We present a new all-sky model of low-frequency diffuse Galactic emission in the regime where synchrotron, free-free, and spinning dust dominate. The model extends the Planck 2015 diffuse component-separation analysis by incorporating recent radio and microwave surveys. We fit 35 full- and partial-sky maps at 1 degree resolution, including S-PASS at 2.30 GHz, C-BASS at 4.76 GHz, and QUIJOTE at 10-20 GHz, together with reprocessed WMAP and Planck LFI data from the Cosmoglobe collaboration and Planck HFI channels. Using a Bayesian parametric approach with Commander, we derive spatially varying amplitude and spectral parameter maps for the dominant low-frequency foreground components in total intensity. The main products are a full-sky synchrotron amplitude and spectral-index solution, an all-sky characterization of spinning dust emission with a single-component log-normal spectral model, and a reconstructed all-sky total-intensity map at 4.76 GHz tracing diffuse synchrotron emission with reduced systematics relative to Haslam 408 MHz. The revised low-frequency anchoring increases the recovered synchrotron amplitude: at 4.76 GHz, it is approximately a factor of two higher than the Pla
For monitoring the night sky conditions, wide-angle all-sky cameras are used in most astronomical observatories to monitor the sky cloudiness. In this manuscript, we apply a deep-learning approach for automating the identification of precipitation clouds in all-sky camera data as a cloud warning system. We construct our original training and test sets using the all-sky camera image archive of the Iranian National Observatory (INO). The training and test set images are labeled manually based on their potential rainfall and their distribution in the sky. We train our model on a set of roughly 2445 images taken by the INO all-sky camera through the deep learning method based on the EfficientNet network. Our model reaches an average accuracy of 99\% in determining the cloud rainfall's potential and an accuracy of 96\% for cloud coverage. To enable a comprehensive comparison and evaluate the performance of alternative architectures for the task, we additionally trained three models LeNet, DeiT, and AlexNet. This approach can be used for early warning of incoming dangerous clouds toward telescopes and harnesses the power of deep learning to automatically analyze vast amounts of all-sky c
A deep, space-based, all-sky near-infrared survey carried out with the Nancy Grace Roman Space Telescope would constitute a foundational astronomical infrastructure for decades to come. In this white paper, we present a concrete and feasible path to imaging the entire sky at $\sim0.1''$ resolution, beginning with high-impact fields in Cycle 1 and scaling to ultra-wide coverage within the nominal mission. This first-epoch survey will reach $\mathrm{H}\sim25.5$ AB mag (5$σ$) and maximize synergies with contemporaneous observatories, while preserving substantial time for other ambitious Roman programs. We outline representative scheduling scenarios and an example Cycle 1 program that triples early Roman-LSST overlap and delivers high-value community data products such as LSST forced photometry, joint \textit{Gaia}-Roman astrometry, and catalogs of Galactic substructure, stong lenses, and other rare systems. The Cycle 1 program will lay the foundation for an eventual all-sky survey, while also delivering high-impact early science. We invite broad community participation in shaping and carrying out both the initial program and the long-term vision of an all-sky Roman survey.
Techniques using multiple tracers of the large scale structure of the universe show great promise for examining the fundamentals of our Universe's cosmology. Such techniques rely on the different relationship between the overdensity of tracers and the broader matter overdensity, enabling cosmic-variance-free tests of primordial non-Gaussianity in the initial curvature perturbations. There is a great opportunity for current and future all-sky extra-galactic radio surveys to make use of this technique to test for non-Gaussianity at a precision greater than existing all-sky constraints from the cosmic microwave background. To realize this goal there is a need for accurate simulations. Previous radio galaxy simulations have either been realistic but covering only a small area (and so unhelpful for cosmological forecasts), or all-sky dark matter only cosmological simulations but having no connection to a real radio galaxy population. In this study, we use the FLAMINGO suite of cosmological surveys, as well as the matching of dark matter halos to radio galaxy population, to create an accurate sky simulation in order to examine the feasibility of multi-tracer techniques. We present an ana
A high-precision calibration method for all-sky cameras has been realized using images from the Ali observatory in Tibet, providing application results for atmospheric extinction, night sky brightness, and known variable stars. This method achieves high-precision calibration for individual all-sky images, with the calibration process introducing deviations of less than 0.5pixels. Within a 70-degree zenith angle, the calibration deviation of the images is less than 0.25pixels. Beyond this angle, the calibration deviation increases significantly due to the sparser distribution of stars. Increasing the number of stars with zenith angles greater than 70degrees used for calibration can improve the calibration accuracy for areas beyond the 70-degree zenith angle, reducing the calibration deviation at an 85-degree zenith angle to 0.2pixels. Analysis of the all-sky images indicates that the atmospheric extinction coefficient at the Ali Observatory is approximately 0.20, and the night sky background brightness is about 21 magnitudes per square arcsecond, suggesting the presence of urban light pollution.
Between the estimated population of Neutron Stars (NSs) and the actual number present in the catalogs, there is a huge gap: O(10$^{8-9}$) vs O(10$^3$). Among the different search techniques for Continuous gravitational waves (CWs), the all-sky could help to reduce the discrepancy. We focus on the all-sky CW pipeline Frequency Hough (FH), which operates without prior knowledge of the source parameters ($f,\dot{f}, λ, β$). Here, we present a Machine Learning strategy, diverging from the standard follow-up(FU) of the FH pipeline. We study the performance with real interferometer data, until reaching $h$ value subthreshold for the standard FU procedure ($CR_{thr}=5$), with encouraging classification results.
Detecting continuous gravitational waves is challenging due to the high computational cost of template-based searches across large parameter spaces, particularly for all-sky searches. Machine learning offers a promising solution to perform these searches with reasonable computational resources. In this study, we trained an attention U-Net, a convolutional neural network, on $\approx$ 10.67 days of simulated data with Gaussian noise for all-sky searches at different frequencies within the 20-1000 Hz band. Our model trained at 20 Hz achieves the best sensitivity, with a 90% detection efficiency sensitivity depth $D^{90\%} = 29.97 \pm 0.24\,\mathrm{Hz}^{-1/2}$ with a 1% false alarm rate per 50 mHz, while the model trained on the entire 20-1000 Hz band yields $D^{90\%} = 18.63 \pm 0.24\,\mathrm{Hz}^{-1/2}$. The sensitivities achieved are comparable to state-of-the-art results using deep learning approaches, with less than 50% of the training time and data. We find that sensitivity scales as $T^{0.28 \pm 0.01}$ with total observation time for the attention U-Net trained at 20 Hz, similar to semi-coherent search methods. The neural network demonstrates robustness on datasets with time ga
Light pollution, a rapidly escalating anthropogenic phenomenon driven by the excessive and often inefficient use of artificial lighting, has profound implications for astronomy, ecology, and human health. This study presents the first comprehensive characterization of night sky quality in Colombia, focusing on sites of astronomical and ecological significance. The selected locations include the Astronomical Observatory of UTP, the Tatacoa Desert, the Bogotá Botanical Garden, and Cerro Guadalupe. Utilizing the Sky Quality Camera, we collected all-sky data to measure surface brightness and correlated color temperature of the night sky. Our findings reveal a significant loss of natural sky visibility in urban areas and demonstrate the detrimental effects of artificial lighting on critical astronomical sites such as La Tatacoa. This study provides a crucial foundation for future research and informs the development of public policies aimed at preserving the night sky.
Fast Radio Bursts (FRBs) are short-duration radio transients that occur at random times in host galaxies distributed all over the sky. Large field of view instruments can play a critical role in the blind search for rare FRBs. We present a concept for an all-sky FRB monitor using a compact all-sky phased array (CASPA), which can efficiently achieve an extremely large field of view of $\sim10^4$ square degrees. Such a system would allow us to conduct a continuous, blind FRB search covering the entire southern sky. Using the measured FRB luminosity function, we investigate the detection rate for this all-sky phased array and compare the result to a number of other proposed large field-of-view instruments. We predict a rate of a few FRB detections per week and determine the dispersion measure and redshift distributions of these detectable FRBs. This instrument is optimal for detecting FRBs in the nearby Universe and for extending the high-end of the FRB luminosity function through finding ultraluminous events. Additionally, this instrument can be used to shadow the new gravitational-wave observing runs, detect high energy events triggered from Galactic magnetars and search for other b
The Transiting Exoplanet Survey Satellite (TESS) mission has observed hundreds of millions of stars, substantially contributing to the available pool of high-precision photometric space data. Among them are the relatively rare $γ$ Doradus / $δ$ Scuti ($γ$ Dor / $δ$ Sct) hybrid pulsators, which have been previously studied using Kepler data. These stars are perfect laboratories to probe both inner and outer interior stellar layers thanks to them exhibiting both pressure and gravity modes. We seek to classify an all-sky sample of AF stars observed by TESS to find previously undiscovered hybrid pulsators and supply them in a catalogue of candidates. We also aim to compare the light curves produced with the TESS-Gaia Light Curve (TGLC) pipeline, currently underused in variability studies, with other publicly available light curves. We compared dominant and secondary frequencies of confirmed hybrid pulsators in Kepler, extended mission Quick Look Pipeline (QLP) data, and nominal and extended mission TGLC data. We then used a feature-based positive unlabelled (PU) learning classifier to search for new hybrid pulsators amongst TESS AF stars and investigated the properties of the detected
Modeling the hemispherical night sky brightness of anthropogenic origin is a demanding computational challenge, due to the intensive calculations required to produce all-sky maps with fine angular resolution including high-order scattering effects. We present in this Letter a physically consistent, semi-analytic two-parameter model of the all-sky radiance produced by an artificial light source that encodes efficiently the spectral radiance in all directions of the sky above the observer. The two parameters of this function are derived from the state of the atmosphere, the distance to the observer, and the source's angular and spectral emission pattern. The anthropogenic all-sky radiance at any place on Earth can be easily calculated by adding up the contributions of the surrounding artificial sources, using the information available from nighttime satellite imagery and ground-truth lighting inventories. This opens the way for the elaboration of a global world map of the artificial all-sky brightness.
We present novel techniques and methodology for unresolved photometric characterization of low-Earth Orbit (LEO) satellites. With the Pomenis LEO Satellite Photometric Survey our team has made over 14,000 observations of Starlink and OneWeb satellites to measure their apparent brightness. From the apparent brightness of each satellite, we calculate a new metric: the effective albedo, which quantifies the specularity of the reflecting satellite. Unlike stellar magnitude units, the effective albedo accounts for apparent range and phase angle and enables direct comparison of different satellites. Mapping the effective albedo from multiple observations across the sky produces an all-sky photometric signature which is distinct for each population of satellites, including the various sub-models of Starlink satellites. Space Situational Awareness (SSA) practitioners can use all-sky photometric signatures to differentiate populations of satellites, compare their reflection characteristics, identify unknown satellites, and find anomalous members. To test the efficacy of all-sky signatures for satellite identification, we applied a machine learning classifier algorithm which correctly identi
This article provides detailed description on the fundamentals of aperture photometry analysis. The differential and all-sky aperture photometry techniques are described thoroughly to depict the difference between the two techniques and their selection for determining the stars' magnitudes and their respective magnitude errors. The crucial calibration parameters required for the all-sky photometry analysis such as atmospheric extinctioncoefficient, air-mass, zero point, color term and color index are discussed comprehensively with their extraction from the Sloan Digital Sky Survey (SDSS) archive. The all-sky aperture photometry technique is applied on the stars of an open cluster NGC 2420 to determine their calibrated magnitudes and magnitude errors in the g, r, and i bands. The images required for the analysis are extracted from data release DR12 of SDSS III archive. Herein, the photometry analysis is performed by the Makali'i: SUBARU Image Processor, a Windows-based software. This software has a simple yet effective GUI and it provides the starlight minus the background sky light value with a single click. This article would aid in providing the insight into the physics of apertu
The C-Band All-Sky Survey (C-BASS) is an all-sky full-polarisation survey at a frequency of 5 GHz, designed to provide complementary data to the all-sky surveys of WMAP and Planck, and future CMB B-mode polarization imaging surveys. The observing frequency has been chosen to provide a signal that is dominated by Galactic synchrotron emission, but suffers little from Faraday rotation, so that the measured polarization directions provide a good template for higher frequency observations, and carry direct information about the Galactic magnetic field. Telescopes in both northern and southern hemispheres with matched optical performance are used to provide all-sky coverage from a ground-based experiment. A continuous-comparison radiometer and a correlation polarimeter on each telescope provide stable imaging properties such that all angular scales from the instrument resolution of 45 arcmin up to full sky are accurately measured. The northern instrument has completed its survey and the southern instrument has started observing. We expect that C-BASS data will significantly improve the component separation analysis of Planck and other CMB data, and will provide important constraints on
We report on a ~5th magnitude flash detected for approximately 10 minutes by two CONCAM all-sky cameras located in Cerro Pachon - Chile and La Palma - Spain. A third all-sky camera, located in Cerro Paranal - Chile did not detect the flash, and therefore the authors of this paper suggest that the flash was a series of cosmic-ray hits, meteors, or satellite glints. Another proposed hypothesis is that the flash was an astronomical transient with variable luminosity. In this paper we discuss bright optical transient detection using fish-eye all-sky monitors, analyze the apparently false-positive optical transient, and propose possible causes to false optical transient detection in all-sky cameras.
The BATSE mission aboard CGRO monitored the whole sky in the 20 keV - 1 MeV energy band continuously from April 1991 until June 2000. Although BATSE had very poor intrinsic angular resolution, the data can be used to survey the entire soft gamma-ray sky with < 1 degree angular resolution and ~ 1 mCrab sensitivity by using the Earth occultation method. This method determines flux by measuring the step in the count rate profile in each BATSE detector as a source rises above or sets below the Earth's limb. A maximum likelihood imaging technique can then be used to build up all-sky maps from the images of the Earth's limb produced by occulting sources. However, since the Earth seen from BATSE has a radius of ~ 70 degrees, the limb images that intersect at the positions of bright point sources have a significant effect over the area of the all-sky map. A method for performing image cleaning on likelihood data has also been developed and is used to effectively remove artefacts from the all-sky maps. This paper describes the 'LIMBO' imaging technique and presents preliminary all-sky maps of 25 - 160 keV emission, the first to be made since the HEAO1-A4 mission of 1978-79.
Most ground-based observatories are equipped with wide-angle all-sky cameras to monitor the night sky conditions. Such camera systems can be used to provide early warning of incoming clouds that can pose a danger to the telescope equipment through precipitation, as well as for sky quality monitoring. We investigate the use of different machine learning approaches for automating the identification of mostly opaque clouds in all-sky camera data as a cloud warning system. In a deep-learning approach, we train a Residual Neural Network (ResNet) on pre-labeled camera images. Our second approach extracts relevant and localized image features from camera images and uses these data to train a gradient-boosted tree-based model (lightGBM). We train both model approaches on a set of roughly 2,000 images taken by the all-sky camera located at Lowell Observatory's Discovery Channel Telescope, in which the presence of clouds has been labeled manually. The ResNet approach reaches an accuracy of 85% in detecting clouds in a given region of an image, but requires a significant amount of computing resources. Our lightGBM approach achieves an accuracy of 95% with a training sample of ~1,000 images an
Identified radio supernova remnants (SNRs) in the Galaxy comprise an incomplete sample of the SNR population due to various selection effects. ROSAT performed the first all-sky survey with an imaging X-ray telescope, and thus provides another window for finding SNRs and compact objects that may reside within them. Performing a search for extended X-ray sources in the ROSAT all-sky survey database about 350 objects were identified as SNR candidates in recent years (Busser 1998). Continuing this systematic search, we have reanalysed the ROSAT all-sky survey (RASS) data of these candidates and correlated the results with radio surveys like NVSS, ATNF, Molonglo and Effelsberg. A further correlation with SIMBAD and NED was performed for subsequent identification purposes. About 50 of the 350 candidates turned out to be likely galaxies or clusters of galaxies. We found 14 RASS sources which are very promising SNR candidates and are currently subject of further follow-up studies. We will provide the details of the identification campaign and present first results.
The C-Band All-Sky Survey (C-BASS) is an all-sky full-polarization survey at a frequency of 5 GHz, designed to provide data complementary to the all-sky surveys of WMAP and Planck and future CMB B-mode polarization imaging surveys. We describe the design and performance of the digital backend used for the northern part of the survey. In particular we describe the features that efficiently implement the demodulation and filtering required to suppress contaminating signals in the time-ordered data, and the capability for real-time correction of detector non-linearity and receiver balance.
We present the results of applying a percolation algorithm to the initial release of the Two Micron All-Sky Survey Extended Source Catalog, using subsequently measured redshifts for almost all of the galaxies with K < 11.25 mag. This group catalog is based on the first near-IR all-sky flux-limited survey that is complete to |b| = 5 deg. We explore the dependence of the clustering on the length and velocity scales involved. The paper describes a group catalog, complete to a limiting redshift of 10,000 km/s, created by maximizing the number of groups containing 3 or more members. A second catalog is also presented, created by requiring a minimum density contrast of 80 to identify groups. We identify known nearby clusters in the catalogs and contrast the groups identified in the two catalogs. We examine and compare the properties of the determined groups and verify that the results are consistent with the UZC-SSRS2 and northern CfA redshift survey group catalogs. The all-sky nature of the catalog will allow the development of a flow-field model based on the density field inferred from the estimated cluster masses.