Search for: All records

While microplastics (MPs) are globally prevalent in marine environments, extending to the Arctic and sub-Arctic regions, the extent and distribution of MPs in terrestrial waters, drinking water sources, and recreational water in these areas remain unknown. This field study establishes a baseline for MPs in surface water sources, including lakes, rivers, and creeks, as well as in snow across three geo-locations (i.e., Far North, Interior, and Southcentral) in Alaska. Results (mean ± SE) show that the highest MP counts exist in snow (681 ± 45 L−1), followed by lakes (361 ± 76 L−1), creeks (377 ± 88 L−1), and rivers (359 ± 106 L−1). The smallest MPs (i.e., 90.6 ± 4 μm) also happened to have occurred in snow, followed by their larger sizes in lakes (203.9 ± 65 μm), creeks (382.8 ± 136.5 μm), and rivers (455.4 ± 212 μm). The physical morphology of MPs varies widely. MP fragments are predominant (i.e., nearly 62–74%) in these sites, while MP fibers (nearly 13–21%), pellets (nearly 13–18%), and films (<6%) also exist in appreciable quantities. Geolocation-wise, the Far North, where MPs were collected from off-road locations, shows the highest MP counts (695 ± 58 L−1), compared to Interior (473 ± 64 L−1) and Southcentral (447 ± 62 L−1) Alaska. Results also indicate that the occurrence of MPs in the source waters and snow decreases with increasing distance from the nearest coastlines and towns or communities. These baseline observations of MPs in terrestrial waters and precipitation across Alaska indicate MP pollution even in less-explored environments. This can be seen as a cause for concern with regard to MP exposure and risks in the region and beyond. 

Abstract We report a gravitational-wave parameter estimation algorithm,AMPLFI, based on likelihood-free inference using normalizing flows. The focus ofAMPLFIis to perform real-time parameter estimation for candidates detected by machine-learning based compact binary coalescence search,Aframe. We present details of our algorithm and optimizations done related to data-loading and pre-processing on accelerated hardware. We train our model using binary black-hole (BBH) simulations on real LIGO-Virgo detector noise. Our model has $\sim 6$million trainable parameters with training times $\lesssim 24$h. Based on online deployment on a mock data stream of LIGO-Virgo data,Aframe+AMPLFIis able to pick up BBH candidates and infer parameters for real-time alerts from data acquisition with a net latency of $\sim 6$s. 

Abstract We report the observation of gravitational waves from two binary black hole coalescences during the fourth observing run of the LIGO–Virgo–KAGRA detector network, GW241011 and GW241110. The sources of these two signals are characterized by rapid and precisely measured primary spins, nonnegligible spin–orbit misalignment, and unequal mass ratios between their constituent black holes. These properties are characteristic of binaries in which the more massive object was itself formed from a previous binary black hole merger and suggest that the sources of GW241011 and GW241110 may have formed in dense stellar environments in which repeated mergers can take place. As the third-loudest gravitational-wave event published to date, with a median network signal-to-noise ratio of 36.0, GW241011 furthermore yields stringent constraints on the Kerr nature of black holes, the multipolar structure of gravitational-wave generation, and the existence of ultralight bosons within the mass range 10⁻¹³–10⁻¹²eV. 

Abstract On 2023 November 23, the two LIGO observatories both detected GW231123, a gravitational-wave signal consistent with the merger of two black holes with masses $137_{-18}^{+23}{M}_{\odot }$and $101_{-50}^{+22}{M}_{\odot }$(90% credible intervals), at a luminosity distance of 0.7–4.1 Gpc, a redshift of $0.40_{-0.25}^{+0.27}$, and with a network signal-to-noise ratio of ∼20.7. Both black holes exhibit high spins— $0.90_{-0.19}^{+0.10}$and $0.80_{-0.52}^{+0.20}$, respectively. A massive black hole remnant is supported by an independent ringdown analysis. Some properties of GW231123 are subject to large systematic uncertainties, as indicated by differences in the inferred parameters between signal models. The primary black hole lies within or above the theorized mass gap where black holes between 60–130M_⊙should be rare, due to pair-instability mechanisms, while the secondary spans the gap. The observation of GW231123 therefore suggests the formation of black holes from channels beyond standard stellar collapse and that intermediate-mass black holes of mass ∼200M_⊙form through gravitational-wave-driven mergers. 

The gravitational-wave signal GW250114 was observed by the two LIGO detectors with a network matched-filter signal-to-noise ratio of 80. The signal was emitted by the coalescence of two black holes with near-equal masses $m_1={33.6}_{-0.8}^{+1.2}{M}_{\odot }$and $m_2={32.2}_{-1.3}^{+0.8}{M}_{\odot }$, and small spins ${\chi }_{1,2}\le 0.26$(90% credibility) and negligible eccentricity $e\le 0.03$. Postmerger data excluding the peak region are consistent with the dominant quadrupolar $(\ell =|m|=2)$mode of a Kerr black hole and its first overtone. We constrain the modes’ frequencies to $\pm 30\%$of the Kerr spectrum, providing a test of the remnant’s Kerr nature. We also examine Hawking’s area law, also known as the second law of black hole mechanics, which states that the total area of the black hole event horizons cannot decrease with time. A range of analyses that exclude up to five of the strongest merger cycles confirm that the remnant area is larger than the sum of the initial areas to high credibility.