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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Dark Energy Survey year 3 results: Constraints on cosmological parameters and galaxy-bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

We constrain cosmological parameters and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey (DES) year-3 data. We describe our modeling framework and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy-bias model and redMaGiC galaxy sample, we obtain 10% constraints on the matter density of the Universe. Here, we also implement a nonlinear galaxy-bias model to probe smaller scales that includes parametrization based on hybrid perturbation theory and find that it leads to a 17% gain in cosmological constraining power. We perform robustness tests of our methodology pipeline and demonstrate stability of the constraints to changes in the theory model. Using the redMaGiC galaxy sample as foreground lens galaxies and adopting the best-fitting cosmological parameters from DES year-1 data, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to decorrelation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the S 8 parameter. We find that a scale-, redshift- and sky-area-independent phenomenological decorrelation parameter can effectively capture this inconsistency between the galaxy clustering and galaxy-galaxy lensing. We trace the source of this correlation to a color-dependent photometric issue and minimize its impact on our result by changing the selection criteria of redMaGiC galaxies. Using this new sample, our constraints on the S 8 parameter are consistent with previous studies and we find a small shift in the Ω m constraints compared to the fiducial redMaGiC sample. We infer the constraints on the mean host-halo mass of the redMaGiC galaxies in this new sample from the large-scale bias constraints, finding the galaxies occupy halos of mass approximately 1.6 × 10 13 M ⊙ /h.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Networked Microgrids for Grid Resilience, Robustness, and Efficiency: A Review

Networked microgrids (NMGs) are clusters of microgrids that are physically connected and functionally interoperable. The massive and unprecedented deployment of smart grid technologies, new business models, and involvement of new stakeholders enable NMGs to be a conceptual operation paradigm for future distribution systems. Much work needs to be done, however, to enable NMGs to achieve seamless coordination, including physical, communication, and functional integration. In this paper, we review and summarize the state-of-the-art methodologies for operation and control of NMGs. Furthermore, we also specifically discuss the notion of dynamic boundaries for advanced microgrid applications. In addition, we introduce the opportunities, challenges, and possible solutions regarding NMGs for improving grid resilience, robustness, and efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and Planck . III. Combined cosmological constraints

Here we present cosmological constraints from the analysis of two-point correlation functions between galaxy positions and galaxy lensing measured in Dark Energy Survey (DES) Year 3 data and measurements of cosmic microwave background (CMB) lensing from the South Pole Telescope (SPT) and Planck. When jointly analyzing the DES-only two-point functions and the DES cross-correlations with SPT+Planck CMB lensing, we find Ω m = 0.344 ± 0.030 and S 8 ≡ σ 8 (Ω m /0.3) 0.5 = 0.773 ± 0.016, assuming ΛCDM. When additionally combining with measurements of the CMB lensing autospectrum, we find Ω m = 0.306$^{+0.018}_{-0.021}$ and S 8 = 0.792 ± 0.012. The high signal-to-noise of the CMB lensing cross-correlations enables several powerful consistency tests of these results, including comparisons with constraints derived from cross-correlations only, and comparisons designed to test the robustness of the galaxy lensing and clustering measurements from DES. Applying these tests to our measurements, we find no evidence of significant biases in the baseline cosmological constraints from the DES-only analyses or from the joint analyses with CMB lensing cross-correlations. However, the CMB lensing cross-correlations suggest possible problems with the correlation function measurements using alternative lens galaxy samples, in particular the redMaGiC galaxies and high-redshift MagLim galaxies, consistent with the findings of previous studies. We use the CMB lensing cross-correlations to identify directions for further investigating these problems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

A Shift Selection Strategy for Parallel Shift-invert Spectrum Slicing in Symmetric Self-consistent Eigenvalue Computation

The central importance of large-scale eigenvalue problems in scientific computation necessitates the development of massively parallel algorithms for their solution. Recent advances in dense numerical linear algebra have enabled the routine treatment of eigenvalue problems with dimensions on the order of hundreds of thousands on the world’s largest supercomputers. In cases where dense treatments are not feasible, Krylov subspace methods offer an attractive alternative due to the fact that they do not require storage of the problem matrices. However, demonstration of scalability of either of these classes of eigenvalue algorithms on computing architectures capable of expressing massive parallelism is non-trivial due to communication requirements and serial bottlenecks, respectively. In this work, we introduce the SISLICE method: a parallel shift-invert algorithm for the solution of the symmetric self-consistent field (SCF) eigenvalue problem. The SISLICE method drastically reduces the communication requirement of current parallel shift-invert eigenvalue algorithms through various shift selection and migration techniques based on density of states estimation and k-means clustering, respectively. This work demonstrates the robustness and parallel performance of the SISLICE method on a representative set of SCF eigenvalue problems and outlines research directions that will be explored in future work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Fock-Space Schrieffer–Wolff Transformation: Classically-Assisted Rank-Reduced Quantum Phase Estimation Algorithm

We present an extension of many-body downfolding methods to reduce the resources required in the quantum phase estimation (QPE) algorithm. In this paper, we focus on the Schrieffer–Wolff (SW) transformation of the electronic Hamiltonians for molecular systems that provides significant simplifications of quantum circuits for simulations of quantum dynamics. We demonstrate that by employing Fock-space variants of the SW transformation (or rank-reducing similarity transformations (RRST)) one can significantly increase the locality of the qubit-mapped similarity-transformed Hamiltonians. The practical utilization of the SW-RRST formalism is associated with a series of approximations discussed in the manuscript. In particular, amplitudes that define RRST can be evaluated using conventional computers and then encoded on quantum computers. The SW-RRST QPE quantum algorithms can also be viewed as an extension of the standard state-specific coupled-cluster downfolding methods to provide a robust alternative to the traditional QPE algorithms to identify the ground and excited states for systems with various numbers of electrons using the same Fock-space representations of the downfolded Hamiltonian. The RRST formalism serves as a design principle for developing new classes of approximate schemes that reduce the complexity of quantum circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Predicting metabolic modules in incomplete bacterial genomes with MetaPathPredict

The reconstruction of complete microbial metabolic pathways using ‘omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from the KEGG module database, MetaPathPredict employs deep learning models to predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as a Python module, and both options are designed to be run locally or on a compute cluster. Benchmarks show that MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2014

Wide-Field Hubble Space Telescope Observations of the Globular Cluster System in NGC 1399*

We present a comprehensive high spatial resolution imaging study of globular clusters (GCs) in NGC 1399, thecentral giant elliptical cD galaxy in the Fornax galaxy cluster, conducted with the Advanced Camera for Surveys(ACS) aboard theHubble Space Telescope(HST).Using a novel technique to construct drizzled point-spreadfunction libraries for HSTACS data, we accurately determine the fidelity of GC structural parameter measurementsfrom detailed artificial star cluster experiments and show the superior robustness of the GC half-light radius,rh,compared with other GC structural parameters, such as King core and tidal radius. The measurement ofrhfor themajor fraction of the NGC 1399 GC system reveals a trend of increasingrhversus galactocentric distance,Rgal,out to about 10 kpc and a flat relation beyond. This trend is very similar for blue and red GCs, which are found tohave a mean size ratio ofrh,redrh,blue0.820.11 at all galactocentric radii from the core regions of the galaxyout to40 kpc. This suggests that the size difference between blue and red GCs is due to internal mechanismsrelated to the evolution of their constituent stellar populations. Modeling the mass density profile of NGC 1399shows that additional external dynamical mechanisms are required to limit the GC size in the galaxy halo regionstorh2 pc. We suggest that this may be realized by an exotic GC orbit distribution function, an extended darkmatter halo, andor tidal stress induced by the increased stochasticity in the dwarf halo substructure at largergalactocentric distances. We compare our results with the GCrhdistribution functions in various galaxies and findthat the fraction of extended GCs withrh5 pc is systematically larger in late-type galaxies compared with GCsystems in early-type galaxies. This is likely due to the dynamically more violent evolution of early-type galaxies.We match our GCrhmeasurements with radial velocity data from the literature and split the resulting sample at themedianrhvalue into compact and extended GCs. We find that compact GCs show a significantly smaller line-of-sight velocity dispersion,cmp22525 km s1, than their extended counterparts,ext31721 km s1.Considering the weaker statistical correlation in the GCrhcolor and the GCrhRgalrelations, the more significantGC sizedynamics relation appears to be astrophysically more relevant and hints at the dominant influence of theGC orbit distribution function on the evolution of GC structural parameters.

Hubble↗

NASA NTRS1994

Cluster evolution and microwave source counts

We present the modeled counts for the expected Sunyaev-Zel'dovich microwave sources associated with clusters of galaxies, predicted for experiments with arcminute-scale spatial resolution, assuming self-similar cluster evolution, for different spectra of the primordial density fluctuations and values of the cosmological density parameter Omega. Our simulations show that the source counts should be a powerful test of the evolution of very high redshift clusters. Experiments with 1 - 2 min spatial resolution, with moderate sensitivity but covering a large area of the sky, would be most effective for studying the SZ source population. Recent arcminute-scale radio experiments, the Owens Valley Radio Observatory (OVRO) RING experiment and VLA deep imaging, achieved sensitivity and sky coverage close to that needed for the detection of negative sources associated with very distant clusters. From the absence of cluster detections in these experiments, we rule out, with 90% confidence, models with Omega less than 0.3 and n = +1 as predicting too many bright sources; or there is no hot gas in clusters more distant than z(sub max) = 5 in such models. If the single negative source detected in the RING experiment is a distant cluster, the Omega = 1, n = -2 model also may be ruled out as it predicts too few sources. The new generation of telescopes, including the new SUZIE and Ryle instruments, will soon be able to detect distant clusters. The cluster population in the past has been modeled by scaling the observed present-day sample of X-ray clusters back to high redshifts, an approach which makes the best use of the observed cluster gas parameters, and makes the simulations robust to the assumed evolution at very early epochs. Although the pure self-similar model may be incompatible with the variety of observed evolutionary effects, we show that reasonable modifications to the intracluster gas history in that model, proposed to reconcile the self-similar evolution of cluster mass and the observed evolution of their X-ray luminosity, do not considerably change our microwave predictions made using the pure self-similar model. That is, the results of our simulations are applicable to the wide class of evolutionary models in which the cluster gas mass times gas temperature evolves as the dark mass times cluster virial temperature.

Markevitch, M.↗

NASA NTRS1998

Galaxy Cluster Masses at Moderate Redshifts

The masses of galaxy clusters are dominated by dark matter, and a robust determination of their masses has the potential of indicating how much dark matter exists on large scales in the universe, and the cosmological parameter Omega. X-ray observations of galaxy clusters provide a direct measure of both the gas mass in the intra-cluster medium, and also the total gravitating mass of the cluster. We used new and archival ROSAT observations to measure these quantities for a sample of intermediate redshift clusters which have also been subject to intensive dynamical studies, in order to compare the mass estimates from different methods. We used data from 14 of the CNOC cluster sample at 0.18 less than z less than 0.55 for this study. A direct comparison of dynamical mass estimates from Carlberg, Yee & Ellingson (1997) yielded surprisingly good results. The X-ray/dynamical mass ratios have a mean of 0.96+/- 0.10, indicating that for this sample, both methods are probably yielding very robust mass estimates. Comparison with mass estimates from gravitational lensing studies from the literature showed a small systematic with weak lensing estimates, and large discrepancies with strong lensing estimates. This latter is not surprising, given that these measurement are made close to the central core, where optical and X-ray estimates are less certain, and where substructure and the effects of individual galaxies will be more pronounced. These results are presented in Lewis, Ellingson, Morris/Carlberg, 1998, submitted to the Astrophysical Journal. (Note that Lewis is Ellingson's Ph.D. thesis, who received direct support from this grant and is using this investigation as part of his thesis.) Three additional papers are in preparation. The first provides a comparison of the mass profiles as measured in X- rays and in galaxy dynamics. These profiles are difficult to determine for individual clusters, and are subject to asphericity and other individual quirks of each cluster. However, a composite profile for each method will allow us to test our assumptions of hydrostatic/dynamical equilibrium in the sample as a whole. A second paper provides a more detailed look at the cluster MS0906+11, which is a merging system. A third paper authord with J. Mohr at U. Chicago will invetigate the size-temoerature relationship for intermediate redshift clusters and its impications on cluster formation and cosmology. Future work on these data will include comparisons of the cluster galaxy populations and the extent of the intra-cluster medium, and a more homogeneous analysis of gravitational lensing.

Ellingson, E.↗

NASA NTRS1998

X-ray Spectra of Distant Clusters

The masses of galaxy clusters are dominated by dark matter, and a robust determination of their temperatures and masses has the potential of indicating how much dark matter exists on large scales in the universe, and the cosmological parameter Omega. X-ray observations of galaxy clusters provide a direct measure of both the gas mass in the intra-cluster medium, and also the total gravitating mass of the cluster. We used new and archival ASCA and ROSAT observations to measure these quantities for a sample of intermediate redshift clusters which have also been subject to intensive dynamical studies, in order to compare the mass estimates from different methods. We used data from 12 of the CNOC cluster sample at 0.18 less than z less than 0.55 for this study. A direct comparison of dynamical mass estimates from Carlberg, Yee & Ellingson (1997) yielded surprisingly good results. The X-ray/dynamical mass ratios have a mean of 0.96+/- 0.10, indicating that for this sample, both methods are probably yielding very robust mass estimates. Comparison with mass estimates from gravitational lensing studies from the literature showed a small systematic with weak lensing estimates, and large discrepancies with strong lensing estimates. This latter is not surprising, given that these measurements are made close to the central core, where optical and Xray estimates are less certain, and where substructure and the effects of individual galaxies will be more pronounced. These results are presented in Lewis, Ellingson, Morris \& Carlberg, 1998, submitted to the Astrophysical Journal.

Ellingson, E.↗

NASA NTRS2011

The Atacama Cosmology Telescope: High-Resolution Sunyaev-Zel'dovich Array Observations of ACT SZE-Selected Clusters from the Equatorial Strip

We present follow-up observations with the Sunyaev-Zel'dovich Array (SZA) of optically-confirmed galaxy clusters found in the equatorial survey region of the Atacama Cosmology Telescope (ACT): ACT-CL J0022-0036, ACT-CL J2051+0057, and ACT-CL J2337+0016. ACT-CL J0022-0036 is a newly-discovered, massive (10(exp 15) Msun), high-redshift (z=0.81) cluster revealed by ACT through the Sunyaev-Zel'dovich effect (SZE). Deep, targeted observations with the SZA allow us to probe a broader range of cluster spatial scales, better disentangle cluster decrements from radio point source emission, and derive more robust integrated SZE flux and mass estimates than we can with ACT data alone. For the two clusters we detect with the SZA we compute integrated SZE signal and derive masses from the SZA data only. ACT-CL J2337+0016, also known as Abell 2631, has archival Chandra data that allow an additional X-ray-based mass estimate. Optical richness is also used to estimate cluster masses and shows good agreement with the SZE and X-ray-based estimates. Based on the point sources detected by the SZA in these three cluster fields and an extrapolation to ACT's frequency, we estimate that point sources could be contaminating the SZE decrement at the less than = 20% level for some fraction of clusters.

Reese, Erik D.↗

NASA NTRS2011

The Atacama Cosmology Telescope: High-Resolution Sunyaev-Zeldovich Array Observations of ACT SZE-Selected Clusters from the Equatorial Strip

We present follow-up observations with the Sunyaev-Zel'dovich Array (SZA) of optically-confirmed galaxy clusters found in the equatorial survey region of the Atacama Cosmology Telescope (ACT): ACT-CL J0022-0036, ACT-CL J2051+0057, and ACT-CL J2337+0016. ACT-CL J0022-0036 is a newly-discovered, massive ( approximately equals 10(exp 15) Solar M), high-redshift (z = 0.81) cluster revealed by ACT through the Sunyaev-Zeldovich effect (SZE). Deep, targeted observations with the SZA allow us to probe a broader range of cluster spatial scales, better disentangle cluster decrements from radio point source emission, and derive more robust integrated SZE flux and mass estimates than we can with ACT data alone. For the two clusters we detect with the SZA we compute integrated SZE signal and derive masses from the SZA data only. ACT-CL J2337+0016, also known as Abell 2631, has archival Chandra data that allow an additional X-ray-based mass estimate. Optical richness is also used to estimate cluster masses and shows good agreement with the SZE and X-ray-based estimates. Based on the point sources detected by the SZA in these three cluster fields and an extrapolation to ACT's frequency, we estimate that point sources could be contaminating the SZE decrement at the approx < 20% level for some fraction of clusters.

galaxies↗

NASA NTRS1993

A robust multilevel simultaneous eigenvalue solver

Multilevel (ML) algorithms for eigenvalue problems are often faced with several types of difficulties such as: the mixing of approximated eigenvectors by the solution process, the approximation of incomplete clusters of eigenvectors, the poor representation of solution on coarse levels, and the existence of close or equal eigenvalues. Algorithms that do not treat appropriately these difficulties usually fail, or their performance degrades when facing them. These issues motivated the development of a robust adaptive ML algorithm which treats these difficulties, for the calculation of a few eigenvectors and their corresponding eigenvalues. The main techniques used in the new algorithm include: the adaptive completion and separation of the relevant clusters on different levels, the simultaneous treatment of solutions within each cluster, and the robustness tests which monitor the algorithm's efficiency and convergence. The eigenvectors' separation efficiency is based on a new ML projection technique generalizing the Rayleigh Ritz projection, combined with a technique, the backrotations. These separation techniques, when combined with an FMG formulation, in many cases lead to algorithms of O(qN) complexity, for q eigenvectors of size N on the finest level. Previously developed ML algorithms are less focused on the mentioned difficulties. Moreover, algorithms which employ fine level separation techniques are of O(q(sub 2)N) complexity and usually do not overcome all these difficulties. Computational examples are presented where Schrodinger type eigenvalue problems in 2-D and 3-D, having equal and closely clustered eigenvalues, are solved with the efficiency of the Poisson multigrid solver. A second order approximation is obtained in O(qN) work, where the total computational work is equivalent to only a few fine level relaxations per eigenvector.

Costiner, Sorin↗

NASA NTRS1998

Galaxy Cluster Masses at Moderate Redshifts

Ellingson, E.↗

DOE OSTI2021

Zeolite-Stabilized Di- and Tetranuclear Molybdenum Sulfide Clusters Form Stable Catalytic Hydrogenation Sites

Supercages of faujasite (FAU)-type zeolites serve as a robust scaffold for stabilizing dinuclear (Mo 2 S 4 ) and tetranuclear (Mo 4 S 4 ) molybdenum sulfide clusters. The FAU-encaged Mo 4 S 4 clusters have a distorted cubane structure similar to the FeMo-cofactor in nitrogenase. Both clusters possess one unpaired electron per Mo atom. Additionally, they show identical catalytic activity per sulfide cluster. Their catalytic activity is stable (> 150 h) for ethene hydrogenation, while layered MoS 2 structures deactivate significantly under the same reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Robust training of machine learning interatomic potentials with dimensionality reduction and stratified sampling

Abstract Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods and play an increasingly important role in the study and design of materials. However, MLIPs are only as accurate and robust as the data on which they are trained. Here, we present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolates more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with the M3GNet universal potential can be used instead of expensive ab initio MD to rapidly create a large configuration space for target systems. We combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. This work paves the way for robust high-throughput development of MLIPs across any compositional complexity.

Qi, Ji (ORCID:0000000158089931)↗

DOE OSTI2021

Deep graph representations embed network information for robust disease marker identification

We report that the accurate disease diagnosis and prognosis based on omics data rely on the effective identification of robust prognostic and diagnostic markers that reflect the states of the biological processes underlying the disease pathogenesis and progression. In this article, we present GCNCC, a Graph Convolutional Network-based approach for Clustering and Classification, that can identify highly effective and robust network-based disease markers. Based on a geometric deep learning framework, GCNCC learns deep network representations by integrating gene expression data with protein interaction data to identify highly reproducible markers with consistently accurate prediction performance across independent datasets possibly from different platforms. GCNCC identifies these markers by clustering the nodes in the protein interaction network based on latent similarity measures learned by the deep architecture of a graph convolutional network, followed by a supervised feature selection procedure that extracts clusters that are highly predictive of the disease state. By benchmarking GCNCC based on independent datasets from different diseases (psychiatric disorder and cancer) and different platforms (microarray and RNA-seq), we show that GCNCC outperforms other state-of-the-art methods in terms of accuracy and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗

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↗