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At least 793 records · Page 44

Photometric redshifts probability density estimation from recurrent neural networks in the DECam local volume exploration survey data release 2

Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this work, we address this challenge by exploring the estimation of Probability Density Functions (PDFs) for the photometric redshifts of galaxies across a vast area of 17,000 square degrees, encompassing objects with a median 5 σ point-source depth of g = 24.3, r = 23 . 9 , i = 23.5, and z = 22.8 mag. Our approach uses deep learning, specifically integrating a Recurrent Neural Network architecture with a Mixture Density Network, to leverage magnitudes and colors as input features for constructing photometric redshift PDFs across the whole DECam Local Volume Exploration (DELVE) survey sky footprint. Subsequently, we rigorously evaluate the reliability and robustness of our estimation methodology, gauging its performance against other well-established machine learning methods to ensure the quality of our redshift estimations. Our best results constrain photometric redshifts with the bias of − 0 . 0013 , a scatter of 0.0293, and an outlier fraction of 5.1%. These point estimates are accompanied by well-calibrated PDFs evaluated using diagnostic tools such as Probability Integral Transform and Odds distribution. We also address the problem of the accessibility of PDFs in terms of disk space storage and the time demand required to generate their corresponding parameters.We present a novel Autoencoder model that reduces the size of PDF parameter arrays to one-sixth of their original length, significantly decreasing the time required for PDF generation to one-eighth of the time needed when generating PDFs directly from the magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

Cost estimation model for advanced planetary programs, fourth edition

The development of the planetary program cost model is discussed. The Model was updated to incorporate cost data from the most recent US planetary flight projects and extensively revised to more accurately capture the information in the historical cost data base. This data base is comprised of the historical cost data for 13 unmanned lunar and planetary flight programs. The revision was made with a two fold objective: to increase the flexibility of the model in its ability to deal with the broad scope of scenarios under consideration for future missions, and to maintain and possibly improve upon the confidence in the model's capabilities with an expected accuracy of 20%. The Model development included a labor/cost proxy analysis, selection of the functional forms of the estimating relationships, and test statistics. An analysis of the Model is discussed and two sample applications of the cost model are presented.

Spadoni, D. J.↗

Is a data set distributed as a power law? A test, with application to gamma-ray burst brightnesses

We present a method to determine whether an observed sample of data is drawn from a parent distribution that is pure power law. The method starts from a class of statistics which have zero expectation value under the null hypothesis, H(sub 0), that the distribution is a pure power law: F(x) varies as x(exp -alpha). We study one simple member of the class, named the `bending statistic' B, in detail. It is most effective for detection a type of deviation from a power law where the power-law slope varies slowly and monotonically as a function of x. Our estimator of B has a distribution under H(sub 0) that depends only on the size of the sample, not on the parameters of the parent population, and is approximated well by a normal distribution even for modest sample sizes. The bending statistic can therefore be used to test a set of numbers is drawn from any power-law parent population. Since many measurable quantities in astrophysics have distriibutions that are approximately power laws, and since deviations from the ideal power law often provide interesting information about the object of study (e.g., a `bend' or `break' in a luminosity function, a line in an X- or gamma-ray spectrum), we believe that a test of this type will be useful in many different contexts. In the present paper, we apply our test to various subsamples of gamma-ray burst brightness from the first-year Burst and Transient Source Experiment (BATSE) catalog and show that we can only marginally detect the expected steepening of the log (N (greater than C(sub max))) - log (C(sub max)) distribution.

Wijers, Ralph A. M. J.↗

Data-Centric Approach to Capture Non-Polynomial Nonlinear Dynamics

We propose an analytical construction of observable functions in the extended dynamic mode decomposition (EDMD) algorithm. EDMD is a numerical method for approximating the spectral properties of the Koopman operator. The choice of observable functions is fundamental for applying EDMD to nonlinear problems arising in systems and control. Existing methods either start from a set of dictionary functions and look for the subset that best fits the underlying nonlinear dynamics or rely on machine learning algorithms to “learn” observable functions. Conversely, in this paper, we start from the dynamical system model and lift it through the Lie derivatives, rendering it into a polynomial form. This proposed transformation into a polynomial form is exact and provides an adequate set of observable functions. The strength of the proposed approach is its applicability to a broader class of nonlinear dynamical systems, particularly those with nonpolynomial functions and compositions thereof. Moreover, it retains the physical interpretability of the underlying dynamical system and can be readily integrated into existing numerical libraries. We demonstrate the proposed approach with an application to electric power systems. The modeled system consists of a single generator connected to an infinite bus, where nonlinear terms include sine and cosine functions. The results demonstrate the effectiveness of the proposed procedure in off-attractor nonlinear dynamics for estimation and prediction; the observable functions obtained from the proposed construction outperform methods that use dictionary functions comprising monomials or radial basis functions.

extended dynamic mode decomposition↗

Satellite-based monitoring of groundwater depletion in California’s Central Valley

Abstract Range change data, obtained from Synthetic Aperture Radar satellites, form the basis for estimates of aquifer volume change in California’s Central Valley. The estimation algorithm incorporates a function penalizing changes far from known well locations, linking the aquifer volume changes to agricultural, industrial, and municipal pumping within the Tulare basin. We show that the range changes are compatible with the hypothesis that the source of aquifer volume changes are variations in effective pressure around documented wells. Specifically, inclusion of the well distance penalty does not degrade the fit to the observations, inversions with and without it both give variance reductions of 99.6%. The patterns of aquifer volume change vary significantly from the drought year, between October 2015 and October 2016, to a wet year in 2017, and into 2018, a year with near average rainfall. The 2.3 million acre-feet of estimated volume reduction, a lower bound on the amount of water extracted from the basin between October 2015 and 2016, agrees with independent estimates of 1.8 and 2.3 million acre-feet. The aquifer volume reduction is also compatible with a loss of 3.1 km 3 (2.5 million acre-feet) in groundwater volume derived from Gravity Recovery and Climate Experiment (GRACE) satellite data.

47 OTHER INSTRUMENTATION↗

The local black hole mass function derived from the M{sub BH}–P and the M{sub BH}–n relations

We present a determination of the supermassive black hole (SMBH) mass function for early- and late-type galaxies in the nearby universe (z < 0.0057), established from a volume-limited sample consisting of a statistically complete collection of the brightest spiral galaxies in the southern hemisphere. The sample is defined by limiting luminosity (redshift-independent) distance, D {sub L} = 25.4 Mpc, and a limiting absolute B-band magnitude, M{sub B}=−19.12. These limits define a sample of 140 spiral, 30 elliptical (E), and 38 lenticular (S0) galaxies. We established the Sérsic index distribution for early-type (E/S0) galaxies in our sample. Davis et al. established the pitch angle distribution for their sample, which is identical to our late-type (spiral) galaxy sample. We then used the pitch angle and the Sérsic index distributions in order to estimate the SMBH mass function for our volume-limited sample. The observational simplicity of our approach relies on the empirical relation between the mass of the central SMBH and the Sérsic index for an early-type galaxy or the logarithmic spiral-arm pitch angle for a spiral galaxy. Our SMBH mass function agrees well at the high-mass end with previous values in the literature. At the low-mass end, although inconsistencies exist in previous works that still need to be resolved, our work is more in line with expectations based on modeling of black hole evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Amplitude Metrics for Field Retrieval with Hard-Edged and Uniformly Illuminated Apertures

In field retrieval, the amplitude and phase of the generalized pupil function for an optical system are estimated from multiple defocused measurements of the system point-spread function. A baseline field reconstruction algorithm optimizing a data consistency metric is described. Additionally, two metrics specifically designed to incorporate a priori knowledge about pupil amplitude for hard-edged and uniformly illuminated aperture systems are given. Experimental results demonstrate the benefit of using these amplitude metrics in addition to the baseline metric

Thurman, Samuel T.↗

Calculation of compressible nonadiabatic boundary layers in laminar, transitional and turbulent flow by the method of integral relations

A computer program was developed to do the calculations for two-dimensional or axisymmetric configurations from low speeds to hypersonic speeds with arbitrary streamwise pressure, temperature, and Mach number distributions. Options are provided for obtaining initial conditions either from experimental information or from a theoretical similarity solution. The transition region can be described either by an arbitrary distribution of intermittency or by a function based on Emmons' probability theory. Correlations were developed for use in estimating the parameters of the theoretical intermittency function. Correlations obtained from other sources are used for estimating the transition point. Comparisons were made between calculated and measured boundary layer quantities for laminar, transitional, and turbulent flows on flat plates, cones, cone flares, and a waisted body of revolution. Excellent agreement was obtained between the present theory and two other theories based on the method of finite differences. The intermittency required to reproduce some experimental heat transfer results in hypersonic flow was found to be quite different from the theoretical function. It is suggested that the simple probability theory of Emmons may not be valid for representing the intermittency of hypersonic transitional boundary layers and that the program could be useful as a tool for detailed study of the intermittency of the transition region.

Kuhn, G. D.↗

Density estimation via measure transport: Outlook for applications in the biological sciences

Abstract One among several advantages of measure transport methods is that they allow or a unified framework for processing and analysis of data distributed according to a wide class of probability measures. Within this context, we present results from computational studies aimed at assessing the potential of measure transport techniques, specifically, the use of triangular transport maps, as part of a workflow intended to support research in the biological sciences. Scenarios characterized by the availability of limited amount of sample data, which are common in domains such as radiation biology, are of particular interest. We find that when estimating a distribution density function given limited amount of sample data, adaptive transport maps are advantageous. In particular, statistics gathered from computing series of adaptive transport maps, trained on a series of randomly chosen subsets of the set of available data samples, leads to uncovering information hidden in the data. As a result, in the radiation biology application considered here, this approach provides a tool for generating hypotheses about gene relationships and their dynamics under radiation exposure.

gene expression data↗

Catalyst design to direct high-octane gasoline fuel properties for improved engine efficiency

The paraffin-to-olefin (P/O) ratio in gasoline fuel is a critical metric affecting fuel properties and engine efficiency. In the conversion of dimethyl ether (DME) to high-octane hydrocarbons over BEA zeolite catalysts, the P/O ratio can be controlled through catalyst design. Here, we report bimetallic catalysts that balance the net hydrogenation and dehydrogenation activity during DME homologation. The Cu-Zn/BEA catalyst exhibited greater relative dehydrogenation activity attributed to higher ionic site density, resulting in a lower P/O ratio (6.6) versus the benchmark Cu/BEA (9.4). The Cu-Ni/BEA catalyst exhibited increased hydrogenation due to reduced Ni species, resulting in a higher P/O ratio (19). The product fuel properties were estimated with an efficiency merit function and compared against finished gasolines and a typical alkylate blendstock. Merit values for the hydrocarbon product from all three BEA catalysts exceeded those of the comparison fuels (0–5.3), with the product from Cu-Zn/BEA exhibiting the highest merit value (9.7).

Catalyst design↗

The X-ray luminosity function of Abell clusters

X-ray sources identified with Abell clusters of galaxies in distance classes less than or equal to 3 give a quantitative estimate of the volume luminosity function for those clusters emitting between 10 to the 44th and 10 to the 45th power ergs/s in X-rays. At higher luminosities, tentative identifications with more distant clusters can be interpreted at least as an upper limit. This limit allows a smooth extension of the luminosity function, but with a fairly steep decrease in the range from 10 to the 45th to 10 to the 46th power ergs/s. No direct information is available for luminosities less than 10 to the 44th power ergs/s because current X-ray surveys are limited to nearby distances with very few Abell clusters; however, constraints at the low-luminosity end can be set by considering the total volume density of Abell clusters and the upper limit to the numbers of unidentified X-ray sources. The luminosity function must flatten or turn over below 10 to the 44th power ergs/s; therefore, counts of distant X-ray clusters to such a faint intrinsic luminosity can yield cosmological information.

Schwartz, D. A.↗

Derivation and Testing of Consumptive Water Use Fraction for Specialty Crops

The Crop Consumptive Use Fraction (CCUF) expresses beneficial water use in the form of seasonal evapotranspiration of applied water (ETAW), relative to total irrigation volume. The metric is an indicator of the efficiency of agricultural water use and is a recommended component for preparation of agricultural water management plans in California. An FAO-56 based web application has been developed to facilitate retrospective evaluation of ETAW, and hence CCUF, at field level. The current application is optimized for prevailing climate in four of the state’s main growing regions: San Joaquin Valley, Sacramento Valley, Central Coast, and North Coast. User inputs include crop type, soil texture, irrigation method, daily irrigation volume, daily rainfall, and seasonal start/stop dates to define the analysis period. Time series of fractional green canopy cover (Fc), based on Landsat and Sentinel-2 Earth-resource satellite observations, are imported from NASA’s Satellite Irrigation Management Support (SIMS) system. Grass reference evapotranspiration (ETo) time series are accessed from Spatial CIMIS (California Irrigation Management Information System). Daily crop height (h) is estimated as a simple function of typical maximum height for the given crop type (from FAO-56) and Fc. A vegetation density coefficient (Kd) is derived from Fc and h. Stomatal control factors during mid-and late-season are applied to tree and vine crops. Typical values for minimum daily relative humidity and mean daily windspeed, derived from historical CIMIS weather data, are used to correct for regional deviations from standard climate (defined as RHmin=45%, windspeed =2m/s). The resulting daily basal crop coefficient (Kcb) represents the ET of a well-watered crop with minimal soil evaporation, relative to ETo. A soil water balance sub-model for the top 0.1 m is used to calculate daily evaporation coefficients (Ke). A second sub-model applies to the root zone to calculate crop water stress coefficients (Ks) and effective precipitation (Pe), which is the fraction of rainfall that is available for crop use. Those coefficients are combined with Kcb and ETo to calculate daily ETc. ETAW is then derived as cumulative ETc less cumulative Pe. For verification purposes, sensor installations were used to measure seasonal ETc in commercial fields for several annual and perennial specialty crops by soil water balance and energy balance methods. Model estimates of seasonal ETc show mean absolute error of <10% compared to the ground measurements.

Derivation↗

Cross Inference of Throughput Profiles Using Micro Kernel Network Method

Dedicated network connections are being increasingly deployed in cloud, centralized and edge computing and data infrastructures, whose throughput profiles are critical indicators of the underlying data transfer performance. Due to the cost and disruptions to physical infrastructures, network emulators, such as Mininet, are often used to generate measurements needed to estimate throughput profiles, typically expressed as a function of the connection round trip time. The profiles estimated using measurements from such emulated networks are usually inaccurate for high bandwidth and high latency connections, since they do not accurately reflect the critical network transport dynamics mainly due to computing and memory constraints of the host. We present a machine learning (ML) method to estimate the throughput profiles using emulation measurements to closely match the testbed and production network profiles. In particular, we propose a micro Kernel Network (mKN) that provides baseline throughput measurements on the host running Mininet emulations, which are used to learn a regression map that converts them to the corresponding testbed measurement estimates. Once initially learned, this map is applied to measurements from subsequent network emulations on the same host. We present experimental measurements to illustrate this approach, and derive generalization equations for the proposed mKN-ML method. Using a four-site scenario emulation, we show the effectiveness of this method in providing accurate concave throughput profiles from inaccurate convex or non-smooth ones indicated by Mininet emulation.

Rao, Nageswara↗

Residual estimation for grid modification in wall-modeled large eddy simulation using unstructured high-order methods

Here, the accuracy and computational cost of a large eddy simulation are highly dependent on the computational grid. Building optimal grids manually from a priori knowledge is not feasible in most practical use cases; instead, solution-adaptive strategies can provide a robust and cost-efficient method to generate a grid with the desired accuracy. We adapt the residual estimation algorithm developed by Toosi and Larsson for Discontinuous Galerkin Spectral Elements Methods (DGSEM) to guide the grid-adaptation process. The core of the method is the computation of the estimated modeling residual using the polynomial basis functions used in DGSEM, and the averaging of the estimated residual over each element. The final method is assessed in multiple channel flow test cases and for the transonic flow over an airfoil, in both cases making use of mortar interfaces between elements with hanging nodes. The method is found to be robust and reliable, and to provide solutions on grids with significantly fewer elements at comparable accuracy compared to when using human-generated grids.

97 MATHEMATICS AND COMPUTING↗

Sequential Bayesian Methods for Analyzing Computer Models

Efficient analysis of computer models is essential for the validation and uncertainty quantification of those models. Surrogate models, and Gaussian processes in particular, are a common and powerful approach to analyzing computer models that treat computer models as a black-box function. Gaussian processes form a Bayesian model over a space of functions that gives a measure of uncertainty about the computer model output at unobserved locations and a framework for sequential sampling. This tutorial will show how to fit Gaussian processes on a series of test functions and apply sequential design techniques to estimate extrema, level sets, and reliabilities of those test functions.

97 MATHEMATICS AND COMPUTING↗

Documentation of the analysis of the benefits and costs of aeronautical research and technology models, volume 1

The analysis of the benefits and costs of aeronautical research and technology (ABC-ART) models are documented. These models were developed by NASA for use in analyzing the economic feasibility of applying advanced aeronautical technology to future civil aircraft. The methodology is composed of three major modules: fleet accounting module, airframe manufacturing module, and air carrier module. The fleet accounting module is used to estimate the number of new aircraft required as a function of time to meet demand. This estimation is based primarily upon the expected retirement age of existing aircraft and the expected change in revenue passenger miles demanded. Fuel consumption estimates are also generated by this module. The airframe manufacturer module is used to analyze the feasibility of the manufacturing the new aircraft demanded. The module includes logic for production scheduling and estimating manufacturing costs. For a series of aircraft selling prices, a cash flow analysis is performed and a rate of return on investment is calculated. The air carrier module provides a tool for analyzing the financial feasibility of an airline purchasing and operating the new aircraft. This module includes a methodology for computing the air carrier direct and indirect operating costs, performing a cash flow analysis, and estimating the internal rate of return on investment for a set of aircraft purchase prices.

Bobick, J. C.↗

Encapsulated diffusion of sulphur into InP

This talk outlines a simple process for the fabrication of n(+)-p solar cells in indium phosphide. Large area cells (greater than 0.25 sq cm) have been made by this process, with a photovoltaic conversion efficiency of 15.21 percent under AM0 conditions of illumination. An ideality factor of 1.1 and a saturation current density of 8 x 10 to the minus 15th power A/sq cm have been observed for these cells. The technique for cell fabrication involves the diffusion of sulfur into InP by an open tube process, and gives highly reproducible results from run to run. A vacuum-deposited layer of gallium sulphide (Ga2S3) was used as the source for sulfur diffusion, with a chemically vapor deposited SiO2 cap layer to prevent decomposition of the InP surface during heat treatment. Diffusions were carried out in a flowing nitrogen ambient at 585 to 708 C, and characterized by their surface carrier concentration and the diffusion constant. The diffusion profile for sulfur in InP is estimated to be of the complementary error function type. The activation energy of the diffusion was estimated to be 1.94 eV. The technique described here is ideally suited for the fabrication of shallow n(+)-p junctions in InP, and has been used for space-borne solar cells.

Parat, K. K.↗

Ionizing Radiation Environment on the International Space Station: Performance vs. Expectations for Avionics and Material

The role of structural shielding mass in the design, verification, and in-flight performance of International Space Station (ISS), in both the natural and induced orbital ionizing radiation (IR) environments, is reported. Detailed consideration of the effects of both the natural and induced ionizing radiation environment during ISS design, development, and flight operations has produced a safe, efficient manned space platform that is largely immune to deleterious effects of the LEO ionizing radiation environment. The assumption of a small shielding mass for purposes of design and verification has been shown to be a valid worst-case approximation approach to design for reliability, though predicted dependences of single event effect (SEE) effects on latitude, longitude, SEP events, and spacecraft structural shielding mass are not observed. The Figure of Merit (FOM) method over predicts the rate for median shielding masses of about 10g/cm(exp 2) by only a factor of 3, while the Scott Effective Flux Approach (SEFA) method overestimated by about one order of magnitude as expected. The Integral Rectangular Parallelepiped (IRPP), SEFA, and FOM methods for estimating on-orbit (Single Event Upsets) SEU rates all utilize some version of the CREME-96 treatment of energetic particle interaction with structural shielding, which has been shown to underestimate the production of secondary particles in heavily shielded manned spacecraft. The need for more work directed to development of a practical understanding of secondary particle production in massive structural shielding for SEE design and verification is indicated. In contrast, total dose estimates using CAD based shielding mass distributions functions and the Shieldose Code provided a reasonable accurate estimate of accumulated dose in Grays internal to the ISS pressurized elements, albeit as a result of using worst-on-worst case assumptions (500 km altitude x 2) that compensate for ignoring both GCR and secondary particle production in massive structural shielding.

Koontz, Steven L.↗