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When particle dark matter is bound gravitationally around a massive black hole in sufficiently high densities, the dark matter will affect the rate of inspiral of a secondary compact object that forms a binary with the massive black hole. In this paper, we revisit previous estimates of the impact of dark-matter accretion by black-hole secondaries on the emitted gravitational waves. We identify a region of parameter space of binaries for which estimates of the accretion were too large (specifically, because the dark-matter distribution was assumed to be unchanging throughout the process, and the secondary black hole accreted more mass in dark matter than that enclosed within the orbit of the secondary). To restore consistency in these scenarios, we propose and implement a method to remove dark-matter particles from the distribution function when they are accreted by the secondary. This new feedback procedure then satisfies mass conservation, and when evolved with physically reasonable initial data, the mass accreted by the secondary no longer exceeds the mass enclosed within its orbital radius. Comparing the simulations with accretion feedback to those without this feedback, including feedback leads to a smaller gravitational-wave dephasing from binaries in which only the effects of dynamical friction are being modeled. Nevertheless, the dephasing can be hundreds to almost a thousand gravitational-wave cycles, an amount that should allow the effects of accretion to be inferred from gravitational-wave measurements of these systems. 

The United States of America has a diverse collection of freshwater mussels comprising 301 species distributed among 59 genera and two families (Margaritiferidae and Unionidae), each having a unique suite of traits. Mussels are among the most imperilled animals and are critical components of their ecosystems, and successful management, conservation and research requires a cohesive and widely accessible data source. Although trait-based analysis for mussels has increased, only a small proportion of traits reflecting mussel diversity in this region has been collated. Decentralized and non-standardized trait information impedes large-scale analysis. Assembling trait data in a synthetic dataset enables comparison across species and lineages and identification of data gaps. We collated data from the primary literature, books, state and federal reports, theses and dissertations, and museum collections into a centralized dataset covering information on taxonomy, morphology, reproductive ecology and life history, fish hosts, habitats, thermal tolerance, geographic distribution, available genetic information, and conservation status. By collating these traits, we aid researchers in assessing variation in mussel traits and modelling ecosystem change.

 

Gravitational-wave memory effects arise from nonoscillatory components of gravitational-wave signals, and they are predictions of general relativity in the nonlinear regime that have close connections to the asymptotic properties of isolated gravitating systems. There are many types of memory effects that have been studied in the literature. In this paper we focus on the “displacement” and “spin” memories, which are expected to be the largest of these effects from sources such as the binary black hole mergers which have already been detected by LIGO and Virgo. The displacement memory is a change in the relative separation of two initially comoving observers due to a burst of gravitational waves, whereas the spin memory is a portion of the change in relative separation of observers with initial relative velocity. As both of these effects are small, LIGO, Virgo, and KAGRA can only detect memory effects from individual events that are much louder (and thus rarer) than those that have been detected so far. By combining data from multiple events, however, these effects could be detected in a population of binary mergers. In this paper, we present new forecasts for how long current and future detectors will need to operate in order to measure these effects from populations of binary black hole systems that are consistent with the populations inferred from the detections from LIGO and Virgo’s first three observing runs. We find that a second-generation detector network of LIGO, Virgo, and KAGRA operating at the O4 (“design”) sensitivity for 1.5 years and then operating at the O5 (“plus”) sensitivity for an additional 1.5 years can detect the displacement memory. For Cosmic Explorer, we find that displacement memory could be detected for individual loud events, and that the spin memory could be detected in a population after 5 years of observation time.