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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improving Peptide-Level Mass Spectrometry Analysis via Double Competition

A critical statistical task in the analysis of shotgun proteomics data involves controlling the false discovery rate (FDR) among the reported set of discoveries. This task is most commonly solved at the peptide-spectrum match (PSM) level by using target-decoy competition (TDC), in which a set of observed spectra are searched against a database containing a mixture of real (target) and decoy peptides. The PSM-level procedure can be adapted to the peptide level by selecting the top-scoring PSM per peptide prior to FDR estimation. Here, we investigate both PSM-level and peptide-level FDR control methods and come to two conclusions. First, although the TDC procedure is provably correct under certain assumptions, we observe that one of these assumptions - that incorrect PSMs are independent of one another - is frequently violated. Hence, we empirically demonstrate that TDC-based PSM-level FDR estimates can be liberally biased. Further, we propose that researchers avoid PSM-level results and instead focus on peptide-level analysis. Second, we investigate three ways to carry out peptide level TDC and show that the most common method ("PSM-only") offers the lowest statistical power in practice. The most powerful method, peptide-level FDR with PSM competition ("PSM-and-peptide"), carries out competition first at the PSM level and then again at the peptide level. In our experiments, this approach yields an average increase of 17% more discovered peptides at a1% FDR threshold relative to the PSM-only method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Preserving correlations between trajectories for efficient path sampling

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to dynamical pathways that are substantial, yet sufficiently modest to obtain reasonable acceptance rates. Satisfying this requirement becomes very challenging in the case of long trajectories, due to the characteristic divergences of chaotic dynamics. Here, we examine schemes for addressing this problem, which engineer correlation between a trial trajectory and its reference path, for instance using artificial forces. Our analysis is facilitated by a modern perspective on Markov chain Monte Carlo sampling, inspired by non-equilibrium statistical mechanics, which clarifies the types of sampling strategies that can scale to long trajectories. Viewed in this light, the most promising such strategy guides a trial trajectory by manipulating the sequence of random numbers that advance its stochastic time evolution, as done in a handful of existing methods. In cases where this “noise guidance” synchronizes trajectories effectively, as the Glauber dynamics of a two-dimensional Ising model, we show that efficient path sampling can be achieved for even very long trajectories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Methods for Bayesian power spectrum inference with galaxy surveys

We derive and implement a full Bayesian large scale structure inference method aiming at precision recovery of the cosmological power spectrum from galaxy redshift surveys. Our approach improves upon previous Bayesian methods by performing a joint inference of the three-dimensional density field, the cosmological power spectrum, luminosity dependent galaxy biases, and corresponding normalizations. We account for all joint and correlated uncertainties between all inferred quantities. Classes of galaxies with different biases are treated as separate subsamples. This method therefore also allows the combined analysis of more than one galaxy survey. In particular, it solves the problem of inferring the power spectrum from galaxy surveys with non-trivial survey geometries by exploring the joint posterior distribution with efficient implementations of multiple block Markov chain and Hybrid Monte Carlo methods. Our Markov sampler achieves high statistical efficiency in low signal-to-noise regimes by using a deterministic reversible jump algorithm. This approach reduces the correlation length of the sampler by several orders of magnitude, turning the otherwise numerically unfeasible problem of joint parameter exploration into a numerically manageable task. We test our method on an artificial mock galaxy survey, emulating characteristic features of the Sloan Digital Sky Survey data release 7, such as its survey geometry and luminosity-dependent biases. These tests demonstrate the numerical feasibility of our large scale Bayesian inference frame work when the parameter space has millions of dimensions. This method reveals and correctly treats the anti-correlation between bias amplitudes and power spectrum, which are not taken into account in current approaches to power spectrum estimation, a 20% effect across large ranges in k space. In addition, this method results in constrained realizations of density fields obtained without assuming the power spectrum or bias parameters in advance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Statistical measurement of the gamma-ray source-count distribution as a function of energy

Statistical properties of photon count maps have recently been proven as a new tool to study the composition of the gamma-ray sky with high precision. We employ the 1-point probability distribution function of six years of Fermi-LAT data to measure the source-count distribution dN/dS and the diffuse components of the high-latitude gamma-ray sky as a function of energy. To that aim, we analyze the gamma-ray emission in five adjacent energy bands between 1 and 171 GeV. It is demonstrated that the source-count distribution as a function of flux is compatible with a broken power law up to energies of ∼50 GeV. The index below the break is between 1.95 and 2.0. For higher energies, a simple power-law fits the data, with an index of 2.2{sub −0.3}{sup +0.7} in the energy band between 50 and 171 GeV. Upper limits on further possible breaks as well as the angular power of unresolved sources are derived. We find that point-source populations probed by this method can explain 83{sub −13}{sup +7}% (81{sub −19}{sup +52}%) of the extragalactic gamma-ray background between 1.04 and 1.99 GeV (50 and 171 GeV). The method has excellent capabilities for constraining the gamma-ray luminosity function and the spectra of unresolved blazars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Covariance matrices for variance-suppressed simulations

ABSTRACT Cosmological N-body simulations provide numerical predictions of the structure of the Universe against which to compare data from ongoing and future surveys, but the growing volume of the Universe mapped by surveys requires correspondingly lower statistical uncertainties in simulations, usually achieved by increasing simulation sizes at the expense of computational power. It was recently proposed to reduce simulation variance without incurring additional computational costs by adopting fixed-amplitude initial conditions. This method has been demonstrated not to introduce bias in various statistics, including the two-point statistics of galaxy samples typically used for extracting cosmological parameters from galaxy redshift survey data, but requires us to revisit current methods for estimating covariance matrices of clustering statistics for simulations. In this work, we find that it is not trivial to construct covariance matrices analytically for fixed-amplitude simulations, but we demonstrate that ezmock (Effective Zel’dovich approximation mock catalogue), the most efficient method for constructing mock catalogues with accurate two- and three-point statistics, provides reasonable covariance matrix estimates for such simulations. We further examine how the variance suppression obtained by amplitude-fixing depends on three-point clustering, small-scale clustering, and galaxy bias, and propose intuitive explanations for the effects we observe based on the ezmock bias model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Stochastic reconstruction and microstructure modeling of SMC chopped fiber composites

Here, to establish an integrated Processing-Microstructure-Property workflow for the prediction of material behaviors, this paper presents a new stochastic pseudo-3D microstructure reconstruction method for Sheet Molding Compounds (SMC) chopped fiber composites. The proposed method captures the bi-level microstructural features of SMC composites. At the higher level, a Voronoi diagram-based algorithm is developed to reconstruct the unique substructure features of SMC fiber tows. The geometry of Voronoi cells is adjusted by a Simulated Annealing (SA) algorithm to match the geometrical statistics of the real fiber tows. At the lower level, the algorithm assigns fiber orientation to each Voronoi cell (which represents a fiber tow). The fiber orientation angles are recovered from a statistical fiber orientation tensor. The proposed method is employed to establish a multi-layer pseudo-3D SMC Representative Volume Element (RVE) model for Finite Element Analysis (FEA) of SMC microstructure. This model enables the prediction of mechanical properties based on the material processing information (e.g. fiber orientation tensor obtained from compression molding simulation), and the microstructure information obtained from microscopic imaging for an SMC composite. Lastly, the predicted properties are successfully validated by experimental tensile tests.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A hybrid approach to excited-state-specific variational Monte Carlo and doubly excited states

We extend our hybrid linear-method/accelerated-descent variational Monte Carlo optimization approach to excited states and investigate its efficacy in double excitations. In addition to showing a superior statistical efficiency when compared to the linear method, our tests on small molecules show good energetic agreement with benchmark methods. We also demonstrate the ability to treat double excitations in systems that are too large for a full treatment by using selected configuration interaction methods via an application to 4-aminobenzonitrile. Finally, we investigate the stability of state-specific variance optimization against collapse to other states’ variance minima and find that symmetry, Ansatz quality, and sample size all have roles to play in achieving stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A New Method to Measure the Post-reionization Ionizing Background from the Joint Distribution of Ly α and Ly β Forest Transmission

The amplitude of the ionizing background that pervades the intergalactic medium (IGM) at the end of the epoch of reionization provides a valuable constraint on the emissivity of the sources that reionized the universe. While measurements of the ionizing background at lower redshifts rely on a simulation-calibrated mapping between the photoionization rate and the mean transmission of the Lyα forest, at z ≳ 6 the IGM becomes increasingly opaque and transmission arises solely in narrow spikes separated by saturated Gunn–Peterson troughs. In this regime, the traditional approach of measuring the average transmission over large ~50 Mpc/h regions is less sensitive and suboptimal. In addition, the five times smaller oscillator strength of the Lyβ transition implies that the Lyβ forest is considerably more transparent at z ≳ 6, even in the presence of contamination by foreground z ~ 5 Lyα forest absorption. We present a novel statistical approach to analyze the joint distribution of transmission spikes in the cospatial z ~ 6 Lyα and Lyβ forests. Our method relies on approximate Bayesian computation (ABC), which circumvents the necessity of computing the intractable likelihood function describing the highly correlated Lyα and Lyβ transmission. We apply ABC to mock data generated from a large-volume hydrodynamical simulation combined with a state-of-the-art model of ionizing background fluctuations in the post-reionization IGM and show that it is sensitive to higher IGM neutral hydrogen fractions than previous techniques. As a proof of concept, we apply this methodology to a real spectrum of a z = 6.54 quasar and measure the ionizing background from 5.4 ≤ z ≤ 6.4 along this sightline with ~0.2 dex statistical uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Automated Resonance Fitting for Nuclear Data Evaluation

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Improvement and generalization of ABCD method with Bayesian inference

To find New Physics or to refine our knowledge of the Standard Model at the LHC is an enterprise that involves many factors, such as the capabilities and the performance of the accelerator and detectors, the use and exploitation of the available information, the design of search strategies and observables, as well as the proposal of new models. We focus on the use of the information and pour our effort in re-thinking the usual data-driven ABCD method to improve it and to generalize it using Bayesian Machine Learning techniques and tools. We propose that a dataset consisting of a signal and many backgrounds is well described through a mixture model. Signal, backgrounds and their relative fractions in the sample can be well extracted by exploiting the prior knowledge and the dependence between the different observables at the event-by-event level with Bayesian tools. We show how, in contrast to the ABCD method, one can take advantage of understanding some properties of the different backgrounds and of having more than two independent observables to measure in each event. In addition, instead of regions defined through hard cuts, the Bayesian framework uses the information of continuous distribution to obtain soft-assignments of the events which are statistically more robust. To compare both methods we use a toy problem inspired by pp\to hh\to b\bar b b \bar b p p → h h → b b ‾ b b ‾ , selecting a reduced and simplified number of processes and analysing the flavor of the four jets and the invariant mass of the jet-pairs, modeled with simplified distributions. Taking advantage of all this information, and starting from a combination of biased and agnostic priors, leads us to a very good posterior once we use the Bayesian framework to exploit the data and the mutual information of the observables at the event-by-event level. We show how, in this simplified model, the Bayesian framework outperforms the ABCD method sensitivity in obtaining the signal fraction in scenarios with 1% and 0.5% true signal fractions in the dataset. We also show that the method is robust against the absence of signal. We discuss potential prospects for taking this Bayesian data-driven paradigm into more realistic scenarios.

Alvarez, Ezequiel↗
DOE OSTI2025

Orbit-averaging and deposition accuracy for runaway electron beams in hybrid kinetic-MHD simulations of the runaway plateau

We develop a new procedure that combines the kinetic orbit runaway electron code (KORC) and the NIMROD extended-magnetohydrodynamic code to simulate runaway electrons (REs) in the post-disruption plateau. KORC integrates guiding-center orbits, with a barycentric-based binary search strategy providing initial guesses for the Newton–Raphson logical-to-physical coordinate inversion, ensuring reliable particle-to-mesh mapping in NIMROD, whose fields remain static for the present study. Samples are drawn in accord with experimental parallel current profiles of RE beams during the plateau phase. Deposition in NIMROD is verified through comparison with a Python-based finite-element code that ensures periodicity in the poloidal direction and continuity at the magnetic axis. Accurate representation of near-axis fields requires finer mesh resolution to prevent under- and overshoots in current density from orbit inaccuracies. Yet, at a fixed particle count, increasing mesh resolution amplifies statistical noise in the deposited fields. An orbit-averaging method accumulates partial current deposits over multiple kinetic steps and reduces the statistical noise with little added computational cost. By coupling kinetic routines from KORC directly into the NIMROD codebase, these developments lay essential groundwork for future self-consistent KORC–NIMROD coupling.

Algorithms and data structure↗
DOE OSTI2017

Active Subspace Methods for Data-Intensive Inverse Problems

The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Improved thermonuclear rate of 42 Ti( p , γ ) 43 V and its astrophysical implication in the rp process

Context. Accurate 42 Ti(p,γ) 43 V reaction rates are crucial for understanding the nucleosynthesis path of the rapid capture process (rp process) that occurs in X-ray bursts. Aims. We aim to improve the thermonuclear rates of 42 Ti(p,γ) 43 V based on more complete resonance information and a more accurate direct component, together with the recently released nuclear masses data. We also explore the impact of the newly obtained rates on the rp process. Methods. We reevaluated the reaction rate of 42 Ti(p,γ) 43 V by the sum of the isolated resonance contribution instead of the Hauser-Feshbach statistical model. We used a Monte Carlo method to derive the associated uncertainties of new rates. The nucleosynthesis simulations were performed via the NuGrid post-processing code ppn. Results. The new rates differ from previous estimations due to the use of a series of updated resonance parameters and a direct S factor. Compared with the previous results from the Hauser-Feshbach statistical model, which assumes compound nucleus 43 V with a sufficiently high-level density in the energy region of astrophysical interest, large differences exist over the entire temperature region of rp-process interest, up to two orders of magnitude. We consistently calculated the photodisintegration rate using our new nuclear masses via the detailed balance principle, and found the discrepancies among the different reverse rates are much larger than those for the forward rate, up to ten orders of magnitude at the temperature of 10 8 K. Using a trajectory with a peak temperature of 1.95×10 9 K, we performed the rp-process nucleosynthesis simulations to investigate the impact of the new rates. Our calculations show that the adoption of the new forward and reverse rates result in abundance variations for Sc and Ca of 128% and 49%, respectively, compared to the variations for the statistical model rates. On the other hand, the overall abundance pattern is not significantly affected. The results of using new rates also confirm that the rp-process path does not bypass the isotope 43 V. Conclusions. Our study found that the Hauser-Feshbach statistical model is inappropriate to the reaction rate evaluation for 42 Ti(p,γ) 43 V. The adoption of the new rates confirms that the reaction path of 42 Ti(p,γ) 43 V(p,γ) 44 Cr(β + ) 44 V is a key branch of the rp process in X-ray bursts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Method for factor analysis of GC/MS data

The method of the present invention provides a fast, robust, and automated multivariate statistical analysis of gas chromatography/mass spectroscopy (GC/MS) data sets. The method can involve systematic elimination of undesired, saturated peak masses to yield data that follow a linear, additive model. The cleaned data can then be subjected to a combination of PCA and orthogonal factor rotation followed by refinement with MCR-ALS to yield highly interpretable results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Anomaly Identification of Synchronized Voltage Waveform for Situational Awareness of Low Inertia Systems

Inverter-based resources (IBRs) such as photovoltaics (PVs), wind turbines, and battery energy storage systems (BESSs) are widely deployed in low-carbon power systems. However, these resources typically do not provide the inertia needed for grid stability, resulting in a low-inertia power system. IBRs and lack of inertia have been known to cause anomalies such as waveform distortions and wideband oscillations in power systems due to the limited inertia level, leading to increased generation trips and load shedding. Here, to achieve effective anomaly identification, this paper proposes a synchro-waveform-based algorithm utilizing real-time synchronized voltage waveform measurements from waveform measurement units (WMUs). In the proposed method, different physical characteristics, as well as statistical features, are extracted from synchronized voltage waveform measurements to filter anomalies. Then, the anomaly identification approach based on the random forest is developed and deployed into the FNET/GridEye system considering trade-offs among accuracy, computational burden, and deployment cost. Moreover, four WMUs are specially designed and deployed on Kauai Island to receive instantaneous synchronized voltage waveform measurements. To verify the performance of the proposed algorithm, different experiments are carried out with collected field test data. The result demonstrates that the performance of the proposed synchro-waveform-based anomaly categorization algorithm can accurately identify anomalies 95.35% of the time, which has comparable performance among benchmarking algorithms.

Situational awareness↗
DOE OSTI2016

Determination of grain boundary mobility during recrystallization by statistical evaluation of electron backscatter diffraction measurements

One of the key aspects influencing microstructural design pathways in metallic systems is grain boundary motion. The present work introduces a method by means of which direct measurement of grain boundary mobility vs. misorientation dependence is made possible. The technique utilizes datasets acquired by means of serial electron backscatter diffraction (EBSD) measurements. The experimental EBSD measurements are collectively analyzed, whereby datasets were used to obtain grain boundary mobility and grain aspect ratio with respect to grain boundary misorientation. The proposed method is further validated using cellular automata (CA) simulations. Single crystal aluminium was cold rolled and scratched in order to nucleate random orientations. Subsequent annealing at 300 °C resulted in grains growing, in the direction normal to the scratch, into a single deformed orientation. Growth selection was observed, wherein the boundaries with misorientations close to Σ7 CSL orientation relationship (38° 〈111〉) migrated considerably faster. The obtained boundary mobility distribution exhibited a non-monotonic behavior with a maximum corresponding to misorientation of 38° ± 2° about 〈111〉 axes ± 4°, which was 10–100 times higher than the mobility values of random high angle boundaries. Correlation with the grain aspect ratio values indicated a strong growth anisotropy displayed by the fast growing grains. The observations have been discussed in terms of the influence of grain boundary character on grain boundary motion during recrystallization. - Highlights: • Statistical microstructure method to measure grain boundary mobility during recrystallization • Method implementation independent of material or crystal structure • Mobility of the Σ7 boundaries in 5N Al was calculated as 4.7 × 10{sup –8} m{sup 4}/J ⋅ s. • Pronounced growth selection in the recrystallizing nuclei in Al • Boundary mobility values during recrystallization 2–3 orders of magnitude larger vis-à-vis curvature driven motion.

36 MATERIALS SCIENCE↗
DOE OSTI2014

A method for multichannel dosimetry with EBT3 radiochromic films

Purpose: An improved method for multichannel dosimetry is presented. This method explicitly takes into account the information provided by the unexposed image of the film. Methods: The method calculates the dose by applying a couple of perturbations to the scanned dose, one dependent and the other independent on the color channel. The method has been compared with previous multichannel and two single channel methods (red and green) against measurements using two different tests: first, five percentage depth dose profiles covering a wide range of doses; second, the dose map perpendicular to the beam axis for a 15 × 15cm{sup 2} square field. Finally, the results of 30 IMRT quality assurances tests are presented. All tests have been evaluated using the gamma analysis. Results: The coefficient of variation was found to be similar for all methods in a wide range of doses. The results of the proposed method are more in agreement with the experimental measurements and with the treatment planning system. Furthermore, the differences in the mean gamma pass rates are statistically significant. Conclusions: The improved multichannel dosimetric method is able to remove many of the common disturbances usually present in radiochromic films and improves the gamma analysis results compared with the other three methods.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Eulerian formulation of the interacting particle representation model of homogeneous turbulence

The Interacting Particle Representation Model (IPRM) of homogeneous turbulence incorporates information about the morphology of turbulent structures within the con nes of a one-point model. In the original formulation [Kassinos & Reynolds, Center for Turbulence Research: Annual Research Briefs, 31{51, (1996)], the IPRM was developed in a Lagrangian setting by evolving second moments of velocity conditional on a given gradient vector. In the present work, the IPRM is re-formulated in an Eulerian framework and evolution equations are developed for the marginal PDFs. Eulerian methods avoid the issues associated with statistical estimators used by Lagrangian approaches, such as slow convergence. A specific emphasis of this work is to use the IPRM to examine the long time evolution of homogeneous turbulence. We first describe the derivation of the marginal PDF in spherical coordinates, which reduces the number of independent variables and the cost associated with Eulerian simulations of PDF models. Next, a numerical method based on radial basis functions over a spherical domain is adapted to the IPRM. Finally, results obtained with the new Eulerian solution method are thoroughly analyzed. The sensitivity of the Eulerian simulations to parameters of the numerical scheme, such as the size of the time step and the shape parameter of the radial basis functions, is examined. A comparison between Eulerian and Lagrangian simulations is performed to discern the capabilities of each of the methods. Finally, a linear stability analysis based on the eigenvalues of the discrete differential operators is carried out for both the new Eulerian solution method and the original Lagrangian approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗