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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Interfacial Chemistry Involved in Selective Separation of NMC/LMO and LCO/LMO Binary Cathode Materials by Froth Flotation Using Oleic Acid

The variability in cathode compositions within recycled lithium-ion battery (LIB) feedstocks poses a significant challenge to efficient downstream refining processes. This study demonstrates the feasibility of using froth flotation with oleic acid as a collector to selectively separate lithium nickel-manganese-cobalt oxide (NMC) and lithium cobalt oxide (LCO) from lithium manganese oxide (LMO) materials. Laboratory-scale flotation tests achieved an 80% separation efficiency in a single stage, producing a froth product with >90% purity of NMC/LCO at approximately 90% yield. Concurrently, the LMO materials were enriched in the sink product with ∼90% purity and ∼90% yield. This approach was further validated using recycled cathode materials, confirming its applicability to realistic feedstocks. The underlying mechanism governing the selective separation of NMC/LCO from LMO was investigated using ζ-potential measurements, contact angle measurements, bubble-particle attachment experiments, and X-ray photoelectron spectroscopy (XPS) analysis. Both contact angle and bubble-particle attachment results confirmed that oleic acid adsorption rendered NMC and LCO surfaces hydrophobic, thereby enhancing flotation recovery. At pH 5, oleic acid adsorbed preferentially onto NMC and LCO surfaces via electrostatic interactions, while exhibiting minimal adsorption on LMO surfaces. However, separation efficiency deteriorated at higher pH, which was attributed to the co-flotation of LMO materials caused by oleate chemisorption on MnOH + species. This work establishes froth flotation as a viable cathode/cathode separation strategy, providing a low-cost, scalable pathway to preconcentrate and enrich nickel-rich and cobalt-rich cathode active materials from incompatible cathode chemistries for direct recycling or hydrometallurgical processing. Furthermore, this study reveals, for the first time, the mechanism of oleate adsorption on the surface of different cathode materials.

PH↗
DOE OSTI2025

Deep learning model for fast, science-based forecasting of fluid migration along faults in geologic carbon storage scenarios

Effective long-term geologic storage depends on robust site selection and credible, science-based forecasting of subsurface behavior to ensure storage integrity. For this work, we develop a deep learning–based reduced-order model (ROM) to quantify potential carbon dioxide (CO₂) and brine migration through geological faults. The ROM combines a Transformer model for binary classification and a Stacked Ensemble for regression, trained on a comprehensive dataset generated from 1400 physics-based reservoir simulations. Key geologic and operational parameters—including fault geometry, reservoir structure, and injection conditions—were systematically varied to capture a wide range of fluid migration scenarios. The ROM accurately predicts the onset of migration, cumulative migration volumes of both CO₂ and brine, and associated migration rates, as compared to an independent set of validation simulations, while significantly reducing computational cost compared to traditional simulation methods. Model performance was evaluated across diverse fault configurations, revealing that shallow reservoir geometry and fault angle are among the most influential factors governing migration behavior. Sensitivity analysis using SHapley Additive exPlanations (SHAP) provided interpretability, revealing distinct patterns in how geological and operational features drive transient versus cumulative migration outcomes. The ROM’s ability to rapidly simulate fault migration scenarios enables efficient sensitivity analyses, scenario evaluations, and decision support for site selection and monitoring design. This approach enhances the safety, scalability, and long-term operational performance of geologic carbon storage (GCS) systems by providing a robust, interpretable tool for predicting subsurface fluid migration and assessing fault-related migration potential.

42 ENGINEERING↗
DOE OSTI2022

Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series: Preprint

PV power and irradiance sensor-based measurements are prone to error, resulting in issues such as abrupt time series data shifts. These shifts, which are usually unintentional, may be caused by software or hardware configuration changes on a PV system, and do not reflect an actual change in overall system performance. Locating these shifts and segmenting the associated time series aids in more accurate future PV analysis. In this research, an offline changepoint detection (CPD) algorithm that automatically detects these abrupt data shifts in sensor-based time series is introduced. Data shift periods in 101 daily PV power and irradiance time series were labeled manually by two solar experts. These data streams represent sensor-based measurements, and display a variety of data shift behaviors. A changepoint detection algorithm was tuned using the 101 labeled data streams, with each model configuration's ability to detect labeled changepoints benchmarked using metrics such as F1-score, recall, and Rand Index. Best performing models on seasonality-corrected data streams include the Pruned Exact Linear (PELT) method, the Binary Segmentation method, and the Bottom-Up method, all scoring an average F1-score of 0.76 or greater at detecting labeled changepoints within a 30-day window for the labeled data sets. To promote further research in this space, we are releasing the labeled data shift sets on U.S. Department of Energy's (DOE) DuraMAT Data Hub, and the associated algorithm in the Python PVAnalytics package.

changepoint detection↗
DOE OSTI2021

Stakeholder Support for Wildlife Conservation Funding Policies

State wildlife management agencies in the United States have depended on a “user-pay” funding model for conservation efforts that relies on revenue from hunting license sales and a federal excise tax on firearms, ammunition, and archery equipment. Declines in hunting participation, however, jeopardize sustainability of the current funding model. Ensuring support among stakeholders for wildlife management and conservation may require expanding sources of funding and incorporating the perspectives and values of a diversifying constituency into decision making processes. We used a web-based survey of wildlife-associated recreationists in Michigan, USA to evaluate support for a range of conservation funding policies. Respondents self-identified primarily as hunters (n = 2,558) or wildlife watchers (n = 942). We used binary logistic regression to evaluate support for four conservation funding policy options: state sales tax, lottery proceeds, extractive industry revenue, and a user-based tax on outdoor gear (i.e., “backpack tax”). Determinants of support varied by type of policy and stakeholder characteristics. We found no statistically significant differences between hunters and wildlife watchers in their support for conservation funding policies when accounting for other variables such as wildlife value orientations, engagement in stewardship behaviors, age, and gender. The industry-based policy achieved the greatest level of approval, while the backpack tax had the lowest. Respondents were mixed in their support of the sales tax and lottery proceeds options. Cluster analysis revealed three homogenous groups related to conservation funding policies: “strong support,” “mixed/opposed,” and “anti-backpack tax.” Clusters differed in their support for conservation funding policies and on psychological and demographic variables. The “strong support” and “anti-backpack tax” groups differed in their levels of stewardship engagement, knowledge of conservation funding mechanisms, and support for the backpack tax option. The “mixed-opposed” group tended to be older, less educated, and less likely to be a member of a conservation organization. Results suggest support for conservation funding differs by policy type and social and psychological characteristics of stakeholders. Based on differences in policy support revealed in this study, we suggest a multi-tiered approach to funding conservation and building on support among wildlife stakeholders to mitigate the looming funding crisis for state wildlife agencies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series

PV power and irradiance sensor-based measurements are prone to error, resulting in issues such as abrupt time series data shifts. These shifts, which are usually unintentional, may be caused by software or hardware configuration changes on a PV system, and do not reflect an actual change in overall system performance. Locating these shifts and segmenting the associated time series aids in more accurate future PV analysis. In this research, an offline changepoint detection (CPD) algorithm that automatically detects these abrupt data shifts in sensor-based time series is introduced. Data shift periods in 101 daily PV power and irradiance time series were labeled manually by two solar experts. These data streams represent sensor-based measurements, and display a variety of data shift behaviors. A changepoint detection algorithm was tuned using the 101 labeled data streams, with each model configuration's ability to detect labeled changepoints benchmarked using metrics such as F1-score, recall, and Rand Index. Best performing models on seasonality-corrected data streams include the Pruned Exact Linear (PELT) method, the Binary Segmentation method, and the Bottom-Up method, all scoring an average F1-score of 0.76 or greater at detecting labeled changepoints within a 30-day window for the labeled data sets. To promote further research in this space, we are releasing the labeled data shift sets on U.S. Department of Energy's (DOE) DuraMAT Data Hub, and the associated algorithm in the Python PVAnalytics package.

changepoint detection↗
DOE OSTI2023

Barium stars as tracers of s -process nucleosynthesis in AGB stars: II. Using machine learning techniques on 169 stars

Barium (Ba) stars are characterised by an abundance of heavy elements made by the slow neutron capture process (s-process). This peculiar observed signature is due to the mass transfer from a stellar companion, bound in a binary stellar system, to the Ba star observed today. The signature is created when the stellar companion is an asymptotic giant branch (AGB) star. We aim to analyse the abundance pattern of 169 Ba stars using machine learning techniques and the AGB final surface abundances predicted by the FRUITY and Monash stellar models. We developed machine learning algorithms that use the abundance pattern of Ba stars as input to classify the initial mass and metallicity of each Ba star’s companion star using stellar model predictions. We used two algorithms. The first exploits neural networks to recognise patterns, and the second is a nearest-neighbour algorithm that focuses on finding the AGB model that predicts the final surface abundances closest to the observed Ba star values. In the second algorithm, we included the error bars and observational uncertainties in order to find the best-fit model. The classification process was based on the abundances of Fe, Rb, Sr, Zr, Ru, Nd, Ce, Sm, and Eu. We selected these elements by systematically removing s-process elements from our AGB model abundance distributions and identifying the elements whose removal had the biggest positive effect on the classification. We excluded Nb, Y, Mo, and La. Our final classification combined the output of both algorithms to identify an initial mass and metallicity range for each Ba star companion. With our analysis tools, we identified the main properties for 166 of the 169 Ba stars in the stellar sample. The classifications based on both stellar sets of AGB final abundances show similar distributions, with an average initial mass of M = 2.23 M ⊙ and 2.34 M ⊙ and an average [Fe/H] = –0.21 and –0.11, respectively. We investigated why the removal of Nb, Y, Mo, and La improves our classification and identified 43 stars for which the exclusion had the biggest effect. We found that these stars have statistically significant and different abundances for these elements compared to the other Ba stars in our sample. We discuss the possible reasons for these differences in the abundance patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Search for 22 Na in novae supported by a novel method for measuring femtosecond nuclear lifetimes

Classical novae are thermonuclear explosions in stellar binary systems, and important sources of 26 Al and 22 Na. While γ rays from the decay of the former radioisotope have been observed throughout the Galaxy, 22 Na remains untraceable. Its half-life (2.6 yr) would allow the observation of its 1.275 MeV γ-ray line from a cosmic source. However, the prediction of such an observation requires good knowledge of its nucleosynthesis. The 22 Na(p, γ) 23 Mg reaction remains the only source of large uncertainty about the amount of 22 Na ejected. Its rate is dominated by a single resonance on the short-lived state at 7785.0(7) keV in 23 Mg. Here, we propose a combined analysis of particle-particle correlations and velocity-difference profiles to measure femtosecond nuclear lifetimes. The application of this method to the study of the 23 Mg states, places strong limits on the amount of 22 Na produced in novae and constrains its detectability with future space-borne observatories.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Multiwavelength analysis of Fermi -LAT blazars with high-significance periodicity: detection of a long-term rising emission in PG 1553+113

ABSTRACT Blazars display variable emission across the entire electromagnetic spectrum, with time-scales that can range from a few minutes to several years. Our recent work has shown that a sample of five blazars exhibit hints of periodicity with a global significance ${\gtrsim}2\, \sigma$ at γ-ray energies, in the range of 0.1 GeV < E < 800 GeV. In this work, we study their multiwavelength emission, covering the X-ray, ultraviolet, optical, and radio bands. We show that three of these blazars present similar periodic patterns in the optical and radio bands. Additionally, fluxes in the different bands of the five blazars are correlated, suggesting a co-spatial origin. Moreover, we detect a long-term (≈10 yr) rising trend in the light curves of PG 1553+113, and we use it to infer possible constraints on the binary black hole hypothesis.

Astronomy & Astrophysics↗
DOE OSTI2024

Evaluating Methods of Software Bill of Materials Generation to Enhance Nuclear Power Plant Cybersecurity

Instrumentation and control (I&C) systems in nuclear power plants (NPPs) are potential targets of cyberattacks and can prove deleterious for the safety of the NPPs. A Software Bill of Materials (SBOM) provides a detailed list of the various components and their dependencies in software, which helps in vulnerability and risk assessment for cyber hygiene and situational awareness. For an NPP, the process of generating an accurate SBOM report can be complex due to the legacy systems and firmware binaries involved. While most current SBOM tools are focused more on modern internet technology software, this research provides insights and guidelines for an NPP to generate an accurate and efficient SBOM. Here, the paper proposes a new methodology to help NPPs categorize software and use appropriate tools to generate SBOMs for their digital I&C systems.

SBOM↗
DOE OSTI2026

Dataset for Top Model Decision Tree: Selecting Segmentation Models for Reliable Quantitative Analysis in Low- and Ultralow-Dose CryoEM

Motivation Multiple deep learning model architectures can be used to segment bacterial membranes in cryoEM images. However, an AI-based tool advancement is often presented with only a single segmentation model for broad use, and this single model may show inconsistent results across datasets from different users. Here, we present the Top Model Decision Tree, a model screening framework to screen for the best model to generate bacterial inner and outer membrane masks based on user priorities. We use pre-trained segmentation models from YOLOv11, YOLO26, U-Net, Detectron2 and SAM3 fine-tuned on bacterial inner and outer membranes imaged with cryoEM. Run the Framework This notebook must be opened in Google Colab. Mount Google Drive and run with a GPU-based runtime. Open the notebook and follow steps to git clone in folders and files within this repository. There will be a repeating top_model_decision_tree.ipynb (notebook clone) that will not be used. Save your .png binary mask files and .csv table outputs within your Google Drive or download before closing the notebook. The models and all analysis/training scripts are available at [GitHub: https://github.com/Lynnicia/CryoEM_membranes_top_model_decision_tree and https://github.com/Sireesiru/Semantic-Segmentation-of-bacterial-cell-envelope-using-U-Nets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The role of Cr concentration and temperature on cavity swelling with co-injected helium in dual-ion irradiated Fe and Fe-Cr alloys

The level of chromium plays an essential role in irradiation tolerance of Fe-Cr ferritic alloys. However, conflicting results have been reported regarding the dependence of cavity swelling under irradiation on Cr level and temperature. Here, we have performed a comprehensive set of simultaneous dual-ion (Ni + He) irradiations to high dose (~30 displacements per atom, dpa) at 400–550 °C on a series of ultra-high purity Fe and Fe-Cr binary alloys (3–14 wt.%Cr). Helium co-implantation rates of 0.1 and 10 appm He/dpa were selected to examine He synergistic effects relevant for fission and fusion reactor conditions, respectively. Cavities were observed in all irradiated samples by transmission electron microscopy. The results show that higher He implantation rate causes a shift in the swelling peak to higher temperatures in both Fe and Fe-Cr alloys. When assuming smaller cavities as biased sinks, the non-monotonic nature of the cavity swelling behavior is related to the ratio of biased to unbiased point defect sink strengths. Cr-enriched precipitates were observed in Fe-14Cr irradiated at 400 °C by atom probe tomography. Our analysis suggests the formation of Cr-enriched precipitates could suppress cavity swelling for Fe-Cr alloys with Cr content above 10 wt%.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Isomers and band assignments in the cryogenic vibrational spectrum of the binary complex between water and protonated formic acid using two color, IR–IR photobleaching and H/D isotopic substitution

Protonated formic acid (PFA) is purported to be the active species in the catalytic activation of condensation reactions at the acidic interface of microdroplets. Here, we investigate the fundamental interaction between PFA and water with cryogenic ion vibrational spectroscopy of the binary PFA–H 2 O complexes generated via electrospray ionization followed by buffer gas cooling to about 20 K. The patterns displayed by the isomer-specific IR spectra of D 2 -tagged PFA–H 2 O indicate that two distinct, non-interconverting rotamers are present at low temperatures based on the cis and trans structures of the HCO 2 $H$$^{+}_{2}$ core ion. Both of these occur with the water molecule attached to the OH that is in a cis-configuration relative to the CH group (denoted E), but differ in the E vs Z (cis vs trans relative to the CH group) orientation of the spectator OH. This assignment scheme corrects a previous theoretical analysis that invoked a scenario in which structures with E- and Z-bound water molecules interconvert at low (20 K) temperatures. Isomer-specific bands arising from the OH stretches and water bending modes are deconvoluted using isotopomer-specific spectroscopy of the complexes with partial H/D exchange. The dependence of the nominal shared proton OH stretch frequency on the deuteration of the tethered water confirms strong coupling between this mode and the water bending fundamental.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Incremental Fermi Large Area Telescope Fourth Source Catalog

We present an incremental version (4FGL-DR3, for Data Release 3) of the fourth Fermi Large Area Telescope (LAT) catalog of γ-ray sources. Based on the first 12 years of science data in the energy range from 50 MeV to 1 TeV, it contains 6658 sources. The analysis improves on that used for the 4FGL catalog over eight years of data: more sources are fit with curved spectra, we introduce a more robust spectral parameterization for pulsars, and we extend the spectral points to 1 TeV. The spectral parameters, spectral energy distributions, and associations are updated for all sources. Light curves are rebuilt for all sources with 1 yr intervals (not 2 month intervals). Among the 5064 original 4FGL sources, 16 were deleted, 112 are formally below the detection threshold over 12 yr (but are kept in the list), while 74 are newly associated, 10 have an improved association, and seven associations were withdrawn. Pulsars are split explicitly between young and millisecond pulsars. Pulsars and binaries newly detected in LAT sources, as well as more than 100 newly classified blazars, are reported. We add three extended sources and 1607 new point sources, mostly just above the detection threshold, among which eight are considered identified, and 699 have a plausible counterpart at other wavelengths. We discuss the degree-scale residuals to the global sky model and clusters of soft unassociated point sources close to the Galactic plane, which are possibly related to limitations of the interstellar emission model and missing extended sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

AT2017gfo: Bayesian inference and model selection of multicomponent kilonovae and constraints on the neutron star equation of state

The joint detection of the gravitational wave GW170817, of the short γ-ray burst GRB170817A and of the kilonova AT2017gfo, generated by the the binary neutron star (NS) merger observed on 2017 August 17, is a milestone in multimessenger astronomy and provides new constraints on the NS equation of state. We perform Bayesian inference and model selection on AT2017gfo using semi-analytical, multicomponents models that also account for non-spherical ejecta. Observational data favour anisotropic geometries to spherically symmetric profiles, with a log-Bayes’ factor of ~104, and favour multicomponent models against single-component ones. The best-fitting model is an anisotropic three-component composed of dynamical ejecta plus neutrino and viscous winds. Using the dynamical ejecta parameters inferred from the best-fitting model and numerical–relativity relations connecting the ejecta properties to the binary properties, we constrain the binary mass ratio to q < 1.54 and the reduced tidal parameter to $120\lt \tilde{\Lambda }\lt 1110$. Finally, we combine the predictions from AT2017gfo with those from GW170817, constraining the radius of a NS of 1.4 M ⊙ to 12.2 ± 0.5 km (1σ level). This prediction could be further strengthened by improving kilonova models with numerical-relativity information.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Evolution of short-range magnetic correlations in ferromagnetic Ni-V alloys

Here we experimentally study how the magnetic correlations develop in a binary alloy close to the ferromagnetic quantum critical point with small-angle neutron scattering (SANS). Upon alloying the itinerant ferromagnet nickel with vanadium, the ferromagnetic order is continuously suppressed. The critical temperature T c vanishes when vanadium concentrations reach the critical value of x c =0.116 indicating a quantum critical point separating the ferromagnetic and paramagnetic phases. Earlier magnetization and μ⁢SR data have indicated the presence of magnetic inhomogeneities in Ni 1-x ⁢V x and, in particular, recognize the magnetic clusters close to x c , on the paramagnetic and on the ferromagnetic sides with nontrivial dynamical properties [R. Wang et al., Phys. Rev. Lett. 118, 267202 (2017)]. We present the results of SANS study with full polarization analysis of polycrystalline Ni 1-x⁢ V x samples with x=0.10 and x=0.11 with low critical temperatures T c <50 K. For both Ni-V samples close to x c we find isotropic magnetic short-range correlations on the nanometer scale persisting at low temperatures. They are suppressed gradually in higher magnetic fields. In addition, signatures of long-range ordered magnetic domains are present below T c . The fraction of these magnetic clusters embedded in the ferromagnetic ordered phase grows toward x c and agrees well with the cluster fraction estimate from the magnetization and μ⁢SR data. Our SANS studies provide new insights into the nature of the inhomogeneities in a ferromagnetic alloy close to a quantum critical point.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cocoon shock breakout emission from binary neutron star mergers

Shock breakout emission is among the first observable signals in a wide variety of astrophysical phenomena, including neutron star (NS) mergers, and it can be the dominant component in low-luminosity short γ-ray bursts, as exemplified by GRB 170817A. In this work, we investigate the cocoon shock breakout emission in NS mergers and how its signal depends on the outermost layers of the ejecta profile, which we derive from general relativistic radiation hydrodynamic simulations. We study the formation of the cocoon as a consequence of a relativistic jet propagating through the ejecta. To explore the influence of the outermost layers of the ejecta on the breakout emission, we explore cases where the ejecta has a sharp cutoff or an extended smooth tail. We find that the shock breakout emission is strongly influenced by the shape of the ejecta outer layers, with extended tails yielding results consistent with the observed properties of GRB 170817A, whereas sharp cutoffs overestimate the radiated energy. Using a Bayesian analysis, we estimate the best fit parameters of the central engine, considering both accreting black hole and magnetized neutron star scenarios. Our findings indicate a slight preference for the scenarios where the engine is a black hole. Furthermore, our work probes the nature of neutron star mergers and highlights the importance of the shape of the ejecta profile in modeling early electromagnetic counterparts to these mergers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

HATS-47b, HATS-48Ab, HATS-49b, and HATS-72b: Four Warm Giant Planets Transiting K Dwarfs

We report the discovery of four transiting giant planets around K dwarfs. The planets HATS-47b, HATS-48Ab, HATS-49b, and HATS-72b have masses of 0.369{sub −0.021}{sup +0.031} M{sub J}, 0.243{sub −0.030}{sup +0.022} M{sub J}, 0.353{sub −0.027}{sup +0.038} M{sub J}, and 0.1254±0.0039 M{sub J}, respectively, and radii of 1.117±0.014 R{sub J}, 0.800±0.015 R{sub J}, 0.765±0.013 R{sub J}, and 0.7224±0.0032 R{sub J}, respectively. The planets orbit close to their host stars with orbital periods of 3.9228 days, 3.1317 days, 4.1480 days, and 7.3279 days, respectively. The hosts are main-sequence K dwarfs with masses of 0.674{sub −0.012}{sup +0.016} M{sub ⊙}, 0.7279 ±0.0066 M{sub ⊙}, 0.7133±0.0075 M{sub ⊙}, and 0.7311±0.0028, and with V-band magnitudes of V=14.829±0.010, 14.35±0.11, 14.998±0.040 and 12.469±0.010. The super-Neptune HATS-72b (a.k.a. WASP-191b and TOI 294.01) was independently identified as a transiting planet candidate by the HATSouth, WASP, and TESS surveys, and we present a combined analysis of all of the data gathered by each of these projects (and their follow-up programs). An exceptionally precise mass is measured for HATS-72b thanks to high-precision radial velocity (RV) measurements obtained with VLT/ESPRESSO, FEROS, HARPS, and Magellan/PFS. We also incorporate TESS observations of the warm Saturn–hosting systems HATS-47 (a.k.a. TOI 1073.01), HATS-48A, and HATS-49. HATS-47 was independently identified as a candidate by the TESS team, while the other two systems were not previously identified from the TESS data. The RV orbital variations are measured for these systems using Magellan/PFS. HATS-48A has a resolved [[Formula]] neighbor in Gaia DR2, which is a common-proper-motion binary star companion to HATS-48A with a mass of 0.22 M{sub ⊙} and a current projected physical separation of ∼1400 au.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Search for Lensing Signatures in the Gravitational-Wave Observations from the First Half of LIGO–Virgo’s Third Observing Run

Here, we search for signatures of gravitational lensing in the gravitational-wave signals from compact binary coalescences detected by Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) and Advanced Virgo during O3a, the first half of their third observing run. We study: (1) the expected rate of lensing at current detector sensitivity and the implications of a non-observation of strong lensing or a stochastic gravitational-wave background on the merger-rate density at high redshift; (2) how the interpretation of individual high-mass events would change if they were found to be lensed; (3) the possibility of multiple images due to strong lensing by galaxies or galaxy clusters; and (4) possible wave-optics effects due to point-mass microlenses. Several pairs of signals in the multiple-image analysis show similar parameters and, in this sense, are nominally consistent with the strong lensing hypothesis. However, taking into account population priors, selection effects, and the prior odds against lensing, these events do not provide sufficient evidence for lensing. Overall, we find no compelling evidence for lensing in the observed gravitational-wave signals from any of these analyses.

79 ASTRONOMY AND ASTROPHYSICS↗