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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A measurement of the distance to the Galactic centre using the kinematics of bar stars

The distance to the Galactic centre R 0 is a fundamental parameter for understanding the Milky Way, because all observations of our Galaxy are made from our heliocentric reference point. The uncertainty in R 0 limits our knowledge of many aspects of the Milky Way, including its total mass and the relative mass of its major components, and any orbital parameters of stars employed in chemo-dynamical analyses. While measurements of R 0 have been improving over a century, measurements in the past few years from a variety of methods still find a wide range of R 0 being somewhere within 8.0 to $8.5\, \mathrm{kpc}$. The most precise measurements to date have to assume that Sgr A* is at rest at the Galactic centre, which may not be the case. In this paper, we use maps of the kinematics of stars in the Galactic bar derived from APOGEE DR17 and Gaia EDR3 data augmented with spectrophotometric distances from the astroNN neural-network method. These maps clearly display the minimum in the rotational velocity v T and the quadrupolar signature in radial velocity v R expected for stars orbiting in a bar. From the minimum in v T , we measure $R_0 = 8.23\pm 0.12\, \mathrm{kpc}$. We validate our measurement using realistic N-body simulations of the Milky Way. We further measure the pattern speed of the bar to be $\Omega _\mathrm{bar} = 40.08\pm 1.78\, \mathrm{km\, s}^{-1}\,\mathrm{kpc}^{-1}$. Because the bar forms out of the disc, its centre is manifestly the barycentre of the bar+disc system and our measurement is therefore one of the most robust and accurate measurements of R 0 to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Pre-Symptomatic COVID Screening

Temperature checks for fever are extensively used for preliminary COVID screenings but are ineffective during the incubation stage of infection when a person is asymptotic. Researchers at the European Centre for Disease Prevention and Control concluded that approximately 75% of passengers infected with COVID-19 and traveling from affected Chinese cities would not be detected by early screening. Core body temperature is normally kept within a narrow range and has the smallest relative standard deviation of all vital signs. Heat in the body is prioritized around internal organs at the expense of the periphery by controlling blood flow. In fact, blood flow to the skin may vary by a factor of 100 depending on thermal conditions. This adaptation causes rapid temperature fluctuations in different skin regions from changes in cardiac output, metabolism, and likely cytokine diffusion during inflammation that would not be seen in average core body temperature. Current IR and thermal scanners used for temperature checks are not necessarily reflective of core body temperatures and require cautious interpretation as they frequently result in false positive and false negative diagnosis. Hand held thermometers measure average skin temperatures and can get readings that differ from core body temperature by as much as 7°. Rather than focusing on a core body temperature threshold assessment we believe that variability of temperature patterns using a novel wearable transdermal microneedle sensor will be more sensitive to infections in the incubation stage and propose to develop a wearable transdermal temperature sensor using established Sandia microneedle technology for pre-symptomatic COVID screening that can additionally be used to monitor disease progression at later stages.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Pre Symptomatic COVID Screening

Temperature checks for fever are extensively used for preliminary COVID screenings but are ineffective during the incubation stage of infection when a person is asymptotic. Researchers at the European Centre for Disease Prevention and Control concluded that approximately 75% of passengers infected with COVID-19 and traveling from affected Chinese cities would not be detected by early screening. Core body temperature is normally kept within a narrow range and has the smallest relative standard deviation of all vital signs. Heat in the body is prioritized around internal organs at the expense of the periphery by controlling blood flow. In fact, blood flow to the skin may vary by a factor of 100 depending on thermal conditions. This adaptation causes rapid temperature fluctuations in different skin regions from changes in cardiac output, metabolism, and likely cytokine diffusion during inflammation that would not be seen in average core body temperature. Current IR and thermal scanners used for temperature checks are not necessarily reflective of core body temperatures and require cautious interpretation as they frequently result in false positive and false negative diagnosis. Hand held thermometers measure average skin temperatures and can get readings that differ from core body temperature by as much as 7°. Rather than focusing on a core body temperature threshold assessment we believe that variability of temperature patterns using a novel wearable transdermal microneedle sensor will be more sensitive to infections in the incubation stage and propose to develop a wearable transdermal temperature sensor using established Sandia microneedle technology for pre symptomatic COVID screening that can additionally be used to monitor disease progression at later stages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

The Carina project. X. On the kinematics of old and intermediate-age stellar populations

We present new radial velocity (RV) measurements of old (horizontal branch) and intermediate-age (red clump) stellar tracers in the Carina dwarf spheroidal. They are based on more than 2200 low-resolution spectra collected with VIMOS at Very Large Telescope (VLT). The targets are faint (20 ≲ V ≲ 21.5 mag), but the accuracy at the faintest limit is ≤9 km s{sup −1}. These data were complemented with RV measurements either based on spectra collected with FORS2 and FLAMES/GIRAFFE at VLT or available in the literature. We ended up with a sample of 2748 stars and among them, 1389 are candidate Carina stars. We found that the intermediate-age stellar component shows a well-defined rotational pattern around the minor axis. The western and the eastern side of the galaxy differ by +5 and −4 km s{sup −1} when compared with the main RV peak. The old stellar component is characterized by a larger RV dispersion and does not show evidence of the RV pattern. We compared the observed RV distribution with N-body simulations for a former disky dwarf galaxy orbiting a giant Milky Way–like galaxy. We rotated the simulated galaxy by 60° with respect to the major axis, we kept the observer on the orbital plane of the dwarf and extracted a sample of stars similar to the observed one. Observed and predicted V{sub rot}/σ ratios across the central regions are in remarkable agreement. This evidence indicates that Carina was a disky dwarf galaxy that experienced several strong tidal interactions with the Milky Way. Owing to these interactions, Carina transformed from a disky to a prolate spheroid and the rotational velocity transformed into random motions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Dislocation Patterning in Deforming Crystals: Theory, Computational Predictions and Validation (Final Technical Report)

This project was awarded for an initial period of three years, followed by a no-cost extension for one year and a funded one-year renewal. During the first four years, the project focused on investigating the role of dislocation reactions and dislocation correlation in dislocation patterning in FCC metals. During the fifth year, the scope of research was expanded to investigate the effects of composition inhomogeneity on the mesoscale plastic response of Body-Centered Cubic (BCC) alloys. In addition to its impact on metal hardening during deformation, dislocation patterning provides the microstructure information required to understand phenomena like fracture and recrystallization in metals. The Continuum Dislocation Dynamics (CDD) framework was the methodology used during the first four years, followed by the use of Discrete Dislocation Dynamics (DDD) during the fifth year. CDD is a density-based formalism of dislocation dynamics in which the plastic deformation of crystals is predicted together with the mesoscale dislocation patterns by tracking the space-time evolution of dislocations as driven by the applied stress, short-range and long-range interactions of dislocations, and cross slip. CDD is a crystal mechanics approach in which the plastic constitutive part is replaced with the equations of dislocation dynamics, which is driven by the internal stress via a mobility laws, while the evolution of the density gives the eigenstrain required to update the internal stress itself. The governing equations are thus those of crystal mechanics cast as an eigenstrain problem and those of dislocation transport and reactions. Our investigations during the first four years were driven by the hypothesis that that dislocation patterning is triggered by spatiotemporal dislocation density and internal stress fluctuations, and that such fluctuations influence the collective dislocation dynamic through their effects on the short-range reaction rates and the collective dislocation mobility. This hypothesis was tested by modeling the influence of the dislocation reactions and dislocation correlations on collective dislocation dynamics. The main research components during the first four years were: 1) Reformulation of the CDD framework to integrate the dislocation correlations and dislocation reactions. 2) Simulation of the dislocation correlations and quantifying their contribution to the long-range stress of complex dislocation systems. 3) Computational implementation of the updated CDD model for FCC single crystals and development of an efficient CDD code. 4) Investigation of dislocation patterning in FCC crystals based on the updated CDD model. Some key findings from these investigations were: 1) The patterning of dislocations is initiated by cross slip and internal stress fluctuations, and the refinement of the pattern results from junction formation. 2) Patterning is more prominent under high stress. 3) The correlation stress was found to be a significant part of the mean field stress in continuum representations of dislocation dynamics. During the last year of the project, we have established a method for performing dislocation dynamics in inhomogeneous alloys and demonstrated the impact of composition inhomogeneity on the characteristics of initial yielding and dislocation character in BCC alloys. We also tested this method using an irradiated ferritic alloy in which the composition and dislocation loops effects are both present. In doing so, we have considered two aspects of the role of inhomogeneity, the creation of internal coherency stress due to the dependence of the lattice parameter on the local composition, and the dependence of the dislocation mobility on the local composition. These two aspects resulted in an unexpected behavior of the dislocation system, and, in turn, the yielding behavior of BCC alloys. Key findings include: 1) The composition inhomogeneity in BCC alloys alters the well-known role of screw dislocations by forcing a level of waviness on the average dislocation character, thus destroying the screw character dominance in the yielding observed in pure or homogeneous BCC metals. 2) In the case of irradiated alloys, while composition inhomogeneity by itself and dislocation loops by themselves result in some hardening, the superposition of the two mechanisms does not result in the sum of the two contributions via any known rule. The latter result contradicts the classical works related hardening via multiple mechanisms, which state that various hardening mechanisms can be added linearly or using some Pythagorean additive rule. We were able to rationalize this unexpected result by a closer loop at the origin of the hardening mechanisms themselves, which both involved long-range elastic interactions with dislocations. We reached the conclusion that the hardening resulting from the total stress associated with these two mechanisms (current work) differs from the sum of the effects of the individual stress fields (classical literature). We have also found a major flaw in the classical theory of spinodal hardening. The latter theory never considered the impact of composition undulation on the solute hardening. We have built a new general theory accounting for the effect of solute friction together with the composition undulations on the dislocation configuration at Critical Resolved Shear Stress (CRSS), which is yielding a new definition of the spinodal hardening and new different results. This work is the first to recognize the lack of the role of solute in spinodal hardening theory of alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Assessing variation in faecal glucocorticoid concentrations in gray whales exposed to anthropogenic stressors

Understanding how individual animals respond to stressors behaviourally and physiologically is a critical step towards quantifying long-term population consequences and informing management efforts. Glucocorticoid (GC) metabolite accumulation in various matrices provides an integrated measure of adrenal activation in baleen whales and could thus be used to investigate physiological changes following exposure to stressors. In this study, we measured GC concentrations in faecal samples of Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) collected over seven consecutive years to assess the association between GC content and metrics of exposure to sound levels and vessel traffic at different temporal scales, while controlling for contextual variables such as sex, reproductive status, age, body condition, year, time of year and location. We develop a Bayesian Generalized Additive Modelling approach that accommodates the many complexities of these data, including non-linear variation in hormone concentrations, missing covariate values, repeated samples, sampling variability and some hormone concentrations below the limit of detection. Estimated relationships showed large variability, but emerging patterns indicate a strong context-dependency of physiological variation, depending on sex, body condition and proximity to a port. Our results highlight the need to control for baseline hormone variation related to context, which otherwise can obscure the functional relationship between faecal GCs and stressor exposure. Therefore, extensive data collection to determine sources of baseline variation in well-studied populations, such as PCFG gray whales, could shed light on cetacean stress physiology and be used to extend applicability to less-well-studied taxa. GC analyses may offer greatest utility when employed as part of a suite of markers that, in aggregate, provide a multivariate measure of physiological status, better informing estimates of individuals’ health and ultimately the consequences of anthropogenic stressors on populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A Study of Physics-Informed Deep Learning for System Fluid Dynamics Closures

The sub-grid-scale (SGS) physics models, or so-called closure relations (CR), are essential in thermal-fluid modeling and simulation codes, ranging from large-eddy simulation to system-level thermo-fluid dynamic problems. While details vary, all thermo-fluid codes solve coupled mass-momentum-energy conservation partial differential equations (PDE). Traditionally, the analytical form of closure models has to be known, and then we calibrate the model using data from a set of applicable experiments. Characteristically, it takes long effort to gain insights and mechanistic understanding needed for developing closure models. Such a model is a compact form of data. The long time required for new model development limits the pace of model application while dealing with new geometries, new coolants or system conditions, particularly in newly designed systems. Alternative to mechanistic and semi-analytical models, it is possible to discover the pattern of closure relations by applying the modern machine learning methods to the body of relevant experimental data. Deep learning (DL) is a relatively new branch in the machine learning family, and a major breakthrough has been achieved since Hinton introduces a fast algorithm to efficiently train a feed-forward neural network (NN) with multilayer perceptrons. Generally, any NN with more than two layers is considered as deep learning, and it contains a large number of hyper-parameters to achieve pattern recognition or regression for complex datasets. Hornik shows that multilayer NN is compatible with universal approximation theorem. There is no constraint for a multilayer NN to capture the properties of any measurable information. This capability makes DL attractive for closure models in a system thermal-hydraulic code. As system geometry and/or operating conditions change, new physical experiments (increasingly sophisticated) are conducted to support evaluation and revision of closure models. Such a so-called data-driven modeling relaxes the structural form of system codes to directly assimilate data instead of hard-wiring the model to pre-calibrated correlations. The objective of this research is to enable cost-effective development of a DL-based closure that reflects the data. The previous work on applying machine learning techniques to fluid dynamics focused on statistical learning with basic NN from direct numerical simulations (DNS) dataset. In the present work, we show that DL-based closure models can cause the fluid calculation to diverge if multilayer NN is used. To address the issue, we investigate conditions by which the DL-based closure models work compatibly, stably, and effectively with PDE-constrained forward prediction problems. Optimally meeting the compatibility conditions constitutes a physics-informed deep learning (PIDL) strategy. We refer to this process as PDE-constrained machine learning or PDE-ML. To develop the technical basis for PDE-ML using DL-based fluid dynamics closure, numerical experiments are performed for manufactured problems of increasing complexity. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A correlation between seasonally changing photoperiod, whole body lipid, and condition factor in juvenile spring Chinook salmon (Oncorhynchus tshawytscha)

The regulation of lipid stores is a central process for the physiology and ecology of fishes. Seasonal variation in lipid stores has been directly linked to survival of fishes across periods of food deprivation. We assessed whether a seasonally changing photoperiod was correlated to seasonal changes in energetic status to help better understand these important processes. Groups of first feeding Chinook salmon fry were introduced to a seasonal photoperiod cycle, but the point of entrance into the seasonal cycle varied from near the winter solstice (December), to either side of the spring equinox (February & May). Temperature and feeding rate were similar for all treatments. Subsequently, condition factor and whole body lipid content were assessed through a seasonal progression. Throughout most of the experiment, length and weight did not differ between the different photoperiod treatments, however whole body lipid and Fulton’s condition factor did. Furthermore, changes in both whole body lipid and Fulton’s condition factor in all treatment groups followed a similar seasonal pattern that was inversely related to day length (highest K and lipid levels found during days with the least light). These results suggest that regardless of age or size, there is a correlation between seasonal changes in photoperiod and changes in body composition in juvenile Chinook salmonids.

Spangenberg, Dina K. (ORCID:000000018861395X)↗
DOE OSTI2017

Reach of the high-energy LHC for gluinos and top squarks in SUSY models with light Higgsinos

We investigate the top squark (stop) and gluino reach of the proposed 33 TeV energy upgrade of the Large Hadron Collider (LHC33) in the Minimal Supersymmetric Standard Model (MSSM) with light Higgsinos and relatively heavy electroweak gauginos. In our analysis, we assume that stops decay to Higgsinos via t ˜ 1 → t Z ˜ 1 , t ˜ 1 → t Z ˜ 2 , and t ˜ 1 → b W ˜ 1 with branching fractions in the ratio 1 : 1 : 2 (expected if the decay occurs dominantly via the superpotential Yukawa coupling), while gluinos decay via g ˜ → t t ˜ 1 or via three-body decays to third-generation quarks plus Higgsinos. These decay patterns are motivated by models of natural supersymmetry where Higgsinos are expected to be close in mass to m Z , but gluinos may be as heavy as 5–6 TeV, and stops may have masses up to ~ 3 TeV . We devise cuts to optimize the signals from stop and gluino pair production at LHC33. We find that experiments at LHC33 should be able to discover stops with > 5 σ significance if m t ˜ 1 < 2.3 (2.8) [3.2] TeV for an integrated luminosity of 0.3 (1) [ 3 ] ab - 1 . The corresponding reach for gluinos extends to 5 (5.5) [6] TeV. These findings imply that experiments at LHC33 should be able to discover at least one of the stop or gluino pair signals even with an integrated luminosity of 0.3 ab - 1 for natural supersymmetry models with no worse than 3% electroweak fine-tuning and quite likely both gluinos and stops for an integrated luminosity of 3 ab - 1 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

RNAi-Mediated Manipulation of Cuticle Coloration Genes in Lygus hesperus Knight (Hemiptera: Miridae)

Cuticle coloration in insects is a consequence of the accumulation of pigments in a species-specific pattern. Numerous genes are involved in regulating the underlying processes of melanization and sclerotization, and their manipulation can be used to create externally visible markers of successful gene editing. To clarify the roles for many of these genes and examine their suitability as phenotypic markers in Lygus hesperus Knight (western tarnished plant bug), transcriptomic data were screened for sequences exhibiting homology with the Drosophila melanogaster proteins. Complete open reading frames encoding putative homologs for six genes (aaNAT, black, ebony, pale, tan, and yellow) were identified, with two variants for black. Sequence and phylogenetic analyses supported preliminary annotations as cuticle pigmentation genes. In accord with observable difference in color patterning, expression varied for each gene by developmental stage, adult age, body part, and sex. Knockdown by injection of dsRNA for each gene produced varied effects in adults, ranging from the non-detectable (black 1, yellow), to moderate decreases (pale, tan) and increases (black 2, ebony) in darkness, to extreme melanization (aaNAT). Based solely on its expression profile and highly visible phenotype, aaNAT appears to be the best marker for tracking transgenic L. hesperus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Hydrodynamic Simulations of Moonlet-induced Propellers in Saturn’s Rings: Application to Blériot

One of the biggest successes of the Cassini mission is the detection of small moons (moonlets) embedded in Saturns rings that cause S-shaped density structures in their close vicinity, called propellers. Here, we present isothermal hydrodynamic simulations of moonlet-induced propellers in Saturn’s A ring that denote a further development of the original model. We find excellent agreement between these new hydrodynamic and corresponding N-body simulations. Furthermore, the hydrodynamic simulations confirm the predicted scaling laws and the analytical solution for the density in the propeller gaps. Finally, this mean field approach allows us to simulate the pattern of the giant propeller Blériot, which is too large to be modeled by direct N-body simulations. Our results are compared to two stellar occultation observations by the Cassini Ultraviolet Imaging Spectrometer (UVIS), which intersect the propeller Blériot. Best fits to the UVIS optical depth profiles are achieved for a Hill radius of 590 m, which implies a moonlet diameter of about 860 m. Furthermore, the model favors a kinematic shear viscosity of the surrounding ring material of ν {sub 0} = 340 cm{sup 2} s{sup −1}, a dispersion velocity in the range of 0.3 cm s{sup −1} < c {sub 0} < 1.5 cm s{sup −1}, and a fairly high bulk viscosity 7 < ξ {sub 0}/ν {sub 0} < 17. These large transport values might be overestimated by our isothermal ring model and should be reviewed by an extended model including thermal fluctuations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Host phylogeny matters: Examining sources of variation in infection risk by blood parasites across a tropical montane bird community in India

Abstract Background Identifying patterns and drivers of infection risk among host communities is crucial to elucidate disease dynamics and predict infectious disease risk in wildlife populations. Blood parasites of the genera Plasmodium and Haemoproteus are a diverse group of vector-borne protozoan parasites that affect bird populations globally. Despite their widespread distribution and exceptional diversity, factors underlying haemosporidian infection risk in wild bird communities remain poorly understood. While some studies have examined variation in avian haemosporidian risk, researchers have primarily focused on host ecological traits without considering host phylogenetic relationships. In this study, we employ a phylogenetically informed approach to examine the association between host ecological traits and haemosporidian infection risk in endemic bird communities in the Western Ghats Sky Islands. Methods We used parasite sequence data based on partial mitochondrial cytochrome b gene, that was amplified from genomic DNA extracted from 1177 birds (28 species) across the Western Ghats to assess infection of birds with haemosporidian parasites. We employed a Bayesian phylogenetic mixed effect modelling approach to test whether haemosporidian infection risk was affected by seven species-specific and four individual-level ecological predictors. We also examined the effect of host phylogenetic relationships on the observed patterns of variation in haemosporidian infection risk by estimating phylogenetic signal. Results Our study shows that host ecological traits and host phylogeny differentially influence infection risk by Plasmodium (generalist parasite) and Haemoproteus (specialist parasite). For Plasmodium , we found that sociality, sexual dimorphism and foraging strata were important ecological predictors. For Haemoproteus , patterns of infection risk among host species were associated with sociality, species elevation and individual body condition. Interestingly, variance in infection risk explained by host phylogeny was higher for Haemoproteus parasites compared to Plasmodium . Conclusions Our study highlights that while host ecological traits promoting parasite exposure and host susceptibility are important determinants of infection risk, host phylogeny also contributes substantially to predicting patterns of haemosporidian infection risk in multi-host communities. Importantly, infection risk is driven by joint contributions of host ecology and host phylogeny and studying these effects together could increase our ability to better understand the drivers of infection risk and predict future disease threats. Graphical abstract

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Metagenomic analysis with strain-level resolution reveals fine-scale variation in the human pregnancy microbiome

Recent studies suggest that the microbiome has an impact on gestational health and outcome. However, characterization of the pregnancy-associated microbiome has largely relied on 16S rRNA gene amplicon-based surveys. Here, we describe an assembly-driven, metagenomics-based, longitudinal study of the vaginal, gut, and oral microbiomes in 292 samples from 10 subjects sampled every three weeks throughout pregnancy. Nonhuman sequences in the amount of 1.53 Gb were assembled into scaffolds, and functional genes were predicted for gene- and pathway-based analyses. Vaginal assemblies were binned into 97 draft quality genomes. Redundancy analysis (RDA) of microbial community composition at all three body sites revealed gestational age to be a significant source of variation in patterns of gene abundance. In addition, health complications were associated with variation in community functional gene composition in the mouth and gut. The diversity of Lactobacillus iners-dominated communities in the vagina, unlike most other vaginal community types, significantly increased with gestational age. The genomes of co-occurring Gardnerella vaginalis strains with predicted distinct functions were recovered in samples from two subjects. In seven subjects, gut samples contained strains of the same Lactobacillus species that dominated the vaginal community of that same subject and not other Lactobacillus species; however, these within-host strains were divergent. CRISPR spacer analysis suggested shared phage and plasmid populations across body sites and individuals. This work underscores the dynamic behavior of the microbiome during pregnancy and suggests the potential importance of understanding the sources of this behavior for fetal development and gestational outcome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Photolithography system including selective light array

A system, device, and method for imparting or transferring a geometric pattern on the surface of a substrate. The device comprises, a housing forming at least a partially enclosed space, a light source body comprising an array of light emitters, a base disposed below the light source body and configured for supporting the substrate having a photoresist layer thereon, and a controller for activating a predetermined number of individual light emitters corresponding to the predetermined geometric pattern. Each individual light emitter within the array of light emitters is selectively activatable to emit a light. The array of light emitters comprises a plurality of light-emitting diodes, a plurality of quantum dots, or both.

Young, Barbara Diane↗
DOE OSTI2017

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Magic-angle semimetals

Abstract Breakthroughs in two-dimensional van der Waals heterostructures have revealed that twisting creates a moiré pattern that quenches the kinetic energy of electrons, allowing for exotic many-body states. We show that cold atomic, trapped ion, and metamaterial systems can emulate the effects of a twist in many models from one to three dimensions. Further, we demonstrate at larger angles (and argue at smaller angles) that by considering incommensurate effects, the magic-angle effect becomes a single-particle quantum phase transition (including in a model for twisted bilayer graphene in the chiral limit). We call these models “magic-angle semimetals”. Each contains nodes in the band structure and an incommensurate modulation. At magic-angle criticality, we report a nonanalytic density of states, flat bands, multifractal wave functions that Anderson delocalize in momentum space, and an essentially divergent effective interaction scale. As a particular example, we discuss how to observe this effect in an ultracold Fermi gas.

Materials Science↗
DOE OSTI2017

Sapling growth rates reveal conspecific negative density dependence in a temperate forest

Local tree species diversity is maintained in part by conspecific negative density dependence (CNDD). This pervasive mechanism occurs in a variety of forms and ecosystems, but research to date has been heavily skewed toward tree seedling survival in tropical forests. To evaluate CNDD more broadly, we investigated how sapling growth rates were affected by conspecific adult neighbors in a fully mapped 25.6 ha temperate deciduous forest. We examined growth rates as a function of the local adult tree neighborhood (via spatial autoregressive modeling) and compared the spatial positioning of faster-growing and slower-growing saplings with respect to adult conspecific and heterospecific trees (via bivariate point pattern analysis). In addition, to determine whether CNDD-driven variation in growth rates leaves a corresponding spatial signal, we extended our point pattern analysis to a static, growth-independent comparison of saplings and the next larger size class. We found that negative conspecific effects on sapling growth were most prevalent. Five of the nine species that were sufficiently abundant for analysis exhibited CNDD, while only one species showed evidence of a positive conspecific effect, and one or two species, depending on the analysis, displayed heterospecific effects. There was general agreement between the autoregressive models and the point pattern analyses based on sapling growth rates, but point pattern analyses based on single-point-in-time size classes yielded results that differed markedly from the other two approaches. Our work adds to the growing body of evidence that CNDD is an important force in temperate forests, and demonstrates that this process extends to sapling growth rates. Further, our findings indicate that point pattern analyses based solely on size classes may fail to detect the process of interest (e.g., neighborhood-driven variation in growth rates), in part due to the confounding of tree size and age.

54 ENVIRONMENTAL SCIENCES↗