Astronomical Software Research Articles

Controlling Randomization in Astronomy Simulations

As the primary requirement, correctly implementing and controlling random number generation is vital for a range of scientific analyses and simulations across astronomy and planetary science. Beyond advice on how to set the seed, there is little guidance in the literature for how best to handle pseudo-random number generation in the current era of open-source astronomical software development. We present our methodology for implementing a pseudo-random number generation in astronomy simulations and software and share the short lines of python code that create the generator. Without sacrificing randomization at run time, our strategy ensures reproducibility on a per function/module basis for unit testing and for run time debugging where there may be multiple functions requiring lists of randomly generated values that occur before a specific function is executed.

Mathematical modeling of velocity and accelerations fields of image motion in the optical equipment of the Earth remote sensing satellite

Objectives. The paper considers a satellite with an optoelectronic payload designed to take pictures of the Earth’s surface. The work sets out to develop a mathematical model for determining the dependencies between the state vector of the satellite, the state vector of the point being imaged on the Earth’s surface, and the distribution fields of the velocity vectors and accelerations of the motion of the image along the focal plane of the optoelectronic payload.Methods. The method is based on double differentiation of the photogrammetry equation when applied to a survey of the Earth’s surface from space. For modeling the orbital and angular motion of the satellite, differential equations with numerical integration were used. The motion parameters of the Earth’s surface were calculated based on the Standards of Fundamental Astronomy software library.Results. Differential equations of motion of the image were obtained. Verification of the developed mathematical model was carried out. The motion of the considered satellite was simulated in orbital orientation mode using an image velocity compensation model. The distribution fields of velocity vectors and accelerations of motion of the image of the Earth’s surface were constructed. The residual motion of the field of image following compensation was investigated.Conclusions. The proposed mathematical model can be used both with an optoelectronic payload when modeling shooting modes and estimating image displacements at the design stage of a satellite, as well as at the satellite operation stage when incorporating the presented model in the onboard satellite software. The presented dependencies can also be used to construct an image transformation matrix, both when restoring an image and when obtaining a super-resolution.

An optimized transient detection pipeline for the ASKAP Variables and Slow Transients (VAST) survey

ABSTRACT In this paper, we present an optimized version of the detection pipeline for the ASKAP Variables and Slow Transients (VAST) survey, offering significant performance improvement. The key to this optimization is the replacement of the original w-projection algorithm integrated in the Common Astronomy Software Applications package with the w-stacking algorithm implemented in the WSClean software. Our experiments demonstrate that this optimization improves the overall processing efficiency of the pipeline by approximately a factor of 3. Moreover, the residual images generated by the optimized pipeline exhibit lower noise levels and fewer artefact sources, suggesting that our optimized pipeline not only enhances detection accuracy but also improves imaging fidelity. This optimized VAST detection pipeline is integrated into the Data Activated Liu Graph Engine (DALiuGE) execution framework, specifically designed for SKA-scale big data processing. Experimental results show that the performance and scalability advantages of the pipeline using DALiuGE over traditional MPI or BASH techniques increase with the data size. In summary, the optimized transient detection pipeline significantly reduces runtime, increases operational efficiency, and decreases implementation costs, offering a practical optimization solution for other ASKAP imaging pipelines as well.

Astrophot: fitting everything everywhere all at once in astronomical images

ABSTRACT We present astrophot, a fast, powerful, and user-friendly python based astronomical image photometry solver. astrophot incorporates automatic differentiation and graphics processing unit (GPU), or parallel central processing unit (CPU), acceleration, powered by the machine learning library pytorch. Everything: astrophot can fit models for sky, stars, galaxies, point spread functions (PSFs), and more in a principled χ2 forward optimization, recovering Bayesian posterior information and covariance of all parameters. Everywhere: astrophot can optimize forward models on CPU or GPU; across images that are large, multiband, multi-epoch, rotated, dithered, and more. All at once: The models are optimized together, thus handling overlapping objects and including the covariance between parameters (including PSF and galaxy parameters). A number of optimization algorithms are available including Levenberg–Marquardt, Gradient descent, and No-U-Turn Markov chain Monte Carlo sampling. With an object-oriented user interface, astrophot makes it easy to quickly extract detailed information from complex astronomical data for individual images or large survey programs. This paper outlines novel features of the astrophot code and compares it to other popular astronomical image modelling software. astrophot is open-source, fully python based, and freely accessible at https://github.com/Autostronomy/AstroPhot .

Plan of prehistoric stilt village in Maranhão Brazil may resemble the Pleiades

Archaeological surveys conducted in the Maranhão estuaries of Brazil, near the Atlantic coast, revealed the remnants of 21 prehistoric stilt villages constructed on piles of Tabebuia handroanthrus hardwood above three seasonal flood water estuaries. Radiocarbon dates of 27 samples from 11 of those sites yielded an Archaic Period of construction (6622 ± 119 calibrated years before present) followed much later by consecutive construction periods from approximately the first century B.C. to the thirteenth century A.D. (1994 to 728 cal. yrs BP). The Formoso site—currently dated as the longest occupied site (1509 to 930 cal. yrs BP)—yielded early Incised-Punctate/Arauquinoid pottery, a previously unreported pottery style in the Amazon region. Additionally, using StarryNight astronomy software, the night sky at Formoso was compared with a map of the pile dwelling layout, revealing a statistically significant resemblance to the Pleiades. This paper focuses on the Formoso site, suggesting that it may have served cultural significance to the Pleiades as early evidence for the later widespread ethnographic use of the star cluster’s annual sighting to mark the seasonal flood cycles and the management of agricultural and ecological activities throughout tropical South America.

The ALMA Interferometric Pipeline Heuristics

We describe the calibration and imaging heuristics developed and deployed in the Atacama Large Millimeter/submillimeter Array (ALMA) interferometric data processing pipeline, as of ALMA Cycle 9 operations. The pipeline software framework is written in Python, with each data reduction stage layered on top of tasks and toolkit functions provided by the Common Astronomy Software Applications package. This framework supports a variety of tasks for observatory operations, including science data quality assurance, observing mode commissioning, and user reprocessing. It supports ALMA and Very Large Array interferometric data along with ALMA and NRO 45 m single dish data, via different stages and heuristics. In addition to producing calibration tables, calibrated measurement sets, and cleaned images, the pipeline creates a WebLog which serves as the primary interface for verifying the quality assurance of the data by the observatory and for examining the contents of the data by the user. Following the adoption of the pipeline by ALMA Operations in 2014, the heuristics have been refined through annual prioritized development cycles, culminating in a new pipeline release aligned with the start of each ALMA Cycle of observations. Initial development focused on basic calibration and flagging heuristics (Cycles 2–3), followed by imaging heuristics (Cycles 4–5). Further refinement of the flagging and imaging heuristics, including the introduction of parallel processing, proceeded for Cycles 6–7. In the 2020 release, the algorithm to identify channels to use for continuum subtraction and imaging was substantially improved by the addition of a moment difference analysis. A spectral renormalization stage was added for the 2021 release (Cycle 8) to correct high spectral resolution visibility data acquired on targets exhibiting strong celestial line emission in their autocorrelation spectra. The calibration heuristics used in the low signal-to-noise regime were improved for the 2022 release (Cycle 9). In the two most recent Cycles, 97% of ALMA data sets were calibrated and imaged with the pipeline, ensuring long-term automated reproducibility of results. We conclude with a brief description of plans for future additions, including a self-calibration stage, support for multi-configuration imaging, and complete calibration and imaging of full polarization data.

Challenging interferometric imaging: Machine learning-based source localization from uv-plane observations

Context. Rising interest in radio astronomy and upcoming projects in the field is expected to produce petabytes of data per day, questioning the applicability of traditional radio astronomy data analysis approaches under the new large-scale conditions. This requires new, intelligent, fast, and efficient methods that potentially involve less input from the domain expert. Aims. In our work, we examine, for the first time, the possibility of fast and efficient source localization directly from the uv-observations, omitting the recovering of the dirty or clean images. Methods. We propose a deep neural network-based framework that takes as its input a low-dimensional vector of sampled uv-data and outputs source positions on the sky. We investigated a representation of the complex-valued input uv-data via the real and imaginary and the magnitude and phase components. We provided a comparison of the efficiency of the proposed framework with the traditional source localization pipeline based on the state-of-the-art Python Blob Detection and Source Finder (PyBDSF) method. The investigation was performed on a data set of 9164 sky models simulated using the Common Astronomy Software Applications (CASA) tool for the Atacama Large Millimeter Array (ALMA) Cycle 5.3 antenna configuration. Results. We investigated two scenarios: (i) noise-free as an ideal case and (ii) sky simulations including noise representative of typical extra-galactic millimeter observations. In the noise-free case, the proposed localization framework demonstrates the same high performance as the state-of-the-art PyBDSF method. For noisy data, however, our new method demonstrates significantly better performance, achieving a completeness level that is three times higher for sources with uniform signal-to-noise ratios (S/N) between 1 and 10, and a high increase in completeness in the low S/N regime. Furthermore, the execution time of the proposed framework is significantly reduced (by factors ~30) as compared to traditional methods that include image reconstructions from the uv-plane and subsequent source detections. Conclusions. The proposed framework for obtaining fast and efficient source localization directly from uv-plane observations shows very encouraging results, which could open new horizons for interferometric imaging with existing and future facilities.

CELEBI: The CRAFT Effortless Localisation and Enhanced Burst Inspection pipeline

Fast radio bursts (FRBs) are being detected with increasing regularity. However, their spontaneous and often once-off nature makes high-precision burst position and frequency–time structure measurements difficult without specialised real-time detection techniques and instrumentation. The Australian Square Kilometre Array Pathfinder (ASKAP) has been enabled by the Commensal Real-time ASKAP Fast Transients Collaboration (CRAFT) to detect FRBs in real-time and save raw antenna voltages containing FRB detections. We present the CRAFT Effortless Localisation and Enhanced Burst Inspection pipeline (CELEBI), an automated offline software pipeline that extends CRAFT’s existing software to process ASKAP voltages in order to produce sub-arcsecond precision localisations and polarimetric data at time resolutions as fine as 3ns of FRB events. We use Nextflow to link together Bash and Python code that performs software correlation, interferometric imaging, and beamforming, making use of common astronomical software packages.

Moliverse: Contextually embedding the microcosm into the universe

We present Moliverse, an integration of the molecular visualization framework VIAMD into the astronomical visualization software OpenSpace, allowing us to bridge the two extreme ends of the scale spectrum to show, for example, the gas composition in a planet’s atmosphere or molecular structures in comet trails and can empower the creation of educational exhibitions. For that purpose we do not use a linear scale traversal but break the scale continuity and show molecular simulations as focus in the context of celestial bodies. We demonstrate the application of our concept in two storytelling scenarios and envision the application both for science presentations to lay audiences and for dedicated exploration, potentially also in a molecule-only environment.

Resolving the Bow Shock and Tail of the Cannonball Pulsar PSR J0002+6216

We present X-ray and radio observations of the recently discovered bow-shock pulsar wind nebula (PWN) associated with PSR J0002+6216, characterizing the PWN morphology, which was unresolved in previous studies. The multifrequency, multiepoch Very Large Array (VLA) radio observations reveal a cometary tail trailing the pulsar and extending up to 5.′3, with multiple kinks along the emission. The presented radio continuum images from multiconfiguration broadband VLA observations are one of the first results from the application of multiterm multifrequency synthesis deconvolution in combination with the AWProject gridder implemented in the Common Astronomy Software Applications (CASA) package. The X-ray emission observed with Chandra extends to only 21″, fades quickly, and has some hot spots present along the extended radio emission. These kinks could indicate the presence of density variations in the local interstellar medium or turbulence. The bow-shock standoff distance estimates a small bow-shock region with a size of 0.003–0.009 pc, consistent with the pulsar spin-down power of = 1.51 × 1035 erg s−1 estimated from timing. The high-resolution radio image reveals the presence of an asymmetry in the bow-shock region, which is also present in the X-ray image. The broadband radio image shows an unusually steep spectrum along with a flat-spectrum sheath, which could indicate varying opacity or energy injection into the region. Spatially resolved X-ray spectra provide marginal evidence of synchrotron cooling along the extended tail. Our analysis of the X-ray data also shows that this pulsar has a low spin-down power and one of the lowest X-ray efficiencies observed in these objects.

中国SKA区域中心原型系统——软件平台

The Square Kilometre Array (SKA) radio telescope is designed to revolutionize scientific breakthroughs in a variety of scientific fields, and the SKA software system is one of the key factors influencing scientific products. The software environment for processing SKA science data must be versatile, flexible, and adaptable. The SKA Regional Centre (SRC) serves as a platform for astronomers to analyze SKA data, conduct scientific research, and interact with other academics. To enable automated parallel processing of observational data from various scientific fields, Chinese scientists have developed the China SRC-prototype (CSRC-P), installed a job scheduling system widely used by large supercomputers, installed an astronomical software platform capable of processing observational data from current leading radio telescopes, and deployed multiple scientific data processing pipelines. This paper describes the software platform of the CSRC-P as well as pipelines for processing SKA precursor telescope data, such as the low-frequency continuum imaging pipeline, spectral line imaging pipeline, and very long baseline interferometry data processing pipeline. Users worldwide have successfully conducted scientific research on SKA using this platform. The knowledge gained from the construction and operation of this platform will be useful in constructing a full-scale SRC in the future.

Connection Between the Comet 1P/Halley Appearance in 760 AD and the Dinoyo Inscription (Preliminary Result)

AbstractAccording to many historical records, 1P/Halley comet was reported to appear in 760 AD. In the same year in Indonesia, the Dinoyo inscription told us the story of the Kanjuruhan kingdom which held a Vedic ceremony to purify a new shrine and statue of Agastya to repel enemy forces (or dispel the epidemic). Many traditions believe that the appearance of a comet is a sign of war, plague/epidemic, death, etc. By applying this understanding to the archaeoastronomical framework, the hypothesis is proposed, that the king’s order which was written on the inscription shows the response to the 1P/Halley comet appearance in 760 AD. There are three ways to examine the hypothesis: by testing the chronological, geographical, and cultural aspects. Through some literature studies and the Stellarium Astronomy Software simulation, the initial research found that the chronological and geographical aspects support the hypothesis.

CASA, the Common Astronomy Software Applications for Radio Astronomy

CASA, the Common Astronomy Software Applications, is the primary data processing software for the Atacama Large Millimeter/submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array (VLA), and is frequently used also for other radio telescopes. The CASA software can handle data from single-dish, aperture-synthesis, and Very Long Baseline Interferometery (VLBI) telescopes. One of its core functionalities is to support the calibration and imaging pipelines for ALMA, VLA, VLA Sky Survey, and the Nobeyama 45 m telescope. This paper presents a high-level overview of the basic structure of the CASA software, as well as procedures for calibrating and imaging astronomical radio data in CASA. CASA is being developed by an international consortium of scientists and software engineers based at the National Radio Astronomy Observatory (NRAO), the European Southern Observatory, the National Astronomical Observatory of Japan, and the Joint Institute for VLBI European Research Infrastructure Consortium (JIV-ERIC), under the guidance of NRAO.

Broad band flux-density monitoring of radio sources with the Onsala twin telescopes

The Onsala twin telescopes (OTT) are two 13 m telescopes located at the Onsala Space Observatory in Sweden. With dual linear polarized broad-band (3-14 GHz) receivers, they are part of the next generation Very Long Baseline Interferometry (VLBI) Global Observing System (VGOS) for geodesy and astrometry. In addition to purely geodetic data products, VGOS will regularly produce full-polarisation images of hundreds of radio sources. These rich monitoring data will be valuable for both astronomy and geodesy. In this pilot study we aimed at monitoring ten bright radio sources to search for flares or similar activity, and at testing the instrument calibration on long (months) and short (hours) time scales. Using the OTT as a standalone instrument, we observed and analysed 91 short (<30 min) sessions spanning seven months. We monitored seven potentially variable radio sources (0059+581, 0552+398, 1144+402, 1156+295, 1617+229, 3C418, OJ287) and three reference calibrators (3C147, 3C286, 3C295). We used the Common Astronomy Software Applications (CASA) package to fringe-fit, bandpass-correct and scale the data to obtain flux densities in the four standard VGOS bands: 3.0-3.5 GHz (band 1), 5.2-5.7 GHz (band 2), 6.3-6.8 GHz (band 3), and 10.2-10.7 GHz (band 4). We obtained simultaneous multi-frequency light curves for ten radio sources. A bright multi-frequency flare is observed in the radio source 0059+581. OJ287 and 1156+295 show significant long-term variability in their light curves. After correcting for instrumental biases, we determine the empirical flux density uncertainty as sim5 %.

Discovery of an optical cocoon tail behind the runaway HD 185806

ABSTRACT Studies on the circumstellar structures around evolved stars provide vital information on the evolution of the parent star and the properties of the local interstellar medium. In this work, we present the discovery and characterization of an optical cocoon tail behind the star HD 185806. The cocoon apex emission is puzzling, as it is detected in the infrared but shows no signal in the optical wavelength. The H α and [O iii] fluxes of the nebular structure vary from 2.7 to 8.5 × 10−12 erg s−1 cm−2 and from 0.9 to 7.0 × 10−13 erg s−1 cm−2, respectively. Through high-resolution spectroscopy, we derive the spectral type of the star, construct the position–velocity diagrams of the cocoon tail for the H α, [O iii], and [N ii] emission lines, and determine its velocity in the range of −100–40 km s−1. Furthermore, we use SED fitting and mesa evolutionary models adopting a distance of 900 pc, and classify HD 185806 as a 1.3 M⊙ star, in the transition phase between the RGB and early AGB stages. Finally, we study the morpho-kinematic structure of the cocoon tail using the astronomical software SHAPE. An ellipsoidal structure, with an inclination of ∼19° with respect to the plane of sky is found to better reproduce the observed cocoon tail of HD 185806.

Astronomy for Precise Positioning and Stellarium

Astronomy studies the Universe as a whole. Astronomy is the science that studies the origin and evolution of the Universe and everything in it. The present study discussed on the application of astronomy in general and explored its application on precise positioning specifically. Calendars, computers, communication satellites, navigation systems, mathematics, trigonometry, solar panels, wireless internet, culture and religions, and many other technological applications development such as aerospace, Global Navigation Satellite System (GNSS) or precise positioning, solar and nuclear energy, medicine, and many other technological applications development are all examples of astronomy. The study is conducted based on secondary information and astronomical observation using virtual application software. This paper also introduced the astronomical application software stellarium. The study shows that the astronomical knowledge and techniques are very useful for precise positioning.

Apercal—The Apertif calibration pipeline

Apertif (APERture Tile In Focus) is one of the Square Kilometre Array (SKA) pathfinder facilities. The Apertif project is an upgrade to the 50-year-old Westerbork Synthesis Radio Telescope (WSRT) using phased-array feed technology. The new receivers create 40 individual beams on the sky, achieving an instantaneous sky coverage of 6.5 square degrees. The primary goal of the Apertif Imaging Survey is to perform a wide survey of 3500 square degrees (AWES) and a medium deep survey of 350 square degrees (AMES) of neutral atomic hydrogen (up to a redshift of 0.26), radio continuum emission and polarisation. Each survey pointing yields 4.6 TB of correlated data. The goal of Apercal is to process this data and fully automatically generate science ready data products for the astronomical community while keeping up with the survey observations. We make use of common astronomical software packages in combination with Python based routines and parallelisation. We use an object oriented module-based approach to ensure easy adaptation of the pipeline. A Jupyter notebook based framework allows user interaction and execution of individual modules as well as a full automatic processing of a complete survey observation. If nothing interrupts processing, we are able to reduce a single pointing survey observation on our five node cluster with 24 physical cores and 256 GB of memory each within 24h keeping up with the speed of the surveys. The quality of the generated images is sufficient for scientific usage for 44 % of the recorded data products with single images reaching dynamic ranges of several thousands. Future improvements will increase this percentage to over 80 %. Our design allowed development of the pipeline in parallel to the commissioning of the Apertif system.

An empirical evaluation on the applicability of the DALiuGE execution framework

The Square Kilometre Array (SKA) project is an international cooperation project to build the largest radio telescope worldwide. Data processing is one of the biggest challenges of building the SKA telescope. As a distributed execution framework, the Data Activated Liu Graph Engine (DALiuGE) was proposed to be one of the candidates for addressing the massive data of the SKA. DALiuGE has many distinctive features, but its actual ability to handle scientific data is still not clear. In this paper, we perform an objective evaluation of the usability of DALiuGE for the execution performance, developer workload, and implementation difficulty of porting the SAGECal to DALiuGE. The evaluation results show that the DALiuGE enables fast integration of astronomical software, but there are significant differences in the efficiency of different parallel granularities. Even with the deep optimization of the program, there is still a gap between the current DALiuGE and the traditional MPI in execution performance. Therefore, we come to a preliminary conclusion that the DALiuGE has no performance advantage in batch processing of massive data. At the same time, it may be more suitable for application scenarios with more customized computational tasks, such as SKA science regional centers.

Fine-grained distributed averaging for large-scale radio interferometric measurement sets

The Square Kilometre Array (SKA) would be the world’s largest radio telescope with eventually over a square kilometre of collecting area. However, there are enormous challenges in its data processing. The use of modern distributed computing techniques to solve the problem of massive data processing in the SKA is one of the most important challenges. In this study, basing on the Dask distribution computational framework, and taking the visibility function integral processing as an example, we adopt a multi-level parallelism method to implement distributed averaging over time and channel. Dask Array was used to implement super large matrix or arrays with supported parallelism. To maximize the usage of memory, we further exploit the data parallelism provided by Dask that intelligently distributes the computational load across a network of computer agents and has a built-in fault tolerance mechanism. The validity of the proposed pattern was also verified by using the Common Astronomy Software Application (CASA), wherein we analyze the smearing effects on images reconstructed from different resolution visibilities.

Offline Correction of Atmospheric Effects on Single-dish Radio Spectroscopy

We present a method to mitigate the atmospheric effects (residual atmospheric lines) in single-dish radio spectroscopy caused by the elevation difference between the target and reference positions. The method is developed as a script using the Atmospheric Transmission at Microwaves (ATM) library built into the Common Astronomy Software Applications (CASA) package. We apply the method to the data taken with the Total Power Array of the Atacama Large Millimeter/submillimeter Array. The intensities of the residual atmospheric (mostly O3) lines are suppressed by, typically, an order of magnitude for the tested cases. The parameters for the ATM model can be optimized to minimize the residual line and, for a specific O3 line at 231.28 GHz, a seasonal dependence of a best-fitting model parameter is demonstrated. The method will be provided as a task within the CASA package in the near future. The atmospheric removal method we developed can be used by any radio/millimeter/submillimeter observatory to improve the quality of its spectroscopic measurements.