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At least 883 records · Page 49

Chimera F-Series Gravitational Wave Emission Sourced from Matter and Neutrino Anisotropy

This dataset contains gravitational wave data sourced from the the time-dependent fluid quadrupole motion as well as neutrino anisotropy, in the Chimera F-Series two-dimensional core collapse supernova simulations. Data from two models initiated from two different progenitors are presented: F15.78 and F15.79. Please see the README for more information about the data structure and progenitors.

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The Tidal Clock Effects of the Lunisolar Gravitational Field and the Earth’s Tidal Deformation

State-of-the-art atomic and optical clocks have the great potential to precisely test fundamental physical assumptions and enhance our understanding of nature. Their widespread applications require us to rigorously deduce the relativistic frequency shift in the framework of general relativity. One interesting question for clocks is tidal field effect which contains variously periodic variations. By introducing tidally deformed Earth, the general algorithms for clock and frequency comparisons are derived. We investigate the effects of external gravitational bodies and Earth’s tidal deformation on the ground- and space-based clocks. The orbital elements of satellite and locations of laboratory are introduced for corresponding clocks, in which the secular and long-period terms and short-period terms are subsequently presented. These effects called tidal clock effects produce the non-negligible contributions in the modern clock experiments and can be directly evaluated from our parameterized formulas. In addition, we also demonstrate for tidal clock effects the position and distance dependences, as well as periodicity. These tidal effects and dependences can provide valuable information for the clock comparison experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovering New Strong Gravitational Lenses in the DESI Legacy Imaging Surveys

We have conducted a search for new strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys' Data Release 8. We use deep residual neural networks, building on previous work presented by Huang et al. These surveys together cover approximately one-third of the sky visible from the Northern Hemisphere, reaching a z-band AB magnitude of ~22.5. We compile a training sample that consists of known lensing systems as well as non-lenses in the Legacy Surveys and the Dark Energy Survey. After applying our trained neural networks to the survey data, we visually inspect and rank images with probabilities above a threshold. In this work, we present 1210 new strong lens candidates.

79 ASTRONOMY AND ASTROPHYSICS↗

Hierarchical Inference with Bayesian Neural Networks: An Application to Strong Gravitational Lensing

In the past few years, approximate Bayesian Neural Networks (BNNs) have demonstrated the ability to produce statistically consistent posteriors on a wide range of inference problems at unprecedented speed and scale. However, any disconnect between training sets and the distribution of real-world objects can introduce bias when BNNs are applied to data. This is a common challenge in astrophysics and cosmology, where the unknown distribution of objects in our universe is often the science goal. In this work, we incorporate BNNs with flexible posterior parameterizations into a hierarchical inference framework that allows for the reconstruction of population hyperparameters and removes the bias introduced by the training distribution. We focus on the challenge of producing posterior PDFs for strong gravitational lens mass model parameters given Hubble Space Telescope–quality single-filter, lens-subtracted, synthetic imaging data. We show that the posterior PDFs are sufficiently accurate (statistically consistent with the truth) across a wide variety of power-law elliptical lens mass distributions. We then apply our approach to test data sets whose lens parameters are drawn from distributions that are drastically different from the training set. We show that our hierarchical inference framework mitigates the bias introduced by an unrepresentative training set's interim prior. Simultaneously, we can precisely reconstruct the population hyperparameters governing our test distributions. Our full pipeline, from training to hierarchical inference on thousands of lenses, can be run in a day. The framework presented here will allow us to efficiently exploit the full constraining power of future ground- and space-based surveys (https://github.com/swagnercarena/ovejero).

79 ASTRONOMY AND ASTROPHYSICS↗

Large-scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant

We investigate the use of approximate Bayesian neural networks (BNNs) in modeling hundreds of time delay gravitational lenses for Hubble constant (H 0 ) determination. Here, our BNN was trained on synthetic Hubble Space Telescope quality images of strongly lensed active galactic nuclei with lens galaxy light included. The BNN can accurately characterize the posterior probability density functions (PDFs) of model parameters governing the elliptical power-law mass profile in an external shear field. We then propagate the BNN-inferred posterior PDFs into an ensemble H 0 inference, using simulated time delay measurements from a plausible dedicated monitoring campaign. Assuming well-measured time delays and a reasonable set of priors on the environment of the lens, we achieve a median precision of 9.3% per lens in the inferred H 0 . A simple combination of a set of 200 test lenses results in a precision of 0.5 km s –1 Mpc –1 (0.7%), with no detectable bias in this H 0 recovery test. The computation time for the entire pipeline—including the generation of the training set, BNN training and H0 inference—translates to 9 minutes per lens on average for 200 lenses and converges to 6 minutes per lens as the sample size is increased. Being fully automated and efficient, our pipeline is a promising tool for exploring ensemble-level systematics in lens modeling for H 0 inference.

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Dark Matter Constraints from a Unified Analysis of Strong Gravitational Lenses and Milky Way Satellite Galaxies

Joint analyses of small-scale cosmological structure probes have been relatively unexplored yet promise to advance measurements of microphysical dark matter properties using heterogeneous data. Here, we present a multidimensional analysis of dark matter substructure using strong gravitational lenses and the Milky Way (MW) satellite galaxy population, accounting for degeneracies in model predictions and using covariances in the constraining power of these individual probes for the first time. We simultaneously infer the projected subhalo number density and the half-mode mass describing the suppression of the subhalo mass function in thermal relic warm dark matter (WDM), $M_{\mathrm{hm}}$, using the semianalytic model \texttt{Galacticus} to connect the subhalo population inferred from MW satellite observations to the strong lensing host halo mass and redshift regime. Combining MW satellite and strong lensing posteriors in this parameter space yields $M_{\mathrm{hm}}<10^{7.0}\ M_{\mathrm{\odot}}$ (WDM particle mass $m_{\mathrm{WDM}}>9.7\ \mathrm{keV}$) at $95\%$ confidence and disfavors $M_{\mathrm{hm}}=10^{7.4}\ M_{\mathrm{\odot}}$ ($m_{\mathrm{WDM}}=7.4\ \mathrm{keV}$) with a 20:1 marginal likelihood ratio, improving limits on $m_{\mathrm{WDM}}$ set by the two methods independently by $\sim 30\%$. These results are marginalized over the line-of-sight contribution to the strong lensing signal, the mass of the MW host halo, and the efficiency of subhalo disruption due to baryons and are robust to differences in the disruption efficiency between the MW and strong lensing regimes at the $\sim 10\%$ level. This work paves the way for unified analyses of next-generation small-scale structure measurements covering a wide range of scales and redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling the Galactic Neutron Star Population for Use in Continuous Gravitational-wave Searches

Searches for continuous gravitational waves (GW) from unknown Galactic neutron stars provide limits on the shapes of neutron stars. A rotating neutron star will produce GW if asymmetric deformations exist in its structure that are characterized by the star's ellipticity. Here, in this study, we use a simple model of the spatial and spin distribution of Galactic neutron stars to estimate the total number of neutron stars probed, using GW, to a given upper limit on the ellipticity. This may help optimize future searches with improved sensitivity. The improved sensitivity of third-generation GW detectors may increase the number of neutron stars probed, to a given ellipticity, by factors of 100 to 1000.

79 ASTRONOMY AND ASTROPHYSICS↗

A Systematic Exploration of Kilonova Candidates from Neutron Star Mergers during the Third Gravitational-wave Observing Run

We present a comprehensive analysis of 653 optical candidate counterparts reported during the third gravitational-wave (GW) observing run. Our sample concentrates on candidates from the 15 events (published in GWTC-2, GWTC-3, or not retracted on GraceDB) that had a >1% chance of including a neutron star in order to assess their viability as true kilonovae. In particular, we leverage tools available in real time, including pre-merger detections and cross-matching with catalogs (i.e., point-source, variable-star, quasar and host-galaxy redshift data sets), to eliminate 65% of candidates in our sample. We further employ spectroscopic classifications, late-time detections, and light-curve behavior analyses and conclude that 66 candidates remain viable kilonovae. These candidates lack sufficient information to determine their classifications, and the majority would require luminosities greater than that of AT 2017gfo. Pre-merger detections in public photometric survey data and comparison of cataloged host-galaxy redshifts with the GW event distances are critical to incorporate into vetting procedures, as these tools eliminated >20% and >30% of candidates, respectively. We expect that such tools that leverage archival information will significantly reduce the strain on spectroscopic and photometric follow-up resources in future observing runs. Finally, we discuss the critical role prompt updates from GW astronomers to the EM community play in reducing the number of candidates requiring vetting.

79 ASTRONOMY AND ASTROPHYSICS↗

GIGA-Lens: Fast Bayesian Inference for Strong Gravitational Lens Modeling

We present GIGA-Lens: a gradient-informed, GPU-accelerated Bayesian framework for modeling strong gravitational lensing systems, implemented in TensorFlow and JAX. The three components, optimization using multistart gradient descent, posterior covariance estimation with variational inference, and sampling via Hamiltonian Monte Carlo, all take advantage of gradient information through automatic differentiation and massive parallelization on graphics processing units (GPUs). We test our pipeline on a large set of simulated systems and demonstrate in detail its high level of performance. The average time to model a single system on four Nvidia A100 GPUs is 105 s. The robustness, speed, and scalability offered by this framework make it possible to model the large number of strong lenses found in current surveys and present a very promising prospect for the modeling of ${ \mathcal O }({10}^{5})$ lensing systems expected to be discovered in the era of the Vera C. Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope.

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CALET Search for Electromagnetic Counterparts of Gravitational Waves during the LIGO/Virgo O3 Run

The CALorimetric Electron Telescope (CALET) on the International Space Station consists of a high-energy cosmic-ray CALorimeter (CAL) and a lower-energy CALET Gamma-ray Burst Monitor (CGBM). CAL is sensitive to electrons up to 20 TeV, cosmic-ray nuclei from Z = 1 through Z ~ 40, and gamma rays over the range 1 GeV–10 TeV. CGBM observes gamma rays from 7 keV to 20 MeV. The combined CAL-CGBM instrument has conducted a search for gamma-ray bursts (GRBs) since 2015 October. We report here on the results of a search for X-ray/gamma-ray counterparts to gravitational-wave events reported during the LIGO/Virgo observing run O3. No events have been detected that pass all acceptance criteria. We describe the components, performance, and triggering algorithms of the CGBM—the two Hard X-ray Monitors consisting of LaBr 3 (Ce) scintillators sensitive to 7 keV–1 MeV gamma rays and a Soft Gamma-ray Monitor BGO scintillator sensitive to 40 keV–20 MeV—and the high-energy CAL consisting of a charge detection module, imaging calorimeter, and the fully active total absorption calorimeter. The analysis procedure is described and upper limits to the time-averaged fluxes are presented.

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A Standard Siren Measurement of the Hubble Constant Using Gravitational-wave Events from the First Three LIGO/Virgo Observing Runs and the DESI Legacy Survey

We present a new constraint on the Hubble constant H 0 using a sample of well-localized gravitational-wave (GW) events detected during the first three LIGO/Virgo observing runs as dark standard sirens. In the case of dark standard sirens, a unique host galaxy is not identified, and the redshift information comes from the distribution of potential host galaxies. From the third LIGO/Virgo observing run detections, we add the asymmetric-mass binary black hole GW190412 and the high-confidence GW candidates S191204r, S200129m, and S200311bg to the sample of dark standard sirens analyzed in Palmese et al. Our sample contains the top 20% (based on localization) GW events and candidates to date with significant coverage by the Dark Energy Spectroscopic Instrument Legacy Survey. We combine the H 0 posterior for eight dark siren events, finding H 0 = $79.8^{+19.1}_{-12.8}$ km s -1 Mpc -1 (68% highest density interval) for a prior in H 0 uniform between [20, 140] km s -1 Mpc -1 . This result shows that a combination of eight well-localized dark sirens combined with an appropriate galaxy catalog is able to provide an H 0 constraint that is competitive (~20% versus 18% precision) with a single bright standard siren analysis (i.e., assuming the electromagnetic counterpart) using GW170817. When combining the posterior with that from GW170817, we obtain H 0 = $72.77^{+11.0}_{-7.55}$ km s -1 Mpc -1 . This result is broadly consistent with recent H 0 estimates from both the cosmic microwave background and supernovae.

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BICEP/Keck. XVII. Line-of-sight Distortion Analysis: Estimates of Gravitational Lensing, Anisotropic Cosmic Birefringence, Patchy Reionization, and Systematic Errors

We present estimates of line-of-sight distortion fields derived from the 95 and 150 GHz data taken by BICEP2, BICEP3, and the Keck Array up to the 2018 observing season, leading to cosmological constraints and a study of instrumental and astrophysical systematics. Cosmological constraints are derived from three of the distortion fields concerning gravitational lensing from large-scale structure, polarization rotation from magnetic fields or an axion-like field, and the screening effect of patchy reionization. We measure an amplitude of the lensing power spectrum ${A}_{L}^{\phi \phi }=0.95\pm 0.20$. We constrain polarization rotation, expressed as the coupling constant of a Chern–Simons electromagnetic term g aγ ≤ 2.6 × 10 -2 /H I , where H I is the inflationary Hubble parameter, and an amplitude of primordial magnetic fields smoothed over 1 Mpc B 1Mpc ≤ 6.6 nG at 95 GHz. We constrain the rms of optical depth fluctuations in a simple "crinkly surface" model of patchy reionization, finding A τ < 0.19 (2σ) for the coherence scale of L c = 100. We show that all of the distortion fields of the 95 and 150 GHz polarization maps are consistent with simulations including lensed ΛCDM, dust, and noise, with no evidence for instrumental systematics. In some cases, the EB and TB quadratic estimators presented here are more sensitive than our previous map-based null tests at identifying and rejecting spurious B-modes that might arise from instrumental effects. Finally, we verify that the standard deprojection filtering in the BICEP/Keck data processing is effective at removing temperature to polarization leakage.

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Gravitational Waves from Primordial Black Hole Dark Matter Spikes

The origin of the binary black hole mergers observed by LIGO–Virgo–KAGRA remains an open question. We calculate the merger rate from primordial black holes (PBHs) within the density spike around supermassive black holes (SMBHs) at the centers of galaxies. We show that the merger rate within the spike is comparable to that within the wider dark matter halo. We also calculate the extreme mass ratio inspiral (EMRI) signal from PBHs hosted within the density spike spiralling into their host SMBHs due to gravitational-wave emission. We predict that LISA may detect ∼10 4 of these EMRIs with a signal-to-noise ratio threshold of 20 within a 4 yr observation run, if all dark matter is made up of ∼30 M ⊙ PBHs. Uncertainties in our rates come from the uncertain mass fraction of PBHs within the dark matter spike, relative to the host central SMBHs, which defines the parameter space LISA can constrain.

dark matter↗

A Reanalysis of Public Galactic Bulge Gravitational Microlensing Events from OGLE-III and -IV

Abstract Modern surveys of gravitational microlensing events have progressed to detecting thousands per year, and surveys are capable of probing Galactic structure, stellar evolution, lens populations, black hole physics, and the nature of dark matter. One of the key avenues for doing this is the microlensing Einstein radius crossing time (t E) distribution. However, systematics in individual light curves as well as oversimplistic modeling can lead to biased results. To address this, we developed a model to simultaneously handle the microlensing parallax due to Earth's motion, systematic instrumental effects, and unlensed stellar variability with a Gaussian process model. We used light curves for nearly 10,000 OGLE-III and -IV Milky Way bulge microlensing events and fit each with our model. We also developed a forward model approach to infer the t E distribution by forward modeling from the data rather than using point estimates from individual events. We find that modeling the variability in the baseline removes a source of significant bias in individual events, and the previous analyses overestimated the number of t E > 100 day events due to their oversimplistic model ignoring parallax effects. We use our fits to identify the hundreds filling a regime in the microlensing parameter space that are 50% pure of black holes. Finally, we have released the largest-ever catalog of Markov Chain Monte Carlo parameter estimates for microlensing events.

79 ASTRONOMY AND ASTROPHYSICS↗

New Strong Gravitational Lenses from the DESI Legacy Imaging Surveys Data Release 9

We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9. This is the third paper in a series. These surveys together cover ~19,000 deg 2 visible from the Northern Hemisphere, reaching a z-band AB magnitude of ~22.5. We use a deep residual neural network, trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. After applying our trained neural network to the survey data, we visually inspect and rank images with probabilities above a threshold which has been chosen to balance precision and recall. We have found 1895 lens candidates, of which 1512 are identified for the first time. Combining the discoveries from this work with those from Papers I (335) and II (1210), we have discovered a total of 3057 new candidates in the Legacy Surveys.

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Radio Afterglow Detection and AI-driven Response (RADAR): A Federated Framework for Gravitational-wave Event Follow-up

The landmark detection of both gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 has spurred efforts to streamline the follow-up of GW alerts in current and future observing runs of ground-based GW detectors. Within this context, the radio band of the EM spectrum presents unique challenges. Sensitive radio facilities capable of detecting the faint radio afterglow seen in GW170817, and with sufficient angular resolution, have small fields of view compared to typical GW localization areas. Additionally, theoretical models predict that the radio emission from binary neutron star mergers can evolve over weeks to years, necessitating long-term monitoring to probe the physics of the various postmerger ejecta components. These constraints, combined with limited radio observing resources, make the development of more coordinated follow-up strategies essential—especially as the next generation of GW detectors promises a dramatic increase in detection rates. Here, we present RADAR, a framework designed to address these challenges by promoting community-driven information sharing, federated data analysis, and system resilience, while integrating AI methods for both GW signal identification and radio data aggregation. We show that it is possible to preserve data rights while sharing models that can help design and/or update follow-up strategies. We demonstrate our approach through a case study of GW170817, and discuss future directions for refinement and broader application.

Gravitational waves↗