Articles from Data

  • The Earth is Our Telescope

    Antares 2007-2012 neutrino coverage

    The coverage of the 2007-2012 Antares neutrinos, with positional uncertainties scaled by three.

    At our Heidelberg data center, we have have already published some neutrino data, for instance the Amanda-II neutrino candiates, the IceCube-40 neutrino candidates, and the 2007-2010 Antares results.

    That latter project has now given us updated data, for the first time including timestamps, available as the Antares service.

    Now, if you look at the coverage (above), you'll notice at least two things: For one, there's no data around the north pole. That's because the instrument sits beyond the waters of the Mediterranean sea, not far from where some of you may now enjoy your vacation. And it is using the Earth as its filter – it's measuring particles as they come ”up” and discards anything that goes “down”. Yes, neutrinos are strange beasts.

    The second somewhat unusual thing is that the positional uncertainties are huge compared to what we're used to from optical catalogs: a degree is not uncommon (we've scaled the error circles by a factor of 3 in the image above, though). And that requires some extra care when working with the data.

    In our table, we have a column origin_est that actually contains circles. Hence, to find images of the “strongest” neutrinos in our obscore table, you could write:

    ivoa.obscore AS o
    JOIN (
      SELECT top 10 * FROM
      ORDER BY n_hits desc
    ) AS n

    in a query to our TAP service.

    But of course, this only gets really exciting when you can hope that perhaps that neutrino was emitted by some violent event that may have been observed serendipitously by someone else. That query then is (and we're using all the neutrinos now):

    ivoa.obscore AS o
    JOIN as n
       epoch_mjd between t_min-0.01 and t_max+0.01
        1=INTERSECTS(origin_est, s_region)

    On our data center, this doesn't yield anything at the moment (it does, though, if you do away with the spatial constraint, which frankly suprised me a bit). But then if you went and ran this query against obscore services of active observatories? And perhaps had your computer try and figure out whether anything unusual is seen on whatever you find?

    We think that would be really nifty, and right after we've published a first version of our little pyVO course (which is a bit on the back burner, but watch this space), we'll probably work that out as a proper pyVO use case.

    And meanwhile: In case you'll be standing on the shores of the Mediterranean this summer, enjoy the view and think of the monster deep down in there waiting for neutrinos to detect – and eventually drop into our data center.

  • See Who's Kinking the Sky

    A new arrival in the GAVO Data Center is UCAC5, another example of a slew of new catalogs combining pre-existing astrometry with Gaia DR1, just like the HSOY catalog we've featured here a couple of weeks back.

    That's a nice opportunity to show how to use ADQL's JOIN operator for something else than the well-known CONTAINS-type crossmatch. Since both UCAC5 and HSOY reference Gaia DR1, both have, for each object, a notion which element of the Gaia source catalog they correspond to. For HSOY, that's the gaia_id column, in UCAC5, it's just source_id. Hence, to compare results from both efforts, all you have to do is to join on source_id=gaia_id (you can save yourself the explicit table references here because the column names are unique to each table.

    So, if you want to compare proper motions, all you need to do is to point your favourite TAP client's interface to and run:

        in_unit(avg(uc.pmra-hsoy.pmra), 'mas/yr') AS pmradiff,
        in_unit(avg(uc.pmde-hsoy.pmde), 'mas/yr') AS pmdediff,
        count(*) as n,
        ivo_healpix_index (6, raj2000, dej2000) AS hpx
        FROM hsoy.main AS hsoy
        JOIN ucac5.main as uc
        ON (uc.source_id=hsoy.gaia_id)
        WHERE comp IS NULL    -- hsoy junk filter
        AND clone IS NULL     -- again, hsoy junk filter
        GROUP BY hpx

    (see Taylor et al's All of the Sky if you're unsure what do make of the healpix/GROUP BY magic).

    Of course, the fact that both tables are in the same service helps, but with a bit of upload magic you could do about the same analysis across TAP services.

    Just so there's a colourful image in this post, too, here's what this query shows for the differences in proper motion in RA:

    (equatorial coordinates, and the aux axis is a bit cropped here; try for yourself to see how things look for PM in declination or when plotted in galactic coordinates).

    What does this image mean? Well, it means that probably both UCAC5 and HSOY would still putt kinks into the sky if you wait long enough.

    In the brightest and darkest points, if you waited 250 years, the coordinate system induced by each catalog on the sky would be off by 1 arcsec with respect to the other (on a sphere, that means there's kinks somewhere). It may seem amazing that there's agreement to at least this level between the two catalogs – mind you, 1 arcsec is still more than 100 times smaller than you could see by eye; you'd have to go back to the Mesolithic age to have the slightest chance of spotting the disagreement without serious optical aids. But when Gaia DR2 will come around (hopefully around April 2018), our sky will be more stable even than that.

    Of course, both UCAC5 and HSOY are, indirectly, standing on the shoulders of the same giant, namely Hipparcos and Tycho, so the agreement may be less surprising, and we strongly suspect that a similar image will look a whole lot less pleasant when Gaia has straightened out the sky, in particular towards weaker stars.

    But still: do you want to bet if UCAC5 or HSOY will turn out to be closer to a non-kinking sky? Let us know. Qualifications („For bright stars...”) are allowed.

  • PPMXL+Gaia DR1=HSOY in the Heidelberg Data Center

    The stunning precision of Gaia's astrometry is already apparent in the first release of the data obtained by the satellite, available since last September. However, apart from the small TGAS subset (objects already observed by the 90ies HIPPARCOS astrometry satellite) there is no information on the objects' proper motions in DR1.

    Until Gaia-quality proper motions will become available in DR2, the HSOY catalog – described in Altmann et al's paper Hot Stuff for One Year (HSOY) freshly up in arXiv and online at – can help if you can live with somewhat lesser-quality kinematics.

    It derives proper motions for roughly half a billion stars from PPMXL and Gaia DR1, which already gives an unprecedented source for 4D astrometry around J2015. And you can start working with it right now. The catalog is available in GAVO's Heidelberg data center (TAP access URL:; there's also an SCS service). Fire up your favourite TAP or SCS client (our preference: TOPCAT) and search for HSOY.

    An all-sky heatmap showing much larger errors south of -30 deg.

    Oh, and in case you're new to the whole TAP/ADQL game: There's our ADQL introduction, and if you're at a German astronomical institution, we'd be happy to hold one of our VO Days at your institute – just drop us a mail.

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