Supermassive black hole binaries (SMBHBs) should form frequently in galactic nuclei as a result of galaxy mergers. At subparsec separations, binaries become strong sources of low-frequency ...gravitational waves (GWs), targeted by Pulsar Timing Arrays. We used recent upper limits on continuous GWs from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) 11 yr data set to place constraints on putative SMBHBs in nearby massive galaxies. We compiled a comprehensive catalog of ∼44,000 galaxies in the local universe (up to redshift ∼0.05) and populated them with hypothetical binaries, assuming that the total mass of the binary is equal to the SMBH mass derived from global scaling relations. Assuming circular equal-mass binaries emitting at NANOGrav's most sensitive frequency of 8 nHz, we found that 216 galaxies are within NANOGrav's sensitivity volume. We ranked the potential SMBHBs based on GW detectability by calculating the total signal-to-noise ratio such binaries would induce within the NANOGrav array. We placed constraints on the chirp mass and mass ratio of the 216 hypothetical binaries. For 19 galaxies, only very unequal-mass binaries are allowed, with the mass of the secondary less than 10% that of the primary, roughly comparable to constraints on an SMBHB in the Milky Way. However, we demonstrated that the (typically large) uncertainties in the mass measurements can weaken the upper limits on the chirp mass. Additionally, we were able to exclude binaries delivered by major mergers (mass ratio of at least 1/4) for several of these galaxies. We also derived the first limit on the density of binaries delivered by major mergers purely based on GW data.
Human collaboration is more likely to lead to cognitive growth when all group-members are actively involved in the collaborative process. However, there are cases that intragroup relationships need ...support. In this paper, we present an autonomous robotic system designed to interact with a pair of children in a problem-solving setting, aiming to understand how the robot behaviour impacts the group-members' social dynamics. We developed an autonomous system with the Haru robot which we evaluated with an experimental study with 5-8yo children (N =84) to test the impact of the robot's cognitive reliability and social positioning on human-to-human social dynamics, task performance and help-seeking behaviour. All participants took part in a baseline session (without the robot), an intervention (with the robot in a turn-taking setting) and an evaluation session (with a robot in a voluntary interaction setting). Results indicate that children who interacted with the reliable robot had a better task performance but children who interacted with the unreliable robot exhibited more task-related social interactions. Based on the results, we propose an interaction design concept which combines the set of the evaluated robot behaviours for an adaptive targeted support of child-robot teaming.
Working with a Social Robot in School Davison, Daniel P.; Wijnen, Frances M.; Charisi, Vicky ...
2020 15th ACM/IEEE International Conference on Human-Robot Interaction (HRI),
03/2020
Conference Proceeding
Open access
Interactive learning technologies, such as robots, increasingly find their way into schools. However, more research is needed to see how children might work with such systems in the future. This ...paper presents the unsupervised, four month deployment of a Robot-Extended Computer Assisted Learning (RECAL) system with 61 children working in their own classroom. Using automatically collected quantitative data we discuss how their usage patterns and self-regulated learning process developed throughout the study.
With its capacity to observe \(\sim 10^{5-6}\) faint active galactic nuclei (AGN) out to redshift \(z\approx 6\), Roman is poised to reveal a population of \(10^{4-6}\, {\rm M_\odot}\) black holes ...during an epoch of vigorous galaxy assembly. By measuring the light curves of a subset of these AGN and looking for periodicity, Roman can identify several hundred massive black hole binaries (MBHBs) with 5-12 day orbital periods, which emit copious gravitational radiation and will inevitably merge on timescales of \(10^{3-5}\) years. During the last few months of their merger, such binaries are observable with the Laser Interferometer Space Antenna (LISA), a joint ESA/NASA gravitational wave mission set to launch in the mid-2030s. Roman can thus find LISA precursors, provide uniquely robust constraints on the LISA source population, help identify the host galaxies of LISA mergers, and unlock the potential of multi-messenger astrophysics with massive black hole binaries.
Analysis of pulsar timing data have provided evidence for a stochastic gravitational wave background in the nHz frequency band. The most plausible source of such a background is the superposition of ...signals from millions of supermassive black hole binaries. The standard statistical techniques used to search for such a background and assess its significance make several simplifying assumptions, namely: i) Gaussianity; ii) isotropy; and most often iii) a power-law spectrum. However, a stochastic background from a finite collection of binaries does not exactly satisfy any of these assumptions. To understand the effect of these assumptions, we test standard analysis techniques on a large collection of realistic simulated datasets. The dataset length, observing schedule, and noise levels were chosen to emulate the NANOGrav 15-year dataset. Simulated signals from millions of binaries drawn from models based on the Illustris cosmological hydrodynamical simulation were added to the data. We find that the standard statistical methods perform remarkably well on these simulated datasets, despite their fundamental assumptions not being strictly met. They are able to achieve a confident detection of the background. However, even for a fixed set of astrophysical parameters, different realizations of the universe result in a large variance in the significance and recovered parameters of the background. We also find that the presence of loud individual binaries can bias the spectral recovery of the background if we do not account for them.
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