Constraining the Black Hole Mass Spectrum with Gravitational Wave Observations I: The Error Kernel

Many scenarios have been proposed for the origin of the supermassive black holes (SMBHs) that are found in the centres of most galaxies. Many of these formation scenarios predict a high-redshift population of intermediate-mass black holes (IMBHs), with masses in the range 100 to 100000 times that of the Sun. A powerful way to observe these IMBHs is via gravitational waves the black holes emit as they merge. The statistics of the observed black hole population should, in principle, allow us to discriminate between competing astrophysical scenarios for the origin and formation of SMBHs. However, gravitational wave detectors such as LISA will not be able to detect all such mergers nor assign precise black hole parameters to the merger, due to weak gravitational wave signal strengths. In order to use LISA observations to infer the statistics of the underlying population, these errors must be taken into account. We describe here a method for folding the LISA gravitational wave parameter error estimates into an `error kernel' designed for use at the population model level. The effects of this error function are demonstrated by applying it to several recent models of black hole mergers, and some tentative conclusions are made about LISA's ability to test scenarios of the origin and formation of supermassive black holes.Comment: 22 pages, 4 figures. There have been various clarifications, typos corrected, and so on, partly in response to referee comments. This second arXiv version has been switched to AASTeX preprint format for better compatibility with the arXiv. Accepted for publication in MNRA

Constraining the Black Hole Mass Spectrum with LISA Observations II: Direct comparison of detailed models

A number of scenarios have been proposed for the origin of the supermassive black holes (SMBHs) that are found in the centres of most galaxies. Many such scenarios predict a high-redshift population of massive black holes (MBHs), with masses in the range 100 to 100000 times that of the Sun. When the Laser Interferometer Space Antenna (LISA) is finally operational, it is likely that it will detect on the order of 100 of these MBH binaries as they merge. The differences between proposed population models produce appreciable effects in the portion of the population which is detectable by LISA, so it is likely that the LISA observations will allow us to place constraints on them. However, gravitational wave detectors such as LISA will not be able to detect all such mergers nor assign precise black hole parameters to the merger, due to weak gravitational wave signal strengths. This paper explores LISA's ability to distinguish between several MBH population models. In this way, we go beyond predicting a LISA observed population and consider the extent to which LISA observations could inform astrophysical modellers. The errors in LISA parameter estimation are applied with a direct method which generates random sample parameters for each source in a population realisation. We consider how the distinguishability varies depending on the choice of source parameters (1 or 2 parameters chosen from masses, redshift or spins) used to characterise the model distributions, with confidence levels determined by 1 and 2-dimensional tests based on the Kolmogorov-Smirnov test.Comment: 32 pages, 21 Figures, 6 Tables; Submitted to MNRA

Intermediate-mass-ratio-inspirals in the Einstein Telescope. II. Parameter estimation errors

We explore the precision with which the Einstein Telescope (ET) will be able to measure the parameters of intermediate-mass-ratio inspirals (IMRIs). We calculate the parameter estimation errors using the Fisher Matrix formalism and present results of a Monte Carlo simulation of these errors over choices for the extrinsic parameters of the source. These results are obtained using two different models for the gravitational waveform which were introduced in paper I of this series. These two waveform models include the inspiral, merger and ringdown phases in a consistent way. One of the models, based on the transition scheme of Ori & Thorne [1], is valid for IMBHs of arbitrary spin, whereas the second model, based on the Effective One Body (EOB) approach, has been developed to cross-check our results in the non-spinning limit. In paper I of this series, we demonstrated the excellent agreement in both phase and amplitude between these two models for non-spinning black holes, and that their predictions for signal-to-noise ratios (SNRs) are consistent to within ten percent. We now use these models to estimate parameter estimation errors for binary systems with masses 1.4+100, 10+100, 1.4+500 and 10+500 solar masses (SMs), and various choices for the spin of the central intermediate-mass black hole (IMBH). Assuming a detector network of three ETs, the analysis shows that for a 10 SM compact object (CO) inspiralling into a 100 SM IMBH with spin q=0.3, detected with an SNR of 30, we should be able to determine the CO and IMBH masses, and the IMBH spin magnitude to fractional accuracies of 0.001, 0.0003, and 0.001, respectively. We also expect to determine the location of the source in the sky and the luminosity distance to within 0.003 steradians, and 10%, respectively. We also assess how the precision of parameter determination depends on the network configuration.Comment: 21 pages, 5 figures. One reference corrected in v3 for consistency with published version in Phys Rev

Astrophysics and cosmology with a deci-hertz gravitational-wave detector: TianGO

We present the astrophysical science case for a space-based, deci-Hz gravitational-wave (GW) detector. We particularly highlight an ability in inferring a source's sky location, both when combined with a network of ground-based detectors to form a long triangulation baseline, and by itself for the early warning of merger events. Such an accurate location measurement is the key for using GW signals as standard sirens for constraining the Hubble constant. This kind of detector also opens up the possibility of testing type Ia supernovae progenitor hypotheses by constraining the merger rates of white dwarf binaries with both super- and sub-Chandrasekhar masses separately. We will discuss other scientific outcomes that can be delivered, including the precise determination of black hole spins, the constraint of structure formation in the early Universe, and the search for intermediate-mass black holes

Gravitational wave emission from binary supermassive black holes

Massive black hole binaries (MBHBs) are unavoidable outcomes of the hierarchical structure formation process, and according to the theory of general relativity are expected to be the loudest gravitational wave (GW) sources in the Universe. In this article I provide a broad overview of MBHBs as GW sources. After reviewing the basics of GW emission from binary systems and of MBHB formation, evolution and dynamics, I describe in some details the connection between binary properties and the emitted gravitational waveform. Direct GW observations will provide an unprecedented wealth of information about the physical nature and the astrophysical properties of these extreme objects, allowing to reconstruct their cosmic history, dynamics and coupling with their dense stellar and gas environment. In this context I describe ongoing and future efforts to make a direct detection with space based interferometry and pulsar timing arrays, highlighting the invaluable scientific payouts of such enterprises.Comment: 26 pages, 9 figures, invited article for the focus issue on astrophysical black holes in Classical and Quantum Gravity, guest editors: D. Merritt and L. Rezzolla. Submitte

Involvement of MicroRNA Families in Cancer

Collecting representative sets of cancer microRNAs (miRs) from the literature we show that their corresponding families are enriched in sets of highly interacting miR families. Targeting cancer genes on a statistically significant level, such cancer miR families strongly intervene with signaling pathways that harbor numerous cancer genes. Clustering miR family-specific profiles of pathway intervention, we found that different miR families share similar interaction patterns. Resembling corresponding patterns of cancer miRs families, such interaction patterns may indicate a miR family’s potential role in cancer. As we find that the number of targeted cancer genes is a naı¨ve proxy for a cancer miR family, we design a simple method to predict candidate miR families based on gene-specific interaction profiles. Assessing the impact of miR families to distinguish between (non-)cancer genes, we predict a set of 84 potential candidate families, including 75% of initially collected cancer miR families. Further confirming their relevance, predicted cancer miR families are significantly indicated in increasing, non-random numbers of tumor types