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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 OSTI2015

Travel Patterns And Characteristics Of Transit Users In New York State

This research is a detailed examination of the travel behaviors and patterns of transit users within New York State (NYS), primarily based on travel data provided by the National Household Travel Survey (NHTS) in 2009 and the associated Add-on sample households purchased by the New York State Department of Transportation (NYSDOT). Other data sources analyzed in this study include: NYS General Transit Feed Specification (GTFS) to assist in analyzing spatial relationships for access to transit and the creation of Transit Shed geographic areas of 1, 2.5, and 5 miles from transit stop locations, LandScan population database to understand transit coverage, and Census Bureau s American Community Survey (ACS) data to examine general transit patterns and trends in NYS over time. The majority of analyses performed in this research aimed at identifying transit trip locations, understanding differences in transit usage by traveler demographics, as well as producing trip/mode-specific summary statistics including travel distance, trip duration, time of trip, and travel purpose of transit trips made by NYS residents, while also analyzing regional differences and unique travel characteristics and patterns. The analysis was divided into two aggregated geographic regions: New York Metropolitan Transportation Council (NYMTC) and NYS minus NYMTC (Rest of NYS). The inclusion of NYMTC in all analysis would likely produce misleading conclusions for other regions in NYS. TRANSIT COVERAGE The NYS transit network has significant coverage in terms of transit stop locations across the state s population. Out of the 19.3 million NYS population in 2011, about 15.3 million (or 79%) resided within the 1-mile transit shed. This NYS population transit coverage increased to 16.9 million (or 88%) when a 2.5-mile transit shed was considered; and raised to 17.7 million (or 92%) when the 5-mile transit shed was applied. KEY FINDINGS Based on 2009 NHTS data, about 40% of NYMTC households used transit as their means of transportation on any typical day; while only 4% of households located elsewhere in NYS did the same. Regardless of geographic regions, 45% of the transit users came from households with income under $40,000, while 20% of transit users were from the top income group of $100,000 plus households. Travel made by NYMTC transit users were nearly twice as likely to be for work trips as compared to their counterpart non-transit users. Transit users in NYS generally made more trips but with shorter distances; they also drove less, which resulted in fewer miles. Furthermore, NYS transit users spent more time on each trip than their counterpart non-transit users. Because of the intensity of transit network services within NYMTC, 88% of the households reside within the 1-mile transit shed. Outside the NYMTC, however, only 54% of the region s households are located within the same distance. Impact to vehicle ownership was clearly evidenced. Nearly all people from zero-vehicle households in NYMTC lived within a 1-mile radius of transit stops. Elsewhere in NYS, 74% of residents from zero-vehicle households resided within the 1-mile transit shed. Close proximity to transit has a significant impact on increasing transit uses. Transit mode share, as a main mode, was higher for NYS residents that lived within the 1-mile transit shed than others. Based on ACS data, over the period from 2005 to 2013, the total number of NYMTC workers increased more than 9%, while transit commuting grew at a higher rate of more than 15% during the same period. REMARKS Note that transit use in areas outside the NYMTC region generally is not common, resulting in a smaller sample size of transit users in the Rest of NYS region. Caution should be exercised for statistics produced based on small sample sizes that tend to be less precise (i.e., with a larger margin of error). Furthermore, standardized transit network data were not available prior to 2005; comparable analyses using 2001 NHTS therefore was not feasible. As a result, this study focused on examining travel behaviors of transit users using 2009 NHTS data only.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Deep nonparametric estimation of intrinsic data structures by chart autoencoders: Generalization error and robustness

Autoencoders have demonstrated remarkable success in learning low-dimensional latent features of high-dimensional data across various applications. Assuming that data are sampled near a low-dimensional manifold, we employ chart autoencoders, which encode data into low-dimensional latent features on a collection of charts, preserving the topology and geometry of the data manifold. Our paper establishes statistical guarantees on the generalization error of chart autoencoders, and we demonstrate their denoising capabilities by considering n noisy training samples, along with their noise-free counterparts, on a d-dimensional manifold. By training autoencoders, we show that chart autoencoders can effectively denoise the input data with normal noise. We prove that, under proper network architectures, chart autoencoders achieve a squared generalization error in the order of n–$\frac{2}{d+2}$log 4 n, which depends on the intrinsic dimension of the manifold and only weakly depends on the ambient dimension and noise level. We further extend our theory on data with noise containing both normal and tangential components, where chart autoencoders still exhibit a denoising effect for the normal component. As a special case, our theory also applies to classical autoencoders, as long as the data manifold has a global parametrization. Furthermore, our results provide a solid theoretical foundation for the effectiveness of autoencoders, which is further validated through several numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Galaxy–Halo Connection of DESI Luminous Red Galaxies with Subhalo Abundance Matching

Abstract We use subhalo abundance and age distribution matching to create magnitude-limited mock galaxy catalogs at z ∼ 0.43, 0.52, and 0.63 with z -band and 3.4 μ m W 1-band absolute magnitudes and r − z and r − W 1 colors. From these magnitude-limited mocks, we select mock luminous red galaxy (LRG) samples according to the ( r − z )-based (optical) and ( r − W 1)-based (infrared) selection criteria for the LRG sample of the Dark Energy Spectroscopic Instrument (DESI) survey. Our models reproduce the number densities, luminosity functions, color distributions, and projected clustering of the DESI Legacy Surveys that are the basis for DESI LRG target selection. We predict the halo occupation statistics of both optical and IR DESI LRGs at fixed cosmology and assess the differences between the two LRG samples. We find that IR-based SHAM modeling represents the differences between the optical and IR LRG populations better than using the z band and that age distribution matching overpredicts the clustering of LRGs, implying that galaxy color is uncorrelated with halo age in the LRG regime. Both the optical and IR DESI LRG target selections exclude some of the most luminous galaxies that would appear to be LRGs based on their position on the red sequence in optical color–magnitude space. Both selections also yield populations with a nontrivial LRG–halo connection that does not reach unity for the most massive halos. We find that the IR selection achieves greater completeness (≳90%) than the optical selection across all redshift bins studied.

Berti, Angela M. (ORCID:0000000335826649)↗
DOE OSTI2025

Increased inflammation as well as decreased endoplasmic reticulum stress and translation differentiate pancreatic islets from donors with pre-symptomatic stage 1 type 1 diabetes and non-diabetic donors

Aims/hypothesis Progression to type 1 diabetes is associated with genetic factors, the presence of autoantibodies and a decline in beta cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting beta cells prior to the onset of type 1 diabetes. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet-autoantibody-positive organ donors with pre-symptomatic stage 1 type 1 diabetes (HbA1c ≤42 mmol/mol [6.0%]). We aimed to identify pathways in islets that are indicative of beta cell dysfunction. Methods Multiple islet sections were collected through laser microdissection of frozen pancreatic tissues from organ donors positive for single or multiple islet autoantibodies (AAb + , n=5), and age (±2 years)- and sex-matched non-diabetic (ND) control donors (n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to MS-based proteomics and analysed with label-free quantification followed by pathway and functional annotations. Results Analyses resulted in ~4500 proteins identified with low false discovery rate (<1%), with 2165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on only the donors with stage 1 type 1 diabetes who were positive for multiple autoantibodies (mAAb + , n=3) and genetic risk compared with their matched ND controls (n=3) for the final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different (unadjusted p<0.025, q<0.15) for mAAb + vs ND donor islets. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including a proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single-cell RNA-seq datasets from AAb + individuals. Conclusions/interpretation In situ human islet proteome alterations in stage 1 type 1 diabetes centred around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation/HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on beta cell changes during type 1 diabetes progression and pathogenesis. Data availability The LC-MS raw datasets that support the findings of this study have been deposited in the online repository: MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) with accession no. MSV000090212.

Autoantibody-positive↗
DOE OSTI2021

Impact of size and thermal gradient on supercooling of phase change materials for thermal energy storage

Phase change material based thermal energy storage has many current and potential applications in the heating and cooling of buildings, battery and electronics thermal management, thermal textiles, and dry cooling of power plants. However, connecting lab scale thermal data obtained with differential scanning calorimetry (DSC) to the performance of large-scale practical systems has been a major challenge primarily due to the dependence of supercooling on the size and temperature gradient of the system. Here we show how a phase change material’s supercooling behavior can be characterized experimentally using common lab scale thermal analysis techniques. We then develop a statistics based theoretical model that uses the lab-scale data on small samples to quantitatively predict the supercooling performance for a general thermal energy storage application of any size, including also allowing for the possibility of temperature gradients. Finally, we validate the modeling methodology by comparing to experimental results for solid-solid phase change in neopentyl glycol, which shows how the model successfully predicts the changes in supercooling temperature across a large range of cooling rates (2 orders of magnitude) and volumes (3 orders of magnitude). By accounting for thermal gradients, the model avoids ~2x error incurred by lumped approximations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigation of process history and underlying phenomena associated with the synthesis of plutonium oxides using Vector Quantizing Variational Autoencoder

Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. Among other candidates, a neural network called a Vector Quantizing Variational Autoencoder (VQ-VAE) has shown the ability to quantitatively describe particle morphology to attain >85% accuracy in identifying uranium oxide processing routes. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO 2 ) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO 2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO 2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE, then further reduce the dimensionality of the feature space using a bottlenecking neural network fit to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO 2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Bi-fidelity variational auto-encoder for uncertainty quantification

Quantifying the uncertainty of quantities of interest (QoIs) from physical systems is a primary objective in model validation. However, achieving this goal entails balancing the need for computational efficiency with the requirement for numerical accuracy. To address this trade-off, we propose a novel bi-fidelity formulation of variational auto-encoders (BF-VAE) designed to estimate the uncertainty associated with a QoI from low-fidelity (LF) and high-fidelity (HF) samples of the QoI. Here, this model allows for the approximation of the statistics of the HF QoI by leveraging information derived from its LF counterpart. Specifically, we design a bi-fidelity auto-regressive model in the latent space which is integrated within the VAE’s probabilistic encoder–decoder structure. An effective algorithm is proposed to maximize the variational lower bound of the HF log-likelihood in the presence of limited HF data, resulting in the synthesis of HF realizations with a reduced computational cost. Additionally, we introduce the concept of the bi-fidelity information bottleneck (BF-IB) to provide an information-theoretic interpretation of the proposed BF-VAE model. Our numerical results demonstrate that the BF-VAE leads to considerably improved accuracy, as compared to a VAE trained using only HF data, when limited HF data is available.

42 ENGINEERING↗
DOE OSTI2015

Dummy Run of Quality Assurance Program in a Phase 3 Randomized Trial Investigating the Role of Internal Mammary Lymph Node Irradiation in Breast Cancer Patients: Korean Radiation Oncology Group 08-06 Study

Purpose: The Korean Radiation Oncology Group (KROG) 08-06 study protocol allowed radiation therapy (RT) technique to include or exclude breast cancer patients from receiving radiation therapy to the internal mammary lymph node (IMN). The purpose of this study was to assess dosimetric differences between the 2 groups and potential influence on clinical outcome by a dummy run procedure. Methods and Materials: All participating institutions were asked to produce RT plans without irradiation (Arm 1) and with irradiation to the IMN (Arm 2) for 1 breast-conservation treatment case (breast-conserving surgery [BCS]) and 1 mastectomy case (modified radical mastectomy [MRM]) whose computed tomography images were provided. We assessed interinstitutional variations in IMN delineation and evaluated the dose-volume histograms of the IMN and normal organs. A reference IMN was delineated by an expert panel group based on the study guidelines. Also, we analyzed the potential influence of actual dose variation observed in this study on patient survival. Results: Although physicians intended to exclude the IMN within the RT field, the data showed almost 59.0% of the prescribed dose was delivered to the IMN in Arm 1. However, the mean doses covering the IMN in Arm 1 and Arm 2 were significantly different for both cases (P<.001). Due to the probability of overdose in Arm 1, the estimated gain in 7-year disease-free survival rate would be reduced from 10% to 7.9% for BCS cases and 7.1% for MRM cases. The radiation doses to the ipsilateral lung, heart, and coronary artery were lower in Arm 1 than in Arm 2. Conclusions: Although this dummy run study indicated that a substantial dose was delivered to the IMN, even in the nonirradiation group, the dose differences between the 2 groups were statistically significant. However, this dosimetric profile should be studied further with actual patient samples and be taken into consideration when analyzing clinical outcomes according to IMN irradiation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Getting lost tracking the carbon footprint of hydropower

In the transition to low-carbon electricity, well-quantified estimates of carbon dynamics are needed to ensure that emissions reduction targets are achieved. Here we review the state of the science on carbon accounting for hydropower reservoirs and identify limitations and future solutions. Nearly all research on reservoir greenhouse-gas (GHG) emissions has focused on individual reservoirs in isolation without considering their position in a freshwater network draining organic matter from upstream watersheds or the coordinated operation of reservoir cascades. Second, carbon inventories have extrapolated from a small, non-probabilistic sample of highly variable measurements of GHG emissions to unsampled reservoirs. A stronger statistical foundation is needed to estimate a global inventory and its uncertainty. Third, attribution to hydropower is based on ranks assigned to reservoir purpose. Instead, the physical influence of hydropower on carbon dynamics could be directly measured. Fourth, current carbon-accounting practices neglect time. A time-varying approach would quantify variation in emissions for electricity portfolios from changes in the fuel mix at different times and account for ancillary services, i.e., the ability to support the grid when variable renewables are not available without using natural gas. Reservoirs also sequester a significant portion of inflowing carbon in sediments and slow the carbon cycle by delaying the return of carbon to the atmosphere for decades to centuries. Together, these refinements would help to illuminate pathways toward meeting energy demand with the longest-possible delay in returning carbon to the atmosphere and without adding ancient sources to the pool of carbon cycling through aquatic ecosystems.

13 HYDRO ENERGY↗
DOE OSTI2014

Oxidative stress/reactive metabolite gene expression signature in rat liver detects idiosyncratic hepatotoxicants

Previously we reported a gene expression signature in rat liver for detecting a specific type of oxidative stress (OS) related to reactive metabolites (RM). High doses of the drugs disulfiram, ethinyl estradiol and nimesulide were used with another dozen paradigm OS/RM compounds, and three other drugs flutamide, phenacetin and sulindac were identified by this signature. In a second study, antiepileptic drugs were compared for covalent binding and their effects on OS/RM; felbamate, carbamazepine, and phenobarbital produced robust OS/RM gene expression. In the present study, liver RNA samples from drug-treated rats from more recent experiments were examined for statistical fit to the OS/RM signature. Of all 97 drugs examined, in addition to the nine drugs noted above, 19 more were identified as OS/RM-producing compounds—chlorpromazine, clozapine, cyproterone acetate, dantrolene, dipyridamole, glibenclamide, isoniazid, ketoconazole, methapyrilene, naltrexone, nifedipine, sulfamethoxazole, tamoxifen, coumarin, ritonavir, amitriptyline, valproic acid, enalapril, and chloramphenicol. Importantly, all of the OS/RM drugs listed above have been linked to idiosyncratic hepatotoxicity, excepting chloramphenicol, which does not have a package label for hepatotoxicity, but does have a black box warning for idiosyncratic bone marrow suppression. Most of these drugs are not acutely toxic in the rat. The OS/RM signature should be useful to avoid idiosyncratic hepatotoxicity of drug candidates. - Highlights: • 28 of 97 drugs gave a positive OS/RM gene expression signature in rat liver. • The specificity of the signature for human idiosyncratic hepatotoxicants was 98%. • The sensitivity of the signature for human idiosyncratic hepatotoxicants was 75%. • The signature can help eliminate hepatotoxicants from drug development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A Retrospective of Findings From the FORTE Satellite Mission

We revisit the findings from the FORTE satellite program (1997–2004), which collected optical imaging of lightning as well as optical and radio frequency time series waveforms globally from low-earth-orbit. These include surveys of the earth's radio frequency anthropogenic noise environment; earth surface reflectivity at radio frequencies; a scheme for classifying lightning discharge types on the basis of their very high frequency time domain power envelope; insights into the polarization and radiation pattern characteristics of different lightning types, with implications for the underlying discharge processes; and estimates of cloud optical properties based on the statistics of scattered light. Most significantly, FORTE was uniquely suited to capture large samples of data from the rare discharge known as “narrow bipolar events,” enabling detailed examination of their basic characteristics and confirming that they appear to result from fundamentally distinct physical processes compared to other lightning. In particular, despite representing huge charge transfer they evidently produce little-to-no light output.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

True randomness from an incoherent source

Quantum random number generators (QRNGs) harness the intrinsic randomness in measurement processes: the measurement outputs are truly random, given the input state is a superposition of the eigenstates of the measurement operators. In the case of trusted devices, true randomness could be generated from a mixed state ρ so long as the system entangled with ρ is well protected. We propose a random number generation scheme based on measuring the quadrature fluctuations of a single mode thermal state using an optical homodyne detector. By mixing the output of a broadband amplified spontaneous emission (ASE) source with a single mode local oscillator (LO) at a beam splitter and performing differential photo-detection, we can selectively detect the quadrature fluctuation of a single mode output of the ASE source, thanks to the filtering function of the LO. Experimentally, a quadrature variance about three orders of magnitude larger than the vacuum noise has been observed, suggesting this scheme can tolerate much higher detector noise in comparison with QRNGs based on measuring the vacuum noise. The high quality of this entropy source is evidenced by the small correlation coefficients of the acquired data. A Toeplitz-hashing extractor is applied to generate unbiased random bits from the Gaussian distributed raw data, achieving an efficiency of 5.12 bits per sample. Furthermore, the output of the Toeplitz extractor successfully passes all the NIST statistical tests for random numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

The trends high-contrast imaging survey. IV. The occurrence rate of giant planets around M dwarfs

Doppler-based planet surveys have discovered numerous giant planets but are incomplete beyond several AU. At larger star-planet separations, direct planet detection through high-contrast imaging has proven successful, but this technique is sensitive only to young planets and characterization relies upon theoretical evolution models. Here we demonstrate that radial velocity measurements and high-contrast imaging can be combined to overcome these issues. The presence of widely separated companions can be deduced by identifying an acceleration (long-term trend) in the radial velocity of a star. By obtaining high spatial resolution follow-up imaging observations, we rule out scenarios in which such accelerations are caused by stellar binary companions with high statistical confidence. We report results from an analysis of Doppler measurements of a sample of 111 M-dwarf stars with a median of 29 radial velocity observations over a median time baseline of 11.8 yr. By targeting stars that exhibit a radial velocity acceleration ({sup t}rend{sup )} with adaptive optics imaging, we determine that 6.5% ± 3.0% of M-dwarf stars host one or more massive companions with 1 < m/M{sub J} < 13 and 0 < a < 20 AU. These results are lower than analyses of the planet occurrence rate around higher-mass stars. We find the giant planet occurrence rate is described by a double power law in stellar mass M and metallicity F ≡ [Fe/H] such that f(M,F)=0.039{sub −0.028}{sup +0.056}M{sup 0.8{sub −}{sub 0}{sub .}{sub 9}{sup +{sup 1{sup .{sup 1}}}}}10{sup (3.8±1.2)F}. Our results are consistent with gravitational microlensing measurements of the planet occurrence rate; this study represents the first model-independent comparison with microlensing observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Diverse properties of interstellar medium embedding gamma-ray bursts at the epoch of reionization

Analysis is performed on ultra-high-resolution large-scale cosmological radiation-hydrodynamic simulations to quantify, for the first time, the physical environment of long-duration gamma-ray bursts (GRBs) at the epoch of reionization. We find that, on parsec scales, 13% of GRBs remain in high-density (≥10{sup 4} cm{sup –3}) low-temperature star-forming regions, whereas 87% of GRBs occur in low-density (∼10{sup –2.5} cm{sup –3}) high-temperature regions heated by supernovae. More importantly, the spectral properties of GRB afterglows, such as the neutral hydrogen column density, total hydrogen column density, dust column density, gas temperature, and metallicity of intervening absorbers, vary strongly from sight line to sight line. Although our model explains extant limited observationally inferred values with respect to circumburst density, metallicity, column density, and dust properties, a substantially larger sample of high-z GRB afterglows would be required to facilitate a statistically solid test of the model. Our findings indicate that any attempt to infer the physical properties (such as metallicity) of the interstellar medium (ISM) of the host galaxy based on a very small number (usually one) of sight lines would be precarious. Utilizing high-z GRBs to probe the ISM and intergalactic medium should be undertaken properly, taking into consideration the physical diversities of the ISM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The spatial clustering of ROSAT all-sky survey active galactic nuclei. IV. More massive black holes reside in more massive dark matter halos

This is the fourth paper in a series that reports on our investigation of the clustering properties of active galactic nuclei (AGNs) identified in the ROSAT All-Sky Survey and Sloan Digital Sky Survey (SDSS). In this paper we investigate the cause of the X-ray luminosity dependence of the clustering of broad-line, luminous AGNs at 0.16<z<0.36. We fit the Hα line profile in the SDSS spectra for all X-ray and optically selected broad-line AGNs, determine the mass of the supermassive black hole (SMBH), M{sub BH}, and infer the accretion rate relative to Eddington (L/L{sub EDD}). Since M{sub BH} and L/L{sub EDD} are correlated, we create AGN subsamples in one parameter while maintaining the same distribution in the other parameter. In both the X-ray and optically selected AGN samples, we detect a weak clustering dependence with M{sub BH} and no statistically significant dependence on L/L{sub EDD}. We find a difference of up to 2.7σ when comparing the objects that belong to the 30% least and 30% most massive M{sub BH} subsamples, in that luminous broad-line AGNs with more massive black holes reside in more massive parent dark matter halos at these redshifts. These results provide evidence that higher accretion rates in AGNs do not necessarily require dense galaxy environments, in which more galaxy mergers and interactions are expected to channel large amounts of gas onto the SMBH. We also present semianalytic models that predict a positive M{sub DMH} dependence on M{sub BH}, which is most prominent at M{sub BH}∼10{sup 8−9} M{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Measurement of the integrated luminosity of the Phase 2 data of the Belle II experiment

From April to July 2018, a data sample at the peak energy of the Υ(4S) resonance was collected with the Belle II detector at the SuperKEKB electron-positron collider. This is the first data sample of the Belle II experiment. Using Bhabha and digamma events, we measure the integrated luminosity of the data sample to be (496.3±0.3±3.0)pb –1 , where the first uncertainty is statistical and the second is systematic. This work provides a basis for future luminosity measurements at Belle II.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

THE DETECTION OF THE LARGE-SCALE ALIGNMENT OF MASSIVE GALAXIES AT z {approx} 0.6

We report on the detection of the alignment between galaxies and large-scale structure at z {approx} 0.6 based on the CMASS galaxy sample from the Baryon Oscillation Spectroscopy Survey Data Release 9. We use two statistics to quantify the alignment signal: (1) the alignment two-point correlation function that probes the dependence of galaxy clustering at a given separation in redshift space on the projected angle ({theta}{sub p}) between the orientation of galaxies and the line connecting to other galaxies, and (2) the cos (2{theta})-statistic that estimates the average of cos (2{theta}{sub p}) for all correlated pairs at a given separation s. We find a significant alignment signal out to about 70 h {sup -1} Mpc in both statistics. Applications of the same statistics to dark matter halos of mass above 10{sup 12} h {sup -1} M{sub Sun} in a large cosmological simulation show scale-dependent alignment signals similar to the observation, but with higher amplitudes at all scales probed. We show that this discrepancy may be partially explained by a misalignment angle between central galaxies and their host halos, though detailed modeling is needed in order to better understand the link between the orientations of galaxies and host halos. In addition, we find systematic trends of the alignment statistics with the stellar mass of the CMASS galaxies, in the sense that more massive galaxies are more strongly aligned with the large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraining galaxy–halo connection with high-order statistics

ABSTRACT We investigate using three-point statistics in constraining the galaxy–halo connection. We show that for some galaxy samples, the constraints on the halo occupation distribution parameters are dominated by the three-point function signal (over its two-point counterpart). We demonstrate this on mock catalogues corresponding to the Luminous red galaxies (LRGs), Emission-line galaxies (ELGs), and quasars (QSOs) targeted by the Dark Energy Spectroscopic Instrument (DESI) Survey. The projected three-point function for triangle sides less up to 20 h−1 Mpc measured from a cubic Gpc of data can constrain the characteristic minimum mass of the LRGs with a preci sion of 0.46 per cent. For comparison, similar constraints from the projected two-point function are 1.55 per cent. The improvements for the ELGs and QSOs targets are more modest. In the case of the QSOs, it is caused by the high shot-noise of the sample, and in the case of the ELGs, it is caused by the range of halo masses of the host haloes. The most time-consuming part of our pipeline is the measurement of the three-point functions. We adopt a tabulation method, proposed in earlier works for the two-point function, to significantly reduce the required compute time for the three-point analysis.

79 ASTRONOMY AND ASTROPHYSICS↗