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

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Disentangling the physical parameters of gaseous nebulae and galaxies

Abstract We present an analysis to disentangle the connection between physical quantities that characterize the conditions of ionized H ii regions – metallicity (Z), ionization parameter (U), and electron density (ne) – and the global stellar mass (M*) and specific star formation rate (sSFR = SFR/M*) of the host galaxies. We construct composite spectra of galaxies at 0.027 ≤ z ≤ 0.25 from Sloan Digital Sky Survey, separating the sample into bins of M* and sSFR, and estimate the nebular conditions from the emission-line flux ratios. Specially, metallicity is estimated from the direct method based on the faint auroral lines [O iii]λ4363 and [O ii]λλ7320,7330. The derived metallicities cover a range of 12 + log O/H ∼ 7.6–8.9. It is found that the three nebular parameters, Z, U, and ne, are tightly correlated with the location in the M*–sSFR plane. With simple physically motivated ansätze, we derive scaling relations between these physical quantities by performing multiregression analysis. In particular, we find that U is primarily controlled by sSFR, as U∝sSFR0.43, but also depends significantly on both Z and ne. The derived partial dependence of U∝Z−0.36 is weaker than the apparent correlation (U∝Z−1.52). The partial dependence of U on ne is found to be $U \propto n_\mathrm{e}^{-0.29}$. The scaling relations we derived are in agreement with predictions from theoretical models and observations of each aspect of the link between these quantities. Our results provide a useful set of equations to predict the nebular conditions and emission-line fluxes of galaxies in semi-analytic models.

Kashino, Daichi↗
DOE OSTI2023

Disentangling the effects of non-adiabatic interactions upon ion self-diffusion within warm dense hydrogen

Warm dense matter is a material state in the region of parameter space connecting condensed matter to classical plasma physics. In this intermediate regime, we investigate the significance of non-adiabatic electron-ion interactions upon ion dynamics. To disentangle non-adiabatic from adiabatic electron-ion interactions, we compare the ion self-diffusion coefficient from the non-adiabatic electron force field computational model with an adiabatic, classical molecular dynamics simulation. A classical pair potential developed through a force-matching algorithm ensures the only difference between the models is due to the electronic inertia. Here, we implement this new method to characterize non-adiabatic effects on the self-diffusion of warm dense hydrogen over a wide range of temperatures and densities. Ultimately we show that the impact of non-adiabatic effects is negligible for equilibrium ion dynamics in warm dense hydrogen.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2010

Disentanglement of three-qubit states in a noisy environment

By applying a modified conjugate gradient method in the evaluation of three-qubit residual entanglement, the disentanglement of three-qubit states in an amplitude-damping and dephasing environment is investigated numerically. It is found that the decay of tripartite entanglement is faster than bipartite entanglement in the same qubits-noise system, which indicates that multipartite entanglement is more fragile than bipartite entanglement in resisting quantum noises. Similar to the case of a two-qubit system, three-qubit entanglement subject to an open environment may also disappear abruptly (sudden death) or decrease asymptotically, which is dependent on the conditions of the initially entangled quantum state and the properties of quantum noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Disentanglement of electron dynamics and space-charge effects in time-resolved photoemission from h-BN/Ni(111)

We observe time-resolved and polarization dependent two-, three-, and four-photon transitions from a Ni(111) surface covered with a monolayer of hexagonal boron nitride. The spectra show features due to transitions involving two unoccupied intermediate states: the n=1 image potential state of Ni(111) and a boron nitride-related interface state. We use these transitions in order to track the effects of space-charge on the spectra in view of pump-probe experiments, at high excitations densities. A simple model is presented, which reproduces the measured energy shifts and broadenings in great detail, allowing the ultrafast dynamics and the space-charge effects to be disentangled. Moreover, owing to the high excitation densities an additional particular three-photon transition via both the interface state and a virtual intermediate state could be measured and identified. The polarization-dependent transient of this transition has successfully been simulated, allowing the lifetime of the involved intermediate state to be extracted from the data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Disentangling correlations in multiple parton interactions

Multiple Parton Interactions are the tool to obtain information on the correlations between partons in the hadron structure. Partons may be correlated in all degrees of freedom and all different correlation terms contribute to the cross section. The contributions due to the different parton flavors can be isolated, at least to some extent, by selecting properly the final state. In the case of high energy proton-proton collisions, the effects of correlations in the transverse coordinates and in fractional momenta are, on the contrary, unavoidably mixed in the final observables. The standard way to quantify the strength of double parton interactions is by the value of the effective cross section and a small value of the effective cross section may be originated both by the relatively short transverse distance between the pairs of partons undergoing the double interaction and by a large dispersion of the distribution in multiplicity of the multiparton distributions. The aim of the present paper is to show how the effects of longitudinal and transverse correlations may be disentangled by taking into account the additional information provided by double parton interactions in high energy proton-deuteron collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Disentangled Cooperative Orderings in Artificial Rare-Earth Nickelates

Coupled transitions between distinct ordered phases are important aspects behind the rich phase complexity of correlated oxides that hinder our understanding of the underlying phenomena. For this reason, fundamental control over complex transitions has become a leading motivation of the designer approach to materials. We have devised a series of new superlattices by combining a Mott insulator and a correlated metal to form ultrashort period superlattices, which allow one to disentangle the simultaneous orderings in RENiO 3 . Tailoring an incommensurate heterostructure period relative to the bulk charge ordering pattern suppresses the charge order transition while preserving metal-insulator and antiferromagnetic transitions. Such selective decoupling of the entangled phases resolves the long-standing puzzle about the driving force behind the metal-insulator transition and points to the site-selective Mott transition as the operative mechanism. In conclusion, this designer approach emphasizes the potential of heterointerfaces for selective control of simultaneous transitions in complex materials with entwined broken symmetries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Disentangling Sources of Momentum Fluctuations in Xe+Xe and Pb+Pb Collisions with the ATLAS Detector

High-energy nuclear collisions create a quark-gluon plasma, whose initial condition and subsequent expansion vary from event to event, impacting the distribution of the eventwise average transverse momentum [𝑃⁡([𝑝 T ])]. Disentangling the contributions from fluctuations in the nuclear overlap size (geometrical component) and other sources at a fixed size (intrinsic component) remains a challenge. This problem is addressed by measuring the mean, variance, and skewness of 𝑃⁡([𝑝 T ]) in 208 Pb + 208 Pb and 129 Xe + 129 Xe collisions at $\sqrt{S{NN}}$ = 5.02 and 5.44 TeV, respectively, using the ATLAS detector at the LHC. All observables show distinct features in ultracentral collisions, which are explained by a suppression of the geometrical component as the overlap area reaches its maximum. These results demonstrate a new technique to separate geometrical and intrinsic fluctuations, providing constraints on initial conditions and properties of the quark-gluon plasma, such as the speed of sound.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Disentangling the role of bond lengths and orbital symmetries in controlling $T_c$ of optimally doped YBa 2 Cu 3 O 7

Optimally doped YBa 2 Cu 3 O 7 (YBCO) has a high critical temperature, at 92 K. It is largely believed that Cooper pairs form in YBCO and other cuprates because of spin fluctuations, but the issue and the detailed mechanism are far from settled. In the present work, we employ a state-of-the-art first-principles ability to compute both the low- and high-energy spin fluctuations in optimally doped YBCO. We benchmark our results against recent inelastic neutron scattering and resonant inelastic x-ray scattering measurements. Further, we use strain as an external parameter to modulate the spin fluctuations and superconductivity. We disentangle the roles of barium-apical oxygen hybridization, interlayer coupling, and orbital symmetries by applying an idealized strain, and also a strain with a fully relaxed structure. We show that shortening the distance between Cu layers is conducive to enhanced Fermi surface nesting, which increases spin fluctuations and drives up $T_c$. However, when the structure is fully relaxed, electrons flow to the $d_{z^2}$ orbital as a consequence of a shortened Ba-O bond, which is detrimental for superconductivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Disentangling the impact of quasiparticles and two-level systems on the statistics of superconducting-qubit lifetime

Temporal fluctuations in the superconducting qubit lifetime, T 1 , present additional challenges in the pursuit of fault-tolerant quantum computing. Although the exact mechanisms remain unclear, T 1 fluctuations are generally attributed to strong coupling between the qubit and a few near-resonant two-level systems (TLSs), which can exchange energy with an ensemble of thermally fluctuating two-level fluctuators (TLFs) at low frequencies. Here, we report T 1 measurements of qubits with varying geometrical footprints and surface dielectrics as a function of temperature. By analyzing the noise spectrum of the qubit depolarization rate, Γ 1 = 1 / T 1 , we disentangle the contributions of TLSs, nonequilibrium quasiparticles (QPs), and equilibrium (thermally excited) QPs to the variance in Γ 1 . We find that the Γ 1 variance in qubits with smaller footprints is more susceptible to QP and TLS fluctuations than that in larger-footprint qubits. Furthermore, the QP-induced variances in all qubits align with the theoretical framework of QP diffusion and fluctuation. These findings offer valuable insights for future qubit design and engineering optimization.

Zhu, Shaojiang [Fermilab] (ORCID:0000000293180092)↗
DOE OSTI2025

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2017

Disentangling the long-term effects of disturbance on soil biogeochemistry in a wet tropical forest ecosystem

Climate change is increasing the intensity of severe tropical storms and cyclones (also referred to as hurricanes or typhoons), with major implications for tropical forest structure and function. These changes in disturbance regime are likely to play an important role in regulating ecosystem carbon (C) and nutrient dynamics in tropical and subtropical forests. Canopy opening and debris deposition resulting from severe storms have complex and interacting effects on ecosystem biogeochemistry. Disentangling these complex effects will be critical to better understand the long-term implications of climate change on ecosystem C and nutrient dynamics. In this paper, we used a well-replicated, long-term (10 years) canopy and debris manipulation experiment in a wet tropical forest to determine the separate and combined effects of canopy opening and debris deposition on soil C and nutrients throughout the soil profile (1 m). Debris deposition alone resulted in higher soil C and N concentrations, both at the surface (0–10 cm) and at depth (50–80 cm). Concentrations of NaOH-organic P also increased significantly in the debris deposition only treatment (20–90 cm depth), as did NaOH-total P (20–50 cm depth). Canopy opening, both with and without debris deposition, significantly increased NaOH-inorganic P concentrations from 70 to 90 cm depth. Soil iron concentrations were a strong predictor of both C and P patterns throughout the soil profile. Our results demonstrate that both surface- and subsoils have the potential to significantly increase C and nutrient storage a decade after the sudden deposition of disturbance-related organic debris. Our results also show that these effects may be partially offset by rapid decomposition and decreases in litterfall associated with canopy opening. Finally, the significant effects of debris deposition on soil C and nutrient concentrations at depth (>50 cm), suggest that deep soils are more dynamic than previously believed, and can serve as sinks of C and nutrients derived from disturbance-induced pulses of organic matter inputs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Holo-Omics disentangle drought response and biotic interactions among plant, endophyte and pathogen

Holo-omics provide a novel opportunity to study the interactions among fungi from different functional guilds in host plants in field conditions. We address the entangled responses of plant pathogenic and endophytic fungi associated with sorghum when droughted through the assembly of the most abundant fungal, endophyte genome from rhizospheric metagenomic sequences followed by a comparison of its metatranscriptome with the host plant metabolome and transcriptome. The rise in relative abundance of endophytic Acremonium persicinum (operational taxonomic unit 5 (OTU5)) in drought co-occurs with a rise in fungal membrane dynamics and plant metabolites, led by ethanolamine, a key phospholipid membrane component. The negative association between endophytic A. persicinum (OTU5) and plant pathogenic fungi co-occurs with a rise in expression of the endophyte's biosynthetic gene clusters coding for secondary compounds. Endophytic A. persicinum (OTU5) and plant pathogenic fungi are negatively associated under preflowering drought but not under postflowering drought, likely a consequence of variation in fungal fitness responses to changes in the availability of water and niche space caused by plant maturation over the growing season. Our findings suggest that the dynamic biotic interactions among host, beneficial and harmful microbiota in a changing environment can be disentangled by a blending of field observation, laboratory validation, holo-omics and ecological modelling.

Chen, Peilin↗
DOE OSTI2012

Feynman method for disentangling operators and a singular oscillator

The problem of the evolution of a singular quantum oscillator with a frequency exhibiting an arbitrary time dependence has been solved. The probabilities w{sub mn} of transitions in the oscillator spectrum and generating functions have been calculated, and the sum rules for w{sub mn} have been derived. The calculations are based on the Feynman disentangling method and the theory of representations of the SU(1, 1) group.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

MSU Disentanglement Analysis Software

This software is used to disentangle the forced-versus-unforced components of tropospheric temperature change over the satellite era (after 1979) using maps of surface temperature change as a predictor. In general, the software assembles training datasets (from pre-computed surface temperature trend maps and domain averaged tropospheric warming rates), trains statistical/machine learning (ML) algorithms, applies the trained statistical/ML model to climate model data and observations, and then saves the results. A leave-one-out approach is used in which the statistical/ML models are iteratively trained on (N- 1) climate model and then applied to the remaining climate model (and observations). Each model includes a large ensemble (i.e., >10) of model simulations. The software relies on scikit-learn ridge regression, PLS regression, and neural network algorithms.

Po-Chedley, StephenD↗
DOE OSTI2025

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability: Supporting Data and Code

This repository contains R code and associated datasets for reproducing the analysis described in the manuscript titled “Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability” (DOI: 10.1029/2024JG008604). The provided scripts facilitate a comprehensive analysis of snow depth variability influenced by microtopography and vegetation distribution in a subarctic watershed. Included datasets are high-resolution spatial maps of snow depth, terrain elevation, vegetation height, and distance from shrubs taller than 1 meter, all formatted as text files (.txt). These data are fully describe in doi:10.15485/2316038. Users can adapt the provided R scripts to accommodate different data formats or larger spatial domains, noting that some output files may require modification due to their size.The code includes implementations for boosted regression tree analysis adapted from methods outlined in Elith et al. (2008). Users interested in understanding or modeling landscape-scale snow distribution patterns, particularly in Arctic or subarctic ecosystems, will find this package useful. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Disentangling Beam Losses in The Fermilab Main Injector Enclosure Using Real-Time Edge AI

The Fermilab Main Injector enclosure houses two accelerators, the Main Injector and Recycler Ring. During normal operation, high intensity proton beams exist simultaneously in both. The two accelerators share the same beam loss monitors (BLM) and monitoring system. Deciphering the origin of any of the 260 BLM readings is often difficult. The (Accelerator) Real-time Edge AI for Distributed Systems project, or READS, has developed an AI/ML model, and implemented it on fast FPGA hardware, that disentangles mixed beam losses and attributes probabilities to each BLM as to which machine(s) the loss originated from in real-time. The model inferences are then streamed to the Fermilab accelerator controls network (ACNET) where they are available for operators and experts alike to aid in tuning the machines.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Semantic Regression for Disentangling Beam Losses in the Fermilab Main Injector and Recycler

Fermilab’s Main Injector enclosure houses two accelerators: the Main Injector (MI) and the Recycler (RR). In periods of joint operation, when both machines contain high intensity beam, radiative beam losses from MI and RR overlap on the enclosure’s beam loss monitoring (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financial and experimental cost. In this work, we introduce a novel neural approach for automatically disentangling each machine’s contributions to those measured losses. Using a continuous adaptation of the popular UNet architecture in conjunction with a novel data augmentation scheme, our model accurately infers the machine of origin on a per-BLM basis in periods of joint and independent operation. Crucially, by extracting beam loss information at varying receptive fields, the method is capable of learning both local and global machine signatures and producing high quality inferences using only raw BLM loss measurements.

43 PARTICLE ACCELERATORS↗