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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dark Energy Survey Year 3 results: Cosmology from cosmic shear and robustness to modeling uncertainty

Here, this work and its companion paper, Amon et al. [Phys. Rev. D 105, 023514 (2022)], present cosmic shear measurements and cosmological constraints from over 100 million source galaxies in the Dark Energy Survey (DES) Year 3 data. We constrain the lensing amplitude parameter 𝑆 8 ≡𝜎 8 ⁢$\sqrt{Ω_{m}/0.3}$ at the 3% level in Λ⁢ CDM: 𝑆 8 =0.75⁢9$^{+0.025}_{−0.023}$ (68% CL). Our constraint is at the 2% level when using angular scale cuts that are optimized for the Λ⁢ CDM analysis: 𝑆 8 =0.77⁢2$^{+0.018}_{−0.017}$ (68% CL). With cosmic shear alone, we find no statistically significant constraint on the dark energy equation-of-state parameter at our present statistical power. We carry out our analysis blind, and compare our measurement with constraints from two other contemporary weak lensing experiments: the Kilo-Degree Survey (KiDS) and Hyper-Suprime Camera Subaru Strategic Program (HSC). We additionally quantify the agreement between our data and external constraints from the Cosmic Microwave Background (CMB). Our DES Y3 result under the assumption of Λ⁢ CDM is found to be in statistical agreement with Planck 2018, although favors a lower 𝑆 8 than the CMB-inferred value by 2.3⁢𝜎 (a 𝑝-value of 0.02). This paper explores the robustness of these cosmic shear results to modeling of intrinsic alignments, the matter power spectrum and baryonic physics. We additionally explore the statistical preference of our data for intrinsic alignment models of different complexity. The fiducial cosmic shear model is tested using synthetic data, and we report no biases greater than 0.3⁢𝜎 in the plane of 𝑆 8 ×Ω m caused by uncertainties in the theoretical models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Code for the manuscript "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Mode

We disclose a python/pytorch implementation of the physics-informed machine learning algorithm described in "Lagrangian Attention Tensor Networks for Velocity Gradient Statistical Modeling", LA-UR-24-30678. Direct numerical simulation (DNS) of ubiquitous turbulence phenomena is computationally infeasible for realistic flows. As a result, reduced modeling for turbulent flows aim to reduce the number of resolved scales while retaining accurate representations of the small-scale physics. The dynamics of the velocity gradient tensor (VGT) is a key ingredient in reduced or subgrid turbulence models. The evolution equation for the VGT involves nonlocal terms, requiring closure modeling. This implementation of the novel methodology of Lagrangian Attention Tensor Networks (LATN), utilizes a structured representation of the history of the VGT to inform a physics-informed machine learning algorithm. This addition of structured memory terms is shown to outperform previous models when trained and evaluated on DNS data.

Livescu, Daniel [LANL]↗
DOE OSTI2021

Turbulence theories and statistical closure approaches

When discussing research in physics and in science more generally, it is common to ascribe equal importance to the three components of the scientific trinity: theoretical, experimental, and computational studies. This review will explore the future of modern turbulence theory by tracing its history, which began in earnest with Kolmogorov’s 1941 analysis of turbulence cascade and inertial range [A.N. Kolmogorov, Dokl. Akad. Nauk SSSR, 30, 299, (1941); 32, 19, (1941)]. The 80th Anniversary of Kolmogorov’s landmark study is a welcome opportunity to survey the achievements and evaluate the future of the theoretical approach of turbulence research. Over the years, turbulence theories have been critically important in laying the foundation of our understanding of the nature of turbulent flows. In particular, the Direct Interaction Approximation (DIA) [R.H. Kraichnan, J. Fluid Mech., 5, 497 (1959)] and its subsequent development, known as the statistical closure approach, can be identified as perhaps the most profound single advancement. The remarkable success of the statistical closure has furnished a platform to study such essential concepts as the energy transfer process and interacting scales, and the roles of the straining and sweeping motions. More recently, the quasi-Lagrangian formulation of V. L’vov & I. Procaccia and Kraichnan’s solvable passive scalar model provided powerful ways to explore another fundamental aspect of turbulent flows, the phenomena of intermittency, and the associated anomalous scaling exponents. In the meantime, the theory of fluid equilibria has been developed to describe the large-scale structures that can emerge from turbulent cascades of two-dimensional and geophysical flows at a later time. And yet, despite all these successes, analytical treatments suffer from mathematical complexities. As a result, the utility of theoretical approaches has been limited to relatively idealized flows. On the other hand, in recent decades, computational abilities and experimental facilities have reached an unprecedented scale. Looking beyond the horizon, the imminent deployment of exascale supercomputers will generate complete datasets of the entire flow field of key benchmark flows, allowing researchers to extract additional measurements concerning fully developed, complex turbulent flow fields far beyond those available from the statistical closure theories. Some other developments that could potentially influence the future course of turbulence theories include the advancement of machine learning, artificial intelligence, and data science; likely disruptions arising from the advent of quantum computation; and the increasingly prominent role of turbulence research in providing more accurate climate scientific data. Finally, turbulence theorists can leverage these developments by asking the right questions and developing advanced, sophisticated frameworks that will be able to predict and correlate vast amounts of data from the other two components of the trinity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Research in Theoretical High Energy Nuclear Physics at the University of Arizona

In the past decade (2004-2015) we addressed the quest for the understanding of how quark confinement works, how it can be dissolved in a limited space-time domain, and what this means: i) for the paradigm of the laws of physics of present day; and, ii) for our understanding of cosmology. The focus of our in laboratory matter formation work has been centered on the understanding of the less frequently produced hadronic particles (e.g. strange antibaryons, charmed and beauty hadrons, massive resonances, charmonium, B c ). We have developed a public analysis tool, SHARE (Statistical HAdronization with REsonances) which allows a precise model description of experimental particle yield and fluctuation data. We have developed a charm recombination model to allow for off-equilibrium rate of charmonium production. We have developed methods and techniques which allowed us to study the hadron resonance yield evolution by kinetic theory. We explored entropy, strangeness and charm as signature of QGP addressing the wide range of reaction energy for AGS, SPS, RHIC and LHC energy range. In analysis of experimental data, we obtained both statistical parameters as well as physical properties of the hadron source. The following pages present listings of our primary writing on these questions. The abstracts are included in lieu of more detailed discussion of our research accomplishments in each of the publications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Extension of the eigenstate thermalization hypothesis to nonequilibrium steady states

We extend the notion of the eigenstate thermalization hypothesis (ETH) to open quantum systems governed by the Gorini-Kossakowski-Lindblad-Sudarshan (GKLS) master equation. We present evidence that the eigenstates of nonequilibrium steady-state (NESS) density matrices obey a generalization of ETH in boundary-driven systems when the bulk Hamiltonian is nonintegrable, just as eigenstates of Gibbs density matrices are conjectured to do in equilibrium. Furthermore, this generalized ETH, which we call NESS ETH, can be used to obtain representative pure states that reproduce the expectation values of few-body operators in the NESS. The density matrices of these representative pure states can be further interpreted as weak solutions of the GKLS master equation. Additionally, we explore the validity and breakdown of NESS-ETH in the presence of symmetries, integrability, and many-body localization in the bulk Hamiltonian.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems

Subsurface applications, including geothermal, geological carbon sequestration, and oil and gas, typically involve maximizing either the extraction of energy or the storage of fluids. Fractures form the main pathways for flow in these systems, and locating these fractures is critical for predicting flow. However, fracture characterization is a highly uncertain process, and data from multiple sources, such as flow and geophysical are needed to reduce this uncertainty. We present a nonintrusive, sequential inversion framework for integrating data from geophysical and flow sources to constrain fracture networks in the subsurface. In this framework, we first estimate bounds on the statistics for the fracture orientations using microseismic data. These bounds are estimated through a combination of a focal mechanism (physics-based approach) and clustering analysis (statistical approach) of seismic data. Then, the fracture lengths are constrained using flow data. In conclusion, the efficacy of this inversion is demonstrated through a representative example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Measuring the Muon Anomalous Magnetic Moment to High Precision [PowerPoint]

The anomalous magnetic moment of the muon, characterized as the anomaly $a_{\mu} \equiv (g_{\mu}-2)/2$, remains a compelling hint of physics beyond the Standard Model (BSM) in light of the Brookhaven E821 measurement from the early 2000s, which differs with theoretical predictions by $>$3\,$\sigma$. To address this discrepancy, the Muon $g-2$ Experiment at Fermilab (E989) has been designed to determine $a_{\mu}$ to a precision of 140 parts per billion, a four-fold improvement over the E821 measurement. This improved precision presents an excellent opportunity to uncover BSM physics, and at minimum constrain BSM prescriptions. To date, the E989 experiment has completed its first two physics runs, recording more than 3 times the statistics recorded in the E821 experiment. The collaboration is preparing for a third physics run starting in October, with the goal of accumulating a factor of three more data than the previous runs combined, resulting in an order of magnitude more statistics than the Brookhaven measurement. An overview of the experimental technique will be discussed, along with a summary of Run 1 and 2. An update of the analysis of the Run 1 data will be presented; additionally, Run 3 progress will be summarized.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1980

The structure of correlation tensors in homogeneous anisotropic turbulence

The study of turbulence with spatially homogeneous but anisotropic statistical properties has applications in space physics and laboratory plasma physics. The first step in the systematic study of such fluctuations is the elucidation of the kinematic properties of the relevant statistical objects, which are the correlation tensors. The theory of isotropic tensors, developed by Robertson, Chandrasekhar and others, is reviewed and extended to cover the general case of turbulence with a pseudo-vector preferred direction, without assuming mirror reflection invariance. Attention is focused on two point correlation functions and it is shown that the form of the decomposition into proper and pseudo-tensor contributions is restricted by the homogeneity requirement. It is also shown that the vector and pseudo-vector preferred direction cases yield different results. An explicit form of the two point correlation tensor is presented which is appropriate for analyzing interplanetary magnetic fluctuations. A procedure for determining the magnetic helicity from experimental data is presented.

Matthaeus, W. H.↗
NASA NTRS1992

Derivation of phase statistics from the Mueller matrix

Experimental observations show a strong dependence of phase differences of scattering matrix elements on the physical parameters of random media. Here, the statistical behavior of the phase differences is studied for distributed targets. The pdfs of the phase differences are derived from the Mueller matrix of the target. In deriving the density functions, it is assumed that the real and imaginary parts of the copolarized and cross-polarized terms of the scattering matrix are jointly Gaussian and their covariance matrices are found in terms of the Mueller matrix elements. The functional forms of the copolarized and cross-polarized density functions are similar and are obtained independently. It is shown that the density function of the phase difference is completely determined in terms of only two parameters.

Sarabandi, K.↗
DOE OSTI2017

Creating a Face from a DNA Sample

The idea of creating a recognizable face from a sample of DNA is moving closer to reality as Oak Ridge National Laboratory (ORNL) researchers employ a novel statistical representation of the face and a genome-wide association study (GWAS) to relate facial characteristics to genetic mutations. The reduction in cost of DNA sequencing and genotyping technology is leading to the availability of massive datasets of human genome sequences and human genotypes representing mutational variation among people. These large-scale data provide for the first time the potential to correlate an individual’s specific genetic code with their physical appearance. Using a specialized statistical method for representing the entire 3D shape of faces, ORNL researchers performed a GWAS to discover associations between genetic mutations and aspects of face shape. Data from 3,556 subjects resulted in the discovery of a very large set of statistically significant associations, which is strong evidence for the viability of predicting faces from DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Accelerating quantum optics experiments with statistical learning

Quantum optics experiments, involving the measurement of low-probability photon events, are known to be extremely time-consuming. We present a methodology for accelerating such experiments using physically motivated ansatzes together with simple statistical learning techniques such as Bayesian maximum a posteriori estimation based on few-shot data. We show that it is possible to reconstruct time-dependent data using a small number of detected photons, allowing for fast estimates in under a minute and providing a one-to-two order of magnitude speed-up in data acquisition time. We test our approach using real experimental data to retrieve the second order intensity correlation function, G (2) ($τ$), as a function of time delay τ between detector counts, for thermal light as well as anti-bunched light emitted by a quantum dot driven by periodic laser pulses. The proposed methodology has a wide range of applicability and has the potential to impact the scientific discovery process across a multitude of domains.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Plackett-Burman experimental design to facilitate syntactic foam development

The use of an eight-experiment Plackett–Burman method can assess six experimental variables and eight responses in a polysiloxane-glass microsphere syntactic foam. The approach aims to decrease the time required to develop a tunable polymer composite by identifying a reduced set of variables and responses suitable for future predictive modeling. The statistical design assesses the main effects of mixing process parameters, polymer matrix composition, microsphere density and volume loading, and the blending of two grades of microspheres, using a dummy factor in statistical calculations. Responses cover rheological, physical, thermal, and mechanical properties. The cure accelerator content of the polymer matrix and the volume loading of the microspheres have the largest effects on foam properties. These factors are the most suitable for controlling the gel point of the curing foam, and the density of the cured foam. The mixing parameters introduce widespread variability and therefore should be fixed at effective levels during follow-up testing. Some responses may require greater contrast in microsphere-related factors. As a result, compared to other possible statistical approaches, the run economy of the Plackett–Burman method makes it a valuable tool for rapidly characterizing new foams.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The CMS data analysis school experience

The CMS Data Analysis School is an official event organized by the CMS Collaboration to teach students and post-docs how to perform a physics analysis. The school is coordinated by the CMS schools committee and was first implemented at the LHC Physics Center at Fermilab in 2010. As part of the training, there are a number of “short” exercises on physics object reconstruction and identification, Monte Carlo simulation, and statistical analysis, which are followed by “long” exercises based on physics analyses. Some of the long exercises go beyond the current state of the art of the corresponding CMS analyses. This paper describes the goals of the school, the preparations for a school, the structure of the training, and student satisfaction with the experience as measured by surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

SDSS-IV MaNGA: the physical origin of off-galaxy H α blobs in the local Universe

ABSTRACT H α blobs are off-galaxy emission-line regions with weak or no optical counterparts. They are mostly visible in H α line, appearing as concentrated blobs. Such unusual objects have been rarely observed and studied, and their physical origin is still unclear. We have identified 13 H α blobs in the public data of MaNGA survey, by visually inspecting both the optical images and the spatially resolved maps of H α line for ∼4600 galaxy systems. Among the 13 H α blobs, 2 were reported in previously MaNGA-based studies and 11 are newly discovered. This sample, though still small in size, is by far the largest sample with both deep imaging and integral field spectroscopy. Therefore, for the first time we are able to perform statistical studies to investigate the physical origin of H α blobs. We examine the physical properties of these H α blobs and their associated galaxies, including their morphology, environments, gas-phase metallicities, kinematics of ionized gas, and ionizing sources. We find that the H α blobs in our sample can be broadly divided into two groups. One is associated with interacting/merging galaxy systems, of which the ionization is dominated by shocks or diffuse ionized gas. It is likely that these H α blobs used to be part of their nearby galaxies, but were stripped away at some point due to tidal interactions. The other group is found in gas-rich systems, appearing as low-metallicity star-forming regions that are visually detached from the main galaxy. These H α blobs could be associated with faint discs, spiral arms, or dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Theory and modeling of molecular modes in the NMR relaxation of fluids

Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. Here, we recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

An ALMA survey of sub-millimeter galaxies in the extended Chandra deep field south: Physical properties derived from ultraviolet-to-radio modeling

The ALESS survey has followed up on a sample of 122 sub-millimeter sources in the Extended Chandra Deep Field South at 870 μm with the Atacama Large Millimeter Array (ALMA), allowing us to pinpoint the positions of sub-millimeter galaxies (SMGs) to ∼0.3 arcsec and to find their precise counterparts at different wavelengths. This enabled the first compilation of the multi-wavelength spectral energy distributions (SEDs) of a statistically reliable survey of SMGs. In this paper, we present a new calibration of the magphys SED modeling code that is optimized to fit these ultraviolet-to-radio SEDs of z>1 star-forming galaxies using an energy balance technique to connect the emission from stellar populations, dust attenuation, and dust emission in a physically consistent way. We derive statistically and physically robust estimates of the photometric redshifts and physical parameters (such as stellar masses, dust attenuation, star formation rates (SFRs), and dust masses) for the ALESS SMGs. We find that the ALESS SMGs have median stellar mass M{sub ∗}=8.9±0.1×10{sup 10} M{sub ⊙}, median SFR = 280±70 M{sub ⊙} yr{sup −1}, median overall V-band dust attenuation A{sub V}=1.9±0.2 mag, median dust mass M{sub dust}=(5.6±1.0)×10{sup 8} M{sub ⊙}, and median average dust temperature T{sub dust}≃40 K. We find that the average intrinsic SED of the ALESS SMGs resembles that of local ultra-luminous infrared galaxies in the infrared range, but the stellar emission of our average SMG is brighter and bluer, indicating lower dust attenuation, possibly because they are more extended. We explore how the average SEDs vary with different parameters (redshift, sub-millimeter flux, dust attenuation, and total infrared luminosity), and we provide a new set of SMG templates that can be used to interpret other SMG observations. To put the ALESS SMGs into context, we compare their stellar masses and SFRs with those of less actively star-forming galaxies at the same redshifts. We find that at z≃2, about half of the SMGs lie above the star-forming main sequence (with SFRs three times larger than normal galaxies of the same stellar mass), while half are consistent with being at the high-mass end of the main sequence. At higher redshifts (z≃3.5), the SMGs tend to have higher SFRs and stellar masses, but the fraction of SMGs that lie significantly above the main sequence decreases to less than a third.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Recovering Interstellar Gas Properties with Hi Spectral Lines: A Comparison between Synthetic Spectra and 21-SPONGE

We analyze synthetic neutral hydrogen (H i) absorption and emission spectral lines from a high-resolution, three-dimensional hydrodynamical simulation to quantify how well observational methods recover the physical properties of interstellar gas. We present a new method for uniformly decomposing H i spectral lines and estimating the properties of associated gas using the Autonomous Gaussian Decomposition (AGD) algorithm. We find that H i spectral lines recover physical structures in the simulation with excellent completeness at high Galactic latitude, and this completeness declines with decreasing latitude due to strong velocity-blending of spectral lines. The temperature and column density inferred from our decomposition and radiative transfer method agree with the simulated values within a factor of <2 for the majority of gas structures. We next compare synthetic spectra with observations from the 21-SPONGE survey at the Karl G. Jansky Very Large Array using AGD. We find more components per line of sight in 21-SPONGE than in synthetic spectra, which reflects insufficient simulated gas scale heights and the limitations of local box simulations. In addition, we find a significant population of low-optical depth, broad absorption components in the synthetic data which are not seen in 21-SPONGE. This population is not obvious in integrated or per-channel diagnostics, and reflects the benefit of studying velocity-resolved components. The discrepant components correspond to the highest spin temperatures (1000<T{sub s}<4000 K), which are not seen in 21-SPONGE despite sufficient observational sensitivity. We demonstrate that our analysis method is a powerful tool for diagnosing neutral interstellar medium conditions, and future work is needed to improve observational statistics and implementation of simulated physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Anharmonic densities of states: A general dynamics-based solution

Density of states is a fundamental physical characteristic that lies at the foundation of statistical mechanics and theoretical constructs that derive from them (e.g., kinetic rate theories, phase diagrams, and others). Even though most real physical systems are anharmonic, the vibrational density of states is customarily treated within the harmonic approximation, or with some partial, often limited, account for anharmonicity. The reason for this is that the problem of anharmonic densities of states stubbornly resisted a general and exact, yet convenient and straightforward in applications, solution. Here we formulate such a solution within both classical and quantum mechanics. It is based on actual dynamical behavior of systems as a function of energy and as observed, or monitored, on a chosen time scale, short or long. As a consequence, the resulting anharmonic densities of states are fully dynamically informed and, in general, time-dependent. As such, they lay the ground for formulation of new statistical mechanical frameworks that incorporate time and are ergodic, by construction, with respect to actual dynamical behavior of systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗