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arXiv:2507.07346v2 Announce Type: replace Abstract: These notes are very much work-in-progress and simply intended to showcase, in various degrees of details (and rigour), some of the cosmology calculations that class_sz can do. We describe the class_sz code in C, Python and Jax. Based on the Boltzmann code class, it can compute a wide range of observables relevant to current and forthcoming CMB and Large Scale Structure surveys. This includes galaxy shear and clustering, CMB lensing, thermal and kinetic Sunyaev and Zeldovich observables, Cosmic Infrared Background, cross-correlations and three-point statistics. Calculations can be done either within the halo model or the linear bias model. For standard $\Lambda$CDM cosmology and extensions, class_sz uses high-accuracy cosmopower emulators of the CMB and matter power spectrum to accelerate calculations. With this, along with efficient numerical integration routines, most class_sz output can be obtained in less than 500 ms (CMB $C_\ell$'s or matter $P(k)$ take $\mathcal{O}(1\mathrm{ms})$), allowing for fast or ultra-fast parameter inference analyses. Parts of the calculations are "jaxified", so the software can be integrated into differentiable pipelines.

Direct Images of the Cosmic Web of Intergalactic and Circumgalactic Gas

The filamentary pattern in which the Universe’s matter concentrates, the cosmic web, is predicted by the ΛCDM cosmological model and contains the majority of the universe’s matter. Detailed mapping of this interconnected structure of gaseous filaments, galaxies, quasars, dark matter, and voids, is central to a comprehensive understanding of the origin and evolution of our Universe. I will describe very deep narrow band imaging observations obtained using the Condor Array Telescope in New Mexico, centered on the Cosmic Evolution Survey (COSMOS) field at a redshift of z=2.45. We use several hydrodynamical simulations to predict the cosmic web Lyman-alpha emission properties. The simulation results show good agreement with the Condor data, supporting the notion that Condor has detected wide-field cosmic web emission, potentially marking the beginning of a new field of cosmology – detailed baryonic and dark matter cartography of the diffuse Universe. I will describe the details of these data and simulations and then discuss the construction of a new Condor in the Atacama that will go even deeper and which we hope will see first light towards the end of 2025.

• Speaker: Oleksii Sokoliuk, Aberdeen University
• Wednesday 16 July 2025, 13:45-14:15
• Venue: Hoyle Lecture theatre + Zoom .
• Series: Institute of Astronomy Seminars; organiser: Cristiano Longarini.

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Chasing the First Stars With Outliers

he OUTLIERS project aims to find and study the most ancient stars in our Galaxy — stars that formed shortly after the Big Bang. These stars carry unique chemical fingerprints that tell us about the very first generations of stars, the first supernovae, and the early stages of galaxy formation. Although extremely rare and faint, they can still be found today thanks to the combined power of Gaia — which maps the positions and motions of over a billion stars — and new large spectroscopic surveys like DESI , WEAVE, and 4MOST. OUTLIERS uses this data to select and follow up the most promising candidates. By studying these stellar fossils in detail, we hope to answer long-standing questions about how the first stars formed, what elements they created, and how the Universe evolved in its earliest phases.

• Speaker: David Aguado, Instituto de Astrofísica de Canarias
• Wednesday 16 July 2025, 13:15-13:45
• Venue: Hoyle Lecture theatre + Zoom .
• Series: Institute of Astronomy Seminars; organiser: Cristiano Longarini.

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Chasing the First Stars With Outliers

he OUTLIERS project aims to find and study the most ancient stars in our Galaxy — stars that formed shortly after the Big Bang. These stars carry unique chemical fingerprints that tell us about the very first generations of stars, the first supernovae, and the early stages of galaxy formation. Although extremely rare and faint, they can still be found today thanks to the combined power of Gaia — which maps the positions and motions of over a billion stars — and new large spectroscopic surveys like DESI , WEAVE, and 4MOST. OUTLIERS uses this data to select and follow up the most promising candidates. By studying these stellar fossils in detail, we hope to answer long-standing questions about how the first stars formed, what elements they created, and how the Universe evolved in its earliest phases.

• Speaker: David Aguado, Instituto de Astrofísica de Canarias
• Wednesday 16 July 2025, 13:15-13:45
• Venue: Hoyle Lecture theatre + Zoom .
• Series: Institute of Astronomy Seminars; organiser: Cristiano Longarini.

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The IceCube neutrino detector has allowed researchers to resolve a debate about what types of particles make up ultra-high-energy cosmic rays – but much remains unknown about these rare events

arXiv:2507.07346v1 Announce Type: new Abstract: These notes are very much work-in-progress and simply intended to showcase, in various degrees of details (and rigour), some of the cosmology calculations that class_sz can do. We describe the class_sz code in C, Python and Jax. Based on the Boltzmann code class, it can compute a wide range of observables relevant to current and forthcoming CMB and Large Scale Structure surveys. This includes galaxy shear and clustering, CMB lensing, thermal and kinetic Sunyaev and Zeldovich observables, Cosmic Infrared Background, cross-correlations and three-point statistics. Calculations can be done either within the halo model or the linear bias model. For standard $\Lambda$CDM cosmology and extensions, class_sz uses high-accuracy cosmopower emulators of the CMB and matter power spectrum to accelerate calculations. With this, along with efficient numerical integration routines, most class_sz output can be obtained in less than 500 ms (CMB $C_\ell$'s or matter $P(k)$ take $\mathcal{O}(1\mathrm{ms})$), allowing for fast or ultra-fast parameter inference analyses. Parts of the calculations are "jaxified", so the software can be integrated into differentiable pipelines.

arXiv:2507.07155v1 Announce Type: new Abstract: We evaluate 9 Retrieval Augmented Generation (RAG) agent configurations on 105 Cosmology Question-Answer (QA) pairs that we built specifically for this purpose.The RAG configurations are manually evaluated by a human expert, that is, a total of 945 generated answers were assessed. We find that currently the best RAG agent configuration is with OpenAI embedding and generative model, yielding 91.4\% accuracy. Using our human evaluation results we calibrate LLM-as-a-Judge (LLMaaJ) system which can be used as a robust proxy for human evaluation. These results allow us to systematically select the best RAG agent configuration for multi-agent system for autonomous scientific discovery in astrophysics (e.g., cmbagent presented in a companion paper) and provide us with an LLMaaJ system that can be scaled to thousands of cosmology QA pairs. We make our QA dataset, human evaluation results, RAG pipelines, and LLMaaJ system publicly available for further use by the astrophysics community.

The awe-inspiring distances of the cosmos are hard to visualise, so how can we be certain we are measuring them correctly? Chanda Prescod-Weinstein explains

Dust grains across the universe: JWST and ALMA insights from cosmic noon to the early universe

Abstract not available

• Speaker: Irene Shivaei (CAB, Madrid)
• Friday 18 July 2025, 11:30-12:30
• Venue: Ryle Seminar Room, KICC + online.
• Series: Galaxies Discussion Group; organiser: Sandro Tacchella.

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Double black hole mergers in nuclear star clusters: eccentricities, spins, masses, and the growth of massive seeds

We investigate the formation of intermediate-mass black holes (IMBHs) through hierarchical mergers of stellar-origin black holes (BHs), as well as BH mergers formed dynamically in nuclear star clusters. Using a semi-analytical approach that incorporates probabilistic, mass-function–dependent double-BH (DBH) pairing, binary–single encounters, and a mass-ratio–dependent prescription for energy dissipation in hardening binaries, we find that IMB Hs with masses of order 10²–10⁴ M⊙ can be formed solely through hierarchical mergers on timescales of a few hundred Myr to a few Gyr. Clusters with escape velocities ≳ 400 km s⁻¹ inevitably form high-mass IMB Hs. The spin distribution of IMB Hs with masses ≳ 10³ M⊙ is strongly clustered at χ ≈ 0.15, while for lower masses it peaks at χ ≈ 0.7. Eccentric mergers are more frequent for equal-mass binaries containing first- and second-generation BHs. Metal-rich, young, dense clusters can produce up to 20 of their DBH mergers with eccentricity ≥ 0.1 at 10 Hz, and ~ 2–9 of all in-cluster mergers form at > 10 Hz. Nuclear star clusters are therefore promising environments for the formation of highly eccentric DBH mergers, detectable with current gravitational-wave detectors. Clusters of extreme mass (∼ 10⁸ M⊙) and density (∼ 10⁸ M⊙ pc⁻³) can have about half of their DBH mergers with primary masses ≥ 100 M⊙. The fraction of in-cluster mergers increases rapidly with increasing escape velocity, approaching unity for Vesc ≳ 200 km s⁻¹. The cosmological DBH merger rate from nuclear clusters varies from ≲ 0.01 to 1 Gpc⁻³ yr⁻¹, where the large uncertainties stem from cluster initial conditions, number-density distributions, and the redshift evolution of nucleated galaxies.

• Speaker: Debatri Chattopadhyay
• Wednesday 09 July 2025, 13:15-13:45
• Venue: Hoyle Lecture theatre + Zoom .
• Series: Institute of Astronomy Seminars; organiser: Cristiano Longarini.

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Title to be confirmed

Abstract not available

• Speaker: Michele Ginolfi (Florence)
• Friday 24 October 2025, 11:30-12:30
• Venue: Ryle Seminar Room, KICC + online.
• Series: Galaxies Discussion Group; organiser: Sandro Tacchella.

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Unveiling the shape of the ionizing spectrum of galaxies

Abstract not available

• Speaker: Anne Verhamme (University of Geneva)
• Friday 11 July 2025, 11:30-12:30
• Venue: Ryle Seminar Room, KICC + online.
• Series: Galaxies Discussion Group; organiser: Sandro Tacchella.

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arXiv:2405.05772v3 Announce Type: replace Abstract: We report the detection of continuum excess in the rest-frame UV between 3000 {\AA} and 3550 {\AA} in the JWST/NIRSpec spectrum of GN-z11, a luminous galaxy $z=10.603$. The shape of the continuum excess resembles a Balmer continuum but has a break around 3546 {\AA}. The fitting result of this excess depends on the assumed origin of the continuum. If the continuum of GN-z11 is dominated by a stellar population with a small Balmer break, the apparent blueshift of the Balmer continuum is not significant and the best-fit Balmer continuum model indicates a temperature of $T_e = 1.78^{+0.25}_{-0.21}\times 10^4$ K. In contrast, if the continuum is dominated by AGN emission, a nebular continuum model cannot fit the spectrum properly. The absence of the Balmer jump indicates an electron temperature of $\sim 3\times 10^4$ K, significantly higher than the temperature of $T_{e}({\rm O^{2+}}) = 1.36\pm 0.13\times 10^{4}$ K inferred from [OIII]$\lambda 4363$ and [OIII]$\lambda 5007$. The temperature difference can result from mixing of different ionized regions: the Balmer emission mainly arises from dense and hot clouds in the Broad Line Region, whereas the forbidden lines originate from less dense and colder gas. An alternative explanation for the observed continuum excess is the FeII emission, which shows a characteristic jump blueward of the Balmer limit as previously seen in the spectra of many lower-redshift quasars. Through comparisons with Cloudy models, we show an Fe abundance above $\sim 1/3$ solar is likely needed, which could be achieved via enrichment from Type-Ia supernovae, hypernovae, or pair-instability supernovae.

Optimizing Data Delivery and Scalable HI Profile Classification for the SKA Era: Infrastructure and Science Challenges at the Spanish SRC

This talk presents ongoing work at the Spanish SKA Regional Centre (esSRC) in the context of the SRC Net 0.1. The first part focuses on the development of efficient data delivery techniques from the distributed Rucio-based storage system to the SRC infrastructure and, ultimately, to user workspaces. Several approaches have been evaluated to support science-ready access, yet current solutions often involve unnecessary data duplication in user areas, resulting in increased usage of storage and computational resources. To address this, we have prototyped mechanisms based on file linking, caching, and data reuse, enabling more efficient access paths for users. While these methods show promising improvements in terms of performance and resource usage, challenges remain, particularly in terms of orchestration, scalability, and compatibility with existing workload managers. The second part presents advances in the automated classification of neutral hydrogen (HI) profiles using machine learning methods, building on previous work [Parra et al., 2024, arXiv:2501.11657]. We outline a roadmap for extending these techniques to handle the data volumes expected from the SKA Observatory. This includes developing scalable pipelines capable of ingesting and processing large spectral datasets in a reproducible and efficient manner, and adapting the classification models to cope with the diversity and complexity of the SKA data products.

• Speaker: Dr. Manu Parra-Royón (Astrophysics Institute of Andalucia - Spanish National Research Council)
• Tuesday 08 July 2025, 11:15-12:00
• Venue: Coffee area, Battcock Centre.
• Series: Hills Coffee Talks; organiser: Charles Walker.

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Nature, Published online: 02 July 2025; doi:10.1038/d41586-025-01979-z

The James Webb Space Telescope has detected molecular hydrogen in a nearby galaxy that has a very low proportion of metals. This implies that considerable quantities of molecular gas can form at low metallicities, and provides insight into similarly metal-poor galaxies in the early Universe.

arXiv:2507.00351v1 Announce Type: new Abstract: We present Dark from Light (DfL) - a novel method to infer the dark sector in wide-field galaxy surveys, leveraging a machine learning approach trained on contemporary cosmological simulations. The aim of this algorithm is to provide a fast, straightforward, and accurate route to estimating dark matter halo masses and group membership in wide-field spectroscopic galaxy surveys. This approach requires a highly limited number of input parameters and yields full probability distribution functions for the output halo masses. To achieve this, we train a series of Random Forest (RF) regression models on the IllustrisTNG and EAGLE simulations at z=0-3, which provide model-dependent mappings from luminous tracers to dark matter halo properties. We incorporate the individual regression models into a virial group-finding algorithm (DfL), which outputs halo properties for observational-like input data. We test the method at z=0-2 for both the EAGLE and IllustrisTNG models, as well as in a cross-validation mode. We demonstrate that known halo masses can be recovered with a mean systematic bias of $\langle b \rangle = \pm 0.10\,$dex (resulting from simulation choice), a mean statistical uncertainty of $\langle \sigma \rangle = 0.12 \,$dex across epochs, and a central - (core) satellite classification accuracy of 96%. We establish that this approach yields superior halo mass recovery to standard abundance matching applied to groups identified through a friends-of-friends algorithm. Additionally, we compare the outputs of DfL to observational constraints on the $M_* - M_{\rm Halo}$ relation from strong gravitational lensing at $z \sim 0$, demonstrating the promise of this novel approach. Finally, we systematically quantify how DfL performs on observational-like input data with varying stellar mass uncertainty and spectroscopic incompleteness, enabling robust error calibration.