Blog
Towards understanding stellar variability at the sub m/s level: Isolating granulation signals in synthetic spectral lines
Granulation in the photospheres of FGK-type stars induces variability in absorption lines, complicating exoplanet detection via radial velocities and characterisation via transmission spectroscopy. We aim to quantify the impact of granulation on the radial velocity and bisector asymmetry of stellar absorption lines...
Universal Methods for Nonlinear Spectral Problems
Nonlinear spectral problems arise across a range of fields, including mechanical vibrations, fluid-solid interactions, and photonic crystals. Discretizing infinite-dimensional nonlinear spectral problems often introduces significant computational challenges, particularly spectral pollution and invisibility, which can distort or obscure the true underlying spectrum. We...
Black hole-accretion disk collision in general relativity: Axisymmetric simulations
Motivated by recent discoveries of X-ray quasi-periodic eruptions, we revisit the collision of a black hole and an accretion disk. Assuming that they are orbiting a supermassive black hole in orthogonal orbits, we perform a general relativistic simulation of the collision, varying...
Ringdown mode amplitudes of precessing binary black holes
The ringdown phase of a binary black-hole merger encodes key information about the remnant properties and provides a direct probe of the strong-field regime of General Relativity. While quasi-normal mode frequencies and damping times are well understood within black-hole perturbation theory, their...
Molecular Communication Channel as a Physical Reservoir Computer
Molecular Communication (MC) channels inherently possess significant memory and nonlinear dynamics due to diffusion and receptor kinetics, often posing challenges for reliable data transmission. This work reconceptualizes these intrinsic properties as computational resources by framing a canonical point-to-point MC channel, consisting of...
An Exact SIR Series Solution and an Exploration of the Related Parameter Space
A convergent power series solution is obtained for the SIR model, using an asymptotically motivated gauge function. For certain choices of model parameter values, the series converges over the full physical domain (d.h., for all positive time). Außerdem, the radius of convergence...
Democracy of AI Numerical Weather Models: An Example of Global Forecasting with FourCastNetv2 Made by a University Research Lab Using GPU
This paper demonstrates the feasibility of democratizing AI-driven global weather forecasting models among university research groups by leveraging Graphics Processing Units (GPUs) and freely available AI models, such as NVIDIA’s FourCastNetv2. FourCastNetv2 is an NVIDIA’s advanced neural network for weather prediction and...
Fried Parameter Estimation from Single Wavefront Sensor Image with Artificial Neural Networks
Atmospheric turbulence degrades the quality of astronomical observations in ground-based telescopes, leading to distorted and blurry images. Adaptive Optics (AO) systems are designed to counteract these effects, using atmospheric measurements captured by a wavefront sensor to make real-time corrections to the incoming...
Breaking the Sorting Barrier for Directed Single-Source Shortest Paths
We give a deterministic $O(m\log^{2/3}N)$-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition model. This is the first result to break the $O(m+n\log n)$ time bound of Dijkstra’s algorithm on sparse graphs, showing...
The $q^{\Mathe{Volume}}$ lozenge tiling model via non-Hermitian orthogonal polynomials
We consider the $q^\text{Volume}$ lozenge tiling model on a large, finite hexagon. It is well-known that random lozenge tilings of the hexagon correspond to a two-dimensional determinantal point process via a bijection with ensembles of non-intersecting paths. The starting point of our...