Overview
The search for life on other worlds has long been a human curiosity and is now becoming a tangible aspiration. Space-based surveys, such as CoRoT and Kepler, seek to find Earth-sized planets by measuring the minuscule dip in brightness as the planet transits its host star. The Kepler mission alone has identified thousands of planetary candidates, several of which lie within the habitable zone. By measuring the velocity of the reflex motion of the host star caused by the orbiting planet, i.e the Doppler/Radial Velocity (RV) shift, one can determine the planetary mass and therefore confirm the planetary nature. Coupled with the radius determined from the transit depth, this also enables estimates of the likely planet composition.
Unfortunately, variability arising from the host star itself (so-called “astrophysical noise" or "stellar jitter”) due to spots, faculae, granulation and stellar oscillations etc. can easily drown out the signal from an Earth-like planet. These phenomena alter the shape of the stellar spectral lines, thereby changing the lines' centre of mass and injecting spurious velocity-shifts that may mask or mimic planetary signals. An example of this is shown on the right, where we see that the dark spot has created an emission 'bump' in the observed line profile. For reference, the Doppler wobble of the Earth around our Sun is a mere 9cm/s, whereas stellar "noise" may range from 10s of cm/s to 100s of m/s (Saar & Donahue, 1997).
Furthermore, today's state-of-the-art instruments promise a precision of 10 cm/s (e.g. ESPRESSO), meaning stellar variability will set the fundamental limit on the confirmation and characterisation of low-mass exoplanets.
Unfortunately, variability arising from the host star itself (so-called “astrophysical noise" or "stellar jitter”) due to spots, faculae, granulation and stellar oscillations etc. can easily drown out the signal from an Earth-like planet. These phenomena alter the shape of the stellar spectral lines, thereby changing the lines' centre of mass and injecting spurious velocity-shifts that may mask or mimic planetary signals. An example of this is shown on the right, where we see that the dark spot has created an emission 'bump' in the observed line profile. For reference, the Doppler wobble of the Earth around our Sun is a mere 9cm/s, whereas stellar "noise" may range from 10s of cm/s to 100s of m/s (Saar & Donahue, 1997).
Furthermore, today's state-of-the-art instruments promise a precision of 10 cm/s (e.g. ESPRESSO), meaning stellar variability will set the fundamental limit on the confirmation and characterisation of low-mass exoplanets.
My interests lies with magnetically "quiet" solar-type stars, as these make the most ideal planet hosts in terms of both planet confirmation and potential habitability, as they lack starspots and flares (Cegla 2019). In particular, I focus on magnetoconvection, i.e. stellar surface granulation. Granular noise originates from asymmetries in the stellar absorption lines produced by bright bubbles of hot plasma (granules) rising to the surface, cooling and falling back into intergranular lanes (shown left). These plasma flows induce km/s Doppler shifts that average to 10s of cm/s over the stellar surface due to the large number of granules. However, solar observations suggest granules tend to appear and disappear in the same locations, thereby making the noise correlated and also difficult to average out further.
Furthermore, the net convective velocity shift varies from the centre to the limb of the star (>100s of m/s for a G dwarf) due to line-of-sight changes (see figure above) and can impact the Rossiter-McLaughlin (RM) effect: when a planet traverses the host star it obscures different regions and line-of-sight velocities, resulting in net radial velocity variations (shown right). The shape of these variations can indicate the projected alignment between the planet’s orbital plane and the stellar spin axis as the primary velocities obscured are due to rotation. In turn, the spin-orbit alignment (i.e. obliquity) helps distinguish between different planetary migration mechanisms and provides insight into planetary formation/evolution theories. Therefore ignoring granulation velocity contributions may bias and/or skew exoplanetary science at a very fundamental level (Cegla et al. 2016a). Hence, the lack of a satisfactory and efficient approach to dealing with granulation poses severe issues to the discovery of the first habitable exoplanets, as well as our understanding of star and planet formation/evolution.
As such, I'm working to answer two key questions critical to exoplanet science: First, how do we disentangle the granulation signature from the Doppler wobble of planetary companions to enable the confirmation of habitable Earth-like worlds? Second, what is the impact of granulation on the RM effect and subsequent obliquity measurements?
As such, I'm working to answer two key questions critical to exoplanet science: First, how do we disentangle the granulation signature from the Doppler wobble of planetary companions to enable the confirmation of habitable Earth-like worlds? Second, what is the impact of granulation on the RM effect and subsequent obliquity measurements?
Disentangling Planetary and Stellar Signatures
I am studying stellar surface magnetoconvection (as a source of astrophysical noise) through the use of sophisticated 3D magnetohydrodynamic (MHD) simulations coupled with 1D radiative transport to synthesise spectral absorption line profiles. From these simulations, we have established a multi-component parameterisation of stellar surface granulation that allows me to produce line profiles with asymmetries and velocity shifts representative of those induced by photospheric convective motions (Cegla et al. 2013, 2018). In turn, we use these models to simulate convection and generate numerous artificial ‘noisy’ stellar surfaces (shown right). From these we can study a number of stellar line characteristics to discern which diagnostics are best suited to capture granulation-induced variations. Thus far, we have found several line characteristics are correlated with the granulation induced velocity shifts. Particularly high correlations were found using the bisector curvature (a measure of the line asymmetry) and brightness variation. Current results indicate significant granulation noise reduction (up to 50%) may be possible (Cegla et al. 2019).
Time series from a 3D magnetohydrodynamical simulation (produced using the MURaM code) of the solar surface at disc centre (i.e. centre-to-limb angle of 0 degrees, snapshot model number indicated in brackets).
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A single snapshot (i.e. single moment in time) from a 3D magnetohydrodynamical simulation (produced using the MURaM code) of solar surface magnetoconvection from disc centre to limb.
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Impact of the Stellar Surface on the RM Effect and Star-Planet Alignment
To explore the impact of granulation on RM observations, we have 'reloaded' the RM technique to spatially resolve stellar surfaces (Cegla et al 2016b). This is done by subtracting in-transit from out-of-transit observations; by doing so we isolate the starlight from the region behind the planet (see left).
As the planet traverses the star, we sample the local photosphere at multiple centre-to-limb angles (see below). The true 3D spin-orbit geometry of the system can then be determined by fitting for the latitude-dependent differential stellar rotation component in the local radial velocities – removing sky-projection ambiguities. Hence, we can not only probe star-planet alignments to new levels, but we can also use these spatially resolved patches to validate 3D simulations.
As the planet traverses the star, we sample the local photosphere at multiple centre-to-limb angles (see below). The true 3D spin-orbit geometry of the system can then be determined by fitting for the latitude-dependent differential stellar rotation component in the local radial velocities – removing sky-projection ambiguities. Hence, we can not only probe star-planet alignments to new levels, but we can also use these spatially resolved patches to validate 3D simulations.