6 research outputs found
Gravitational wave bursts from cosmic (super)strings: Quantitative analysis and constraints
We discuss data analysis techniques that can be used in the search for
gravitational wave bursts from cosmic strings. When data from multiple
interferometers are available, we describe consistency checks that can be used
to greatly reduce the false alarm rates. We construct an expression for the
rate of bursts for arbitrary cosmic string loop distributions and apply it to
simple known solutions. The cosmology is solved exactly and includes the
effects of a late-time acceleration. We find substantially lower burst rates
than previous estimates suggest and explain the disagreement. Initial LIGO is
unlikely to detect field theoretic cosmic strings with the usual loop sizes,
though it may detect cosmic superstrings as well as cosmic strings and
superstrings with non-standard loop sizes (which may be more realistic). In the
absence of a detection, we show how to set upper limits based on the loudest
event. Using Initial LIGO sensitivity curves, we show that these upper limits
may result in interesting constraints on the parameter space of theories that
lead to the production of cosmic strings.Comment: Replaced with version accepted for publication in PR
Incorporating information from source simulations into searches for gravitational-wave bursts
The detection of gravitational waves from astrophysical sources of
gravitational waves is a realistic goal for the current generation of
interferometric gravitational-wave detectors. Short duration bursts of
gravitational waves from core-collapse supernovae or mergers of binary black
holes may bring a wealth of astronomical and astrophysical information. The
weakness of the waves and the rarity of the events urges the development of
optimal methods to detect the waves. The waves from these sources are not
generally known well enough to use matched filtering however; this drives the
need to develop new ways to exploit source simulation information in both
detections and information extraction. We present an algorithmic approach to
using catalogs of gravitational-wave signals developed through numerical
simulation, or otherwise, to enhance our ability to detect these waves. As more
detailed simulations become available, it is straightforward to incorporate the
new information into the search method. This approach may also be useful when
trying to extract information from a gravitational-wave observation by allowing
direct comparison between the observation and simulations.Comment: 8 pages, 1 figur
Plans for the LIGO-TAMA Joint Search for Gravitational Wave Bursts
We describe the plans for a joint search for unmodelled gravitational wave
bursts being carried out by the LIGO and TAMA collaborations using data
collected during February-April 2003. We take a conservative approach to
detection, requiring candidate gravitational wave bursts to be seen in
coincidence by all four interferometers. We focus on some of the complications
of performing this coincidence analysis, in particular the effects of the
different alignments and noise spectra of the interferometers.Comment: Proceedings of the 8th Gravitational Wave Data Analysis Workshop,
Milwaukee, WI, USA. 10 pages, 3 figures, documentclass ``iopart'
Price dynamics in political prediction markets
Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series