Weekly Update from the Open Journal of Astrophysics – 28/06/2025
It’s Saturday morning again so time for an update of papers published at the Open Journal of Astrophysics. Since the last update we have published eight new papers, which brings the number in Volume 8 (2025) up to 82, and the total so far published by OJAp up to 317. With about half the year gone, we’re on target to published around 160 papers this year.
The papers published this week, with their overlays, are as follows. You can click on the images of the overlays to make them larger should you wish to do so.
The first paper to report is “Spectroscopic and X-ray Modeling of the Strong Lensing Galaxy Cluster MACS J0138.0-2155” by Abigail Flowers (University of California at Santa Cruz; UCSZ), Jackson H. O’Donnell (UCSZ), Tesla E. Jeltema (UCSZ), Vernon Wetzell (U. Pennsylvania) & M. Grant Roberts (UCSZ). This artticle, which is in the folder marked Cosmology and NonGalactic Astrophysics, presents a study of the mass distribution and substructure of a galaxy cluster that acts as a gravitational lens for a source galaxy at z=1.95 that contains two supernovae. It was published on 23rd June 2025. The overlay is here:
The officially-accepted version can be found on arXiv here.
“Illuminating the Physics of Dark Energy with the Discovery Simulations” by Gillian D. Beltz-Mohrmann (Argonne National Laboratory, USA) and 12 others based in the USA and Spain. This describes new high-resolution cosmological simulations providing a testbed for alternative cosmological probes that may offer additional constraining power beyond Baryon Accoustic Oscillations. It is filed in the folder marked Cosmology and NonGalactic Astrophysics.
The overlay is here:
You can read the final accepted version on arXiv here.
Next one up is in the folder marked Astrophysics of Galaxies. The title is “On the minimum number of radiation field parameters to specify gas cooling and heating functions” and it is by David Robinson & Camille Avestruz (U. Michigan) and Nickolay Y. Gnedin (U.Chicago) and was published on 23rd June 2025. It presents an analysis using machine learning of atomic gas cooling and heating functions computed by the spectral synthesis code Cloudy.
The overlay is here:
You can find the officially-accepted version of the paper on arXiv here.
The thirtd paper is “On the Use of WGANs for Super Resolution in Dark-Matter Simulations” by John Brennan (Maynooth), Sreedhar Balu (U. Melbourne), Yuxiang Qin (ANU), John Regan (Maynooth) and Chris Power (U. Western Australia). This one is also in the folder marked Astrophysics of Galaxies and was also published on Monday 23rd June. It is about using the Wasserstein Generative Adversarial Network (WGAN) model to increase the particle resolution of dark-matter-only simulations of galaxy formation. The overlay is here:
You can find the officially-accepted version of the paper on arXiv here.
Next we have “Cosmic Rays Masquerading as Hot CGM Gas: An Inverse-Compton Origin for Diffuse X-ray Emission in the Circumgalactic Medium” by Philip F. Hopkins (Caltech), Eliot Quataert (Princeton), Sam B. Ponnada (Caltech) and Emily Silich (Caltech), all based in the USA. This one was published on 24th June 2025 in the folder High-Energy Astrophysical Phenomena
You can find the officially-accepted version on arXiv here.
The fifth paper this week is “Compact Binary Formation in Open Star Clusters III: Probability of Binary Black Holes Hidden Inside of Gaia Black Hole Binary” by Ataru Tanikawa (Fukui Prefectural University, Japan), Long Wang (Sun Yat-sen University, China), Michiko S. Fujii (University of Tokyo, Japan), Alessandro A. Trani (Niels Bohr Institute, Denmark), Toshinori Hayashi (Kyoto University, Japan) and Yasushi Suto (Kochi University of Technology, Japan). This one is in the folder marked Astrophysics of Galaxies and was published on Tuesday 24th June. It presents an investigation into whether some Gaia black hole binary systems may in fact involve three black holes, including a pair too compact to be resolved astrometrically. Here is the overlay:
You can find the officially-accepted paper on arXiv here.
Next we have “Rapid identification of lensed type Ia supernovae with color-magnitude selection” by Prajakta Mane (IISER) and Anupreeta More & Surhud More (IUCAA), all based in India. This paper presents an extension of the use of color-magnitude diagrams, used previously as a means to identify lensed supernovae, with applications to LSST-like photometric data. It is in the folder marked Astrophysics of Galaxies and was published on Thursday 26th June.
The officially-accepted version of the article can be found on arXiv here.
The penultimate article this week is: “Cosmic Reionization On Computers: Biases and Uncertainties in the Measured Mean Free Path at the End Stage of Reionization” by Huanqing Chen (U. Alberta, Canada), and Jiawen Fan & Camille Avestruz (U. Michigan, USA). This one is in the folder Cosmology and Nongalactic Astrophysics and was published on 26th June 2025. This paper studies possible systematic effects in computer simulations of cosmic reionization especially when it results from quasar radiation.
The overlay is here:
You can find the officially-accepted version on arXiv here.
Eighth and last paper this week is “Exploring the Core-galaxy Connection” by Isabele Lais de Souza Vitório (U. Michigan) and Michael Buehlmann, Eve Kovacs, Patricia Larsen, Nicholas Frontiere & Katrin Heitmann (Argonne National Laboratory, USA). This one is in the folder Cosmology and Nongalactic Astrophysics and was published on Friday 27th June 2025 (i.e. yesterday).
The overlay is here:
You can find the officially-accepted version on arXiv here.
And that’s all the papers for this week. I do, however, have some more news to pass on. We are delighted to welcome two new recruits to our Editorial Board, Dr Foteini Oikonomou of the Norwegian University of Science and Technology, who specializes in the application of particle physics theories to high-energy astrophysical phenomena, and Dr Heloise Stevance of Oxford University (UK), who specializes in the interface between Machine Learning and Astrophysics.
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