Related papers: Starspot mapping with adaptive parallel tempering …
Variability in the light curves of spotted, rotating stars is often non-sinusoidal and quasi-periodic --- spots move on the stellar surface and have finite lifetimes, causing stellar flux variations to slowly shift in phase. A strictly…
In this work the latitude dependent stellar spot rotation is investigated based on dynamo models. The maps of the magnetic pressure at the surface from the dynamo calculations are treated similarly to the temperature maps obtained using…
Deconvolution is the most widely used aberration correction technique in microscopy, however most techniques assume that the aberrations are the same for each point in the image, which is rarely true. Methods for tracking spatially varying…
We present a fast algorithm to produce light curves of distant stars undergoing microlensing near critical curves. The need of these type of algorithms is motivated by recent observations of microlensing events of distant stars at high…
An adaptive algorithm for spectral proper orthogonal decomposition (SPOD) of mixed broadband-tonal turbulent flows is developed. Sharp peak resolution at tonal frequencies is achieved by locally minimizing the bias of the spectrum. Smooth…
To enhance the efficiency, scalability, and cross-survey applicability of stellar parameter inference in large spectroscopic datasets, we present a modular, parallelized Python framework with automated error estimation, built on the LAMOST…
Sunspots are dark spots on the solar surface associated with strong magnetic fields. The number, area, and brightness of sunspots are supposed to reflect the intensity of the solar magnetic fields and are often used as proxies for their…
This paper proposes a novel feature called spectrum congruency for describing edges in images. The spectrum congruency is a generalization of the phase congruency, which depicts how much each Fourier components of the image are congruent in…
Density perturbations at the decoupling epoch produce angular fluctuations in the temperature of the Cosmic Microwave Background (CMB) radiation that may appear as hot and cold spots. Observational data of the CMB includes instrumental…
Mapper algorithm can be used to build graph-based representations of high-dimensional data capturing structurally interesting features such as loops, flares or clusters. The graph can be further annotated with additional colouring of…
1D stellar evolution codes employ rudimentary treatments of turbulent convection. For stars with convective envelopes, this leads to systematic errors in the predicted oscillation frequencies needed for asteroseismology. One way of mending…
In this work we present the solution of the stellar spot problem using the Kelvin-Stokes theorem. Our result is applicable for any given location and dimension of the spots on the stellar surface. We present explicitely the result up to the…
Detached eclipsing binary stars (dEBs) are a key source of data on fundamental stellar parameters. Within the light curve databases of survey missions such as Kepler and TESS are a wealth of new systems awaiting characterisation. We aim to…
Variable-intensity astronomical sources are the result of complex and often extreme physical processes. Abrupt changes in source intensity are typically accompanied by equally sudden spectral shifts, i.e., sudden changes in the wavelength…
Fitting model spectral energy distributions (SED) to galaxy photometric data is a widely used method to recover galaxy parameters from galaxy surveys. However, the parameter space used to describe galaxies is wide and interdependent, and…
We present a promising approach to the extremely fast sensing and correction of small wavefront errors in adaptive optics systems. As our algorithm's computational complexity is roughly proportional to the number of actuators, it is…
Convective overshoot mixing is a critical ingredient of stellar structure models, but is treated in most cases by ad hoc extensions of the mixing-length theory for convection. Advanced theories which are both more physical and numerically…
We present a machine learning method to assign stellar parameters (temperature, surface gravity, metallicity) to the photometric data of large photometric surveys such as SDSS and SKYMAPPER. The method makes use of our previous effort in…
Recent developments in computational power and machine learning techniques motivate their use in many different astrophysical research areas. Consequently, many machine learning models have been trained to classify exoplanet transit signals…
Context. There exist few variability studies of stars in the region in the Hertzsprung-Russell diagram between the A and B-star pulsational instability strips. With the aid of the high precision continuous measurements of the CoRoT space…