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The process of seeking, sampling, and characterizing deep hydrothermal systems is benefited by the use of autonomous underwater vehicles (AUVs) equipped with in situ sensors. Traditional AUV operations require multiple deployments with manual data analysis by ship-board scientists. Development of advanced autonomous methods that analyze in situ data in real-time and allow the vehicle itself to make decisions would improve the efficiency of operations and enable new frontiers in exploration at hydrothermal systems on Ocean Worlds. Adaptive robotic decision making is facilitated by computational models of hydrothermal systems and selected in situ sensors used to refine and validate these predictions. Improving autonomous missions requires better models, and thus an understanding of how different sensors respond to hydrothermally altered seawater. During cruise AT50-15 (Juan De Fuca Ridge, 2023), we performed surveys of the hydrothermal plumes at the Endeavour Segment with AUV Sentry to investigate the utility of in situ sensors measuring tracers such as oxidation-reduction potential, optical backscatter, methane abundance, conductivity, and temperature, for building working models of plume dynamics. We investigated length scales of under 1 km to 5 km with a focus on reoccupying locations over varying time scales. Persistent deep current data were available through the Ocean Networks Canada mooring array. Using these datasets, we investigate two questions: (1) how reliably and at what length scales can real-time current information be used to predict the location and source of a hydrothermal plume? (2) How does the relative age (hence, biogeochemical maturation) of the hydrothermal plume fluid affect the response of different in situ sensors? These results will be used to inform the development of autonomous plume detection algorithms that use real-time, in situ data with the purpose of improving AUV exploration of hydrothermal plumes on Earth and other Ocean Worlds. 

Deep-sea hydrothermal vents inject dissolved and particulate metals, dissolved gasses, and biological matter into the water column, creating plumes several hundred meters above the seafloor that can be traced thousands of kilometers. To understand the impact of these plumes, rosettes equipped with sample bottles and in situ instruments, e.g., for turbidity, oxidation-reduction potential, and temperature, have been key tools for collecting water column fluid for informative ex situ analysis. However, deploying rosettes strategically in distal (>1km) plume-derived fluids is difficult when plume material is entrained rapidly with background water and transported by complicated bathymetric, internal, and/or tidal currents. This problem is exacerbated when the controlling dynamics are also poorly constrained (e.g., no persistent monitoring, few historical data) and data collected while in the field to estimate or compensate for these dynamics are only available to be analyzed hours or days following an asset deployment. Autonomous underwater vehicles (AUVs) equipped with equivalent in situ instruments to rosettes excel at exploration missions and creating highly-resolved maps at different spatial scales. Utilization of AUVs for hydrothermal plume charting and strategic sampling with rosettes is at a techno-scientific frontier that requires new data transmission and visualization interfaces for supporting real-time evidence-based operational decisions made at sea. We formulated a method for monitoring in situ water properties while an AUV is underway that (1) builds situational awareness of deep fluid mass distributions, (2) allows scientists-in-the-loop to rapidly identify fluid distribution patterns that inform adaptations to AUV missions or deployments of other assets, like rosettes, for targeted sample collection, and (3) supports robust formulation of working hypotheses of plume dynamics for in-field investigation. We will present a description of the method with preliminary results from cruise AT50-15 (Juan de Fuca Ridge, 2023) using AUV Sentry and discuss how supervised autonomy will improve ocean robotics for future science missions. 

Gravitational lensing by massive objects along the line of sight to the source causes distortions to gravitational wave (GW) signals; such distortions may reveal information about fundamental physics, cosmology, and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO-Virgo network. We search for repeated signals from strong lensing by (1) performing targeted searches for subthreshold signals, (2) calculating the degree of overlap among the intrinsic parameters and sky location of pairs of signals, (3) comparing the similarities of the spectrograms among pairs of signals, and (4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by (1) frequency-independent phase shifts in strongly lensed images, and (2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the nondetection of GW lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects.

 

We report the observation of a coalescing compact binary with component masses 2.5–4.5M_⊙and 1.2–2.0M_⊙(all measurements quoted at the 90% credible level). The gravitational-wave signal GW230529_181500 was observed during the fourth observing run of the LIGO–Virgo–KAGRA detector network on 2023 May 29 by the LIGO Livingston observatory. The primary component of the source has a mass less than 5M_⊙at 99% credibility. We cannot definitively determine from gravitational-wave data alone whether either component of the source is a neutron star or a black hole. However, given existing estimates of the maximum neutron star mass, we find the most probable interpretation of the source to be the coalescence of a neutron star with a black hole that has a mass between the most massive neutron stars and the least massive black holes observed in the Galaxy. We provisionally estimate a merger rate density of${55}_{-47}^{+127}{\mathrm{Gpc}}^{-3}{\mathrm{yr}}^{-1}$for compact binary coalescences with properties similar to the source of GW230529_181500; assuming that the source is a neutron star–black hole merger, GW230529_181500-like sources may make up the majority of neutron star–black hole coalescences. The discovery of this system implies an increase in the expected rate of neutron star–black hole mergers with electromagnetic counterparts and provides further evidence for compact objects existing within the purported lower mass gap.

 

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational-wave (GW) candidate events identified during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Using Fermi-GBM onboard triggers and subthreshold gamma-ray burst (GRB) candidates found in the Fermi-GBM ground analyses, the Targeted Search and the Untargeted Search, we investigate whether there are any coincident GRBs associated with the GWs. We also search the Swift-BAT rate data around the GW times to determine whether a GRB counterpart is present. No counterparts are found. Using both the Fermi-GBM Targeted Search and the Swift-BAT search, we calculate flux upper limits and present joint upper limits on the gamma-ray luminosity of each GW. Given these limits, we constrain theoretical models for the emission of gamma rays from binary black hole mergers.