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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A measurement of stellar surface gravity hidden in radial velocity differences of comoving stars

The gravitational redshift induced by stellar surface gravity is notoriously difficult to measure for non-degenerate stars, since its amplitude is small in comparison with the typical Doppler shift induced by stellar radial velocity. In this study, we make use of the large observational data set of the Gaia mission to achieve a significant reduction of noise caused by these random stellar motions. By measuring the differences in velocities between the components of the pairs of comoving stars and wide binaries, in this work we are able to statistically measure the combined effects of gravitational redshift and convective blueshifting of spectral lines, and nullify the effect of the peculiar motions of the stars. For the subset of stars considered in this study, we find a positive correlation between the observed differences in Gaia radial velocities and the differences in surface gravity and convective blueshift inferred from effective temperature and luminosity measurements. The results rule out a null signal at the 5σ level for our full data set. Additionally, we study the subdominant effects of binary motion, and possible systematic errors in radial velocity measurements within Gaia. Results from the technique presented in this study are expected to improve significantly with data from the next Gaia data release. Such improvements could be used to constrain the mass–luminosity relation and stellar models that predict the magnitude of convective blueshift.

(stars:) binaries: general↗
DOE OSTI2023

Accurate model of the projected velocity distribution of galaxies in dark matter haloes

ABSTRACT We present a per cent-level accurate model of the line-of-sight velocity distribution of galaxies around dark matter haloes as a function of projected radius and halo mass. The model is developed and tested using synthetic galaxy catalogues generated with the UniverseMachine run on the Multi-Dark Planck 2 N-body simulations. The model decomposes the galaxies around a cluster into three kinematically distinct classes: orbiting, infalling, and interloping galaxies. We demonstrate that: (1) we can statistically distinguish between these three types of galaxies using only projected line-of-sight velocity information; (2) the halo edge radius inferred from the line-of-sight velocity dispersion is an excellent proxy for the three-dimensional halo edge radius; and (3) we can accurately recover the full velocity dispersion profile for each of the three populations of galaxies. Importantly, the velocity dispersion profiles of the orbiting and infalling galaxies contain five independent parameters – three distinct radial scales and two velocity dispersion amplitudes – each of which is correlated with mass. Thus, the velocity dispersion profile of galaxy clusters has inherent redundancies that allow us to perform non-trivial systematics checks from a single data set. We discuss several potential applications of our new model for detecting the edge radius and constraining cosmology and astrophysics using upcoming spectroscopic surveys.

Astronomy & Astrophysics↗
DOE OSTI2020

Cosmic-ray Antinuclei as Messengers of New Physics: Status and Outlook for the New Decade

The precise measurement of cosmic-ray antinuclei serves as an important means for identifying the nature of dark matter and other new astrophysical phenomena, and could be used with other cosmic-ray species to understand cosmic-ray production and propagation in the Galaxy. For instance, low-energy antideuterons would provide a "smoking gun" signature of dark matter annihilation or decay, essentially free of astrophysical background. Studies in recent years have emphasized that models for cosmic-ray antideuterons must be considered together with the abundant cosmic antiprotons and any potential observation of antihelium. Therefore, a second dedicated Antideuteron Workshop was organized at UCLA in March 2019, bringing together a community of theorists and experimentalists to review the status of current observations of cosmic-ray antinuclei, the theoretical work towards understanding these signatures, and the potential of upcoming measurements to illuminate ongoing controversies. This review aims to synthesize this recent work and present implications for the upcoming decade of antinuclei observations and searches. This includes discussion of a possible dark matter signature in the AMS-02 antiproton spectrum, the most recent limits from BESS Polar-II on the cosmic antideuteron flux, and reports of candidate antihelium events by AMS-02; recent collider and cosmic-ray measurements relevant for antinuclei production models; the state of cosmic-ray transport models in light of AMS-02 and Voyager data; and the prospects for upcoming experiments, such as GAPS. This provides a roadmap for progress on cosmic antinuclei signatures of dark matter in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

TDCOSMO. X. Automated modeling of nine strongly lensed quasars and comparison between lens-modeling software

When strong gravitational lenses are to be used as an astrophysical or cosmological probe, models of their mass distributions are often needed. We present a new, time-efficient automation code for the uniform modeling of strongly lensed quasars with GLEE, a lens-modeling software for multiband data. By using the observed positions of the lensed quasars and the spatially extended surface brightness distribution of the host galaxy of the lensed quasar, we obtain a model of the mass distribution of the lens galaxy. We applied this uniform modeling pipeline to a sample of nine strongly lensed quasars for which images were obtained with the Wide Field Camera 3 of the Hubble Space Telescope. The models show well-reconstructed light components and a good alignment between mass and light centroids in most cases. We find that the automated modeling code significantly reduces the input time during the modeling process for the user. The time for preparing the required input files is reduced by a factor of 3 from ~3 h to about one hour. The active input time during the modeling process for the user is reduced by a factor of 10 from ~ 10 h to about one hour per lens system. This automated uniform modeling pipeline can efficiently produce uniform models of extensive lens-system samples that can be used for further cosmological analysis. A blind test that compared our results with those of an independent automated modeling pipeline based on the modeling software Lenstronomy revealed important lessons. Quantities such as Einstein radius, astrometry, mass flattening, and position angle are generally robustly determined. Other quantities, such as the radial slope of the mass density profile and predicted time delays, depend crucially on the quality of the data and on the accuracy with which the point spread function is reconstructed. Better data and/or a more detailed analysis are necessary to elevate our automated models to cosmography grade. Nevertheless, our pipeline enables the quick selection of lenses for follow-up and further modeling, which significantly speeds up the construction of cosmography-grade models. This important step forward will help us to take advantage of the increase in the number of lenses that is expected in the coming decade, which is an increase of several orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

Lunar base options in support of the permanent habitation of space

An overview of the NASA lunar base program which would establish a permanent beachhead on the moon is given. The lunar base would be used to attain science and astronomy objectives, to manufacture lunar-derived resources (particularly propellant oxygen), to support the growing space infrastructure, and to develop and test technologies that would enable near self-sufficiuency in space, limiting the amount of resources required from earth. Research concerning lunar base development, modeling and simulation are presented, including modeling engines, data bases, and subsystem transforms.

Fairchild, Kyle↗
NASA NTRS2006

NASA Laboratory Astrophysics Workshop 2006 Introductory Remarks

NASA Laboratory Astrophysics Workshop 2006, is the fourth in a series of workshops held at four year intervals, to assess the laboratory needs of NASA's astrophysics missions - past, current and future. Investigators who need laboratory data to interpret their observations from space missions, theorists and modelers, experimentalists who produce the data, and scientists who compile databases have an opportunity to exchange ideas and understand each other's needs and limitations. The multi-wavelength character of these workshops allows cross-fertilization of ideas, raises awareness in the scientific community of the rapid advances in other fields, and the challenges it faces in prioritizing its laboratory needs in a tight budget environment. Currently, we are in the golden age of Space Astronomy, with three of NASA s Great Observatories, Hubble Space Telescope (HST), Chandra X-Ray Observatory (CXO), and Spitzer Space Telescope (SST), in operation and providing astronomers and opportunity to perform synergistic observations. In addition, the Far Ultraviolet Spectroscopic Explorer (FUSE), XMM-Newton, HETE-2, Galaxy Evolution Explorer (GALEX), INTEGRAL and Wilkinson Microwave Anisotropy Probe (WMAP), are operating in an extended phase, while Swift and Suzaku are in their prime phase of operations. The wealth of data from these missions is stretching the Laboratory Astrophysics program to its limits. Missions in the future, which also need such data include the James Webb Space Telescope (JWST), Space Interferometry Mission (SIM), Constellation-X (Con-X), Herschel, and Planck. The interpretation of spectroscopic data from these missions requires knowledge of atomic and molecular parameters such as transition probabilities, f-values, oscillator strengths, excitation cross sections, collision strengths, which have either to be measured in the laboratory by simulating space plasma and interactions therein, or by theoretical calculations and modeling. Once the laboratory data are obtained, a key step to making them available to the observer is the creation and maintenance of critically compiled databases. Other areas of study, that are important for understanding planet formation, and for detection of molecules that are indicators of life, are also supported by the Laboratory Astrophysics program. Some examples are: studies of ices and dust grains in a space environment; nature and evolution of interstellar carbon-rich dust; and polycyclic aromatic hydrocarbons. In addition, the program provides an opportunity for the investigation of novel ideas, such as simulating radiative shock instabilities in plasmas, in order to understand jets observed in space. A snapshot of the currently funded program, mission needs, and relevance of laboratory data to interpreting observations, will be obtained at this workshop through invited and contributed talks and poster papers. These will form the basis for discussions in splinter groups. The Science Organization Committee will integrate the results of the discussions into a coherent White Paper, which will provide guidance to NASA in structuring the Laboratory Astrophysics program in subsequent years, and also to the scientific community in submitting research proposals to NASA for funding.

Hasan, Hashima↗
DOE OSTI2022

Photometric redshift estimation with convolutional neural networks and galaxy images: Case study of resolving biases in data-driven methods

Deep-learning models have been increasingly exploited in astrophysical studies, but these data-driven algorithms are prone to producing biased outputs that are detrimental for subsequent analyses. In this work, we investigate two main forms of biases: class-dependent residuals, and mode collapse. We do this in a case study, in which we estimate photometric redshift as a classification problem using convolutional neural networks (CNNs) trained with galaxy images and associated spectroscopic redshifts. We focus on point estimates and propose a set of consecutive steps for resolving the two biases based on CNN models, involving representation learning with multichannel outputs, balancing the training data, and leveraging soft labels. The residuals can be viewed as a function of spectroscopic redshift or photometric redshift, and the biases with respect to these two definitions are incompatible and should be treated individually. We suggest that a prerequisite for resolving biases in photometric space is resolving biases in spectroscopic space. Experiments show that our methods can better control biases than benchmark methods, and they are robust in various implementing and training conditions with high-quality data. Our methods hold promises for future cosmological surveys that require a good constraint of biases, and they may be applied to regression problems and other studies that make use of data-driven models. Nonetheless, the bias-variance tradeoff and the requirement of sufficient statistics suggest that we need better methods and optimized data usage strategies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

H 0 = 69.8 ± 1.3 km s - 1 Mpc - 1 , Ω m 0 = 0.288 ± 0.017 , and other constraints from lower-redshift, non-CMB, expansion-rate data

Here, we use updated Type Ia Pantheon+ supernova, baryon acoustic oscillation, and Hubble parameter (now also accounting for correlations) data, as well as new reverberation-measured C $\tiny{IV}$ quasar data, and quasar angular size, H $\tiny{II}$ starburst galaxy, reverberation-measured Mg $\tiny{II}$ quasar, and Amati correlated gamma-ray burst data to constrain cosmological parameters. We show that these data sets result in mutually consistent constraints and jointly use them to constrain cosmological parameters in six different spatially-flat and non-flat cosmological models. Our analysis provides summary model independent determinations of two key cosmological parameters: the Hubble constant, H 0 = 69.8 ± 1.3 km s -1 Mpc -1 , and the current non-relativistic matter density parameter, Ω m0 = 0.288 ± 0.017. Our summary error bars are 2.4 and 2.3 times those obtained using the flat ΛCDM model and Planck TT,TE,EE + lowE + lensing cosmic microwave background (CMB) anisotropy data. Our H 0 value is very consistent with that from the local expansion rate based on the Tip of the Red Giant Branch and Type Ia supernova (SN Ia) data, is 2σ lower than that from the local expansion rate based on Cepheid and SN Ia data, and is 2σ higher than that in the flat ΛCDM model based on Planck TT,TE,EE + lowE + lensing CMB data. Our data compilation shows at most mild evidence for non-flat spatial hypersurfaces, but more significant evidence for dark energy dynamics, 2σ or larger in the spatially-flat dynamical dark energy models we study.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Selected computations of transonic cavity flows

An efficient diagonal scheme implemented in an overset mesh framework has permitted the analysis of geometrically complex cavity flows via the Reynolds averaged Navier-Stokes equations. Use of rapid hyperbolic and algebraic grid methods has allowed simple specification of critical turbulent regions with an algebraic turbulence model. Comparisons between numerical and experimental results are made in two dimensions for the following problems: a backward-facing step; a resonating cavity; and two quieted cavity configurations. In three-dimensions the flow about three early concepts of the stratospheric Observatory For Infrared Astronomy (SOFIA) are compared to wind-tunnel data. Shedding frequencies of resolved shear layer structures are compared against experiment for the quieted cavities. The results demonstrate the progress of computational assessment of configuration safety and performance.

Atwood, Christopher A.↗
DOE OSTI2023

Domain Adaptation for Measurements of Strong Gravitational Lenses

Upcoming surveys are predicted to discover galaxy-scale strong lenses on the magnitude of 105, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but training only on simulated data results in poor performance on real data. Domain adaptation can bridge the gap between simulated and real datasets. We adopt domain adaptation on the estimation of Einstein radius in simulated galaxy-scale gravitational lensing images. We evaluate two domain adaptation techniques - domain adversarial neural networks (DANN) and maximum mean discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain with emulation of DES survey conditions. We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain datasets. Our results show the potential of using domain adaptation to perform analysis on future survey data with a deep neural network trained on simulated data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Photometric identification of compact galaxies, stars, and quasars using multiple neural networks

We present MargNet, a deep learning-based classifier for identifying stars, quasars, and compact galaxies using photometric parameters and images from the Sloan Digital Sky Survey Data Release 16 catalogue. MargNet consists of a combination of convolutional neural network and artificial neural network architectures. Using a carefully curated data set consisting of 240 000 compact objects and an additional 150 000 faint objects, the machine learns classification directly from the data, minimizing the need for human intervention. MargNet is the first classifier focusing exclusively on compact galaxies and performs better than other methods to classify compact galaxies from stars and quasars, even at fainter magnitudes. This model and feature engineering in such deep learning architectures will provide greater success in identifying objects in the ongoing and upcoming surveys, such as Dark Energy Survey and images from the Vera C. Rubin Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2022

A Census of Young Stellar Objects in Two Line-of-Sight Star-Forming Regions Toward IRAS 22147+5948 in the Outer Galaxy

Context. Star formation in the outer Galaxy, namely, outside of the Solar circle, has not been extensively studied in part due to the low CO brightness of the molecular clouds linked with the negative metallicity gradient. Recent infrared surveys provide an overview of dust emission in large sections of the Galaxy, but they suffer from cloud confusion and poor spatial resolution at far-infrared wavelengths. Aims. We aim to develop a methodology to identify and classify young stellar objects (YSOs) in star-forming regions in the outer Galaxy and use it to resolve a long-standing disparity in terms of the distance and evolutionary status of IRAS 22147+5948. Methods. We used a support vector machine learning algorithm to complement standard color–color and color–magnitude diagrams in our search for YSOs in the IRAS 22147 region, based on publicly available data from the Spitzer Mapping of the Outer Galaxy survey. The agglomerative hierarchical clustering algorithm was used to identify clusters. Then the physical properties of individual YSOs were calculated. The distances were determined using CO 1–0 from the Five College Radio Astronomy Observatory survey. Results. We identified 13 Class I and 13 Class II YSO candidates using the color–color diagrams, along with an additional 2 and 21 sources, respectively, using the applied machine learning techniques. The spectral energy distributions of 23 sources were modeled with a star and a passive disk, corresponding to Class II objects. The models of three sources include envelopes that are typical for Class I objects. The objects were grouped into two clusters located at a distance of 2:2 kpc and 5 clusters at 5:6 kpc. The spatial extent of CO, radio continuum, and dust emission confirms the origin of YSOs in two distinct star-forming regions along a similar line of sight. Conclusions. The outer Galaxy may serve as a unique laboratory for exploring star formation across environments, on the condition that complementary methods and ancillary data are used to properly account for cloud confusion and distance uncertainties.

Agata Karska↗
NASA NTRS1981

Ground-based detection of stratospheric ClO and average column density measurement over 17 days of observation

A very sensitive mm-wave heterodyne receiver of a type originally developed for radio astronomy is used in combination with a broadband filter bank spectrometer to detect and measure the 204-GHz rotational transition of stratospheric ClO. Data is acquired in the form of a dimensionless ratio and is converted to units expressing signal intensity. Computed line shapes are matched against the data for a comparison with theoretical stratospheric models and previous measurements. The ClO distribution in the stratosphere measured at 42 deg N latitude in early spring is significantly different from that expected based on existing theoretical models. There is much less ClO at latitudes below about 36 km than predicted, and average ClO column density found for 42 deg N is 20-30% less than that from existing balloon flight measurements at 32 deg N.

Dezafra, R.↗
NASA NTRS2002

Earth Occultation Techniques

Earth occultation is a familiar phenomenon to all residents of the Earth, although most know it as sunrise and sunset. Satellites observe Earth occultations of an astrophysical source when it sets behind or rises above the Earth's horizon (also called the Earth's limb). Two occultations, a rise and a set, occur every satellite orbit. The most extensive use of Earth occultation to measure sources was with the Burst and Transient Source Experiment (BATSE) on the Compton Gamma Ray Observatory (CGRO) for 9 years. The entire sky was subject to Earth occultation for some portion of CGRO's precession period. In BATSE data, atmospheric attenuation produced step-like features when astrophysical sources underwent occultation. The observed change in count rate in several energy bands provided a measurement of the source intensity and spectrum without requiring sophisticated background models. I will describe (1) a brief history of occultation techniques in X-ray and gamma ray astronomy; (2) how occultation features were used to locate and monitor astrophysical sources with BATSE and (3) how the Earth occultation technique can be applied to future instruments.

Wilson, Colleen A.↗
DOE OSTI2023

MaNGA DynPop – I. Quality-assessed stellar dynamical modelling from integral-field spectroscopy of 10K nearby galaxies: a catalogue of masses, mass-to-light ratios, density profiles, and dark matter

ABSTRACT This is the first paper in our series on the combined analysis of the Dynamics and stellar Population (DynPop) for the MaNGA survey in the final SDSS Data Release 17 (DR17). Here, we present a catalogue of dynamically determined quantities for over 10 000 nearby galaxies based on integral-field stellar kinematics from the MaNGA survey. The dynamical properties are extracted using the axisymmetric Jeans Anisotropic Modelling (JAM) method, which was previously shown to be the most accurate for this kind of study. We assess systematic uncertainties using eight dynamical models with different assumptions. We use two orientations of the velocity ellipsoid: either cylindrically aligned JAMcyl or spherically aligned JAMsph. We also make four assumptions for the models’ dark versus luminous matter distributions: (1) mass-follows-light, (2) free NFW dark halo, (3) cosmologically constrained NFW halo, (4) generalized NFW dark halo, i.e. with free inner slope. In this catalogue, we provide the quantities related to the mass distributions (e.g. the density slopes and enclosed mass within a sphere of a given radius for total mass, stellar mass, and dark matter mass components). We also provide the complete models which can be used to compute the full luminous and mass distribution of each galaxy. Additionally, we visually assess the qualities of the models to help with model selections. We estimate the observed scatter in the measured quantities which decreases as expected with improvements in quality. For the best data quality, we find a remarkable consistency of measured quantities between different models, highlighting the robustness of the results.

Astronomy & Astrophysics↗
DOE OSTI2023

Fast and accurate simulations of calorimeter showers with normalizing flows

In this study, we introduce caloflow, a fast detector simulation framework based on normalizing flows. For the first time, we demonstrate that normalizing flows can reproduce many-channel calorimeter showers with extremely high fidelity, providing a fresh alternative to computationally expensive geant4 simulations, as well as other state-of-the-art fast simulation frameworks based on generative adversarial networks (GANs) or variational autoencoders (VAEs). In addition to the usual histograms of physical features and images of calorimeter showers, we introduce a new metric for judging the quality of generative modeling: the performance of a classifier trained to differentiate real from generated images. We show that GAN-generated images can be identified by the classifier with nearly 100% accuracy, while images generated from caloflow are better able to fool the classifier. More broadly, normalizing flows offer several advantages compared to other state-of-the-art approaches (GANs and VAEs), including tractable likelihoods, stable and convergent training, and principled model selection. Normalizing flows also provide a bijective mapping between data and the latent space, which could have other applications beyond simulation, for example, to detector unfolding.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Probing intergalactic intergalactic magnetic fields with LOFAR LoTSS DR2 data

We use Faraday rotation measurements from the latest catalog LoTSS DR2 from LOFAR to probe intergalactic magnetic fields. To identify the extragalactic component of the observed rotation measure (RM) we use two different techniques: residual rotation measure (RRM) and close radio pairs. For the RRM approach, we conclude that, despite smaller measurement errors in the LOFAR data, robust and conservative treatment of the systematic uncertainties in the Galactic contribution to RM results in the constraint on a homogeneous volume-filling magnetic field at the level 2.4 nG, slightly weaker than previous constraints from NVSS data, and does not allow to probe the presence of over-magnetized bubbles predicted by the AGN feedback model of the IllustrisTNG. Analyzing close radio pairs we found that in only 0.5% of our mock realizations of observed data, the expected contribution from the over-magnetized bubbles does not exceed LoTSS DR2 data.

79 ASTRONOMY AND ASTROPHYSICS↗