Astronomical imaging: The theory of everything

10/21/2008
by   David W. Hogg, et al.
0

We are developing automated systems to provide homogeneous calibration meta-data for heterogeneous imaging data, using the pixel content of the image alone where necessary. Standardized and complete calibration meta-data permit generative modeling: A good model of the sky through wavelength and time--that is, a model of the positions, motions, spectra, and variability of all stellar sources, plus an intensity map of all cosmological sources--could synthesize or generate any astronomical image ever taken at any time with any equipment in any configuration. We argue that the best-fit or highest likelihood model of the data is also the best possible astronomical catalog constructed from those data. A generative model or catalog of this form is the best possible platform for automated discovery, because it is capable of identifying informative failures of the model in new data at the pixel level, or as statistical anomalies in the joint distribution of residuals from many images. It is also, in some sense, an astronomer's "theory of everything".

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/13/2020

Bayesian Calibration of Computer Models with Informative Failures

There are many practical difficulties in the calibration of computer mod...
research
08/14/2017

Colorimetric Calibration of a Digital Camera

In this paper, we introduce a novel - physico-chemical - approach for ca...
research
08/21/2018

Text-to-image Synthesis via Symmetrical Distillation Networks

Text-to-image synthesis aims to automatically generate images according ...
research
11/01/2017

On the variance of radio interferometric calibration solutions: Quality-based Weighting Schemes

SKA-era radio interferometric data volumes are expected to be such that ...
research
02/08/2022

DURableVS: Data-efficient Unsupervised Recalibrating Visual Servoing via online learning in a structured generative model

Visual servoing enables robotic systems to perform accurate closed-loop ...
research
06/26/2019

Morpheus: A Deep Learning Framework For Pixel-Level Analysis of Astronomical Image Data

We present Morpheus, a new model for generating pixel level morphologica...

Please sign up or login with your details

Forgot password? Click here to reset