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DOE OSTI2024

Statistical modelling and Bayesian inversion for a Compton imaging system: application to radioactive source localization

Abstract This paper presents a statistical forward model for a Compton imaging system, called Compton imager. This system, under development at the University of Illinois Urbana Champaign, is a variant of Compton cameras with a single type of sensors which can simultaneously act as scatterers and absorbers. This imager is convenient for imaging situations requiring a wide field of view. The proposed statistical forward model is then used to solve the inverse problem of estimating the location and energy of point-like sources from observed data. This inverse problem is formulated and solved in a Bayesian framework by using a Metropolis within Gibbs algorithm for the estimation of the location, and an expectation-maximization algorithm for the estimation of the energy. This approach leads to more accurate estimation when compared with the deterministic standard back-projection approach, with the additional benefit of uncertainty quantification in the low photon imaging setting.

Tarpau, Cécilia (ORCID:0000000286539490)↗
DOE OSTI2023

A simple data-driven level finding method of many-electron atoms and heavy nuclei based on statistical outlier detection

Here, we report a simple and pure data-driven method to find new energy levels of quantum many-body systems only from observed line wavelengths. In our method, all the possible combinations are computed from known energy levels and wavelengths of unidentified lines. As each excited state exhibits many transition lines to different lower levels, the true levels should be reconstructed coincidentally from many level-line combinations, while the wrong combinations distribute randomly. Such a coincidence can be easily detected statistically. We demonstrate this statistical method by finding new levels for various atomic and nuclear systems from unidentified line lists available online.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Turbulence statistical analysis of the L-H transition and RMPs in KSTAR

Here, we investigate the turbulence statistics associated with low-to-high confinement (L-H) transitions and externally applied resonant magnetic perturbations (RMPs) in KSTAR. Time-series fluctuations of electron density n e , electron temperature T e , and the time derivative of the poloidal magnetic field dB θ /dt (Mirnov coils) are analysed using information-geometric measures (information rate Γ and information length $\mathcal{L}$ = ∫ Γ dt), together with kurtosis κ and variance σ 2 . In low-density upper single-null plasmas (n e ~ 1.2 x 10 19 m -3 ), a ~80 kHz magnetic mode coupling n e , T e , dB θ /dt and emerges prior to the L-H transition and persists into the edge-localised modes H-mode. Edge-localised RMPs (ERMPs) suppress this coherent mode but enhance intermittency, producing frequent bursts that abruptly reshape the time-dependent probability density functions (PDFs) and generate large spikes in Γ (with smaller changes in κ), signalling ERMP-driven departures from quasi-stationarity. The impact of ERMPs on background fluctuation levels depends on density, radial location, and the fluctuating variable itself ($\tilde{n}$, $\tilde{T}$, $\dot{B}$ θ ), whereas $\mathcal{L}$ provides a robust, regime-agnostic measure of cumulative statistical reorganisation and spatial decorrelation. In particular, at low density we observe weaker coupling between $\tilde{n}$ and $\tilde{T}$, along with a tendency toward decreased radial correlation-most clearly for $\tilde{T}$-under ERMPs. Overall, information geometry cleanly captures intermittent events, quantifies non-equilibrium PDF evolution, and offers a compact, cross-diagnostic metric for assessing resonant magnetic perturbation effects on edge transport and correlation across densities, radial locations, and confinement states.

Kim, Eun-jin [Coventry Univ. (United Kingdom); Seo↗
DOE OSTI2014

CMB statistical anisotropy from noncommutative gravitational waves

Primordial statistical anisotropy is a key indicator to investigate early Universe models and has been probed by the cosmic microwave background (CMB) anisotropies. In this paper, we examine tensor-mode CMB fluctuations generated from anisotropic gravitational waves, parametrised by P{sub h}(k) = P{sub h}{sup (0)}(k) [ 1 + ∑{sub LM} f{sub L}(k) g{sub LM} Y{sub LM} ( k-circumflex )], where P{sub h}{sup (0)}(k) is the usual scale-invariant power spectrum. Such anisotropic tensor fluctuations may arise from an inflationary model with noncommutativity of fields. It is verified that in this model, an isotropic component and a quadrupole asymmetry with f{sub 0}(k) = f{sub 2}(k) ∝ k{sup -2} are created and hence highly red-tilted off-diagonal components arise in the CMB power spectra, namely ℓ{sub 2} = ℓ{sub 1} ± 2 in TT, TE, EE and BB, and ℓ{sub 2} = ℓ{sub 1} ± 1 in TB and EB. We find that B-mode polarisation is more sensitive to such signals than temperature and E-mode polarisation due to the smallness of large-scale cosmic variance and we can potentially measure g{sub 00} = 30 and g{sub 2M} = 58 at 68% CL in a cosmic-variance-limited experiment. Such a level of signal may be measured in a PRISM like experiment, while the instrumental noise contaminates it in the Planck experiment. These results imply that it is impossible to measure the noncommutative parameter if it is small enough for the perturbative treatment to be valid. Our formalism and methodology for dealing with the CMB tensor statistical anisotropy are general and straightforwardly applicable to other early Universe models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

CMB statistical anisotropies of classical and quantum origins

We examine the impact of different anisotropic relics on inflation, in particular the predictions on the density perturbations. These relics can be the source of the large scale anomalies in the cosmic microwave background. There are two different types of background relics, one from the matter sector and the other purely from the metric. Although the angular-dependence of the statistical anisotropy in both cases are degenerate, the scale-dependence are observationally distinctive. In addition, we demonstrate that non-Bunch-Davies vacuum states can extend the statistical anisotropy to much shorter scales, and leave a scale-dependence that is insensitive to the different backgrounds but sensitive to the initial quantum state.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Origin of structure: statistical characterization of the primordial density fluctuations and the collapse of the wave function

The statistical properties of the primordial density perturbations has been considered in the past decade as a powerful probe of the physical processes taking place in the early universe. Within the inflationary paradigm, the properties of the bispectrum are one of the keys that serves to discriminate among competing scenarios concerning the details of the origin of cosmological perturbations. However, all of the scenarios, based on the conventional approach to the so-called ''quantum-to-classical transition'' during inflation, lack the ability to point out the precise physical mechanism responsible for generating the inhomogeneity and anisotropy of our universe starting from and exactly homogeneous and isotropic vacuum state associated with the early inflationary regime. In past works, we have shown that the proposals involving a spontaneous dynamical reduction of the quantum state provide plausible explanations for the birth of said primordial inhomogeneities and anisotropies. In the present manuscript we show that, when considering within the context of such proposals, the characterization of the spectrum and bispectrum turn out to be quite different from those found in the traditional approach, and in particular, some of the statistical features, must be treated in a different way leading to some rather different conclusions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Parity-violating CMB correlators with non-decaying statistical anisotropy

We examine the effect induced on cosmological correlators by the simultaneous breaking of parity and of statistical isotropy. As an example of this, we compute the scalar-scalar, scalar-tensor, tensor-tensor and scalar-scalar-scalar cosmological correlators in presence of the coupling L = f(φ) ( − 1/4 F{sup 2} + γ/4 F ∼F ) between the inflaton φ and a vector field with vacuum expectation value A. For a suitably chosen function f, the energy in the vector field ρ{sub A} does not decay during inflation. This results in nearly scale-invariant signatures of broken statistical isotropy and parity. Specifically, we find that the scalar-scalar correlator of primordial curvature perturbations includes a quadrupolar anisotropy, P{sub ζ}(k) = P(k)[1+g{sub *}( k-circumflex ⋅Â){sup 2}], and a (angle-averaged) scalar bispectrum that is a linear combination of the first 3 Legendre polynomials, B{sub ζ}(k{sub 1}, k{sub 2}, k{sub 3}) = ∑{sub L} c{sub L} P{sub L} ( k-circumflex {sub 1} ⋅ k-circumflex {sub 2}) P(k{sub 1}) P(k{sub 2}) + 2 perms , with c{sub 0}:c{sub 1}:c{sub 2}=2-3:1 (c{sub 1}≠0 is a consequence of parity violation, corresponding to the constant 0γ ≠ ). The latter is one of the main results of this paper, which provides for the first time a clear example of an inflationary model where a non-negligible c{sub 1} contribution to the bispectrum is generated. The scalar-tensor and tensor-tensor correlators induce characteristic signatures in the Cosmic Microwave Background temperature anisotropies (T) and polarization (E/B modes); namely, non-diagonal contributions to (a{sub ℓ1m1}a{sup *}{sub ℓ2m2}), with |ℓ{sub 1} − ℓ{sub 2}| = 1 in TT, TE, EE and BB, and |ℓ{sub 1} − ℓ{sub 2}| = 2 in TB and EB. The latest CMB bounds on the scalar observables (g{sub *}, c{sub 0}, c{sub 1} and c{sub 2}), translate into the upper limit ρ{sub A} / ρ{sub φ} ∼< 10{sup −9} at 0γ=. We find that the upper limit on the vector energy density becomes much more stringent as γ grows.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Effective field theory of statistical anisotropies for primordial bispectrum and gravitational waves

We present the effective field theory studies of primordial statistical anisotropies in models of anisotropic inflation. The general action in unitary gauge is presented to calculate the leading interactions between the gauge field fluctuations, the curvature perturbations and the tensor perturbations. The anisotropies in scalar power spectrum and bispectrum are calculated and the dependence of these anisotropies to EFT couplings are presented. In addition, we calculate the statistical anisotropy in tensor power spectrum and the scalar-tensor cross correlation. Our EFT approach incorporates anisotropies generated in models with non-trivial speed for the gauge field fluctuations and sound speed for scalar perturbations such as in DBI inflation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

DESI 2024: reconstructing dark energy using crossing statistics with DESI DR1 BAO data

Here, we implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negligible presence of dark energy at z ≳ 1, at varying significance depending on data sets combined. In all these reconstructions, the cosmological constant lies outside the 95% confidence intervals for some redshift ranges. This dark energy behaviour, reconstructed using Crossing Statistics, is in agreement with results from the conventional w 0 –w a dark energy equation of state parametrization reported in the DESI Key cosmology paper. Our results add an extensive class of model-agnostic reconstructions with acceptable fits to the data, including models where cosmic acceleration slows down at low redshifts. We also report constraints on H 0 r d from our model-agnostic analysis, independent of the pre-recombination physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

thornado-transport: IMEX schemes for two-moment neutrino transport respecting Fermi-Dirac statistics

We develop implicit-explicit (IMEX) schemes for neutrino transport in a background material in the context of a two-moment model that evolves the angular moments of a neutrino phase-space distribution function. Considering the upper and lower bounds that are introduced by Pauli's exclusion principle on the moments, an algebraic moment closure based on Fermi-Dirac statistics and a convex-invariant time integrator both are demanded. A finite-volume/first-order discontinuous Galerkin(DG) method is used to illustrate how an algebraic moment closure based on Fermi-Dirac statistics is needed to satisfy the bounds. Several algebraic closures are compared with these bounds in mind, and the Cernohorsky and Bludman closure, which satisfies the bounds, is chosen for our IMEX schemes. For the convex-invariant time integrator, two IMEX schemes named PD-ARS have been proposed. PD-ARS denotes a convex-invariant IMEX Runge-Kutta scheme that is high-order accurate in the streaming limit, and works well in the diffusion limit. Our two PD-ARS schemes use second-and third-order, explicit, strong-stability-preserving Runge-Kutta methods as their explicit part, respectively, and therefore are second-and third-order accurate in the streaming limit, respectively. The accuracy and convex-invariance of our PD-ARS schemes are demonstrated in the numerical tests with a third-order DG method for spatial discretization and a simple Lax-Friedrichs flux. The method has been implemented in our high-order neutrino-radiation hydrodynamics (thornado) toolkit. We show preliminary results employing tabulated neutrino opacities.

Chu, Ran↗
DOE OSTI2025

Improving seasonal precipitation forecasts in the Western United States through statistical downscaling

Abstract Seasonal precipitation forecasts in the western United States are critical resources for water resource management, especially during winter. While current seasonal forecasting systems provide monthly precipitation forecasts operationally, their coarse resolution limits their effectiveness in capturing the localized precipitation patterns and snowpack conditions essential for water resource managers in the mountainous regions. Here, analog statistical downscaling is demonstrated as an effective approach to enhance the spatial resolution of operational seasonal forecasts provided by the North American Multi-Model Ensemble. Downscaling was performed by building an analog ‘library’, in which corresponding model forecasts and observed values during the training period were stored. In the testing period, unseen model forecasts referenced the closest historical forecast from the analog library and applied the corresponding observational value for each point. This analysis indicates that downscaled products can capture localized features more accurately than the original coarse resolution forecasts, reducing forecast error across the western United States. Moreover, downscaling individual ensemble members—rather than downscaling the ensemble mean—further reduces forecasting error for their multi-model ensemble mean products. The greatest error reductions in the downscaled product, measured by root mean squared error (RMSE), were observed at low to mid-elevations (500–2000 meters), with 50%–70% improvement relative to the original forecasts. In the higher elevations (2000 meters and above), changes in RMSE relative to the original forecast were limited to 10%–30% improvements. The improvement is more substantial for forecast systems with 10 ensemble members compared to that with 4 members, but this relationship does not hold for the system with 24 ensemble members. These findings show that analog statistical downscaling can effectively address the spatial limitations of seasonal precipitation forecasts with minimal computational cost, providing a valuable framework for enhancing coarse resolution forecasting products while providing insights into the timing of ensemble mean calculations during the downscaling process.

Vernon, B. (ORCID:0009000891670689)↗
DOE OSTI2025

CoverM: read alignment statistics for metagenomics

SUMMARY: Genome-centric analysis of metagenomic samples is a powerful method for understanding the function of microbial communities. Calculating read coverage is a central part of analysis, enabling differential coverage binning for recovery of genomes and estimation of microbial community composition. Coverage is determined by processing read alignments to reference sequences of either contigs or genomes. Per-reference coverage is typically calculated in an ad-hoc manner, with each software package providing its own implementation and specific definition of coverage. Here we present a unified software package CoverM which calculates several coverage statistics for contigs and genomes in an ergonomic and flexible manner. It uses "Mosdepth arrays" for computational efficiency and avoids unnecessary I/O overhead by calculating coverage statistics from streamed read alignment results. AVAILABILITY AND IMPLEMENTATION: CoverM is free software available at https://github.com/wwood/coverm. CoverM is implemented in Rust, with Python (https://github.com/apcamargo/pycoverm) and Julia (https://github.com/JuliaBinaryWrappers/CoverM_jll.jl) interfaces.

Aroney, Samuel T N↗
DOE OSTI2021

Brightest cluster galaxies are statistically special from z = 0.3 to z = 1

ABSTRACT We study brightest cluster galaxies (BCGs) in ∼5000 galaxy clusters from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The sample is selected over an area of 830 deg2 and is uniformly distributed in redshift over the range of z = 0.3−1.0. The clusters have stellar masses in the range of 1011.8−1012.9M⊙. We compare the stellar mass of the BCGs in each cluster to what we would expect if their masses were drawn from the mass distribution of the other member galaxies of the clusters. The BCGs are found to be ‘special’, in the sense that they are not consistent with being a statistical extreme of the mass distribution of other cluster galaxies. This result is robust over the full range of cluster stellar masses and redshifts in the sample, indicating that BCGs are special up to a redshift of z = 1.0. However, BCGs with a large separation from the centre of the cluster are found to be consistent with being statistical extremes of the cluster member mass distribution. We discuss the implications of these findings for BCG formation scenarios.

Dalal, Roohi (ORCID:0000000279989899)↗
DOE OSTI2023

A framework to measure the properties of intergalactic metal systems with two-point flux statistics

ABSTRACT The abundance, temperature, and clustering of metals in the intergalactic medium are important parameters for understanding their cosmic evolution and quantifying their impact on cosmological analysis with the Ly α forest. The properties of these systems are typically measured from individual quasar spectra redward of the quasar’s Ly α emission line, yet that approach may provide biased results due to selection effects. We present an alternative approach to measure these properties in an unbiased manner with the two-point statistics commonly employed to quantify large-scale structure. Our model treats the observed flux of a large sample of quasar spectra as a continuous field and describes the one-dimensional, two-point statistics of this field with three parameters per ion: the abundance (column density distribution), temperature (Doppler parameter), and clustering (cloud–cloud correlation function). We demonstrate this approach on multiple ions (e.g. ${\rm C\, \small {\rm IV}}$ , ${\rm Si\, \small {\rm IV}}$ , and ${\rm Mg\, \small {\rm II}}$ ) with early data from the Dark Energy Spectroscopic Instrument (DESI) and high-resolution spectra from the literature. Our initial results show some evidence that the ${\rm C\, \small {\rm IV}}$ abundance is higher than previous measurements and evidence for abundance evolution over time. The first full year of DESI observations will have over an order of magnitude more quasar spectra than this study. In a future paper, we will use those data to measure the growth of clustering and its impact on the Ly α forest, as well as test other DESI analysis infrastructure such as the pipeline noise estimates and the resolution matrix.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Halo exclusion criteria impacts halo statistics

ABSTRACT Every halo-finding algorithm must make a critical yet relatively arbitrary choice: it must decide which structures are parent haloes, and which structures are subhaloes of larger haloes. We refer to this choice as percolation. We demonstrate that the choice of percolation impacts the statistical properties of the resulting halo catalogue. Specifically, we modify the halo-finding algorithm rockstar to construct three different halo catalogues from the same simulation data, each with identical mass definitions, but different choice of percolation. The resulting haloes exhibit significant differences in both halo abundance and clustering properties. Differences in the halo mass function reach 6 per cent for haloes of mass $10^{13}\ h^{-1}\ {\rm {\rm M}_{\odot }}$, larger than the few per cent precision necessary for current cluster abundance experiments such as the Dark Energy Survey. Comparable differences are observed in the large-scale clustering bias, while differences in the halo–matter correlation function reach 30 per cent on translinear scales. These effects can bias weak-lensing estimates of cluster masses at a level comparable to the statistical precision of current state-of-the-art experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

ProteoSign: an end-user online differential proteomics statistical analysis platform

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a userfriendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ ProteoSign.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Calibration and Statistical Performance of Al2O3: C Optically Stimulated Luminescent Dosimeters With and Without Annealing Using a 137Cs Source

A series of experiments were conducted using commercially available Al 2 O 3 :C optically stimulated luminescent dosimeters to provide a technical basis for their precise calibration and statistical performance at irradiated air kerma doses between 0.02 mGy and 5 mGy using 137 Cs. This study examines the dose response linearity, studies the background signal for annealed dosimeters, and compares the statistical performance of dosimeters that were annealed and not annealed prior to their irradiation and readout. The average and standard deviation for the response of groups of dosimeters annealed and nonannealed prior to their irradiation were determined at each delivered dose. The batch of dosimeters that were annealed prior to their irradiation exhibited a coefficient of variation in its mean dose response below 10% when using three or more irradiation trials at each delivered air kerma dose between 0.02 mGy and 5m Gy. The reader calibration factor was calculated using the response of the annealed batch of dosimeters and was determined to be 756 ± 7 photomultiplier tube counts perm Gy. Best estimates of the individual sensitivity factors were determined to be between 0.79 and 1.12 for the annealed batch of dosimeters. The minimum number of irradiations required to accurately determine the sensitivity factor of each individual dosimeter is reported with the recommended reader and dosimeter calibration procedures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Sensitive Detection of Structural Differences using a Statistical Framework for Comparative Crystallography

Chemical and conformational changes underlie the functional cycles of proteins. Comparative crystallography can reveal these changes over time, over ligands, and over chemical and physical perturbations in atomic detail. A key difficulty, however, is that the resulting observations must be placed on the same scale by correcting for experimental factors. We recently introduced a Bayesian framework for correcting (scaling) X-ray diffraction data by combining deep learning with statistical priors informed by crystallographic theory. To scale comparative crystallography data, we here combine this framework with a multivariate statistical theory of comparative crystallography. By doing so, we find strong improvements in the detection of protein dynamics, element-specific anomalous signal, and the binding of drug fragments.

Hekstra, Doeke R. [Harvard Univ., Cambridge, MA (U↗