Search for: All records

Context.We identified and analysed massive quiescent galaxies (MQGs) atz ≈ 3.1 within the 2 deg²COSMOS field and explored the effect of the galaxy environment on quenching processes. By examining the variation in the quenched fraction and physical properties of these galaxies in different environmental contexts, including local densities, protoclusters, and cosmic filaments, we investigated the connection between environmental factors and galaxy quenching at cosmic noon. Aims.We selected MQGs atz ≈ 3.1 using deep photometric data from the COSMOS2020 catalogue combined with narrow-band-selected Lyman-αemitters (LAEs) from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey. We performed a spectral energy distribution fitting using the code BAGPIPES to derive the star formation histories and quenching timescales. We constructed Voronoi-tessellation density maps using LAEs, and we independently selected galaxies photometrically to characterize the galaxy environments. Methods.We identified 24 MQGs atz ≈ 3.1, each of which has a stellar mass higher than 10^10.6 M_⊙. These MQGs share remarkably uniform star-formation histories, with intense starburst phases followed by rapid quenching within short timescales (≤400 Myr). The consistency of these quenching timescales suggests a universal and highly efficient quenching mechanism in this epoch. We found no significant correlation between environmental density (either local or large scale) and galaxy quenching parameters such as the quenching duration, the quenched fraction, or the timing. MQGs show no preferential distribution with respect to protoclusters or filaments compared to massive star-forming galaxies. Some MQGs reside close to gas-rich filaments, but show no evidence of rejuvenated star formation. This implies gas-heating mechanisms and not gas exhaustion. These results indicate that the quenching processes atz ≈ 3.1 likely depend little on the immediate galaxy environment. Results.Our findings suggest that environmental processes alone, such as galaxy mergers, interactions, or gas stripping, cannot fully explain the galaxy quenching atz ≈ 3.1. Internal mechanisms such as feedback from AGN, stellar feedback, virial shock heating, or morphological quenching instead play an important role in quenching. Future spectroscopic observations must confirm the quiescent nature and precise redshifts of these galaxies. Observational studies of gas dynamics, gas temperature, and ionisation conditions within and around MQGs will also clarify the physical mechanisms driving galaxy quenching during this critical epoch of galaxy evolution. 

Context.Submillimeter galaxies (SMGs) constitute a key population of bright star-forming galaxies at high-redshift. These galaxies challenge galaxy formation models, particularly regarding the reproduction of their observed number counts and redshift distributions. Furthermore, although SMGs contribute significantly to the cosmic star formation rate density (SFRD), their precise role remains uncertain. Upcoming surveys, such as the Ultra Deep Survey with the TolTEC camera, are expected to offer valuable insights into SMG properties and their broader impact in the Universe. Aims.Robust modeling of SMGs in a cosmological representative volume is necessary to investigate their nature in preparation for next-generation submillimeter surveys. Here, we test different parametric models for SMGs in large-volume hydrodynamical simulations, assess their contribution to the SFRD, and build expectations for future submillimeter surveys. Methods.We implement and test parametric relations derived from radiative transfer calculations across three cosmological simulation suites: EAGLE, IllustrisTNG, and FLAMINGO. We place particular emphasis on the FLAMINGO simulations due to their large volume and robust statistical sampling of SMGs. Based on the model that best reproduces observational number counts, we forecast submillimeter fluxes within the simulations, analyze the properties of SMGs, and evaluate their evolution over cosmic time. Results.Our results show that the FLAMINGO simulation reproduces the observed redshift distribution and source number counts of SMGs without requiring a top-heavy initial mass function. On the other hand, the EAGLE and IllustrisTNG simulations show a deficit of bright SMGs. We find that SMGs with S₈₅₀ > 1 mJy contribute up to ∼27% of the cosmic SFRD atz ∼ 2.6 in the FLAMINGO simulation, which is consistent with recent observations. Flux density functions reveal a rise in SMG abundance fromz = 6 toz = 2.5 that is followed by a sharp decline in the number of brighter SMGs fromz = 2.5 toz = 0. Leveraging the SMG population in FLAMINGO, we forecast that the TolTEC UDS will detect ∼80 000 sources over 0.8 deg²at 1.1 mm (at the 4σdetection limit), capturing about 50% of the cosmic SFRD atz ∼ 2.5. 

Abstract The One-hundred-deg²DECam Imaging in Narrowbands (ODIN) survey is carrying out a systematic search for protoclusters during Cosmic Noon, using Lyα-emitting galaxies (LAEs) as tracers. Once completed, ODIN aims to identify hundreds of protoclusters at redshifts of 2.4, 3.1, and 4.5 across seven extragalactic fields, covering a total area of up to 91 deg². In this work, we report the high clustering strength of the ODIN protoclusters, determined via measurements of their cross-correlation with LAEs. Our sample consists of 150 protocluster candidates atz = 2.4 and 3.1, identified in two ODIN fields with a total area of 13.9 deg². Atz = 2.4 and 3.1, the inferred protocluster biases are $6.6_{-1.1}^{+1.3}$and $6.1_{-1.1}^{+1.3}$, corresponding to mean halo masses of $\log 〈M/M_{\odot }〉=13.53_{-0.24}^{+0.21}$and $12.96_{-0.33}^{+0.28}$, respectively. By the present day, these protoclusters are expected to evolve into virialized galaxy clusters with a mean mass of ∼10^14.5M_⊙. By comparing the observed number density of protoclusters to that of halos with the same measured clustering strength, we find that the completeness of our sample is of order unity. Finally, the similar descendant masses derived for our samples atz= 2.4 and 3.1, assuming that the halo number density remains constant, suggest that they represent similar structures observed at different cosmic epochs. As a consequence, any observed differences between the two samples can be understood as redshift evolution. The ODIN protocluster samples will thus provide valuable insights into the cosmic evolution of cluster galaxies. 

A solvent-free post-treatment process known as vapor phase infiltration (VPI) is used to engineer the organic solvent reverse osmosis (OSRO) performance of polymer of intrinsic microporosity 1 (PIM-1) membranes via infiltration of trimethylaluminum (TMA) metal-organic vapor. The infiltration of inorganic aluminum constituents hybridizes the pure polymer PIM-1 into an organic-inorganic material (AlOxHy/PIM-1) with enhanced chemical stability. A homogenous distribution of inorganic loading in PIM-1 is achieved due to the reaction-limited infiltration mechanism, and the OSRO performance is enhanced as a result. OSRO separations of ethanol/isooctane mixtures using these membranes are shown to be capable of breaking the azeotropic composition with a separation factor for ethanol over isooctane greater than 5 and an ethanol permeance of 0.1 Lm–2h–1bar–1. Thus, these organic-inorganic hybrid membranes created via VPI show promise as an alternative method for separating azeotropic liquid mixtures. 

Abstract Whitebark pine (WBP, Pinus albicaulis) is a white pine of subalpine regions in the Western contiguous United States and Canada. WBP has become critically threatened throughout a significant part of its natural range due to mortality from the introduced fungal pathogen white pine blister rust (WPBR, Cronartium ribicola) and additional threats from mountain pine beetle (Dendroctonus ponderosae), wildfire, and maladaptation due to changing climate. Vast acreages of WBP have suffered nearly complete mortality. Genomic technologies can contribute to a faster, more cost-effective approach to the traditional practices of identifying disease-resistant, climate-adapted seed sources for restoration. With deep-coverage Illumina short reads of haploid megagametophyte tissue and Oxford Nanopore long reads of diploid needle tissue, followed by a hybrid, multistep assembly approach, we produced a final assembly containing 27.6 Gb of sequence in 92,740 contigs (N50 537,007 bp) and 34,716 scaffolds (N50 2.0 Gb). Approximately 87.2% (24.0 Gb) of total sequence was placed on the 12 WBP chromosomes. Annotation yielded 25,362 protein-coding genes, and over 77% of the genome was characterized as repeats. WBP has demonstrated the greatest variation in resistance to WPBR among the North American white pines. Candidate genes for quantitative resistance include disease resistance genes known as nucleotide-binding leucine-rich repeat receptors (NLRs). A combination of protein domain alignments and direct genome scanning was employed to fully describe the 3 subclasses of NLRs. Our high-quality reference sequence and annotation provide a marked improvement in NLR identification compared to previous assessments that leveraged de novo-assembled transcriptomes. 

Abstract PremiseRobust standards to evaluate quality and completeness are lacking in eukaryotic structural genome annotation, as genome annotation software is developed using model organisms and typically lacks benchmarking to comprehensively evaluate the quality and accuracy of the final predictions. The annotation of plant genomes is particularly challenging due to their large sizes, abundant transposable elements, and variable ploidies. This study investigates the impact of genome quality, complexity, sequence read input, and method on protein‐coding gene predictions. MethodsThe impact of repeat masking, long‐read and short‐read inputs, and de novo and genome‐guided protein evidence was examined in the context of the popular BRAKER and MAKER workflows for five plant genomes. The annotations were benchmarked for structural traits and sequence similarity. ResultsBenchmarks that reflect gene structures, reciprocal similarity search alignments, and mono‐exonic/multi‐exonic gene counts provide a more complete view of annotation accuracy. Transcripts derived from RNA‐read alignments alone are not sufficient for genome annotation. Gene prediction workflows that combine evidence‐based and ab initio approaches are recommended, and a combination of short and long reads can improve genome annotation. Adding protein evidence from de novo assemblies, genome‐guided transcriptome assemblies, or full‐length proteins from OrthoDB generates more putative false positives as implemented in the current workflows. Post‐processing with functional and structural filters is highly recommended. DiscussionWhile the annotation of non‐model plant genomes remains complex, this study provides recommendations for inputs and methodological approaches. We discuss a set of best practices to generate an optimal plant genome annotation and present a more robust set of metrics to evaluate the resulting predictions. 

Abstract To understand the formation and evolution of massive cosmic structures, studying them at high redshift, in the epoch when they formed the majority of their mass, is essential. The One-hundred-deg²DECam Imaging in Narrowbands (ODIN) survey is undertaking the widest-area narrowband program to date, to use Lyα-emitting galaxies (LAEs) to trace the large-scale structure (LSS) of the Universe on the scale of 10–100 cMpc at three cosmic epochs. In this work, we present results atz= 3.1 based on early ODIN data in the COSMOS field. We identify protoclusters and cosmic filaments using multiple methods and discuss their strengths and weaknesses. We then compare our observations against the IllustrisTNG suite of cosmological hydrodynamical simulations. The two are in excellent agreement, identifying a similar number and angular size of structures above a specified density threshold. We successfully recover the simulated protoclusters with log(M_z=0/M_⊙) ≳ 14.4 in ∼60% of the cases. With these objects, we show that the descendant masses of our observed protoclusters can be estimated purely based on our 2D measurements, finding a medianz= 0 mass of ∼10^14.5M_⊙. The lack of information on the radial extent of each protocluster introduces a ∼0.4 dex uncertainty in its descendant mass. Finally, we show that the recovery of the cosmic web in the vicinity of protoclusters is both efficient and accurate. The similarity of our observations and the simulations implies that our structure selection is likewise robust and efficient, demonstrating that LAEs are reliable tracers of the LSS. 

Abstract Lyman-alpha-emitting galaxies (LAEs) are typically young, low-mass, star-forming galaxies with little extinction from interstellar dust. Their low dust attenuation allows their Lyαemission to shine brightly in spectroscopic and photometric observations, providing an observational window into the high-redshift Universe. Narrowband surveys reveal large, uniform samples of LAEs at specific redshifts that probe large-scale structure and the temporal evolution of galaxy properties. The One-hundred-deg²DECam Imaging in Narrowbands (ODIN) utilizes three custom-made narrowband filters on the Dark Energy Camera (DECam) to discover LAEs at three equally spaced periods in cosmological history. In this paper, we introduce the hybrid-weighted double-broadband continuum estimation technique, which yields improved estimation of Lyαequivalent widths. Using this method, we discover 6032, 5691, and 4066 LAE candidates atz= 2.4, 3.1, and 4.5 in the extended COSMOS field (∼9 deg²). We find that [Oii] emitters are a minimal contaminant in our LAE samples, but that interloping Green Pea–like [Oiii] emitters are important for our redshift 4.5 sample. We introduce an innovative method for identifying [Oii] and [Oiii] emitters via a combination of narrowband excess and galaxy colors, enabling their study as separate classes of objects. We present scaled median stacked spectral energy distributions for each galaxy sample, revealing the overall success of our selection methods. We also calculate rest-frame Lyαequivalent widths for our LAE samples and find that the EW distributions are best fit by exponential functions with scale lengths ofw₀= 53 ± 1, 65 ± 1, and 59 ± 1 Å, respectively.