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DOE OSTI2011

p-Wave Cold Collisions in an Optical Lattice Clock

We study ultracold collisions in fermionic ytterbium by precisely measuring the energy shifts they impart on the atoms' internal clock states. Exploiting Fermi statistics, we uncover p-wave collisions, in both weakly and strongly interacting regimes. With the higher density afforded by two-dimensional lattice confinement, we demonstrate that strong interactions can lead to a novel suppression of this collision shift. In addition to reducing the systematic errors of lattice clocks, this work has application to quantum information and quantum simulation with alkaline-earth atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Induced seismicity in geothermal reservoirs: A review of forecasting approaches

In order to reach Europe's 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced seismicity is often perceived as an unsolicited and uncontrollable side effect of geothermal development. In the last decade, significant advances were made in the development of models to forecast induced seismicity, which are either based on catalogues of induced seismicity, on the underlying physical processes, or on a hybrid philosophy. In this paper, we provide a comprehensive overview of the existing approaches applied to geothermal contexts. This overview will outline the advantages and drawbacks of the different approaches, identify the gaps in our understanding, and describe the needs for geothermal observations. Most of the forecasting approaches focus on the stimulation phase of enhanced geothermal systems which are most prone to generate seismic events. Besides the statistical models suited for real-time applications during reservoir stimulation, the physics-based models have the advantage of considering sub-surface characteristics and estimating the impact of fluid circulation on the reservoir. Thus, to mitigate induced seismicity during major hydraulic stimulations, application of hybrid methods in a decision support system seems the best available solution. So far, however, little attention has been paid to geochemical effects on the failure process and to production periods. Quantitative modelling of induced seismicity still is a challenging and complex matter. Appropriate resources remain to be invested for the scientific community to continue its research and development efforts to successfully forecast induced seismicity in geothermal fields. This is a prerequisite for making this renewable energy resource sustainable and accessible worldwide.

58 GEOSCIENCES↗

DOE OSTI2023

Variance Reduction within Implicit Monte Carlo Thermal Radiation Transport using the Local Importance Function Transform [Slides]

System of equations derived by Fleck and Cummings to model time-dependent thermal radiative transfer (TRT) problems: Solution of radiation specific intensity (I), non-linearly coupled to material internal energy (U); Absorption and re-emission approximated by effective scattering events. Useful for high-energy density physics simulations: i.e., astrophysics, inertial confinement fusion (ICF). Whereas deterministic methods are fully discretized and free of statistical noise, Monte Carlo methods allow for dynamic sampling of the phase space at the price of statistical noise; Monte Carlo methods are also characterized by a slow $\frac{1}{√Ν}$ convergence rate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2000

Spacewatch Survey of the Solar System

The purpose of the Spacewatch project is to explore the various populations of small objects throughout the solar system. Statistics on all classes of small bodies are needed to infer their physical and dynamical evolution. More Earth Approachers need to be found to assess the impact hazard. (We have adopted the term "Earth Approacher", EA, to include all those asteroids, nuclei of extinct short period comets, and short period comets that can approach close to Earth. The adjective "near" carries potential confusion, as we have found in communicating with the media, that the objects are always near Earth, following it like a cloud.) Persistent and voluminous accumulation of astrometry of incidentally observed main belt asteroids MBAs will eventually permit the Minor Planet Center (MPQ to determine the orbits of large numbers (tens of thousands) of asteroids. Such a large body of information will ultimately allow better resolution of orbit classes and the determinations of luminosity functions of the various classes, Comet and asteroid recoveries are essential services to planetary astronomy. Statistics of objects in the outer solar system (Centaurs, scattered-disk objects, and Trans-Neptunian Objects; TNOs) ultimately will tell part of the story of solar system evolution. Spacewatch led the development of sky surveying by electronic means and has acted as a responsible interface to the media and general public on this discipline and on the issue of the hazard from impacts by asteroids and comets.

McMillan, Robert S.↗

DOE OSTI2015

Bootstrap performance profiles in stochastic algorithms assessment

Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Making inertial confinement fusion models more predictive

Computer models of inertial confinement fusion (ICF) implosions play an essential role in experimental design and interpretation as well as our understanding of fundamental physics under the most extreme conditions that can be reached in the laboratory. Building truly predictive models is a significant challenge, with the potential to greatly accelerate progress to high yield and ignition. One path to more predictive models is to use experimental data to update the underlying physics in a way that can be extrapolated to new experiments and regimes. We describe a statistical framework for the calibration of ICF simulations using data collected at the National Ignition Facility (NIF). We perform Bayesian inferences for a series of laser shots using an approach that is designed to respect the physics simulation as much as possible and then build a second model that links the individual-shot inferences together. We show that this approach is able to match multiple X-ray and neutron diagnostics for a whole series of NIF “BigFoot” shots. Within the context of 2D radiation hydrodynamic simulations, our inference strongly favors a significant reduction in fuel compression over other known degradation mechanisms (namely, hohlraum issues and engineering perturbations). This analysis is expanded using a multifidelity technique to pick fuel-ablator mix from several candidate causes of the degraded fuel compression (including X-ray preheat and shock timing errors). Finally, we use our globally calibrated model to investigate the extra laser drive energy that would be required to overcome the inferred fuel compression issues in NIF BigFoot implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Statistical Learning for Nonlinear Model Reduction from Local Simulations of Stochastic and Particle- and Agent-Based Systems

Stochastic physical systems across the sciences that have very high-dimensional state spaces, with a large number of fast degrees of freedom that force direct simulators to proceed by integration steps that are orders of magnitude smaller than events of interests (e.g., particle collisions). Examples range from molecular motion to dynamics of large populations of cells. A grand challenge in the simulation and understanding of such systems is the systematic construction of accurate, interpretable, reduced models, enabling faster simulations, revealing fundamental properties of the dynamics, and predicting phenomena of interest that the original simulator could not reached with sufficient accuracy or within a given computational budget. In this projected we developed novel statistical estimation/machine learning techniques for analyzing and building empirical reduced models for important families of high-dimensional stochastic systems, in particular: - we developed techniques for estimating interaction kernels in interacting particle- and agent-based systems, which are ubiquitous in Physics, Biology and many other sciences, given observed trajectories of the system; - we developed techniques for nonlinear model reduction for high-dimensional stochastic systems that have a small number of unknown, nonlinear slow variables, and a large number of fast modes, that are possibly of large magnitude, given observed short trajectories of the system in the form of bursts of trajectories from different initial conditions; - we developed novel techniques for estimating linear dynamical systems on graphs when both the dynamics and the underlying graph are unknown, and we have a sparse set of space-time observations; - we considered the problem of estimating an unknown nonlinear observation function of a standard process (e.g. Brownian motion), so that we can recognized if an observed dynamics is "just" a nonlinear version of a known dynamics; we also developed benchmarks for learning algorithms aimed at learning and classifying diffusion processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Automating galaxy morphology classification using k -nearest neighbours and non-parametric statistics

ABSTRACT Morphology is a fundamental property of any galaxy population. It is a major indicator of the physical processes that drive galaxy evolution and in turn the evolution of the entire Universe. Historically, galaxy images were visually classified by trained experts. However, in the era of big data, more efficient techniques are required. In this work, we present a k-nearest neighbours based approach that utilizes non-parametric morphological quantities to classify galaxy morphology in Sloan Digital Sky Survey images. Most previous studies used only a handful of morphological parameters to identify galaxy types. In contrast, we explore 1023 morphological spaces (defined by up to 10 non-parametric statistics) to find the best combination of morphological parameters. Additionally, while most previous studies broadly classified galaxies into early types and late types or ellipticals, spirals, and irregular galaxies, we classify galaxies into 11 morphological types with an average accuracy of ${\sim} 80\!-\!90 \, {{\rm per\, cent}}$ per T-type. Our method is simple, easy to implement, and is robust to varying sizes and compositions of the training and test samples. Preliminary results on the performance of our technique on deeper images from the Hyper Suprime-Cam Subaru Strategic Survey reveal that an extension of our method to modern surveys with better imaging capabilities might be possible.

Mukundan, Kavya↗

DOE OSTI2023

Model averaging approaches to data subset selection

Model averaging is a useful and robust method for dealing with model uncertainty in statistical analysis. Often, it is useful to consider data subset selection at the same time, in which model selection criteria are used to compare models across different subsets of the data. Two different criteria have been proposed in the literature for how the data subsets should be weighted. We compare the two criteria closely in a unified treatment based on the Kullback-Leibler divergence and conclude that one of them is subtly flawed and will tend to yield larger uncertainties due to loss of information. Here, analytical and numerical examples are provided.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

Modeling Radiation Detection Using a Mixed-Effects Statistical Model for Background Variation

In this paper, we consider radiation source localization in an urban environment as an inverse problem and use Bayesian parameter estimation techniques to infer the source location and intensity. Since parameter estimation generally requires a large number of model evaluations, we employ a simplified photon transport model, as in a 2017 paper by Stefanescu, et al., to reduce computational requirements. However, the model in the 2017 paper does not account for the physical reality that background radiation varies with position within an urban locale. We incorporate statistical mixed-effects modeling into the simplified transport equation from the Stefanescu, et al. paper to reflect individual variation among the background radiation measurements at multiple detector locations. With our new model, we use a Bayesian DRAM-within-Gibbs technique, which incorporates the Delayed Rejection Adaptive Metropolis (DRAM) algorithm, to estimate the mixed-effects parameters. We note that without adequate prior information, we were unable to simultaneously estimate the set of parameters corresponding to the source intensity, source location, and individual background radiation counts. By calibrating the background in the absence of a source, we obtained narrow prior distributions, which permitted us to jointly infer the source intensity and location and the background radiation distribution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

On-chip generation of Einstein-Podolsky-Rosen states with arbitrary symmetry

We experimentally demonstrate a method for integrated-optical generation of two-photon Einstein-Podolsky-Rosen states featuring arbitrary symmetries. In our setting, we employ detuned directional couplers to impose a freely tailorable phase between the two modes of the state. Our results allow to mimic the quantum random walk statistics of bosons, fermions, and anyons, particles with fractional exchange statistics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

Statistical modeling support for calibration of a multiphysics model of subcooled boiling flows

Nuclear reactor system analyses rely on multiple complex models which describe the physics of reactor neutronics, thermal hydraulics, structural mechanics, coolant physico-chemistry, etc. Such coupled multiphysics models require extensive calibration and validation before they can be used in practical system safety study and/or design/technology optimization. This paper presents an application of statistical modeling and Bayesian inference in calibrating an example multiphysics model of subcooled boiling flows which is widely used in reactor thermal hydraulic analysis. The presence of complex coupling of physics in such a model together with the large number of model inputs, parameters and multidimensional outputs poses significant challenge to the model calibration method. However, the method proposed in this work is shown to be able to overcome these difficulties while allowing data (observation) uncertainty and model inadequacy to be taken into consideration. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2011

What HERA May Provide?

More than 100 people participated in a discussion session at the DIS08 workshop on the topic What HERA may provide. A summary of the discussion with a structured outlook and list of desirable measurements and theory calculations is given. The HERA accelerator and the HERA experiments H1, HERMES and ZEUS stopped running in the end of June 2007. This was after 15 years of very successful operation since the first collisions in 1992. A total luminosity of {approx} 500 pb{sup -1} has been accumulated by each of the collider experiments H1 and ZEUS. During the years the increasingly better understood and upgraded detectors and HERA accelerator have contributed significantly to this success. The physics program remains in full swing and plenty of new results were presented at DIS08 which are approaching the anticipated final precision, fulfilling and exceeding the physics plans and the previsions of the upgrade program. Most of the analyses presented at DIS08 were still based on the so called HERA I data sample, i.e. data taken until 2000, before the shutdown for the luminosity upgrade. This sample has an integrated luminosity of {approx} 100 pb{sup -1}, and the four times larger statistics sample from HERA II is still in the process of being analyzed.

43 PARTICLE ACCELERATORS↗

DOE OSTI2011

QUANTUM STATISTICAL CORRECTIONS TO ASTROPHYSICAL PHOTODISINTEGRATION RATES

Tabulated rates for astrophysical photodisintegration reactions make use of Boltzmann statistics for the photons involved as well as the interacting nuclei. Here, we derive analytic corrections for the Planck-spectrum quantum statistics of the photon energy distribution. These corrections can be deduced directly from the detailed balance condition without the assumption of equilibrium as long as the photons are represented by a Planck spectrum. Moreover, we show that these corrections affect not only the photodisintegration rates but also modify the conditions of nuclear statistical equilibrium as represented in the Saha equation. We deduce new analytic corrections to the classical Maxwell-Boltzmann statistics which can easily be added to the reverse reaction rates of existing reaction network tabulations. We show that the effects of quantum statistics, though generally quite small, always tend to speed up photodisintegration rates and are largest for nuclei and environments for which Q/kT {approx} 1. As an illustration, we examine possible effects of these corrections on the r-process, the rp-process, explosive silicon burning, the {gamma}-process, and big bang nucleosynthesis. We find that in most cases one is quite justified in neglecting these corrections. The correction is largest for reactions near the drip line for an r-process with very high neutron density, or an rp-process at high temperature.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1978

A statistical study of crater-associated wind streaks in the north equatorial zone of Mars

The physical characteristics of all crater-related streaks within the north equatorial zone of Mars (between 0 and 30 deg N) are studied. The survey includes 25% of the Martian surface area and covers the latitude band of major interest to the Viking missions. Nine characteristic parameters are measured for each of 2325 streaks, of which 82.3% are classified as light tone, 8.1% as dark tone, and 9.6% as mixed tone. The location of streaks in the investigated zone is considered together with the indicated wind regimes, and the characteristics of the streaks and of their associated craters are discussed. The results show that: (1) the streaks are not uniformly distributed throughout the north equatorial zone but are strongly concentrated in certain areas; (2) the density of streaks displays a significant latitude variation not apparently related to terrain type between 0 and 30 deg N; (3) the percentage of craters with streaks reaches a maximum between 10 and 15 deg N and falls off significantly toward both the equator and higher latitudes; and (4) the density of streaks correlates well with geological terrain type.

Veverka, J.↗

DOE OSTI2013

CONFRONTING COLD DARK MATTER PREDICTIONS WITH OBSERVED GALAXY ROTATIONS

The rich statistics of galaxy rotations as captured by the velocity function (VF) provide invaluable constraints on galactic baryon physics and the nature of dark matter (DM). However, the comparison of observed galaxy rotations against cosmological models is prone to subtle caveats that can easily lead to misinterpretations. Our analysis reveals full statistical consistency between {approx}5000 galaxy rotations, observed in line-of-sight projection, and predictions based on the standard cosmological model ({Lambda}CDM) at the mass-resolution of the Millennium simulation (H I line-based circular velocities above {approx}50 km s{sup -1}). Explicitly, the H I linewidths in the H I Parkes All Sky Survey (HIPASS) are found to be consistent with those in S{sup 3}-SAX, a post-processed semi-analytic model for the Millennium simulation. Previously found anomalies in the VF can be plausibly attributed to (1) the mass-limit of the Millennium simulation, (2) confused sources in HIPASS, (3) inaccurate inclination measurements for optically faint sources, and (4) the non-detectability of gas-poor early-type galaxies. These issues can be bypassed by comparing observations and models using linewidth source counts rather than VFs. We investigate if and how well such source counts can constrain the temperature of DM.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1991

Avalanches and the distribution of solar flares

The solar coronal magnetic field is proposed to be in a self-organized critical state, thus explaining the observed power-law dependence of solar-flare-occurrence rate on flare size which extends over more than five orders of magnitude in peak flux. The physical picture that arises is that solar flares are avalanches of many small reconnection events, analogous to avalanches of sand in the models published by Bak and colleagues in 1987 and 1988. Flares of all sizes are manifestations of the same physical processes, where the size of a given flare is determined by the number of elementary reconnection events. The relation between small-scale processes and the statistics of global-flare properties which follows from the self-organized magnetic-field configuration provides a way to learn about the physics of the unobservable small-scale reconnection processes. A simple lattice-reconnection model is presented which is consistent with the observed flare statistics. The implications for coronal heating are discussed and some observational tests of this picture are given.

Lu, Edward T.↗