Sparse modeling

A data-scientific noise-removal method for efficient submillimeter spectroscopy with single-dish telescopes

For submillimeter spectroscopy with ground-based single-dish telescopes, removing the noise contribution from the Earth's atmosphere and the instrument is essential. For this purpose, here we propose a new method based on a data-scientific approach. …

Three-Dimensional Reconstruction of Weak Lensing Mass Maps with a Sparsity Prior. I. Cluster Detection

Published in Apj

Three-dimensional Reconstruction of Weak-lensing Mass Maps with a Sparsity Prior. I. Cluster Detection

We propose a novel method to reconstruct high-resolution three-dimensional mass maps using data from photometric weak-lensing surveys. We apply an adaptive LASSO algorithm to perform a sparsity-based reconstruction on the assumption that the …

Super-resolution Imaging of the Protoplanetary Disk HD 142527 Using Sparse Modeling

With an emphasis on improving the fidelity even in super-resolution regimes, new imaging techniques have been intensively developed over the last several years, which may provide substantial improvements to the interferometric observation of …

Amino-acid selective isotope labeling enables simultaneous overlapping signal decomposition and information extraction from NMR spectra

Signal overlapping is a major bottleneck for protein NMR analysis. We propose a new method, stable-isotope-assisted parameter extraction (SiPex), to resolve overlapping signals by a combination of amino-acid selective isotope labeling (AASIL) and …

An image reconstruction method for X-ray telescope system with an angular resolution booster

We propose an image reconstruction method for an X-ray telescope system with an angular resolution booster proposed by Maeda et al. (2018, PASJ, submitted). The system consists of double multi-grid masks in front of an X-ray mirror and an off-focused …

Acceleration of the Sparse Modeling imaging tool for ALMA radio interferometric data

Sparse modeling is widely used in image processing, signal processing, and machine learning recently. Thanks to the research and progress in statistical mathematics along with the evolution of computational power, the technique is applicable to the …

Faraday tomography with sparse modeling

Faraday tomography (or rotation measure synthesis) is a procedure to convert linear polarization spectra into the Faraday dispersion function, which provides us with unique information of magneto-ionic media along the line of sight. Mathematical …

New synthesis imaging tool for ALMA based on the sparse modeling

A new imaging tool for radio interferometry has been developed based on the sparse modeling approach. It has been implemented as a Python module operating on Common Astronomy Software Applications (CASA) so that the tool is able to process the data …

Super-resolution imaging of the protoplanetary disk HD 142527 using sparse modeling

High-resolution observations of protoplanetary disks with radio interferometers are crucial for understanding the planet formation process. Recent observations using Atacama Large Millimeter/submillimeter Array (ALMA) have revealed various …