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Register a new userCatalog of averaged magnetic phase curves of stars
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The second version of the catalog contains information about 275 stars of different types. During the time that has elapsed since the creation of the first catalog, situation fundamentally changed primarily due to the significant increase of accuracy of magnetic fields (MF) measurements. Up to now global magnetic field were discoverd and measured in stars of many types and their behavior partially was studied. Magnetic behavior of Ap Bp stars is the most thoroughly studied. The catalog contains information about 182 such objects. The main goals for the construction of the catalog are: 1. Review and summarize our kowledge about magnetic behavior of different types of stars. 2. The whole data are uniformly presented and processed which will allow one to perform statistical analysis of the variability of the (longitudinal) magnetic fields of stars. 3. The informations are presented in the most convenient form for testing different theoretical models of different kind. 4. The catalog will be useful for the development of observational programs.
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Magnetized stars exhibit periodic variations of their longitudinal global magnetic fields, $B_e$, owing to rotation. Here, we present the second catalog of averaged stellar magnetic rotational phase curves and their parameters derived from a compilation of the published observational data and personal communications for 350 stars of various spectral types, which were published up to the end of December 2019. Magnetic Ap and Bp stars constitute the most numerous subset in the catalog (215 objects). Phase curves were obtained by fitting either a sinusoid or a double sine wave to series of the observed $B_e$ measurements using the least squares method. For some stars, we present magnetic phase curves derived from time series of the surface magnetic field, $B_s$, or obtained improved values of the rotational period, $P_{rm rot}$. We have also identified eight stars in our catalog that host planets or planetary systems.
The number of known variable stars has increased by several magnitudes over the last decade, and automated classification routines are becoming increasingly important to cope with this development. Here we show that the upside-down CBH variables, which were proposed as a potentially new class of variable stars by Heinze et al. (2018) in the ATLAS First Catalogue of Variable Stars, are, at least to a high percentage, made up of alpha2 Canum Venaticorum (ACV) variables - that is, photometrically variable magnetic chemically peculiar (CP2/He-peculiar) stars - with distinct double-wave light curves. Using suitable selection criteria, we identified 264 candidate ACV variables in the ATLAS variable star catalogue. 62 of these objects were spectroscopically confirmed with spectra from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (all new discoveries except for nine stars) and classified on the MK system. The other 202 stars are here presented as ACV star candidates that require spectroscopic confirmation. The vast majority of our sample of stars are main-sequence objects. Derived masses range from 1.4M(Sun) to 5M(Sun), with half our sample stars being situated in the range from 2 M(Sun) to 2.4 M(Sun), in good agreement with the spectral classifications. Most stars belong to the thin or thick disk; four objects, however, classify as members of the halo population. With a peak magnitude distribution at around 14th magnitude, the here presented stars are situated at the faint end of the known Galactic mCP star population. Our study highlights the need to consider rare variability classes, like ACV variables, in automated classification routines.
We present a catalog of 93 very-well-observed nova light curves. The light curves were constructed from 229,796 individual measured magnitudes, with the median coverage extending to 8.0 mag below peak and 26% of the light curves following the eruption all the way to quiescence. Our time-binned light curves are presented in figures and as complete tabulations. We also calculate and tabulate many properties about the light curves, including peak magnitudes and dates, times to decline by 2, 3, 6, and 9 magnitudes from maximum, the time until the brightness returns to quiescence, the quiescent magnitude, power law indices of the decline rates throughout the eruption, the break times in this decline, plus many more properties specific to each nova class. We present a classification system for nova light curves based on the shape and the time to decline by 3 magnitudes from peak (t3). The designations are S for smooth light curves (38% of the novae), P for plateaus (21%), D for dust dips (18%), C for cusp-shaped secondary maxima (1%), O for quasi-sinusoidal oscillations superposed on an otherwise smooth decline (4%), F for flat-topped light curves (2%), and J for jitters or flares superposed on the decline (16%). Our classification consists of this single letter followed by the t3 value in parentheses; so for example V1500 Cyg is S(4), GK Per is O(13), DQ Her is D(100), and U Sco is P(3).
The increasing number of transiting exoplanets sparked a significant interest in discovering their moons. Most of the methods in the literature utilize timing analysis of the raw light curves. Here we propose a new approach for the direct detection of a moon in the transit light curves via the so called Scatter Peak. The essence of the method is the valuation of the local scatter in the folded light curves of many transits. We test the ability of this method with different simulations: Kepler short cadence, Kepler long cadence, ground-based millimagnitude photometry with 3-min cadence, and the expected data quality of the planned ESA mission of PLATO. The method requires ~100 transit observations, therefore applicable for moons of 10-20 day period planets, assuming 3-4-5 year long observing campaigns with space observatories. The success rate for finding a 1 R_Earth moon around a 1 R_Jupiter exoplanet turned out to be quite promising even for the simulated ground-based observations, while the detection limit of the expected PLATO data is around 0.4 R_Earth. We give practical suggestions for observations and data reduction to improve the chance of such a detection: (i) transit observations must include out-of-transit phases before and after a transit, spanning at least the same duration as the transit itself; (ii) any trend filtering must be done in such a way that the preceding and following out-of-transit phases remain unaffected.
We are using computer models to explore the observational sensitivity to changes in atmospheric and surface properties, and the detectability of biosignatures, in the globally averaged spectra and light-curves of the Earth. Using AIRS (Atmospheric Infrared Sounder) data, as input for atmospheric and surface properties, we have generated spatially resolved high-resolution synthetic spectra using the SMART radiative transfer model, for a variety of conditions, from the UV to the far-IR (beyond the range of current Earth-based satellite data). We have then averaged over the visible disk for a number of different viewing geometries to quantify the sensitivity to surface types and atmospheric features as a function of viewing geometry, and spatial and spectral resolution. These results have been processed with an instrument simulator to improve our understanding of the detectable characteristics of Earth-like planets as viewed by the first generation extrasolar terrestrial planet detection and characterization missions (Terrestrial Planet Finder/Darwin and Life finder). The wavelength range of our results are modelled over are applicable to both the proposed visible coronograph and mid-infrared interferometer TPF architectures. We have validated this model against disk-averaged observations by the Mars Global Surveyor Thermal Emission Spectrometer (MGS TES). This model was also used to analyze Earth-shine data for detectability of planetary characteristics and biosignatures in disk-averaged spectra.
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