Searching for globular cluster chemical anomalies on the main sequence of a young massive cluster

The spectroscopic and photometric signals of the star-to-star abundance variations found in globular clusters seem to be correlated with global parameters like the cluster’s metallicity, mass, and age. Understanding this behaviour could bring us closer to the origin of these intriguing abundance spreads. In this work we use deep HST photometry to look for evidence of abundance variations in the main sequence of a young massive cluster NGC 419 (∼105 M⊙, ∼1.4 Gyr). Unlike previous studies, here we focus on stars in the same mass range found in old globulars (∼0.75–1 M⊙), where light elements variations are detected. We find no evidence for N abundance variations among these stars in the Un − B and U − B colour–magnitude diagrams of NGC 419. This is at odds with the N variations found in old globulars like 47 Tuc, NGC 6352, and NGC 6637 with similar metallicity to NGC 419. Although the signature of the abundance variations characteristic of old globulars appears to be significantly smaller or absent in this young cluster, we cannot conclude if this effect is mainly driven by its age or its mass

The Interstellar Medium In Galaxies Seen A Billion Years After The Big Bang

Evolution in the measured rest frame ultraviolet spectral slope and ultraviolet to optical flux ratios indicate a rapid evolution in the dust obscuration of galaxies during the first 3 billion years of cosmic time (z>4). This evolution implies a change in the average interstellar medium properties, but the measurements are systematically uncertain due to untested assumptions, and the inability to measure heavily obscured regions of the galaxies. Previous attempts to directly measure the interstellar medium in normal galaxies at these redshifts have failed for a number of reasons with one notable exception. Here we report measurements of the [CII] gas and dust emission in 9 typical (~1-4L*) star-forming galaxies ~1 billon years after the big bang (z~5-6). We find these galaxies have >12x less thermal emission compared with similar systems ~2 billion years later, and enhanced [CII] emission relative to the far-infrared continuum, confirming a strong evolution in the interstellar medium properties in the early universe. The gas is distributed over scales of 1-8 kpc, and shows diverse dynamics within the sample. These results are consistent with early galaxies having significantly less dust than typical galaxies seen at z<3 and being comparable to local low-metallicity systems.Comment: Submitted to Nature, under review after referee report. 22 pages, 4 figures, 4 Extended Data Figures, 5 Extended Data table

Lensing without borders. I. A blind comparison of the amplitude of galaxy-galaxy lensing between independent imaging surveys

Lensing Without Borders is a cross-survey collaboration created to assess the consistency of galaxy-galaxy lensing signals (ΔΣ) across different data-sets and to carry out end-to-end tests of systematic errors. We perform a blind comparison of the amplitude of ΔΣ using lens samples from BOSS and six independent lensing surveys. We find good agreement between empirically estimated and reported systematic errors which agree to better than 2.3σ in four lens bins and three radial ranges. For lenses with zL &amp;gt; 0.43 and considering statistical errors, we detect a 3-4σ correlation between lensing amplitude and survey depth. This correlation could arise from the increasing impact at higher redshift of unrecognised galaxy blends on shear calibration and imperfections in photometric redshift calibration. At zL &amp;gt; 0.54 amplitudes may additionally correlate with foreground stellar density. The amplitude of these trends is within survey-defined systematic error budgets which are designed to include known shear and redshift calibration uncertainty. Using a fully empirical and conservative method, we do not find evidence for large unknown systematics. Systematic errors greater than 15 per cent (25 per cent) ruled out in three lens bins at 68 per cent (95 per cent) confidence at z &amp;lt; 0.54. Differences with respect to predictions based on clustering are observed to be at the 20-30 per cent level. Our results therefore suggest that lensing systematics alone are unlikely to fully explain the ‘lensing is low’ effect at z &amp;lt; 0.54. This analysis demonstrates the power of cross-survey comparisons and provides a promising path for identifying and reducing systematics in future lensing analyses

Euclid preparation: X. The Euclid photometric-redshift challenge

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-zs at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2−2.6 redshift range that the Euclid mission will probe. We designed a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data was divided into two samples: one calibration sample for which photometry and redshifts were provided to the participants; and the validation sample, containing only the photometry to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates the sources they consider unfit for use in cosmological analyses. The performance of each method was assessed through a set of informative metrics, using cross-matched spectroscopic and highlyaccurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, that is to say sources for which the photo-z deviates by more than 0.15(1 + z) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. We find that no machine-learning method provides good results in the regions of galaxy color-space that are sparsely populated by spectroscopic-redshifts, for example z > 1. However they generally perform better than template-fitting methods at low redshift (z < 0.7), indicating that template-fitting methods do not use all of the information contained in the photometry. We introduce metrics that quantify both photo-z precision and completeness of the samples (post-rejection), since both contribute to the final figure of merit of the science goals of the survey (e.g., cosmic shear from Euclid). Template-fitting methods provide the best results in these metrics, but we show that a combination of template-fitting results and machine-learning results with rejection criteria can outperform any individual method. On this basis, we argue that further work in identifying how to best select between machine-learning and template-fitting approaches for each individual galaxy should be pursued as a priority

Observations of Lyα\alpha Emitters at High Redshift

In this series of lectures, I review our observational understanding of high-$z$ Ly$\alpha$ emitters (LAEs) and relevant scientific topics. Since the discovery of LAEs in the late 1990s, more than ten (one) thousand(s) of LAEs have been identified photometrically (spectroscopically) at $z\sim 0$ to $z\sim 10$. These large samples of LAEs are useful to address two major astrophysical issues, galaxy formation and cosmic reionization. Statistical studies have revealed the general picture of LAEs' physical properties: young stellar populations, remarkable luminosity function evolutions, compact morphologies, highly ionized inter-stellar media (ISM) with low metal/dust contents, low masses of dark-matter halos. Typical LAEs represent low-mass high-$z$ galaxies, high-$z$ analogs of dwarf galaxies, some of which are thought to be candidates of population III galaxies. These observational studies have also pinpointed rare bright Ly$\alpha$ sources extended over $\sim 10-100$ kpc, dubbed Ly$\alpha$ blobs, whose physical origins are under debate. LAEs are used as probes of cosmic reionization history through the Ly$\alpha$ damping wing absorption given by the neutral hydrogen of the inter-galactic medium (IGM), which complement the cosmic microwave background radiation and 21cm observations. The low-mass and highly-ionized population of LAEs can be major sources of cosmic reionization. The budget of ionizing photons for cosmic reionization has been constrained, although there remain large observational uncertainties in the parameters. Beyond galaxy formation and cosmic reionization, several new usages of LAEs for science frontiers have been suggested such as the distribution of {\sc Hi} gas in the circum-galactic medium and filaments of large-scale structures. On-going programs and future telescope projects, such as JWST, ELTs, and SKA, will push the horizons of the science frontiers.Comment: Lecture notes for `Lyman-alpha as an Astrophysical and Cosmological Tool', Saas-Fee Advanced Course 46. Verhamme, A., North, P., Cantalupo, S., & Atek, H. (eds.) --- 147 pages, 103 figures. Abstract abridged. Link to the lecture program including the video recording and ppt files : https://obswww.unige.ch/Courses/saas-fee-2016/program.cg

The outer stellar mass of massive galaxies: a simple tracer of halo mass with scatter comparable to richness and reduced projection effects

Using the weak gravitational lensing data from the Hyper Suprime-Cam Subaru Strategic Program (HSC survey), we study the potential of different stellar mass estimates in tracing halo mass. We consider galaxies with log10(M∗/M⊙) &gt; 11.5 at 0.2 &lt; z &lt; 0.5 with carefully measured light profiles, and clusters from the redMaPPer and CAMIRA richness-based algorithms. We devise a method (the 'Top-N test') to evaluate the scatter in the halo mass-observable relation for different tracers, and to inter-compare halo mass proxies in four number density bins using stacked galaxy-galaxy lensing profiles. This test reveals three key findings. Stellar masses based on CModel photometry and aperture luminosity within R &lt;30 kpc are poor proxies of halo mass. In contrast, the stellar mass of the outer envelope is an excellent halo mass proxy. The stellar mass within R = [50, 100] kpc, M∗, [50, 100], has performance comparable to the state-of-the-art richness-based cluster finders at log10Mvir ⪎ 14.0 and could be a better halo mass tracer at lower halo masses. Finally, using N-body simulations, we find that the lensing profiles of massive haloes selected by M∗, [50, 100] are consistent with the expectation for a sample without projection or mis-centring effects. Richness-selected clusters, on the other hand, display an excess at R ∼1 Mpc in their lensing profiles, which may suggest a more significant impact from selection biases. These results suggest that M∗-based tracers have distinct advantages in identifying massive haloes, which could open up new avenues for cluster cosmology. The codes and data used in this work can be found here

Nested sampling for physical scientists

We review Skilling's nested sampling (NS) algorithm for Bayesian inference and more broadly multi-dimensional integration. After recapitulating the principles of NS, we survey developments in implementing efficient NS algorithms in practice in high-dimensions, including methods for sampling from the so-called constrained prior. We outline the ways in which NS may be applied and describe the application of NS in three scientific fields in which the algorithm has proved to be useful: cosmology, gravitational-wave astronomy, and materials science. We close by making recommendations for best practice when using NS and by summarizing potential limitations and optimizations of NS

Euclid preparation: X. The Euclid photometric-redshift challenge

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-zs at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2pdbl-pdbl2.6 redshift range that the Euclid mission will probe. We designed a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data was divided into two samples: one calibration sample for which photometry and redshifts were provided to the participants; and the validation sample, containing only the photometry to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates the sources they consider unfit for use in cosmological analyses. The performance of each method was assessed through a set of informative metrics, using cross-matched spectroscopic and highly-accurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, that is to say sources for which the photo-z deviates by more than 0.15(1pdbl+pdblz) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. We find that no machine-learning method provides good results in the regions of galaxy color-space that are sparsely populated by spectroscopic-redshifts, for example zpdbl&gt; pdbl1. However they generally perform better than template-fitting methods at low redshift (zpdbl&lt; pdbl0.7), indicating that template-fitting methods do not use all of the information contained in the photometry. We introduce metrics that quantify both photo-z precision and completeness of the samples (post-rejection), since both contribute to the final figure of merit of the science goals of the survey (e.g., cosmic shear from Euclid). Template-fitting methods provide the best results in these metrics, but we show that a combination of template-fitting results and machine-learning results with rejection criteria can outperform any individual method. On this basis, we argue that further work in identifying how to best select between machine-learning and template-fitting approaches for each individual galaxy should be pursued as a priority