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DOE OSTI2025

Microstructure and bonding between calcium aluminate cement‐containing gahnite–alumina matrix and refractory aggregates

Calcium aluminate cement enhances the thermomechanical properties of refractory castables through the formation of acicular calcium hexaluminate (CaO·6Al 2 O 3 ), Ca 2 Mg 2 Al 28 O 46 (CAM-I), and CaMg 2 Al 16 O 27 (CAM-II) phases in MgO- or MgAl 2 O 4 -containing castables. The compatibility of CA 6 with gahnite (ZnAl 2 O 4 ), and acicular Ca 2 Zn 2 Al 28 O 46 (CAZ-I) and CaZn 2 Al 16 O 27 (CAZ-II) phases formation have been previously reported. Here, in this work, the interaction between a CAC binder containing ZnAl 2 O 4 -Al 2 O 3 matrix with commonly used refractory aggregates such as tabular alumina (TA), alumina-rich (AR90, AR78) and stoichiometric (SM72) MgAl 2 O 4 spinels, and fused and dead-burned magnesia (FM, DBM, respectively) were investigated at 1650°C for 5 h. Microstructural analysis, using digital microscopy, scanning electron microscopy, and energy dispersive spectroscopy, revealed the formation of acicular CaZn 0.18 Al 11.82 O 18.91 , CAZ-I and CAZ-II grains, and strong interfacial bonding between the matrix and TA and spinel aggregates. FM and DBM were found to debond from the matrix. Thick interface layers were observed between the matrix and all the aggregates but TA. Null hypothesis significance testing (NHST) shows that the difference in the number of acicular grains between the interface zone and the bulk matrix (Z) is statistically significant for AR90/Z, SM72/Z, FM/Z, and DBM/Z interfaces, but not significant for TA/Z and AR78/Z. The role of the aggregates’ chemistry on the interfacial bonding and microstructure evolution is discussed.

Ramteke, Rajat Durgesh [Univ. of Alabama, Birmingh↗
DOE OSTI2020

The ALFALFA-SDSS Galaxy Catalog

We present a H i optical catalog of ~30,000 galaxies based on the 100% complete Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA) survey combined with data from the Sloan Digital Sky Survey (SDSS). Our goal is to facilitate the public use of the completed ALFALFA catalog by providing carefully determined matches to SDSS counterparts, including matches for ~10,000 galaxies that do not have SDSS spectra. These identifications can provide a basis for further crossmatching with other surveys using SDSS photometric IDs as a reference point. We derive absolute magnitudes and stellar masses for each galaxy using optical colors combined with an internal reddening correction designed for small- and intermediate-mass galaxies with active star formation. We also provide measures of stellar masses and star formation rates based on infrared and/or ultraviolet photometry for galaxies that are detected by the Wide-field Infrared Survey Explorer and/or the Galaxy Evolution Explorer. Finally, we compare the galaxy population in the ALFALFA-SDSS sample with the populations in several other publicly available galaxy catalogs and confirm that ALFALFA galaxies typically have lower masses and bluer colors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The SAGA Survey. V. Modeling Satellite Systems around Milky Way–Mass Galaxies with Updated UniverseMachine

Abstract Environment plays a critical role in shaping the assembly of low-mass galaxies. Here, we use the U niverse M achine (UM) galaxy–halo connection framework and Data Release 3 of the Satellites Around Galactic Analogs (SAGA) Survey to place dwarf galaxy star formation and quenching into a cosmological context. UM is a data-driven forward model that flexibly parameterizes galaxy star formation rates (SFRs) using only halo mass and assembly history. We add a new quenching model to UM, tailored for galaxies with m ⋆ ≲ 10 9 M ⊙ , and constrain the model down to m ⋆ ≳ 10 7 M ⊙ using new SAGA observations of 101 satellite systems around Milky Way (MW)–mass hosts and a sample of isolated field galaxies in a similar mass range from the Sloan Digital Sky Survey. The new best-fit model, “UM-SAGA,” reproduces the satellite stellar mass functions, average SFRs, and quenched fractions in SAGA satellites while keeping isolated dwarfs mostly star-forming. The enhanced quenching in satellites relative to isolated field galaxies leads the model to maximally rely on halo assembly to explain the observed environmental quenching. Extrapolating the model down to m ⋆ ∼ 10 6.5 M ⊙ yields a quenched fraction of ≳30% for isolated field galaxies and ≳80% for satellites of MW-mass hosts at this stellar mass. Spectroscopic surveys can soon test this specific prediction to reveal the relative importance of internal feedback, cessation of mass and gas accretion, satellite-specific gas processes, and reionization for the evolution of faint low-mass galaxies.

Wang, Yunchong (ORCID:000000018913626X)↗
DOE OSTI2022

Discovering Ca II absorption lines with a neural network

Quasar absorption line analysis is critical for studying gas and dust components and their physical and chemical properties as well as the evolution and formation of galaxies in the early universe. Calcium II (Ca II ) absorbers, which are one of the dustiest absorbers and are located at lower redshifts than most other absorbers, are especially valuable when studying physical processes and conditions in recent galaxies. However, the number of known quasar Ca II absorbers is relatively low due to the difficulty of detecting them with traditional methods. In this work, we developed an accurate and quick approach to search for Ca II absorption lines using deep learning. In our deep learning model, a convolutional neural network, tuned using simulated data, is used for the classification task. The simulated training data are generated by inserting artificial Ca II absorption lines into original quasar spectra from the Sloan Digital Sky Survey (SDSS), while an existing Ca II catalogue is adopted as the test set. The resulting model achieves an accuracy of 96 per cent on the real data in the test set. Our solution runs thousands of times faster than traditional methods, taking a fraction of a second to analyse thousands of quasars, while traditional methods may take days to weeks. The trained neural network is applied to quasar spectra from SDSS’s DR7 and DR12 and discovered 399 new quasar Ca II absorbers. In addition, we confirmed 409 known quasar Ca II absorbers identified previously by other research groups through traditional methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Volumetric and shear strain localization throughout triaxial compression experiments on rocks

Deformation localization is a widely observed, but rarely quantified process in the crust. Recent observations suggest that the localization of seismicity and fracture networks can help identify the approach to catastrophic failure. Here, we quantify the localization processes of the volumetric and deviatoric strain components in twelve triaxial compression experiments imaged with X-ray tomography. We capture three-dimensional images of the rock cores during triaxial compressing toward failure, and then calculate the local strain components using digital volume correlation. The divergence and curl of the incremental displacement vector field provide the volumetric and deviatoric components of the strain field. We quantify localization using the proportion of the rock occupied by high magnitudes of the volumetric and deviatoric strains, and the Gini coefficient of these high magnitude strains, which measures the deviation from a uniform process. We find that the vast majority, but not all, of the experiments experience strain localization toward failure. The rocks typically experience their maximum degree of strain localization not immediately preceding failure, but on average at 90% of the failure stress. The volumetric strain tends to localize more than the deviatoric strain. Finally, these observations support using the localization of the volumetric strain, along with the deviatoric strain, to identify the evolution of the precursory phase preceding earthquakes.

58 GEOSCIENCES↗
DOE OSTI2025

Atacama Cosmology Telescope: Multiprobe cosmology with unWISE galaxies and ACT DR6 CMB lensing

We present a joint analysis of the cosmic microwave background (CMB) lensing power spectra measured from the Data Release 6 of the Atacama Cosmology Telescope (ACT) and Planck PR4, cross-correlations between the ACT and Planck lensing reconstruction and galaxy clustering from unWISE, and the unWISE clustering auto-spectrum. We obtain 1.5% constraints on the matter density fluctuations at late times parametrized by the best constrained parameter combination 𝑆$^{3⁢x⁢2⁢pt}_{8}$ ≡ 𝜎 8 ⁢(Ω 𝑚 /0.3) 0.4 = 0.815 ± 0.012. The commonly used 𝑆 8 ≡ 𝜎 8⁢ (Ω 𝑚 /0.3) 0.5 parameter is constrained to 𝑆 8 = 0.816 ± 0.015. In combination with baryon acoustic oscillation (BAO) measurements we find 𝜎 8 = 0.815 ± 0.012. We also present sound-horizon-independent estimates of the present day Hubble rate of 𝐻 0 = 66.4$^{+3.2}_{−3.7}$ km s −1 Mpc −1 from our large scale structure data alone and 𝐻 0 = 64.3$^{+2.1}_{−2.4}$ km s −1 Mpc −1 in combination with uncalibrated supernovae from Pantheon+. Using parametric estimates of the evolution of matter density fluctuations, we place constraints on cosmic structure in a range of high redshifts typically inaccessible with cross-correlation analyses. Combining lensing cross- and autocorrelations, we derive a 3.3% constraint on the integrated matter density fluctuations above 𝑧 = 2.4, one of the tightest constraints in this redshift range and fully consistent with a Λ cold dark matter (Λ⁢CDM) model fit to the primary CMB from Planck. Finally, combining with primary CMB observations and using the extended low redshift coverage of these combined datasets we derive constraints on a variety of extensions to the Λ⁢CDM model including massive neutrinos, spatial curvature, and dark energy. We find in flat Λ⁢CDM⁢ ∑𝑚 𝜈 < 0.12 eV at 95% confidence using the large scale structure data, BAO measurements from Sloan Digital Sky Survey, and primary CMB observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Mass Dependence of Galaxy–Halo Alignment in LOWZ and CMASS

We measure the galaxy-ellipticity (GI) correlations for the Sloan Digital Sky Survey Data Release 12 LOWZ and CMASS samples with the shape measurements from the DESI Legacy Imaging Surveys. We model the GI correlations in an N-body simulation with our recent accurate stellar–halo mass relation from the Photometric object Around Cosmic webs (PAC) method. The large data set and our accurate modeling turns out an accurate measurement of the alignment angle between central galaxies and their host halos. We find that the alignment of central elliptical galaxies with their host halos increases monotonically with galaxy stellar mass or host halo mass, which can be well described by a power law for the massive galaxies. We also find that central elliptical galaxies are more aligned with their host halos in LOWZ than in CMASS, which might indicate an evolution of galaxy–halo alignment, though future studies are needed to verify this is not induced by the sample selections. In contrast, central disk galaxies are aligned with their host halos about 10 times more weakly in the GI correlation. These results have important implications for intrinsic alignment (IA) correction in weak lensing studies, IA cosmology, and theory of massive galaxy formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Chandra view of the relation between X-ray and UV emission in quasars

Here, we present a study of the relation between X-rays and ultraviolet emission in quasars for a sample of broad-line, radio-quiet objects obtained from the cross-match of the Sloan Digital Sky Survey DR14 with the latest Chandra Source Catalog 2.0 (2332 quasars) and the Chandra COSMOS Legacy survey (273 quasars). The non-linear relation between the ultraviolet (at 2500 Å, L UV ) and the X-ray (at 2 keV, L X ) emission in quasars has been proved to be characterised by a smaller intrinsic dispersion than the observed one, as long as a homogeneous selection, aimed at preventing the inclusion of contaminants in the sample, is fulfilled. By leveraging on the low background of Chandra, we performed a complete spectral analysis of all the data available for the SDSS-CSC2.0 quasar sample (i.e. 3430 X-ray observations), with the main goal of reducing the uncertainties on the source properties (e.g. flux, spectral slope). We analysed whether any evolution of the L X – L UV relation exists by dividing the sample in narrow redshift intervals across the redshift range spanned by our sample, z ≃ 0.5–4. We find that the slope of the relation does not evolve with redshift and it is consistent with the literature value of 0.6 over the explored redshift range, implying that the mechanism underlying the coupling of the accretion disc and hot corona is the same at the different cosmic epochs. We also find that the dispersion decreases when examining the highest redshifts, where only pointed observations are available. These results further confirm that quasars are ‘standardisable candles’, that is we can reliably measure cosmological distances at high redshifts where very few cosmological probes are available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The KLEVER survey: nitrogen abundances at z ~ 2 and probing the existence of a fundamental nitrogen relation

Here we present a comparison of the nitrogen-to-oxygen ratio (N/O) in 37 high-redshift galaxies at z ~ 2 taken from the KMOS Lensed Emission Lines and VElocity Review (KLEVER) Survey with a comparison sample of local galaxies, taken from the Sloan Digital Sky Survey (SDSS). The KLEVER sample shows only a mild enrichment in N/O of +0.1 dex when compared to local galaxies at a given gas-phase metallicity (O/H), but shows a depletion in N/O of –0.35 dex when compared at a fixed stellar mass (M * ). We find a strong anticorrelation in local galaxies between N/O and SFR in the M * –N/O plane, similar to the anticorrelation between O/H and SFR found in the mass–metallicity relation (MZR). We use this anticorrelation to construct a fundamental nitrogen relation (FNR), analogous to the fundamental metallicity relation (FMR). We find that KLEVER galaxies are consistent with both the FMR and the FNR. This suggests that the depletion of N/O in high-z galaxies when considered at a fixed M * is driven by the redshift evolution of the mass–metallicity relation in combination with a near redshift-invariant N/O–O/H relation. Furthermore, the existence of an fundamental nitrogen relation suggests that the mechanisms governing the fundamental metallicity relation must be probed by not only O/H, but also N/O, suggesting pure-pristine gas inflows are not the primary driver of the FMR, and other properties such as variations in galaxy age and star formation efficiency must be important.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2024

The Impact of Void-finding Algorithms on Galaxy Classification

We explore how the definition of a void influences the conclusions drawn about the impact of the void environment on galactic properties using two void-finding algorithms in the Void Analysis Software Toolkit: Voronoi Voids (V 2 ), a Python implementation of ZOnes Bordering On Voidness (ZOBOV); and VoidFinder, an algorithm that grows and merges spherical void regions. Using the Sloan Digital Sky Survey Data Release 7, we find that galaxies found in VoidFinder voids tend to be bluer and fainter and to have higher (specific) star formation rates than galaxies in denser regions. Conversely, galaxies found in V 2 voids show less significant differences when compared to galaxies in denser regions, less consistent with the large-scale environmental effects on galaxy properties expected from both simulations and previous observations. These results align with previous simulation results that show V 2 -identified voids “leak” into the dense walls between voids because their boundaries extend up to the density maxima in the walls. As a result, when using ZOBOV-based void-finders, galaxies likely to be part of wall regions are instead classified as void galaxies, a misclassification that can be critical to our understanding of galaxy evolution.

cosmic web↗
DOE OSTI2026

How Snow Drives the Seasonal Evolution of Land and Sea Surface Albedos in the Alaskan High Arctic: Final Technical Report

The purpose of the project was to observe and quantify temporal variation in snow albedo and snow characteristics across the Arctic coastal landscape as winter transitioned into spring and snowmelt occurred, both on tundra and sea ice. This transition is bounded by fully snow-covered landscapes with broadband albedos of approximately 0.8 and snow-free landscapes with albedos of 0.15 (tundra or ponded sea ice). For these landscapes, we monitored the spring surface characteristics and radiative properties nearly daily at three locations on or near the Department of Energy ARM North Slope of Alaska (NSA) User Facility in Utqiagvik, Alaska: the central NSA Facility (hereafter called ARM), one near NSA-E12 (BEO), and one on the sea ice of Elson Lagoon (ICE) during three melt seasons (2019, 2022, and 2024). The field campaign component of this award was named SALVO ( S now AL bedo E VO lution). Typical field seasons began in mid-April and lasted until mid-June. Main measurements included snow depth (at 1-m intervals), broadband albedo (at 5-m intervals), spectral albedo (at 5- m intervals), and multiple digital images. Orthomosaics were converted into binary images to determine the snow-covered fraction over time across various landscapes. Additional measurements included basic weather data and snow-ground (or ice) interface temperatures. Sky conditions were observed and photographed to help assess albedo values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Influence of cementation on the yield surface of rocks numerically determined from digital microstructures

Digital Rock Physics has reached a level of maturity on the characterisation of primary properties that depend on the microstructure – such as porosity, permeability or elastic moduli – by numerically solving field equations on μCT scan images of rock. After small deformations or at depth though, most rocks eventually reach their limit of elasticity and the complementary plastic properties are needed to describe the full mechanical behaviour. Currently, determination of a rock’s yield surface from its microstructure is often restricted to semi-analytical criteria derived by limit analysis or numerical simulations performed on idealised geometries. Such simplification lacks representativeness, particularly for processes that affect directly the pore-grain interface such as the cementation phenomenon, happening during diagenesis. Eventually, only direct numerical simulation of elasto-plasticity performed on digitalised microstructures can be used to assess the strength of different cemented materials and its evolution with the alteration of the microstructure. In this study, we provide a comprehensive parametric study on the impact of cementation on rock strength for real microstructures of cemented granular materials. Compared to most previous studies, the whole yield surface is determined numerically (using Finite Element Method) in order to assess the influence of cementation for different stress-paths. The previously known tendency of rock to strengthen with increasing cementation volume is verified. New results on the influence of cement property namely Young’s modulus, friction and cohesion on the rock’s yield surface are explored. The envelopes obtained are compared to the ones obtained by experimental data and existing models. Finally, the framework presented in this study showcases the wider possibility of determining any rock’s or porous material’s yield surface from its microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.

galaxies: interactions↗
DOE OSTI2020

Reliable photometric membership (RPM) of galaxies in clusters – I. A machine learning method and its performance in the local universe

ABSTRACT We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probability from galaxy photometric parameters and finally derive a membership classification. After testing several machine learning techniques (such as stochastic gradient boosting, model averaged neural network and k-nearest neighbours), we found the support vector machine algorithm to perform better when applied to our data. Our training and validation data are from the Sloan Digital Sky Survey main sample. Hence, to be complete to $M_r^* + 3$, we limit our work to 30 clusters with $z$phot-cl ≤ 0.045. Masses (M200) are larger than $\sim 0.6\times 10^{14} \, \mathrm{M}_{\odot }$ (most above $3\times 10^{14} \, \mathrm{M}_{\odot }$). Our results are derived taking in account all galaxies in the line of sight of each cluster, with no photometric redshift cuts or background corrections. Our method is non-parametric, making no assumptions on the number density or luminosity profiles of galaxies in clusters. Our approach delivers extremely accurate results (completeness, C $\sim 92{\rm{ per\ cent}}$ and purity, P $\sim 87{\rm{ per\ cent}}$) within R200, so that we named our code reliable photometric membership. We discuss possible dependencies on magnitude, colour, and cluster mass. Finally, we present some applications of our method, stressing its impact to galaxy evolution and cosmological studies based on future large-scale surveys, such as eROSITA, EUCLID, and LSST.

Lopes, Paulo A. A.↗
DOE OSTI2026

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗
DOE OSTI2022

Quasar UV Luminosity Function at 3.5 < z < 5.0 from SDSS Deep Imaging Data

We present a well-designed sample of more than 1000 type 1 quasars at 3.5 < z < 5 and derive UV quasar luminosity functions (QLFs) in this redshift range. These quasars were selected using the Sloan Digital Sky Survey (SDSS) imaging data in the Stripe 82 and overlap regions with repeat imaging observations that are about 1 mag fainter than the SDSS single-epoch data. The follow-up spectroscopic observations were conducted by the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) as one of the BOSS ancillary programs. Reaching i ~ 21.5 mag, our sample bridges previous samples from brighter and deeper surveys. We use a 1/V a method to derive binned QLFs at 3.6 < z < 4.0, 4.0 < z < 4.5, and 4.5 < z < 4.9 and then use a double power-law model to parameterize the QLFs. We also combine our data with literature QLFs to better constrain the QLFs across a much wider luminosity baseline. The faint- and bright-end slopes of the QLFs in this redshift range are around –1.7 and –3.7, respectively, with uncertainties from 0.2 to 0.3 to >0.5. The evolution of the QLFs from z ~ 5 to 3.5 can be described by a pure density evolution model (∝10 kz ) with a parameter k similar to that at 5 < z < 7, suggesting a nearly uniform evolution of the quasar density at z = 3.5–7.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Transient Radio Emission from Low-redshift Galaxies at z < 0.3 Revealed by the VLASS and FIRST Surveys

We present the discovery of a sample of 18 low-redshift (z < 0.3) galaxies with transient nuclear radio emission. These galaxies are not detected or are weakly detected in the Faint Images of the Radio Sky at Twenty cm survey, performed from 1993–2009, but have brightened significantly in radio flux (by a factor of ≳5) in the epoch I (2017–2019) observations of the Very Large Array Sky Survey (VLASS). All 18 galaxies have been detected in VLASS epoch II observations, from 2020–2021, from which the radio flux has been found to evolve slowly (with variability amplitudes of ≳40%) over a period of about 3 yr. 15 galaxies have been observed in the Rapid ASKAP Continuum Survey, and a flat or inverted spectral slope between 888 MHz and 3 GHz is found. Based on the Sloan Digital Sky Survey spectra taken before the radio brightening, 14 of the 18 galaxies can be classified as LINERs or normal galaxies with weak or no nuclear activity. Most galaxies are red and massive, with more than half having central black hole masses above 10 8 M ⊙ . We find that only one galaxy in our sample displays an optical flare lasting for at least two months, with a long decay in the infrared light curve that can be explained as the dust-heated echo emission of a central optical flare, such as a stellar tidal disruption event. We discuss several possibilities for the transient radio emission and conclude that it is likely associated with a newborn radio jet triggered by short sporadic fueling of a supermassive black hole. Such a scenario can be tested with further multifrequency radio observations of these sources, via measuring their radio flux variability and spectral evolution.

79 ASTRONOMY AND ASTROPHYSICS↗