Search

To date, over 5000 exoplanets have been confirmed, and studies of their characteristics have unveiled an extremely wide range of masses, sizes, system architectures, and orbital periods. More than two-thirds of these known planets were identified using dedicated planet detection algorithms that search for transit events in data obtained by space-based survey satellites, such as the Transiting Exoplanet Survey Satellite (TESS). These automated transit detection algorithms are, however, strongly biased towards the detection of short-period planets. For example, 90% of the pipeline-detected TESS planet candidates known to date have orbital periods shorter than 27 days. In this thesis, I show that we can address this period bias by visually inspecting TESS data with the help of a global community of over 30,000 volunteers. I present the Planet Hunters TESS (PHT) citizen science project that I designed, built, and continue to manage. Throughout this thesis I demonstrate that with visual vetting we are sensitive to detecting both short- and longer-period planets. This makes PHT an effective tool to help populate under-explored regions of parameter space that have limited prospects for being studied by automated searches that typically require a minimum of two transit events for detection. To that end, the PHT planet sample can benefit studies of planet occurrence rates, as well as inform theories of physical processes involved with the formation and evolution of different types of exoplanets. I also present LATTE; a new open-source vetting suite that includes numerous diagnostic tests to aid in the detection and characterisation of planetary and stellar signals. The tool, which is regularly used by both professional astronomers and citizen scientists, forms part of the PHT pipeline and helps identify promising candidates for ground-based follow-up. The large-scale visual vetting with PHT, combined with the LATTE vetting suite, has led to the discovery of 139 new planet candidates in the two-minute cadence data from the first three years of TESS data alone. In addition to discussing this ensemble sample of new planet candidates, I present a detailed analysis of two of these systems. First, I discuss a Saturn-sized planet orbiting around a bright subgiant on an ~84-day orbit. The planet's relatively long orbital period combined with the evolved nature of the host star places this planet in a relatively under explored region of parameter space and is, therefore, an exciting target for further characterisation. Second, I present a two-planet system orbiting around a bright G dwarf. Preliminary mass estimates derived from ground-based radial velocity observations, combined with detailed transit modelling, suggest that both planets in this second system have low bulk densities and therefore extended H/He atmospheres. This makes both planets prime candidates for future atmospheric characterisation and comparative planetology. Finally, I show that visual inspection of large amounts of data via PHT yields many scientifically valuable by-products, including the identification of 4584 eclipsing binary candidates and multi-stellar systems. I discuss one of these systems - a massive compact hierarchical triple star system - in more detail and present a dynamical analysis of its past, present, and future. Overall, this thesis demonstrates the scientific value of citizen science for identifying unique signals that are often missed by automated searches and, therefore, shows that people-powered planet hunting can play an important role in a world that is becoming increasingly automated.

A quarter century after the famous discovery of 51 Peg b, the radial velocity (RV) method remains a key exoplanet detection and characterisation method. For transiting planets, RVs allow us to measure mean densities and draw conclusions about the planets' compositions. This is particularly valuable for young planets, which are sensitive probes of formation and evolution models. Stellar activity is the main factor limiting RV searches for both young planets and small, temperate planets around older stars. In this thesis, I developed and tested novel approaches to extract RVs from spectra using Gaussian process (GP) regression. I then used a multi-dimensional GP framework to model the impact of stellar activity on those RVs and to disentangle activity-induced and planetary signals in the data from a year-long intensive RV monitoring campaign of the bright, young M-dwarf AU Mic using the HARPS spectrograph. This enabled me and my collaborators to measure the masses of two transiting planets, which have previously been discovered by the TESS satellite, finding Mb = 11.7±5.0 M⊕ and Mc = 22.2±6.7 M⊕. As both planets are similar in size to Neptune, their contrasting densities represent a challenge for current planet formation models, and warrant further investigation. Finally, I also present extensions to the standard Generalised Least-squares Periodogram (GLS), which attempt to account for stellar activity explicitly. I used these to search for additional planets in the AU Mic system using both archival and new HARPS data, excluding the presence of any additional planets with RV semi-amplitudes ≥ 50 ms−1 and periods 20 ≤ P ≤ 1000days.

Extrasolar planets (exoplanets) are planetary-mass objects that orbit different stars in our galaxy. To date, there have been over 4000 of these objects discovered, with a bias towards objects that transit their host star. This thesis focuses on interpreting the emission spectra of hot to ultra-hot Jupiter exoplanets. These are Jupiter-sized objects which orbit close to their host star, resulting in high effective temperatures and a tidally-locked orbital configuration. The study of the emission spectra of exoplanets lets us probe the vertical chemical and thermal structure of the planet's atmosphere. The majority of the current observations are of hot to ultra-hot Jupiter planets, as the day-side flux is readily measurable with current telescopes. Therefore the first part of the thesis focuses on upgrading the NEMESIS model to calculate H⁻ opacities and implementing a temperature-pressure parameterisation that can handle temperature profiles that can span the parameter space that contain non-inverted and inverted profiles. These objects exhibit large day-night contrasts due to their tidally-locked nature, and it has been shown that this is detectable with current observations. We explore in this thesis the biases that can arise when studying an exoplanet with a non homogeneous thermal structure. We find that if we assume the thermal structure to be uniform on the disc, this can lead to spurious detection of molecules. We show that by retrieving the nightside and the dayside of the planet simultaneous we can perform an unbiased retrieval. We find that if the nightside contribution is small enough, a simple dilution factor can be used to account for the spatial inhomogeneity of the atmosphere. Finally, we explore how scattering clouds can affect the way we interpret the emission spectra of cloudy exoplanets. We show that using a model that does not contain scattering to study the emission spectra of a cloudy exoplanet can lead to incorrectly inferred chemical abundances and also an erroneous detection of a thermal inversion. To provide a more agnostic approach to the modelling of clouds, in this thesis we have developed a novel technique to retrieve the cloud scattering properties, namely the single scattering albedo, which approximately encapsulates the real and imaginary refractive index spectra and the particle size of the cloud condensing species. This thesis has broader impacts on the exoplanet community. The tools developed for hot and large planets will ensure that when moving to study smaller and cooler objects in the future, we can trust that our techniques are well verified.

Brown dwarfs (BDs) are substellar mass objects with masses ≤80MJup, the hydrogenburning limit. Deuterium fusion occurs in objects with ≥13MJup, lasting only a very short period (4-50 Myrs). This means that brown dwarfs are constantly cooling over their lifetime, passing through temperature ranges equivalent to those of exoplanets and planets in the Solar System. This aging and cooling creates a spectral sequence (hottest to coolest: M, L, T, Y) as various molecules and condensates begin to form. The atmospheres created during this sequence are extremely similar to gas giant planets. As brown dwarfs are free-floating objects, it is possible to attain much higher resolution spectra than with exoplanets because we do not have to subtract out the light from the host star, and thus they provide the perfect testbed for atmospheric modelling of objects beyond our Solar System. The aim of this thesis is to characterise the coolest brown dwarf atmospheres, spectrally classified as Y dwarfs, and the associated change in their atmospheric structure and composition with decreasing temperature. In order to achieve this ultimate goal, a number of steps are taken. The first is the updating of the molecular and atomic data to include the latest line lists and pressure broadening parameters, which enables us to more accurately model BDs with our radiative transfer calculations. Along the way, we discuss the most effective method to calculate gaseous absorption, and illustrate the effects of using sub-optimal techniques. With the radiative transfer calculations optimised, we proceed to implement a new inverse method to our NEMESIS retrieval code: Nested Sampling. This algorithm employs state-of-the-art Bayesian statistics to fit spectra and derive probability distributions for each parameter of interest. We verify our new Bayesian method and radiative transfer code against two other codes from separate groups, and investigate the model dependency of parameters using realistic atmospheric models of exoplanets that may be probed by the James Webb Space Telescope. We discuss the model-dependency of each parameter in the context of changing signal-to-noise, finding that some retrieved parameters are more model-dependent than others. Finally, having updated and verified our code through the methods previously discussed, we apply it to a range of ultracool T and Y dwarf atmospheres. The retrieved probability distributions of each parameter representing the atmospheric structure and composition of the brown dwarfs are compared to one another to elucidate trends with decreasing temperature. For the coldest object that we analysed, we discovered a cloud that is consistent with a Na2S cloud, which is expected to form at these temperatures. This is the first Bayesian detection of such a feature on a Y dwarf. We also discuss the plausibility that this cloud may instead be a water cloud. The analysis of these objects and the work presented here helps elucidate the atmospheric structure and composition of the Y dwarf population. We hope that this work will assist not only in future analyses of Y dwarf atmospheres, but also more generally in any atmosphere within or beyond our Solar System.

Gyrochronology, which describes the empirical relationship among stellar mass, rotation period, and age, is a potentially powerful tool for determining the ages of stars, upon which the understanding of stellar evolutionary models hangs. Well-calibrated with open clusters up to the age of ~2.5 Gyr, predictions from gyrochronology are in conflict with asteroseismic observations of older stars, and the underlying physics are poorly understood. The solar-age, open cluster M67, recently observed by the NASA K2 mission, offers the opportunity to test both gyrochronology and more physically-motivated angular momentum evolution models. Here, we seek to gain insight into the angular momentum evolution of solar-age stars through the analysis of K2 data. Using our own pipeline, we extract and process K2 light curves that encompass the inner and outer portions of M67. We describe various rotation period detection methods, focusing on the Lomb-Scargle periodogram, autocorrelation function (ACF), and Gaussian processes (GPs), before presenting our own preliminary results. Observed scatter between colour and period, combined with disagreement from the first published sets of K2 M67 periods, prompted a comprehensive round of sinusoidal injection tests to probe our absolute detection limits with K2 data using two different light curve preparation pipelines. Finding low sensitivity for 25 d, 0.1% amplitude signals and lingering systematics on the order of 25 d and greater, we use a combination of the Lomb-Scargle, ACF, and GP methods to determine our 'final' M67 rotation periods from K2 data. We find agreement between tidal synchronization theory and observed rotation periods for our M67 binaries. While angular momentum evolution models may perform slightly better than gyrochronology, we cannot make any conclusive statements regarding the validity of either due to the inherent scatter and small sample size. Future work at refining detection methods is needed, along with complementary data from upcoming missions such as LSST and PLATO.

The discovery of exoplanets represents one of the greatest scientific revolutions in history, and exoplanetary science has rapidly become uniquely positioned to address profound questions about the origins of life, and about humanity's place (and future) in the cosmos. Since the discovery of the first exoplanet over two decades ago, the radial velocity (RV) method has been one of the most productive techniques for discovering new planets. It has also become indispensable for characterising exoplanets detected via other techniques, notably transit photometry. Unfortunately, signals intrinsic to stars themselves - especially magnetic activity signals - can induce RV variations that can drown out or even mimic planetary signals. Modelling and thus mitigating these signals is notoriously difficult, which represents a major obstacle to using next-generation instruments to detect lower mass planets, planets with longer periods, and planets around more magnetically-active stars. Enter Gaussian processes (GPs), which have a number of features that make them very well suited to the joint modelling of stochastic activity processes and dynamical (e.g. planetary) signals. In this thesis, I leverage GPs to enable the study of smaller planets around a wider variety of stars than has previously been possible. In particular, I develop a principled and sophisticated Bayesian framework, based on GPs, for modelling RV time series jointly with ancillary activity-sensitive proxies, thus allowing activity signals to be constrained and disentangled from genuine planetary signals. I show that my framework succeeds even in cases where existing techniques would fail to detect planets, e.g. the case of a weak planetary signal with period identical to its host star's rotation period. In a first application of the framework, I demonstrate that Alpha Centauri Bb - until 2016, thought to be the closest exoplanet to Earth, and also the lowest minimum-mass exoplanet around a Sun-like star - was, in fact, an astrophysical false positive. Next, I use the framework to re-characterise the well-studied Kepler-10 system, thereby resolving a mystery surrounding the mass of planet Kepler-10c. I also use the framework to help discover or characterise various exoplanets. Finally, the activity modelling framework aside, I also present in outline form a few promising applications of GPs in the context of modelling stellar signals and studying exoplanets, viz. GPs for (i) enhanced characterisation of stellar rotation; (ii) generating realistic synthetic observations, and modelling in a systematic way the effects of an observing window function; and (iii) ultra-precise extraction of RV shifts directly from observed spectra, without requiring template cross-correlation.

The discovery and characterization of extrasolar planets is a leading frontier of science, which is limited by our ability to extract real astrophysical signals masked by systematic noise. In this Thesis I develop techniques for self-calibration in optical astronomy, in both imaging and photometry, applicable both to observations from the ground and for space telescopes, and apply these to searching for exoplanets. Kernel phase interferometry is a method for improving high angular resolution astronomical imaging by cancelling out the effects of the turbulent atmosphere. I derive a generalization, kernel amplitude, to correct also for the effects of scintillation, or twinkling. I go on to demonstrate kernel phase for the first time from the ground using the Palomar Hale 200-Inch Telescope, as a test case for the extreme adaptive optics instruments SPHERE and GPI. The Kepler satellite and its successor, the K2 mission, have been crucial to our understanding both of exoplanets, and via asteroseismology, of stellar physics. The success of K2 depends on correcting for its unstable pointing. Using semi-parametric Bayesian statistical models to overcome this issue, I report the discovery of 145 new transiting planet candidates in data from Campaigns 5 and 6 of the K2 mission. Furthermore, with two novel techniques, 'smear' and 'halo' photometry, which dramatically extend the dynamic range of Kepler and K2, I recover light curves of bright stars that were previously too saturated to study, and definitively detect variability in the seven naked-eye stars in the Pleiades cluster. These new data analysis approaches enable the K2 and TESS space missions to discover planets transiting the nearest and brightest stars, which will be ideal targets for the coming era of exoplanet characterization.

Stellar ages will play a big role in the next generation of astronomy. Useful to exoplaneteers and galactic archaeologists alike, this relatively under-exploited stellar property is currently limited by the precision of dating techniques. The work presented in this thesis contributes incrementally to a greater understanding of rotation period decay in Main Sequence (MS) stars as a proxy for stellar age. Inferring stellar ages from rotation periods, 'gyrochronology', is the only dating method with the potential to provide ages for stars on the hundreds-of-thousands scale. Unfortunately however, it suffers from being poorly calibrated as the sample of cool, MS stars with precise ages is extremely sparse. Using light curves of spotted, rotating, MS, FGK stars with asteroseismic ages from the Kepler spacecraft, I attempted to recalibrate the relation between rotation period, colour and age. I demonstrate that the simple, 'straight line' gyrochronology relations used in the past are unable to explain the new asteroseismic sample. Questions are raised about the power of gyrochronology---does it accurately predict ages for old stars? To fully answer this question, it will be necessary to exploit new data from the K2 (the repurposed Kepler mission). K2 has observed (and is still observing) several open clusters and asteroseismic field stars which may provide new insight into stellar rotational evolution. Unfortunately, systematic features in K2 light curves produced by Kepler's reduced pointing precision inhibit the detection of astrophysical signals in the data. These systematic features can be removed by modelling and subtracting them from the time series, 'detrending', but this process can remove some signals and can even inject noise. For this reason I developed a method for detecting periodic signals in K2 light curves without detrending: the Systematics-Insensitive Periodogram (SIP). This method is particularly useful for red giant asteroseismology. Precise ages can be inferred for oscillating red giants using the SIP and will be useful for galactic archaeology and open cluster age inference. In the next chapter of this thesis I return to the problem of stellar rotation period inference. Current methods for rotation period inference can produce inaccurate, imprecise periods with poorly approximated uncertainties and often without uncertainties altogether. I present a new method for inferring precise, accurate, probabilistic rotation periods with accurate uncertainties using Gaussian processes. Although expensive to compute, this method is ideal for applying to individual targets. I hope to continue to develop this method and apply it to a large ensemble light curves from Kepler and other photometric surveys in the future. Star spots and acoustic (p-mode) oscillations are not the only mechanisms that produce variability in dwarfs and giants. A combination of asteroseismic pulsations and granulation on the stellar surface produces variability on short timescales. It has been shown that the amplitude of this short-term variability, called 'flicker' is strongly correlated with both surface gravity and stellar density (Bastien et al., 2013, Bastien et al., 2016, Kipping et al., 2014). However, there is substantial additional scatter in these relations that is not accounted for by the observational uncertainties. I provide a new calibration of these relations which models this level of additional, astrophysical variance using hierarchical probabilistic inference. In the final chapter of this thesis I explore rotation period recovery with the Large Synoptic Survey Telescope (LSST). With its ten year baseline, LSST light curves will be sensitive to long rotation periods which are characteristic of old and low-mass stars. If the rotation periods of such stars can be measured from LSST light curves, it may be possible to improve the gyrochronology relations. We find that LSST is most sensitive to rotation periods between 10 and 20 days. Its sensitivity falls at short periods due to the sparsity of its sampling and at longer periods due to the lower amplitudes of variability and smaller apparent magnitudes of slow rotators.

Stellar evolution models underpin much of astrophysics, yet they are severely under-constrained on the pre-main sequence. The masses, radii, temperatures and luminosities of detached double-lined eclipsing binaries (EBs) can be determined in a model-independent manner from the light and radial velocity curves of the system. When these reach a precision of a few percent or less, they provide one of the most powerful observational tests of stellar evolution theory. Furthermore, young binary star systems display significant photometric and spectroscopic variability over a range of timescales and wavelengths. EBs offer powerful test-beds for characterising such variability, as the stellar parameters and orbital geometry are known to high precision. This thesis presents the characterisation of EBs discovered by the CoRoT and Spitzer space missions in the ~3 Myr old NGC 2264 star forming region. A sample of EBs in a young open cluster such as this, constitutes a particularly strong test of stellar evolution models because the EBs share the same age and composition, yet span a wide range of masses. We present the discovery of CoRoT 223992193, a detached, double-lined eclipsing binary, which comprises two pre-main sequence M-dwarfs and shows evidence of a circumbinary disk. We develop innovative approaches, based on Gaussian process regression, to determine the fundamental stellar parameters. At the time of discovery this was only the ninth pre-main sequence eclipsing binary (PMS EB) with component masses below 1.5 M? and provides a useful test of stellar evolution models. CoRoT 223992193 is the first low-mass PMS EB to show evidence of a circumbinary disk and displays significant photometric and spectroscopic variability. The two stars are found to possess slightly different rotation periods: the primary is consistent with synchronisation while the secondary rotates slightly supersynchronously. The photometric and spectroscopic variations are consistent with the picture of two active stars possibly undergoing non-steady, low-level accretion; the system's very high inclination provides a new view of such variability. The techniques developed in characterising CoRoT223992193 are applied to the NGC2264 EB sample. These work well for near equal-mass systems and two main sequence EBs are solved. However, primarily due to the one-dimensional nature of the radial velocity determination, the majority of the sample remains unsolved; more powerful methods are presented and are suggested for further work. Four low-mass EBs show evidence for youth, with three of these displaying low-to-extreme brightness (and hence mass) ratios. No such PMS systems have been reported in the literature. Once complete the full NGC 2264 sample will form one of the most stringent tests of PMS stellar evolution models to date. Finally, we present a visual multiple containing three EBs spanning B-M spectral types. Two of these systems show evidence for youth and cluster membership; the third is more ambiguous. Further observations are required to confirm the nature of this multiple, but if all three EBs are constituent members, it would be the first triply-eclipsing multiple system discovered, and will provide a powerful test of star formation and stellar evolution models in dense cluster environments.

Precise measurements of transit lightcurves can be used to constrain the composition and structure of exoplanet atmospheres. Unfortunately, efforts to extract this information are usually hampered by the presence of correlated noise that is degenerate with the astrophysical signal of interest. A major theme of this thesis is the application of robust analysis methods to properly account for such degeneracies. In particular, I advocate the use of Bayesian inference for lightcurve fitting. For this study, the Bayesian framework is exploited by modelling lightcurves as Gaussian processes (GPs), which offer numerous advantages over traditional decorrelation methods. The main advantage is that GPs do not require a functional form to be specified for the poorly understood lightcurve systematics. Instead, the high-level properties of the signal covariance are parameterised, allowing complex correlations to be marginalised over relatively low-dimension parameter spaces. I use GP models to analyse transit and eclipse lightcurves for the hot Jupiters HD189733b, HD209458b, and HAT-P-32b. The work is spread over three separate projects. Firstly, I re-analyse the majority of the transits and eclipses that have been observed using the Spitzer Space Telescope Infrared Array Camera (IRAC) for HD189733b and HD20945b. The GP analyses generally produce uncertainties for inferred planet parameters that are factors of ~1-5 larger than those quoted in the literature. In a number of cases, I obtain results that are fundamentally different to those published previously, with significant implications for the understanding of the atmospheres. Secondly, I report an eclipse observation for HD189733b that was made using the Hubble Space Telescope (HST) Space Telescope Imaging Spectrograph (STIS) over the 290-570nm wavelength range. Geometric albedos of Ag=0.37+12_-13 and Ag=0.37+13_-12 are measured in the wavelength ranges 290-450nm and 450-570nm, respectively. This represents the first ever multi-wavelength eclipse measurement made for an exoplanet at visible wavelengths. The nonzero albedo in the 290-450nm wavelength channel provides evidence for scattering in the atmosphere, possibly by haze/clouds or H2 molecules. The relatively low albedo in the 450-570nm wavelength channel is interpreted as being due to absorption by the wings of the Na 589nm doublet. Thirdly, I present two transit observations for HAT-P-32b made using the Nordic Optical Telescope (NOT) Andalucia Faint Object Spectrograph (ALFOSC) in multi-object spectroscopy mode over the 414-702nm wavelength range. A joint GP model is fit to the two white lightcurves produced by integrating the spectra over the full wavelength range. Spectroscopic lightcurves are also generated by binning into 32nm-wide wavelength channels, and preliminary lightcurve analyses are performed. The extracted transmission spectrum shows some evidence for absorption features, but this interpretation is currently very tentative. Further refinements to the data reduction and lightcurve analysis are suggested, which will allow the transmission spectrum to be evaluated more definitively.

The recent space-based exoplanet transit searches, CoRoT and Kepler, have revolutionised the field of stellar variability. In this thesis I exploit the public Kepler data to characterise stellar variability, and study rotation periods. For the study of stellar variability it is a complicated but necessary process to remove instrumental systematics while maintaining intrinsic stellar signal. I was involved in the development of a new correction method for systematics, denoted ARC (Astrophysically Robust Correction). This method relies on the removal of a set of basis functions that are determined to be present in small amounts across many light curves. Using the first month of Kepler data, corrected with the ARC method, I studied the variability properties of main sequence stars as a function of fundamental stellar parameters. I find that the fraction of stars with variability greater than that of the Sun is 60%, and confirm the trend of increasing variability with decreasing effective temperatures. I show tentative evidence that the more active stars have lower proper motions and may be located closer to the galactic plane. I also investigate the frequency content of the variability, showing that there exist significant differences in the nature of variability between spectral types, with a trend towards longer periods at later spectral types. In order to exploit the full potential of the Kepler data for stellar rotation period measurement, I developed a novel method of period detection for use on star spot modulated light curves. Standard approaches to period detection are based on Fourier decomposition or least-squares fitting of sinusoidal models. However, typical stellar light curves are neither sinusoidal nor strictly periodic. Therefore, I developed an algorithm for period detection based on the autocorrelation function (ACF) of the light curve. Because the ACF measures only the degree of self-similarity of the light curve at a given time lag, the period remains detectable even when the amplitude and phase of the photometric modulation evolve significantly. I applied the ACF method for the sample of M-dwarfs observed during the first 10 months of the Kepler mission, and detected rotation periods in 1570, ranging from 0.37-69.7 days. The rotation period distribution is clearly bimodal, with peaks at ~19 and ~33 days, hinting at two distinct waves of star formation. These two peaks form two distinct sequences in period-temperature space, with the period decreasing with increasing temperature. In a natural continuation to this work I applied measured periods for 1000 stars in each of the F, G and K-dwarf sets observed by Kepler, and combined these with the M-dwarf results. The trend of increasing rotation period with increasing mass is clear throughout, as the observations fall along a wide by distinct sequence. Comparison to the rotational isochrones of Barnes (2007) show an overall agreement, although the dataset, which I believe is the largest set of rotation period measurements for main sequence stars, shows addition detail, not captured by the gyrochronology relations. This includes a dip in the rotation period distribution at ~0.6 M⊙ and a steep increase in period for the M-dwarfs. I also applied the ACF method to the Kepler exoplanet candidate host stars and used the results to search for evidence of tidal interaction between the star and planet. I show that for the majority of exoplanet host stars, spin-orbit interaction will not have affected the stellar rotation period, permitting the application of gyrochronology for age determination. A comparison of the host stars with a sample of field stars selected to match their temperature and magnitude distribution also indicates no significant difference in the period or amplitude distributions of the two sets. The only notable variation is the lack of planets around the very fast rotators across all spectral types.

The combined observations of a planet’s transits and the radial velocity variations of its host star allow the determination of the planet’s orbital parameters, and most inter- estingly of its radius and mass, and hence its mean density. Observed densities provide important constraints to planet structure and evolution models. The uncertainties on the parameters of large exoplanets mainly arise from those on stellar masses and radii. For small exoplanets, the treatment of stellar variability limits the accuracy on the de- rived parameters. The goal of this PhD thesis was to reduce these sources of uncertainty by developing new techniques for stellar variability filtering and for the determination of stellar temperatures, and by robustly fitting the transits taking into account external constraints on the planet’s host star. To this end, I developed the Iterative Reconstruction Filter (IRF), a new post-detection stellar variability filter. By exploiting the prior knowledge of the planet’s orbital period, it simultaneously estimates the transit signal and the stellar variability signal, using a com- bination of moving average and median filters. The IRF was tested on simulated CoRoT light curves, where it significantly improved the estimate of the transit signal, particu- lary in the case of light curves with strong stellar variability. It was then applied to the light curves of the first seven planets discovered by CoRoT, a space mission designed to search for planetary transits, to obtain refined estimates of their parameters. As the IRF preserves all signal at the planet’s orbital period, t can also be used to search for secondary eclipses and orbital phase variations for the most promising cases. This en- abled the detection of the secondary eclipses of CoRoT-1b and CoRoT-2b in the white (300–1000 nm) CoRoT bandpass, as well as a marginal detection of CoRoT-1b’s orbital phase variations. The wide optical bandpass of CoRoT limits the distinction between thermal emission and reflected light contributions to the secondary eclipse. I developed a method to derive precise stellar relative temperatures using equiv- alent width ratios and applied it to the host stars of the first eight CoRoT planets. For stars with temperature within the calibrated range, the derived temperatures are con- sistent with the literature, but have smaller formal uncertainties. I then used a Markov Chain Monte Carlo technique to explore the correlations between planet parameters derived from transits, and the impact of external constraints (e.g. the spectroscopically derived stellar temperature, which is linked to the stellar density). Globally, this PhD thesis highlights, and in part addresses, the complexity of perform- ing detailed characterisation of transit light curves. Many low amplitude effects must be taken into account: residual stellar activity and systematics, stellar limb darkening, and the interplay of all available constraints on transit fitting. Several promising areas for further improvements and applications were identified. Current and future high precision photometry missions will discover increasing numbers of small planets around relatively active stars, and the IRF is expected to be useful in characterising them.