1,398 research outputs found
A Markov Chain Monte Carlo approach to the study of massive black hole binary systems with LISA
The Laser Interferometer Space Antenna (LISA) will produce a data stream
containing a vast number of overlapping sources: from strong signals generated
by the coalescence of massive black hole binary systems to much weaker
radiation form sub-stellar mass compact binaries and extreme-mass ratio
inspirals. It has been argued that the observation of weak signals could be
hampered by the presence of loud ones and that they first need to be removed to
allow such observations. Here we consider a different approach in which sources
are studied simultaneously within the framework of Bayesian inference. We
investigate the simplified case in which the LISA data stream contains
radiation from a massive black hole binary system superimposed over a (weaker)
quasi-monochromatic waveform generated by a white dwarf binary. We derive the
posterior probability density function of the model parameters using an
automatic Reversible Jump Markov Chain Monte Carlo algorithm (RJMCMC). We show
that the information about the sources and noise are retrieved at the expected
level of accuracy without the need of removing the stronger signal. Our
analysis suggests that this approach is worth pursuing further and should be
considered for the actual analysis of the LISA data.Comment: submitted to cqg as GWDAW-10 conference proceedings, 10 pages, 4
figures, some changes to plots and numerical detail
LISA Response Function and Parameter Estimation
We investigate the response function of LISA and consider the adequacy of its
commonly used approximation in the high-frequency range of the observational
band. We concentrate on monochromatic binary systems, such as white dwarf
binaries. We find that above a few mHz the approxmation starts becoming
increasingly inaccurate. The transfer function introduces additional amplitude
and phase modulations in the measured signal that influence parameter estmation
and, if not properly accounted for, lead to losses of signal-to-noise ratio.Comment: 4 pages, 2 figures, amaldi 5 conference proceeding
MCMC Exploration of Supermassive Black Hole Binary Inspirals
The Laser Interferometer Space Antenna will be able to detect the inspiral
and merger of Super Massive Black Hole Binaries (SMBHBs) anywhere in the
Universe. Standard matched filtering techniques can be used to detect and
characterize these systems. Markov Chain Monte Carlo (MCMC) methods are ideally
suited to this and other LISA data analysis problems as they are able to
efficiently handle models with large dimensions. Here we compare the posterior
parameter distributions derived by an MCMC algorithm with the distributions
predicted by the Fisher information matrix. We find excellent agreement for the
extrinsic parameters, while the Fisher matrix slightly overestimates errors in
the intrinsic parameters.Comment: Submitted to CQG as a GWDAW-10 Conference Proceedings, 9 pages, 5
figures, Published Versio
Facing the LISA Data Analysis Challenge
By being the first observatory to survey the source rich low frequency region
of the gravitational wave spectrum, the Laser Interferometer Space Antenna
(LISA) will revolutionize our understanding of the Cosmos. For the first time
we will be able to detect the gravitational radiation from millions of galactic
binaries, the coalescence of two massive black holes, and the inspirals of
compact objects into massive black holes. The signals from multiple sources in
each class, and possibly others as well, will be simultaneously present in the
data. To achieve the enormous scientific return possible with LISA,
sophisticated data analysis techniques must be developed which can mine the
complex data in an effort to isolate and characterize individual signals. This
proceedings paper very briefly summarizes the challenges associated with
analyzing the LISA data, the current state of affairs, and the necessary next
steps to move forward in addressing the imminent challenges.Comment: 4 pages, no figures, Proceedings paper for the TeV Particle
Astrophysics II conference held Aug 28-31 at the Univ. of Wisconsi
Discrete Model of Ideological Struggle Accounting for Migration
A discrete in time model of ideological competition is formulated taking into
account population migration. The model is based on interactions between global
populations of non-believers and followers of different ideologies. The complex
dynamics of the attracting manifolds is investigated.
Conversion from one ideology to another by means of (i) mass media influence
and (ii) interpersonal relations is considered. Moreover a different birth rate
is assumed for different ideologies, the rate being assumed to be positive for
the reference population, made of initially non-believers. Ideological
competition can happen in one or several regions in space. In the latter case,
migration of non-believers and adepts is allowed; this leads to an enrichment
of the ideological dynamics. Finally, the current ideological situation in the
Arab countries and China is commented upon from the point of view of the
presently developed mathematical model. The massive forced conversion by
Ottoman Turks in the Balkans is briefly discussed.Comment: 24 pages, with 5 figures and 52 refs.; prepared for a Special issue
of Advances in Complex System
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 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
Effect of intragastric acid stability of fat emulsions on gastric emptying, plasma lipid profile and postpradial satiety
Fat is often included in common foods as an emulsion of dispersed oil droplets to enhance the organoleptic quality and stability. The intragastric acid stability of emulsified fat may impact on gastric emptying, satiety and plasma lipid absorption. The aim of the present study was to investigate whether, compared with an acid-unstable emulsion, an acid-stable fat emulsion would empty from the stomach more slowly, cause more rapid plasma lipid absorption and cause greater satiety. Eleven healthy male volunteers received on two separate occasions 500 ml of 15% (w/w) [13C]palmitate-enriched olive oil-in-water emulsion meals which were either stable or unstable in the acid gastric environment. MRI was used to measure gastric emptying and the intragastric oil fraction of the meals. Blood sampling was used to measure plasma lipids and visual analogue scales were used to assess satiety. The acid-unstable fat emulsion broke and rapidly layered in the stomach. Gastric emptying of meal volume was slower for the acid-stable fat emulsion (P,0·0001; two-way ANOVA). The rate of energy delivery of fat from the stomach to the duodenum was not different up to t ¼ 110 min. The acid-stable emulsion induced increased fullness (P,0·05), decreased hunger (P,0·0002), decreased appetite (P,0·0001) and increased the concentration of palmitic acid tracer in the chylomicron fraction (P,0·04). This shows that it is possible to delay gastric emptying and increase satiety by stabilising the intragastric distribution of fat emulsions against the gastric acid environment. This could have implications for the design of novel foods
Optimal statistic for detecting gravitational wave signals from binary inspirals with LISA
A binary compact object early in its inspiral phase will be picked up by its
nearly monochromatic gravitational radiation by LISA. But even this innocuous
appearing candidate poses interesting detection challenges. The data that will
be scanned for such sources will be a set of three functions of LISA's twelve
data streams obtained through time-delay interferometry, which is necessary to
cancel the noise contributions from laser-frequency fluctuations and
optical-bench motions to these data streams. We call these three functions
pseudo-detectors. The sensitivity of any pseudo-detector to a given sky
position is a function of LISA's orbital position. Moreover, at a given point
in LISA's orbit, each pseudo-detector has a different sensitivity to the same
sky position. In this work, we obtain the optimal statistic for detecting
gravitational wave signals, such as from compact binaries early in their
inspiral stage, in LISA data. We also present how the sensitivity of LISA,
defined by this optimal statistic, varies as a function of sky position and
LISA's orbital location. Finally, we show how a real-time search for inspiral
signals can be implemented on the LISA data by constructing a bank of templates
in the sky positions.Comment: 22 pages, 15 eps figures, Latex, uses iopart style/class files. Based
on talk given at the 8th Gravitational Wave Data Analysis Workshop,
Milwaukee, USA, December 17-20, 2003. Accepted for publication in Class.
Quant. Gra
Time-frequency analysis of extreme-mass-ratio inspiral signals in mock LISA data
Extreme-mass-ratio inspirals (EMRIs) of ~ 1-10 solar-mass compact objects
into ~ million solar-mass massive black holes can serve as excellent probes of
strong-field general relativity. The Laser Interferometer Space Antenna (LISA)
is expected to detect gravitational wave signals from apprxomiately one hundred
EMRIs per year, but the data analysis of EMRI signals poses a unique set of
challenges due to their long duration and the extensive parameter space of
possible signals. One possible approach is to carry out a search for EMRI
tracks in the time-frequency domain. We have applied a time-frequency search to
the data from the Mock LISA Data Challenge (MLDC) with promising results. Our
analysis used the Hierarchical Algorithm for Clusters and Ridges to identify
tracks in the time-frequency spectrogram corresponding to EMRI sources. We then
estimated the EMRI source parameters from these tracks. In these proceedings,
we discuss the results of this analysis of the MLDC round 1.3 data.Comment: Amaldi-7 conference proceedings; requires jpconf style file
The Reliability of Global and Hemispheric Surface Temperature Records
The purpose of this review article is to discuss the development and associated estimation of uncertainties in the global and hemispheric surface temperature records. The review begins by detailing the groups that produce surface temperature datasets. After discussing the reasons for similarities and differences between the various products, the main issues that must be addressed when deriving accurate estimates, particularly for hemispheric and global averages, are then considered. These issues are discussed in the order of their importance for temperature records at these spatial scales: biases in SST data, particularly before the 1940s; the exposure of land-based thermometers before the development of louvred screens in the late 19th century; and urbanization effects in some regions in recent decades. The homogeneity of land-based records is also discussed; however, at these large scales it is relatively unimportant. The article concludes by illustrating hemispheric and global temperature records from the four groups that produce series in near-real time
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