Random template placement and prior information

In signal detection problems, one is usually faced with the task of searching a parameter space for peaks in the likelihood function which indicate the presence of a signal. Random searches have proven to be very efficient as well as easy to implement, compared e.g. to searches along regular grids in parameter space. Knowledge of the parameterised shape of the signal searched for adds structure to the parameter space, i.e., there are usually regions requiring to be densely searched while in other regions a coarser search is sufficient. On the other hand, prior information identifies the regions in which a search will actually be promising or may likely be in vain. Defining specific figures of merit allows one to combine both template metric and prior distribution and devise optimal sampling schemes over the parameter space. We show an example related to the gravitational wave signal from a binary inspiral event. Here the template metric and prior information are particularly contradictory, since signals from low-mass systems tolerate the least mismatch in parameter space while high-mass systems are far more likely, as they imply a greater signal-to-noise ratio (SNR) and hence are detectable to greater distances. The derived sampling strategy is implemented in a Markov chain Monte Carlo (MCMC) algorithm where it improves convergence.Comment: Proceedings of the 8th Edoardo Amaldi Conference on Gravitational Waves. 7 pages, 4 figure

Localizing gravitational wave sources with optical telescopes and combining electromagnetic and gravitational wave data

Neutron star binaries, which are among the most promising sources for the direct detection of gravitational waves (GW) by ground based detectors, are also potential electromagnetic (EM) emitters. Gravitational waves will provide a new window to observe these events and hopefully give us glimpses of new astrophysics. In this paper, we discuss how EM information of these events can considerably improve GW parameter estimation both in terms of accuracy and computational power requirement. And then in return how GW sky localization can help EM astronomers in follow-up studies of sources which did not yield any prompt emission. We discuss how both EM source information and GW source localization can be used in a framework of multi-messenger astronomy. We illustrate how the large error regions in GW sky localizations can be handled in conducting optical astronomy in the advance detector era. We show some preliminary results in the context of an array of optical telescopes called BlackGEM, dedicated for optical follow-up of GW triggers, that is being constructed in La Silla, Chile and is expected to operate concurrent to the advanced GW detectors.Comment: 8 pages, 8 figures, Proceeding for Sant Cugat Forum for Astrophysic

The effects of LIGO detector noise on a 15-dimensional Markov-chain Monte-Carlo analysis of gravitational-wave signals

Gravitational-wave signals from inspirals of binary compact objects (black holes and neutron stars) are primary targets of the ongoing searches by ground-based gravitational-wave (GW) interferometers (LIGO, Virgo, and GEO-600). We present parameter-estimation results from our Markov-chain Monte-Carlo code SPINspiral on signals from binaries with precessing spins. Two data sets are created by injecting simulated GW signals into either synthetic Gaussian noise or into LIGO detector data. We compute the 15-dimensional probability-density functions (PDFs) for both data sets, as well as for a data set containing LIGO data with a known, loud artefact ("glitch"). We show that the analysis of the signal in detector noise yields accuracies similar to those obtained using simulated Gaussian noise. We also find that while the Markov chains from the glitch do not converge, the PDFs would look consistent with a GW signal present in the data. While our parameter-estimation results are encouraging, further investigations into how to differentiate an actual GW signal from noise are necessary.Comment: 11 pages, 2 figures, NRDA09 proceeding

Analyse und Bewertung zu Stand und Entwicklungsmöglichkeiten von Futterbau und Tierernährung im ökologischen Landbau - Themenbezogenes Netzwerk Tierernährung im Ökologischen Landbau

Das Ziel des Vorhabens war es, ein Netzwerk zum Thema „Futterbau und Tierernährung im Ökologischen Landbau“ zu etablieren. Es soll dazu dienen, Fachleute aus der landwirtschaftlichen Praxis, der Beratung und der Forschung zu verbinden, um einen Wissensaustausch zu ermöglichen und durch inter- und transdisziplinäre Diskussionen Entwicklungsperspektiven aufzuzeigen. Zur detaillierten Analyse und Bewertung der Problematik wurden Arbeitsgruppen gebildet, die für die Bereiche Rinder-, Schweine- und Geflügelfütterung jeweils den Handlungsbedarf aufzeigen und Lösungsansätze für die bedarfsgerechte Versorgung dieser Nutztiere insbesondere im Hinblick auf die Umsetzung der 100 % Biofütterung erarbeiten sollten. Ergänzend dazu wurde eine umfangreiche Literaturrecherche und Schwachstellenanalyse durchgeführt. Die Steuerungsgruppe als zentrales Organ legte die Arbeitsweise des Netzwerks fest und gab die Inhalte vor, die als Grundlage für Diskussionen und wissenschaftliche Auseinandersetzungen dienen sollten. Sie wirkte beratend bei der Ausarbeitung der Schwachstellenanalyse mit und formulierte die Ziele des im Rahmen des Projektes durchgeführten Workshops. Die Koordination des gesamten Vorhabens oblag dem Zentrum Landwirtschaft und Umwelt der Universität Göttingen. Auf einem Workshop im März 2007 wurden die Ergebnisse der Netzwerkarbeit vorgestellt und mit Experten aus Wissenschaft, Beratung und Praxis diskutiert und bewertet. Empfehlungen für Futterbau und Tierernährung im ökologischen Landbau wurden differenziert nach Umsetzungs- und Forschungsbedarf formuliert. Zusätzlich wurden die Ergebnisse in der Zeitschrift „Ökologie und Landbau“ in Form eines Sonderheftes publiziert und so einer breiten landwirtschaftlichen Fachöffentlichkeit zugänglich gemacht. Die Arbeit im Netzwerk hat sich als effiziente Methode erwiesen, vorhandenes Wissen zwischen und innerhalb der einzelnen Disziplinen und Institutionen zu transferieren und zu bündeln. Sie sollte im Interesse aller Beteiligten weitergeführt werden, um den wissenschaftlichen Austausch weiter zu entwickeln und für Kooperationen in der Forschung, aber auch zwischen Praxis und Forschung zu nutzen

Inference on inspiral signals using LISA MLDC data

In this paper we describe a Bayesian inference framework for analysis of data obtained by LISA. We set up a model for binary inspiral signals as defined for the Mock LISA Data Challenge 1.2 (MLDC), and implemented a Markov chain Monte Carlo (MCMC) algorithm to facilitate exploration and integration of the posterior distribution over the 9-dimensional parameter space. Here we present intermediate results showing how, using this method, information about the 9 parameters can be extracted from the data.Comment: Accepted for publication in Classical and Quantum Gravity, GWDAW-11 special issu

Coherent Bayesian analysis of inspiral signals

We present in this paper a Bayesian parameter estimation method for the analysis of interferometric gravitational wave observations of an inspiral of binary compact objects using data recorded simultaneously by a network of several interferometers at different sites. We consider neutron star or black hole inspirals that are modeled to 3.5 post-Newtonian (PN) order in phase and 2.5 PN in amplitude. Inference is facilitated using Markov chain Monte Carlo methods that are adapted in order to efficiently explore the particular parameter space. Examples are shown to illustrate how and what information about the different parameters can be derived from the data. This study uses simulated signals and data with noise characteristics that are assumed to be defined by the LIGO and Virgo detectors operating at their design sensitivities. Nine parameters are estimated, including those associated with the binary system, plus its location on the sky. We explain how this technique will be part of a detection pipeline for binary systems of compact objects with masses up to 20 \sunmass, including cases where the ratio of the individual masses can be extreme.Comment: Accepted for publication in Classical and Quantum Gravity, Special issue for GWDAW-1

Parameter estimation of spinning binary inspirals using Markov-chain Monte Carlo

We present a Markov-chain Monte-Carlo (MCMC) technique to study the source parameters of gravitational-wave signals from the inspirals of stellar-mass compact binaries detected with ground-based gravitational-wave detectors such as LIGO and Virgo, for the case where spin is present in the more massive compact object in the binary. We discuss aspects of the MCMC algorithm that allow us to sample the parameter space in an efficient way. We show sample runs that illustrate the possibilities of our MCMC code and the difficulties that we encounter.Comment: 10 pages, 2 figures, submitted to Classical and Quantum Gravit

A Student-t based filter for robust signal detection

The search for gravitational-wave signals in detector data is often hampered by the fact that many data analysis methods are based on the theory of stationary Gaussian noise, while actual measurement data frequently exhibit clear departures from these assumptions. Deriving methods from models more closely reflecting the data's properties promises to yield more sensitive procedures. The commonly used matched filter is such a detection method that may be derived via a Gaussian model. In this paper we propose a generalized matched-filtering technique based on a Student-t distribution that is able to account for heavier-tailed noise and is robust against outliers in the data. On the technical side, it generalizes the matched filter's least-squares method to an iterative, or adaptive, variation. In a simplified Monte Carlo study we show that when applied to simulated signals buried in actual interferometer noise it leads to a higher detection rate than the usual ("Gaussian") matched filter.Comment: 17 pages, 6 figure

On the distortion of twin building lattices

We show that twin building lattices are undistorted in their ambient group; equivalently, the orbit map of the lattice to the product of the associated twin buildings is a quasi-isometric embedding. As a consequence, we provide an estimate of the quasi-flat rank of these lattices, which implies that there are infinitely many quasi-isometry classes of finitely presented simple groups. In an appendix, we describe how non-distortion of lattices is related to the integrability of the structural cocycle