arXiv subjects

Alan Hsu

Publications and source records attributed to Alan Hsu.

3 recordsLinked to original sources

arXiv2026

A Probabilistic Calibration Procedure for the CORSAIR Polarimeter

We present a novel Bayesian model and a corresponding robust, probabilistic calibration procedure for the CORSAIR polarimeter that can be applied to other polarimeters. Our calibration procedure combines existing Mueller matrix representations of polarimeters with Bayesian methods, and computes the posterior distribution of the parameters by collecting data from the polarimeter at different states. We show that the algorithm is able to converge and recover a well-constrained posterior of the free parameters with a credible interval that is consistent with the ground truth values. Posterior predictive checks indicate that our generative model with inferred parameters can reproduce the calibration data within the predictive uncertainty, and captures the dominant systematic effects of the calibration procedure. We further show that we can propagate calibration uncertainties in the distributions to downstream reconstructions of Stokes measurements and magnetic-field estimates. We find that the contribution of calibration uncertainty towards the reconstructed results is minimal relative to that of the photon noise uncertainty, indicating that estimates using our Bayesian calibration algorithm can achieve photon noise-limited measurements in the magnetic-field parameters. Finally, we test the Bayesian calibration algorithm on a lab prototype of the CORSAIR polarimeter, and show that it converges and closely recovers theoretical estimates of the free parameters from real-world measurements.

astro-ph.SR↗

arXiv2024

Reconstructing Galaxy Cluster Mass Maps using Score-based Generative Modeling

We present a novel approach to reconstruct gas and dark matter projected density maps of galaxy clusters using score-based generative modeling. Our diffusion model takes in mock SZ and X-ray images as conditional inputs, and generates realizations of corresponding gas and dark matter maps by sampling from a learned data posterior. We train and validate the performance of our model by using mock data from a cosmological simulation. The model accurately reconstructs both the mean and spread of the radial density profiles in the spatial domain, indicating that the model is able to distinguish between clusters of different mass sizes. In the spectral domain, the model achieves close-to-unity values for the bias and cross-correlation coefficients, indicating that the model can accurately probe cluster structures on both large and small scales. Our experiments demonstrate the ability of score models to learn a strong, nonlinear, and unbiased mapping between input observables and fundamental density distributions of galaxy clusters. These diffusion models can be further fine-tuned and generalized to not only take in additional observables as inputs, but also real observations and predict unknown density distributions of galaxy clusters.

astro-ph.CO↗

arXiv2018

Air Flow Analysis of a Rotating Cylinder through Numerical Simulation

The complete flow field surrounding a rotating cylinder is calculated by solving the Navier-Stokes equations using the finite difference method. The numerical simulation is performed on a transformed rectilinear grid, with axes representing the radial and angular dimensions. Different boundary conditions of the simulations are tested by changing the tangential speed of the rotating cylinder, ranging from subsonic to supersonic speed. The following variables in the modeled flow fields are analyzed: temperature, velocity, pressure, density, and stress. The large gradient of velocity near the cylinder is found to create high stress, which leads to rise in temperature. Pressure and density near the cylinder decreases as the speed of the cylinder increases. The proposed simulation method and analysis of air flow can be extended to the modeling of air flow around a Diabolo.

physics.comp-ph↗