Thesis Topic: Identification of low mass nearby objects from multi-epoch near-infrared surveys

 

Thesis Supervisor: Valentin Ivanov

 


Abstract

Recently a number of wide field surveys have made it possible to revise and improve the census of intrinsically faint nearby low-mass objects. The WISE satellite mission has been especially successful in this regard, but wide-field ground based surveys have also contributed.

I am a member of two deep wide field near-infrared surveys - of the Magellanic Cloud system (VMC) and of the inner Milky Way (VVV), covering a combined area of nearly 700 sq. deg on the sky down to bellow Ks~20 mag. The former has 12 Ks epochs, the later between 60 and 100 Ks epoch per pointing. The VVV just got extended to double its original footprint. These unprecedentedly deep data sets have been mined for high proper motion nearby objects, but only the brightest (J<=11 mag). The rest still needs to be explored.

The proposed thesis will include data mining for identification of high proper motion objects from the VMC and VVV archive, and follow up observations - spectroscopy and AO imaging to study the newly identified nearby objects.

 

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The distributions of the proper motion vectors for bright high proper motion stars in the VVV footprint. The length of the vectors is proportional to the proper motion (scale for 1 arcsecĀ per year is shown in the upper right corner). Reproduced from Kurtev et al. (submitted).