Rates and Characteristics of Intermediate Mass Ratio Inspirals Detectable by Advanced LIGO

Gravitational waves (GWs) from the inspiral of a neutron star (NS) or stellar-mass black hole (BH) into an intermediate-mass black hole (IMBH) with mass between ~50 and ~350 solar masses may be detectable by the planned advanced generation of ground-based GW interferometers. Such intermediate mass ratio inspirals (IMRIs) are most likely to be found in globular clusters. We analyze four possible IMRI formation mechanisms: (1) hardening of an NS-IMBH or BH-IMBH binary via three-body interactions, (2) hardening via Kozai resonance in a hierarchical triple system, (3) direct capture, and (4) inspiral of a compact object from a tidally captured main-sequence star; we also discuss tidal effects when the inspiraling object is an NS. For each mechanism we predict the typical eccentricities of the resulting IMRIs. We find that IMRIs will have largely circularized by the time they enter the sensitivity band of ground-based detectors. Hardening of a binary via three-body interactions, which is likely to be the dominant mechanism for IMRI formation, yields eccentricities under 10^-4 when the GW frequency reaches 10 Hz. Even among IMRIs formed via direct captures, which can have the highest eccentricities, around 90% will circularize to eccentricities under 0.1 before the GW frequency reaches 10 Hz. We estimate the rate of IMRI coalescences in globular clusters and the sensitivity of a network of three Advanced LIGO detectors to the resulting GWs. We show that this detector network may see up to tens of IMRIs per year, although rates of one to a few per year may be more plausible. We also estimate the loss in signal-to-noise ratio that will result from using circular IMRI templates for data analysis and find that, for the eccentricities we expect, this loss is negligible.Comment: Accepted for publication in ApJ; revised version reflects changes made to the article during the acceptance proces

Transcriptomic signatures of neuronal differentiation and their association with risk genes for autism spectrum and related neuropsychiatric disorders.

Genes for autism spectrum disorders (ASDs) are also implicated in fragile X syndrome (FXS), intellectual disabilities (ID) or schizophrenia (SCZ), and converge on neuronal function and differentiation. The SH-SY5Y neuroblastoma cell line, the most widely used system to study neurodevelopment, is currently discussed for its applicability to model cortical development. We implemented an optimal neuronal differentiation protocol of this system and evaluated neurodevelopment at the transcriptomic level using the CoNTeXT framework, a machine-learning algorithm based on human post-mortem brain data estimating developmental stage and regional identity of transcriptomic signatures. Our improved model in contrast to currently used SH-SY5Y models does capture early neurodevelopmental processes with high fidelity. We applied regression modelling, dynamic time warping analysis, parallel independent component analysis and weighted gene co-expression network analysis to identify activated gene sets and networks. Finally, we tested and compared these sets for enrichment of risk genes for neuropsychiatric disorders. We confirm a significant overlap of genes implicated in ASD with FXS, ID and SCZ. However, counterintuitive to this observation, we report that risk genes affect pathways specific for each disorder during early neurodevelopment. Genes implicated in ASD, ID, FXS and SCZ were enriched among the positive regulators, but only ID-implicated genes were also negative regulators of neuronal differentiation. ASD and ID genes were involved in dendritic branching modules, but only ASD risk genes were implicated in histone modification or axonal guidance. Only ID genes were over-represented among cell cycle modules. We conclude that the underlying signatures are disorder-specific and that the shared genetic architecture results in overlaps across disorders such as ID in ASD. Thus, adding developmental network context to genetic analyses will aid differentiating the pathophysiology of neuropsychiatric disorders

Uterine NK cells are critical in shaping DC immunogenic functions compatible with pregnancy progression.

Dendritic cell (DC) and natural killer (NK) cell interactions are important for the regulation of innate and adaptive immunity, but their relevance during early pregnancy remains elusive. Using two different strategies to manipulate the frequency of NK cells and DC during gestation, we investigated their relative impact on the decidualization process and on angiogenic responses that characterize murine implantation. Manipulation of the frequency of NK cells, DC or both lead to a defective decidual response characterized by decreased proliferation and differentiation of stromal cells. Whereas no detrimental effects were evident upon expansion of DC, NK cell ablation in such expanded DC mice severely compromised decidual development and led to early pregnancy loss. Pregnancy failure in these mice was associated with an unbalanced production of anti-angiogenic signals and most notably, with increased expression of genes related to inflammation and immunogenic activation of DC. Thus, NK cells appear to play an important role counteracting potential anomalies raised by DC expansion and overactivity in the decidua, becoming critical for normal pregnancy progression

Post- and peritraumatic stress in disaster survivors: An explorative study about the influence of individual and event characteristics across different types of disasters

Background: Examination of existing research on posttraumatic adjustment after disasters suggests that survivors’ posttraumatic stress levels might be better understood by investigating the influence of the characteristics of the event experienced on how people thought and felt, during the event as well as afterwards. Objective: To compare survivors’ perceived post- and peritraumatic emotional and cognitive reactions across different types of disasters. Additionally, to investigate individual and event characteristics. Design: In a European multi-centre study, 102 survivors of different disasters terror attack, flood, fire and collapse of a building were interviewed about their responses during the event. Survivors’ perceived posttraumatic stress levels were assessed with the Impact of Event Scale-Revised (IES-R). Peritraumatic emotional stress and risk perception were rated retrospectively. Influences of individual characteristics, such as socio-demographic data, and event characteristics, such as time and exposure factors, on post- and peritraumatic outcomes were analyzed. Results: Levels of reported post- and peritraumatic outcomes differed significantly between types of disasters. Type of disaster was a significant predictor of all three outcome variables but the factors gender, education, time since event, injuries and fatalities were only significant for certain outcomes. Conclusion: Results support the hypothesis that there are differences in perceived post- and peritraumatic emotional and cognitive reactions after experiencing different types of disasters. However, it should be noted that these findings were not only explained by the type of disaster itself but also by individual and event characteristics. As the study followed an explorative approach, further research paths are discussed to better understand the relationships between variables

Extreme mass ratio inspiral rates: dependence on the massive black hole mass

We study the rate at which stars spiral into a massive black hole (MBH) due to the emission of gravitational waves (GWs), as a function of the mass M of the MBH. In the context of our model, it is shown analytically that the rate approximately depends on the MBH mass as M^{-1/4}. Numerical simulations confirm this result, and show that for all MBH masses, the event rate is highest for stellar black holes, followed by white dwarfs, and lowest for neutron stars. The Laser Interferometer Space Antenna (LISA) is expected to see hundreds of these extreme mass ratio inspirals per year. Since the event rate derived here formally diverges as M->0, the model presented here cannot hold for MBHs of masses that are too low, and we discuss what the limitations of the model are.Comment: Accepted to CQG, special LISA issu

A log-quadratic relation for predicting supermassive black hole masses from the host bulge Sersic index

We reinvestigate the correlation between black hole mass and bulge concentration. With an increased galaxy sample, updated estimates of galaxy distances, black hole masses, and Sersic indices `n' - a measure of concentration - we perform a least-squares regression analysis to obtain a relation suitable for the purpose of predicting black hole masses in other galaxies. In addition to the linear relation, log(M_bh) = 7.81(+/-0.08) + 2.69(+/-0.28)[log(n/3)] with epsilon_(intrin)=0.31 dex, we investigated the possibility of a higher order M_bh-n relation, finding the second order term in the best-fitting quadratic relation to be inconsistent with a value of zero at greater than the 99.99% confidence level. The optimal relation is given by log(M_bh) = 7.98(+/-0.09) + 3.70(+/-0.46)[log(n/3)] - 3.10(+/-0.84)[log(n/3)]^2, with epsilon_(intrin)=0.18 dex and a total absolute scatter of 0.31 dex. Extrapolating the quadratic relation, it predicts black holes with masses of ~10^3 M_sun in n=0.5 dwarf elliptical galaxies, compared to ~10^5 M_sun from the linear relation, and an upper bound on the largest black hole masses in the local universe, equal to 1.2^{+2.6}_{-0.4}x10^9 M_sun}. In addition, we show that the nuclear star clusters at the centers of low-luminosity elliptical galaxies follow an extrapolation of the same quadratic relation. Moreover, we speculate that the merger of two such nucleated galaxies, accompanied by the merger and runaway collision of their central star clusters, may result in the late-time formation of some supermassive black holes. Finally, we predict the existence of, and provide equations for, a relation between M_bh and the central surface brightness of the host bulge

Detecting extreme mass ratio inspiral events in LISA data using the Hierarchical Algorithm for Clusters and Ridges (HACR)

One of the most exciting prospects for the Laser Interferometer Space Antenna (LISA) is the detection of gravitational waves from the inspirals of stellar-mass compact objects into supermassive black holes. Detection of these sources is an extremely challenging computational problem due to the large parameter space and low amplitude of the signals. However, recent work has suggested that the nearest extreme mass ratio inspiral (EMRI) events will be sufficiently loud that they might be detected using computationally cheap, template-free techniques, such as a time-frequency analysis. In this paper, we examine a particular time-frequency algorithm, the Hierarchical Algorithm for Clusters and Ridges (HACR). This algorithm searches for clusters in a power map and uses the properties of those clusters to identify signals in the data. We find that HACR applied to the raw spectrogram performs poorly, but when the data is binned during the construction of the spectrogram, the algorithm can detect typical EMRI events at distances of up to $\sim2.6$Gpc. This is a little further than the simple Excess Power method that has been considered previously. We discuss the HACR algorithm, including tuning for single and multiple sources, and illustrate its performance for detection of typical EMRI events, and other likely LISA sources, such as white dwarf binaries and supermassive black hole mergers. We also discuss how HACR cluster properties could be used for parameter extraction.Comment: 21 pages, 11 figures, submitted to Class. Quantum Gravity. Modified and shortened in light of referee's comments. Updated results consider tuning over all three HACR thresholds, and show 10-15% improvement in detection rat

Minimum Conductivity and Evidence for Phase Transitions in Ultra-clean Bilayer Graphene

Bilayer graphene (BLG) at the charge neutrality point (CNP) is strongly susceptible to electronic interactions, and expected to undergo a phase transition into a state with spontaneous broken symmetries. By systematically investigating a large number of singly- and doubly-gated bilayer graphene (BLG) devices, we show that an insulating state appears only in devices with high mobility and low extrinsic doping. This insulating state has an associated transition temperature Tc~5K and an energy gap of ~3 meV, thus strongly suggesting a gapped broken symmetry state that is destroyed by very weak disorder. The transition to the intrinsic broken symmetry state can be tuned by disorder, out-of-plane electric field, or carrier density