Research

For the full publication record, please view it on ADS, ORCID, or Google Scholar. 

Below are my main research projects. Feel free to contact me at yaguangli@hawaii.edu, if you are want to work with me or just fancy a chat.

How to obtain the best possible stellar properties (mass, radius, age)?

Improving scaling-relations based techniques

Testing the intrinsic scatter of the scaling relations. The intrinsic scatter of the scaling relations could cause seemingly random fluctuations in the measured stellar properties. We can show that the intrinsic scatter is a few per cent, ~1.7% for mass and ~0.4% for radius, which sets a fundamental floor for the precision. This project involved a novel approach: we used the sharp features that are naturally formed in the H-R diagram by the stellar populations (see Li et al. 2021 to know how we did this!). 

Testing the surface effect induced bias of the scaling relations. There are theoretically motivated corrections for the Dnu scaling relation, a relation that links Dnu to the stellar mean density. We showed that the previous corrections included a 2% systematic bias due to the surface effect, which was unaccounted for before. Our new correction suggests changes of up to 8% in mass and 4% in radius (Li et al. 2022). 

Developing stellar-model based techniques

The surface effect is a disparity between the observed and the modelled oscillation frequencies. It originates from improper modelling of the surface layers in stars with solar-like oscillations. Correcting the surface effect conventionally uses functions with free parameters, although they should vary smoothly across the H--R diagram. By parameterising the surface correction to relate with surface gravity, Teff, and [M/H], we used a novel approach of ensemble modelling to calibrate the stellar surface correction. We successfully reduced the scatter of the model-derived parameters, such as ages for each star in the same open cluster (Li et al. 2022). 

How to transfer our knowledge on stellar properties?

Post-mass-transfer red clump stars were discovered as anamolies in our precise characterisations of red clump stars. Most red giants that have partially transferred envelopes remain cool on the surface and are almost indistinguishable from those that have not. We discovered two classes of red clump stars that must have undergone dramatic mass loss, presumably due to binary stripping (Li et al. 2022). The first class contains underluminous stars with smaller helium-burning cores than their single-star counterparts. The second class consists of very low-mass stars, whose implied ages would exceed the age of the universe had no excessive mass loss occurred. 

There are more questions needed to be answered: do they host companions? What are their formation channels? Are they fast rotators? Are they structrually different compared to regular stars (could one tell from oscillation frequencies)?

Wide double-oscillating binaries are fantastic labs to test various stellar astrophysics by exploring the fact that the two stars are coeval and share the same initial chemistry. We have characterised a binary system with observed oscillations from both components (Li et al. 2018). We are in the search of more systems alike and hopefully we can have a curate a catalog to enable calibrations of uncertain stellar physics (especially the mixing length parameter and helium abundance).

Rotation and activity based age-dating methods for main-sequence dwarfs will unlock precise ages, which are crucial for the characterisation of exoplanet hosts. It is incredibly difficult to extract the ages of G-M dwarfs from isochrone fitting, because they barely move on the H-R diagram during their main-sequence lifetimes. However, many of them are exoplanet hosts. Knowing their ages is invaluable to studying the evolution of exoplanetary systems. Stellar rotation and activity hold the key to unlocking precise age determinations due to their sensitivity on age. We are in the work of using knowledge of known stellar properties to calibrate these relations.

How to determine the best possible oscillation properties?

Extraction of oscillation frequencies

Kepler subgiants: oscillation parameters (frequencies, amplitudes, damping rates) extracted for 36 subgiants - a perfect sample for subgiant modelling (Li et al. 2020).

Kepler red giants: oscillation frequencies of l=0 modes for 3642 red-giant-branch stars (Li et al. 2022).

Modelling oscillation signals in photometry and RV

Something I am interested in...