Extracting information from stochastic fields is a ubiquitous task in science. However, from cosmology to biology, it tends to be done either through correlation analyses, which is often too limited to capture the full complexity, or through the use of neural nets, which require large training sets and lack interpretability. I will present a new approach that borrows ideas from both extremes ...
Gravitational waves (GWs) from binary neutron stars (BNSs) offer valuable understanding of the nature of compact objects and hadronic matter. However, the analyses accompanied require massive computational power due to the difficulties in Bayesian stochastic sampling. The third-generation (3G) GW detectors are expected to detect BNS signals with significantly extended signal duration, detection...
The field of asteroseismology has grown explosively in the past two decades. It has evolved from bespoke examination of individual variable stars, to now having become both our main means of constraining stellar properties at large scale, and our sole observational probe into the astrophysics of their interiors. I will lay out recent developments of its observational methods and discoveries, pa...
The first two-year results of JWST have unveiled an unexpectedly large number of accreting black holes in the early Universe. Unlike the general populations of super massive black holes at the low redshifts, these early black holes exhibit distinctly different properties. They appear over-massive compared to the stellar content of their host galaxies, generally show non-detection in the hard X-...
Extinction correction is crucial for understanding the intrinsic properties of celestial objects within and beyond the Milky Way, especially with Gaia’s photometric precision reaching millimagnitude levels. Leveraging millions of high-quality spectra and precise atmospheric parameters from LAMOST, we have achieved unprecedented accuracy in extinction measurements. Using the “star-pair” techn...