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Register a new userSearch for exoplanets with the radial-velocity technique: quantitative diagnostics of stellar activity
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Aims: Stellar activity may complicate the analysis of high-precision radial-velocity spectroscopic data when looking for exoplanets signatures. We aim at quantifying the impact of stellar spots on stars with various spectral types and rotational velocities and comparing the simulations with data obtained with the HARPS spectrograph. Methods: We have developed detailed simulations of stellar spots and estimated their effects on a number of observables commonly used in the analysis of radial-velocity data when looking for extrasolar planets, such as radial-velocity curves, cross-correlation functions, bisector spans and photometric curves. The computed stellar spectra are then analyzed in the same way as when searching for exoplanets. Results: 1) A first grid of simulation results is built for F-K type stars, with different stellar and spot properties. 2) It is shown quantitatively that star spots with typical sizes of 1% can mimic both radial-velocity curves and the bisector behavior of short-period giant planets around G-K type stars with a vsini lower than the spectrograph resolution. For stars with intermediate vsini, smaller spots may produce similar features. In these cases, additional observables (e.g., photometry, spectroscopic diagnostics) are mandatory to confirm the presence of short-period planets. We show that, in some cases, photometric variations may not be enough to clearly rule out spots as explanations of the observed radial-velocity variations. This is particularly important when searching for super-Earth planets. 3) It is also stressed that quantitative values obtained for radial-velocity and bisector span amplitudes depend strongly on the detailed star properties, on the spectrograph used, on the set of lines used, and on the way they are measured.
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Exoplanet detection with precise radial velocity (RV) observations is currently limited by spurious RV signals introduced by stellar activity. We show that machine learning techniques such as linear regression and neural networks can effectively remove the activity signals (due to starspots/faculae) from RV observations. Previous efforts focused on carefully filtering out activity signals in time using modeling techniques like Gaussian Process regression (e.g. Haywood et al. 2014). Instead, we systematically remove activity signals using only changes to the average shape of spectral lines, and no information about when the observations were collected. We trained our machine learning models on both simulated data (generated with the SOAP 2.0 software; Dumusque et al. 2014) and observations of the Sun from the HARPS-N Solar Telescope (Dumusque et al. 2015; Phillips et al. 2016; Collier Cameron et al. 2019). We find that these techniques can predict and remove stellar activity from both simulated data (improving RV scatter from 82 cm/s to 3 cm/s) and from more than 600 real observations taken nearly daily over three years with the HARPS-N Solar Telescope (improving the RV scatter from 1.47 m/s to 0.78 m/s, a factor of ~ 1.9 improvement). In the future, these or similar techniques could remove activity signals from observations of stars outside our solar system and eventually help detect habitable-zone Earth-mass exoplanets around Sun-like stars.
Planetary rotation rates and obliquities provide information regarding the history of planet formation, but have not yet been measured for evolved extrasolar planets. Here we investigate the theoretical and observational perspective of the Rossiter-McLauglin effect during secondary eclipse (RMse) ingress and egress for transiting exoplanets. Near secondary eclipse, when the planet passes behind the parent star, the star sequentially obscures light from the approaching and receding parts of the rotating planetary surface. The temporal block of light emerging from the approaching (blue-shifted) or receding (red-shifted) parts of the planet causes a temporal distortion in the planets spectral line profiles resulting in an anomaly in the planets radial velocity curve. We demonstrate that the shape and the ratio of the ingress-to-egress radial velocity amplitudes depends on the planetary rotational rate, axial tilt and impact factor (i.e. sky-projected planet spin-orbital alignment). In addition, line asymmetries originating from different layers in the atmosphere of the planet could provide information regarding zonal atmospheric winds and constraints on the hot spot shape for giant irradiated exoplanets. The effect is expected to be most-pronounced at near-infrared wavelengths, where the planet-to-star contrasts are large. We create synthetic near-infrared, high-dispersion spectroscopic data and demonstrate how the sky-projected spin axis orientation and equatorial velocity of the planet can be estimated. We conclude that the RMse effect could be a powerful method to measure exoplanet spins.
In order to study the state of gas in galaxies, diagrams of the relation of optical emission line fluxes are used allowing one to separate main ionization sources: young stars in the H II regions, active galactic nuclei, and shock waves. In the intermediate cases, when the contributions of radiation from OB stars and from shock waves mix, identification becomes uncertain, and the issue remains unresolved on what determines the observed state of the diffuse ionized gas (DIG) including the one on large distances from the galactic plane. Adding of an extra parameter - the gas line-of-sight velocity dispersion - to classical diagnostic diagrams helps to find a solution. In the present paper, we analyze the observed data for several nearby galaxies: for UGC 10043 with the galactic wind, for the star forming dwarf galaxies VII Zw 403 and Mrk 35, for the galaxy Arp 212 with a polar ring. The data on the velocity dispersion are obtained at the 6-m SAO RAS telescope with the Fabry-Perot scanning interferometer, the information on the relation of main emission-line fluxes - from the published results of the integral-field spectroscopy (the CALIFA survey and the MPFS spectrograph). A positive correlation between the radial velocity dispersion and the contribution of shock excitation to gas ionization are observed. In particular, in studying Arp 212, BPT-sigma relation allowed us to confirm the assumption on a direct collision of gaseous clouds on the inclined orbits with the main disk of the galaxy.
Long-term stellar activity variations can affect the detectability of long-period and Earth-analogue extrasolar planets. We have, for 54 stars, analysed the long-term trend of five activity indicators: log$R_mathrm{{HK}}$, the cross-correlation function (CCF) bisector span, CCF full-width-at-half-maximum, CCF contrast, and the area of the Gaussian fit to the CCF; and studied their correlation with the RVs. The sign of the correlations appears to vary as a function of stellar spectral type, and the transition in sign signals a noteworthy change in the stellar activity properties where earlier type stars appear more plage dominated. These transitions become more clearly defined when considered as a function of the convective zone depth. Therefore, it is the convective zone depth (which can be altered by stellar metallicity) that appears to be the underlying fundamental parameter driving the observed activity correlations. In addition, for most of the stars, we find that the RVs become increasingly red-shifted as activity levels increase, which can be explained by the increase in the suppression of convective blue-shift. However, we also find a minority of stars where the RVs become increasingly blue-shifted as activity levels increase. Finally, using the correlation found between activity indicators and RVs, we removed RV signals generated by long-term changes in stellar activity. We find that performing simple cleaning of such long-term signals enables improved planet detection at longer orbital periods.
We investigate the estimation of orbital parameters by least-$chi^2$ Keplerian fits to radial velocity (RV) data using synthetic data sets. We find that while the fitted period is fairly accurate, the best-fit eccentricity and $M_psin i$ are systematically biased upward from the true values for low signal-to-noise ratio $K/sigmalesssim 3$ and moderate number of observations $N_{rm obs}lesssim 60$, leading to a suppression of the number of nearly circular orbits. Assuming intrinsic distributions of orbital parameters, we generate a large number of mock RV data sets and study the selection effect on the eccentricity distribution. We find the overall detection efficiency only mildly decreases with eccentricity. This is because although high eccentricity orbits are more difficult to sample, they also have larger RV amplitudes for fixed planet mass and orbital semi-major axis. Thus the primary source of uncertainties in the eccentricity distribution comes from biases in Keplerian fits to detections with low-amplitude and/or small $N_{rm obs}$, rather than from selection effects. Our results suggest that the abundance of low-eccentricity exoplanets may be underestimated in the current sample and we urge caution in interpreting the eccentricity distributions of low-amplitude detections in future RV samples.
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