A Fermi gamma-ray burst monitor search for electromagnetic signals coincident with gravitational-wave candidates in Advanced LIGO's first observing run

We present a search for prompt gamma-ray counterparts to compact binary coalescence gravitational wave (GW) candidates from Advanced LIGO's first observing run (O1). As demonstrated by the multimessenger observations of GW170817/GRB 170817A, electromagnetic and GW observations provide complementary information about the astrophysical source, and in the case of weaker candidates, may strengthen the case for an astrophysical origin. Here we investigate low-significance GW candidates from the O1 compact binary coalescence searches using the Fermi Gamma-Ray Burst Monitor (GBM), leveraging its all sky and broad energy coverage. Candidates are ranked and compared to background to measure the significance. Those with false alarm rates (FARs) of less than 10−5 Hz (about one per day, yielding a total of 81 candidates) are used as the search sample for gamma-ray follow-up. No GW candidates were found to be coincident with gamma-ray transients independently identified by blind searches of the GBM data. In addition, GW candidate event times were followed up by a separate targeted search of GBM data. Among the resulting GBM events, the two with the lowest FARs were the gamma-ray transient GW150914-GBM presented in Connaughton et al. and a solar flare in chance coincidence with a GW candidate

Estimating the contribution of dynamical ejecta in the kilonova associated with GW170817

The source of the gravitational-wave (GW) signal GW170817, very likely a binary neutron star merger, was also observed electromagnetically, providing the first multi-messenger observations of this type. The two-week-long electromagnetic (EM) counterpart had a signature indicative of an r-process-induced optical transient known as a kilonova. This Letter examines how the mass of the dynamical ejecta can be estimated without a direct electromagnetic observation of the kilonova, using GW measurements and a phenomenological model calibrated to numerical simulations of mergers with dynamical ejecta. Specifically, we apply the model to the binary masses inferred from the GW measurements, and use the resulting mass of the dynamical ejecta to estimate its contribution (without the effects of wind ejecta) to the corresponding kilonova light curves from various models. The distributions of dynamical ejecta mass range between Mej = 10 -³ - 10-² M⊙ for various equations of state, assuming that the neutron stars are rotating slowly. In addition, we use our estimates of the dynamical ejecta mass and the neutron star merger rates inferred from GW170817 to constrain the contribution of events like this to the r-process element abundance in the Galaxy when ejecta mass from post-merger winds is neglected. We find that if 10% of the matter dynamically ejected from binary neutron star (BNS) mergers is converted to r-process elements, GW170817-like BNS mergers could fully account for the amount of r-process material observed in the Milky Way

New insights into the genetic etiology of Alzheimer’s disease and related dementias

Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele. © 2022, The Author(s)