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Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

Since solids are only sometimes seen en masse in a pure bulk form, and for liquids other than water almost never, a capability to model reflectance spectra from analytes deposited on various substrates would be highly advantageous. If available, the real, n ( ν ) , and imaginary, k ( ν ) , components of the complex refractive index, n n + i k , can be used to simulate infrared spectra, accounting for reflection, refraction, and absorption phenomena as a function of wavelength. We focus on using the Pacific Northwest National Laboratory (PNNL) derived n / k vectors for solid and liquid analytes deposited as thin layers on different types of substrates including conductors, such as aluminum, and inorganic dielectrics, such as glass. The model is an adaptation of the Monte Carlo ray trace modeling program, TracePro, extended through the use of its macrolanguage. The model is tested using thin films of organic liquids including silicone oil and no. 2 diesel fuel, as well as organic solids such as caffeine and acetaminophen on aluminum and glass. The predicted spectra for the solid films were compared to experimental hemispherical reflectance data measured using a Fourier transform spectrometer with an integrating sphere. The thickness of the calculated layer is a parameter for predicting the (transflectance) spectra and is obtained using the areal density measured from gravimetric methods to generate the thin-layer samples. Comparison of the calculated spectra with experimental hemispherical reflectance data shows excellent agreement, indicating promise for the use of measured n / k data to synthesize reference spectral data. In particular, accounting for the inhomogeneity of the deposits greatly improved the match with experimental data. Finally, the theoretical modeling shows that for thicker layers (ca. 20 to 100 μm) of typical organics possessing moderately strong k values, the longwave infrared features are often saturated and better spectral contrast is obtained from the overtone/combination bands in the shortwave infrared.

42 ENGINEERING↗

Accelerated fission rate irradiation design, pre-irradiation characterization, and adaptation of conventional PIE methods for U-10Mo and U-17Mo

Metallic U alloys have high U density and thermal conductivity and thus have been explored since the beginning of nuclear power research. Alloys of U with modest amounts of Mo, such as U-10 wt % Mo (U-10Mo), are of particular interest because the γ-U crystal structure in this alloying addition shows prolonged stability in reactor service. Historically, radiation data on U-10Mo fuels were collected in Na fast reactors or lower temperature research reactor conditions, but little is known about irradiation behavior, particularly swelling and creep, at irradiation temperatures between 250 and 500°C. This work discusses the methodology and pre-irradiation characterization results from a U-Mo irradiation campaign performed in the High Flux Isotope Reactor at Oak Ridge National Laboratory. U-10Mo and U-17Mo samples irradiations are being completed at temperatures ranging from 250 to 500°C to three targeted fission densities between 2 × 10 20 and 1.5 × 10 21 fissions per cubic centimeter. Swelling measurement of the specimen sizes studied here required development and assessment of new methods for volume determination before and after irradiation. Laser profilometry and X-ray computation tomography (XCT) were used to provide preirradiation characterization of samples to determine the error and applicability of each to determine swelling following irradiation. These outcomes are contextualized through use of BISON simulations performed to assess the predicted expansion of U-Mo fuels subjected to the irradiation conditions of this work. Use of existing BISON fuel performance models predicted a maximum of 7% swelling under the irradiation conditions of this study. Pre-irradiation characterization revealed the as-cast U-Mo fuel samples were uniformly large-grained fully cubic U crystals with small U-C/N bearing precipitates and pores distributed throughout. Samples were found to contain a bulk porosity between .4 and 3% because of the casting process. Local porosity in areas far from large, interconnected pores was found by Slice-and-View to be under .2%. Nanometer-sized precipitates rich in C and N were identified in all samples, likely because of impurities during the fabrication process. Dendritic bands were also observed throughout the samples. These bands were characterized by variable Mo content that deviated from the overall Mo content by 2–3 wt %. No other microstructural features were correlated to these bands. Mechanical properties were found to be slightly strengthened compared to literature reports of bulk U-Mo fuels due to the nano-scale precipitates throughout the sample.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Patient-Specific Bacteroides Genome Variants in Pouchitis

Here, a 2-year longitudinal microbiome study of 22 patients who underwent colectomy with an ileal pouch anal anastomosis detected significant increases in distinct populations of Bacteroides during 9 of 11 patient visits that coincided with inflammation (pouchitis). Oligotyping and metagenomic short-read annotation identified Bacteroides populations that occurred in early samples, bloomed during inflammation, and reappeared after antibiotic treatment. Targeted cultivation of Bacteroides isolates from the same individual at multiple time points and from several patients detected subtle genomic changes, including the identification of rapidly evolving genomic elements that differentiate isogenic strains of Bacteroides fragilis from the mucosa versus lumen. Each patient harbored Bacteroides spp. that are closely related to commonly occurring clinical isolates, including Bacteroides ovatus , B. thetaiotaomicron , B. vulgatus , and B. fragilis , which contained unique loci in different patients for synthesis of capsular polysaccharides. The presence of unique Bacteroides capsular polysaccharide loci within different hosts and between the lumen and mucosa may represent adaptations to stimulate, suppress, and evade host-specific immune responses at different microsites of the ileal pouch.

59 BASIC BIOLOGICAL SCIENCES↗

Proactive Defense for Evolving Cyber Threats

There is great interest to develop proactive methods of cyber defense, in which future attack strategies are anticipated and these insights are incorporated into defense designs; however, little has been done to place this ambitious objective on a sound scientific foundation. Indeed, even fundamental issues associated with how the “arms race” between attackers and defenders actually leads to predictability in attacker activity, or how to effectively and scalably detect this predictability in the relational/temporal data streams generated by attacker/defender adaptation, haven’t been resolved. This LDRD project addressed many of these challenges and the results are briefly summarized here. We have characterized the predictability of attacker/defender coevolution and have leveraged our findings to create a framework for designing proactive defenses for large (organizational) networks. More specifically, this project applied rigorous predictability-based analytics to two central and complementary aspects of the network defense problem – attack strategies of the adversaries and vulnerabilities of the defenders’ systems – and used the results to develop a scientifically-grounded, practically-implementable methodology for designing proactive cyber defense systems. Briefly, predictive analysis of attack strategies involved first conducting predictability assessments to characterize attacker adaptation patterns in given domains, and then used these patterns to “train” adaptive defense systems capable of providing robust performance against both current and (near) future threats. The problem of identifying and prioritizing defender system vulnerabilities was addressed using statistical and machine learning to analyze a broad range of data (e.g., cyber, social media) on recently detected system vulnerabilities to “learn” classifiers that predict how likely it is that, and how soon, new vulnerabilities will be exploited. A variety of cyber threat case studies were developed and investigated throughout the project, one selected from the cyber security research community and one that is more comprehensive and of higher priority to SNL and to external national security partners. A sample of research results and application of this methodology are included in this report (as a series of peer-reviewed publications). For ease of reference the title and SAND number are included below.

97 MATHEMATICS AND COMPUTING↗

miniGMG

miniGMG is a compact geometric multigrid (MG benchmark designed to proxy the performance characteristics of the solves found in adaptive mesh refinement multigrid (AMR MG) applications. It solves the equation a*alpha*u - b div beta grad u = f on a large cubical domain using cell-centered values and periodic boundaries. a and b are scalar constants, alpha and beta are space varying constants, f is the right hand side, and u is the solution. The cubical domain is divided into cubical subdomains which are distributed across the supercomputer. The righthand side f is generated from a continuous function for u. Thus, one can solve this linear system of equations and verify the error properties of the discrete solution u by comparing to a sampling of the continuous u. miniGMG implements both v- and f- cycles, as well as two constant coeffficient discretications of the equation above (one 27pt 2nd order, and one 13pt 4th order). In both cases, the (embedded) v-cycles are truncated when a subdomain reaces 4^3, 2^3, or 1^3 cells (a u-cycle). The multigrd solver then swtiches to one of seven coarse grid (bottom) solves. relaxation, BiCGStab, CABiCGStab, TelescopingCABiCGStab, CG, or CACG. The code exploits two forms of communication-avoiding. The first is exemplified by the referenced SC'12 paper in which DRAM data movment is avoided when smoothing. The second, described in the IPDPS'14 paper avoids collectives in a bottom solve (the CA bottom solves). There are a number of implementations of the operators for both CPUs and NVIDIA GPUs. The CPUs have been optimized to exploit a wavefront approach to communication-avoiding. The GPU versions include a number of optimized and tunable implementations. The code has been demonstrated to scale to 46K nodes on the BGQ Mira (750K cores), 9K nodes on Edison (111K cores), and 14K GPUs on Titan (37M cuda cores). It thus acts as a scalable testbed for a wide range of computer science and applied math research. Nominally, one invokes the benchmark as ./run b x y z alpha beta gamma Each subdomain is (2^b)^3 cells Each MPI process receives a x-by-y-by-z collection of subdomains. There are alpha*beta*gamma total MPI processes For correctness (a cubical domain), *alpha==y*beta==z*gamma.

Williams, Sameul↗

In situ multi-tier auto-ignition detection applied to dual-fuel combustion simulations

Here we use an anomaly detection methodology that is centered on analyzing fourth-order joint moments (co-kurtosis), particularly focusing on its application in auto-ignition of combustion problems with large numbers of species. Unsupervised anomaly detection is challenging to generalize across problem types and domains. A recent technique, centered on analyzing information in the fourth-order joint moment co-kurtosis, has shown promise, especially for high-dimensional scientific data. In this work we present developments to the co-kurtosis based anomaly detection method needed to make it effective and scalable for large-scale distributed scientific data, such as those generated by massively parallel simulations. An in situ co-kurtosis algorithm is employed as the anomaly detection method for identifying ignition kernels in simulations of turbulent combustion. Here, we extend an existing methodology which identifies regions of the domain where anomalies are present, and add another tier of anomaly detection where the individual samples contributing to the anomaly are identified. We apply this algorithm on-the-fly to a variety of turbulent reacting flow problems and compare it to the widely used (but significantly more expensive) chemical explosive mode analysis (CEMA). We demonstrate the ability of the method to detect and identify the onset of low and high temperature ignition which can be used for computational steering, as chemical and combustion anomalies occur intermittently at spatio-temporal locations unknown a priori. Finally, we apply our lightweight in situ algorithm to an exascale high-fidelity simulation with a total of 2.4 Trillion degrees of freedom, performed using an adaptive mesh refinement solver. Furthermore, through a scalability analysis, we show that the relative computational cost of this in-situ anomaly detection algorithm compared to an iteration of the reacting flow solver is negligible.

97 MATHEMATICS AND COMPUTING↗

Acoustic inverse scattering via Helmholtz operator factorization and optimization

We present a joint acoustic/seismic inverse scattering and finite-frequency (reflection) tomography program, formulated as a coupled set of optimization problems, in terms of inhomogeneous Helmholtz equations. We use a higher order finite difference scheme for these Helmholtz equations to guarantee sufficient accuracy. We adapt a structured approximate direct solver for the relevant systems of algebraic equations, which addresses storage requirements through compression, to yield a complexity for computing the gradients or images in the optimization problems that consists of two parts, viz., the cost for all the matrix factorizations which is roughly O(rN) (for example O(rNlogN) when d = 2) times the number of frequencies, and the cost for all solutions by substitution which is roughly O(N) (for example O(Nlog(rlogN)) when d = 2) times the number of frequencies times the number of sources (events), where N = n{sup d} if n is the number of grid samples in any direction, and r is a parameter depending on the preset accuracy and the problem at hand. With this complexity, the multi-frequency approach to inverse scattering and finite-frequency tomography becomes computationally feasible with large data sets, in dimensions d = 2 and 3.

97 MATHEMATICS AND COMPUTING↗

A method to evaluate dose errors introduced by dose mapping processes for mass conserving deformations

Purpose: To present a method to evaluate the dose mapping error introduced by the dose mapping process. In addition, apply the method to evaluate the dose mapping error introduced by the 4D dose calculation process implemented in a research version of commercial treatment planning system for a patient case. Methods: The average dose accumulated in a finite volume should be unchanged when the dose delivered to one anatomic instance of that volume is mapped to a different anatomic instance--provided that the tissue deformation between the anatomic instances is mass conserving. The average dose to a finite volume on image S is defined as d{sub S}=e{sub s}/m{sub S}, where e{sub S} is the energy deposited in the mass m{sub S} contained in the volume. Since mass and energy should be conserved, when d{sub S} is mapped to an image R(d{sub S{yields}R}=d{sub R}), the mean dose mapping error is defined as {Delta}d{sub m}=|d{sub R}-d{sub S}|=|e{sub R}/m{sub R}-e{sub S}/m{sub S}|, where the e{sub R} and e{sub S} are integral doses (energy deposited), and m{sub R} and m{sub S} are the masses within the region of interest (ROI) on image R and the corresponding ROI on image S, where R and S are the two anatomic instances from the same patient. Alternatively, application of simple differential propagation yields the differential dose mapping error, {Delta}d{sub d}=|({partial_derivative}d/{partial_derivative}e)*{Delta}e+({partial_derivative}d/{partial_derivative}m)*{Delta}m|=|((e{sub S}-e{sub R})/m{sub R})-((m{sub S}-m{sub R})/m{sub R}{sup 2})*e{sub R}|={alpha}|d{sub R}-d{sub S}| with {alpha}=m{sub S}/m{sub R}. A 4D treatment plan on a ten-phase 4D-CT lung patient is used to demonstrate the dose mapping error evaluations for a patient case, in which the accumulated dose, D{sub R}={Sigma}{sub S=0}{sup 9}d{sub S{yields}R}, and associated error values ({Delta}D{sub m} and {Delta}D{sub d}) are calculated for a uniformly spaced set of ROIs. Results: For the single sample patient dose distribution, the average accumulated differential dose mapping error is 4.3%, the average absolute differential dose mapping error is 10.8%, and the average accumulated mean dose mapping error is 5.0%. Accumulated differential dose mapping errors within the gross tumor volume (GTV) and planning target volume (PTV) are lower, 0.73% and 2.33%, respectively. Conclusions: A method has been presented to evaluate the dose mapping error introduced by the dose mapping process. This method has been applied to evaluate the 4D dose calculation process implemented in a commercial treatment planning system. The method could potentially be developed as a fully-automatic QA method in image guided adaptive radiation therapy (IGART).

61 RADIATION PROTECTION AND DOSIMETRY↗

P finder: genomic and metagenomic annotation of RNase P RNA gene (rnpB)

Abstract Background The rnpB gene encodes for an essential catalytic RNA (RNase P). Like other essential RNAs, RNase P’s sequence is highly variable. However, unlike other essential RNAs (i.e. tRNA, 16 S, 6 S,...) its structure is also variable with at least 5 distinct structure types observed in prokaryotes. This structural variability makes it labor intensive and challenging to create and maintain covariance models for the detection of RNase P RNA in genomic and metagenomic sequences. The lack of a facile and rapid annotation algorithm has led to the rnpB gene being the most grossly under annotated essential gene in completed prokaryotic genomes with only a 24% annotation rate. Here we describe the coupling of the largest RNase P RNA database with the local alignment scoring algorithm to create the most sensitive and rapid prokaryote rnpB gene identification and annotation algorithm to date. Results Of the 2772 completed microbial genomes downloaded from GenBank only 665 genomes had an annotated rnpB gene. We applied P Finder to these genomes and were able to identify 2733 or nearly 99% of the 2772 microbial genomes examined. From these results four new rnpB genes that encode the minimal T-type P RNase P RNAs were identified computationally for the first time. In addition, only the second C-type RNase P RNA was identified in Sphaerobacter thermophilus . Of special note, no RNase P RNAs were detected in several obligate endosymbionts of sap sucking insects suggesting a novel evolutionary adaptation. Conclusions The coupling of the largest RNase P RNA database and associated structure class identification with the P Finder algorithm is both sensitive and rapid, yielding high quality results to aid researchers annotating either genomic or metagenomic data. It is the only algorithm to date that can identify challenging RNAse P classes such as C-type and the minimal T-type RNase P RNAs. P Finder is written in C# and has a user-friendly GUI that can run on multiple 64-bit windows platforms (Windows Vista/7/8/10). P Finder is free available for download at https://github.com/JChristopherEllis/P-Finder as well as a small sample RNase P RNA file for testing.

59 BASIC BIOLOGICAL SCIENCES↗

Rapid Response of Eastern Mediterranean Deep Sea Microbial Communities to Oil

Deep marine oil spills like the Deepwater Horizon (DWH) in the Gulf of Mexico have the potential to drastically impact marine systems. Crude oil contamination in marine systems remains a concern, especially for countries around the Mediterranean Sea with off shore oil production. The goal of this study was to investigate the response of indigenous microbial communities to crude oil in the deep Eastern Mediterranean Sea (E. Med.) water column and to minimize potential bias associated with storage and shifts in microbial community structure from sample storage. 16S rRNA amplicon sequencing was combined with GeoChip metagenomic analysis to monitor the microbial community changes to the crude oil and dispersant in on-ship microcosms set up immediately after water collection. After 3 days of incubation at 14 °C, the microbial communities from two different water depths: 824 m and 1210 m became dominated by well-known oil degrading bacteria. The archaeal population and the overall microbial community diversity drastically decreased. Similarly, GeoChip metagenomic analysis revealed a tremendous enrichment of genes related to oil biodegradation, which was consistent with the results from the DWH oil spill. Furthermore, these results highlight a rapid microbial adaption to oil contamination in the deep E. Med., and indicate strong oil biodegradation potential.

54 ENVIRONMENTAL SCIENCES↗

Synthesis and magnetic properties of Co-Ti-Bi codoped M-type barium ferrite

The effects of Co{sup 2+}, Ti{sup 4+}, and Bi{sup 3+} substitution on the microstructures and properties of low-temperature fired M-type barium hexaferrites have been studied in order to adapt the development of low-temperature cofired ferrites technology and produce gyromagnetic devices with a multilayer process. It is found that Bi{sup 3+} ions can enter into the 2a sublattice and consequently enhance the grain growth and densification due to the activation of the lattice, which in turn first lead to an increase and then a decrease of M{sub s}. The substitution of Bi{sup 3+} ions is beneficial to forming the M phase and lowers the sintering temperature to about 900 deg. C, which is ideal for cofiring with silver paste. Scanning electron microscope and x-ray diffraction analysis have shown that the samples have excellent crystalline grains with a uniform size about 1-2 {mu}m. Moreover, nonmagnetic Ti{sup 4+} ions prefer to enter the 4f{sub VI} octahedral sites, giving rise to the weakening of the strong 12k-4f{sub VI} superexchange path and thus the isotropic exchange energy approaches the other second-order terms on the magnetic Hamiltonian, such as the antisymmetric interaction or even the magnetocrystalline anisotropy. With increasing the substitution content, some Co{sup 2+} ions, which locate in octahedral 12k sites, give a strong planar contribution to the anisotropy. Therefore, M{sub s} and H{sub c} decrease with the Co-Ti-substitution.

36 MATERIALS SCIENCE↗

STELLAR VELOCITY DISPERSION MEASUREMENTS IN HIGH-LUMINOSITY QUASAR HOSTS AND IMPLICATIONS FOR THE AGN BLACK HOLE MASS SCALE

We present new stellar velocity dispersion measurements for four luminous quasars with the Near-Infrared Integral Field Spectrometer instrument and the ALTAIR laser guide star adaptive optics system on the Gemini North 8 m telescope. Stellar velocity dispersion measurements and measurements of the supermassive black hole (BH) masses in luminous quasars are necessary to investigate the coevolution of BHs and galaxies, trace the details of accretion, and probe the nature of feedback. We find that higher-luminosity quasars with higher-mass BHs are not offset with respect to the M{sub BH}-{sigma}{sub *} relation exhibited by lower-luminosity active galactic nuclei (AGNs) with lower-mass BHs, nor do we see correlations with galaxy morphology. As part of this analysis, we have recalculated the virial products for the entire sample of reverberation-mapped AGNs and used these data to redetermine the mean virial factor (f) that places the reverberation data on the quiescent M{sub BH}-{sigma}{sub *} relation. With our updated measurements and new additions to the AGN sample, we obtain (f) = 4.31 {+-} 1.05, which is slightly lower than, but consistent with, most previous determinations.

79 ASTRONOMY AND ASTROPHYSICS↗

A CENSUS OF ROTATION AND VARIABILITY IN L1495: A UNIFORM ANALYSIS OF TRANS-ATLANTIC EXOPLANET SURVEY LIGHT CURVES FOR PRE-MAIN-SEQUENCE STARS IN TAURUS

We analyze light curves obtained by the Trans-atlantic Exoplanet Survey (TrES) for a field centered on the L1495 dark cloud in Taurus. The Spitzer Taurus Legacy Survey catalog identifies 179 bona fide Taurus members within the TrES field; 48 of the known Taurus members are detected by TrES, as well as 26 candidate members identified by the Spitzer Legacy team. We quantify the variability of each star in our sample using the ratio of the standard deviation of the original light curve ({sigma}{sub orig.}) to the standard deviation of a light curve that has been smoothed by 9 or 1001 epochs ({sigma}{sub 9} and {sigma}{sub 1001}, respectively). Known Taurus members typically demonstrate ({sigma}{sub orig.}/{sigma}{sub 9}) < 2.0, and ({sigma}{sub orig.}/{sigma}{sub 1001}) < 5, while field stars reveal ({sigma}{sub orig.}/{sigma}{sub 9}) {approx} 3.0 and ({sigma}{sub orig.}/{sigma}{sub 1001}) {approx} 10, as expected for light curves dominated by unstructured white noise. Of the 74 Taurus members/candidates with TrES light curves, we detect significant variability in 49 sources. Adapting a quantitative metric originally developed to assess the reliability of transit detections, we measure the amount of red and white noise in each light curve and identify 18 known or candidate Taurus members with highly significant period measurements. These appear to be the first periods measured for four of these sources (HD 282276, CX Tau, FP Tau, TrES J042423+265008), and in two other cases, the first non-aliased periods (LkCa 21 and DK Tau AB). For the remainder, the TrES measurements typically agree very well ({delta}P < 1%) with previously reported values. Including periods measured at lower confidence for 15 additional sources, we report periods for 11 objects where no previous periods were found, including 8 confirmed Taurus members. We also identify 10 of the 26 candidate Taurus members that demonstrate variability levels consistent with being bona fide T Tauri stars. A Kolomgorov-Smirnov (K-S) test confirms that these new periods confirm the distinction between the rotation period distributions of stars with and without circumstellar disks, with only a 10% probability of the two populations sharing the same parent period distribution. K-S tests do suggest, however, that the updated Taurus period distribution now more closely resembles those measured in other young star-forming clusters (i.e., NGC 2264, NGC 6530, and the ONC). This improved agreement may reflect the exclusion of long rotation periods which are detected in Taurus at lower significance, and which may be beyond the limits of detectability in more distant star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗

High-order parabolic beam approximation for aero-optics

The parabolic beam equations are solved using high-order compact differences for the Laplacians and Runge-Kutta integration along the beam path. The solution method is verified by comparison to analytical solutions for apertured beams and both constant and complex index of refraction. An adaptive 4th-order Runge-Kutta using an embedded 2nd-order method is presented that has demonstrated itself to be very robust. For apertured beams, the results show that the method fails to capture near aperture effects due to a violation of the paraxial approximation in that region. Initial results indicate that the problem appears to be correctable by successive approximations. A preliminary assessment of the effect of turbulent scales is undertaken using high-order Lagrangian interpolation. The results show that while high fidelity methods are necessary to accurately capture the large scale flow structure, the method may not require the same level of fidelity in sampling the density for the index of refraction. The solution is used to calculate a phase difference that is directly compared with that commonly calculated via the optical path difference. Propagation through a supersonic boundary layer shows that for longer wavelengths, the traditional method to calculate the optical path is less accurate than for shorter wavelengths. While unlikely to supplant more traditional methods for most aero-optics applications, the current method can be used to give a quantitative assessment of the other methods as well as being amenable to the addition of more physics.

97 MATHEMATICS AND COMPUTING↗

CONSTRAINTS ON THE ASSEMBLY AND DYNAMICS OF GALAXIES. II. PROPERTIES OF KILOPARSEC-SCALE CLUMPS IN REST-FRAME OPTICAL EMISSION OF z {approx} 2 STAR-FORMING GALAXIES

We study the properties of luminous stellar 'clumps' identified in deep, high-resolution Hubble Space Telescope NIC2/F160W imaging at 1.6 {mu}m of six z {approx} 2 star-forming galaxies with existing near-infrared integral field spectroscopy from SINFONI at the Very Large Telescope. Individual clumps contribute {approx}0.5%-15% of the galaxy-integrated rest-frame {approx}5000 A emission, with median of {approx}2%; the total contribution of clump light ranges from 10% to 25%. The median intrinsic clump size and stellar mass are {approx}1 kpc and {approx}10{sup 9} M{sub sun}, in the ranges for clumps identified in rest-UV or line emission in other studies. The clump sizes and masses in the subset of disks are broadly consistent with expectations for clump formation through gravitational instabilities in gas-rich, turbulent disks given the host galaxies' global properties. By combining the NIC2 data with Advanced Camera for Surveys (ACS)/F814W imaging available for one source, and adaptive-optics-assisted SINFONI H{alpha} data for another, we infer modest color, M/L, and stellar age variations within each galaxy. In these two objects, sets of clumps identified at different wavelengths do not fully overlap; NIC2-identified clumps tend to be redder/older than ACS- or H{alpha}-identified clumps without rest-frame optical counterparts. There is evidence for a systematic trend of older ages at smaller galactocentric radii among the clumps, consistent with scenarios where inward migration of clumps transports material toward the central regions. From constraints on a bulge-like component at radii {approx}< 1-3 kpc, none of the five disks in our sample appears to contain a compact massive stellar core, and we do not discern a trend of bulge stellar mass fraction with stellar age of the galaxy. Further observations are necessary to probe the buildup of stellar bulges and the role of clumps in this process.

79 ASTRONOMY AND ASTROPHYSICS↗

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗

Kent Island Boundary Layer Field Campaign Report

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations about the impacts of climate change and associated mitigation and adaptation measures. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) was conducted to study the interactions among the earth’s surface, the atmospheric boundary layer (ABL), aerosols, atmospheric composition, clouds, radiation, and precipitation at each experimental site, and to examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. In this activity we performed weekly soundings, alternating between day and night from Kent Island, to get low-frequency, long-term observations of ABL/lower tropospheric thermodynamic structure. However, during the CoURAGE intensive operational period (IOP), we performed high-frequency sampling (2x/day), at times coinciding with CoURAGE IOP soundings at the main site. The short-term, high-frequency sounding information that was launched at 12Z and 18Z was to complement the longer-term data set.

54 ENVIRONMENTAL SCIENCES↗