Gravitational-wave data analysis using binary black-hole waveforms

Coalescing binary black-hole systems are among the most promising sources of gravitational waves for ground-based interferometers. While the \emph{inspiral} and \emph{ring-down} stages of the binary black-hole coalescence are well-modelled by analytical approximation methods in general relativity, the recent progress in numerical relativity has enabled us to compute accurate waveforms from the \emph{merger} stage also. This has an important impact on the search for gravitational waves from binary black holes. In particular, while the current gravitational-wave searches look for each stage of the coalescence separately, combining the results from analytical and numerical relativity enables us to \emph{coherently} search for all three stages using a single template family. `Complete' binary black-hole waveforms can now be produced by matching post-Newtonian waveforms with those computed by numerical relativity. These waveforms can be parametrised to produce analytical waveform templates. The `complete' waveforms can also be used to estimate the efficiency of different search methods aiming to detect signals from black-hole coalescences. This paper summarises some recent efforts in this direction.Comment: Minor modifications in the text, added table of phenomenological coefficient

Constraining the mass of the graviton using coalescing black-hole binaries

We study how well the mass of the graviton can be constrained from gravitational-wave (GW) observations of coalescing binary black holes. Whereas the previous investigations employed post-Newtonian (PN) templates describing only the inspiral part of the signal, the recent progress in analytical and numerical relativity has provided analytical waveform templates coherently describing the inspiral-merger-ringdown (IMR) signals. We show that a search for binary black holes employing IMR templates will be able to constrain the mass of the graviton much more accurately (about an order of magnitude) than a search employing PN templates. The best expected bound from GW observatories (lambda_g > 7.8 x 10^13 km from Adv. LIGO, lambda_g > 7.1 x 10^14 km from Einstein Telescope, and lambda_g > 5.9 x 10^17 km from LISA) are several orders-of-magnitude better than the best available model-independent bound (lambda_g > 2.8 x 10^12 km, from Solar system tests). Most importantly, GW observations will provide the first constraints from the highly dynamical, strong-field regime of gravity.Comment: 8 pages, 4 figures, 3 table

ANTIDS: Self-Organized Ant-based Clustering Model for Intrusion Detection System

Security of computers and the networks that connect them is increasingly becoming of great significance. Computer security is defined as the protection of computing systems against threats to confidentiality, integrity, and availability. There are two types of intruders: the external intruders who are unauthorized users of the machines they attack, and internal intruders, who have permission to access the system with some restrictions. Due to the fact that it is more and more improbable to a system administrator to recognize and manually intervene to stop an attack, there is an increasing recognition that ID systems should have a lot to earn on following its basic principles on the behavior of complex natural systems, namely in what refers to self-organization, allowing for a real distributed and collective perception of this phenomena. With that aim in mind, the present work presents a self-organized ant colony based intrusion detection system (ANTIDS) to detect intrusions in a network infrastructure. The performance is compared among conventional soft computing paradigms like Decision Trees, Support Vector Machines and Linear Genetic Programming to model fast, online and efficient intrusion detection systems.Comment: 13 pages, 3 figures, Swarm Intelligence and Patterns (SIP)- special track at WSTST 2005, Muroran, JAPA