Related papers: Sick, the spectroscopic inference crank
Bayesian inference is an effective approach for solving statistical learning problems especially with uncertainty and incompleteness. However, inference efficiencies are physically limited by the bottlenecks of conventional computing…
The Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy (SCALES) instrument is a lenslet-based integral field spectrograph that will operate at 2 to 5 microns, imaging and characterizing colder (and thus older) planets than…
There is an especially strong need in modern large-scale data analysis to prioritize samples for manual inspection. For example, the inspection could target important mislabeled samples or key vulnerabilities exploitable by an adversarial…
Searches for new astrophysical phenomena often involve several sources of non-random uncertainties which can lead to highly misleading results. Among these, model-uncertainty arising from background mismodelling can dramatically compromise…
Multiple codes are available to derive atmospheric parameters and individual chemical abundances from high-resolution spectra of AFGKM stars. Almost all spectroscopists have their own preferences regarding which code and method to use. But…
The analysis of high spectral resolution spectroscopic and spectropolarimetric observations constitute a very powerful way of inferring the dynamical, thermodynamical, and magnetic properties of distant objects. However, these techniques…
A data sketch algorithm scans a big data set, collecting a small amount of data -- the sketch, which can be used to statistically infer properties of the big data set. Some data sketch algorithms take a fixed-size random sample of a big…
Spectroscopy is one of the most important tools that an astronomer has for studying the universe. This chapter begins by discussing the basics, including the different types of optical spectrographs, with extension to the ultraviolet and…
Sparse Subspace Clustering (SSC) has achieved state-of-the-art clustering quality by performing spectral clustering over a $\ell^{1}$-norm based similarity graph. However, SSC is a transductive method which does not handle with the data not…
All spectrometers rely on some mechanism to achieve spectral selectivity; common examples include gratings, prisms, and interferometers with moving mirrors. We experimentally demonstrated and validated a spectroscopic technique -- here…
X-ray echo spectroscopy, a space-domain counterpart of neutron spin echo, is a recently proposed inelastic x-ray scattering (IXS) technique. X-ray echo spectroscopy relies on imaging IXS spectra, and does not require x-ray…
Individual-based models of contagious processes are useful for predicting epidemic trajectories and informing intervention strategies. In such models, the incorporation of contact network information can capture the non-randomness and…
Upcoming large-scale spectroscopic surveys such as WEAVE and 4MOST will provide thousands of spectra of massive stars, which need to be analysed in an efficient and homogeneous way. Studies on massive stars are usually based on samples of a…
Spectral estimation (SE) aims to identify how the energy of a signal (e.g., a time series) is distributed across different frequencies. This can become particularly challenging when only partial and noisy observations of the signal are…
A flood of reliable seismic data will soon arrive. The migration to larger telescopes on the ground may free up 4-m class instruments for multi-site campaigns, and several forthcoming satellite missions promise to yield nearly uninterrupted…
Current and upcoming generations of visible-shortwave infrared (VSWIR) imaging spectrometers promise unprecedented capacity to quantify Earth System processes across the globe. However, reliable cloud screening remains a fundamental…
We present results from the first on-sky demonstration of a prototype astronomical integrated photonic spectrograph (IPS) using the Anglo-Australian Telescope near-infrared imaging spectrometer (IRIS2) at Siding Spring Observatory to…
We examine a probabilistic model for the diagnosis of multiple diseases. In the model, diseases and findings are represented as binary variables. Also, diseases are marginally independent, features are conditionally independent given…
The speckle imaging is a photographic technique that resolves objects viewed through severely distorted media. The results are insensitive to the errors caused by apparent size of the isoplanatic patch and the telescope aberrations. In this…
Large sets of objects with spectroscopic redshift measurements will be needed for imaging dark energy experiments to achieve their full potential, serving two goals:_training_, i.e., the use of objects with known redshift to develop and…