Ultraluminous X-ray sources

Ultraluminous X-ray sources (ULXs) are accreting black holes with X-ray luminosities in excess of the Eddington limit for a typical ~10 solar mass Galactic black hole. There is an emerging consensus that most ULXs are probably fairly typical stellar remnant black holes in a new super-Eddington `ultraluminous' accretion state, characterised by a soft excess and high energy spectral curvature, which may be associated with a radiatively-driven wind and cool, optically thick Comptonisation respectively. However, this scenario may be insufficient to produce some of the most luminous ULXs. Here we present a sample of extreme luminosity ULXs, and show that their X-ray spectral and timing properties are consistent with most of them being in the sub-Eddington low/hard state. Given their luminosities, this suggests that these ULXs contain 10^3-10^4 solar mass black holes. But, in one of the extreme ULXs we find evidence of high energy spectral curvature, which is a key feature of the ultraluminous state. We explore this ULX further, and show that its X-ray spectrum is consistent with being in the ultraluminous state, but with any wind emission obscured from view by the high column density of material in the direction of the source. We also investigate the ultraluminous state further, and present an X-ray spectral and timing study of ULXs with some of the highest quality XMM-Newton data. We show that their spectral and timing properties are consistent with current models of super-Eddington accretion, where a massive, radiatively-driven wind forms a funnel-like geometry around the source. Then, the observed X-ray properties are dependant on both the accretion rate, and the inclination at which the ULX system is observed. Finally, we consider optical counterparts to a small sample of ULXs. We fit the X-ray and optical data of these with a new spectral model of an irradiated, colour-temperature-corrected accretion disc, finding that ~0.1 per cent of their bolometric luminosity is reprocessed in the outer disc. This may be due to the opposing effects of self-shielding in the accretion disc and reflection in a super-Eddington wind

Timing in trace conditioning of the nictitating membrane response of the rabbit (Oryctolagus cuniculus) : scalar, nonscalar, and adaptive features

Using interstimulus intervals (ISIs) of 125, 250, and 500 msec in trace conditioning of the rabbit nictitating membrane response, the offset times and durations of conditioned responses (CRs) were collected along with onset and peak latencies. All measures were proportional to the ISI, but only onset and peak latencies conformed to the criterion for scalar timing. Regarding the CR’s possible protective overlap of the unconditioned stimulus (US), CR duration increased with ISI, while the peak’s alignment with the US declined. Implications for models of timing and CR adaptiveness are discussed

How I Got My Name

During the last days of slavery, my grandfather was a child on a plantation in Mississippi. He, being the son of a favorite household servant, was given the privilege of studying with the master\u27s children under an efficient tutor. Gratefulness for this opportunity and eagerness to learn caused him to advance rapidly

Analysis of combinatorial search spaces for a class of NP-hard problems, An

2011 Spring.Includes bibliographical references.Given a finite but very large set of states X and a real-valued objective function ƒ defined on X, combinatorial optimization refers to the problem of finding elements of X that maximize (or minimize) ƒ. Many combinatorial search algorithms employ some perturbation operator to hill-climb in the search space. Such perturbative local search algorithms are state of the art for many classes of NP-hard combinatorial optimization problems such as maximum k-satisfiability, scheduling, and problems of graph theory. In this thesis we analyze combinatorial search spaces by expanding the objective function into a (sparse) series of basis functions. While most analyses of the distribution of function values in the search space must rely on empirical sampling, the basis function expansion allows us to directly study the distribution of function values across regions of states for combinatorial problems without the need for sampling. We concentrate on objective functions that can be expressed as bounded pseudo-Boolean functions which are NP-hard to solve in general. We use the basis expansion to construct a polynomial-time algorithm for exactly computing constant-degree moments of the objective function ƒ over arbitrarily large regions of the search space. On functions with restricted codomains, these moments are related to the true distribution by a system of linear equations. Given low moments supplied by our algorithm, we construct bounds of the true distribution of ƒ over regions of the space using a linear programming approach. A straightforward relaxation allows us to efficiently approximate the distribution and hence quickly estimate the count of states in a given region that have certain values under the objective function. The analysis is also useful for characterizing properties of specific combinatorial problems. For instance, by connecting search space analysis to the theory of inapproximability, we prove that the bound specified by Grover's maximum principle for the Max-Ek-Lin-2 problem is sharp. Moreover, we use the framework to prove certain configurations are forbidden in regions of the Max-3-Sat search space, supplying the first theoretical confirmation of empirical results by others. Finally, we show that theoretical results can be used to drive the design of algorithms in a principled manner by using the search space analysis developed in this thesis in algorithmic applications. First, information obtained from our moment retrieving algorithm can be used to direct a hill-climbing search across plateaus in the Max-k-Sat search space. Second, the analysis can be used to control the mutation rate on a (1+1) evolutionary algorithm on bounded pseudo-Boolean functions so that the offspring of each search point is maximized in expectation. For these applications, knowledge of the search space structure supplied by the analysis translates to significant gains in the performance of search