Long slit spectroscopy for exoplanet characterization in SPHERE

被引:0
|
作者
Vigan, Arthur [1 ]
Langlois, Maud [1 ]
Moutou, Claire [1 ]
Dohlen, Kjetil [1 ]
机构
[1] Technopole Marseille Etoile, Lab Astrophys Marseille, F-13013 Marseille, France
关键词
Direct exoplanet detection; long slit spectroscopy; speckle noise;
D O I
10.1117/12.788838
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Extrasolar planet observation and characterization is a, major objective for astronomy in the coming decade. The Spectro-Polarimetric High contrast imager for Exoplanets Research (SPHERE) instrument for the Very Large Telescope (VLT) is currently under development to achieve this objective with greater performances than any existing instruments. It will have the capability to observe planets down to few masses of Jupiter at separations m small as 0.1 arcseconds from the central star thanks to dedicated extreme adaptive optics system and coronagraph. Planets characterization will be achieved with IRDIS, one of the 3 science modules of SPHERE, using its long slit spectroscopy (LSS) mode along with a Lyot coronagraph at low (similar to 40) or medium (similar to 400) resolution. Similarly to the dual-band imaging (DBI) technique dedicated to detection, the main limitation of the long slit spectroscopy is the speckles generated by instrumental static and quasi-static aberrations, especially when observing very close to the star. Another performance limitation is the chromatic dependence of the speckles in the field, known as speckle chromatism, which creates a modulation of the spectrum. Finally, we are also facing problems related to long slit spectroscopy, such as slit efficiency, thermal background and difficulty to preserve the spectrum continuum. Intensive simulations have been performed using the CAOS framework under IDL, in order to simulate realistic spectra in terms of signal, noise and instrumental artifacts. We present here in details the expected performances among with a detailed analysis of the various noise sources contributions. This analysis leads to a quantitative estimation of the characterization limitations and optimized data reduction procedures.
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页数:11
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