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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

The most luminous, merger-free AGNs show only marginal correlation with bar presence

The role of large-scale bars in the fuelling of active galactic nuclei (AGNs) is still debated, even as evidence mounts that black hole growth in the absence of galaxy mergers cumulatively dominates and may substantially influence disc (i.e. merger-free) galaxy evolution. We investigate whether large-scale galactic bars are a good candidate for merger-free AGN fuelling. Specifically, we combine slit spectroscopy and Hubble Space Telescope imagery to characterize star formation rates (SFRs) and stellar masses of the unambiguously disc-dominated host galaxies of a sample of luminous, Type-1 AGN with 0.02 < z < 0.24. After carefully correcting for AGN signal, we find no clear difference in SFRs between AGN hosts and a stellar mass-matched sample of galaxies lacking an AGN (0.013 < z < 0.19), although this could be due to small sample size (nAGN = 34). We correct for SFR and stellar mass to minimize selection biases, and compare the bar fraction in the two samples. We find that AGNs are marginally (~1.7σ) more likely to host a bar than inactive galaxies, with AGN hosts having a bar fraction, $f_{\mathrm{bar}}=0.59^{+0.08}_{-0.09}$ and inactive galaxies having a bar fraction, $f_{\mathrm{bar}}=0.44^{+0.08}_{-0.09}$. However, we find no further differences between SFR- and mass-matched AGNs and inactive samples. While bars could potentially trigger AGN activity, they appear to have no further, unique effect on a galaxy’s stellar mass or SFR.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Gamma-ray bursts, supernovae Ia, and baryon acoustic oscillations: A binned cosmological analysis

Abstract Cosmological probes at any redshift are necessary to reconstruct consistently the cosmic history. Studying properly the tension on the Hubble constant, H0, obtained by supernovae type Ia (SNe Ia) and the Planck measurements of the cosmic microwave background radiation would require complete samples of distance indicators at any epoch. Gamma-ray bursts (GRBs) are necessary for the aforementioned task because of their huge luminosity that allows us to extend the cosmic ladder to very high redshifts. However, using GRBs alone as standard candles is challenging, because their luminosity varies widely. To this end, we choose a reliable correlation for GRBs with a very small intrinsic scatter: the so-called fundamental plane correlation for GRB afterglows corrected for selection biases and redshift evolution. We choose a well defined sample: the platinum sample, composed of 50 long GRBs. To further constrain the cosmological parameters, we use baryon acoustic oscillations (BAOs) given their reliability as standard rulers. Thus, we have applied GRBs, SNe Ia, and BAOs in a binned analysis in redshifts so that the GRB contribution is fully included in the last redshift bin, which reaches z = 5. We use the fundamental plane correlation (also known as the 3D Dainotti relation), together with SNe Ia and BAOs, to constrain H0 and the density matter today, ΩM. This methodology allows us to assess the role of GRBs combined with SNe Ia and BAOs. We have obtained results for H0 and ΩM using GRBs+SNe Ia+BAOs with better precision than SNe Ia alone for every bin, thus confirming the beneficial role of BAOs and GRBs added together. In addition, consistent results between GRBs+SNe Ia+BAOs are obtained when compared with SNe Ia+BAOs, showing the importance of GRBs since the distance ladder is extended up to z = 5 with a similar precision obtained with other probes without including GRBs.

Dainotti, Maria Giovanna↗
DOE OSTI2026

Effect of recoils on soft-drop-groomed observables in 𝛾-tagged jets in a multistage approach

We investigate medium-induced modifications to jet substructure observables that characterize hard components in central Pb-Pb collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02 TeV. Using a multistage Monte Carlo simulation of in-medium jet shower evolution, we explore flavor-dependent medium effects through simulations of inclusive and 𝛾-tagged jets. The results show that quark jets undergo a nonmonotonic modification compared with gluon jets in observables such as the Pb-Pb to 𝑝−𝑝 ratio of the soft drop prong angle 𝑟 𝑔 , the relative prong transverse momentum 𝑘 𝑇,𝑔 , and the groomed mass 𝑚 𝑔 distributions. Due to this nonmonotonic modification, 𝛾-tagged jets, enriched in quark jets, provide surprisingly clear signals of medium-induced structural modifications, distinct from effects dominated by selection bias. Further systematic studies demonstrate that these effects are dominated by recoil medium response. This work highlights the potential of hard substructures in 𝛾-tagged jets as powerful tools for probing the jet-medium interactions in high-energy heavy-ion collisions, in particular by enabling detailed investigations of jet-medium parton scatterings via their associated medium response. All simulations for 𝛾-tagged jet analyses carried out in this paper used triggered events containing at least one hard photon, which highlights the utility of these observables for future Bayesian analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Jet suppression and azimuthal anisotropy from RHIC to LHC

Azimuthal anisotropies of high- p T particles produced in heavy-ion collisions are understood as an effect of a geometrical selection bias. Particles oriented in the direction in which the QCD medium formed in these collisions is shorter suffer less energy loss, and thus, are over-represented in the final ensemble compared to those oriented in the direction in which the medium is longer. In this work we present the first semianalytical predictions, including propagation through a realistic, hydrodynamical background, of the elliptic azimuthal anisotropy for jets, obtaining a quantitative agreement with available experimental data as a function of the jet p T , its cone size R , and the collisions centrality. Jets are multipartonic, extended objects and their energy loss is sensitive to substructure fluctuations. This sensitivity is determined by the physics of color coherence that relates to the ability of the medium to resolve those partonic fluctuations. Specifically, color dipoles with an angular separation smaller than a critical angle, θ c , are not resolved by the medium and they effectively act as a coherent source of energy loss. We find that elliptic jet azimuthal anisotropy has a specially strong dependence on coherence physics due to the marked length dependence of θ c . By combining our predictions for the collision systems and center-of-mass energies studied at RHIC and the LHC, covering a wide range of typical values of θ c , we show that the relative size of elliptic jet azimuthal anisotropies for jets with different cone sizes R follows a universal trend that indicates a transition from a coherent regime of jet quenching to a decoherent regime. These results suggest a way forward to reveal the role played by the physics of jet color decoherence in probing deconfined QCD matter. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Robust impurity detection and tracking for tokamaks

A robust impurity detection and tracking code, able to generate large sets of dust tracks from tokamak camera footage, is presented. This machine learning–based code is tested with cameras from the Joint European Torus, Doublet-III-D, and Magnum-PSI and is able to generate dust tracks with a 65 – 100 % classification accuracy. Moreover, the number dust particles detected from a single camera shot can be up to the order of 1000. Several areas of improvement for the code are highlighted, such as generating more significant training data sets and accounting for selection biases. Finally, although the code is tested with dust in single two-dimensional camera views, it could easily be applied to multiple-camera stereoscopic reconstruction or nondust impurities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Electroluminescence Characterization of Recombination in Back Junction Silicon Heterojunction Test Structures: Role of the Inversion Layer

Electroluminescence (EL) characterization technique is used to quantify recombination properties in back junction silicon (Si) heterojunction (HJ) solar cell test structures with interdigitated back contact (IBC) emitters and metal contacts. These test structures are three terminal devices that allow the selective biasing and injection of minority carriers into spatially isolated emitter strips having different widths. This allows the study of minority carriers' current transport, flow, and recombination in these regions, which can, then, be applied to full IBC cells. EL is used to verify that emission is proportional to the minority carriers' concentration in the corresponding regions of the device, thus providing information relevant to minority carriers' collection when compared with laser beam induced current technique in considerably less time and with a higher spatial resolution. Current transport through the inversion layer that occurs due to the band bending at the n crystalline Si and p amorphous Si interface is discussed relying on the distance that minority carriers travel in different configurations and on their diffusion length. Laser defect spots (LDS) were, then, introduced in the emitter regions to analyze the spatial profile of minority carriers as they recombine at the LDS due to their high surface recombination velocity. Ideality factors in different configurations are spatially mapped from EL before and after introducing LDS and are used to show the effect of the inversion layer on the different recombination mechanisms. Current transport through the inversion layer is studied at different biasing conditions and correlated with current transport after LDS.

42 ENGINEERING↗
DOE OSTI2022

Effect of vaccination on the case fatality rate for COVID-19 infections 2020–2021: multivariate modelling of data from the US Department of Veterans Affairs

Objectives: To evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections. Design, setting and participants: The US Department of Veterans Affairs has 130 medical centres. We created multivariate models from these data—339 772 patients with COVID-19—as of 30 September 2021. Outcome measures: The primary outcome for all models was death within 60 days of the diagnosis. Logistic regression was used to derive adjusted ORs for vaccination and infection with Delta versus earlier variants. Models were adjusted for confounding factors, including demographics, comorbidity indices and novel parameters representing prior diagnoses, vital signs/baseline laboratory tests and outpatient treatments. Patients with a Delta infection were divided into eight cohorts based on the time from vaccination to diagnosis. A common model was used to estimate the odds of death associated with vaccination for each cohort relative to that of unvaccinated patients. Results: 9.1% of subjects were vaccinated. 21.5% had the Delta variant. 18 120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for a Delta infection was 1.87±0.05, which corresponds to a relative risk (RR) of 1.78. The overall adjusted OR for prior vaccination was 0.280±0.011 corresponding to an RR of 0.291. Raw CFR rose steadily after 10–14 weeks. The OR for vaccination remained stable for 10–34 weeks. Conclusions: Our CFR model controls for the severity of confounding factors and priority of vaccination, rather than solely using the presence of comorbidities. Our results confirm that Delta was more lethal than earlier variants and that vaccination is an effective means of preventing death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks. We suggest that this model can be used to evaluate vaccines designed for emerging variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

TULIP: An RNA-seq-based Primary Tumor Type Prediction Tool Using Convolutional Neural Networks

Background: With cancer as one of the leading causes of death worldwide, accurate primary tumor type prediction is critical in identifying genetic factors that can inhibit or slow tumor progression. There have been efforts to categorize primary tumor types with gene expression data using machine learning, and more recently with deep learning, in the last several years. Methods In this paper, we developed four 1-dimensional (1D) Convolutional Neural Network (CNN) models to classify RNA-seq count data as one of 17 highly represented primary tumor types or 32 primary tumor types regardless of imbalanced representation. Additionally, we adapted the models to take as input either all Ensembl genes (60,483) or protein coding genes only (19,758). Unlike previous work, we avoided selection bias by not filtering genes based on expression values. RNA-seq count data expressed as FPKM-UQ of 9,025 and 10,940 samples from The Cancer Genome Atlas (TCGA) were downloaded from the Genomic Data Commons (GDC) corresponding to 17 and 32 primary tumor types respectively for training and validating the models. Results: All 4 1D-CNN models had an overall accuracy of 94.7% to 97.6% on the test dataset. Further evaluation indicates that the models with protein coding genes only as features performed with better accuracy compared to the models with all Ensembl genes for both 17 and 32 primary tumor types. For all models, the accuracy by primary tumor type was above 80% for most primary tumor types. Conclusions: We packaged all 4 models as a Python-based deep learning classification tool called TULIP (TUmor CLassIfication Predictor) for performing quality control on primary tumor samples and characterizing cancer samples of unknown tumor type. Further optimization of the models is needed to improve the accuracy of certain primary tumor types.

Jones, Sara↗
DOE OSTI2025

Third-order photon correlations extract single-nanocrystal multiexciton properties in solution

Colloidal semiconductor nanocrystals are considered promising materials for high-flux optical applications, including lasing, light-emitting diodes, biological imaging, and quantum optics. In high-flux applications, multiexcitons can significantly contribute to emission, influencing its brightness, spectral purity, and kinetics. As a result, understanding and controlling multiexciton emission in colloidal nanocrystal materials is of the utmost importance. In the past, single-nanocrystal photon correlation methods have been applied to understand biexciton and triexciton efficiencies, lifetimes, and spectra. While powerful, such methods suffer from user selection bias and require stable emission from single nanocrystals. To compensate for this shortcoming, second-order correlation methods were developed to extract sample-averaged biexciton properties from a solution of nanocrystals. Until now, however, the analogous third-order solution photon correlation methods remained unexplored. In this work, we present a pair of third-order photon correlation techniques to obtain the sample-averaged single-nanocrystal triexciton quantum yield and lifetime in a solution-phase experiment. These techniques derive from the relationship between the Poisson probability of nanocrystal photon absorption and the intrinsic probability of nanocrystal photon emission. We validate the theoretical background of these techniques by creating a numerical model to simulate the diffusion and emission of many nanocrystals in solution. Our simulations confirm that the average triexciton quantum yield and triexciton lifetime can be extracted from a solution of nanocrystals. These techniques will enable researchers to gain a better understanding of the fundamental multiexciton properties of colloidal nanocrystals.

Horowitz, Jonah R. [Massachusetts Institute of Tec↗
DOE OSTI2022

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system. Methods: We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ) and ground-level ozone (O 3 ), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ longterm exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage. Results: Among the 151105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM 2.5 (1.70 µg/m 3 ), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO 2 . We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O 3 for hospital admission, ICU admission and death, respectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Bayesian Characterization of Main-sequence Binaries in the Old Open Cluster NGC 188

The binary fractions of open and globular clusters yield powerful constraints on their dynamical state and evolutionary history. We apply publicly available Bayesian analysis tools to a UBV RIJHK {sub S} photometric catalog of the open cluster NGC 188 to detect and characterize photometric binaries along the cluster main sequence. This technique has the advantage of self-consistently handling photometric errors, missing data in various bandpasses, and star-by-star prior constraints on cluster membership. Simulations are used to verify uncertainties and quantify selection biases in our analysis, illustrating that among binaries with mass ratios >0.5, we recover the binary fraction to better than 7% in the mean, with no significant dependence on binary fraction and a mild dependence on assumed mass-ratio distribution. Using our photometric catalog, we recover the majority (65% ± 11%) of spectroscopically identified main-sequence binaries, including eight of the nine with spectroscopically measured mass ratios. Accounting for incompleteness and systematics, we derive a mass-ratio distribution that rises toward lower mass ratios (within our q > 0.5 analysis domain). We observe a raw binary fraction for solar-type main-sequence stars with mass ratios q > 0.5 of 42% ± 4%, independent of the assumed mass-ratio distribution to within its uncertainties, consistent with literature values for old open clusters but significantly higher than the field solar-type binary fraction. We confirm that the binaries identified by our method are more concentrated than single stars, in agreement with previous studies, and we demonstrate that the binary nature of those candidates that remain unidentified spectroscopically is strongly supported by photometry from Gaia DR2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Nature Versus Nurture: A Bayesian Framework for Assessing Apparent Correlations between Planetary Orbital Properties and Stellar Ages

Many exoplanets have orbital characteristics quite different from those seen in our own solar system, including planets locked in orbital resonances and planets on orbits that are elliptical or highly inclined from their host star’s spin axis. It is debated whether the wide variety in system architecture is primarily due to differences in formation conditions (nature) or due to evolution over time (nurture). Identifying trends between planetary and stellar properties, including stellar age, can help distinguish between these competing theories and offer insights as to how planets form and evolve. However, it can be challenging to determine whether observed trends between planetary properties and stellar age are driven by the age of the system—pointing to evolution over time being an important factor—or other parameters to which the age may be related, such as stellar mass or stellar temperature. The situation is complicated further by the possibilities of selection biases, small number statistics, uncertainties in stellar age, and orbital evolution timescales that are typically much shorter than the range of observed ages. Here, we develop a Bayesian statistical framework to assess the robustness of such observed correlations and to determine whether they are indeed due to evolutionary processes, are more likely to reflect different formation scenarios, or are merely coincidental. We apply this framework to reported trends between stellar age and 2:1 orbital resonances, spin–orbit misalignments, and hot Jupiters’ orbital eccentricities. We find strong support for the nurture hypothesis only in the final case.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

WIYN Open Cluster Study. LXXXV. Li in NGC 2243: Implications for Stellar and Galactic Evolution

High-dispersion spectra in the Li λ6708 region have been obtained and analyzed in the old, metal-deficient cluster NGC 2243. From Hydra spectra for 29 astrometric and radial velocity members, we derive rotational velocities, as well as [Fe/H], [Ca/H], [Si/H], and [Ni/H] based on 17, 1, 1, and 3 lines, respectively. Using ROBOSPECT, an automatic equivalent width measurement program, we derive [Fe/H] = −0.54 ± 0.11 (MAD), for an internal precision for the cluster [Fe/H] below 0.03 dex. Given the more restricted line set, comparable values for [Ca/H], [Si/H], and [Ni/H] are −0.48 ± 0.19, −0.44 ± 0.11, and −0.61 ± 0.06, respectively. With E(B − V) = 0.055, appropriate isochrones imply (m − M) = 13.2 ± 0.1 and an age of 3.6 ± 0.2 Gyr. Using available VLT spectra and published Li abundances, we construct an Li sample of over 100 stars extending from the tip of the giant branch to 0.5 mag below the Li dip. The Li dip is well populated and, when combined with results for NGC 6819 and Hyades/Praesepe, implies a mass/metallicity slope of 0.4 M {sub ⊙}/dex for the high-mass edge of the Li dip. The A(Li) distribution among giants reflects the degree of Li variation among the turnoff stars above the Li dip, itself a function of stellar mass and metallicity and strongly anticorrelated with a v {sub rot} distribution that dramatically narrows with age. Potential implications of these patterns for the interpretation of Li among dwarf and giant field populations, especially selection biases tied to age and metallicity, are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Early Ultraviolet Observations of Type IIn Supernovae Constrain the Asphericity of Their Circumstellar Material

Here we present a survey of the early evolution of 12 Type IIn supernovae (SNe IIn) at ultraviolet and visible light wavelengths. We use this survey to constrain the geometry of the circumstellar material (CSM) surrounding SN IIn explosions, which may shed light on their progenitor diversity. In order to distinguish between aspherical and spherical CSM, we estimate the blackbody radius temporal evolution of the SNe IIn of our sample, following the method introduced by Soumagnac et al. We find that higher-luminosity objects tend to show evidence for aspherical CSM. Depending on whether this correlation is due to physical reasons or to some selection bias, we derive a lower limit between 35% and 66% for the fraction of SNe IIn showing evidence for aspherical CSM. This result suggests that asphericity of the CSM surrounding SNe IIn is common - consistent with data from resolved images of stars undergoing considerable mass loss. It should be taken into account for more realistic modeling of these events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The X-Ray Fundamental Plane of the Platinum Sample, the Kilonovae, and the SNe Ib/c Associated with GRBs

A large fraction of gamma-ray burst (GRB) lightcurves (LCs) show X-ray plateaus. We analyze all GRBs with known redshifts presenting plateaus observed by The Neil Gehrels Swift Observatory from its launch until 2019 August. The fundamental plane relation between the rest-frame time and X-ray luminosity at the end of the plateau emission and the peak prompt luminosity holds for all the GRB classes when selection biases and cosmological evolutions are applied. We have discovered two important findings: (1) a new class of long GRBs with good data coverage: the platinum sample; and (2) the platinum, the SNe-LGRB, and the KN-SGRB samples, yield the smallest intrinsic scatter with σ platinum , GRB-SNe = 0.22 ± 0.10 and σ KN-SGRB = 0.24 ± 0.12. The SNe-LGRBs are composed of GRBs associated spectroscopically with the SNe Ib,c, the KN-SGRBs are composed by eight GRBs associated with kilonovae or where there could have been such an association. The highest correlation coefficients are yielded for the SN-LGRB-ABC sample, which includes GRBs spectroscopically associated with SNe Ib/c or with a clear optical bump in the LC resembling the SNe Ib/c, ( ), the SN-LGRBs ( ), and the KN-SGRBs ( ) when the redshift evolution is considered. We find that these category planes are reliable candidates to use as cosmological tools. Furthermore, the distance from the gold fundamental plane is a crucial discriminant among classes. In fact, we find that the distributions of the distances of the SNe-LGRB, SNe-LGRB-ABC, KN-SGRB, and SGRB samples from the gold fundamental plane are statistically different from the distribution of the gold GRBs' distances from the gold fundamental plane with and without considering evolution cases. <

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Closure Relations in Optical Afterglow of Gamma-Ray Bursts

Gamma-ray bursts (GRBs) are extremely high-energy events that can be observed at very high redshift. In addition to γ rays, they can emit in X-ray, optical, and sometimes radio wavelengths. Here, following the approach in Srinivasaragavan et al.; Dainotti et al.; and Dainotti et al., we consider 82 GRBs from Dainotti et al. that have been observed in optical wavelengths and fitted with a broken power law. We consider the relations between the spectral and temporal indices (closure relations; CRs) according to the synchrotron forward-shock model evolving in the constant-density interstellar medium (ISM; k = 0) and the stellar wind environment (k = 2) in both slow- and fast-cooling regimes, where the density profile is defined as n ∝ r -k . We find the $ν$ > $max${$ν$ c , $ν$ m } regime is most favored, where ν c and ν m are the cooling and characteristic frequencies, respectively. Finally, we test the 2D Dainotti correlation between the rest-frame end time of the plateau and the luminosity at that time on GRBs that fulfill the most-favored CRs. When we compare the intrinsic scatter σ int of those 2D correlations to the scatter presented in Dainotti et al., we see the scatters of our correlations generally agree with the previous values within 1σ, both before and after correction for selection bias. This new information has helped us to pinpoint subsamples of GRBs with features that could drive the GRB emission mechanism, and eventually allow for GRBs to be used as standard candles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Luminosity Function of Quasars at 1.0 < z < 3.5 from SDSS and DESI

We present a study of the evolution of type 1 quasars at 1.0 < z < 3.5, covering the peak epoch of quasar activity. The quasar evolution has been extensively explored by a variety of previous works and the derived quasar luminosity functions (QLFs) are not very consistent with each other, presumably due to the complexities introduced by different quasar selection techniques and associated completeness corrections. We use a new strategy to construct QLFs based on a library of all known quasars. We focus on a wide region of ∼1700 deg 2 and a deep field of ∼265 deg 2 that have rich spectroscopic data primarily from the Sloan Digital Sky Survey and DESI. We then apply traditional color cuts in the rest-frame UV–optical to select quasar candidates and use the quasar library to identify them. Our final sample consists of 62,426 quasars at 1.0 < z < 3.5, with a high completeness (∼96%) and a high purity (∼93%) in the color selection. Simple color cuts can potentially minimize selection biases for the study of quasar evolution. We derive binned QLFs and characterize them using a double power-law model. Sample incompleteness and contamination are considered as part of the uncertainties in the calculation. Compared to previous results, our QLFs are slightly higher at the faint end, and also higher at the bright end at 2.5 < z < 3.5. The QLFs suggest that the quasar evolution at 1.0 < z < 2.5 can be well described by the pure luminosity evolution model, while at 2.5 < z < 3.5, it can be described by either the pure luminosity evolution or the pure density evolution model.

Luminosity function↗
DOE OSTI2022

The Optical Two- and Three-dimensional Fundamental Plane Correlations for Nearly 180 Gamma-Ray Burst Afterglows with Swift/UVOT, RATIR, and the Subaru Telescope

Gamma-ray bursts (GRBs) are fascinating events due to their panchromatic nature. We study optical plateaus in GRB afterglows via an extended search into archival data. We comprehensively analyze all published GRBs with known redshifts and optical plateaus observed by many ground-based telescopes (e.g., Subaru Telescope, RATIR) around the world and several space-based observatories such as the Neil Gehrels Swift Observatory. We fit 500 optical light curves, showing the existence of the plateau in 179 cases. This sample is 75% larger than the previous one, and it is the largest compilation so far of optical plateaus. We discover the 3D fundamental plane relation at optical wavelengths using this sample. This correlation is between the rest-frame time at the end of the plateau emission, ${T}_{\mathrm{opt}}^{* }$, its optical luminosity, L opt , and the peak in the optical prompt emission, L peak,opt , thus resembling the three-dimensional (3D) X-ray fundamental plane (the so-called 3D Dainotti relation). We correct our sample for redshift evolution and selection effects, discovering that this correlation is indeed intrinsic to GRB physics. We investigate the rest-frame end-time distributions in X-rays and optical (${T}_{\mathrm{opt}}^{* }$, ${T}_{{\rm{X}}}^{* }$), and conclude that the plateau is achromatic only when selection biases are not considered. We also investigate if the 3D optical correlation may be a new discriminant between optical GRB classes and find that there is no significant separation between the classes compared to the Gold sample plane after correcting for evolution.

79 ASTRONOMY AND ASTROPHYSICS↗