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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Redshift Evolution of the Feedback–Cooling Equilibrium in the Core of 48 SPT Galaxy Clusters: A Joint Chandra–SPT–ATCA Analysis

We analyze the cooling and feedback properties of 48 galaxy clusters at redshifts 0.4 < z < 1.3 selected from the South Pole Telescope (SPT) catalogs to evolve like the progenitors of massive and well-studied systems at z ~ 0. We estimate the radio power at the brightest cluster galaxy (BCG) location of each cluster from an analysis of Australia Telescope Compact Array data. Assuming that the scaling relation between the radio power and active galactic nucleus (AGN) cavity power P cav observed at low redshift does not evolve with redshift, we use these measurements in order to estimate the expected AGN cavity power in the core of each system. We estimate the X-ray luminosity within the cooling radius L cool of each cluster from a joint analysis of the available Chandra X-ray and SPT Sunyaev–Zel'dovich (SZ) data. This allows us to characterize the redshift evolution of the P cav /L cool ratio. When combined with low-redshift results, these constraints enable investigations of the properties of the feedback–cooling cycle across 9 Gyr of cluster growth. We model the redshift evolution of this ratio measured for cool-core clusters by a log-normal distribution Log-N (α + βz, σ 2 ) and constrain the slope of the mean evolution to β = -0.05 ± 0.47. This analysis improves the constraints on the slope of this relation by a factor of two. We find no evidence of redshift evolution of the feedback–cooling equilibrium in these clusters, which suggests that the onset of radio-mode feedback took place at an early stage of cluster formation. High values of P cav /L cool are found at the BCG location of noncool-core clusters, which might suggest that the timescales of the AGN feedback cycle and the cool core–noncool core transition are different. This work demonstrates that the joint analysis of radio, SZ, and X-ray data solidifies the investigation of AGN feedback at high redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Machine Learning–Based Approach to Time-series Wave Identification in the Solar Wind

The Wind spacecraft has yielded several decades of high-resolution magnetic field data, a large fraction of which displays small-scale structures. In particular, the solar wind is full of wavelike fluctuations that appear in both the field magnitude and its components. The nature of these fluctuations can be tied to the properties of other structures in the solar wind, such as shocks, that have implications for the time evolution of the solar wind. As such, having a large collection of wave events would facilitate further study of the effects that these fluctuations have on solar wind evolution. Given the large volume of magnetic field data available, machine learning is the most practical approach to classifying the myriad small-scale structures observed. To this end, a subset of Wind data is labeled and used as a training set for a multibranch 1D convolutional neural network aimed at classifying circularly polarized wave modes. Using this algorithm, a preliminary statistical study of 1 yr of data is performed, yielding about 300,000 wave intervals out of about 5,000,000 solar wind intervals. The wave intervals come about more often in the fast solar wind and at higher temperatures, and the number of waves per day is highly periodic. This machine learning–based approach to wave detection has the potential to be a powerful, inexpensive way to catalog waves throughout decades of spacecraft data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Improved Tomographic Binning of 3 × 2 pt Lens Samples: Neural Network Classifiers and Optimal Bin Assignments

Abstract Large imaging surveys, such as the Legacy Survey of Space and Time, rely on photometric redshifts and tomographic binning for 3 × 2 pt analyses that combine galaxy clustering and weak lensing. In this paper, we propose a method for optimizing the tomographic binning choice for the lens sample of galaxies. We divide the CosmoDC2 and Buzzard simulated galaxy catalogs into a training set and an application set, where the training set is nonrepresentative in a realistic way, and then estimate photometric redshifts for the application sets. The galaxies are sorted into redshift bins covering equal intervals of redshift or comoving distance, or with an equal number of galaxies in each bin, and we consider a generalized extension of these approaches. We find that bins of equal comoving distance produce the highest dark energy figure of merit of the initial binning choices, but that the choice of bin edges can be further optimized. We then train a neural network classifier to identify galaxies that are either highly likely to have accurate photometric redshift estimates or highly likely to be sorted into the correct redshift bin. The neural network classifier is used to remove poor redshift estimates from the sample, and the results are compared to the case when none of the sample is removed. We find that the neural network classifiers are able to improve the figure of merit by ∼13% and are able to recover ∼25% of the loss in the figure of merit that occurs when a nonrepresentative training sample is used.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Constraints on Populations of Neutrino Sources from Searches in the Directions of IceCube Neutrino Alerts

Beginning in 2016, the IceCube Neutrino Observatory has sent out alerts in real time containing the information of high-energy ($E$ ≳ 100 TeV) neutrino candidate events with moderate to high (≳30%) probability of astrophysical origin. In this work, we use a recent catalog of such alert events, which, in addition to events announced in real time, includes events that were identified retroactively and covers the time period of 2011–2020. We also search for additional, lower-energy neutrinos from the arrival directions of these IceCube alerts. We show how performing such an analysis can constrain the contribution of rare populations of cosmic neutrino sources to the diffuse astrophysical neutrino flux. After searching for neutrino emission coincident with these alert events on various timescales, we find no significant evidence of either minute-scale or day-scale transient neutrino emission or of steady neutrino emission in the direction of these alert events. This study also shows how numerous a population of neutrino sources has to be to account for the complete astrophysical neutrino flux. Assuming that sources have the same luminosity, an $E$ -2.5 neutrino spectrum, and number densities that follow star formation rates, the population of sources has to be more numerous than 7 × 10 -9 Mpc -3 . This number changes to 3 × 10 -7 Mpc -3 if number densities instead have no cosmic evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80-channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Identification of Galaxy–Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning

We perform a search for galaxy–galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey, which contains ~520 million astronomical sources covering ~4000 deg 2 of the southern sky to a 5σ point–source depth of g = 24.3, r= 23.9, i = 23.3, and z = 22.8 mag. Following the methodology of similar searches using Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of ~11 million extended astronomical sources. After scoring with our CNN, the highest-scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap (b > 10 deg) and southern celestial hemisphere (decl. < 0 deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates that were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The Demographics, Stellar Populations, and Star Formation Histories of Fast Radio Burst Host Galaxies: Implications for the Progenitors

We present a comprehensive catalog of observations and stellar population properties for 23 highly secure host galaxies of fast radio bursts (FRBs). Our sample comprises 6 repeating FRBs and 17 apparent nonrepeaters. We present 82 new photometric and 8 new spectroscopic observations of these hosts. Using stellar population synthesis modeling and employing nonparametric star formation histories (SFHs), we find that FRB hosts have a median stellar mass of ≈10 9.9 M ⊙ , mass-weighted age ≈5.1 Gyr, and ongoing star formation rate ≈1.3 M ⊙ yr -1 but span wide ranges in all properties. Classifying the hosts by degree of star formation, we find that 87% (20 of 23 hosts) are star-forming, two are transitioning, and one is quiescent. The majority trace the star-forming main sequence of galaxies, but at least three FRBs in our sample originate in less-active environments (two nonrepeaters and one repeater). Across all modeled properties, we find no statistically significant distinction between the hosts of repeaters and nonrepeaters. However, the hosts of repeating FRBs generally extend to lower stellar masses, and the hosts of nonrepeaters arise in more optically luminous galaxies. While four of the galaxies with the clearest and most prolonged rises in their SFHs all host repeating FRBs, demonstrating heightened star formation activity in the last ≲100 Myr, one nonrepeating host shows this SFH as well. Our results support progenitor models with short delay channels (i.e., magnetars formed via core-collapse supernova) for most FRBs, but the presence of some FRBs in less-active environments suggests a fraction form through more delayed channels.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2023

FAST Drift Scan Survey for Ηι Intensity Mapping: I. Preliminary Data Analysis

This work presents the initial results of the drift-scan observation for the neutral hydrogen (Hi) intensity mapping survey with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The data analyzed in this work were collected in night observations from 2019 through 2021. The primary findings are based on 28 hr of drift-scan observation carried out over 7 nights in 2021, which covers 60 deg 2 sky area. Our main findings are, first, our calibration strategy can successfully correct both the temporal and bandpass gain variation over the 4 hr drift-scan observation. Second, the continuum maps of the surveyed region are made with frequency resolution of 28 kHz and pixel area of $_{2.95\,{\mathrm{arcmin}}^{2}}$. The pixel noise levels of the continuum maps are slightly higher than the forecast assuming $T$ sys = 20 K, which are 36.0 mK (for 10.0 s integration time) at the 1050–1150 MHz band, and 25.9 mK (for 16.7 s integration time) at the 1323–1450 MHz band, respectively. Third, the flux-weighted differential number count is consistent with the NRAO-VLA Sky Survey (NVSS) catalog down to the confusion limit ~7 mJy beam –1 . Finally, the continuum flux measurements of the sources are consistent with those found in the literature. The difference in the flux measurement of 81 isolated NVSS sources is about 6.3%. Our research offers a systematic analysis for the FAST Hi intensity mapping drift-scan survey and serves as a helpful resource for further cosmology and associated galaxies sciences with the FAST drift-scan survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program

Abstract We introduce the DESI LOW- Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift target selection method. Our selection consists of a set of color and surface brightness cuts, combined with modern machine-learning methods, to target low-redshift dwarf galaxies ( z < 0.03) between 19 < r < 21 with high completeness. We employ a convolutional neural network (CNN) to select high-priority targets. The LOW- Z survey has already obtained over 22,000 redshifts of dwarf galaxies ( M * < 10 9 M ⊙ ), comparable to the number of dwarf galaxies discovered in the Sloan Digital Sky Survey DR8 and GAMA. As a spare fiber survey, LOW- Z currently receives fiber allocation for just ∼50% of its targets. However, we estimate that our selection is highly complete: for galaxies at z < 0.03 within our magnitude limits, we achieve better than 95% completeness with ∼1% efficiency using catalog-level photometric cuts. We also demonstrate that our CNN selections z < 0.03 galaxies from the photometric cuts subsample at least 10 times more efficiently while maintaining high completeness. The full 5 yr DESI program will expand the LOW- Z sample, densely mapping the low-redshift Universe, providing an unprecedented sample of dwarf galaxies, and providing critical information about how to pursue effective and efficient low-redshift surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Search for IceCube Sub-TeV Neutrinos Correlated with Gravitational-wave Events Detected By LIGO/Virgo

The LIGO/Virgo collaboration published the catalogs GWTC-1, GWTC-2.1, and GWTC-3 containing candidate gravitational-wave (GW) events detected during its runs O1, O2, and O3. These GW events can be possible sites of neutrino emission. In this paper, we present a search for neutrino counterparts of 90 GW candidates using IceCube DeepCore, the low-energy infill array of the IceCube Neutrino Observatory. The search is conducted using an unbinned maximum likelihood method, within a time window of 1000 s, and uses the spatial and timing information from the GW events. The neutrinos used for the search have energies ranging from a few GeV to several tens of TeV. We do not find any significant emission of neutrinos, and place upper limits on the flux and the isotropic-equivalent energy emitted in low-energy neutrinos. We also conduct a binomial test to search for source populations potentially contributing to neutrino emission. We report a nondetection of a significant neutrino-source population with this test.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

A Comparison of Void-finding Algorithms Using Crossing Numbers

We study how well void-finding algorithms identify cosmic void regions and whether we can quantitatively and qualitatively compare the voids they find with dynamical information from the underlying matter distribution. Using the ORIGAMI algorithm to determine the number of dimensions along which dark matter particles have undergone shell crossing (crossing number) in N-body simulations from the AbacusSummit simulation suite, we identify dark matter particles that have undergone no shell crossing as belonging to voids. We then find voids in the corresponding halo distribution using two different void-finding algorithms: VoidFinder and V 2 , a ZOBOV-based algorithm. The resulting void catalogs are compared to the distribution of dark matter particles to examine how their crossing numbers depend on void proximity. While both algorithms' voids have a similar distribution of crossing numbers near their centers, we find that beyond 0.25 times the effective void radius, voids found by VoidFinder exhibit a stronger preference for particles with low crossing numbers than those found by V 2 . We examine two possible methods of mitigating this difference in efficacy between the algorithms. While we are able to partially mitigate the ineffectiveness of V 2 by using the distance from the void edge as a measure of centrality, we conclude that VoidFinder more reliably identifies dynamically distinct regions of low crossing number.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

DESI Survey Validation Data in the COSMOS/Hyper Suprime-Cam Field: Cool Gas Trace Main-sequence Star-forming Galaxies at the Cosmic Noon

We present the first result in exploring the gaseous halo and galaxy correlation using the Dark Energy Spectroscopic Instrument survey validation data in the Cosmic Evolution Survey (COSMOS) and Hyper Suprime-Cam field. We obtain multiphase gaseous halo properties in the circumgalactic medium by using 115 quasar spectra (signal-to-noise ratio > 3). We detect Mg ii absorption at redshift 0.6 < z < 2.5, C iv absorption at 1.6 < z < 3.6, and H i absorption associated with the Mg ii and C iv. By crossmatching the COSMOS2020 catalog, we identify the Mg ii and C iv host galaxies in 10 quasar fields at 0.9< z < 3.1. We find that within the impact parameter of 250 kpc, a tight correlation is seen between the strong Mg ii equivalent width and the host galaxy star formation rate. The covering fraction f c of the strong Mg ii selected galaxies, which is the ratio of the absorbing galaxy in a certain galaxy population, shows significant evolution in the main-sequence galaxies and marginal evolution in all the galaxy populations within 250 kpc at 0.9 < z < 2.2. The f c increase in the main-sequence galaxies likely suggests the coevolution of strong Mg ii absorbing gas and the main-sequence galaxies at the cosmic noon. Furthermore, Mg ii and C iv absorbing gas is detected out of the galaxy virial radius, tentatively indicating the feedback produced by the star formation and/or the environmental effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Fermi-LAT Detection of the Supernova Remnant G312.4-0.4 in the Vicinity of 4FGL J1409.1-6121e

Abstract Gamma-ray emission provides constraints on the nonthermal radiation processes at play in astrophysical particle accelerators. This allows both the nature of accelerated particles and the maximum energy that they can reach to be determined. Notably, it remains an open question to what extent supernova remnants contribute to the sea of Galactic cosmic rays. In the Galactic plane, at around 312° of Galactic longitude, Fermi-LAT observations show an extended source (4FGL J1409.1−6121e) around five powerful pulsars. This source is described by one large disk of 0.°7 radius with a high significance of 45σin the 4FGL-DR3 catalog. Using 14 yr of Fermi-LAT observations, we revisited this region with a detailed spectro-morphological analysis in order to disentangle its underlying structure. Three sources have been distinguished, including the supernova remnant G312.4−0.4 whose gamma-ray emission correlates well with the shell observed at radio energies. The hard spectrum detected by the LAT, extending up to 100 GeV without any sign of a cutoff, is well reproduced by a purely hadronic model.

Astronomy & Astrophysics↗
DOE OSTI2024

Characterizing the Gamma-Ray Emission Properties of the Globular Cluster M5 with the Fermi-LAT

Abstract We analyzed the globular cluster M5 (NGC 5904) using 15 yr of gamma-ray data from the Fermi Large Area Telescope (LAT). Using rotation ephemerides generated from Arecibo and FAST radio telescope observations, we searched for gamma-ray pulsations from the seven millisecond pulsars (MSPs) identified in M5. We detected no significant pulsations from any of the individual pulsars. In addition, we searched for possible variations of the gamma-ray emission as a function of orbital phase for all six MSPs in binary systems, but we did not detect any significant modulations. The gamma-ray emission from the direction of M5 is well described by an exponentially cutoff power-law spectral model, although other models cannot be excluded. The phase-averaged emission is consistent with being steady on a timescale of a few months. We estimate the number of MSPs in M5 to be between 1 and 10, using the gamma-ray conversion efficiencies for well-characterized gamma-ray MSPs in the Third Fermi-LAT Catalog of Gamma-ray Pulsars, suggesting that the sample of known MSPs in M5 is (nearly) complete, even if it is not currently possible to rule out a diffuse component of the observed gamma rays from the cluster.

Astronomy & Astrophysics↗
DOE OSTI2024

symfind : Addressing the Fragility of Subhalo Finders and Revealing the Durability of Subhalos

Abstract A major question in ΛCDM is what this theory actually predicts for the properties of subhalo populations. Subhalos are difficult to accurately simulate and to find within simulations, and this propagates into uncertainty in theoretical predictions for satellite galaxies. We present Symfind , a new particle-tracking-based subhalo finder, and demonstrate that it can track subhalos to orders-of-magnitude lower masses than commonly used halo-finding tools, with a focus on Rockstar and consistent-trees . These longer survival times mean that at a fixed peak subhalo mass, we find ≈ 15%–40% more subhalos within the virial radius, R vir , and ≈35%–120% more subhalos within R vir /4 in the Symphony dark-matter-only simulation suite. More subhalos are found as the resolution is increased, in contrast to the Rockstar halo finder, which appears to be converged at smaller subhalo counts. We perform extensive numerical testing. In agreement with idealized simulations, we show that the v max , the maximum circular velocity, is systematically biased low until high resolutions ( n peak ≳ 3 × 10 4 ) are achieved, but that mass loss itself can be resolved at much more modest resolutions ( n peak ≳ 4 × 10 3 ). We show that Rockstar converges to false solutions for the mass function, radial distribution, and disruption masses of subhalos. We argue that our new method can trace resolved subhalos until the point of typical galaxy disruption without invoking post hoc orphan modeling. We outline a concrete set of steps for determining whether other subhalo finders meet the same criteria. We publicly release Symfind catalogs and particle data for the Symphony simulation suite at http://web.stanford.edu/group/gfc/symphony .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Filaments of the Slime Mold Cosmic Web and How They Affect Galaxy Evolution

Abstract We present a novel approach for identifying cosmic web filaments within theDisPerSEstructure identification framework, using cosmic density field estimates from the Monte Carlo Physarum Machine (MCPM), inspired by the slime mold organism. We apply our method to the IllustrisTNG (TNG100) cosmological simulations and investigate the impact of filaments on galaxies. The MCPM density field is superior to the Delaunay tessellation field estimator in tracing the true underlying matter distribution and allows filaments to be identified with higher fidelity, finding more low-prominence/diffuse filaments. Using our new filament catalogs, we find that ≳90% of galaxies are located within ∼1.5 Mpc of a filamentary spine, with little change in the median star formation activity with distance to the nearest filament. Instead, we uncover a differential effect of the local filament line density, Σ fil (MCPM)—the total MCPM overdensity per unit length along a filament segment—on galaxy formation: most galaxies are quenched and gas-poor near high-line density filaments atz≤ 1. At earlier times, the filamentary environment appears to have no effect on galactic gas supply and quenching. Atz= 0, quenching in log ( M * / M ⊙ ) ≳ 10.5 galaxies is mainly driven by mass, while lower-mass galaxies are significantly affected by the filament line density. Satellites are far more susceptible to filaments than centrals. The local environments of massive halos are not sufficient to account for the effect of filament line density on gas removal and quenching. Our new approach holds great promise for observationally identifying filaments from galaxy surveys such as SDSS and DESI.

Astronomy & Astrophysics↗