Interferometers (e.g., ALMA and NOEMA) allow us to obtain the detailed brightness distribution of astronomical sources in three dimensions (R.A., Dec., and frequency). However, the spatial correlation of the noise makes it difficult to evaluate the statistical uncertainty of the measured quantities and the statistical significance of the results obtained. The noise correlation properties in the interferometric image are fully characterized and easily measured by the noise autocorrelation function (ACF). We present the method for (1) estimating the statistical uncertainty due to the correlated noise in the spatially integrated flux and spectra directly, (2) simulating the correlated noise to perform a Monte Carlo simulation in image analyses, and (3) constructing the covariance matrix and chi-square χ2 distribution to be used when fitting a model to an image with spatially correlated noise, based on the measured noise ACF. We demonstrate example applications to scientific data showing that ignoring noise correlation can lead to significant underestimation of statistical uncertainty of the results and false detections/interpretations.
Recent interferometers (e.g. ALMA and NOEMA) allow us to obtain the detailed brightness distribution of the astronomical sources in 3 dimension (R.A., Dec., frequency). However, the interpixel correlation of the noise due to the limited uv coverage makes it difficult to evaluate the statistical uncertainty of the measured quantities and the statistical significance of the obtained results. The noise correlation properties are characterized by the noise autocorrelation function (ACF). We will present the method for (1) estimating the statistical uncertainty due to the correlated noise in the spatially integrated flux and spectra directly from the noise ACF and (2) simulating the correlated noise to perform a Monte Carlo simulation in image analyses. Our method has potential applications to a range of astronomical images of not only interferometers but also single dish mapping observation and interpolated and resampled optical images.
We develop a machine learning (ML) software to estimate morphological parameters (e.g., the half-light radius re) of high redshift galaxies in the Subaru/Hyper Suprime-Cam data. To make the ML software capture simultaneously galaxy morphological features and point spread function (PSF) broadening effects, we implement a two-stream convolutional neural network (CNN) for inputs of galaxy and PSF images. Thanks to large training samples of galaxy and PSF images, the two-stream CNN estimates re more accurately than a single-stream CNN with only galaxy images. Our ML software would be a useful tool to investigate galaxy morphological properties with PSF-unstable images obtained in future large-area ground-based surveys.
The Simultaneous-color Wide-field Infrared Multi-object Spectrograph (SWIMS) is one of the 1st generation facility instruments for the University of Tokyo Atacama Observatory (TAO) 6.5 m telescope currently being constructed at the summit of Cerro Chajnantor (5,640 m altitude) in northern Chile. SWIMS has two optical arms, the blue arm covering 0.9–1.4 µm and the red 1.4–2.5 µm, by inserting a dichroic mirror into the collimated beam, and thus is capable of taking images in two filter-bands simultaneously in imaging mode, or whole nearinfrared (0.9–2.5 µm) low-to-medium resolution multi-object spectra in spectroscopy (MOS) mode, both with a single exposure. SWIMS was carried into Subaru Telescope in 2017 for performance evaluation prior to completion of the construction of the 6.5 m telescope, and successfully saw the imaging first light in May 2018 and MOS first light in Jan 2019. After three engineering runs including the first light observations, SWIMS has been accepted as a new PI instrument for Subaru Telescope from the semester S21A until S22B. In this paper, we report on details of on-sky performance of the instrument evaluated during the engineering observations for a total of 7.5 nights.
The Simultaneous-color Wide-field Infrared Multi-object Spectrograph, SWIMS, is a first-generation near-infrared instrument for the University of Tokyo Atacama Observatory (TAO) 6.5m Telescope now being constructed in northern Chile. To utilize the advantage of the site that almost continuous atmospheric window appears from
0.9 to 2.5 μm, the instrument is capable of simultaneous two-color imaging with a field-of-view of 9.′6 in diameter or λ/▵λ 1000 multi-object spectroscopy at 0.9–2.5 μm in a single exposure. The instrument has been trans- ported in 2017 to the Subaru Telescope as a PI-type instrument for carrying out commissioning observations before starting science operation on the 6.5m telescope. In this paper, we report the latest updates on the instrument and present preliminary results from the on-sky performance verification observations.
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