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LCLU Coffee - Ligia F Coelho on "the changing colours of our planet as a tool for ilfe detection on icy moons and exoplanets"

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We cannot predict life. We can, instead, learn from Earth’s biodiversity and their varied molecular catalogue of markers of adaptability. Biopigments are widespread biomolecules that serve as powerful surface biomarkers of adaptability to extreme conditions on our planet. These molecules have distinct and unique spectral signatures providing a promising avenue for detecting extraterrestrial life. However, current surface models for other planets overlook Earth’s broader biodiversity. In the Solar System, current models struggle to constrain non-icy mysterious spots on the surface of the Jovian icy moon Europa for lack of matching reference spectra. In parallel, exoplanet surface models tend to overemphasize chlorophyll-based landscapes, often constrained by the assumption that photosynthesis requires visible light. This introduces unnecessary restrictions on atmospheric opacity and composition. In reality, Earth’s biosphere hosts a vast array of biopigments capable of harnessing energy across the UV to IR spectrum, driving diverse metabolisms, volatile byproducts, and environmental adaptations—many of which serve as analogues for targets to be studied with future telescopes and space missions. By integrating Earth’s biological and evolutionary diversity with astrophysical tools, I will present life-detection frameworks based on a broad spectral dataset. I will show how in situ reflectance data from Svalbard (Arctic) and Atacama Desert can help us correlate biosignatures with specific environments. These findings contribute to biologically informed planetary models, crucial for the next generation missions, including Extremely Large Telescopes (ELTs), the Habitable Worlds Observatory (HWO) and Large Interferometer For Exoplanets (LIFE), as well as NASA ’s Europa Clipper, ESA ’s Juice and Enceladus L4. These exciting new instruments will probe several planetary surfaces for a new biosphere where orange, yellow, or purple may be the new green.

• Speaker: Ligia F Coelho (Cornell Astronomy)
• Thursday 15 May 2025, 11:00-12:00
• Venue: tba.
• Series: LCLU Coffee Meetings; organiser: Paul B. Rimmer.

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• Speaker: Etienne Camphuis (Institut d'Astrophysique de Paris)
• Monday 09 June 2025, 13:00-14:00
• Venue: CMS, Pav. B, CTC Common Room (B1.19) [Potter Room].
• Series: Cosmology Lunch; organiser: Louis Legrand.

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• Speaker: Levon Pogosian (Simon Fraser University)
• Monday 23 June 2025, 13:00-14:00
• Venue: CMS, Pav. B, CTC Common Room (B1.19) [Potter Room].
• Series: Cosmology Lunch; organiser: Louis Legrand.

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• Speaker: George Becker (UC Riverside)
• Friday 06 June 2025, 11:30-12:30
• Venue: Ryle Seminar Room, KICC + online.
• Series: Galaxies Discussion Group; organiser: Sandro Tacchella.

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The Odysseus spacecraft made a rough landing on the moon last year, toppling over and rendering much of its equipment unusable, but an onboard NASA radio telescope called ROLSES-1  was able to make some observations

arXiv:2503.16325v1 Announce Type: new Abstract: Chondrules are small spherical objects that formed at high temperatures early in the history of the Solar System. The key compositional characteristics of chondrules may be well explained by high gas pressures in their formation environment (Galy et al. 2000; Alexander et al. 2008). However, such high gas pressures are widely considered astrophysically unreasonable (Ebel et al. 2023). Here, we propose that chondrules were formed via the processing of dust grains in the dust-rich envelopes of planetary embryos, before getting ejected via convective diffusion. We show that this scenario can explain many salient constraints on chondrule formation, including formation locations; mass and timescale of chondrule production; repeat chondrule heating events; heating timescales; and, most crucially, high prevailing gas pressures. Our work suggests that high gas pressures may indeed have prevailed during the formation of chondrules, reconciling previous analytical observations, experimental evidence, and theory. We suggest that chondrules are mostly the products rather than the precursors of planetary embryo formation - a result which would have important implications for our understanding of the early history of the Solar System.

arXiv:2503.16325v1 Announce Type: new Abstract: Chondrules are small spherical objects that formed at high temperatures early in the history of the Solar System. The key compositional characteristics of chondrules may be well explained by high gas pressures in their formation environment (Galy et al. 2000; Alexander et al. 2008). However, such high gas pressures are widely considered astrophysically unreasonable (Ebel et al. 2023). Here, we propose that chondrules were formed via the processing of dust grains in the dust-rich envelopes of planetary embryos, before getting ejected via convective diffusion. We show that this scenario can explain many salient constraints on chondrule formation, including formation locations; mass and timescale of chondrule production; repeat chondrule heating events; heating timescales; and, most crucially, high prevailing gas pressures. Our work suggests that high gas pressures may indeed have prevailed during the formation of chondrules, reconciling previous analytical observations, experimental evidence, and theory. We suggest that chondrules are mostly the products rather than the precursors of planetary embryo formation - a result which would have important implications for our understanding of the early history of the Solar System.

arXiv:2503.15635v1 Announce Type: new Abstract: The European Space Agency's Euclid mission will observe approximately 14,000 $\rm{deg}^{2}$ of the extragalactic sky and deliver high-quality imaging for many galaxies. The depth and high spatial resolution of the data will enable a detailed analysis of stellar population properties of local galaxies. In this study, we test our pipeline for spatially resolved SED fitting using synthetic images of Euclid, LSST, and GALEX generated from the TNG50 simulation. We apply our pipeline to 25 local simulated galaxies to recover their resolved stellar population properties. We produce 3 types of data cubes: GALEX + LSST + Euclid, LSST + Euclid, and Euclid-only. We perform the SED fitting tests with two SPS models in a Bayesian framework. Because the age, metallicity, and dust attenuation estimates are biased when applying only classical formulations of flat priors, we examine the effects of additional priors in the forms of mass-age-$Z$ relations, constructed using a combination of empirical and simulated data. Stellar-mass surface densities can be recovered well using any of the 3 data cubes, regardless of the SPS model and prior variations. The new priors then significantly improve the measurements of mass-weighted age and $Z$ compared to results obtained without priors, but they may play an excessive role compared to the data in determining the outcome when no UV data is available. The spatially resolved SED fitting method is powerful for mapping the stellar populations of galaxies with the current abundance of high-quality imaging data. Our study re-emphasizes the gain added by including multiwavelength data from ancillary surveys and the roles of priors in Bayesian SED fitting. With the Euclid data alone, we will be able to generate complete and deep stellar mass maps of galaxies in the local Universe, thus exploiting the telescope's wide field, NIR sensitivity, and high spatial resolution.

arXiv:2503.15635v1 Announce Type: new Abstract: The European Space Agency's Euclid mission will observe approximately 14,000 $\rm{deg}^{2}$ of the extragalactic sky and deliver high-quality imaging for many galaxies. The depth and high spatial resolution of the data will enable a detailed analysis of stellar population properties of local galaxies. In this study, we test our pipeline for spatially resolved SED fitting using synthetic images of Euclid, LSST, and GALEX generated from the TNG50 simulation. We apply our pipeline to 25 local simulated galaxies to recover their resolved stellar population properties. We produce 3 types of data cubes: GALEX + LSST + Euclid, LSST + Euclid, and Euclid-only. We perform the SED fitting tests with two SPS models in a Bayesian framework. Because the age, metallicity, and dust attenuation estimates are biased when applying only classical formulations of flat priors, we examine the effects of additional priors in the forms of mass-age-$Z$ relations, constructed using a combination of empirical and simulated data. Stellar-mass surface densities can be recovered well using any of the 3 data cubes, regardless of the SPS model and prior variations. The new priors then significantly improve the measurements of mass-weighted age and $Z$ compared to results obtained without priors, but they may play an excessive role compared to the data in determining the outcome when no UV data is available. The spatially resolved SED fitting method is powerful for mapping the stellar populations of galaxies with the current abundance of high-quality imaging data. Our study re-emphasizes the gain added by including multiwavelength data from ancillary surveys and the roles of priors in Bayesian SED fitting. With the Euclid data alone, we will be able to generate complete and deep stellar mass maps of galaxies in the local Universe, thus exploiting the telescope's wide field, NIR sensitivity, and high spatial resolution.

arXiv:2503.15305v2 Announce Type: replace Abstract: The Euclid satellite is an ESA mission that was launched in July 2023. \Euclid is working in its regular observing mode with the target of observing an area of $14\,000~\text{deg}^2$ with two instruments, the Visible Camera (VIS) and the Near IR Spectrometer and Photometer (NISP) down to $I_{\rm E} = 24.5~\text{mag}$ ($10\, \sigma$) in the Euclid Wide Survey. Ground-based imaging data in the \textit{ugriz} bands complement the \Euclid data to enable photo-$z$ determination and VIS PSF modeling for week lensing analysis. Euclid investigates the distance-redshift relation and the evolution of cosmic structures by measuring shapes and redshifts of galaxies and clusters of galaxies out to $z\sim 2$. Generating the multi-wavelength catalogues from \Euclid and ground-based data is an essential part of the \Euclid data processing system. In the framework of the \Euclid Science Ground Segment (SGS), the aim of the MER Processing Function (PF) pipeline is to detect objects in the \Euclid imaging data, measure their properties, and MERge them into a single multi-wavelength catalogue. The MER PF pipeline performs source detection on both visible (VIS) and near-infrared (NIR) images and offers four different photometric measurements: Kron total flux, aperture photometry on PSF-matched images, template fitting photometry, and S\'ersic fitting photometry. Furthermore, the MER PF pipeline measures a set of ancillary quantities, spanning from morphology to quality flags, to better characterise all detected sources. In this paper, we show how the MER PF pipeline is designed, detailing its main steps, and we show that the pipeline products meet the tight requirements that Euclid aims to achieve on photometric accuracy. We also present the other measurements (e.g. morphology) that are included in the OU-MER output catalogues and we list all output products coming out of the MER PF pipeline.

arXiv:2503.15305v2 Announce Type: replace Abstract: The Euclid satellite is an ESA mission that was launched in July 2023. \Euclid is working in its regular observing mode with the target of observing an area of $14\,000~\text{deg}^2$ with two instruments, the Visible Camera (VIS) and the Near IR Spectrometer and Photometer (NISP) down to $I_{\rm E} = 24.5~\text{mag}$ ($10\, \sigma$) in the Euclid Wide Survey. Ground-based imaging data in the \textit{ugriz} bands complement the \Euclid data to enable photo-$z$ determination and VIS PSF modeling for week lensing analysis. Euclid investigates the distance-redshift relation and the evolution of cosmic structures by measuring shapes and redshifts of galaxies and clusters of galaxies out to $z\sim 2$. Generating the multi-wavelength catalogues from \Euclid and ground-based data is an essential part of the \Euclid data processing system. In the framework of the \Euclid Science Ground Segment (SGS), the aim of the MER Processing Function (PF) pipeline is to detect objects in the \Euclid imaging data, measure their properties, and MERge them into a single multi-wavelength catalogue. The MER PF pipeline performs source detection on both visible (VIS) and near-infrared (NIR) images and offers four different photometric measurements: Kron total flux, aperture photometry on PSF-matched images, template fitting photometry, and S\'ersic fitting photometry. Furthermore, the MER PF pipeline measures a set of ancillary quantities, spanning from morphology to quality flags, to better characterise all detected sources. In this paper, we show how the MER PF pipeline is designed, detailing its main steps, and we show that the pipeline products meet the tight requirements that Euclid aims to achieve on photometric accuracy. We also present the other measurements (e.g. morphology) that are included in the OU-MER output catalogues and we list all output products coming out of the MER PF pipeline.

Science, Volume 387, Issue 6740, Page 1240-1241, March 2025.

This NASA/ESA Hubble Space Telescope Picture of the Week features a sparkling spiral galaxy paired with a prominent star, both in the constellation Virgo. While the galaxy and the star appear to be close to one another, even overlapping, they’re actually a great distance apart.ESA/Hubble & NASA, S. J. Smartt, C. Kilpatrick

This NASA/ESA Hubble Space Telescope image features a sparkling spiral galaxy paired with a prominent star, both in the constellation Virgo. While the galaxy and the star appear to be close to one another, even overlapping, they’re actually a great distance apart. The star, marked with four long diffraction spikes, is in our own galaxy. It’s just 7,109 light-years away from Earth. The galaxy, named NGC 4900, lies about 45 million light-years from Earth.

This image combines data from two of Hubble’s instruments: the Advanced Camera for Surveys, installed in 2002 and still in operation today, and the older Wide Field and Planetary Camera 2, which was in use from 1993 to 2009. The data used here were taken more than 20 years apart for two different observing programs — a real testament to Hubble’s long scientific lifetime!

Both programs aimed to understand the demise of massive stars. In one, researchers studied the sites of past supernovae, aiming to estimate the masses of the stars that exploded and investigate how supernovae interact with their surroundings. They selected NGC 4900 for the study because it hosted a supernova named SN 1999br.

In the other program, researchers laid the groundwork for studying future supernovae by collecting images of more than 150 nearby galaxies. When researchers detect a supernova in one of these galaxies, they can refer to these images, examining the star at the location of the supernova. Identifying a supernova progenitor star in pre-explosion images gives valuable information about how, when, and why supernovae occur.

Image credit: ESA/Hubble & NASA, S. J. Smartt, C. Kilpatrick

Nature, Published online: 20 March 2025; doi:10.1038/s41586-025-08836-z

Author Correction: Observation of an ultra-high-energy cosmic neutrino with KM3NeT

arXiv:2503.15332v1 Announce Type: new Abstract: The matter distribution around galaxy clusters is distributed over several filaments, reflecting their positions as nodes in the large-scale cosmic web. The number of filaments connected to a cluster, namely its connectivity, is expected to affect the physical properties of clusters. Using the first Euclid galaxy catalogue from the Euclid Quick Release 1 (Q1), we investigate the connectivity of galaxy clusters and how it correlates with their physical and galaxy member properties. Around 220 clusters located within the three fields of Q1 (covering $\sim 63 \ \text{deg}^2$), are analysed in the redshift range $0.2 < z < 0.7$. Due to the photometric redshift uncertainty, we reconstruct the cosmic web skeleton, and measure cluster connectivity, in 2-D projected slices with a thickness of 170 comoving $h^{-1}.\text{Mpc}$ and centred on each cluster redshift, by using two different filament finder algorithms on the most massive galaxies ($M_*\ > 10^{10.3} \ M_\odot$). In agreement with previous measurements, we recover the mass-connectivity relation independently of the filament detection algorithm, showing that the most massive clusters are, on average, connected to a larger number of cosmic filaments, consistent with hierarchical structure formation models. Furthermore, we explore possible correlations between connectivities and two cluster properties: the fraction of early-type galaxies and the S\'ersic index of galaxy members. Our result suggests that the clusters populated by early-type galaxies exhibit higher connectivity compared to clusters dominated by late-type galaxies. These preliminary investigations highlight our ability to quantify the impact of the cosmic web connectivity on cluster properties with Euclid.

arXiv:2503.15332v1 Announce Type: new Abstract: The matter distribution around galaxy clusters is distributed over several filaments, reflecting their positions as nodes in the large-scale cosmic web. The number of filaments connected to a cluster, namely its connectivity, is expected to affect the physical properties of clusters. Using the first Euclid galaxy catalogue from the Euclid Quick Release 1 (Q1), we investigate the connectivity of galaxy clusters and how it correlates with their physical and galaxy member properties. Around 220 clusters located within the three fields of Q1 (covering $\sim 63 \ \text{deg}^2$), are analysed in the redshift range $0.2 < z < 0.7$. Due to the photometric redshift uncertainty, we reconstruct the cosmic web skeleton, and measure cluster connectivity, in 2-D projected slices with a thickness of 170 comoving $h^{-1}.\text{Mpc}$ and centred on each cluster redshift, by using two different filament finder algorithms on the most massive galaxies ($M_*\ > 10^{10.3} \ M_\odot$). In agreement with previous measurements, we recover the mass-connectivity relation independently of the filament detection algorithm, showing that the most massive clusters are, on average, connected to a larger number of cosmic filaments, consistent with hierarchical structure formation models. Furthermore, we explore possible correlations between connectivities and two cluster properties: the fraction of early-type galaxies and the S\'ersic index of galaxy members. Our result suggests that the clusters populated by early-type galaxies exhibit higher connectivity compared to clusters dominated by late-type galaxies. These preliminary investigations highlight our ability to quantify the impact of the cosmic web connectivity on cluster properties with Euclid.

arXiv:2503.15332v1 Announce Type: new Abstract: The matter distribution around galaxy clusters is distributed over several filaments, reflecting their positions as nodes in the large-scale cosmic web. The number of filaments connected to a cluster, namely its connectivity, is expected to affect the physical properties of clusters. Using the first Euclid galaxy catalogue from the Euclid Quick Release 1 (Q1), we investigate the connectivity of galaxy clusters and how it correlates with their physical and galaxy member properties. Around 220 clusters located within the three fields of Q1 (covering $\sim 63 \ \text{deg}^2$), are analysed in the redshift range $0.2 < z < 0.7$. Due to the photometric redshift uncertainty, we reconstruct the cosmic web skeleton, and measure cluster connectivity, in 2-D projected slices with a thickness of 170 comoving $h^{-1}.\text{Mpc}$ and centred on each cluster redshift, by using two different filament finder algorithms on the most massive galaxies ($M_*\ > 10^{10.3} \ M_\odot$). In agreement with previous measurements, we recover the mass-connectivity relation independently of the filament detection algorithm, showing that the most massive clusters are, on average, connected to a larger number of cosmic filaments, consistent with hierarchical structure formation models. Furthermore, we explore possible correlations between connectivities and two cluster properties: the fraction of early-type galaxies and the S\'ersic index of galaxy members. Our result suggests that the clusters populated by early-type galaxies exhibit higher connectivity compared to clusters dominated by late-type galaxies. These preliminary investigations highlight our ability to quantify the impact of the cosmic web connectivity on cluster properties with Euclid.

arXiv:2503.15330v1 Announce Type: new Abstract: We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering $63.1\,\mathrm{deg^2}$). This catalogue is the result of the visual inspection of 1260 cluster fields. Each galaxy cluster was ranked with a probability, $\mathcal{P}_{\mathrm{lens}}$, based on the number and plausibility of the identified strong lensing features. Specifically, we identified 83 gravitational lenses with $\mathcal{P}_{\mathrm{lens}}>0.5$, of which 14 have $\mathcal{P}_{\mathrm{lens}}=1$, and clearly exhibiting secure strong lensing features, such as giant tangential and radial arcs, and multiple images. Considering the measured number density of lensing galaxy clusters, approximately $0.3\,\mathrm{deg}^{-2}$ for $\mathcal{P}_{\mathrm{lens}}>0.9$, we predict that \Euclid\ will likely see more than 4500 strong lensing clusters over the course of the mission. Notably, only three of the identified cluster-scale lenses had been previously observed from space. Thus, \Euclid has provided the first high-resolution imaging for the remaining $80$ galaxy cluster lenses, including those with the highest probability. The identified strong lensing features will be used for training deep-learning models for identifying gravitational arcs and multiple images automatically in \Euclid observations. This study confirms the huge potential of \Euclid for finding new strong lensing clusters, enabling exciting new discoveries on the nature of dark matter and dark energy and the study of the high-redshift Universe.

arXiv:2503.15330v1 Announce Type: new Abstract: We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering $63.1\,\mathrm{deg^2}$). This catalogue is the result of the visual inspection of 1260 cluster fields. Each galaxy cluster was ranked with a probability, $\mathcal{P}_{\mathrm{lens}}$, based on the number and plausibility of the identified strong lensing features. Specifically, we identified 83 gravitational lenses with $\mathcal{P}_{\mathrm{lens}}>0.5$, of which 14 have $\mathcal{P}_{\mathrm{lens}}=1$, and clearly exhibiting secure strong lensing features, such as giant tangential and radial arcs, and multiple images. Considering the measured number density of lensing galaxy clusters, approximately $0.3\,\mathrm{deg}^{-2}$ for $\mathcal{P}_{\mathrm{lens}}>0.9$, we predict that \Euclid\ will likely see more than 4500 strong lensing clusters over the course of the mission. Notably, only three of the identified cluster-scale lenses had been previously observed from space. Thus, \Euclid has provided the first high-resolution imaging for the remaining $80$ galaxy cluster lenses, including those with the highest probability. The identified strong lensing features will be used for training deep-learning models for identifying gravitational arcs and multiple images automatically in \Euclid observations. This study confirms the huge potential of \Euclid for finding new strong lensing clusters, enabling exciting new discoveries on the nature of dark matter and dark energy and the study of the high-redshift Universe.

arXiv:2503.15328v1 Announce Type: new Abstract: The Euclid Wide Survey (EWS) is expected to identify of order $100\,000$ galaxy-galaxy strong lenses across $14\,000$deg$^2$. The Euclid Quick Data Release (Q1) of $63.1$deg$^2$ Euclid images provides an excellent opportunity to test our lens-finding ability, and to verify the anticipated lens frequency in the EWS. Following the Q1 data release, eight machine learning networks from five teams were applied to approximately one million images. This was followed by a citizen science inspection of a subset of around $100\,000$ images, of which $65\%$ received high network scores, with the remainder randomly selected. The top scoring outputs were inspected by experts to establish confident (grade A), likely (grade B), possible (grade C), and unlikely lenses. In this paper we combine the citizen science and machine learning classifiers into an ensemble, demonstrating that a combined approach can produce a purer and more complete sample than the original individual classifiers. Using the expert-graded subset as ground truth, we find that this ensemble can provide a purity of $52\pm2\%$ (grade A/B lenses) with $50\%$ completeness (for context, due to the rarity of lenses a random classifier would have a purity of $0.05\%$). We discuss future lessons for the first major Euclid data release (DR1), where the big-data challenges will become more significant and will require analysing more than $\sim300$ million galaxies, and thus time investment of both experts and citizens must be carefully managed.