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Register a new userBuilding galaxies, stars, planets and the ingredients for life between the stars. A scientific proposal for a European Ultraviolet-Visible Observatory (EUVO)
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Ana Ines Gomez de Castro Prof
Publication date
2013
fields
Physics
and research's language is
English
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The growth of luminous structures and the building blocks of life in the Universe began as primordial gas was processed in stars and mixed at galactic scales. The mechanisms responsible for this development are not well understood and have changed over the intervening 13 billion years. To follow the evolution of matter over cosmic time, it is necessary to study the strongest (resonance) transitions of the most abundant species in the Universe. Most of them are in the ultraviolet (UV; 950A-3000A) spectral range that is unobservable from the ground. A versatile space observatory with UV sensitivity a factor of 50-100 greater than existing facilities will revolutionize our understanding of the Universe. Habitable planets grow in protostellar discs under ultraviolet irradiation, a by-product of the star-disk interaction that drives the physical and chemical evolution of discs and young planetary systems. The electronic transitions of the most abundant molecules are pumped by the UV field, providing unique diagnostics of the planet-forming environment that cannot be accessed from the ground. Earths atmosphere is in constant interaction with the interplanetary medium and the solar UV radiation field. A 50-100 times improvement in sensitivity would enable the observation of the key atmospheric ingredients of Earth-like exoplanets (carbon, oxygen, ozone), provide crucial input for models of biologically active worlds outside the solar system, and provide the phenomenological baseline to understand the Earth atmosphere in context. In this white paper, we outline the key science that such a facility would make possible and outline the instrumentation to be implemented.
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Young stars and planets both grow by accreting material from the proto-stellar disks. Planetary structure and formation models assume a common origin of the building blocks, yet, thus far, there is no direct conclusive observational evidence correlating the composition of rocky planets to their host stars. Here we present evidence of a chemical link between rocky planets and their host stars. The iron-mass fraction of the most precisely characterized rocky planets is compared to that of their building blocks, as inferred from the atmospheric composition of their host stars. We find a clear and statistically significant correlation between the two. We also find that this correlation is not one-to-one, owing to the disk-chemistry and planet formation processes. Therefore rocky planet composition depends on the chemical composition of the proto-planetary disk and contains signatures about planet formation processes.
Understanding the solar outer atmosphere requires concerted, simultaneous solar observations from the visible to the vacuum ultraviolet (VUV) and soft X-rays, at high spatial resolution (between 0.1 and 0.3), at high temporal resolution (on the order of 10 s, i.e., the time scale of chromospheric dynamics), with a wide temperature coverage (0.01 MK to 20 MK, from the chromosphere to the flaring corona), and the capability of measuring magnetic fields through spectropolarimetry at visible and near-infrared wavelengths. Simultaneous spectroscopic measurements sampling the entire temperature range are particularly important. These requirements are fulfilled by the Japanese Solar-C mission (Plan B), composed of a spacecraft in a geosynchronous orbit with a payload providing a significant improvement of imaging and spectropolarimetric capabilities in the UV, visible, and near-infrared with respect to what is available today and foreseen in the near future. The Large European Module for solar Ultraviolet Research (LEMUR), described in this paper, is a large VUV telescope feeding a scientific payload of high-resolution imaging spectrographs and cameras. LEMUR consists of two major components: a VUV solar telescope with a 30 cm diameter mirror and a focal length of 3.6 m, and a focal-plane package composed of VUV spectrometers covering six carefully chosen wavelength ranges between 17 and 127 nm. The LEMUR slit covers 280 on the Sun with 0.14 per pixel sampling. In addition, LEMUR is capable of measuring mass flows velocities (line shifts) down to 2 km/s or better. LEMUR has been proposed to ESA as the European contribution to the Solar C mission.
This white paper describes the science case for Very Long Baseline Interferometry (VLBI) and provides suggestions towards upgrade paths for the European VLBI Network (EVN). The EVN is a distributed long-baseline radio interferometric array, that operates at the very forefront of astronomical research. Recent results, together with the new science possibilities outlined in this vision document, demonstrate the EVNs potential to generate new and exciting results that will transform our view of the cosmos. Together with e-MERLIN, the EVN provides a range of baseline lengths that permit unique studies of faint radio sources to be made over a wide range of spatial scales. The science cases are reviewed in six chapters that cover the following broad areas: cosmology, galaxy formation and evolution, innermost regions of active galactic nuclei, explosive phenomena and transients, stars and stellar masers in the Milky Way, celestial reference frames and space applications. The document concludes with identifying the synergies with other radio, as well as multi-band/multi-messenger instruments, and provide the recommendations for future improvements. The appendices briefly describe other radio VLBI arrays, the technological framework for EVN developments, and a selection of spectral lines of astrophysical interest below 100 GHz. The document includes a glossary for non-specialists, and a list of acronyms at the end.
Young nearby stars are good candidates in the search for planets with both radial velocity (RV) and direct imaging techniques. This, in turn, allows for the computation of the giant planet occurrence rates at all separations. The RV search around young stars is a challenge as they are generally faster rotators than older stars of similar spectral types and they exhibit signatures of magnetic activity (spots) or pulsation in their RV time series. Specific analyses are necessary to characterize, and possibly correct for, this activity. Our aim is to search for planets around young nearby stars and to estimate the giant planet (GP) occurrence rates for periods up to 1000 days. We used the HARPS spectrograph on the 3.6m telescope at La Silla Observatory to observe 89 A-M young (< 600 Myr) stars. We used our SAFIR (Spectroscopic data via Analysis of the Fourier Interspectrum Radial velocities ) software to compute the RV and other spectroscopic observables. Then, we computed the companion occurrence rates on this sample. We confirm the binary nature of HD177171, HD181321 and HD186704. We report the detection of a close low mass stellar companion for HIP36985. No planetary companion was detected. We obtain upper limits on the GP (< 13 MJup) and BD (13-80 MJup) occurrence rates based on 83 young stars for periods less than 1000 days, which are set, 2_-2^+3 % and 1_-1^+3 %.
We present a machine learning package for the classification of periodic variable stars. Our package is intended to be general: it can classify any single band optical light curve comprising at least a few tens of observations covering durations from weeks to years, with arbitrary time sampling. We use light curves of periodic variable stars taken from OGLE and EROS-2 to train the model. To make our classifier relatively survey-independent, it is trained on 16 features extracted from the light curves (e.g. period, skewness, Fourier amplitude ratio). The model classifies light curves into one of seven superclasses - Delta Scuti, RR Lyrae, Cepheid, Type II Cepheid, eclipsing binary, long-period variable, non-variable - as well as subclasses of these, such as ab, c, d, and e types for RR Lyraes. When trained to give only superclasses, our model achieves 0.98 for both recall and precision as measured on an independent validation dataset (on a scale of 0 to 1). When trained to give subclasses, it achieves 0.81 for both recall and precision. In order to assess classification performance of the subclass model, we applied it to the MACHO, LINEAR, and ASAS periodic variables, which gave recall/precision of 0.92/0.98, 0.89/0.96, and 0.84/0.88, respectively. We also applied the subclass model to Hipparcos periodic variable stars of many other variability types that do not exist in our training set, in order to examine how much those types degrade the classification performance of our target classes. In addition, we investigate how the performance varies with the number of data points and duration of observations. We find that recall and precision do not vary significantly if the number of data points is larger than 80 and the duration is more than a few weeks. The classifier software of the subclass model is available from the GitHub repository (https://goo.gl/xmFO6Q).
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