es/iode’s Post

📃Scientific paper: Evolution of X-ray galaxy Cluster Properties in a Representative Sample \(EXCPReS\). Optimal binning for temperature profile extraction Abstract: We present XMM-Newton observations of a representative X-ray selected sample of 31 galaxy clusters at moderate redshift $\(0.4\<z\<0.6\)$, spanning the mass range $10^\{14\} \< M\_\{\textrm 500\} \< 10^\{15\}$\~M$\_\odot$. This sample, EXCPRES \(Evolution of X-ray galaxy Cluster Properties in a Representative Sample\), is used to test and validate a new method to produce optimally-binned cluster X-ray temperature profiles. The method uses a dynamic programming algorithm, based on partitioning of the soft-band X-ray surface brightness profile, to obtain a binning scheme that optimally fulfills a given signal-to-noise threshold criterion out to large radius. From the resulting optimally-binned EXCPRES temperature profiles, and combining with those from the local REXCESS sample, we provide a generic scaling relation between the relative error on the temperature and the \[0.3-2\] keV surface brightness signal-to-noise ratio, and its dependence on temperature and redshift. We derive an average scaled 3D temperature profile for the sample. Comparing to the average scaled 3D temperature profiles from REXCESS, we find no evidence for evolution of the average profile shape within the redshift range that we probe. ;Comment: 18 pages, 13 figures, submitted to Astronomy & Astrophysics Continued on ES/IODE ➡️ https://etcse.fr/CUuw ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

📃Scientific paper: Evolution of X-ray galaxy Cluster Properties in a Representative Sample \(EXCPReS\). Optimal binning for temperature profile extraction Abstract: We present XMM-Newton observations of a representative X-ray selected sample of 31 galaxy clusters at moderate redshift $\(0.4\<z\<0.6\)$, spanning the mass range $10^\{14\} \< M\_\{\textrm 500\} \< 10^\{15\}$\~M$\_\odot$. This sample, EXCPRES \(Evolution of X-ray galaxy Cluster Properties in a Representative Sample\), is used to test and validate a new method to produce optimally-binned cluster X-ray temperature profiles. The method uses a dynamic programming algorithm, based on partitioning of the soft-band X-ray surface brightness profile, to obtain a binning scheme that optimally fulfills a given signal-to-noise threshold criterion out to large radius. From the resulting optimally-binned EXCPRES temperature profiles, and combining with those from the local REXCESS sample, we provide a generic scaling relation between the relative error on the temperature and the \[0.3-2\] keV surface brightness signal-to-noise ratio, and its dependence on temperature and redshift. We derive an average scaled 3D temperature profile for the sample. Comparing to the average scaled 3D temperature profiles from REXCESS, we find no evidence for evolution of the average profile shape within the redshift range that we probe. ;Comment: 18 pages, 13 figures, submitted to Astronomy & Astrophysics Continued on ES/IODE ➡️ https://etcse.fr/CUuw ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

📃Scientific paper: ZTF J185259.31+124955.2: A new evolved disc-eclipsing binary system Abstract: Discs in long-period eclipsing binary systems are rare and can lead to extraordinary eclipsing events. ZTF J185259.31+124955.2 was identified as a candidate disc-eclipsing system through a continuing search programme of ZTF variables with a near-IR excess in the WISE data. Examination of the combined ZTF and ATLAS photometry shows seven eclipses since 2017 with depths of 0\fm34 in all bands on a period of $289.57\pm0.09$\,d. The eclipse width is $\sim 40$\,d but this and the profile evolve over time. Comparison with library spectra shows that the spectral energy distribution from the available photometry is consistent with an early K-type giant, and fitting black-body profiles suggests $T\_\{eff\} \sim 4000$\,K for the stellar component, with a cool component having $T\_\{eff\} \< 500$\,K. The reddening and distance, and hence the luminosity place the star within the giant branch. The most likely scenario is that the system is in a state of rapid evolution following Case B/C mass transfer into an extended disc around an unseen companion. ;Comment: 7 pages, 8 figures. Accepted for Astronomy and Astrophysics Continued on ES/IODE ➡️ https://etcse.fr/ayLXY ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

📃Scientific paper: VODKA-JWST: Synchronized growth of two SMBHs in a massive gas disk? A 3.8 kpc separation dual quasar at cosmic noon with JWST NIRSpec IFU Abstract: The search for dual supermassive black holes \(SMBHs\) is of immense interest in modern astrophysics. Galaxy mergers may be an important route to fuel and to produce SMBH pairs. Actively accreting SMBH pairs can be observed as a dual quasar, which are vital probes of SMBH growth. Gaia observations have enabled a novel technique to systematically search for such dual quasars at previously unreachable sub-kpc scales, based on the small jitters of the light centroid as the two quasars vary stochastically. Here we present the first detailed study of a 0.46'', 3.8 kpc separation, VODKA-selected dual quasar, J0749+2255, at $z=2.17$ using JWST/NIRSpec integral field unit spectroscopy. This is one of the most distant, small separation dual quasars identified today. Dual quasars at cosmic noon are not well characterized. We detect the faint ionized gas of the host galaxy, best traced by the narrow \ha\ emission. Line ratio diagnostics show a mix of ionization from the two quasars and intense star formation. The spatially-resolved spectra of the two quasars suggest that they have very similar black hole properties \(two $M\_\{BH\}\sim 10^9\ \textrm\{M\}\_\{\odot\}$ with large Eddington ratio reaching $L/L\_\{Edd\}\sim0.2$\) hinting at the possible synchronized growth and accretion from the same gas supply. Surprisingly, the ionized gas kinematics suggest an extended, rotating disk rather than a disturbed system that would be expected in a major gas-rich galaxy merger. While it is unclear... Continued on ES/IODE ➡️ https://etcse.fr/2kJls ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

📃Scientific paper: BxC Toolkit: Generating Tailored Turbulent 3D Magnetic Fields Abstract: Turbulent states are ubiquitous in plasmas and the understanding of turbulence is fundamental in modern astrophysics. Numerical simulations, which are the state-of-the-art approach to the study of turbulence, require substantial computing resources. Recently, attention shifted to methods for generating synthetic turbulent magnetic fields, affordably creating fields with parameter-controlled characteristic features of turbulence. In this context, the BxC toolkit was developed and validated against direct numerical simulations (DNS) of isotropic turbulent magnetic fields. Here, we demonstrate novel extensions of BxC to generate realistic turbulent magnetic fields in a fast, controlled, geometric approach. First, we perform a parameter study to determine quantitative relations between the BxC input parameters and desired characteristic features of the turbulent power spectrum, such as the extent of the inertial range, its spectral slope, and the injection and dissipation scale. Second, we introduce in the model a set of structured background magnetic fields B0, as a natural and more realistic extension to the purely isotropic turbulent fields. Third, we extend the model to include anisotropic turbulence properties in the generated fields. With all these extensions combined, our tool can quickly generate any desired structured magnetic field with controlled, anisotropic turbulent fluctuations, faster by orders of magnitude with respect to DNSs. These can be used, e.g.,... Continued on ES/IODE ➡️ https://etcse.fr/Dy2fp ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

Ever since the beginning of my academic journey at KUL, I promised to myself that I would remain transparent regarding how things are done in our models and why, even if it sometimes means judgment from the side of the academic community (because, while some approximations might almost always be necessary in numerics, they may still hurt to look at). At the end of the day, we are developing models for others to make use of, and there is only so much confidence one may have in a black box. Based on my own experience, transparent and thorough reporting also often encourages further collaboration, prevents inappropriate use and may even result in the final product being improved by the community feedback. I am thus happy to announce a new forthcoming article, https://lnkd.in/eJcpf_bb the Arxiv version (draft) of which is already available here: https://lnkd.in/eR67iRrP in which we develop a simple approximate technique to constrain unphysical features in our global coronal simulations for #spaceweather modelling using insights from the Bifrost solar atmospheric software of the RoCS group at Institute of Theoretical Astrophysics, University of Oslo. I thank the staff of A&A and the reviewers for helping us get this research out there.

🌟 Save the date!! 🌟 We invite you to our next #NFDITalk about #AMPEL: A FAIR analysis engine for high-throughput, heterogeneous data streams    📅 21 October, 4 PM – Online 🎤 Speaker:  Dr. Jakob Nordin     ℹ About the talk:   Modern astronomical observatories generate high-throughput alert streams from photons, cosmic rays, neutrinos, and gravitational waves, revealing a dynamic universe. Effectively managing this data requires scalable tools that maintain #FAIR principles and support scientific creativity. 🌠   #AMPEL is a modular, scalable framework for handling complex datasets in real-time, with provenance tracking for reproducibility. While designed for multi-messenger astrophysics, #AMPEL can be applied in other fields. It is written in Python, executes multiple analyses concurrently, de-duplicates calculations, and uses a YAML-based configuration language. It supports local development and large-scale execution.     ➡ Join the Zoom Meeting: https://www.nfdi.de/talks   ➡ Share the YouTube stream: https://lnkd.in/eRXncwDq #rdm #fdm #NFDI #NFDITalk #savethedate

🌌 Exciting advancements in astrophysical modeling! 🌌 Had an amazing call yesterday with the brilliant Sayantan Auddy. From there, I came to his last paper called "GRINN: A Physics-Informed Neural Network for Solving Hydrodynamic Systems in the Presence of Self-Gravity" They introduce GRINN, a PINN-based (Physics-Informed Neural Network) solver that tackles the complexities of modeling self-gravitating gas flows—a challenge in astrophysics, especially for studying phenomena like star and galaxy formation. 🔹 Why GRINN? Traditional finite difference methods, though powerful, struggle with 3D simulations due to computational demands that increase with dimensionality. GRINN, leveraging the flexibility of PINNs, overcomes this by achieving efficient, mesh-free 3D hydrodynamic simulations. 🔹 Key results: GRINN not only achieved <1% error in the linear regime but also matched conventional grid codes with only a 5% variance in non-linear cases. It's 10x faster than grid-based methods for 3D calculations, promising a significant impact in modeling 3D astrophysical flows. 🔹 Future Potential: By addressing self-gravity and complex, time-dependent PDEs, GRINN paves the way for scalable, GPU-optimized modeling in astrophysics, making it an excellent tool for both current and future research in large-scale cosmic phenomena. Kudos to the authors for pushing the boundaries of SciML! 👏 #PhysicsInformedNeuralNetworks #Astrophysics #MachineLearning #Hydrodynamics #SciML #DeepLearning #GRINN #SelfGravity

I'm pleased to share an upgrade from my academic journey (again)! 🌌 Recently, I learned how to use GitHub to collaborate and share my works in computational astronomy, and I have a few updates to share. ✨I just launched a personal website hosted on my GitHub, highlighting my academic journey, interest, and works. You can check it out here: https://lnkd.in/gPaBFVqB ✨I've uploaded my recent work on a cosmology calculator! This allows us to compute cosmological parameters for any universe component you choose. It also compares numerical solutions with analytical ones and includes some analysis plots (it’s written in Jupyter). Explore it here: https://lnkd.in/gvT-9xEw I’m excited to continue sharing my work, so stay tuned for more updates from my GitHub account!

There’s a proverb in astronomy that goes something like, “black holes have no hair.” This indicates that black holes are extremely straightforward entities under the framework of general relativity. The only necessary characteristics of a black hole are its mass, electric charge, and spin rate. You now know everything there is to know about black holes just from those three numbers. That is to say, they are bare; they lack any further data. This feature of black holes has been a major source of frustration for astronomers trying to figure out the inner workings of these cosmic behemoths. However, understanding black holes and their inner workings is impossible due to the absence of any kind of “hair” on their surfaces. Unfortunately, black holes continue to be among the universe’s most elusive and baffling features. The present knowledge of general relativity, however, is essential to the “no-hair” black hole notion. The emphasis of this relativity illustration is on the curved nature of space-time. Any object with enough mass or energy to bend space-time around it will provide that object directions for movement. However, this is not the only viable option for building a relativity theory. Space-time’s “twistiness,” as opposed to its curvature, is the subject of a whole distinct method. According to this interpretation, the presence of anything heavy or energetic causes localized distortions in space-time, which in turn direct the motion of nearby objects. ----- P.S. Look at the extension after the URL. When we visit a website, your browser saves the history, and when you use a tracker, or click a link from a different site, the information that was on the previous site, stays with it, and goes to the next one. This is how they track the untraceable, similar to information paradox with a black hole https charmingscience com/twisty-new-theory-of-gravity-suggests-information-can-escape-black-holes-after-all/?fbclid=IwY2xjawFa3lRleHRuA2FlbQIxMQABHboKnu2M27uftw6GfBqwCyu-fhPUv88zxRan10GCPd562zPPwrKkUTGsQg_aem_xQYBOG530G2txTCxHBlm-Q https://lnkd.in/ez-zfdHQ