameters. Different numerical modeling approaches and configurations are addressed, providing an overview of the modeling capabilities and limitations. In addition, we discuss the comparison of simulation results with experimental observables. In particular, we address the question of surrogacy of today's experiments for the full-scale fast ignition problem.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding window Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.

36 MATERIALS SCIENCE↗

Roadmap of ultrafast x-ray atomic and molecular physics

X-ray free-electron lasers (XFELs) and table-top sources of x-rays based upon high harmonic generation (HHG) have revolutionized the field of ultrafast x-ray atomic and molecular physics, largely due to an explosive growth in capabilities in the past decade. XFELs now provide unprecedented intensity (10 20 W cm -2 ) of x-rays at wavelengths down to ~1 Ångstrom, and HHG provides unprecedented time resolution (~50 attoseconds) and a correspondingly large coherent bandwidth at longer wavelengths. For context, timescales can be referenced to the Bohr orbital period in hydrogen atom of 150 attoseconds and the hydrogen-molecule vibrational period of 8 femtoseconds; wavelength scales can be referenced to the chemically significant carbon K-edge at a photon energy of ~280 eV (44 Ångstroms) and the bond length in methane of ~1 Ångstrom. With these modern x-ray sources one now has the ability to focus on individual atoms, even when embedded in a complex molecule, and view electronic and nuclear motion on their intrinsic scales (attoseconds and Ångstroms). These sources have enabled coherent diffractive imaging, where one can image non-crystalline objects in three dimensions on ultrafast timescales, potentially with atomic resolution. The unprecedented intensity available with XFELs has opened new fields of multiphoton and nonlinear x-ray physics where behavior of matter under extreme conditions can be explored. The unprecedented time resolution and pulse synchronization provided by HHG sources has kindled fundamental investigations of time delays in photoionization, charge migration in molecules, and dynamics near conical intersections that are foundational to AMO physics and chemistry. This roadmap coincides with the year when three new XFEL facilities, operating at Ångstrom wavelengths, opened for users (European XFEL, Swiss-FEL and PAL-FEL in Korea) almost doubling the present worldwide number of XFELs, and documents the remarkable progress in HHG capabilities since its discovery roughly 30 years ago, showcasing experiments in AMO physics and other applications. Here in this paper, we capture the perspectives of 17 leading groups and organize the contributions into four categories: ultrafast molecular dynamics, multidimensional x-ray spectroscopies; high-intensity x-ray phenomena; attosecond x-ray science.

74 ATOMIC AND MOLECULAR PHYSICS↗

Turbulence in core-collapse supernovae

Multidimensional simulations show that non-radial, turbulent, fluid motion is a fundamental component of the core-collapse supernova explosion mechanism. Neutrino-driven convection, the standing accretion shock instability, and relic-perturbations from advanced nuclear burning stages can all impact the outcome of core collapse in a qualitative and quantitative way. Here, we review the current understanding of these phenomena and their role in the explosion of massive stars. We also discuss the role of protoneutron star convection and of magnetic fields in the context of the delayed neutrino mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Time resolved surface photovoltage measurements using a big data capture approach to KPFM

Optoelectronic behavior in materials such as organic/inorganic hybrid perovskites depend on a complex interplay between fast (electronic) and slower (ionic) processes. These processes are thought to be influenced by structural inhomogeneities (e.g. interfaces and grain boundaries) bringing forward the necessity for development of techniques capable of correlating nanostructure and photo-transport behavior. While Kelvin probe force microscopy (KPFM) is ideally suited to map surface potentials on relevant length scales, it lacks sufficient temporal resolution to extract the meaningful system dynamics. Here, we develop a time resolved surface photovoltage (SPV) measurement based on full information capture of the photodetector stream during open loop KPFM operation. G-Mode, or G-KPFM allows quantification of SPV with microsecond temporal and nanoscale spatial resolution. Using this technique, we observe concurrent spatial and fast temporal variations in the SPV generated across a methylammonium lead bromide (MAPbBr3) thin film, a possible indicator relating microstructure with heterogenous photo-transport behavior. Here, we further demonstrate the advantage of adopting big data analytics including unsupervised clustering methods to quickly discern spatial variability in the information rich SPV dataset. Beyond G-KPFM, such clustering methods will be useful for interpretation of the multidimensional datasets arising from the growing number of time resolved KPFM approaches now available.

36 MATERIALS SCIENCE↗

A 3D percolation model for multicomponent nanocarbon composites: the critical role of nematic transition

A three-dimensional (3D) continuum percolation model has been developed on the basis of Monte Carlo simulation to investigate the percolation behavior of an electrically insulating matrix reinforced with multiple conductive fillers of different dimensionalities. Impenetrable fillers of large aspect ratio are found to preferentially align with each other to maximize the packing entropy rather than forming randomly oriented clusters. This entropy-driven transition from isotropic to nematic phase is shown to critically affect the percolation threshold. It suggests that an isotropic phase with a smaller nematic order parameter leads to a reduction in percolation threshold. In addition, a combination of two fillers with different dimensionalities can achieve a working concentration below the percolation threshold of single component system, which is further validated by the experiments of electrical conductivity in multicomponent multidimensional nanocarbon composites.

Ni, Xiaojuan↗

Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models

The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.

Bayesian optimization↗

On the character of turbulent-like flows in self-consistent models of core-collapse supernovae

Neutrino-driven convection plays a crucial role in the development of core-collapse supernova (CCSN) explosions. However, the complex mechanism that triggers the shock revival and the subsequent explosion has remained inscrutable for many decades. Multidimensional simulations suggest that the growth of fluid instabilities, especially development of convection, will determine the morphology of the explosion. We have performed 3D simulations using spherical-polar coordinates covering a reduced angular extent (90° computational domain), and with angular resolutions of 2°, 1°, 1/2°, and 1/4°, to study the development of turbulent-like flows in core-collapse supernova explosions on a time scale of order 100 ms. We have employed the multi-physics Chimera code that includes detailed nuclear physics and spectral neutrino transport. Coarse resolution models do not develop an inertial range, presumably due to the bottleneck effect, such that the energy is prevented from cascading down to small scales and tends to accumulate at large scales. High-resolution models instead, start to recover the k −5/3 scaling of Kolmogorov's theory. Stochasticity and few simulation samples limit our ability to predict the development of explosions. Over the simulated time period, our models show no clear trend in improving (or diminishing) conditions for explosion as the angular resolution is increased. However, we find that disordered flow provides an effective pressure, as characterized by the Reynolds stress, behind the shock. This contribution, ~40%–50% of the thermal pressure, aids shock revival and thus the development of the explosion. Finally, we show that the kinetic energy power spectrum of reduced angular extent and full 4π models are consistent, thus indicating that a 90° computational domain is an adequate configuration to study the character of turbulence in CCSNe.

Casanova Bustamante, Jordi↗

Global fits of the dark matter-nucleon effective interactions

The effective theory of isoscalar dark matter-nucleon interactions mediated by heavy spin-one or spin-zero particles depends on 10 coupling constants besides the dark matter particle mass. Here we compare this 11-dimensional effective theory to current observations in a comprehensive statistical analysis of several direct detection experiments, including the recent LUX, SuperCDMS and CDMSlite results. From a multidimensional scan with about 3 million likelihood evaluations, we extract the marginalized posterior probability density functions (a Bayesian approach) and the profile likelihoods (a frequentist approach), as well as the associated credible regions and confidence levels, for each coupling constant vs dark matter mass and for each pair of coupling constants. We compare the Bayesian and frequentist approach in the light of the currently limited amount of data. We find that current direct detection data contain sufficient information to simultaneously constrain not only the familiar spin-independent and spin-dependent interactions, but also the remaining velocity and momentum dependent couplings predicted by the dark matter-nucleon effective theory. For current experiments associated with a null result, we find strong correlations between some pairs of coupling constants. For experiments that claim a signal (i.e., CoGeNT and DAMA), we find that pairs of coupling constants produce degenerate results.

79 ASTRONOMY AND ASTROPHYSICS↗

Spiky CMB distortions from primordial bubbles

Primordial bubbles that possibly nucleate through quantum tunneling during inflation in a multidimensional potential might have left some relic detectable at the present time. These bubbles turn into black holes during the radiation era, which may account for the LIGO black holes, supermassive black holes, and may play an important role in dark matter. Typically, these black holes are surrounded by an energy deficit in the form of a spherical sound wave packet propagating outwards. In this work we study how this perturbation of the cosmic plasma dissipates before the time of recombination, leading to spectral distortions in CMB. Finally, we find that there may exist some rare regions on the last scattering surface containing huge black holes, which have produced potentially detectable point-like signals of µ-type distortions.

79 ASTRONOMY AND ASTROPHYSICS↗

Study of the muon component in the core-corona model using CONEX 3D

The discrepancy between models and data regarding the muon content in air showers generated by ultra-high energy cosmic rays still needs to be solved. The CONEX simulation framework provides a flexible tool to assess the impact of different interaction properties and thus address the muon puzzle. In this work, we present the multidimensional extension of CONEX and show its performance compared to CORSIKA by discussing muon-related air-shower features for three experiments: KASCADE, IceTop, and the Pierre Auger Observatory. We also implement an effective version of the core-corona model to demonstrate the impact of the core effect, as observed at the LHC, on the muon content in air showers produced by ultra-high energy cosmic rays. At a primary energy of E$_{0}$ = 10$^{19}$ eV, we obtain an increase of 15% to 20% in the muon content.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Parametrizing the detector response with neural networks

In high energy physics, characterizing the response of a detector to radiation is one of the most important and fundamental experimental tasks. In many cases, this task is accomplished by parameterizing summary statistics of the full detector response probability density. The parameterized detector response can then be used for calibration as well as for directly improving physics analysis sensitivity. This paper reports on how to parameterize summary statistics of the detector response using neural networks. Specifically, neural networks are powerful tools for incorporating multidimensional data and the loss function used during training determines which summary statistic is learned. One common summary statistic that has not been combined with deep learning (as far as the authors are aware) is the mode. A neural network-based approach to mode learning is proposed and empirically demonstrated in the context of high energy jet calibrations. Altogether, the neural network-based toolkit for detector response parameterization can enhance the utility of data collected at high energy physics experiments and beyond.

47 OTHER INSTRUMENTATION↗