Developing Tools For Probing Stellar Interiors With Asteroseismology

Asteroseismology is the study of stellar oscillations. Recent space missions, such as CoRoT, Kepler, and TESS, are rapidly revolutionising the field by collecting vast amounts of data. These data have enabled accurate characterisation of stellar oscillations for a wide range of stars, leading to improved understanding of stellar physics and knowledge of Galactic and planetary populations. This thesis builds on existing tools and develops new techniques to advance our understanding of stars using their oscillations. Firstly, we investigate 36 subgiants observed by Kepler, measuring their oscillation parameters and extracting their frequencies, amplitudes and linewidths. They are used as modelling input to derive accurate stellar parameters. Secondly, we measure the core and envelope rotation rates for these subgiants, and study them as a function of stellar properties. We find near solid-body rotation in early subgiants and differential rotation in later stages. Thirdly, we evaluate the intrinsic scatter of the asteroseismic scaling relations, using the sharpness of population-level features that are naturally formed by stars. We constrain the intrinsic scatter to be a few percent. Fourthly, we propose a new method to correct the stellar surface effect, which involves prescribing the surface effect as a function of stellar surface parameters. This method reduces the scatter of model-derived stellar properties and provides a revised correction for the Dnu scaling relation. Fifthly, we test the numax scaling relation by comparing observed numax with model-inferred scaling numax constrained by individual frequencies. We conclude no noticeable deviation of the numax scaling relation and a lack of metallicity dependency. Lastly, we construct a mass-radius diagram for red clump stars, leading to the discovery of two new types of post-mass-transfer stars. The new finding offers exciting opportunities to study binary evolution using asteroseismology

Sparse Reconstruction of Compressive Sensing Magnetic Resonance Imagery using a Cross Domain Stochastic Fully Connected Conditional Random Field Framework

Prostate cancer is a major health care concern in our society. Early detection of prostate cancer is crucial in the successful treatment of the disease. Many current methods used in detecting prostate cancer can either be inconsistent or invasive and discomforting to the patient. Magnetic resonance imaging (MRI) has demonstrated its ability as a non-invasive and non-ionizing medical imaging modality with a lengthy acquisition time that can be used for the early diagnosis of cancer. Speeding up the MRI acquisition process can greatly increase the number of early detections for prostate cancer diagnosis. Compressive sensing has exhibited the ability to reduce the imaging time for MRI by sampling a sparse yet sufficient set of measurements. Compressive sensing strategies are usually accompanied by strong reconstruction algorithms. This work presents a comprehensive framework for a cross-domain stochastically fully connected conditional random field (CD-SFCRF) reconstruction approach to facilitate compressive sensing MRI. This approach takes into account original k-space measurements made by the MRI machine with neighborhood and spatial consistencies of the image in the spatial domain. This approach facilitates the difference in domain between MRI measurements made in the k-space, and the reconstruction results in spatial domain. An adaptive extension of the CD-SFCRF approach that takes into account regions of interest in the image and changes the CD-SFCRF neighborhood connectivity based on importance is presented and tested as well. Finally, a compensated CD-SFCRF approach that takes into account MRI machine imaging apparatus properties to correct for degradations and aberrations from the image acquisition process is presented and tested. Clinical MRI data were collected from twenty patients with ground truth data examined and con firmed by an expert radiologist with multiple years of prostate cancer diagnosis experience. Compressive sensing simulations were performed and the reconstruction results show the CD-SFCRF and extension frameworks having noticeable improvements over state of the art methods. Tissue structure and image details are well preserved while sparse sampling artifacts were reduced and eliminated. Future work on this framework include extending the current work in multiple ways. Extensions including integration into computer aided diagnosis applications as well as improving on the compressive sensing strategy

Asteroseismic Modeling of 1,153 Kepler Red Giant Branch Stars: Improved Stellar Parameters with Gravity-Mode Period Spacings and Luminosity Constraints

This paper reports estimated stellar parameters of 1,153 Kepler red giant branch stars determined with asteroseismic modeling. We use radial-mode oscillation frequencies, gravity-mode period spacings, Gaia luminosities, and spectroscopic data to characterize these stars. Compared with previous studies, we find that the two additional observed constraints, i.e., the gravity-mode period spacing and luminosity, significantly improve the precision of fundamental stellar parameters. The typical uncertainties are 2.9% for the mass, 11% for the age, 1.0% for the radius, 0.0039 dex for the surface gravity, and 0.5\% for the helium core mass, making this the best-characterized large sample of red-giant stars available to date. With better characterizations for these red giants, we recalibrate the seismic scaling relations and study the surface term on the red-giant branch. We confirm that the surface term depends on the surface gravity and effective temperature, but there is no significant correlation with metallicity.Comment: Accepted by Ap

Solar-type Stars Observed by LAMOST and Kepler

Obtaining measurements of chromospheric and photometric activity of stars with near-solar fundamental parameters and rotation periods is important for a better understanding of solar-stellar connection. We select a sample of 2603 stars with near-solar fundamental parameters from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST)-Kepler field and use LAMOST spectra to measure their chromospheric activity and Kepler light curves to measure their photospheric activity (i.e., the amplitude of the photometric variability). While the rotation periods of 1556 of these stars could not be measured due to the low amplitude of the photometric variability and highly irregular temporal profile of light curves, 254 stars were further identified as having near-solar rotation periods. We show that stars with near-solar rotation periods have chromospheric activities that are systematically higher than stars with undetected rotation periods. Furthermore, while the solar level of photospheric and chromospheric activity appears to be typical for stars with undetected rotation periods, the Sun appears to be less active than most stars with near-solar rotation periods (both in terms of photospheric and chromospheric activity).Comment: 7 pages, 6 figure