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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Relativistic Hartree–Fock chiral Lagrangians with confinement, nucleon finite size and short-range effects

A relativistic Hartree–Fock Lagrangian including a chiral potential and nucleon polarisation is investigated in hopes of providing a better description of dense nuclear matter. Here, we fully consider the contribution of the exchange Fock term to the energy and the self-energies, and in addition we investigate the nucleon’s compositeness and finite size effects (confinement and form factors) and short range correlations modeled by a Jastrow ansatz. These effects are added step by step, such that their impact on the dense matter properties can be analysed in details. The parameters of the model are adjusted to reproduce fundamental properties related to the QCD theory at low energy, such as the chiral symmetry breaking, nucleon’s quark substructure and Lattice-QCD predictions, as well as two empirical properties at saturation: the binding energy and the density. All other empirical parameters, e.g., symmetry energy and its slope, incompressibility modulus, effective mass, as well as spin–isospin Landau–Midgal parameter are predictions of the models and can be used to evaluate the gain of the different approximation schemes in describing nuclear properties. Bayesian statistics is employed in order to propagate parameter uncertainties into predictions for the nuclear matter properties. We show that the splitting of the effective Landau mass is largely influenced by the value of the ρ T coupling, and we show that the fit to the symmetry energy, which induces an increase of the coupling constant g ρ by about 20–25% compared to the case where it is fixed by the quark model, provides a very good EoS compatible with the present nuclear physics knowledge.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

QLBT: a linear Boltzmann transport model for heavy quarks in a quark-gluon plasma of quasi-particles

Abstract We develop a new heavy quark transport model, QLBT, to simulate the dynamical propagation of heavy quarks inside the quark-gluon plasma (QGP) created in relativistic heavy-ion collisions. Our QLBT model is based on the linear Boltzmann transport (LBT) model with the ideal QGP replaced by a collection of quasi-particles to account for the non-perturbative interactions among quarks and gluons of the hot QGP. The thermal masses of quasi-particles are fitted to the equation of state from lattice QCD simulations using the Bayesian statistical analysis method. Combining QLBT with our advanced hybrid fragmentation-coalescence hadronization approach, we calculate the nuclear modification factor $$R_\mathrm {AA}$$ R AA and the elliptic flow $$v_2$$ v 2 of D mesons at the Relativistic Heavy-Ion Collider and the Large Hadron Collider. By comparing our QLBT calculation to the experimental data on the D meson $$R_\mathrm {AA}$$ R AA and $$v_2$$ v 2 , we extract the heavy quark transport parameter $$\hat{q}$$ q ^ and diffusion coefficient $$D_\mathrm {s}$$ D s in the temperature range of $$1-4~T_\mathrm {c}$$ 1 - 4 T c , and compare them with the lattice QCD results and other phenomenological studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

EFBMC

SAND2026-23986O EFBMC performs elastic Bayesian model calibration by applying Bayesian statistics and functional analysis. The software provides Python, R, and MATLAB scripts that enable users to calibrate models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tucker, J. Derek [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2016

Uncertainty Quantification in Climate Modeling and Projection

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop reported herein aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

A New Ensemble of Perturbed-Input-Parameter Simulations by the Community Atmosphere Model

Uncertainty quantification (UQ) is a fundamental challenge in the numerical simulation of Earth's weather and climate, and other complex systems. It entails much more than attaching defensible error bars to predictions: in particular it includes assessing low-probability but high-consequence events. To achieve these goals with models containing a large number of uncertain input parameters, structural uncertainties, etc., raw computational power is needed. An automated, self-adapting search of the possible model configurations is also useful. Our UQ initiative at the Lawrence Livermore National Laboratory has produced the most extensive set to date of simulations from the US Community Atmosphere Model. We are examining output from about 3,000 twelve-year climate simulations generated with a specialized UQ software framework, and assessing the model's accuracy as a function of 21 to 28 uncertain input parameter values. Most of the input parameters we vary are related to the boundary layer, clouds, and other sub-grid scale processes. Our simulations prescribe surface boundary conditions (sea surface temperatures and sea ice amounts) to match recent observations. Fully searching this 21+ dimensional space is impossible, but sensitivity and ranking algorithms can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination. Bayesian statistical constraints, employing a variety of climate observations as metrics, also seem promising. Observational constraints will be important in the next step of our project, which will compute sea surface temperatures and sea ice interactively, and will study climate change due to increasing atmospheric carbon dioxide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Chicago Area Waterway System Microbiome Research

This report summarizes the research conducted by Argonne National Laboratory (Argonne) for the Metropolitan Water Reclamation District of Greater Chicago (MWRD) for the first five years (2013-2017) of a seven-year study with emphasis on the impact of disinfection (2016-2017) on the microbial community of the Chicago Area Waterway System (CAWS). The study examines microbial communities following disinfection of secondary treated effluents at the T.J. O’Brien (UV) and Calumet (chlorine and dechlorination) Water Reclamation Plants (WRPs) and the phased implementation of the Tunnel and Reservoir Plan (TARP). The Thornton Composite Reservoir (TCR) was completed in 2015. It provides 7.9 billion gallons of storage and since its completion has captured more than 11.0 billion gallons of combined stormwater and sewage from Calumet WRP that would otherwise overflow into CAWS in rainy weather. In addition to the effects of TARP and disinfection, we present an analysis of potential sources of the microbes found in the CAWS and the results of 16S rRNA amplicon gene sequencing which was used to characterize microbial community variability as a function of location, season, and environmental conditions. A total of 2,077 samples were collected from 2013 to 2017 from WRPs and CAWS and analyzed using high-throughput sequencing. The whole microbial community composition using all the genetic material in the environmental sample was characterized using 16S rRNA gene-based analysis, while functional subsystem attributes of these microbial communities were characterized using shotgun metagenomics. We used a Bayesian statistical tool, SourceTracker 2.0 to determine the likely sources of microbes found in CAWS by sampling location and sampling period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Bayesian Optimal Sensor Augmentation Via Estimated Mutual Information

We consider the problem of designing a sensor network to most efficiently locate the source of a seismic event. The left panel of Figure 1 shows 982 possible sensor locations in a region of interest. The objective is to infer the unknown location of an earthquake, indicated by the gold dot for illustration purposes. Assume that three sensors have already been placed for data collection. Travel times of the P-wave from the source to the three sensors are observed and used to infer the unknown source location via a Bayesian statistical model described subsequently. The right panel of Figure 1 shows samples from the resulting posterior distribution for source location along with a posterior estimate of this location.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Compressed Natural Gas Component Leak Frequency Estimation

The frequency of unintended releases in a compressed natural gas system is an important aspect of the system quantitative risk assessment. The frequencies for possible release scenarios, along with engineering models, are utilized to quantify the risks for compressed natural gas facilities. This report documents component leakage frequencies representative of compressed natural gas components that were estimated as a function of the normalized leak size. A Bayesian statistical method was used which results in leak frequency distributions for each component which represent variation and uncertainty in the leak frequency. The analysis shows that there is high uncertainty in the estimated leak frequencies due to sparsity in compressed natural gas data. These leak frequencies may still be useful in compressed natural gas system risk assessments, as long as this high uncertainty is acknowledged and considered appropriately.

03 NATURAL GAS↗
DOE OSTI2023

Hawai‘i Play Fairway (Final Report)

Most of Hawai'i's geothermal resources are blind—their manifestations, such as hot springs and steam vents, do not appear on the ground surface because the heated water flows far below. With the exception of $K\bar{i}lauea East Rift Zone$, in most areas of Hawai'i, high lateral permeability in the first kilometer below ground surface prevents surface thermal features from developing. As a methodology for discovering these blind resources, Play Fairway Analysis (PFA) involves finding potential locations of blind hydrothermal systems and describing potential geothermal sources in rift-zone settings. Using the PFA to find Hawai'i's geothermal resources, the University of Hawai'i (UH) conducted the Hawai‘i Play Fairway Project, Hawai'i's first statewide geothermal resource assessment since 1985. Sponsored by the U.S. Department of Energy, the Hawai'i Play Fairway Project provided an updated resource assessment, a roadmap for additional exploration activities, and the identification of areas for further exploration. Benefitting from UH's core competency in earth sciences and experienced geothermal researchers, the project comprised three phases. During the first phase, the team identified, compiled, and ranked existing geologic, groundwater, and geophysical datasets relevant to subsurface heat, fluid and permeability. Using a Bayesian statistical approach, the team developed a statistical methodology to integrate these data into a resource probability map. The team evaluated the confidence in the probability value and considered development viability of areas with geothermal resources. With these analyses, the team identified 10 locations in the Hawaiian Islands for exploration activities. For the second phase, the team collected new groundwater data in 10 locations across the state and new geophysical data on $L\bar{a}na‘i, Maui$, and central Hawai'i Island and modeled topographically induced stress to better characterize subsurface permeability. Analyzing the subsurface stresses, the team evaluated the potential for fracture-induced permeability. The team inverted the MT and gravity data to produce 3D models of resistivity and density, respectively, on $L\bar{a}na‘i$, across $Haleakal\bar{a}'s$ SW rift (Maui), and surrounding Mauna Kea (Hawai‘i Island). The team developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The team incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. Through combining data from the first and second phases, the team determined locations for further exploration during the third phase. For MT and gravity surveys, the team recommended $Kaua'i's$ $L\bar{i}hu'e$ $Basin$, the east rift of $Maui's$ $Haleakal\bar{a}$ volcano, and the southwest rift of Hawai'i Island's Mauna Loa volcano. The MT and gravity surveys aimed to enable improved confidence in the resource potential in these locations. For drilling deep groundwater well(s), the team recommended Southeast Mauna Kea and $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$. During the third phase, further exploration involved drilling a groundwater well in $L\bar{a}na's$ $P\bar{a}l\bar{a}wai$ $Basin$ and performing more geophysical surveys. We deepened an existing water well proximal to our target area on $L\bar{a}na'i$ due to funding constraints that precluded us from spudding a new well that would exceed 1km depth. Drilling was preceded by a number of substantial elements including: writing an Environmental Assessment and the subsequent legal process, performance of deviation logging, lowering a camera down the well, coordinating site preparation with $P\bar{u}lama$ $L\bar{a}na'i$, shipping the UH-owned rig interisland, procuring supplies, and leading 3 community meetings on $L\bar{a}na'i$. Drilling occurred 24/7 the entire month of June 2019 over which time $L\bar{a}na'i$ $Well$ 10 was deepened from 427 m to 1057 m, with continuous core collected. We measured a roughly linear temperature gradient averaging 42°C/km and a maximum bottom hole temperature of 66°C. This gradient is more than twice the background for Hawai'i and within a range of gradients measured in this depth range for some exploration wells within KERZ. We consider these results encouraging for $L\bar{a}na'i's$ resource potential and recommend following with a slim hole within $L\bar{a}na'i's$ caldera (our target zone) to ~ 2 km. Further, the positive implications such results have for the island of O‘ahu are substantial - the shield stage of O'ahu's volcanoes ended 1-2 My earlier. However, O'ahu uses more electricity than the rest of the islands combined, and the utility recently called for 500-700MW of firm, dispatchable renewable electricity on O'ahu by 2033. In Phase 3, we also collected limited new encouraging groundwater data, and updated our thoughts on the probabilities of fluid and permeability at resource depths (Pr F = 1; Pr P = mostly unconstrained). Ultimately, we advocate for using our final probability of heat, and confidence in this probability, to drive the next phase of exploration. We contend further development of geothermal in Hawai‘i will enable the state to achieve its 100% renewable policy objective and Hawai'i to transition off of fossil fuels through geothermal discovery and development. The project not only produced a large amount of data and expanded the existing knowledge of Hawai'i's geothermal resources, but also produced publications, theses, presentations, core photos, datasets, media reports, television interviews, community events, and a blog. Students and new professionals benefitted from the project's hands-on research experiences and educational opportunities and earned awards and recognition.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

LPG Component Leak Frequency Estimation

Liquefied petroleum gas (LPG) is used in heating, cooking, and as a vehicle fuel (called autogas). A safety risk assessment may be needed to assess potential hazard scenarios and inform the regulations, codes, and standards that apply to LPG facilities, such as autogas refueling facilities. The frequency of unintended releases in an LPG system is an important aspect of a system quantitative risk assessment. This report documents estimation of leakage frequencies for individual components of LPG systems. These frequencies are described using uncertainty distributions obtained with Bayesian statistical methods, generic data, and LPG data which were publicly available. There was a lack of LPG data in the literature, so frequencies for most components were developed with generic data and should be used cautiously; without additional information about component leak frequencies in LPG systems, it is not known whether these generic frequencies may be conservative or non-conservative.

02 PETROLEUM↗
DOE OSTI2016

The dense matter equation of state from neutron star radius and mass measurements

We present a comprehensive study of spectroscopic radius measurements of twelve neutron stars obtained during thermonuclear bursts or in quiescence. We incorporate, for the first time, a large number of systematic uncertainties in the measurement of the apparent angular sizes, Eddington fluxes, and distances, in the composition of the interstellar medium, and in the flux calibration of X-ray detectors. We also take into account the results of recent theoretical calculations of rotational effects on neutron star radii, of atmospheric effects on surface spectra, and of relativistic corrections to the Eddington critical flux. We employ Bayesian statistical frameworks to obtain neutron star radii from the spectroscopic measurements as well as to infer the equation of state from the radius measurements. Combining these with the results of experiments in the vicinity of nuclear saturation density and the observations of ∼2 M{sub ⊙} neutron stars, we place strong and quantitative constraints on the properties of the equation of state between ≈2--8 times the nuclear saturation density. We find that around M=1.5M{sub ⊙}, the preferred equation of state predicts radii between 10.1 and 11.1 km. When interpreting the pressure constraints in the context of high density equations of state based on interacting nucleons, our results suggest a relatively weak contribution of the three-body interaction potential.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A NEW REFERENCE CHEMICAL COMPOSITION FOR TMC-1

Recent detections of complex organic molecules in dark clouds have rekindled interest in the astrochemical modeling of these environments. Because of its relative closeness and rich molecular complexity, TMC-1 has been extensively observed to study the chemical processes taking place in dark clouds. We use local thermodynamical equilibrium radiative transfer modeling coupled with a Bayesian statistical method which takes into account outliers to analyze the data from the Nobeyama spectral survey of TMC-1 between 8 and 50 GHz. We compute the abundance relative to molecular hydrogen of 57 molecules, including 19 isotopologues in TMC-1 along with their associated uncertainty. The new results are in general agreement with previous abundance determination from Ohishi and Kaifu and the values reported in the review from Agúndez and Wakelam. However, in some cases, large opacity and low signal to noise effects allow only upper or lower limits to be derived, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Thermal Proximity Effect: A New Probe of the He ii Reionization History and Quasar Lifetime

Despite decades of effort, the timing and duration of He ii reionization and the properties of the quasars believed to drive it are still not well constrained. We present a new method to study both via the thermal proximity effect—the heating of the intergalactic medium (IGM) around quasars when their radiation doubly ionizes helium. We post-process hydrodynamical simulations with 1D radiative transfer and study how the thermal proximity effect depends on the He ii fraction, x{sub HeII,0}, which prevailed in the IGM before the quasar turned on, and the quasar lifetime t{sub Q}. We find that the amplitude of the temperature boost in the quasar environment depends on x{sub HeII,0}, with a characteristic value of ΔT≃10{sup 4} K for x{sub HeII,0}=1.0, whereas the size of the thermal proximity zone is sensitive to t{sub Q}, with typical sizes of ≃100 cMpc for t{sub Q}=10{sup 8} yr. This temperature boost increases the thermal broadening of H i absorption lines near the quasar. We introduce a new Bayesian statistical method based on measuring the Lyα forest power spectrum as a function of distance from the quasar, and demonstrate that the thermal proximity effect should be easily detectable. For a mock data set of 50 quasars at z≃4, we predict that one can measure x{sub HeII,0} to an (absolute) precision ≈0.04 and t{sub Q} to a precision of ≈0.1 dex. By applying our formalism to existing high-resolution Lyα forest spectra, one should be able to reconstruct the He ii reionization history, providing a global census of hard photons in the high-z universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

From Neutron Star Observables to the Equation of State. II. Bayesian Inference of Equation of State Pressures

One of the key goals of observing neutron stars is to infer the equation of state (EoS) of the cold, ultradense matter in their interiors. Here, we present a Bayesian statistical method of inferring the pressures at five fixed densities, from a sample of mock neutron star masses and radii. We show that while five polytropic segments are needed for maximum flexibility in the absence of any prior knowledge of the EoS, regularizers are also necessary to ensure that simple underlying EoS are not over-parameterized. For ideal data with small measurement uncertainties, we show that the pressure at roughly twice the nuclear saturation density, ρ{sub sat}, can be inferred to within 0.3 dex for many realizations of potential sources of uncertainties. The pressures of more complicated EoS with significant phase transitions can also be inferred to within ∼30%. We also find that marginalizing the multi-dimensional parameter space of pressure to infer a mass–radius relation can lead to biases of nearly 1 km in radius, toward larger radii. Using the full, five-dimensional posterior likelihoods avoids this bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Modeling the He II Transverse Proximity Effect: Constraints on Quasar Lifetime and Obscuration

The He II transverse proximity effect - enhanced He II Lyα transmission in a background sightline caused by the ionizing radiation of a foreground quasar - offers a unique opportunity to probe the emission properties of quasars, in particular the emission geometry (obscuration, beaming) and the quasar lifetime. Building on the foreground quasar survey published in Schmidt et al., we present a detailed model of the He II transverse proximity effect, specifically designed to include light travel time effects, finite quasar ages, and quasar obscuration. Here, we post-process outputs from a cosmological hydrodynamical simulation with a fluctuating He ii ultraviolet background model, with the added effect of the radiation from a single bright foreground quasar. We vary the age t age and obscured sky fractions Ω obsc of the foreground quasar, and explore the resulting effect on the He ii transverse proximity effect signal. Fluctuations in intergalactic medium density and the ultraviolet background, as well as the unknown orientation of the foreground quasar, result in a large variance of the He II Lyα transmission along the background sightline. We develop a fully Bayesian statistical formalism to compare far-ultraviolet He ii Lyα transmission spectra of the background quasars to our models, and extract joint constraints on t age and Ω obsc for the six Schmidt et al. foreground quasars with the highest implied He II photoionization rates. Our analysis suggests a bimodal distribution of quasar emission properties, whereby one foreground quasar, associated with a strong He II transmission spike, is relatively old (22 Myr) and unobscured (Ω obsc < 35%), whereas three others are either younger than 10 Myr or highly obscured (Ω obsc > 70%).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Quantitative Constraints on the Reionization History from the IGM Damping Wing Signature in Two Quasars at z > 7

During reionization, neutral hydrogen in the intergalactic medium (IGM) imprints a damping wing absorption feature on the spectrum of high-redshift quasars. A detection of this signature provides compelling evidence for a significantly neutral universe, and enables measurements of the hydrogen neutral fraction x HI (z) at that epoch. Obtaining reliable quantitative constraints from this technique, however, is challenging due to stochasticity induced by the patchy inside-out topology of reionization, degeneracies with quasar lifetime, and the unknown unabsorbed quasar spectrum close to rest-frame Lyα. Here, we combine a large-volume semi-numerical simulation of reionization topology with 1D radiative transfer through high-resolution hydrodynamical simulations of the high-redshift universe to construct models of quasar transmission spectra during reionization. Our state-of-the-art approach captures the distribution of damping wing strengths in biased quasar halos that should have reionized earlier, as well as the erosion of neutral gas in the quasar environment caused by its own ionizing radiation. Combining this detailed model with our new technique for predicting the quasar continuum and its associated uncertainty, we introduce a Bayesian statistical method to jointly constrain the neutral fraction of the universe and the quasar lifetime from individual quasar spectra. We apply this methodology to the spectra of the two quasars with the highest redshifts known, ULAS J1120+0641 and ULAS J1342+0928, and measure volume-averaged neutral fractions {x HI }(Z = 7.09) = 0.48 $+0.26\atop{-0.26}$and {x HI }(Z = 7.54) = 0.60 $+0.20\atop{-0.23}$ (posterior medians and 68% credible intervals) when marginalized over quasar lifetimes of 10 3 ≤ t q ≤ 10 8 yr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Mapping Quasar Light Echoes in 3D with Ly α Forest Tomography

The intense radiation emitted by luminous quasars dramatically alters the ionization state of their surrounding IGM. This so-called proximity effect extends out to tens of Mpc, and manifests as large coherent regions of enhanced Ly (Ly) forest transmission in absorption spectra of background sightlines. In this work, we present a novel method based on Ly forest tomography, which is capable of mapping these quasar "light echoes" in three dimensions. Using a dense grid (10-100) of faint (m r ≈ 24.7 mag) background galaxies as absorption probes, one can measure the ionization state of the IGM in the vicinity of a foreground quasar, yielding detailed information about the quasar's radiative history and emission geometry. An end-to-end analysis-combining cosmological hydrodynamical simulations post-processed with a quasar emission model, realistic estimates of galaxy number densities, and instrument + telescope throughput-is conducted to explore the feasibility of detecting quasar light echoes. We present a new, fully Bayesian statistical method that allows one to reconstruct quasar light echoes from thousands of individual low-S/N transmission measurements. Armed with this tool, we undertake an exhaustive parameter study and show that light echoes can be convincingly detected for luminous (M 1450 <-27.5 mag, corresponding to m 1450 < 18.4 mag at z≃3.6) quasars at redshifts 3 < z QSO < 5, and that a relative precision better than 20% on the quasar age can be achieved for individual objects in the expected range of ages between 1 and 100 Myr. The observational requirements are relatively modest: Moderate-resolution (R ≳ 750), multiobject spectroscopy at a low signal-to-noise ratio (S/N > 5) is sufficient, requiring three-hour integrations using existing instruments on 8 m class telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Bayesian Inference of High-density Nuclear Symmetry Energy from Radii of Canonical Neutron Stars

The radius R 1.4 of neutron stars (NSs) with a mass of 1.4 M ⊙ has been extracted consistently in many recent studies in the literature. Using representative R 1.4 data, we infer high-density nuclear symmetry energy E sym (ρ) and the associated nucleon specific energy E 0 (ρ) in symmetric nuclear matter (SNM) within a Bayesian statistical approach using an explicitly isospin-dependent parametric equation of state (EOS) for nucleonic matter. We found the following. (1) The available astrophysical data can already significantly improve our current knowledge about the EOS in the density range of ρ 0 - 2.5ρ 0 . In particular, the symmetry energy at twice the saturation density ρ 0 of nuclear matter is determined to be E sym (2ρ 0 )=${39.2}_{-8.2}^{+12.1}$ MeV at a 68% confidence level. (2) A precise measurement of R 1.4 alone with a 4% 1σ statistical error but no systematic error will not greatly improve the constraints on the EOS of dense neutron-rich nucleonic matter compared to what we extracted from using the available radius data. (3) The R 1.4 radius data and other general conditions, such as the observed NS maximum mass and causality condition, introduce strong correlations for the high-order EOS parameters. Consequently, the high-density behavior of E sym (ρ) inferred depends strongly on how the high-density SNM EOS E 0 (ρ) is parameterized, and vice versa. (4) Finally, the value of the observed maximum NS mass and whether it is used as a sharp cutoff for the minimum maximum mass or through a Gaussian distribution significantly affects the lower boundaries of both E 0 (ρ) and E sym (ρ) only at densities higher than about 2.5ρ 0 .

79 ASTRONOMY AND ASTROPHYSICS↗