Measuring the local dark matter density

Garbari, S; Lake, G; Read, J (2009). Measuring the local dark matter density. In: Hunting for the Dark: the Hidden Side of Galaxy Formation, Qawra, Malta, 19 October 2009 - 23 October 2009, 411-412.

Abstract

We examine systematic problems in determining the local matter density from the vertical motion of stars, i.e. the Oort limit''. Using collisionless simulations and a Monte Carlo Markov Chain technique, we determine the data quality required to detect local dark matter at its expected density. We find that systematic errors are more important than observational errors and apply our technique to Hipparcos data to reassign realistic error bars to the local dark matter density.

Abstract

We examine systematic problems in determining the local matter density from the vertical motion of stars, i.e. the Oort limit''. Using collisionless simulations and a Monte Carlo Markov Chain technique, we determine the data quality required to detect local dark matter at its expected density. We find that systematic errors are more important than observational errors and apply our technique to Hipparcos data to reassign realistic error bars to the local dark matter density.

Statistics

Citations

1 citation in Web of Science®
1 citation in Scopus®
Google Scholar™

Downloads

56 downloads since deposited on 03 Mar 2011
7 downloads since 12 months
Detailed statistics

Additional indexing

Item Type: Conference or Workshop Item (Paper), refereed, original work 07 Faculty of Science > Institute for Computational Science 530 Physics English 23 October 2009 03 Mar 2011 13:30 12 Aug 2017 20:24 American Institute of Physics AIP Conference Proceedings 1240 0094-243X 978-0-7354-0786-2 Publisher DOI. An embargo period may apply. https://doi.org/10.1063/1.3458549 http://arxiv.org/abs/1001.1038http://opac.nebis.ch/F/?local_base=NEBIS&con_lng=GER&func=find-b&find_code=SYS&request=006162632http://www.star.uclan.ac.uk/malta2009/index.shtml (Organisation)

Download

Preview
Content: Published Version
Filetype: PDF
Size: 279kB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.