Search for post-merger gravitational waves from the remnant of the binary neutron star merger GW170817

The first observation of a binary neutron star (NS) coalescence by the Advanced LIGO and Advanced Virgo gravitational-wave (GW) detectors offers an unprecedented opportunity to study matter under the most extreme conditions. After such a merger, a compact remnant is left over whose nature depends primarily on the masses of the inspiraling objects and on the equation of state of nuclear matter. This could be either a black hole (BH) or an NS, with the latter being either long-lived or too massive for stability implying delayed collapse to a BH. Here, we present a search for GWs from the remnant of the binary NS merger GW170817 using data from Advanced LIGO and Advanced Virgo. We search for short- (lesssim1 s) and intermediate-duration (lesssim500 s) signals, which include GW emission from a hypermassive NS or supramassive NS, respectively. We find no signal from the post-merger remnant. Our derived strain upper limits are more than an order of magnitude larger than those predicted by most models. For short signals, our best upper limit on the root sum square of the GW strain emitted from 1–4 kHz is ${h}_{\mathrm{rss}}^{50 \% }=2.1\times {10}^{-22}\,{\mathrm{Hz}}^{-1/2}$ at 50% detection efficiency. For intermediate-duration signals, our best upper limit at 50% detection efficiency is ${h}_{\mathrm{rss}}^{50 \% }=8.4\times {10}^{-22}\,{\mathrm{Hz}}^{-1/2}$ for a millisecond magnetar model, and ${h}_{\mathrm{rss}}^{50 \% }=5.9\times {10}^{-22}\,{\mathrm{Hz}}^{-1/2}$ for a bar-mode model. These results indicate that post-merger emission from a similar event may be detectable when advanced detectors reach design sensitivity or with next-generation detectors

Adaptive optics imaging and optical spectroscopy of a multiple merger in a luminous infrared galaxy

(abridged) We present near-infrared (NIR) adaptive optics imaging obtained with VLT/NACO and optical spectroscopy from the Southern African Large Telescope (SALT) of a luminous infrared galaxy (LIRG) IRAS 19115-2124. These data are combined with archival HST imaging and Spitzer imaging and spectroscopy, allowing us to study this disturbed interacting/merging galaxy, dubbed the Bird, in extraordinary detail. In particular, the data reveal a triple system where the LIRG phenomenon is dominated by the smallest of the components. One nucleus is a regular barred spiral with significant rotation, while another is highly disturbed with a surface brightness distribution intermediate to that of disk and bulge systems, and hints of remaining arm/bar structure. We derive dynamical masses in the range 3-7x10^10 M_solar for both. The third component appears to be a 1-2x10^10 M_solar mass irregular galaxy. The total system exhibits HII galaxy-like optical line ratios and strengths, and no evidence for AGN activity is found from optical or mid-infrared data. The star formation rate is estimated to be 190 M_solar/yr. We search for SNe, super star clusters, and detect 100-300 km/s outflowing gas from the Bird. Overall, the Bird shows kinematic, dynamical, and emission line properties typical for cool ultra luminous IR galaxies. However, the interesting features setting it apart for future studies are its triple merger nature, and the location of its star formation peak - the strongest star formation does not come from the two major K-band nuclei, but from the third irregular component. Aided by simulations, we discuss scenarios where the irregular component is on its first high-speed encounter with the more massive components.Comment: 24 pages, 16 figures. Accepted MNRAS version, minor corrections only, references added. Higher resolution version (1.3MB) is available from http://www.saao.ac.za/~petri/bird/ulirg_bird_highres_vaisanen_v2.pd

Statistics of Merging Peaks of Random Gaussian Fluctuations: Skeleton Tree Formalism

In order to study the statistics of the objects with hierarchical merging, we propose the skeleton tree formalism, which can analytically distinguish the episodic merging and the continuous accretion in the mass growth processes. The distinction was not clear in extended Press-Schechter (PS) formalism. The skeleton tree formalism is a natural extension of the peak theory which is an alternative formalism for the statistics of the bound objects. The fluctuation field smoothing with Gaussian filter produces the landscape with adding the extra-dimension of the filter resolution scale to the spatial coordinate of the original fluctuation. In the landscape, some smoothing peaks are nesting into the neighboring peaks at a type of critical points called sloping saddles appears, which can be interpreted as merging events of the objects in the context of the hierarchical structure formation. The topological properties of the landscape can be abstracted in skeleton trees, which consist of line process of the smoothing peaks and the point process of the sloping saddles. According to this abstract topological picture, in this paper, we present the concept and the basic results of the skeleton tree formalism to describe (1) the distinction between the accretion and the merger in the hierarchical structure formation from various initial random Gaussian fields; (2) the instantaneous number density of the sloping saddles which gives the instantaneous scale function of the objects with the destruction and reformation in the mergers; (3) the rates of the destruction, the reformation, and the relative accretion growth; (4) the self-consistency of the formalism for the statistics of the mass growth processes of the objects; (5) the mean growth history of the objects at the fixed mass.Comment: 16 pages, 4 figures, submitted to MNRAS at 28th July, not yet refereed until 4th Oc

The polar ring galaxy AM1934-563 revisited

We report long-slit spectroscopic observations of the dust-lane polar-ring galaxy AM1934-563 obtained with the Southern African Large Telescope (SALT) during its performance-verification phase. The observations target the spectral region of the Ha, [NII] and [SII] emission-lines, but show also deep NaI stellar absorption lines that we interpret as produced by stars in the galaxy. We derive rotation curves along the major axis of the galaxy that extend out to about 8 kpc from the center for both the gaseous and the stellar components, using the emission and absorption lines. We derive similar rotation curves along the major axis of the polar ring and point out differences between these and the ones of the main galaxy. We identify a small diffuse object visible only in Ha emission and with a low velocity dispersion as a dwarf HII galaxy and argue that it is probably metal-poor. Its velocity indicates that it is a fourth member of the galaxy group in which AM1934-563 belongs. We discuss the observations in the context of the proposal that the object is the result of a major merger and point out some observational discrepancies from this explanation. We argue that an alternative scenario that could better fit the observations may be the slow accretion of cold intergalactic gas, focused by a dense filament of galaxies in which this object is embedded (abridged).Comment: 19 pages, 13 figures, submitted to MNRAS. Some figures were bitmapped to reduce the size. Full resolution version is available from http://www.saao.ac.za/~akniazev/pub/AM1934_563.pd

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/