Related papers: A Bayesian approach to high fidelity interferometr…

We describe techniques concerning wavelength calibration and sky subtraction to maximise the scientific utility of data from tunable filter instruments. While we specifically address data from the Optical System for Imaging and low…

Modern neural networks have found to be miscalibrated in terms of confidence calibration, i.e., their predicted confidence scores do not reflect the observed accuracy or precision. Recent work has introduced methods for post-hoc confidence…

Bayesian calibration of computer models tunes unknown input parameters by comparing outputs with observations. For model outputs that are distributed over space, this becomes computationally expensive because of the output size. To overcome…

Inter-survey calibration remains an important systematic uncertainty in cosmological studies using type Ia supernova (SNe Ia). Ideally, each survey would measure its system throughputs, for instance with bandpass measurements combined with…

Extracting polarimetric information from very long baseline interferometry (VLBI) data is demanding but vital for understanding the synchrotron radiation process and the magnetic fields of celestial objects, such as active galactic nuclei…

The redshifted cosmological 21 cm signal emitted by neutral hydrogen during the first billion years of the universe is much fainter relative to other galactic and extragalactic radio emissions, posing a great challenge towards detection of…

Low-resolution spectroscopy is a frequently used technique. Aperture prism spectroscopy in particular is an important tool for large-scale survey observations. The ongoing ESA space mission Gaia is the currently most relevant example. In…

This manual is intended to help ALMA and other interferometer users improve images by recognising limitations and how to overcome them and deciding when and how to use self-calibration. The images provided by the ALMA Science Archive are…

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…

We present an algorithm to photometrically calibrate wide field optical imaging surveys, that simultaneously solves for the calibration parameters and relative stellar fluxes using overlapping observations. The algorithm decouples the…

We present a new approach to multi-frequency synthesis in radio astronomy. Using Bayesian inference techniques, the new technique estimates the sky brightness and the spectral index simultaneously. In principle, the bandwidth of a wide-band…

We consider the problem of estimating cross-spectral quantities in the low-frequency regime, where long observation times limit averaging over large ensembles of periodograms, thereby preventing the use of approximate Gaussian statistics.…

We present an end-to-end simulation and data-processing framework for digital beamforming experiments conducted with four stations of the 21 Centimeter Array (21CMA). Motivated by the need to characterize instrumental systematics, such as…

Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information-updating rules. In many applications, however, prior distributions are introduced merely as…

Computer models, aiming at simulating a complex real system, are often calibrated in the light of data to improve performance. Standard calibration methods assume that the optimal values of calibration parameters are invariant to the model…

We present a filtering technique that can be applied to individual baselines of wide-bandwidth, wide-field interferometric data to geometrically select regions on the celestial sphere that contain primary calibration sources. The technique…

A key factor in ensuring the accuracy of computer simulations that model physical systems is the proper calibration of their parameters based on real-world observations or experimental data. Inevitably, uncertainties arise, and Bayesian…

Bayesian model selection is a tool to decide whether the introduction of a new parameter is warranted by data. I argue that the usual sampling statistic significance tests for a null hypothesis can be misleading, since they do not take into…

Self-calibration methods with the CLEAN algorithm have been widely employed in Very Long Baseline Interferometry (VLBI) data processing in order to correct antenna-based amplitude and phase corruptions present in the data. However, human…

Context: Radio interferometers measure frequency components of the sky brightness, modulated by the gains of the individual radio antennas. Due to atmospheric turbulence and variations in the operational conditions of the antennas these…