Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-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 amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst 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 non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Functional Specialization of the Small Interfering RNA Pathway in Response to Virus Infection

<div><p>In <i>Drosophila</i>, post-transcriptional gene silencing occurs when exogenous or endogenous double stranded RNA (dsRNA) is processed into small interfering RNAs (siRNAs) by Dicer-2 (Dcr-2) in association with a dsRNA-binding protein (dsRBP) cofactor called Loquacious (Loqs-PD). siRNAs are then loaded onto Argonaute-2 (Ago2) by the action of Dcr-2 with another dsRBP cofactor called R2D2. Loaded Ago2 executes the destruction of target RNAs that have sequence complementarity to siRNAs. Although Dcr-2, R2D2, and Ago2 are essential for innate antiviral defense, the mechanism of virus-derived siRNA (vsiRNA) biogenesis and viral target inhibition remains unclear. Here, we characterize the response mechanism mediated by siRNAs against two different RNA viruses that infect Drosophila. In both cases, we show that vsiRNAs are generated by Dcr-2 processing of dsRNA formed during viral genome replication and, to a lesser extent, viral transcription. These vsiRNAs seem to preferentially target viral polyadenylated RNA to inhibit viral replication. Loqs-PD is completely dispensable for silencing of the viruses, in contrast to its role in silencing endogenous targets. Biogenesis of vsiRNAs is independent of both Loqs-PD and R2D2. R2D2, however, is required for sorting and loading of vsiRNAs onto Ago2 and inhibition of viral RNA expression. Direct injection of viral RNA into Drosophila results in replication that is also independent of Loqs-PD. This suggests that triggering of the antiviral pathway is not related to viral mode of entry but recognition of intrinsic features of virus RNA. Our results indicate the existence of a vsiRNA pathway that is separate from the endogenous siRNA pathway and is specifically triggered by virus RNA. We speculate that this unique framework might be necessary for a prompt and efficient antiviral response.</p></div

Viral polyadenylated RNA is a major target of slicing by Ago2.

<p>(<b>A,B</b>) Levels of genome RNA, antigenome RNA, and polyadenylated virus RNA from <i>Dcr-2</i> mutants (hollow bars) and wildtype controls (solid bars) at different times post infection with VSV (<b>A</b>) and SINV (<b>B</b>). Asterisks indicate <i>p</i><0.05 comparing RNA levels between mutant and wildtype samples. (<b>C</b>) Fold increase in polyadenylated viral RNA, genome RNA, and antigenome RNA in <i>Dcr-2</i> mutants relative to wildtype at different times post infection with VSV or SINV. (<b>D</b>) VSV RNA levels in null <i>Ago2⁴¹⁴</i>, <i>Ago2^V966M/Ago2⁴¹⁴</i>, and wildtype heterozygous animals at different days post infection. Asterisks indicate <i>p</i><0.05 comparing RNA levels between mutant and matched wildtype samples; (@) indicates <i>p</i><0.05 comparing RNA levels between <i>Ago2⁴¹⁴</i> and <i>Ago2^V966M/Ago2⁴¹⁴</i> mutants.</p

Characterization of vsiRNAs.

<p>(<b>A,B</b>) Coverage of vsiRNAs along viral genomes in samples from wildtype (wt), <i>Dcr-2</i>, <i>R2D2</i> and <i>loqs</i> mutant animals. Shown is read density in 20-nt bins for positive-stranded RNAs (blue) and negative-stranded RNAs (red) matching VSV (<b>A</b>) and SINV (<b>B</b>). Genome structures of the viruses are also shown oriented 5′ – 3′ for the positive strand. Protein-coding genes are highlighted. (<b>C,D</b>) Shown are the regions in the VSV (<b>C</b>) and SINV (<b>D</b>) genomes in which no vsiRNAs were detected by high-throughput sequencing. These gaps in vsiRNA coverage are scaled to the genome. Vertical lines in each plot mark the gene promoters within the VSV genome and the 5′ end of the subgenomic RNA in the SINV genome, respectively. The probability that each gap did not occur by chance is shown as the inverse expected value (E-value) on a log10 scale. The horizontal line in each plot represents a significance cutoff of <i>p</i> = 0.05 that the gap occurred by chance. E-values above the line are even more significant. Gaps are present in samples from wildtype (wt), <i>R2D2</i> and <i>loqs</i> mutant infected animals. Since there were fewer sequence reads in wildtype samples, the number of gaps are greater and their significance is smaller.</p

Requirement for Dcr-2 helicase activity and detection of vsiRNA phasing in SINV.

<p>(<b>A</b>) SINV genome RNA levels in <i>Dcr-2^A500V</i> and wildtype animals at different times post infection. Asterisks indicate <i>p</i><0.05. (<b>B</b>) Autocorrelation functions (ACF) of the distance in nucleotides between 5′ ends of vsiRNAs from the SINV positive strand. Shown are all vsiRNAs mapping to the 5′-most 1000 nts of the positive strand. The sample was derived from infected <i>R2D2</i> mutants. ACF values above the dotted line are statistically significant (<i>p</i><0.05).</p

vsiRNA abundance is dependent on Dcr-2 but not Loqs-PD.

<p>(<b>A</b>) Levels of the genome RNA strand, antigenome RNA strand, and total virus RNA from VSV and SINV infected animals 48 hours post infection. The polarity of SINV and VSV genomes are indicated. (<b>B,C</b>) Normalized levels of sequenced small RNAs of different size that match the VSV (<b>B</b>) and SINV (<b>C</b>) genomes. Shown are levels after infection of wildtype (wt), <i>Dcr-2</i>, <i>R2D2</i> and <i>loqs</i> mutants. Bars above the midline denote positive-stranded small RNAs, and bars below the midline denote negative-stranded small RNAs.</p