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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The genetic architecture of leaf stable carbon isotope composition in Zea mays and the effect of transpiration efficiency on leaf elemental accumulation

With increased demand on freshwater resources for agriculture, it is imperative that more water-use efficient crops are developed. Leaf stable carbon isotope composition, δ 13 C, is a proxy for transpiration efficiency and a possible tool for breeders, but the underlying mechanisms effecting δ 13 C in C 4 plants are not known. It has been suggested that differences in specific leaf area (SLA), which potentially reflects variation in internal CO 2 diffusion, can impact leaf δ 13 C. Furthermore, although it is known that water movement is important for elemental uptake, it is not clear how manipulation of transpiration for increased water-use efficiency may impact nutrient accumulation. Here, we characterize the genetic architecture of leaf δ 13 C and test its relationship to SLA and the ionome in five populations of maize. Five significant QTL for leaf δ 13 C were identified, including novel QTL as well as some that were identified previously in maize kernels. One of the QTL regions contains an Erecta-like gene, the ortholog of which has been shown to regulate transpiration efficiency and leaf δ 13 C in Arabidopsis. QTL for δ 13 C were located in the same general chromosome region, but slightly shifted, when comparing data from two different years. Our data does not support a relationship between δ 13 C and SLA, and of the 19 elements analyzed, only a weak correlation between molybdenum and δ 13 C was detected. Together these data add to the genetic understanding of leaf δ 13 C in maize and suggest that improvements to plant water use may be possible without significantly influencing elemental homeostasis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean ( Glycine max ) nested association mapping population

We report photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500–2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R 2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A viscoelastic model for seismic attenuation using fractal mechanical networks

SUMMARY Seismic attenuation (quantified by the quality factor Q) has a significant impact on the seismic waveforms, especially in the fluid-saturated rocks. This dissipative process can be phenomenologically represented by viscoelastic models. Previous seismological studies show that the Q value of Earth media exhibits a nearly frequency-independent behaviour (often referred to as constant-Q in literature) in the seismic frequency range. Such attenuation can be described by the mathematical Kjartansson constant-Q model, which lacks of a physical representation in the viscoelastic sense. Inspired by the fractal nature of the pore fluid distribution in patchy-saturated rocks, here we propose two fractal mechanical network (FMN) models, that is, a fractal tree model and a quasi-fractal ladder model, to phenomenologically represent the frequency-independent Q behaviour. As with the classic viscoelastic models, the FMN models are composed of mechanical elements (spring and dashpots) arranged in different hierarchical patterns. A particular parametrization of each model can produce the same complex modulus as in the Kjartansson model, which leads to the constant-Q. Applying the theory to several typical rock samples, we find that the seismic attenuation signature of these rocks can be accurately represented by either one of the FMN models. Besides, we demonstrate that the ladder model in particular exhibits the realistic multiscale fractal structure of the saturated rocks. Therefore, the FMN models as a proxy could provide a new way to estimate the microscopic rock structure property from macroscopic seismic attenuation observation.

Geochemistry & Geophysics↗
DOE OSTI2023

Transforming microseismic clouds into near real-time visualization of the growing hydraulic fracture

SUMMARY Microseismic observations during unconventional reservoir stimulation are typically seen as a proxy for clusters of hydraulic fractures and the extent of the stimulated reservoir. Such straightforward interpretation is often misleading and fails to provide a physically reasonable image of the fracturing process. This paper demonstrates the application of a physics-based machine learning algorithm which enables a rapid and accurate fracture mapping from the microseismic data. Our training and validation data set relies on a history-matched geomechanical modelling workflow implemented in GEOS software for the Hydraulic Fracturing Test Site 1 (HFTS-1) project. For this study we augmented the simulated fracture growth through geostatistical modelling of induced seismicity, so that the synthetic microseismic catalogue matches the main statistical properties of the field observations. We formulated the problem of mapping the actual fracture in the clutter of events to parallel common video segmentation workflows: several past video frames (microseismic density snapshots) are passed through a deep convolutional network to classify whether a given voxel is associated with a fracture or intact rock. We found that for accurate fracture mapping, the network’s input and architecture must be augmented to incorporate the fluid injection parameters (pressure, rate, concentration of proppant, and location of the perforation within the cluster). The error rate for the network reached as little as 10 per cent of the fracture area, while a conventional microseismic interpretation approach yielded ∼300 per cent. Our approach also yields must faster predictions than conventional methods (minutes instead of weeks), and could enable engineers to make rapid decisions regarding engineering parameters (pumping rate, viscosity) in real time during stimulation.

58 GEOSCIENCES↗
DOE OSTI2023

An adjoint-based optimization method for jointly inverting heterogeneous material properties and fault slip from earthquake surface deformation data

SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.

Geochemistry & Geophysics↗
DOE OSTI2023

The effect of shear strain and shear localization on fault healing

The seismic cycle of repeated earthquake failure requires that faults regain frictional strength during the interseismic phase, when the fault is locked or undergoing quasi-static creep. Fault healing plays a central role in determining earthquake stress drop, recurrence interval, elastic radiation frequency and other source parameters. In particular, the longer a fault remains quasi-stationary, the stronger it becomes and the larger the potential stress drop can be for the next event. Here, we address the role of shear strain and strain localization on fault healing and healing rate. We performed slide-hold-slide friction experiments on quartz gouge in the double-direct shear configuration for shear strain up to 25 and hold times from 10 to 1000 s. The results show that both healing and healing rate increase nonlinearly with increasing shear strain. Frictional healing scales with volumetric strain within the laboratory fault zone. Using the volumetric strain upon reshear as a proxy for strain localization, we demonstrate that the capacity of a fault to heal is directly proportional to shear bandwidth and degree of strain localization. The more the deformation is localized, the higher are the healing and healing rate, and thus, the fault strength. Our data provide a framework for understanding variations in fault strength over the seismic cycle and the role of brecciation and strain localization on spatiotemporal variations in fault strength.

58 GEOSCIENCES↗
DOE OSTI2025

Integrating Intermediate Traits in Phylogenetic Genotype-to-Phenotype Studies

A major goal of research in evolution and genetics is linking genotype to phenotype. This work could be direct, such as determining the genetic basis of a phenotype by leveraging genetic variation or divergence in a developmental, physiological, or behavioral trait. The work could also involve studying the evolutionary phenomena (e.g., reproductive isolation, adaptation, sexual dimorphism, behavior) that reveal an indirect link between genotype and a trait of interest. When the phenotype diverges across evolutionarily distinct lineages, this genotype-to-phenotype problem can be addressed using phylogenetic genotype-to-phenotype (PhyloG2P) mapping, which uses genetic signatures and convergent phenotypes on a phylogeny to infer the genetic bases of traits. The PhyloG2P approach has proven powerful in revealing key genetic changes associated with diverse traits, including the mammalian transition to marine environments and transitions between major mechanisms of photosynthesis. However, there are several intermediate traits layered in between genotype and the phenotype of interest, including but not limited to transcriptional profiles, chromatin states, protein abundances, structures, modifications, metabolites, and physiological parameters. Each intermediate trait is interesting and informative in its own right, but synthesis across data types has great promise for providing a deep, integrated, and predictive understanding of how genotypes drive phenotypic differences and convergence. We argue that an expanded PhyloG2P framework (the PhyloG2P matrix) that explicitly considers intermediate traits, and imputes those that are prohibitive to obtain, will allow a better mechanistic understanding of any trait of interest. Furthermore, this approach provides a proxy for functional validation and mechanistic understanding in organisms where laboratory manipulation is impractical.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Seabird distribution is better predicted by abundance of prey than oceanography. A case study in the Gulf of Cadiz (SW, Iberian Peninsula)

Abstract Quantifying factors that influence marine predator distributions is essential to understanding the current and future change in marine biodiversity. Here, we test whether marine predator distribution relates to prey, or is better predicted by other specific habitat features. We examine the correlation between spatial distribution of three seabird species and their prey, as well as environmental proxies (oceanographic characteristics) in the Gulf of Cadiz, NE Atlantic. We modeled the at-sea distribution of Cory's shearwater, Balearic shearwater and Northern gannet, based on: (i) pelagic fish abundance according to acoustic surveys, and (ii) a forecast-model of remotely sensed environmental variables (productivity, sea surface temperature, and salinity). In general, seabird distributions were better predicted by abundance of fish than by environmental variables at the habitat scale. We obtained consistent correlations between seabird presence and the abundance of medium-sized (10–20 cm) sardines, anchovies and Mediterranean horse mackerel, providing information on their preferred prey. Additionally, oceanographic productivity variables moderately contributed to seabird distribution models, with better predictive value for the critically endangered Balearic shearwater and Northern gannet in the summer, whilst the model for Cory's shearwater's produced poorer predictions. Predator–prey combined studies may represent essential tools for an efficient ecosystem-based management of marine environments.

de la Cruz, Andrés (ORCID:0000000203632498)↗
DOE OSTI2024

The Kinematics of Proal Chewing in Rats

Chewing kinematics are well-documented in several mammal species with fused mandibular symphyses, but relatively understudied in mammals with an unfused symphysis, despite the fact that more than half of extant Mammalia have an unfused mandibular symphysis. The Wistar brown rat (Rattus norvegicus) is widely used in human health research, including studies of mastication or neurological studies where mastication is the output behavior. These animals are known to have unfused mandibular symphyses and proal jaw (rostrocaudal) motion during occlusion, but the lack of high resolution, 3-dimensional analysis of rat chewing leaves the functional significance of symphyseal mobility unknown. We used biplanar fluoroscopy and the X-ray reconstruction of moving morphology workflow to quantify chewing kinematics in 3 brown rats, quantifying overall jaw kinematics, including motions about the temporomandibular joint and unfused mandibular symphysis. During occlusion, the teeth and the mandibular condyle translate almost exclusively anteriorly (proal) during occlusion, with little motion in any other degrees of freedom. At the symphysis, we observed minimal flexion throughout the chew cycle. Overall, there are fundamental differences in jaw kinematics between rats and other mammals and therefore rats are not an appropriate proxy for ancestral mammal jaw mechanics. Additionally, differences between humans and rat chewing kinematics must be considered when using rats as a clinical model for pathological feeding research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Characterizing the effect of incrementally increasing dry bulb temperature on linear and nonlinear measures of heart rate variability in nonpregnant, mid-gestation, and late-gestation sows

Abstract Characterizing the sow physiological response to an increased heat load is essential for effective heat stress mitigation. The study objective was to characterize the effects of a 400-min heating episode on sow heart rate variability (HRV) at different reproductive stages. HRV is a commonly used noninvasive proxy measure of autonomic function. Twenty-seven sows were enrolled in the study according to their gestation stage at time of selection: 1) nonpregnant (NP; n = 7), 2) mid-gestation (MID; 57.3 ± 11.8 d gestation; n = 11), and 3) late-gestation (LATE; 98.8 ± 4.9 d gestation; n = 8). The HRV data utilized in the study were collected from each pig as the dry bulb temperature in the room increased incrementally from 19.84 ± 2.15 °C to 35.54 ± 0.43 °C (range: 17.1–37.5 °C) over a 400-min period. After data collection, one 5-min set of continuous heart rate data were identified per pig for each of nine temperature intervals (19–20.99, 21–22.99, 23–24.99, 25–26.99, 27–28.99, 29–30.99, 31–32.99, 33–34.99, and 35–36.99 °C). Mean inter-beat interval length (RR), standard deviation of r-r intervals (SDNN), root mean square of successive differences (RMSSD), high frequency spectral power (HF), sample entropy (SampEn), short-term detrended fluctuation analysis (DFAα1), and three measures (%REC, DET, LMEAN) derived from recurrence quantification analysis were calculated for each data set. All data were analyzed using the PROC GLIMMIX procedure in SAS 9.4. Overall, LATE sows exhibited lower RR than NP sows (P < 0.01). The standard deviation of r–r intervals and RMSSD differed between each group (P < 0.01), with LATE sows exhibiting the lowest SDNN and RMSSD and NP sows exhibiting the greatest SDNN and RMSSD. Late-gestation sows exhibited lower HF than both MID and NP sows (P < 0.0001), greater DFA values than NP sows (P = 0.05), and greater DET compared to MID sows (P = 0.001). Late-gestation also sows exhibited greater %REC and LMEAN compared to MID (P < 0.01) and NP sows (all P < 0.01). In conclusion, LATE sows exhibited indicators of greater autonomic stress throughout the heating period compared to MID and NP sows. However, temperature by treatment interactions were not detected as dry bulb increased. Future studies are needed to fully elucidate the effect of gestational stage and increasing dry bulb temperature on sow HRV.

Agriculture↗
DOE OSTI2024

Development of modular expression across phylogenetically distinct diazotrophs

Diazotrophic bacteria can reduce atmospheric nitrogen into ammonia enabling bioavailability of the essential element. Many diazotrophs closely associate with plant roots increasing nitrogen availability, acting as plant growth promoters. These associations have the potential to reduce the need for costly synthetic fertilizers if they could be engineered for agricultural applications. However, despite the importance of diazotrophic bacteria, genetic tools are poorly developed in a limited number of species, in turn narrowing the crops and root microbiomes that can be targeted. Here, we report optimized protocols and plasmids to manipulate phylogenetically diverse diazotrophs with the goal of enabling synthetic biology and genetic engineering. Three broad-host-range plasmids can be used across multiple diazotrophs, with the identification of one specific plasmid (containing origin of replication RK2 and a kanamycin resistance marker) showing the highest degree of compatibility across bacteria tested. We then demonstrated modular expression by testing seven promoters and eleven ribosomal binding sites using proxy fluorescent proteins. Finally, we tested four small molecule inducible systems to report expression in three diazotrophs and demonstrated genome editing in Klebsiella michiganensis M5al.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Process-based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Culex pipiens/restuans Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration, and validation is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a discrete, semi-stochastic, mechanistic process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens (Diptera, Culicidae) and Culex restuans (Diptera, Culicidae) mosquito populations. This model combines known models for development and survival into a fully connected age-structured model that can reproduce mosquito population dynamics. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like West Nile virus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Greater aperture counteracts effects of reduced stomatal density on WUE: a case study on sugarcane and meta-analysis

Stomata regulate CO 2 and water vapor exchange between leaves and the atmosphere. Stomata are a target for engineering to improve crop intrinsic water use efficiency (iWUE). One example is by expressing genes that lower stomatal density (SD) and reduce stomatal conductance (g sw ). However, the quantitative relationship between reduced SD, g sw , and the mechanisms underlying it is poorly understood. We addressed this knowledge gap using low-SD sugarcane (Saccharum spp. hybrid) as a case study alongside a meta-analysis of data from 10 species. Transgenic expression of EPIDERMAL PATTERNING FACTOR 2 from Sorghum bicolor (SbEFP2) in sugarcane reduced SD by 26-38% but did not affect gsw compared to wildtype. Further, no changes occurred in stomatal complex size or proxies for photosynthetic capacity. Measurements of gas exchange at low CO 2 concentrations that promote complete stomatal opening to normalize aperture size between genotypes were combined with modeling of maximum gsw from anatomical data. These data suggest that increased stomatal aperture is the only possible explanation for maintaining gsw when SD is reduced. Meta-analysis across C 3 dicots, C 3 monocots, and C 4 monocots revealed engineered reductions in SD are strongly correlated with lower gsw (r 2 =0.60-0.98), but this response is damped relative to the change in anatomy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Identifying Spectral Descriptors for Protonation in BaZr 0.8 Y 0.2 O 3-x with Electron Energy Loss Spectroscopy

Hydrogen economy is of paramount importance in the global transition to a sustainable, clean energy source that contributes to decarbonization efforts. In particular, the proton conducting proton ceramic fuel cells (PCFCs) play a crucial role in promoting hydrogen energy technology [1-5]. In a PCFC, the electrolyte is typically a solid oxide material that enables proton transport and can operate at temperatures lower than those of traditional oxygen ion conducting fuel cells [6]. The reduced operating temperature of PCFCs contributes to their durability, scalability, and efficiency [7,8]. BaZr 0.8 Y 0.2 O 3-x (BZY) is a promising proton conducting solid oxide electrolyte [9,10]. The emphasis on proton conductivity entails the importance of understanding proton content in the system. However, previous studies have largely relied on bulk techniques such as electrochemical impedance spectroscopy [7,11], Karl-Fischer titration [12,13], and thermogravimetric analysis [14] to obtain proton concentration. This is due to the small atomic size and light mass of hydrogen species making direct detection challenging. Bulk methods may be useful in estimating the proton content; however, it overlooks possible proton concentration gradient or segregation that may occur across or within a nanoparticle, especially when proton incorporation occurs nonuniformly through steam exposure on powder samples. In this paper, BZY is protonated at an estimated 0.15 mol of protons via steam exposure. Electron energy loss spectroscopy (EELS) with nanoscale spatial resolution is explored to identify proxy signals for proton detection using a JEOL ARM300 microscope operated at 300 kV with a Gatan GIF Continuum detector.

08 HYDROGEN↗
DOE OSTI2023

L1 0 Ordering in MnAl and FeNi Influenced by Magnetic Field and Strain

Due to various materials supply chain challenges, magnets free of constrained elements are attracting increasing interest. Magnetic materials such as rare-earth free FeNi and MnAl have been receiving considerable attention due to the high magnetocrystalline anisotropy and other associated magnetic properties derived from their unique chemically ordered tetragonal crystal structure, denoted as the L1 0 structure. However, synthesis of L1 0 FeNi has had limited success due to the extremely low atomic mobilities of Fe and Ni. In this work, isostructural MnAl was first studied as proxy to understand the L1 0 ordering process. Here, evidence of L1 0 ordering in FeNi derived from TEM studies is presented, where ordering was facilitated by the application of strain and magnetic field provided during thermal treatment of a severely plastically deformed FeNi alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Environments of dwarf galaxies with optical AGN characteristics

ABSTRACT This study aims to explore the relation between dwarf galaxies (M* ≤ 5 × 109 M⊙) with active galactic nuclei (AGNs) and their environment by comparing neighbourhood parameters of AGN and non-AGN samples. Using the NASA-Sloan Atlas, both the local environment and the immediate environment of dwarf galaxies with z ≤ 0.055 are analysed. Of the 145 155 galaxies in the catalogue, 62 258 of them are classified as dwarf galaxies, and by employing two AGN selection methods based on emission-line fluxes (BPT and WHAN), 4476 are found to have AGN characteristics in their optical spectra. Regardless of selection method, this study finds no discernible differences in environment between AGN and non-AGN host dwarf galaxies and these results indicate that environment is not an important factor in triggering AGN activity in dwarf galaxies. This is in line with existing literature on environments of regular galaxies with AGNs and suggests universality in terms of reaction to environment across the mass regime. The biases of AGN selection in low-mass galaxies, and the biases of different measures of environment are also considered. It is found that there are several mass trends in emission-line ratios and that the SDSS fibre covers galaxies non-uniformly with redshift. These biases should be accounted for in future work by possibly including other wavelength regimes or mass weighting of emission-line ratios. Lastly, a discussion of the environment estimation methods is included since they may not gauge the desired properties due to factors such as time delay or using loosely constrained proxy parameters.

Kristensen, Mikkel T.↗
DOE OSTI2020

Concentrations of dark haloes emerge from their merger histories

ABSTRACT The concentration parameter is a key characteristic of a dark matter halo that conveniently connects the halo’s present-day structure with its assembly history. Using ‘Dark Sky’, a suite of cosmological N-body simulations, we investigate how halo concentration evolves with time and emerges from the mass assembly history. We also explore the origin of the scatter in the relation between concentration and assembly history. We show that the evolution of halo concentration has two primary modes: (1) smooth increase due to pseudo-evolution; and (2) intense responses to physical merger events. Merger events induce lasting and substantial changes in halo structures, and we observe a universal response in the concentration parameter. We argue that merger events are a major contributor to the uncertainty in halo concentration at fixed halo mass and formation time. In fact, even haloes that are typically classified as having quiescent formation histories experience multiple minor mergers. These minor mergers drive small deviations from pseudo-evolution, which cause fluctuations in the concentration parameters and result in effectively irreducible scatter in the relation between concentration and assembly history. Hence, caution should be taken when using present-day halo concentration parameter as a proxy for the halo assembly history, especially if the recent merger history is unknown.

Wang, Kuan↗
DOE OSTI2020

Cosmological constraints from CODEX galaxy clusters spectroscopically confirmed by SDSS-IV/SPIDERS DR16

ABSTRACT This paper presents a cosmological analysis based on the properties of X-ray selected clusters of galaxies from the CODEX survey which have been spectroscopically followed up within the SPIDERS programme as part of the sixteenth data release (DR16) of SDSS-IV. The cosmological sub-sample contains a total of 691 clusters over an area of 5350 deg2 with newly measured optical properties provided by a reanalysis of the CODEX source catalogue using redMaPPer and the DESI Legacy Imaging Surveys (DR8). Optical richness is used as a proxy for the cluster mass, and the combination of X-ray, optical, and spectroscopic information ensures that only confirmed virialized systems are considered. Clusters are binned in observed redshift, $\tilde{z} \in \left[0.1, 0.6 \right)$ and optical richness, $\tilde{\lambda } \in \left[25, 148 \right)$ and the number of clusters in each bin is modelled as a function of cosmological and richness–mass scaling relation parameters. A high-purity sub-sample of 691 clusters is used in the analysis and best-fitting cosmological parameters are found to be $\Omega _{m_{0}}=0.34^{+0.09}_{-0.05}$ and $\sigma _8=0.73^{+0.03}_{-0.03}$. The redshift evolution of the self-calibrated richness–mass relation is poorly constrained due to the systematic uncertainties associated with the X-ray component of the selection function (which assumes a fixed X-ray luminosity–mass relation with h = 0.7 and $\Omega _{m_{0}}=0.30$). Repeating the analysis with the assumption of no redshift evolution is found to improve the consistency between both cosmological and scaling relation parameters with respect to recent galaxy cluster analyses in the literature.

59 BASIC BIOLOGICAL SCIENCES↗