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We use a sample of 11 $z\approx0.2-0.5$ ($z_{\text{med.}} = 0.36$) galaxy clusters from the Cluster Lensing And Supernovae survey with Hubble (CLASH) to analyse the angular dependence of satellite galaxy colour $(B-R)$ and passive galaxy fraction ($f_{\text{pass.}}$) with respect to the major axis of the brightest cluster galaxy (BCG). This phenomenon has been dubbed as \say{anisotropic quenching}, \say{angular conformity} or \say{angular segregation}, and it describes how satellite galaxies along the major axis of the BCG are more likely to be quenched than those along the minor axis. A highly significant anisotropic quenching signal is found for satellites, with a peak in $(B-R)$ and $f_{\text{pass.}}$ along the major axis. We are the first to measure anisotropic quenching out to cluster-centric radii of $3R_{200}$ ($R_{200\text{, med.}} \approx 933$ \si{\kilo\parsec}). We find that the signal is significant out to at least $2.5R_{200}$, and the amplitude of the signal peaks at $\approx1.25R_{200}$. This is the first time a radial peak of the anisotropic quenching signal has been measured directly. We suggest that this peak could be caused by a build-up of backsplash galaxies at this radius. Finally, we find that $f_{\text{pass.}}$ is significantly higher along the major axis for fixed values of local surface density. The density drops less rapidly along the major axis and so satellites spend more time being pre-processed here compared to the minor axis. We therefore conclude that pre-processing in large-scale structure, and not active galactic nuclei outflows (AGN), is the cause of the anisotropic quenching signal in massive galaxy clusters, however this may not be the cause in lower mass halos., Comment: 15 pages, 10 figures. This paper has been accepted for publication in MNRAS

We present a detailed study of the large-scale shock front in Stephan's Quintet, a byproduct of past and ongoing interactions. Using integral-field spectroscopy from the new William Herschel Telescope Enhanced Area Velocity Explorer (WEAVE), recent 144 MHz observations from the LOFAR Two-metre Sky Survey (LoTSS), and archival data from the Very Large Array and James Webb Space Telescope (JWST), we obtain new measurements of key shock properties and determine its impact on the system. Harnessing the WEAVE large integral field unit's (LIFU) field of view (90 $\times$ 78 arcsec$^{2}$), spectral resolution ($R\sim2500$) and continuous wavelength coverage across the optical band, we perform robust emission line modeling and dynamically locate the shock within the multi-phase intergalactic medium (IGM) with higher precision than previously possible. The shocking of the cold gas phase is hypersonic, and comparisons with shock models show that it can readily account for the observed emission line ratios. In contrast, we demonstrate that the shock is relatively weak in the hot plasma visible in X-rays (with Mach number of $\mathcal{M} \sim 2 - 4$), making it inefficient at producing the relativistic particles needed to explain the observed synchrotron emission. Instead, we propose that it has led to an adiabatic compression of the medium, which has increased the radio luminosity ten-fold. Comparison of the Balmer line-derived extinction map with the molecular gas and hot dust observed with JWST suggests that pre-existing dust may have survived the collision, allowing the condensation of H$_{2}$ - a key channel for dissipating the shock energy., Comment: 23 pages, 15 figures, accepted for publication in MNRAS

We present the first results of the JWST Emission Line Survey (JELS). Utilising the first NIRCam narrow-band imaging at 4.7$\mu$m, over 63 arcmin$^{2}$ in the PRIMER/COSMOS field, we identified 609 emission line galaxy candidates. From these, we robustly selected 35 H$\alpha$ star-forming galaxies at $z \sim 6.1$, with H$\alpha$ star-formation rates ($\rm{SFR_{H\alpha}}$) $\sim0.9-15\ \rm{M_{\odot} \ yr^{-1}}$. Combining our unique H$\alpha$ sample with the exquisite panchromatic data in the field, we explored their physical properties and star-formation histories, and compared these to a broad-band selected sample at $z\sim 6$ which offered vital new insights into the nature of high-redshift galaxies. UV-continuum slopes ($\beta$) were considerably redder for our H$\alpha$ sample ($\langle\beta\rangle\sim-1.92$) compared to the broad-band sample ($\langle\beta\rangle\sim-2.35$). This was not due to dust attenuation as our H$\alpha$ sample was relatively dust-poor (median $A_V=0.23$); instead, we argued the reddened slopes could be due to nebular continuum. We compared $\rm{SFR_{H\alpha}}$ and the UV-continuum-derived $\rm{SFR_{UV}}$ to SED-fitted measurements averaged over canonical timescales of 10 and 100 Myr ($\rm{SFR_{10}}$ and $\rm{SFR_{100}}$). We found an increase in recent SFR for our sample of H$\alpha$ emitters, particularly at lower stellar masses ($<10^9 \ \rm{M_{\odot}}$). We also found $\rm{SFR_{H\alpha}}$ strongly traced SFR averaged over 10 Myr timescales, whereas the UV-continuum over-predicts SFR on 100 Myr timescales at low stellar masses. These results point to our H$\alpha$ sample undergoing `bursty' star formation. Our F356W $z \sim 6$ sample showed a larger scatter in $\rm{SFR_{10}/SFR_{100}}$ across all stellar masses, which highlighted how narrow-band photometric selections of H$\alpha$ emitters are key to quantifying the burstiness of star-formation activity., Comment: Submitted to MRNAS; 27 pages, 19 figures. Accompanying data will be publicly released upon acceptance of this manuscript

We present the JWST Emission Line Survey (JELS), a Cycle 1 JWST imaging programme exploiting the wavelength coverage and sensitivity of NIRCam to extend narrow-band rest-optical emission line selection into the epoch of reionization (EoR) for the first time, and to enable unique studies of the resolved ionised gas morphology in individual galaxies across cosmic history. The primary JELS observations comprise $\sim4.7\mu$m narrow-band imaging over $\sim63$ arcmin$^{2}$ designed to enable selection of H$\alpha$ emitters at $z\sim6.1$, as well as the selection of a host of novel emission-line samples including [OIII] at $z\sim8.3$ and Pa $\alpha/\beta$ at $z\sim1.5/2.8$. For the prime F466N and F470N narrow-band observations, the emission-line sensitivities achieved are up to $\sim2\times$ more sensitive than current slitless spectroscopy surveys (5$\sigma$ limits of 1.1-1.6$\times10^{-18}\text{erg s}^{-1}\text{cm}^{-2}$), corresponding to unobscured H$\alpha$ star-formation rates (SFRs) of 1-1.6 $\text{M}_{\odot}\,\text{yr}^{-1}$ at $z\sim6.1$ and extending emission-line selections in the EoR to fainter populations. Simultaneously, JELS also obtained F200W broadband and F212N narrow-band imaging (H$\alpha$ at $z\sim2.23$) that probes SFRs $\gtrsim5\times$ fainter than previous ground-based narrow-band studies ($\sim0.2 \text{M}_{\odot}\text{yr}^{-1}$), offering an unprecedented resolved view of star formation at cosmic noon. In this paper we describe the detailed JELS survey design, key data processing steps specific to the survey observations, and demonstrate the exceptional data quality and imaging sensitivity achieved. We then summarise the key scientific goals of JELS and present some early science results, including examples of spectroscopically confirmed H$\alpha$ and [OIII] emitters discovered by JELS that illustrate the novel parameter space probed., Comment: Submitted to MRNAS; 13 pages, 8 figures. Accompanying data will be publicly released upon acceptance of this and companion paper (Pirie et al., arXiv:2410.11808). V2 updated to reflect revised author list and cross-citation to Pirie et al

Submillimetre galaxies (SMGs) are some of the most extreme star-forming systems in the Universe, whose place in the framework of galaxy evolution is as yet uncertain. It has been hypothesised that SMGs are progenitors of local early-type galaxies, requiring that SMGs generally reside in galaxy cluster progenitors at high redshift. We test this hypothesis and explore SMG environments using a narrowband VLT/HAWK-I+GRAAL study of H$\alpha$ and [OIII] emitters around an unbiased sample of three ALMA-identified and spectroscopically-confirmed SMGs at $z \sim 2.3$ and $z \sim 3.3$, where these SMGs were selected solely on spectroscopic redshift. Comparing with blank-field observations at similar epochs, we find that one of the three SMGs lies in an overdensity of emission-line sources on the $\sim4$ Mpc scale of the HAWK-I field of view, with overdensity parameter $\delta_{g} = 2.6^{+1.4}_{-1.2}$. A second SMG is significantly overdense only on $\lesssim 1.6$ Mpc scales and the final SMG is consistent with residing in a blank field environment. The total masses of the two overdensities are estimated to be $\log(M_{h}/{\rm M}_{\odot}) =$12.1--14.4, leading to present-day masses of $\log(M_{h,z=0}/{\rm M}_{\odot}) =$12.9--15.9. These results imply that SMGs occupy a range of environments, from overdense protoclusters or protogroups to the blank field, suggesting that while some SMGs are strong candidates for the progenitors of massive elliptical galaxies in clusters, this may not be their only possible evolutionary pathway., Comment: 21 pages, 12 figures. Accepted for publication in MNRAS

The field of Detection and Attribution is rapidly moving beyond weather and climate, and towards incorporating hazards and their impacts on natural and human systems. Here, we review the comprehensive literature base relevant for the UK ahead of the next Climate Change Risk Assessment. The current literature highlights a detectable and non-trivial influence of climate change in many UK impact sectors already - notably health, agriculture, and infrastructure. We found that heatwaves were the most studied hazard overall, with a unanimous consensus on a strong attributable signal of human-induced climate change in their increased frequency and intensity over the last century. The most notable gap identified overall was in attributing climate-related impacts to human influence, with a few impact studies for only a handful of the hazards assessed. Furthermore, just under half of the 29 hazards were not found to have any UK-relevant attribution studies, with most of the remainder having three or fewer. This review highlights requirements for and opportunities to develop attribution scicnce to meet the needs of the UK. Diversifying hazards and impacts studied, in conjunction with the techniques and approaches used, will undoubtedly benefit the community.

Commercially impactful quantum algorithms such as quantum chemistry and Shor's algorithm require a number of qubits and gates far beyond the capacity of any existing quantum processor. Distributed architectures, which scale horizontally by networking modules, provide a route to commercial utility and will eventually surpass the capability of any single quantum computing module. Such processors consume remote entanglement distributed between modules to realize distributed quantum logic. Networked quantum computers will therefore require the capability to rapidly distribute high fidelity entanglement between modules. Here we present preliminary demonstrations of some key distributed quantum computing protocols on silicon T centres in isotopically-enriched silicon. We demonstrate the distribution of entanglement between modules and consume it to apply a teleported gate sequence, establishing a proof-of-concept for T centres as a distributed quantum computing and networking platform., Comment: 14 pages, 13 figures

Weather forecasts are fundamentally uncertain, so predicting the range of probable weather scenarios is crucial for important decisions, from warning the public about hazardous weather, to planning renewable energy use. Here, we introduce GenCast, a probabilistic weather model with greater skill and speed than the top operational medium-range weather forecast in the world, the European Centre for Medium-Range Forecasts (ECMWF)'s ensemble forecast, ENS. Unlike traditional approaches, which are based on numerical weather prediction (NWP), GenCast is a machine learning weather prediction (MLWP) method, trained on decades of reanalysis data. GenCast generates an ensemble of stochastic 15-day global forecasts, at 12-hour steps and 0.25 degree latitude-longitude resolution, for over 80 surface and atmospheric variables, in 8 minutes. It has greater skill than ENS on 97.4% of 1320 targets we evaluated, and better predicts extreme weather, tropical cyclones, and wind power production. This work helps open the next chapter in operational weather forecasting, where critical weather-dependent decisions are made with greater accuracy and efficiency., Comment: Main text 11 pages, Appendices 76 pages

We present analysis of the mass-metallicity relation (MZR) for a sample of 67 [OIII]-selected star-forming galaxies at a redshift range of $z=1.99 - 2.32$ ($z_{\text{med}} = 2.16$) using \emph{Hubble Space Telescope} Wide Field Camera 3 grism spectroscopy from the Quasar Sightline and Galaxy Evolution (QSAGE) survey. Metallicities were determined using empirical gas-phase metallicity calibrations based on the strong emission lines [OII]3727,3729, [OIII]4959,5007 and H$\beta$. Star-forming galaxies were identified, and distinguished from active-galactic nuclei, via Mass-Excitation diagrams. Using $z\sim0$ metallicity calibrations, we observe a negative offset in the $z=2.2$ MZR of $\approx -0.51$ dex in metallicity when compared to locally derived relationships, in agreement with previous literature analysis. A similar offset of $\approx -0.46$ dex in metallicity is found when using empirical metallicity calibrations that are suitable out to $z\sim5$, though our $z=2.2$ MZR, in this case, has a shallower slope. We find agreement between our MZR and those predicted from various galaxy evolution models and simulations. Additionally, we explore the extended fundamental metallicity relation (FMR) which includes an additional dependence on star formation rate (SFR). Our results consistently support the existence of the FMR, as well as revealing an offset of $0.28\pm0.04$ dex in metallicity compared to locally-derived relationships, consistent with previous studies at similar redshifts. We interpret the negative correlation with SFR at fixed mass, inferred from an FMR existing for our sample, as being caused by the efficient accretion of metal-poor gas fuelling SFR at cosmic noon., Comment: 15 pages, 10 figures. This paper has been accepted for publication in MNRAS

We use Dark Energy Survey Year 3 (DES Y3) clusters with archival X-ray data from XMM-Newton and Chandra to assess the centering performance of the redMaPPer cluster finder and to measure key richness observable scaling relations. In terms of centering, we find that 10-20% of redMaPPer clusters are miscentered with no significant difference in bins of low versus high richness ($20<\lambda<40$ and $\lambda>40$) or redshift ($0.2

A few percent of red giants are enriched in Lithium with $A(\mathrm{Li}) > 1.5$. Their evolutionary status has remained uncertain because these Li-rich giants can be placed both on the red-giant branch (RGB) near the bump luminosity and in the red clump (RC) region. However, thanks to asteroseismology, it has been found that most of them are actually RC stars. Starting at the bump luminosity, RGB progenitors of the RC stars experience extra mixing in the radiative zone separating the H-burning shell from the convective envelope followed by a series of convective He-shell flashes at the RGB tip, known as the He-core flash. The He-core flash was proposed to cause fast extra mixing in the stars at the RGB tip that is needed for the Cameron-Fowler mechanism to produce Li. We propose that the RGB stars are getting enriched in Li by the RGB extra mixing that is getting enhanced and begins to produce Li, instead of destroying it, when the stars are approaching the RGB tip. After a discussion of several mechanisms of the RGB extra mixing, including the joint operation of rotation-driven meridional circulation and turbulent diffusion, the Azimuthal Magneto-Rotational Instability (AMRI), thermohaline convection, buoyancy of magnetic flux tubes, and internal gravity waves, and based on results of (magneto-) hydrodynamics simulations and asteroseismology observations, we are inclined to conclude that it is the mechanism of the AMRI or magnetically-enhanced thermohaline convection, that is most likely to support our hypothesis., Comment: 17 pages, 11 figures, accepted for publication in MNRAS

The second data release of the LOFAR Two-Metre Sky Survey (LoTSS) covers 27% of the northern sky, with a total area of $\sim 5,700$ deg$^2$. The high angular resolution of LOFAR with Dutch baselines (6 arcsec) allows us to carry out optical identifications of a large fraction of the detected radio sources without further radio followup; however, the process is made more challenging by the many extended radio sources found in LOFAR images as a result of its excellent sensitivity to extended structure. In this paper we present source associations and identifications for sources in the second data release based on optical and near-infrared data, using a combination of a likelihood-ratio cross-match method developed for our first data release, our citizen science project Radio Galaxy Zoo: LOFAR, and new approaches to algorithmic optical identification, together with extensive visual inspection by astronomers. We also present spectroscopic or photometric redshifts for a large fraction of the optical identifications. In total 4,116,934 radio sources lie in the area with good optical data, of which 85% have an optical or infrared identification and 58% have a good redshift estimate. We demonstrate the quality of the dataset by comparing it with earlier optically identified radio surveys. This is by far the largest ever optically identified radio catalogue, and will permit robust statistical studies of star-forming and radio-loud active galaxies., Comment: 29 pages. Accepted by A&A; data products available at https://lofar-surveys.org/dr2_release.html

We cross-match and compare characteristics of galaxy clusters identified in observations from two sky surveys using two completely different techniques. One sample is optically selected from the analysis of three years of Dark Energy Survey observations using the redMaPPer cluster detection algorithm. The second is X-ray selected from XMM observations analysed by the XMM Cluster Survey. The samples comprise a total area of 57.4 deg$^2$, bounded by the area of 4 contiguous XMM survey regions that overlap the DES footprint. We find that the X-ray selected sample is fully matched with entries in the redMaPPer catalogue, above $\lambda>$20 and within 0.1$< z <$0.9. Conversely, only 38\% of the redMaPPer catalogue is matched to an X-ray extended source. Next, using 120 optically clusters and 184 X-ray selected clusters, we investigate the form of the X-ray luminosity-temperature ($L_{X}-T_{X}$), luminosity-richness ($L_{X}-\lambda$) and temperature-richness ($T_{X}-\lambda$) scaling relations. We find that the fitted forms of the $L_{X}-T_{X}$ relations are consistent between the two selection methods and also with other studies in the literature. However, we find tentative evidence for a steepening of the slope of the relation for low richness systems in the X-ray selected sample. When considering the scaling of richness with X-ray properties, we again find consistency in the relations (i.e., $L_{X}-\lambda$ and $T_{X}-\lambda$) between the optical and X-ray selected samples. This is contrary to previous similar works that find a significant increase in the scatter of the luminosity scaling relation for X-ray selected samples compared to optically selected samples., Comment: Accepted for publication to MNRAS

We prove that the "pseudo-$F_4$" group is isomorphic to $F_4$, answering a question of Brin. Both of these groups can be described as fast groups of homeomorphisms of the interval generated by bumps, as introduced by Bleak, Brin, Kassabov, Moore, and Zaremsky. The proof uses a representation of fast groups as Guba-Sapir diagram groups in order to leverage known results on isomorphisms of diagram groups.

Global medium-range weather forecasting is critical to decision-making across many social and economic domains. Traditional numerical weather prediction uses increased compute resources to improve forecast accuracy, but cannot directly use historical weather data to improve the underlying model. We introduce a machine learning-based method called "GraphCast", which can be trained directly from reanalysis data. It predicts hundreds of weather variables, over 10 days at 0.25 degree resolution globally, in under one minute. We show that GraphCast significantly outperforms the most accurate operational deterministic systems on 90% of 1380 verification targets, and its forecasts support better severe event prediction, including tropical cyclones, atmospheric rivers, and extreme temperatures. GraphCast is a key advance in accurate and efficient weather forecasting, and helps realize the promise of machine learning for modeling complex dynamical systems., Comment: GraphCast code and trained weights are available at: https://github.com/deepmind/graphcast