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H

H. Pentikäinen

Researcher at University of Helsinki

Publications -  10
Citations -  5597

H. Pentikäinen is an academic researcher from University of Helsinki. The author has contributed to research in topics: Astrometry & Markov chain Monte Carlo. The author has an hindex of 8, co-authored 9 publications receiving 4386 citations.

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The Gaia mission

T. Prusti, +624 more
TL;DR: Gaia as discussed by the authors is a cornerstone mission in the science programme of the European Space Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach.
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Gaia Data Release 1. Open cluster astrometry: performance, limitations, and future prospects

F. van Leeuwen, +590 more
TL;DR: The first Gaia Data Release contains the Tycho-Gaia Astrometric Solution (TGAS) component by means of the astrometric data for open clusters as mentioned in this paper, which is a subset of about 2 million stars for which, besides the position and photometry, the proper motion and parallax are calculated using Hipparcos and Tycho 2 positions in 1991.
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Gaia Data Release 1. Testing parallaxes with local Cepheids and RR Lyrae stars

G. Clementini, +637 more
TL;DR: In this article, the first parallax measurements of the primary standard candles of the cosmological distance ladder, that involve astrometry collected by Gaia during the initial 14 months of science operation, are published in Gaia Data Release 1 (DR1) as part of the Tycho-Gaia Astrometric Solution (TGAS).
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Gaia Data Release 1. Testing the parallaxes with local Cepheids and RR Lyrae stars

G. Clementini, +589 more
TL;DR: In this paper, the first parallax measurements of the primary standard candles of the cosmological distance ladder, that involve astrometry collected by Gaia during the initial 14 months of science operation, are published in Gaia Data Release 1 (DR1) as part of the Tycho-Gaia Astrometric Solution (TGAS).
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Streak detection and analysis pipeline for space-debris optical images

TL;DR: An automated streak detection and processing pipeline is developed and demonstrated its performance with an extensive database of semisynthetic images simulating streak observations both from ground-based and space-based observing platforms.