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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Optimization of the Coupled Cluster Implementation in NWChem on Petascale Parallel Architectures

Coupled cluster singles and doubles (CCSD) algorithm has been optimized in NWChem software package. This modification alleviated the communication bottleneck and provided from 2- to 5-fold speedup in the CCSD iteration time depending on the problem size and available memory. Sustained 0.60 petaflop/sec performance on CCSD(T) calculation has been obtained on NCSA Blue Waters. This number included all stages of the calculation from initialization till termination, iterative computation of single and double excitations, and perturbative accounting for triple excitations. In the section of perturbative triples alone, the computation maintained 1.18 petaflop/sec performance level. CCSD computations have been performed on Guanine-Cytosine deoxydinucleotide monophosphate (GC-dDMP) to probe the conformational energy difference in DNA single strand in A- and B-conformations. The computation revealed significant discrepancy between CCSD and classical force fields in prediction of relative energy of A- and B-conformations of GC-dDMP.

calculations↗
DOE OSTI2017

Tensor-structured coupled cluster theory

We derive and implement a new way of solving coupled cluster equations with lower computational scaling. Our method is based on the decomposition of both amplitudes and two electron integrals, using a combination of tensor hypercontraction and canonical polyadic decomposition. While the original theory scales as O ( N 6 ) with respect to the number of basis functions, we demonstrate numerically that we achieve sub-millihartree difference from the original theory with O ( N 4 ) scaling. This is accomplished by solving directly for the factors that decompose the cluster operator. Here, the proposed scheme is quite general and can be easily extended to other many-body methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Ruprecht 147: A Paradigm of Dissolving Star Cluster

We employed recent Gaia/DR2 data to investigate the dynamical status of the nearby (300 pc), old (2.5 Gyr) open cluster Ruprecht 147. We found prominent leading and trailing tails of stars along the cluster orbit, which demonstrates that Ruprecht 147 is losing stars at fast pace. Star counts indicate the cluster has a core radius of 33.3 arcmin and a tidal radius of 137.5 arcmin. The cluster also possesses an extended corona, which cannot be reproduced by a simple King model. We computed the present-day cluster mass using its luminosity and mass function, and derived an estimate of 234 ± 52 M {sub ⊙}. We also estimated the cluster original mass using available recipes extracted from N-body simulations obtaining a mass at birth of 50,000 ± 6500 M {sub ⊙}. Therefore dynamical mass loss, mostly caused by tidal interaction with the Milky Way, reduced the cluster mass by about 99%. We then conclude that Ruprecht 147 is rapidly dissolving into the general Galactic disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Gaussian mixture models as automated particle classifiers for fast neutron detectors

Pulse shape discrimination (PSD) is the task of classifying electronic pulse shapes for different particle types such as gamma rays and fast neutrons interacting in scintillators and read out by photo sensitive detectors. This field has been limited in its adoption of techniques found in the statistical learning community. Methods initially employed in the 1960s for analog electronic circuitry persist in the current PSD literature describing operations performed on digitized pulses, which are amenable to statistical rigor. Despite vast amounts of data collected at low energy levels, traditional PSD methods are unable to discriminate particles below a certain threshold. As such, in this work, Gaussian mixture models (GMMs) are used as a clustering technique for fast neutron detection in the absence of labeled data. GMMs yield improvements spanning the energy spectrum in a desirably efficient, unsupervised fashion. An extension, the Dirichlet Process GMM, provides further flexibility and classification improvement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Charliecloud

Charliecloud is a set of scripts to let users run a virtual cluster of virtual machines (VMs) on a desktop or supercomputer. Key functions include: 1. Creating (typically by installing an operating system from vendor media) and updating VM images; 2. Running a single VM; 3. Running multiple VMs in a virtual cluster. The virtual machines can talk to one another over the network and (in some cases) the outside world. This is accomplished by calling external programs such as QEMU and the Virtual Distributed Ethernet (VDE) suite. The goal is to let users have a virtual cluster containing nodes where they have privileged access, while isolating that privilege within the virtual cluster so it cannot affect the physical compute resources. Host configuration enforces security; this is not included in Charliecloud, though security guidelines are included in its documentation and Charliecloud is designed to facilitate such configuration. Charliecloud manages passing information from host computers into and out of the virtual machines, such as parameters of the virtual cluster, input data specified by the user, output data from virtual compute jobs, VM console display, and network connections (e.g., SSH or X11). Parameters for the virtual cluster (number of VMs, RAM and disk per VM, etc.) are specified by the user or gathered from the environment (e.g., SLURM environment variables). Example job scripts are included. These include computation examples (such as a "hello world" MPI job) as well as performance tests. They also include a security test script to verify that the virtual cluster is appropriately sandboxed. Tests include: 1. Pinging hosts inside and outside the virtual cluster to explore connectivity; 2. Port scans (again inside and outside) to see what services are available; 3. Sniffing tests to see what traffic is visible to running VMs; 4. IP address spoofing to test network functionality in this case; 5. File access tests to make sure host access permissions are enforced. This test script is not a comprehensive scanner and does not test for specific vulnerabilities. Importantly, no information about physical hosts or network topology is included in this script (or any of Charliecloud); while part of a sensible test, such information is specified by the user when the test is run. That is, one cannot learn anything about the LANL network or computing infrastructure by examining Charliecloud code.

Priedhorsky, Reid↗
DOE OSTI2015

Charliecloud

Charliecloud is a set of scripts to let users run a virtual cluster of virtual machines (VMs) on a desktop or supercomputer. Key functions include: 1. Creating (typically by installing an operating system from vendor media) and updating VM images; 2. Running a single VM; 3. Running multiple VMs in a virtual cluster. The virtual machines can talk to one another over the network and (in some cases) the outside world. This is accomplished by calling external programs such as QEMU and the Virtual Distributed Ethernet (VDE) suite. The goal is to let users have a virtual cluster containing nodes where they have privileged access, while isolating that privilege within the virtual cluster so it cannot affect the physical compute resources. Host configuration enforces security; this is not included in Charliecloud, though security guidelines are included in its documentation and Charliecloud is designed to facilitate such configuration. Charliecloud manages passing information from host computers into and out of the virtual machines, such as parameters of the virtual cluster, input data specified by the user, output data from virtual compute jobs, VM console display, and network connections (e.g., SSH or X11). Parameters for the virtual cluster (number of VMs, RAM and disk per VM, etc.) are specified by the user or gathered from the environment (e.g., SLURM environment variables). Example job scripts are included. These include computation examples (such as a "hello world" MPI job) as well as performance tests. They also include a security test script to verify that the virtual cluster is appropriately sandboxed. Tests include: 1. Pinging hosts inside and outside the virtual cluster to explore connectivity; 2. Port scans (again inside and outside) to see what services are available; 3. Sniffing tests to see what traffic is visible to running VMs; 4. IP address spoofing to test network functionality in this case; 5. File access tests to make sure host access permissions are enforced. This test script is not a comprehensive scanner and does not test for specific vulnerabilities. Importantly, no information about physical hosts or network topology is included in this script (or any of Charliecloud); while part of a sensible test, such information is specified by the user when the test is run. That is, one cannot learn anything about the LANL network or computing infrastructure by examining Charliecloud code.

Priedhorsky, Reid↗
DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A computational study of Al n - and Al n -1 1Pt - clusters: the effects of doping and a uniform tuning gauge for single-atom nanocatalysts

Results of density functional theory calculations on Al n - and Al n -1 1Pt - , n = 2-8, clusters are presented and analyzed. The analysis includes different structural forms of the clusters characterized in terms of binding energy, spin and symmetry, and a comparative evaluation of various properties of the two systems viewed as connected through a single-Pt substitutional doping and examined in terms of their respective most stable structures. Furthermore, the Al n -1 1Pt - clusters are then used as a paradigmatic (model) case of single-atom nanocatalysts, with Pt as the catalytic center and Al n-1 as its support, to implement a uniform descriptor for gauging the tuning effects of all the parameters ( "knobs ") of a nanocatalyst that include the identity of the active center and the material and size of its support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The antimony-group 11 chemical bond: Dissociation energies of the diatomic molecules CuSb, AgSb, and AuSb

The intermetallic molecules CuSb, AgSb, and AuSb were identified in the effusive molecular beam produced at high temperature under equilibrium conditions in a double-cell-like Knudsen source. Several gaseous equilibria involving these species were studied by mass spectrometry as a function of temperature in the overall range 1349–1822 K, and the strength of the chemical bond formed between antimony and the group 11 metals was for the first time measured deriving the following thermochemical dissociation energies (D{sub 0}{sup ∘}, kJ/mol): 186.7 ± 5.1 (CuSb), 156.3 ± 4.9 (AgSb), 241.3 ± 5.8 (AuSb). The three species were also investigated computationally at the coupled cluster level with single, double, and noniterative quasiperturbative triple excitations (CCSD(T)). The spectroscopic parameters were calculated from the potential energy curves and the dissociation energies were evaluated at the Complete Basis Set limit, resulting in an overall good agreement with experimental values. An approximate evaluation of the spin-orbit effect was also performed. CCSD(T) calculations were further extended to the corresponding group 11 arsenide species which are here studied for the first time and the following dissociation energies (D{sub 0}{sup ∘}, kJ/mol): 190 ± 10 (CuAs), 151 ± 10 (AgAs), 240 ± 15 (AuAs) are proposed. Taking advantage of the new experimental and computational information here presented, the bond energy trends along group 11 and 4th and 5th periods of the periodic table were analyzed and the bond energies of the diatomic species CuBi and AuBi, yet experimentally unobserved, were predicted on an empirical basis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Formulation of Multicomponent Lattice Gas Model Cluster Expansions Parameterized on Ab Initio Data: An Introduction to the Ab Initio Mean-Field Augmented Lattice Gas Modeling Code

A formalism is presented for the construction of multicomponent lattice gas models parameterized with ab initio (typically density functional theory) data. The leave-multiple-out and the leave-one-out cross validation score are showcased, and practical algorithms are developed and implemented in a new code called the Ab initio Mean-field Augmented Lattice Gas Modeling (AMALGM) code. Here, the functionality of these algorithms is demonstrated with a fully worked out example using the O/Fe(100) system. AMALGM and the formalism on which it is based are envisioned as a surface-oriented lattice gas alternative to other cluster expansion codes that are typically geared toward bulk systems whose lateral interactions between components are parameterized using an Ising model. While the formalism is created within the context of surfaces, it is equally applicable to bulk materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Parameters associated with design effect of child anthropometry indicators in small-scale field surveys

Background: Cluster surveys provide rapid but representative estimates of key nutrition indicators in humanitarian crises. For these surveys, an accurate estimate of the design effect is critical to calculate a sample size that achieves adequate precision with the minimum number of sampling units. This paper describes the variability in design effect for three key nutrition indicators measured in small-scale surveys and models the association of design effect with parameters hypothesized to explain this variability. Methods: 380 small-scale surveys from 28 countries conducted between 2006 and 2013 were analyzed. We calculated prevalence and design effect of wasting, underweight, and stunting for each survey as well as standard deviations of the underlying continuous Z-score distribution. Mean cluster size, survey location and year were recorded. To describe design effects, median and interquartile ranges were examined. Generalized linear regression models were run to identify potential predictors of design effect. Results: Median design effect was under 2.00 for all three indicators; for wasting, the median was 1.35, the lowest among the indicators. Multivariable linear regression models suggest significant, positive associations of design effect and mean cluster size for all three indicators, and with prevalence of wasting and underweight, but not stunting. Standard deviation was positively associated with design effect for wasting but negatively associated for stunting. Survey region was significant in all three models. Conclusions: This study supports the current field survey guidance recommending the use of 1.5 as a benchmark for design effect of wasting, but suggests this value may not be large enough for surveys with a primary objective of measuring stunting or underweight. The strong relationship between design effect and region in the models underscores the continued need to consider country- and locality-specific estimates when designing surveys. These models also provide empirical evidence of a positive relationship between design effect and both mean cluster size and prevalence, and introduces standard deviation of the underlying continuous variable (Z-scores) as a previously unexplored factor significantly associated with design effect. The magnitude and directionality of this association differed by indicator, underscoring the need for further investigation into the relationship between standard deviation and design effect.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Beyond the plane-parallel approximation for redshift surveys

Redshift -space distortions privilege the location of the observer in cosmological redshift surveys, breaking the translational symmetry of the underlying theory. This violation of statistical homogeneity has consequences for the modelling of clustering observables, leading to what are frequently called 'wide-angle effects'. We study these effects analytically, computing their signature in the clustering of the multipoles in configuration and Fourier space. We take into account both physical wide-angle contributions as well as the terms generated by the galaxy selection function. Similar considerations also affect the way power spectrum estimators are constructed. We quantify in an analytical way the biases that enter and clarify the relation between what we measure and the underlying theoretical modelling. The presence of an angular window function is also discussed. Motivated by this analysis, we present new estimators for the three dimensional Cartesian power spectrum and bispectrum multipoles written in terms of spherical Fourier-Bessel coefficients. In conclusion, we show how the latter have several interesting properties, allowing in particular a clear separation between angular and radial modes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Measuring and Modeling Bipartite Graphs with Community Structure

Network science is a powerful tool for analyzing complex systems in fields ranging from sociology to engineering to biology. This paper is focused on generative models of bipartite graphs, also known as two-way graphs. We propose two generative models that can be easily tuned to reproduce the characteristics of real-world networks, not just qualitatively, but quantitatively. The measurements we consider are the degree distributions and the bipartite clustering coefficient, which we refer to as the metamorphosis coefficient. We define edge, node, and degreewise metamorphosis coefficients, enabling a more detailed understand of the bipartite community structure. Our proposed bipartite Chung-Lu model is able to reproduce real-world degree distributions, and our proposed bipartite “BTER” model reproduces both the degree distributions as well as the degreewise metamorphosis coefficients. We demonstrate the effectiveness of these models on several real-world data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Fundamental Vibrational Analyses of the HCN Monomer, Dimer and Associated Isotopologues

In this work we provide high level ab initio treatments of the structures, vibrational frequencies, and electronic energies of the HCN monomer and dimer systems along with several isotopologues. Additionally, the plethora of information related to this system within the literature is summarized and serves as a basis for comparison with the results of this paper. The geometry of the dimer and monomer are reported at the all electroncoupled-cluster singles, doubles, and perturbative triples level of theory [AE-CCSD(T)] with the correlation consistent quadruple-zeta quality basis sets with extra core functions (cc-pCVQZ) from Dunning. The theoretical geometries and electronic structures are further analyzed through the use of the Natural Bond Orbital (NBO) method and Natural Resonance Theory (NRT). At the AE-CCSD(T)/cc-pCVQZ level of theory, the full cubic with semi-diagonal quartic force field for nine dimer and four monomer isotopologues (the parent isotopologue along with 15N, 13C, and D derivatives) were obtained to treat the anharmonicity of the vibrations via second order vibrational perturbation theory (VPT2). Lastly, the enthalpy change associated with the formation of the dimer from two monomer units was determined using the focal point analysis. Computations including coupled-cluster through perturbative quadruples as well as basis sets up to six-zeta quality, including core functions (cc-pCVXZ, X=D,T,Q,5,6) were used to extrapolate to the AE-CCSDT(Q)/CBS energy associated with this hydrogen-bond forming process. After appending anharmonic zero-point vibrational, relativistic, and diagonal Born-Oppenheimer corrections, we report a value of -3.93 kcal mol -1 for the enthalpy of formation. To our knowledge, each set of results (geometries, vibrational frequencies, and energetics) reported in this study represents the highest-level and most reliable theoretical predictions reported for this system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Global Optimization of Chemical Cluster Structures: Methods, Applications, and Challenges

Chemical clusters are relevant to many applications in catalysis, separations, materials, and energy sciences. Experimentally, the structure of clusters is difficult to determine, but it is very important in understanding their chemistry and properties. Computational methods can be used to examine cluster structure, however finding the most stable structure is not simple, particularly as the cluster size increases. Global optimization techniques have long been used to tackle the problem of the most stable structure, but such approaches would have to look for a global minimum, while sampling local minima over the whole potential energy surface as well. In this review, the state-of-the-art theory of global optimization theory is summarized. First, the definition, significance, relation to experiments, and a brief history of global optimization is presented. We then discuss, in more detail, three versatile global optimization methods: the basin hopping, the artificial bee colony algorithm, and the genetic algorithm. We close with some representative application examples of global optimization of clusters since 2016 and the challenges, open questions and opportunities in this field.

Global optimization, Chemical clusters, Artificial↗
DOE OSTI2020

Profiles of upcoming HPC Applications and their Impact on Reservation Strategies

With the expected convergence between HPC, BigData and AI, new applications with different profiles are coming to HPC infrastructures. Here, we aim at better understanding the features and needs of these applications in order to be able to run them efficiently on HPC platforms. The approach followed is bottom-up: we study thoroughly an emerging application from the neuroscience community (SLANT) to understand its behavior. Based on these observations, we derive a generic, yet simple, application model (namely, a linear sequence of stochastic jobs). We expect this model to be representative for a large set of upcoming applications that require the computational power of HPC clusters without fitting the typical behavior of large-scale traditional applications. In a second step, we show how one can manipulate this generic model in a scheduling framework. Specifically we consider the problem of making reservations (both time and memory) for an execution on an HPC platform. We derive solutions using the model of the first step of this work. We experimentally show the robustness of the model, even with very few data or with another application, to generate the model, and provide performance gains with regards to standard and more recent approaches used in the neuroscience community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Programmable photonic integrated meshes for modular generation of optical entanglement links

Abstract Large-scale generation of quantum entanglement between individually controllable qubits is at the core of quantum computing, communications, and sensing. Modular architectures of remotely-connected quantum technologies have been proposed for a variety of physical qubits, with demonstrations reported in atomic and all-photonic systems. However, an open challenge in these architectures lies in constructing high-speed and high-fidelity reconfigurable photonic networks for optically-heralded entanglement among target qubits. Here we introduce a programmable photonic integrated circuit (PIC), realized in a piezo-actuated silicon nitride (SiN)-in-oxide CMOS-compatible process, that implements an N × N Mach–Zehnder mesh (MZM) capable of high-speed execution of linear optical transformations. The visible-spectrum photonic integrated mesh is programmed to generate optical connectivity on up to N = 8 inputs for a range of optically-heralded entanglement protocols. In particular, we experimentally demonstrated optical connections between 16 independent pairwise mode couplings through the MZM, with optical transformation fidelities averaging 0.991 ± 0.0063. The PIC’s reconfigurable optical connectivity suffices for the production of 8-qubit resource states as building blocks of larger topological cluster states for quantum computing. Our programmable PIC platform enables the fast and scalable optical switching technology necessary for network-based quantum information processors.

47 OTHER INSTRUMENTATION↗