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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Ab Initio Calculations Of Light-Ion Reactions

The exact treatment of nuclei starting from the constituent nucleons and the fundamental interactions among them has been a long-standing goal in nuclear physics. In addition to the complex nature of nuclear forces, one faces the quantum-mechanical many-nucleon problem governed by an interplay between bound and continuum states. In recent years, significant progress has been made in ab initio nuclear structure and reaction calculations based on input from QCD employing Hamiltonians constructed within chiral effective field theory. In this contribution, we present one of such promising techniques capable of describing simultaneously both bound and scattering states in light nuclei. By combining the resonating-group method (RGM) with the ab initio no-core shell model (NCSM), we complement a microscopic cluster approach with the use of realistic interactions and a microscopic and consistent description of the clusters. We discuss applications to light nuclei scattering, radiative capture and fusion reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

DIFFRACTION-LIMITED VISIBLE LIGHT IMAGES OF ORION TRAPEZIUM CLUSTER WITH THE MAGELLAN ADAPTIVE SECONDARY ADAPTIVE OPTICS SYSTEM (MagAO)

We utilized the new high-order (250-378 mode) Magellan Adaptive Optics system (MagAO) to obtain very high spatial resolution observations in ''visible light'' with MagAO's VisAO CCD camera. In the good-median seeing conditions of Magellan (0.''5-0.''7), we find MagAO delivers individual short exposure images as good as 19 mas optical resolution. Due to telescope vibrations, long exposure (60 s) r' (0.63 {mu}m) images are slightly coarser at FWHM = 23-29 mas (Strehl {approx}28%) with bright (R < 9 mag) guide stars. These are the highest resolution filled-aperture images published to date. Images of the young ({approx}1 Myr) Orion Trapezium {theta}{sup 1} Ori A, B, and C cluster members were obtained with VisAO. In particular, the 32 mas binary {theta}{sup 1} Ori C{sub 1} C{sub 2} was easily resolved in non-interferometric images for the first time. The relative positions of the bright trapezium binary stars were measured with {approx}0.6-5 mas accuracy. We are now sensitive to relative proper motions of just {approx}0.2 mas yr{sup -1} ({approx}0.4 km s{sup -1} at 414 pc)-this is a {approx}2-10 Multiplication-Sign improvement in orbital velocity accuracy compared to previous efforts. For the first time, we see clear motion of the barycenter of {theta}{sup 1} Ori B{sub 2} B{sub 3} about {theta}{sup 1} Ori B{sub 1}. All five members of the {theta}{sup 1} Ori B system appear likely to be a gravitationally bound ''mini cluster'', but we find that not all the orbits can be both circular and co-planar. The lowest mass member of the {theta}{sup 1} Ori B system (B{sub 4}; mass {approx}0.2 M{sub Sun }) has a very clearly detected motion (at 4.1 {+-} 1.3 km s{sup -1}; correlation = 99.9%) w.r.t. B{sub 1}. Previous work has suggested that B{sub 4} and B{sub 3} are on long-term unstable orbits and will be ejected from this ''mini cluster''. However, our new ''baseline'' model of the {theta}{sup 1} Ori B system suggests a more hierarchical system than previously thought, and so the ejection of B{sub 4} may not occur for many orbits, and B{sub 3} may be stable against ejection in the long-term. This ''ejection'' process of the lowest mass member of a ''mini cluster'' could play a major role in the formation of low-mass stars and brown dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE CONTRIBUTION OF HALOS WITH DIFFERENT MASS RATIOS TO THE OVERALL GROWTH OF CLUSTER-SIZED HALOS

We provide a new observational test for a key prediction of the ΛCDM cosmological model: the contributions of mergers with different halo-to-main-cluster mass ratios to cluster-sized halo growth. We perform this test by dynamically analyzing 7 galaxy clusters, spanning the redshift range 0.13 < z{sub c} < 0.45 and caustic mass range 0.4-1.5 10{sup 15} h{sub 0.73}{sup -1} M{sub ☉}, with an average of 293 spectroscopically confirmed bound galaxies to each cluster. The large radial coverage (a few virial radii), which covers the whole infall region, with a high number of spectroscopically identified galaxies enables this new study. For each cluster, we identify bound galaxies. Out of these galaxies, we identify infalling and accreted halos and estimate their masses and their dynamical states. Using the estimated masses, we derive the contribution of different mass ratios to cluster-sized halo growth. For mass ratios between ∼0.2 and ∼0.7, we find a ∼1σ agreement with ΛCDM expectations based on the Millennium simulations I and II. At low mass ratios, ∼< 0.2, our derived contribution is underestimated since the detection efficiency decreases at low masses, ∼2 × 10{sup 14} h{sub 0.73}{sup -1} M{sub ☉}. At large mass ratios, ∼> 0.7, we do not detect halos probably because our sample, which was chosen to be quite X-ray relaxed, is biased against large mass ratios. Therefore, at large mass ratios, the derived contribution is also underestimated.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Ceria nanoclusters on graphene/Ru(0001): A new model catalyst system

The growth of ceria nanoclusters on single-layer graphene on Ru(0001) has been examined, with a view towards fabricating a stable system for model catalysis studies. The surface morphology and cluster distribution as a function of oxide coverage and substrate temperature has been monitored by scanning tunneling microscopy (STM), whereas the chemical composition of the cluster deposits has been determined by Auger electron spectroscopy (AES). The ceria nanoparticles are of the CeO2(111)-type and are anchored at the intrinsic defects of the graphene surface, resulting in a variation of the cluster densities across the macroscopic sample surface. The ceria clusters on graphene display a remarkable stability against reduction in ultrahigh vacuum up to 900 K, but some sintering of clusters is observed for temperatures >450 K. The evolution of the cluster size distribution suggests that the sintering proceeds via a Smoluchowski ripening mechanism, i.e. diffusion and aggregation of entire clusters.

Ceria, CeO2, nanoclusters, graphene, Ru(0001), Smo↗
DOE OSTI2017

Analysis of the Amplitude of the Sunyaev–Zel’dovich Effect out to Redshift z = 0.8

The interaction of the cosmic microwave background (CMB) with the hot gas in clusters of galaxies, the so-called Sunyaev–Zel’dovich (SZ) effect, is a very useful tool that allows us to determine the physical conditions in such clusters and fundamental parameters of the cosmological models. In this work, we determine the dependence of the SZ surface brightness amplitude with redshift and mass of the clusters. We have used PLANCK+IRAS data in the microwave-far-infrared and a catalog with ≳10{sup 5} clusters of galaxies extracted from the SDSS by Wen et al. We estimate and subtract the dust emission from those clusters. From the residual flux, we extract its SZ flux densities. The absolute value of the SZ amplitude indicates that the gas mass is around 10% of the total mass for cluster masses of M∼10{sup 14} M{sub ⊙}. This amplitude is compatible with no evolution with redshift and proportional to M{sup 2.70±0.37} (using X-ray derived masses) or M{sup 2.51±0.38} (using weak-lensing derived masses), with some tension regarding the expectations of the self-similar dependence (amplitude proportional to M{sup 5/3}). Other secondary products of our analysis include that clusters have a dust emission with emissivity index β∼2 and temperature T∼25 K; we confirm that the CMB temperature agrees with a dependence of T{sub 0}(1+z) with clusters of much lower mass than those explored previously; and we find that the cluster masses derived by Wen et al. from a richness-mass relationship are biased by a factor of (1+z){sup −1.8} with respect to the X-ray and weak-lensing measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2011

A COSMIC COINCIDENCE: THE POWER-LAW GALAXY CORRELATION FUNCTION

We model the evolution of galaxy clustering through cosmic time to investigate the nature of the power-law shape of {xi}(r), the galaxy two-point correlation function. While {xi}(r) at large scales is set by primordial fluctuations, departures from a power law are governed by galaxy pair counts at small scales, subject to nonlinear dynamics. We assume that galaxies reside within dark matter halos and subhalos. Therefore, the shape of the correlation function at small scales depends on the amount of halo substructure. We use a semi-analytic substructure evolution model to study subhalo populations within host halos. We find that tidal mass loss and, to a lesser extent, dynamical friction dramatically deplete the number of subhalos within larger host halos over time, resulting in a {approx}90% reduction by z = 0 compared to the number of distinct mergers that occur during the assembly of a host halo. We show that these nonlinear processes resulting in this depletion are essential for achieving a power law {xi}(r). We investigate how the shape of {xi}(r) depends on subhalo mass (or luminosity) and redshift. We find that {xi}(r) breaks from a power law at high masses, implying that only galaxies of luminosities {approx}< L{sub *} should exhibit power-law clustering. Moreover, we demonstrate that {xi}(r) evolves from being far from a power law at high redshift, toward a near power-law shape at z = 0. We argue that {xi}(r) will once again evolve away from a power law in the future. This is in large part caused by the evolving competition between the accretion and destruction rates of subhalos over time, which happen to strike just the right balance at z {approx} 0. We then investigate the conditions required for {xi}(r) to be a power law in a general context. We use the halo model, along with simple parameterizations of the halo occupation distribution, to probe galaxy occupation at various masses and redshifts. We show that the key ingredients determining the shape of {xi}(r) are the fraction of galaxies that are satellites, the relative difference in mass between the halos of isolated galaxies and halos that contain a single satellite on average, and the rareness of halos that host galaxies. These pieces are intertwined and we find no simple, universal rule for which a power law {xi}(r) will occur. However, we do show that the physics responsible for setting the galaxy content of halos do not care about the conditions needed to achieve a power law {xi}(r) and that these conditions are met only in a narrow mass and redshift range. We conclude that the power-law nature of {xi}(r) for L{sub *} and fainter galaxy samples at low redshift is a cosmic coincidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Programming Non-Trivial Algorithms in the Measurement Based Quantum Computation Model

We provide a set of prescriptions for implementing a quantum circuit model algorithm as measurement based quantum computing (MBQC) algorithm1, 2 via a large cluster state. As means of illustration we draw upon our numerical modeling experience to describe a large graph state capable of searching a logical 8 element list (a non-trivial version of Grover's algorithm3 with feedforward). We develop several prescriptions based on analytic evaluation of cluster states and graph state equations which can be generalized into any circuit model operations. Such a resulting cluster state will be able to carry out the desired operation with appropriate measurements and feed forward error correction. We also discuss the physical implementation and the analysis of the principal 3-qubit entangling gate (Toffoli) required for a non-trivial feedforward realization of an 8-element Grover search algorithm.

Alsing, Paul↗
DOE OSTI2020

A Look Inside the Black Box: Using graph-theoretical descriptors to interpret a Continuous-Filter Convolutional Neural Network (CF-CNN) trained on the global and local minimum energy structures of neutral water clusters

A Continuous Filter Convolutional Neural Network (CF-CNN) was trained to predict the potential energy of water cluster networks \ce{(H2O)_{\textit{N}}}, \textit{N}=10--30, corresponding to local minima lying within 5 kcal/mol from the putative minima taken from a newly published database containing over 5 million unique networks. The chemical sampling space of the database was characterized using chemical descriptors derived from graph theory, which led to the identification of important trends in the topology, connectivity, polygon structures associated with the various networks as a function of cluster size. The resulting graphs are available alongside the original database at \url{https://sites.uw.edu/wdbase/}. The CF-CNN trained on a subset of 500,000 networks for (\textit{N}=10, 30) yielded a mean absolute error of 0.002$\pm$0.002 kcal/mol per water molecule, giving the trained CF-CNN the highest accuracy of any neural network-based surrogate model to date. In addition, clusters of sizes not included in the training set exhibited errors of the same magnitude, indicating that the CF-CNN ptotocol is general enough to accurately predict energies of networks for both smaller and larger sizes than those used during training. The graph-theoretical descriptors were developed in order to analyze the properties of the full database and interpret the predictive power of the CF-CNN. Using topology measures, such as the Wiener index and the average shortest path length along with two similarity measures, we showed that all networks from the test set were within the range of the ones from the training set, suggesting that the training set covered the chemical space of interest quite well. Our graph analysis suggests that the mean degree and number of polygons for networks with larger errors tend to lie further from the mean than those with lower errors. The generality of the used CF-CNN was thus demonstrated, while the use of the graph-theoretical descriptors assisted in interpreting the predicted results.

Bilbrey, Jenna A.↗
DOE OSTI2025

Weak lensing mass-richness relation of redMaPPer clusters in LSST DESC DC2 simulations

Cluster scaling relations are key ingredients in cluster abundance-based cosmological studies. In optical cluster cosmology, where clusters are detected through their richness, cluster-weak gravitational lensing has proven to be a powerful tool to constrain the cluster mass-richness relation. This work is conducted as part of the Dark Energy Science Collaboration (DESC), which aims to analyze the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory, starting in 2026. Cluster properties inferred from weak lensing, such as mass, suffer from several sources of bias. In this paper, we aim to test the impact of modeling choices and observational systematics in cluster lensing on the inference of the mass-richness relation. We constrained the mass-richness relation of 3600 clusters detected by the redMaPPer algorithm in the cosmoDC2 extragalactic mock catalog of the LSST DESC DC2 simulation, covering 440 deg 2 , using number count measurements and either stacked weak lensing profiles or mean cluster masses in several intervals of richness (20 ≤ λ ≤ 200) and redshift (0.2 ≤ z ≤ 1). We provide the first constraints on the redMaPPer cluster mass-richness relation detected in cosmoDC2. We find that for an LSST-like source galaxy density, our constraints are robust to changes in the concentration-mass relation, as well as the dark matter density profile modeling choices, when source redshifts and shapes are perfectly known. We find that photometric redshift uncertainties can introduce bias at the 1σ level, which could be mitigated by an overall correction factor fitted jointly with the scaling parameters. We find that including positive shear-richness covariance in the fit shifts the results by up to 0.5σ. Our constraints also offer a fair comparison to a fiducial mass-richness relation, obtained from matching cosmoDC2 halo masses to redMaPPer-detected cluster richness results.

galaxy clusters↗
DOE OSTI2012

AGE AND MASS FOR 920 LARGE MAGELLANIC CLOUD CLUSTERS DERIVED FROM 100 MILLION MONTE CARLO SIMULATIONS

We present new age and mass estimates for 920 stellar clusters in the Large Magellanic Cloud (LMC) based on previously published broadband photometry and the stellar cluster analysis package, MASSCLEANage. Expressed in the generic fitting formula, d{sup 2} N/dMdt{proportional_to}M{sup {alpha}} t{sup {beta}}, the distribution of observed clusters is described by {alpha} = -1.5 to -1.6 and {beta} = -2.1 to -2.2. For 288 of these clusters, ages have recently been determined based on stellar photometric color-magnitude diagrams, allowing us to gauge the confidence of our ages. The results look very promising, opening up the possibility that this sample of 920 clusters, with reliable and consistent age, mass, and photometric measures, might be used to constrain important characteristics about the stellar cluster population in the LMC. We also investigate a traditional age determination method that uses a {chi}{sup 2} minimization routine to fit observed cluster colors to standard infinite-mass limit simple stellar population models. This reveals serious defects in the derived cluster age distribution using this method. The traditional {chi}{sup 2} minimization method, due to the variation of U, B, V, R colors, will always produce an overdensity of younger and older clusters, with an underdensity of clusters in the log (age/yr) = [7.0, 7.5] range. Finally, we present a unique simulation aimed at illustrating and constraining the fading limit in observed cluster distributions that includes the complex effects of stochastic variations in the observed properties of stellar clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Synopsis of SURF and SURFplus

Developed by Menikoff and Shaw, the SURF reactive burn model builds on the Ignition and Growth concept by incorporating the lead shock pressure directly into the volumetric hot-spot burn rate. The plus-extension augments the model with a late time surface burn rate due to carbon clustering. Together, SURF and SURFplus allow for robust modeling of both conventional and insensitive high explosives. Practically, the SURF burn models require shock detection and the advection of the lead shock pressure as an additional material field. Calibrated parameters for given equations of state and thermodynamic closure are dependent on initial temperature and density. An implementation in Python is given.

42 ENGINEERING↗
DOE OSTI2024

Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample

We present a clustering analysis of the BOSS DR12 CMASS galaxy sample, combining measurements of the galaxy two-point correlation function and density-split clustering down to a scale of $1 \, h^{-1}\, \text{Mpc}$. Our theoretical framework is based on emulators trained on high-fidelity mock galaxy catalogues that forward model the cosmological dependence of the clustering statistics within an extended-ΛCDM framework, including redshift-space and Alcock–Paczynski distortions. Our base-ΛCDM analysis finds ω cdm = 0.1201 ± 0.0022, σ 8 = 0.792 ± 0.034, and n s = 0.970 ± 0.018, corresponding to fσ 8 = 0.462 ± 0.020 at z ≈ 0.525, which is in agreement with Planck 2018 predictions and various clustering studies in the literature. We test single-parameter extensions to base-ΛCDM, varying the running of the spectral index, the dark energy equation of state, and the density of mass-less relic neutrinos, finding no compelling evidence for deviations from the base model. We model the galaxy–halo connection using a halo occupation distribution framework, finding signatures of environment-based assembly bias in the data. We validate our pipeline against mock catalogues that match the clustering and selection properties of CMASS, showing that we can recover unbiased cosmological constraints even with a volume 84 times larger than the one used in this study.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

Cluster analysis of multiple planetary flow regimes

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Mo, Kingtse↗
DOE OSTI2011

THE GLOBAL EVOLUTION OF GIANT MOLECULAR CLOUDS. II. THE ROLE OF ACCRETION

We present virial models for the global evolution of giant molecular clouds (GMCs). Focusing on the presence of an accretion flow and accounting for the amount of mass, momentum, and energy supplied by accretion and star formation feedback, we are able to follow the growth, evolution, and dispersal of individual GMCs. Our model clouds reproduce the scaling relations observed in both galactic and extragalactic clouds. We find that accretion and star formation contribute roughly equal amounts of turbulent kinetic energy over the lifetime of the cloud. Clouds attain virial equilibrium and grow in such a way as to maintain roughly constant surface densities, with typical surface densities of order 50-200 M{sub sun} pc{sup -2}, in good agreement with observations of GMCs in the Milky Way and nearby external galaxies. We find that as clouds grow, their velocity dispersion and radius must also increase, implying that the linewidth-size relation constitutes an age sequence. Lastly, we compare our models to observations of GMCs and associated young star clusters in the Large Magellanic Cloud and find good agreement between our model clouds and the observed relationship between H II regions, young star clusters, and GMCs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Cosmic variance of the galaxy cluster weak lensing signal

Intrinsic variations of the projected density profiles of clusters of galaxies at fixed mass are a source of uncertainty for cluster weak lensing. We present a semi-analytical model to account for this effect, based on a combination of variations in halo concentration, ellipticity and orientation, and the presence of correlated haloes. We calibrate the parameters of our model at the 10 per cent level to match the empirical cosmic variance of cluster profiles at M 200m ≈ 10 14 …10 15 h –1 M ⊙ , z = 0.25…0.5 in a cosmological simulation. We show that weak lensing measurements of clusters significantly underestimate mass uncertainties if intrinsic profile variations are ignored, and that our model can be used to provide correct mass likelihoods. Effects on the achievable accuracy of weak lensing cluster mass measurements are particularly strong for the most massive clusters and deep observations (with ≈20 per cent uncertainty from cosmic variance alone at M 200m ≈ 10 15 h –1 M ⊙ and z = 0.25), but significant also under typical ground-based conditions. We show that neglecting intrinsic profile variations leads to biases in the mass-observable relation constrained with weak lensing, both for intrinsic scatter and overall scale (the latter at the 15 per cent level). Furthermore, these biases are in excess of the statistical errors of upcoming surveys and can be avoided if the cosmic variance of cluster profiles is accounted for.

79 ASTRONOMY AND ASTROPHYSICS↗