Sazuna/UAT_keywords huggingface dataset:
Unsupervised Galaxy Morphological Visual Representation with Deep Contrastive Learning. Galaxy morphology reflects structural properties that contribute to the understanding of the formation and evolution of galaxies. Deep convolutional networks have proven to be very successful in learning hidden features that allow for unprecedented performance in the morphological classification of galaxies. Such networks mostly follow the supervised learning paradigm, which requires sufficient labeled data for training. However, the labeling of a million galaxies is an expensive and complicated process, particularly for forthcoming survey projects. In this paper, we present an approach, based on contrastive learning, with aim of learning galaxy morphological visual representation using only unlabeled data. Considering the properties of low semantic information and contour dominated of galaxy images, the feature extraction layer of the proposed method incorporates vision transformers and a convolutional network to provide rich semantic representation via the fusion of multi-hierarchy features. We train and test our method on three classifications of data sets from Galaxy Zoo 2 and SDSS-DR17, and four classifications from Galaxy Zoo DECaLS. The testing accuracy achieves 94.7%, 96.5% and 89.9%, respectively. The experiment of cross validation demonstrates our model possesses transfer and generalization ability when applied to new data sets. The code that reveals our proposed method and pretrained models are publicly available and can be easily adapted to new surveys. 6 6 https://github.com/kustcn/galaxy_contrastive

Keywords: Surveys, Astrostatistics techniques, Galaxy evolution
APERO: A PipelinE to Reduce Observations-Demonstration with SPIRou. With the maturation of near-infrared high-resolution spectroscopy, especially when used for precision radial velocity, data reduction has faced unprecedented challenges in terms of how one goes from raw data to calibrated, extracted, and corrected data with required precisions of thousandths of a pixel. Here we present A PipelinE to Reduce Observations (APERO), specifically focused on Spectro Polarimètre Infra ROUge (SPIROU), the near-infrared spectropolarimeter on the Canada-France-Hawaii Telescope (SPectropolarimètre InfraROUge, CFHT). In this paper, we give an overview of APERO and detail the reduction procedure for SPIROU. APERO delivers telluric-corrected 2D and 1D spectra as well as polarimetry products. APERO enables precise stable radial velocity measurements on the sky (via the LBL algorithm), which is good to at least ~2 m s-1 over the current 5 yr lifetime of SPIROU.

Keywords: Spectropolarimetry, Calibration, Spectroscopy, Radial velocity, Astronomy data reduction, Near infrared astronomy
Pixel Centroid Characterization with Laser Speckle and Application to the Nancy Grace Roman Space Telescope Detector Arrays. The Nancy Grace Roman Space Telescope will use its wide-field instrument to carry out a suite of sky surveys in the near-infrared. Several of the science objectives of these surveys, such as the measurement of the growth of cosmic structure using weak gravitational lensing, require exquisite control of instrument-related distortions of the images of astronomical objects. Roman will fly new large-format (4 × 4 k) Teledyne H4RG-10 infrared detector arrays. This paper investigates whether the pixel centroids are located on a regular grid by projecting laser speckle patterns through a double slit aperture onto a non-flight detector array. We develop a method to reconstruct the pixel centroid offsets from the stochastic speckle pattern. Due to the orientation of the test setup, only x-offsets are measured here. We test the method both on simulations, and by injecting artificial offsets into the real images. We use cross-correlations of the reconstructions from different speckle realizations to determine how much of the variance in the pixel offset maps is signal (fixed to the detector) and how much is noise. After performing this reconstruction on 64 × 64 pixel patches, and fitting out the best-fit linear mapping from pixel index to position, we find that there are residual centroid offsets in the x (column) direction from a regular grid of 0.0107 pixels rms (excluding shifts of an entire row relative to another, which our speckle patterns cannot constrain). This decreases to 0.0097 pix rms if we consider residuals from a quadratic rather than linear mapping. These rms offsets include both the physical pixel offsets, as well as any apparent offsets due to crosstalk and remaining systematic errors in the reconstruction. We comment on the advantages and disadvantages of speckle scene measurements as a tool for characterizing the pixel-level behavior in astronomical detectors.

Keywords: Weak gravitational lensing, Astrometry, Infrared observatories
Fabrication and Performance of Lobster Eye X-Ray Micro Pore Optics with the Ultra-high Aspect Ratio. Since the idea of bionic Lobster eye micropore optics was put forward, the possibility of focusing hard X-rays by this new lightweight X-ray optics has been proposed. Limited by the technological conditions of the aspect ratio (≥500), low surface roughness (≤1 nm) and the difficulty of applying metal coatings inside such narrow square channels, the high quality of these new optics have not been realized. This work demonstrates the test results for an Ultra-high aspect ratio (500:1) of iridium-coated with microchannel plate technology and atomic layer deposition technology. The sidewalls of the square channel are smoothed with a special acid-base treatment and the Root-Mean-Square of the inner wall was 0.52 ± 0.1 nm in 3 μm × 3 μm scale roughness, such that they work well as X-ray mirrors. The thickness of the metal iridium film layer was 19 nm. At the working voltage of 2 kV, the current was 0.1 mA and the angular resolution of the slumped chip in horizontal and vertical directions was 3.'9 and 4.'2, respectively. The simulation results were in good agreement with the X-ray test results.

Keywords: X-ray astronomy, X-ray telescopes, X-ray identification, X-ray transient sources, X-ray surveys
Research on the Fiducial Fibre Coding and Identification Algorithm of the LAMOST Fibre Positioning System. To obtain the world coordinates of a measured object in camera measurement, a certain number of image control points should be established around the detected object as fiducial points for data processing. The precision of a fiducial point directly determines the measurement accuracy of the measured object in the camera measurement. Fiducial points in camera measurement are widely used in various fields of measurement, such as aerial surveys, close-range surveys, and 3D reconstruction. In addition, a fiducial point generally adopts an encoding structure to reduce the search cost in the detection. Camera measurement is used in the LAMOST fiber positioning system, which also requires fiducial points to ensure the accuracy of fiber positioning. Different from a general fiducial point, the whole system needs to operate under dark conditions during LAMOST observation, and optical fiber positioning is carried out by the "backlighting method", which measures the optical fiber spot under a dark background. In addition, fiber positioning needs to reach an accuracy of 40 μm at a distance of 20 m, which is difficult to achieve with the fiducial points used in general vision measurements. To meet the requirements of LAMOST optical fiber positioning with high accuracy, this paper presents a fiducial fiber and its recognition algorithm for optical fiber positioning of optical fiber spectroscopic telescopes. The fiducial fiber can be applied to a wide-field optical fiber spectroscopic telescope measurement system in a high-precision long-distance measurement environment. The experimental results show that fiducial fiber can ensure the accuracy of closed-loop positioning for LAMOST fiber units.

Keywords: Astronomical techniques, Astronomical instrumentation
Techniques for Measuring Parallax and Proper Motion with VLBI. Astrometry at centimeter wavelengths using Very Long Baseline Interferometry is approaching accuracies of ~1 μas for the angle between a target and a calibrator source separated by ≲1° on the sky. The BeSSeL Survey and the Japanese VERA project are using this to map the spiral structure of the Milky Way by measuring trigonometric parallaxes of hundreds of maser sources associated with massive, young stars. This paper outlines how μas astrometry is done, including details regarding the scheduling of observations, calibration of data, and measuring positions.

Keywords: Very long baseline interferometry, Radio astrometry, Astronomical techniques, Astrophysical masers, Annual parallax
Machine Learning-based Prediction of Sunspots using Fourier Transform Analysis of the Time Series. The study of solar activity holds special importance since the changes in our star's behavior affect both the Earth's atmosphere and the conditions of the interplanetary environment. They can interfere with air navigation, space flight, satellites, radar, high-frequency communications, and overhead power lines, and can even negatively influence human health. We present here a machine learning-based prediction of the evolution of the current sunspot cycle (solar cycle 25). First, we analyze the Fourier Transform of the total time series (from 1749 to 2022) to find periodicities with which to lag this series and then add attributes (predictors) to the forecasting models to obtain the most accurate result possible. Consequently, we build a trained model of the series considering different starting points (from 1749 to 1940, with 1 yr steps), applying Random Forests, Support Vector Machines, Gaussian Processes, and Linear Regression. We find that the model with the lowest error in the test phase (cycle 24) arises with Random Forest and with 1915 as the start year of the time series (yielding a Root Mean Squared Error of 9.59 sunspots). Finally, for cycle 25 this model predicts that the maximum number of sunspots (90) will occur in 2025 March.

Keywords: Sunspots, Linear regression, Support vector machine, Gaussian Processes regression, Solar activity, Random Forests, Time series analysis
SImMER: A Pipeline for Reducing and Analyzing Images of Stars. We present the first public version of SImMER, an open-source Python reduction pipeline for astronomical images of point sources. Current capabilities include dark-subtraction, flat-fielding, sky-subtraction, image registration, FWHM measurement, contrast curve calculation, and table and plot generation. SImMER supports observations taken with the ShARCS camera on the Shane 3 m telescope and the PHARO camera on the Hale 5.1 m telescope. The modular nature of SImMER allows users to extend the pipeline to accommodate additional instruments with relative ease. One of the core functions of the pipeline is its image registration module, which is flexible enough to reduce saturated images and images of similar-brightness, resolved stellar binaries. Furthermore, SImMER can compute contrast curves for reduced images and produce publication-ready plots. The code is developed online at https://github.com/arjunsavel/SImMER and is both pip- and conda-installable. We develop tutorials and documentation alongside the code and host them online. With SImMER, we aim to provide a community resource for accurate and reliable data reduction and analysis.

Keywords: Photometry, Astronomy data analysis, Astronomy data reduction
The Spectroscopic Classification of Astronomical Transients (SCAT) Survey: Overview, Pipeline Description, Initial Results, and Future Plans. We present the Spectroscopic Classification of Astronomical Transients (SCAT) survey, which is dedicated to spectrophotometric observations of transient objects such as supernovae and tidal disruption events. SCAT uses the SuperNova Integral-Field Spectrograph (SNIFS) on the University of Hawai'i 2.2 m (UH2.2m) telescope. SNIFS was designed specifically for accurate transient spectrophotometry, including absolute flux calibration and host-galaxy removal. We describe the data reduction and calibration pipeline including spectral extraction, telluric correction, atmospheric characterization, nightly photometricity, and spectrophotometric precision. We achieve ≲5% spectrophotometry across the full optical wavelength range (3500-9000 Å) under photometric conditions. The inclusion of photometry from the SNIFS multi-filter mosaic imager allows for decent spectrophotometric calibration (10%-20%) even under unfavorable weather/atmospheric conditions. SCAT obtained ≈640 spectra of transients over the first 3 yr of operations, including supernovae of all types, active galactic nuclei, cataclysmic variables, and rare transients such as superluminous supernovae and tidal disruption events. These observations will provide the community with benchmark spectrophotometry to constrain the next generation of hydrodynamic and radiative transfer models.

Keywords: Atmospheric extinction, Transient sources, Active galactic nuclei, Cataclysmic variable stars, Supernovae, Spectrophotometry
A Robust RFI Identification Method for Radio Interferometry Based on LightGBM. Radio frequency interference is an essential factor affecting the observation data quality of radio telescopes. In constructing the Square Kilometer Array (SKA) radio interferometer, dealing with radio frequency interference (RFI) effectively is always a hot issue in data processing. Traditional identification methods have poor precision or recall, and existing machine-learning-based methods have complicated models and low processing efficiency. We propose a LightGBM identification method based on previous machine-learning research to identify RFI. Based on the data of SKA1-LOW simulation observations, we construct five visibility function data sets, one for modeling and the rest for validation. The experimental results show that the F 2-score reaches 0.9583, and the training and prediction speed are much more efficient than those of convolutional neural networks in a similar recent study. Then, we further investigate the effectiveness of this model in identifying RFI from actual MeerKAT observations. The results show that the overall effectiveness is comparable to tools such as Tfcrop and Rflag, improving over existing methods in identification speed.

Keywords: Astronomy data modeling, Classification, Neural networks, Astrostatistics techniques, Astronomy data analysis, Astronomical simulations
Tracking ALMA System Temperature with Water Vapor Data at High Frequency. As the world-leading submillimeter telescope, the Atacama Large Millimeter/submillimeter Array observatory is now putting more focus on high-frequency observations at Band 7-10 (frequencies from 275 to 950 GHz). However, high-frequency observations often suffer from rapid variations in atmospheric opacity that directly affect the system temperature T sys. Current observations perform discrete atmospheric calibrations (Atm-cals) every few minutes, with typically 10-20 occurring per hour for high frequency observation and each taking 30-40 s. In order to obtain more accurate flux measurements and reduce the number of atmospheric calibrations (Atm-cals), a new method to monitor T sys continuously is proposed using existing data in the measurement set. In this work, we demonstrate the viability of using water vapor radiometer (WVR) data to track the T sys continuously. We find a tight linear correlation between T sys measured using the traditional method and T sys extrapolated based on WVR data with scatter of 0.5%-3%. Although the exact form of the linear relation varies among different data sets and spectral windows, we can use a small number of discrete T sys measurements to fit the linear relation and use this heuristic relationship to derive T sys every 10 s. Furthermore, we successfully reproduce the observed correlation using atmospheric transmission at microwave modeling and demonstrate the viability of a more general method to directly derive the T sys from the modeling. We apply the semi-continuous T sys from heuristic fitting on a few data sets from Band 7 to Band 10 and compare the flux measured using these methods. We find the discrete and continuous T sys methods give us consistent flux measurements with differences up to 5%. Furthermore, this method has significantly reduced the flux uncertainty due to T sys variability for one data set, which has large precipitable water vapor fluctuation, from 10% to 0.7%.

Keywords: Flux calibration, Astronomical techniques, Radio telescopes, Astronomical instrumentation, Interferometry
Global Extinction: Gemini North and South GMOS Combined Photometry Relative to the Gaia Catalog, and Long-term Atmospheric Change. Effects of long-term atmospheric change were looked for in photometry employing Gemini North and South twin Multi-Object Spectrograph (GMOS-N and GMOS-S) archival data. The whole GMOS imaging database, beginning from 2003, was compared against the all-sky Gaia object catalog, yielding ~106 Sloan $r^{\prime} $ -filter samples, ending in 2021. These were combined with reported sky and meteorological conditions, and versus a simple model of the atmosphere plus cloud together with simulated throughputs. One exceptionally extincted episode in 2009 is seen, as is a trend (similar at both sites) of about 2 mmag worsening attenuation per decade. This is consistent with solar-radiance transmissivity records going back over six decades, aerosol density measurements, and more than 0.2°C/decade rise in air temperature, which has implications for the calibration of historic data sets or future surveys.

Keywords: Astronomical site protection, Astronomical instrumentation, Astronomical methods
Modeling the Lunar Wake Response to a CME Using a Hybrid PIC Model. In the solar wind, a low-density wake region forms downstream of the nightside lunar surface. In this study, we use a series of 3D hybrid particle-in-cell simulations to model the response of the lunar wake to a passing coronal mass ejection (CME). Average plasma parameters are derived from the Wind spacecraft located at 1 au during three distinct phases of a passing halo (Earth-directed) CME on 2015 June 22. Each set of plasma parameters, representing the shock/plasma sheath, a magnetic cloud, and plasma conditions we call the mid-CME phase, are used as the time-static upstream boundary conditions for three separate simulations. These simulation results are then compared with results that use nominal solar wind conditions. Results show a shortened plasma void compared to nominal conditions and a distinctive rarefaction cone originating from the terminator during the CME's plasma sheath phase, while a highly elongated plasma void reforms during the magnetic cloud and mid-CME phases. Developments of electric and magnetic field intensification are also observed during the plasma sheath phase along the central wake, while electrostatic turbulence dominates along the plasma void boundaries and 2-3 lunar radii R  M  downstream in the central wake during the magnetic cloud and mid-CME phases. The simulations demonstrate that the lunar wake responds in a dynamic way with the changes in the upstream solar wind during a CME.

Keywords: Space plasmas, The Moon, Theoretical models, Solar coronal mass ejections
ExoCAM: A 3D Climate Model for Exoplanet Atmospheres. The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI) project was initiated to compare 3D climate models that are commonly used for predicting theoretical climates of habitable zone extrasolar planets. One of the core models studied as part of THAI is ExoCAM, an independently curated exoplanet branch of the National Center for Atmospheric Research Community Earth System Model (CESM), version 1.2.1. ExoCAM has been used for studying atmospheres of terrestrial extrasolar planets around a variety of stars. To accompany the THAI project and provide a primary reference, here we describe ExoCAM and what makes it unique from standard configurations of CESM. Furthermore, we also conduct a series of intramodel sensitivity tests of relevant moist physical tuning parameters while using the THAI protocol as our starting point. A common criticism of 3D climate models used for exoplanet modeling is that cloud and convection routines often contain free parameters that are tuned to the modern Earth, and thus may be a source of uncertainty in evaluating exoplanet climates. Here, we explore sensitivities to numerous configuration and parameter selections, including a recently updated radiation scheme, a different cloud and convection physics package, different cloud and precipitation tuning parameters, and a different sea ice albedo. Improvements to our radiation scheme and the modification of cloud particle sizes have the largest effects on global mean temperatures, with variations up to ~10 K, highlighting the requirement for accurate radiative transfer and the importance of cloud microphysics for simulating exoplanetary climates. However, for the vast majority of sensitivity tests, climate differences are small. For all cases studied, intramodel differences do not bias general conclusions regarding climate states and habitability.

Keywords: Exoplanet atmospheres, Planetary climates
A CO<SUB>2</SUB> Cycle on Ariel? Radiolytic Production and Migration to Low-latitude Cold Traps. CO2 ice is present on the trailing hemisphere of Ariel but is mostly absent from its leading hemisphere. The leading/trailing hemispherical asymmetry in the distribution of CO2 ice is consistent with radiolytic production of CO2, formed by charged particle bombardment of H2O ice and carbonaceous material in Ariel's regolith. This longitudinal distribution of CO2 on Ariel was previously characterized using 13 near-infrared reflectance spectra collected at "low" sub-observer latitudes between 30°S and 30°N. Here we investigated the distribution of CO2 ice on Ariel using 18 new spectra: 2 collected over low sub-observer latitudes, 5 collected at "mid" sub-observer latitudes (31°N-44°N), and 11 collected over "high" sub-observer latitudes (45°N-51°N). Analysis of these data indicates that CO2 ice is primarily concentrated on Ariel's trailing hemisphere. However, CO2 ice band strengths are diminished in the spectra collected over mid and high sub-observer latitudes. This sub-observer latitudinal trend may result from radiolytic production of CO2 molecules at high latitudes and subsequent migration of this constituent to low-latitude cold traps. We detected a subtle feature near 2.13 μm in two spectra collected over high sub-observer latitudes, which might result from a "forbidden" transition mode of CO2 ice that is substantially stronger in well-mixed substrates composed of CO2 and H2O ice, consistent with regolith-mixed CO2 ice grains formed by radiolysis. Additionally, we detected a 2.35 μm feature in some low sub-observer latitude spectra, which might result from CO formed as part of a CO2 radiolytic production cycle.

Keywords: Planetary surfaces, Uranian satellites, Surface processes, Surface composition, Surface ices