Stellar noise: physics and mechanisms Ignasi Ribas Institut de Ciències de l Espai (CSIC IEEC, Barcelona) Leiden, October 2012
Stellar signal: physics and mechanisms Ignasi Ribas Institut de Ciències de l Espai (CSIC IEEC, Barcelona) Leiden, October 2012
The star planet connection Our knowledge of planets is directly driven by our knowledge of the parent star By influencing our ability to detect and measure planets ( systematic errors!) In indirect methods, all we see is the starlight (activity, binarity/rotation) In direct methods, there can be challenges to detectability (zodiacal light, binarity) Planet properties (mass, radius) are relative to those of the star By determining the intrinsic properties of planets The star is the overwhelmingly larger source of energy The stellar radiations i affect the composition, ii thermal properties and the existence of planetary atmospheres
The Sun is not a quiet, homogeneous gas sphere Spots and faculae (plages) Flares (coronal Flares (coronal loops)
The Sun is not a quiet, homogeneous gas sphere Meridional circulation Acoustic oscillations Granulation
The Sun is not a quiet, homogeneous gas sphere - Minutes to hours: granulation, p-mode oscillations - Hours to days: magnetic field + super- granulation - Days to rotation period: modulation by spots (magnetic field) - Rotation period to activity cycle: active region evolution (magnetic field) - Centuries: magnetic field variability + cycles - 10 5 10 9 yr: stellar evolution
Variability patterns: oscillations Sun (GONG) Modesexcited excited tend to be of high degree (lots of nodes on the surface) Timescale: 4 7 min Amplitude: 20 30 cm s 1 Cen A (Bazot et al. 2007, A&A)
Variability patterns: oscillations Radial velocity amplitude: 10 60 cm s 1 (Kjeldsen & Bedding, 2011, A&A) Chaplin et al. (2009, A&A) 16.7 min 8.3 min 5.6 min 4.2 min 3.3 min Huber et al. (2011, ApJ) Chaplin et al. (2011, Science)
Variability patterns: granulation Frohlich h& Lean (2004, A&ARv) Supergranulation Mesogranulation Granulation
Variability patterns: active regions The Sun, and low mass stars in general, are magnetically active Magnetic dynamo theory Rotation and the convective outer envelope interact to generate magnetic fields
Variability patterns: active regions Measured Total Solar Irradiance (TSI) 0.1% f PMOD composite of TSI based on measurements from instruments in space
Irradiance Sunspots Long term light variations dominated by faculae: the Sun is brightest when the number of sunspots is largest
Variability patterns: active regions Eker et al. (2003, A&A) Center to limb variation of an active region: limb brightening of faculae Active regions evolve over time: grow and decay (even simultaneously!) l Typical lifetimes of ordinary active regions range from a few days to a few months
Variability patterns: active regions Ball et al. (2012, A&A) Model assumes that all irradiance variations on time scales > 1 day are due to changes in solar surface magnetism Input: B, f sp, f fac ; params: quiet Sun, spots (umbra/penumbra), faculae, network associated with emergent intensity = f(, ) Good performance, but still lack of data for SSI
Variability patterns: active regions Spots (dark/bright) on the surface distort the line profile and give rise to non dynamical radial velocity variations Convective blueshifts also present and vary with line strength! cores of strong lines form high (low vel.); cores of shallow lines form deep (high vel.) Meunier et al. (2010, A&A)
The solar stellar stellar connection It is assumed that stellar magnetic activity works in the same way as in our Sun Rotation time scale: roughly 50% of G stars are more variable ibl than Sun (Basri et al. 2010, 2011; McQuillan et al. 2012). Solar cycle time scale: Sun appears to be less variable than comparison stars (Lockwood et al. 1992, 2007; Radick et al. 1998; Radick 2011) More active stars than the Sun aredarker when More active stars than the Sun are darker when averaged over times of higher activity
The solar stellar stellar connection: not so easy Lockwood et al. (2007, ApJS) Berdyugina (2005, LRSP) Lots of unknowns (TBD): Relative faculae contribution Temperature contrast General surface distribution (latitude?) Lifetimes: polar cap spots seem to be very long lived (years!)
The solar stellar stellar connection: surface modeling dl Maximum entropy modeling using Kepler and CoRoT light curves with parametric fit (f, Q, P rot, ) Very strong degeneracies: size, contrast, facular contribution, See, e.g., Lanza et al. (2009, 2010, 2011, A&A) LHS 6343 A Kepler data and Maximum Entropy best fit (Herrero et al., 2012, A&A, submitted)
Variability patterns: flares Audard et al. (2000, A&A) Fuhrmeister et al. (2008, A&A) Duration: 10 100 min (250 min) Amplitude: Very large
Stellar activity as a challenge to discovering terrestrial planets Sun like stars Spot pattern variations (modulation, (dis)appearance) impact on astrometry and radial velocity Ast noise ~0.09 as RV noise ~0.38 m/s Makarov et al. (2009, ApJL) Sampling strategies can mitigate the noise Dumusque et al. (2011, A&A) Lagrange et al. (2010, A&A) Meunier et al. (2010, A&A)
M type stars Astrometric and RV jitter is even more of a concern for M type stars Long term (3 6 yr) magnetic cycles have been found to induce ~5 m s 1 RV variations (Gomes da Silva et al. 2012, A&A)
M type stars An option is to go into the NIR CARMENES project approach Amplitude of RV effect reduced by factor >1.5 But what is the temperature contrast spot photosphere? Reiners et al. (2010, ApJ) Barnes et al. (2010, MNRAS)
Activity diagnostics in RVs Boisse et al. (2011, A&A) Hor Queloz et al. (2009, A&A) CoRoT-7 Correlation of line bisector span with RVs Works only if surface is simple (i.e., 1 or few active regions) & fast rotators
Activity diagnostics in RVs HD 166435: Queloz et al. (2001, A&A) Correlation with activity indices and brightness monitoring GJ 674: Bonfils et al. (2007, A&A)
Stellar activity as a challenge to characterizing planets Differential effects within the NIR are of a few parts in 10 4, but significant in the visible CoRoT-2 Beaulieu et al. (2008, ApJ) Ballerini et al. (2011, A&A)
Conclusions Progress in the understanding of planets is directly linked to progress in the understanding of stars The star is more than a source of noise Variations can be characterized and modeled and, when necessary, strategies can be put in place to mitigate effects